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{
"abstract": " This paper analyzes the market impacts of expanding California's centralized\nelectricity market across the western United States and provides the first\nstatistical assessment of this issue. Using market data from 2015-2018, I\nestimate the short-term effects of increasing regional electricity trade\nbetween California and neighboring states on prices, emissions, and generation.\nConsistent with economic theory, I find negative price impacts from regional\ntrade, with each 1 gigawatt-hour (GWh) increase in California electricity\nimports associated with an average 0.15 dollar decrease in CAISO price. The\nprice effect yields significant consumer savings well in excess of\nimplementation costs required to set up a regional market. I find a short-term\ndecrease in California carbon dioxide emissions associated with trading that is\npartially offset by increased emissions in neighboring regions. Specifically,\neach 1 GWh increase in regional trade is associated with a net 70-ton average\ndecrease in CO2 emissions across the western U.S. A small amount of increased\nSO2 and NOx emissions are also observed in neighboring states associated with\nincreased exports to California. This implies a small portion (less than 10\npercent) of electricity exports to California are supplied by coal generation.\nThis study identifies substantial short-term monetary benefits from market\nregionalization for California consumers. It also shows that California's cap\nand trade program is relatively effective in limiting the carbon content of\nimported electricity, even absent a regional cap on CO2. The conclusions\nsuggest efforts to reduce trade barriers should move forward in parallel with\nstrong greenhouse gas policies that cap emissions levels across the market\nregion.\n",
"title": "Integrating electricity markets: Impacts of increasing trade on prices and emissions in the western United States"
}
| null | null |
[
"Quantitative Finance"
] | null | true | null |
13201
| null |
Validated
| null | null |
null |
{
"abstract": " Peer code review and continuous integration often interleave with each other\nin the modern software quality management. Although several studies investigate\nhow non-technical factors (e.g., reviewer workload), developer participation\nand even patch size affect the code review process, the impact of continuous\nintegration on code reviews is not yet properly understood. In this paper, we\nreport an exploratory study using 578K automated build entries where we\ninvestigate the impact of automated builds on the code reviews. Our\ninvestigation suggests that successfully passed builds are more likely to\nencourage new code review participation in a pull request. Frequently built\nprojects are found to be maintaining a steady level of reviewing activities\nover the years, which was quite missing from the rarely built projects.\nExperiments with 26,516 automated build entries reported that our proposed\nmodel can identify 64% of the builds that triggered new code reviews later.\n",
"title": "Impact of Continuous Integration on Code Reviews"
}
| null | null |
[
"Computer Science"
] | null | true | null |
13202
| null |
Validated
| null | null |
null |
{
"abstract": " The tree inclusion problem is, given two node-labeled trees $P$ and $T$ (the\n\"pattern tree\" and the \"text tree\"), to locate every minimal subtree in $T$ (if\nany) that can be obtained by applying a sequence of node insertion operations\nto $P$. The ordered tree inclusion problem is known to be solvable in\npolynomial time while the unordered tree inclusion problem is NP-hard. The\ncurrently fastest algorithm for the latter is from 1995 and runs in\n$O(poly(m,n) \\cdot 2^{2d}) = O^{\\ast}(4^{d})$ time, where $m$ and $n$ are the\nsizes of the pattern and text trees, respectively, and $d$ is the degree of the\npattern tree. Here, we develop a new algorithm that improves the exponent $2d$\nto $d$ by considering a particular type of ancestor-descendant relationships\nand applying dynamic programming, thus reducing the time complexity to\n$O^{\\ast}(2^{d})$. We then study restricted variants of the unordered tree\ninclusion problem where the number of occurrences of different node labels\nand/or the input trees' heights are bounded and show that although the problem\nremains NP-hard in many such cases, if the leaves of $P$ are distinctly labeled\nand each label occurs at most $c$ times in $T$ then it can be solved in\npolynomial time for $c = 2$ and in $O^{\\ast}(1.8^d)$ time for $c = 3$.\n",
"title": "New Algorithms for Unordered Tree Inclusion"
}
| null | null | null | null | true | null |
13203
| null |
Default
| null | null |
null |
{
"abstract": " As a firm varies the price of a product, consumers exhibit reference effects,\nmaking purchase decisions based not only on the prevailing price but also the\nproduct's price history. We consider the problem of learning such behavioral\npatterns as a monopolist releases, markets, and prices products. This context\ncalls for pricing decisions that intelligently trade off between maximizing\nrevenue generated by a current product and probing to gain information for\nfuture benefit. Due to dependence on price history, realized demand can reflect\ndelayed consequences of earlier pricing decisions. As such, inference entails\nattribution of outcomes to prior decisions and effective exploration requires\nplanning price sequences that yield informative future outcomes. Despite the\nconsiderable complexity of this problem, we offer a tractable systematic\napproach. In particular, we frame the problem as one of reinforcement learning\nand leverage Thompson sampling. We also establish a regret bound that provides\ngraceful guarantees on how performance improves as data is gathered and how\nthis depends on the complexity of the demand model. We illustrate merits of the\napproach through simulations.\n",
"title": "Learning to Price with Reference Effects"
}
| null | null | null | null | true | null |
13204
| null |
Default
| null | null |
null |
{
"abstract": " Inverse Reinforcement Learning (IRL) is the task of learning a single reward\nfunction given a Markov Decision Process (MDP) without defining the reward\nfunction, and a set of demonstrations generated by humans/experts. However, in\npractice, it may be unreasonable to assume that human behaviors can be\nexplained by one reward function since they may be inherently inconsistent.\nAlso, demonstrations may be collected from various users and aggregated to\ninfer and predict user's behaviors. In this paper, we introduce the\nNon-parametric Behavior Clustering IRL algorithm to simultaneously cluster\ndemonstrations and learn multiple reward functions from demonstrations that may\nbe generated from more than one behaviors. Our method is iterative: It\nalternates between clustering demonstrations into different behavior clusters\nand inverse learning the reward functions until convergence. It is built upon\nthe Expectation-Maximization formulation and non-parametric clustering in the\nIRL setting. Further, to improve the computation efficiency, we remove the need\nof completely solving multiple IRL problems for multiple clusters during the\niteration steps and introduce a resampling technique to avoid generating too\nmany unlikely clusters. We demonstrate the convergence and efficiency of the\nproposed method through learning multiple driver behaviors from demonstrations\ngenerated from a grid-world environment and continuous trajectories collected\nfrom autonomous robot cars using the Gazebo robot simulator.\n",
"title": "Inverse Reinforce Learning with Nonparametric Behavior Clustering"
}
| null | null | null | null | true | null |
13205
| null |
Default
| null | null |
null |
{
"abstract": " A proper ideal $I$ in a commutative ring with unity is called a\n$z^\\circ$-ideal if for each $a$ in $I$, the intersection of all minimal prime\nideals in $R$ which contain $a$ is contained in $I$. For any totally ordered\nfield $F$ and a completely $F$-regular topological space $X$, let $C(X,F)$ be\nthe ring of all $F$-valued continuous functions on $X$ and $B(X,F)$ the\naggregate of all those functions which are bounded over $X$. An explicit\nformula for all the $z^\\circ$-ideals in $A(X,F)$ in terms of ideals of closed\nsets in $X$ is given. It turns out that an intermediate ring $A(X,F)\\neq\nC(X,F)$ is never regular in the sense of Von-Neumann. This property further\ncharacterizes $C(X,F)$ amongst the intermediate rings within the class of\n$P_F$-spaces $X$. It is also realized that $X$ is an almost $P_F$-space if and\nonly if each maximal ideal in $C(X,F)$ is $z^\\circ$-ideal. Incidentally this\nproperty also characterizes $C(X,F)$ amongst the intermediate rings within the\nfamily of almost $P_F$-spaces.\n",
"title": "$z^\\circ$-ideals in intermediate rings of ordered field valued continuous functions"
}
| null | null |
[
"Mathematics"
] | null | true | null |
13206
| null |
Validated
| null | null |
null |
{
"abstract": " Many real-world time-series analysis problems are characterised by scarce\ndata. Solutions typically rely on hand-crafted features extracted from the time\nor frequency domain allied with classification or regression engines which\ncondition on this (often low-dimensional) feature vector. The huge advances\nenjoyed by many application domains in recent years have been fuelled by the\nuse of deep learning architectures trained on large data sets. This paper\npresents an application of deep learning for acoustic event detection in a\nchallenging, data-scarce, real-world problem. Our candidate challenge is to\naccurately detect the presence of a mosquito from its acoustic signature. We\ndevelop convolutional neural networks (CNNs) operating on wavelet\ntransformations of audio recordings. Furthermore, we interrogate the network's\npredictive power by visualising statistics of network-excitatory samples. These\nvisualisations offer a deep insight into the relative informativeness of\ncomponents in the detection problem. We include comparisons with conventional\nclassifiers, conditioned on both hand-tuned and generic features, to stress the\nstrength of automatic deep feature learning. Detection is achieved with\nperformance metrics significantly surpassing those of existing algorithmic\nmethods, as well as marginally exceeding those attained by individual human\nexperts.\n",
"title": "Mosquito Detection with Neural Networks: The Buzz of Deep Learning"
}
| null | null |
[
"Computer Science",
"Statistics"
] | null | true | null |
13207
| null |
Validated
| null | null |
null |
{
"abstract": " The two major approaches to studying macroevolution in deep time are the\nfossil record and reconstructed relationships among extant taxa from molecular\ndata. Results based on one approach sometimes conflict with those based on the\nother, with inconsistencies often attributed to inherent flaws of one (or the\nother) data source. What is unquestionable is that both the molecular and\nfossil records are limited reflections of the same evolutionary history, and\nany contradiction between them represents a failure of our existing models to\nexplain the patterns we observe. Fortunately, the different limitations of each\nrecord provide an opportunity to test or calibrate the other, and new\nmethodological developments leverage both records simultaneously. However, we\nmust reckon with the distinct relationships between sampling and time in the\nfossil record and molecular phylogenies. These differences impact our\nrecognition of baselines, and the analytical incorporation of age estimate\nuncertainty. These differences in perspective also influence how different\npractitioners view the past and evolutionary time itself, bearing important\nimplications for the generality of methodological advancements, and differences\nin the philosophical approach to macroevolutionary theory across fields.\n",
"title": "The inseparability of sampling and time and its influence on attempts to unify the molecular and fossil records"
}
| null | null | null | null | true | null |
13208
| null |
Default
| null | null |
null |
{
"abstract": " This is the second paper of a series aimed to study the stellar kinematics\nand population properties of bulges in highly-inclined barred galaxies. In this\nwork, we carry out a detailed analysis of the stellar age, metallicity and\n[Mg/Fe] of 28 highly-inclined ($i > 65^{o}$) disc galaxies, from S0 to S(B)c,\nobserved with the SAURON integral-field spectrograph. The sample is divided\ninto two clean samples of barred and unbarred galaxies, on the basis of the\ncorrelation between the stellar velocity and h$_3$ profiles, as well as the\nlevel of cylindrical rotation within the bulge region. We find that while the\nmean stellar age, metallicity and [Mg/Fe] in the bulges of barred and unbarred\ngalaxies are not statistically distinct, the [Mg/Fe] gradients along the minor\naxis (away from the disc) of barred galaxies are significantly different than\nthose without bars. For barred galaxies, stars that are vertically further away\nfrom the midplane are in general more [Mg/Fe]--enhanced and thus the vertical\ngradients in [Mg/Fe] for barred galaxies are mostly positive, while for\nunbarred bulges the [Mg/Fe] profiles are typically negative or flat. This\nresult, together with the old populations observed in the barred sample,\nindicates that bars are long-lasting structures, and therefore are not easily\ndestroyed. The marked [Mg/Fe] differences with the bulges of unbarred galaxies\nindicate that different formation/evolution scenarios are required to explain\ntheir build-up, and emphasizes the role of bars in redistributing stellar\nmaterial in the bulge dominated regions.\n",
"title": "The imprints of bars on the vertical stellar population gradients of galactic bulges"
}
| null | null | null | null | true | null |
13209
| null |
Default
| null | null |
null |
{
"abstract": " We introduce a new finite element (FE) discretization framework applicable\nfor covariant split equations. The introduction of additional differential\nforms (DF) that form pairs with the original ones permits the splitting of the\nequations into topological momentum and continuity equations and\nmetric-dependent closure equations that apply the Hodge-star operator. Our\ndiscretization framework conserves this geometrical structure and provides for\nall DFs proper FE spaces such that the differential operators hold in strong\nform. We introduce lowest possible order discretizations of the split 1D wave\nequations, in which the discrete momentum and continuity equations follow by\ntrivial projections onto piecewise constant FE spaces, omitting partial\nintegrations. Approximating the Hodge-star by nontrivial Galerkin projections\n(GP), the two discrete metric equations follow by projections onto either the\npiecewise constant (GP0) or piecewise linear (GP1) space.\nOur framework gives us three schemes with significantly different behavior.\nThe split scheme using twice GP1 is unstable and shares the dispersion relation\nwith the P1-P1 FE scheme that approximates both variables by piecewise linear\nspaces (P1). The split schemes that apply a mixture of GP1 and GP0 share the\ndispersion relation with the stable P1-P0 FE scheme that applies piecewise\nlinear and piecewise constant (P0) spaces. However, the split schemes exhibit\nsecond order convergence for both quantities of interest. For the split scheme\napplying twice GP0, we are not aware of a corresponding standard formulation to\ncompare with. Though it does not provide a satisfactory approximation of the\ndispersion relation as short waves are propagated much too fast, the discovery\nof the new scheme illustrates the potential of our discretization framework as\na toolbox to study and find FE schemes by new combinations of FE spaces.\n",
"title": "A structure-preserving split finite element discretization of the split 1D wave equations"
}
| null | null | null | null | true | null |
13210
| null |
Default
| null | null |
null |
{
"abstract": " Quench dynamics is an active area of study encompassing condensed matter\nphysics and quantum information, with applications to cold-atomic gases and\npump-probe spectroscopy of materials. Recent theoretical progress in studying\nquantum quenches is reviewed. Quenches in interacting one dimensional systems\nas well as systems in higher spatial dimensions are covered. The appearance of\nnon-trivial steady states following a quench in exactly solvable models is\ndiscussed, and the stability of these states to perturbations is described.\nProper conserving approximations needed to capture the onset of thermalization\nat long times are outlined. The appearance of universal scaling for quenches\nnear critical points, and the role of the renormalization group in capturing\nthe transient regime, are reviewed. Finally the effect of quenches near\ncritical points on the dynamics of entanglement entropy and entanglement\nstatistics is discussed. The extraction of critical exponents from the\nentanglement statistics is outlined.\n",
"title": "Quantum quench dynamics"
}
| null | null | null | null | true | null |
13211
| null |
Default
| null | null |
null |
{
"abstract": " Fermilab is committed to upgrade its accelerator complex to support HEP\nexperiments at the intensity frontier. The ongoing Proton Improvement Plan\n(PIP) enables us to reach 700 kW beam power on the NuMI neutrino targets. By\nthe end of the next decade, the current 400 MeV normal conducting LINAC will be\nreplaced by an 800 MeV superconducting LINAC (PIP-II) with an increased beam\npower >50% of the PIP design goal. Both in PIP and PIP-II era, the existing\nBooster is going to play a very significant role, at least for next two\ndecades. In the meanwhile, we have recently developed an innovative beam\ninjection and bunching scheme for the Booster called \"early injection scheme\"\nthat continues to use the existing 400 MeV LINAC and implemented into\noperation. This scheme has the potential to increase the Booster beam intensity\nby >40% from the PIP design goal. Some benefits from the scheme have already\nbeen seen. In this paper, I will describe the basic principle of the scheme,\nresults from recent beam experiments, our experience with the new scheme in\noperation, current status, issues and future plans. This scheme fits well with\nthe current and future intensity upgrade programs at Fermilab.\n",
"title": "R&D On Beam Injection and Bunching Schemes In The Fermilab Booster"
}
| null | null | null | null | true | null |
13212
| null |
Default
| null | null |
null |
{
"abstract": " Deep generative models have shown promising results in generating realistic\nimages, but it is still non-trivial to generate images with complicated\nstructures. The main reason is that most of the current generative models fail\nto explore the structures in the images including spatial layout and semantic\nrelations between objects. To address this issue, we propose a novel deep\nstructured generative model which boosts generative adversarial networks (GANs)\nwith the aid of structure information. In particular, the layout or structure\nof the scene is encoded by a stochastic and-or graph (sAOG), in which the\nterminal nodes represent single objects and edges represent relations between\nobjects. With the sAOG appropriately harnessed, our model can successfully\ncapture the intrinsic structure in the scenes and generate images of\ncomplicated scenes accordingly. Furthermore, a detection network is introduced\nto infer scene structures from a image. Experimental results demonstrate the\neffectiveness of our proposed method on both modeling the intrinsic structures,\nand generating realistic images.\n",
"title": "Deep Structured Generative Models"
}
| null | null | null | null | true | null |
13213
| null |
Default
| null | null |
null |
{
"abstract": " We apply machine learning techniques in an attempt to predict and classify\nstellar properties from noisy and sparse time series data. We preprocessed over\n94 GB of Kepler light curves from MAST to classify according to ten distinct\nphysical properties using both representation learning and feature engineering\napproaches. Studies using machine learning in the field have been primarily\ndone on simulated data, making our study one of the first to use real light\ncurve data for machine learning approaches. We tuned our data using previous\nwork with simulated data as a template and achieved mixed results between the\ntwo approaches. Representation learning using a Long Short-Term Memory (LSTM)\nRecurrent Neural Network (RNN) produced no successful predictions, but our work\nwith feature engineering was successful for both classification and regression.\nIn particular, we were able to achieve values for stellar density, stellar\nradius, and effective temperature with low error (~ 2 - 4%) and good accuracy\n(~ 75%) for classifying the number of transits for a given star. The results\nshow promise for improvement for both approaches upon using larger datasets\nwith a larger minority class. This work has the potential to provide a\nfoundation for future tools and techniques to aid in the analysis of\nastrophysical data.\n",
"title": "Machine Learning Techniques for Stellar Light Curve Classification"
}
| null | null | null | null | true | null |
13214
| null |
Default
| null | null |
null |
{
"abstract": " We report frequency measurement of the clock transition in an 115In+ ion\nsympathetically-cooled with Ca+ ions in a linear rf trap. The Ca+ ions are used\nas a probe of the external electromagnetic field and as the coolant for\npreparing the cold In+. The frequency is determined to be 1 267 402 452 901\n049.9 (6.9) Hz by averaging 36 measurements using an optical frequency comb\nreferenced to the frequency standards located in the same site.\n",
"title": "Frequency measurement of the clock transition of an indium ion sympathetically-cooled in a linear trap"
}
| null | null | null | null | true | null |
13215
| null |
Default
| null | null |
null |
{
"abstract": " Identifying the different varieties of the same language is more challenging\nthan unrelated languages identification. In this paper, we propose an approach\nto discriminate language varieties or dialects of Mandarin Chinese for the\nMainland China, Hong Kong, Taiwan, Macao, Malaysia and Singapore, a.k.a., the\nGreater China Region (GCR). When applied to the dialects identification of the\nGCR, we find that the commonly used character-level or word-level uni-gram\nfeature is not very efficient since there exist several specific problems such\nas the ambiguity and context-dependent characteristic of words in the dialects\nof the GCR. To overcome these challenges, we use not only the general features\nlike character-level n-gram, but also many new word-level features, including\nPMI-based and word alignment-based features. A series of evaluation results on\nboth the news and open-domain dataset from Wikipedia show the effectiveness of\nthe proposed approach.\n",
"title": "Sentence-level dialects identification in the greater China region"
}
| null | null | null | null | true | null |
13216
| null |
Default
| null | null |
null |
{
"abstract": " Whether neural networks can learn abstract reasoning or whether they merely\nrely on superficial statistics is a topic of recent debate. Here, we propose a\ndataset and challenge designed to probe abstract reasoning, inspired by a\nwell-known human IQ test. To succeed at this challenge, models must cope with\nvarious generalisation `regimes' in which the training and test data differ in\nclearly-defined ways. We show that popular models such as ResNets perform\npoorly, even when the training and test sets differ only minimally, and we\npresent a novel architecture, with a structure designed to encourage reasoning,\nthat does significantly better. When we vary the way in which the test\nquestions and training data differ, we find that our model is notably\nproficient at certain forms of generalisation, but notably weak at others. We\nfurther show that the model's ability to generalise improves markedly if it is\ntrained to predict symbolic explanations for its answers. Altogether, we\nintroduce and explore ways to both measure and induce stronger abstract\nreasoning in neural networks. Our freely-available dataset should motivate\nfurther progress in this direction.\n",
"title": "Measuring abstract reasoning in neural networks"
}
| null | null | null | null | true | null |
13217
| null |
Default
| null | null |
null |
{
"abstract": " This paper was published in the special issue of the Journal of Inequalities\nand Special Functions dedicated to Professor Ivan Dimovski's contributions to\ndifferent fields of mathematics: transmutation theory, special functions,\nintegral transforms, function theory etc.\nIn this paper we study fractional powers of the Bessel differential operator.\nThe fractional powers are defined explicitly in the integral form without use\nof integral transforms in its definitions. Some general properties of the\nfractional powers of the Bessel differential operator are proved and some are\nlisted. Among them are different variations of definitions, relations with the\nMellin and Hankel transforms, group property, generalized Taylor formula with\nBessel operators, evaluation of resolvent integral operator in terms of the\nWright or generalized Mittag--Leffler functions. At the end, some topics are\nindicated for further study and possible generalizations. Also the aim of the\npaper is to attract attention and give references to not widely known results\non fractional powers of the Bessel differential operator.\n",
"title": "On fractional powers of Bessel operators"
}
| null | null |
[
"Mathematics"
] | null | true | null |
13218
| null |
Validated
| null | null |
null |
{
"abstract": " The XO project aims at detecting transiting exoplanets around bright stars\nfrom the ground using small telescopes. The original configuration of XO\n(McCullough et al. 2005) has been changed and extended as described here. The\ninstrumental setup consists of three identical units located at different\nsites, each composed of two lenses equipped with CCD cameras mounted on the\nsame mount. We observed two strips of the sky covering an area of 520 deg$^2$\nfor twice nine months. We build lightcurves for ~20,000 stars up to magnitude\nR~12.5 using a custom-made photometric data reduction pipeline. The photometric\nprecision is around 1-2% for most stars, and the large quantity of data allows\nus to reach a millimagnitude precision when folding the lightcurves on\ntimescales that are relevant to exoplanetary transits. We search for periodic\nsignals and identify several hundreds of variable stars and a few tens of\ntransiting planet candidates. Follow-up observations are underway to confirm or\nreject these candidates. We found two close-in gas giant planets so far, in\nline with the expected yield.\n",
"title": "Small Telescope Exoplanet Transit Surveys: XO"
}
| null | null |
[
"Physics"
] | null | true | null |
13219
| null |
Validated
| null | null |
null |
{
"abstract": " Standard model-free deep reinforcement learning (RL) algorithms sample a new\ninitial state for each trial, allowing them to optimize policies that can\nperform well even in highly stochastic environments. However, problems that\nexhibit considerable initial state variation typically produce high-variance\ngradient estimates for model-free RL, making direct policy or value function\noptimization challenging. In this paper, we develop a novel algorithm that\ninstead partitions the initial state space into \"slices\", and optimizes an\nensemble of policies, each on a different slice. The ensemble is gradually\nunified into a single policy that can succeed on the whole state space. This\napproach, which we term divide-and-conquer RL, is able to solve complex tasks\nwhere conventional deep RL methods are ineffective. Our results show that\ndivide-and-conquer RL greatly outperforms conventional policy gradient methods\non challenging grasping, manipulation, and locomotion tasks, and exceeds the\nperformance of a variety of prior methods. Videos of policies learned by our\nalgorithm can be viewed at this http URL\n",
"title": "Divide-and-Conquer Reinforcement Learning"
}
| null | null |
[
"Computer Science"
] | null | true | null |
13220
| null |
Validated
| null | null |
null |
{
"abstract": " An electrified visco-capillary jet shows different dynamic behavior, such as\ncone forming, breakage into droplets, whipping and coiling, depending on the\nconsidered parameter regime. The whipping instability that is of fundamental\nimportance for electrospinning has been approached by means of stability\nanalysis in previous papers. In this work we alternatively propose a model\nframework in which the instability can be computed straightforwardly as the\nstable stationary solution of an asymptotic Cosserat rod description. For this\npurpose, we adopt a procedure by Ribe (Proc. Roy. Soc. Lond. A, 2004)\ndescribing the jet dynamics with respect to a frame rotating with the a priori\nunknown whipping frequency that itself becomes part of the solution. The rod\nmodel allows for stretching, bending and torsion, taking into account inertia,\nviscosity, surface tension, electric field and air drag. For the resulting\nparametric boundary value problem of ordinary differential equations we present\na continuation-collocation method. On top of an implicit Runge-Kutta scheme of\nfifth order, our developed continuation procedure makes the efficient and\nrobust simulation and navigation through a high-dimensional parameter space\npossible. Despite the simplicity of the employed electric force model the\nnumerical results are convincing, the whipping effect is qualitatively well\ncharacterized.\n",
"title": "Whipping of electrified visco-capillary jets in airflows"
}
| null | null | null | null | true | null |
13221
| null |
Default
| null | null |
null |
{
"abstract": " A receiver with perfect channel state information (CSI) in a point-to-point\nmultiple-input multiple-output (MIMO) channel can compute the transmit\nbeamforming vector that maximizes the transmission rate. For frequency-division\nduplex, a transmitter is not able to estimate CSI directly and has to obtain a\nquantized transmit beamforming vector from the receiver via a rate-limited\nfeedback channel. We assume that time evolution of MIMO channels is modeled as\na Gauss-Markov process parameterized by a temporal-correlation coefficient.\nSince feedback rate is usually low, we assume rank-one transmit beamforming or\ntransmission with single data stream. For given feedback rate, we analyze the\noptimal feedback interval that maximizes the average received power of the\nsystems with two transmit or two receive antennas. For other system sizes, the\noptimal feedback interval is approximated by maximizing the rate difference in\na large system limit. Numerical results show that the large system\napproximation can predict the optimal interval for finite-size system quite\naccurately. Numerical results also show that quantizing transmit beamforming\nwith the optimal feedback interval gives larger rate than the existing\nKalman-filter scheme does by as much as 10% and than feeding back for every\nblock does by 44% when the number of feedback bits is small.\n",
"title": "On Optimizing Feedback Interval for Temporally Correlated MIMO Channels With Transmit Beamforming And Finite-Rate Feedback"
}
| null | null |
[
"Computer Science"
] | null | true | null |
13222
| null |
Validated
| null | null |
null |
{
"abstract": " We describe a deep learning approach for automated brain hemorrhage detection\nfrom computed tomography (CT) scans. Our model emulates the procedure followed\nby radiologists to analyse a 3D CT scan in real-world. Similar to radiologists,\nthe model sifts through 2D cross-sectional slices while paying close attention\nto potential hemorrhagic regions. Further, the model utilizes 3D context from\nneighboring slices to improve predictions at each slice and subsequently,\naggregates the slice-level predictions to provide diagnosis at CT level. We\nrefer to our proposed approach as Recurrent Attention DenseNet (RADnet) as it\nemploys original DenseNet architecture along with adding the components of\nattention for slice level predictions and recurrent neural network layer for\nincorporating 3D context. The real-world performance of RADnet has been\nbenchmarked against independent analysis performed by three senior radiologists\nfor 77 brain CTs. RADnet demonstrates 81.82% hemorrhage prediction accuracy at\nCT level that is comparable to radiologists. Further, RADnet achieves higher\nrecall than two of the three radiologists, which is remarkable.\n",
"title": "RADNET: Radiologist Level Accuracy using Deep Learning for HEMORRHAGE detection in CT Scans"
}
| null | null | null | null | true | null |
13223
| null |
Default
| null | null |
null |
{
"abstract": " Robustness of any statistics depends upon the number of assumptions it makes\nabout the measured data. We point out the advantages of median statistics using\ntoy numerical experiments and demonstrate its robustness, when the number of\nassumptions we can make about the data are limited. We then apply the median\nstatistics technique to obtain estimates of two constants of nature, Hubble\nConstant ($H_0$) and Newton's Gravitational Constant($G$), both of which show\nsignificant differences between different measurements. For $H_0$, we update\nthe analysis done by Chen and Ratra (2011) and Gott et al. (2001) using $576$\nmeasurements. We find after grouping the different results according to their\nprimary type of measurement, the median estimates are given by\n$H_0=72.5^{+2.5}_{-8}$ km/sec/Mpc with errors corresponding to 95% c.l.\n(2$\\sigma$) and $G=6.674702^{+0.0014}_{-0.0009} \\times 10^{-11} \\mathrm{N\nm^{2}kg^{-2}}$ corresponding to 68% c.l. (1$\\sigma$).\n",
"title": "Median statistics estimates of Hubble and Newton's Constant"
}
| null | null | null | null | true | null |
13224
| null |
Default
| null | null |
null |
{
"abstract": " We present a new proof of results of Kurdyka & Paunescu, and of Rainer, about\nreal-analytic multi-parameters generalizations of classical results by Rellich\nand Kato about the reduction in families of univariate deformations of normal\noperators over real or complex vector spaces of finite dimensions.\nGiven a real analytic family of normal operators over a finite dimensional\nreal or complex vector space, there exists a locally finite composition of\nblowings-up with smooth centers re-parameterizing the given family such that at\neach point of the source space of the re-parameterizing mapping, there exists a\nneighbourhood of any given point over which exists a real analytic orthonormal\nframe in which the pull back of the operator is in reduced form at every point\nof the neighbourhood.\nA free by-product of our proof is the local real analyticity of the\neigen-values, which in all prior works was a prerequisite step to get local\nregular reducing bases.\n",
"title": "Re-parameterizing and reducing families of normal operators"
}
| null | null |
[
"Mathematics"
] | null | true | null |
13225
| null |
Validated
| null | null |
null |
{
"abstract": " Robots typically possess sensors of different modalities, such as colour\ncameras, inertial measurement units, and 3D laser scanners. Often, solving a\nparticular problem becomes easier when more than one modality is used. However,\nwhile there are undeniable benefits to combine sensors of different modalities\nthe process tends to be complicated. Segmenting scenes observed by the robot\ninto a discrete set of classes is a central requirement for autonomy as\nunderstanding the scene is the first step to reason about future situations.\nScene segmentation is commonly performed using either image data or 3D point\ncloud data. In computer vision many successful methods for scene segmentation\nare based on conditional random fields (CRF) where the maximum a posteriori\n(MAP) solution to the segmentation can be obtained by inference. In this paper\nwe devise a new CRF inference method for scene segmentation that incorporates\nglobal constraints, enforcing the sets of nodes are assigned the same class\nlabel. To do this efficiently, the CRF is formulated as a relaxed quadratic\nprogram whose MAP solution is found using a gradient-based optimisation\napproach. The proposed method is evaluated on images and 3D point cloud data\ngathered in urban environments where image data provides the appearance\nfeatures needed by the CRF, while the 3D point cloud data provides global\nspatial constraints over sets of nodes. Comparisons with belief propagation,\nconventional quadratic programming relaxation, and higher order potential CRF\nshow the benefits of the proposed method.\n",
"title": "Urban Scene Segmentation with Laser-Constrained CRFs"
}
| null | null | null | null | true | null |
13226
| null |
Default
| null | null |
null |
{
"abstract": " In the framework of the GAPS project, we are conducting an observational\nprogramme aimed at the determination of the orbital obliquity of known\ntransiting exoplanets. The targets are selected to probe the obliquity against\na wide range of stellar and planetary physical parameters. We exploit\nhigh-precision radial velocity (RV) measurements, delivered by the HARPS-N\nspectrograph at the 3.6m Telescopio Nazionale Galileo, to measure the\nRossiter-McLaughlin (RM) effect in RV time-series bracketing planet transits,\nand to refine the orbital parameters determinations with out-of-transit RV\ndata. We also analyse new transit light curves obtained with several 1-2m class\ntelescopes to better constrain the physical fundamental parameters of the\nplanets and parent stars. We report here on new transit spectroscopic\nobservations for three very massive close-in giant planets: WASP43b, HATP20b\nand Qatar2b orbiting dwarf K-type stars with effective temperature well below\n5000K. We find lambda = 3.5pm6.8 deg for WASP43b and lambda = -8.0pm6.9 deg for\nHATP20b, while for Qatar2, our faintest target, the RM effect is only\nmarginally detected, though our best-fit value lambda = 15pm20 deg is in\nagreement with a previous determination. In combination with stellar rotational\nperiods derived photometrically, we estimate the true spin-orbit angle, finding\nthat WASP43b is aligned while the orbit of HATP20b presents a small but\nsignificant obliquity (Psi=36 _{-12}^{+10} deg). By analyzing the CaII H&K\nchromospheric emission lines for HATP20 and WASP43, we find evidence for an\nenhanced level of stellar activity which is possibly induced by star-planet\ninteractions.\n",
"title": "The GAPS Programme with HARPS-N at TNG. XIII. The orbital obliquity of three close-in massive planets hosted by dwarf K-type stars: WASP-43, HAT-P-20 and Qatar-2"
}
| null | null | null | null | true | null |
13227
| null |
Default
| null | null |
null |
{
"abstract": " We tackle the problem of deciding whether two probabilistic programs are\nequivalent in Probabilistic NetKAT, a formal language for specifying and\nreasoning about the behavior of packet-switched networks. We show that the\nproblem is decidable for the history-free fragment of the language by\ndeveloping an effective decision procedure based on stochastic matrices. The\nmain challenge lies in reasoning about iteration, which we address by designing\nan encoding of the program semantics as a finite-state absorbing Markov chain,\nwhose limiting distribution can be computed exactly. In an extended case study\non a real-world data center network, we automatically verify various\nquantitative properties of interest, including resilience in the presence of\nfailures, by analyzing the Markov chain semantics.\n",
"title": "Probabilistic Program Equivalence for NetKAT"
}
| null | null |
[
"Computer Science"
] | null | true | null |
13228
| null |
Validated
| null | null |
null |
{
"abstract": " Colocalization analysis aims to study complex spatial associations between\nbio-molecules via optical imaging techniques. However, existing colocalization\nanalysis workflows only assess an average degree of colocalization within a\ncertain region of interest and ignore the unique and valuable spatial\ninformation offered by microscopy. In the current work, we introduce a new\nframework for colocalization analysis that allows us to quantify colocalization\nlevels at each individual location and automatically identify pixels or regions\nwhere colocalization occurs. The framework, referred to as spatially adaptive\ncolocalization analysis (SACA), integrates a pixel-wise local kernel model for\ncolocalization quantification and a multi-scale adaptive propagation-separation\nstrategy for utilizing spatial information to detect colocalization in a\nspatially adaptive fashion. Applications to simulated and real biological\ndatasets demonstrate the practical merits of SACA in what we hope to be an\neasily applicable and robust colocalization analysis method. In addition,\ntheoretical properties of SACA are investigated to provide rigorous statistical\njustification.\n",
"title": "Spatially Adaptive Colocalization Analysis in Dual-Color Fluorescence Microscopy"
}
| null | null |
[
"Statistics"
] | null | true | null |
13229
| null |
Validated
| null | null |
null |
{
"abstract": " Given a vertex of interest in a network $G_1$, the vertex nomination problem\nseeks to find the corresponding vertex of interest (if it exists) in a second\nnetwork $G_2$. A vertex nomination scheme produces a list of the vertices in\n$G_2$, ranked according to how likely they are judged to be the corresponding\nvertex of interest in $G_2$. The vertex nomination problem and related\ninformation retrieval tasks have attracted much attention in the machine\nlearning literature, with numerous applications to social and biological\nnetworks. However, the current framework has often been confined to a\ncomparatively small class of network models, and the concept of statistically\nconsistent vertex nomination schemes has been only shallowly explored. In this\npaper, we extend the vertex nomination problem to a very general statistical\nmodel of graphs. Further, drawing inspiration from the long-established\nclassification framework in the pattern recognition literature, we provide\ndefinitions for the key notions of Bayes optimality and consistency in our\nextended vertex nomination framework, including a derivation of the Bayes\noptimal vertex nomination scheme. In addition, we prove that no universally\nconsistent vertex nomination schemes exist. Illustrative examples are provided\nthroughout.\n",
"title": "On consistent vertex nomination schemes"
}
| null | null | null | null | true | null |
13230
| null |
Default
| null | null |
null |
{
"abstract": " Passivity is an imperative concept and a widely utilized tool in the analysis\nand control of interconnected systems. It naturally arises in the modelling of\nphysical systems involving passive elements and dynamics. While many theorems\non passivity are known in the theory of robust control, very few converse\npassivity results exist. This paper establishes various versions of converse\npassivity theorems for nonlinear feedback systems. In particular, open-loop\npassivity is shown to be necessary to ensure closed-loop passivity from an\ninput-output perspective. Moreover, the stability of the feedback\ninterconnection of a specific system with an arbitrary passive system is shown\nto imply passivity of the system itself.\n",
"title": "Converse passivity theorems"
}
| null | null |
[
"Mathematics"
] | null | true | null |
13231
| null |
Validated
| null | null |
null |
{
"abstract": " Restricted Boltzmann Machines are key tools in Machine Learning and are\ndescribed by the energy function of bipartite spin-glasses. From a statistical\nmechanical perspective, they share the same Gibbs measure of Hopfield networks\nfor associative memory. In this equivalence, weights in the former play as\npatterns in the latter. As Boltzmann machines usually require real weights to\nbe trained with gradient descent like methods, while Hopfield networks\ntypically store binary patterns to be able to retrieve, the investigation of a\nmixed Hebbian network, equipped with both real (e.g., Gaussian) and discrete\n(e.g., Boolean) patterns naturally arises. We prove that, in the challenging\nregime of a high storage of real patterns, where retrieval is forbidden, an\nextra load of Boolean patterns can still be retrieved, as long as the ratio\namong the overall load and the network size does not exceed a critical\nthreshold, that turns out to be the same of the standard\nAmit-Gutfreund-Sompolinsky theory. Assuming replica symmetry, we study the case\nof a low load of Boolean patterns combining the stochastic stability and\nHamilton-Jacobi interpolating techniques. The result can be extended to the\nhigh load by a non rigorous but standard replica computation argument.\n",
"title": "Neural Networks retrieving Boolean patterns in a sea of Gaussian ones"
}
| null | null | null | null | true | null |
13232
| null |
Default
| null | null |
null |
{
"abstract": " We discuss the connection between colorings of a link diagram and the Goeritz\nmatrix.\n",
"title": "Link colorings and the Goeritz matrix"
}
| null | null | null | null | true | null |
13233
| null |
Default
| null | null |
null |
{
"abstract": " Let M be a real analytic Riemannian manifold. An adapted complex structure on\nTM is a complex structure on a neighborhood of the zero section such that the\nleaves of the Riemann foliation are complex submanifolds. This structure is\ncalled entire if it may be extended to the whole of TM. We call such manifolds\nGrauert tubes, or simply tubes. We consider here the case of M = G a compact\nconnected Lie group with a left-invariant metric, and try to determine for\nwhich such metrics the associated tube is entire. It is well-known that the\nGrauert tube of a bi-invariant metric on a Lie group is entire. The case of the\nsmallest group SU(2) is treated completely, thanks to the complete\nintegrability of the geodesic flow for such a metric, a standard result in\nclassical mechanics. Along the way we find a new obstruction to tubes being\nentire which is made visible by the complete integrability. (New reference and\nexposition shortened, 11/17/2017.)\n",
"title": "Left-invariant Grauert tubes on SU(2)"
}
| null | null | null | null | true | null |
13234
| null |
Default
| null | null |
null |
{
"abstract": " The main objective of this thesis is the study of the evolution under the\nRicci flow of surfaces with singularities of cone type. A second objective,\nemerged from the techniques we use, is the study of families of Ricci flow\nsolitons in dimension 2 and 3. The Ricci flow is an evolution equation for\nRiemannian manifolds, introduced by R. Hamilton in 1982. It is from the\nachievements made by G. Perelman with this technique in 2002 when the Ricci\nflow has been established in a discipline itself, generating a great interest\nin the community. This thesis contains four original results. First result is a\ncomplete classification of solitons in smooth and cone surfaces. This\nclassification completes the preceding results found by Hamilton, Chow and Wu\nand others, and we obtain explicit descriptions of all solitons in dimension 2.\nSecond result is a Geometrization of cone surfaces by Ricci flow. This result,\nwhich uses the aforementioned first result, extends the theory of Hamilton to\nthe singular case. This is the most comprehensive result in the thesis, for\nwhich we use and develop analysis and PDE techniques, as well as comparison\ngeometry techniques. Third result is the existence of a Ricci flow that removes\ncone singularities. This clearly exposes the non-uniqueness of solutions to the\nflow , in analogy to the Ricci flow with cusps of P. Topping. The fourth result\nis the construction of a new expanding gradient Ricci soliton in dimension 3.\nJust as we do with solitons on cone surfaces, we give an explicit construction\nusing techniques of phase portraits. We also prove that this is the only\nsoliton with its topology and its lower bound of the curvature, and besides\nthis is a critical case amongst all expanding solitons in dimension 3 with\ncurvature bounded below.\n",
"title": "Ricci flow on cone surfaces and a three-dimensional expanding soliton"
}
| null | null |
[
"Mathematics"
] | null | true | null |
13235
| null |
Validated
| null | null |
null |
{
"abstract": " We show that the dynamics of the Higgs field during inflation is not affected\nby metric fluctuations if the Higgs is an energetically subdominant light\nspectator. For Standard Model parameters we find that couplings between Higgs\nand metric fluctuations are suppressed by $\\mathcal{O}(10^{-7})$. They are\nnegligible compared to both pure Higgs terms in the effective potential and the\nunavoidable non-minimal Higgs coupling to background scalar curvature. The\nquestion of the electroweak vacuum instability during high energy scale\ninflation can therefore be studied consistently using the Jordan frame action\nin a Friedmann--Lemaître--Robertson--Walker metric, where the Higgs-curvature\ncoupling enters as an effective mass contribution. Similar results apply for\nother light spectator scalar fields during inflation.\n",
"title": "Do metric fluctuations affect the Higgs dynamics during inflation?"
}
| null | null |
[
"Physics"
] | null | true | null |
13236
| null |
Validated
| null | null |
null |
{
"abstract": " In topology, a torus remains invariant under certain non-trivial\ntransformations known as modular transformations. In the context of\ntopologically ordered quantum states of matter, these transformations encode\nthe braiding statistics and fusion rules of emergent anyonic excitations and\nthus serve as a diagnostic of topological order. Moreover, modular\ntransformations of higher genus surfaces, e.g. a torus with multiple handles,\ncan enhance the computational power of a topological state, in many cases\nproviding a universal fault-tolerant set of gates for quantum computation.\nHowever, due to the intrusive nature of modular transformations, which\nabstractly involve global operations and manifold surgery, physical\nimplementations of them in local systems have remained elusive. Here, we show\nthat by folding manifolds, modular transformations can be applied in a single\nshot by independent local unitaries, providing a novel class of transversal\nlogic gates for fault-tolerant quantum computation. Specifically, we\ndemonstrate that multi-layer topological states with appropriate boundary\nconditions and twist defects allow modular transformations to be effectively\nimplemented by a finite sequence of local SWAP gates between the layers. We\nfurther provide methods to directly measure the modular matrices, and thus the\nfractional statistics of anyonic excitations, providing a novel way to directly\nmeasure topological order.\n",
"title": "Quantum Origami: Transversal Gates for Quantum Computation and Measurement of Topological Order"
}
| null | null | null | null | true | null |
13237
| null |
Default
| null | null |
null |
{
"abstract": " The proliferation of small-scale renewable generators and price-responsive\nloads makes it a challenge for distribution network operators (DNOs) to\nschedule the controllable loads of the load aggregators and the generation of\nthe generators in real-time. Additionally, the high computational burden and\nviolation of the entities' (i.e., load aggregators' and generators') privacy\nmake a centralized framework impractical. In this paper, we propose a\ndecentralized energy trading algorithm that can be executed by the entities in\na real-time fashion. To address the privacy issues, the DNO provides the\nentities with proper control signals using the Lagrange relaxation technique to\nmotivate them towards an operating point with maximum profit for entities. To\ndeal with uncertainty issues, we propose a probabilistic load model and robust\nframework for renewable generation. The performance of the proposed algorithm\nis evaluated on an IEEE 123-node test feeder. When compared with a benchmark of\nnot performing load management for the aggregators, the proposed algorithm\nbenefits both the load aggregators and generators by increasing their profit by\n17.8%and 10.3%, respectively. When compared with a centralized approach, our\nalgorithm converges to the solution of the DNO's centralized problem with a\nsignificantly lower running time in 50 iterations per time slot.\n",
"title": "A Decentralized Framework for Real-Time Energy Trading in Distribution Networks with Load and Generation Uncertainty"
}
| null | null | null | null | true | null |
13238
| null |
Default
| null | null |
null |
{
"abstract": " Electrical brain stimulation is currently being investigated as a therapy for\nneurological disease. However, opportunities to optimize such therapies are\nchallenged by the fact that the beneficial impact of focal stimulation on both\nneighboring and distant regions is not well understood. Here, we use network\ncontrol theory to build a model of brain network function that makes\npredictions about how stimulation spreads through the brain's white matter\nnetwork and influences large-scale dynamics. We test these predictions using\ncombined electrocorticography (ECoG) and diffusion weighted imaging (DWI) data\nwho volunteered to participate in an extensive stimulation regimen. We posit a\nspecific model-based manner in which white matter tracts constrain stimulation,\ndefining its capacity to drive the brain to new states, including states\nassociated with successful memory encoding. In a first validation of our model,\nwe find that the true pattern of white matter tracts can be used to more\naccurately predict the state transitions induced by direct electrical\nstimulation than the artificial patterns of null models. We then use a targeted\noptimal control framework to solve for the optimal energy required to drive the\nbrain to a given state. We show that, intuitively, our model predicts larger\nenergy requirements when starting from states that are farther away from a\ntarget memory state. We then suggest testable hypotheses about which structural\nproperties will lead to efficient stimulation for improving memory based on\nenergy requirements. Our work demonstrates that individual white matter\narchitecture plays a vital role in guiding the dynamics of direct electrical\nstimulation, more generally offering empirical support for the utility of\nnetwork control theoretic models of brain response to stimulation.\n",
"title": "White Matter Network Architecture Guides Direct Electrical Stimulation Through Optimal State Transitions"
}
| null | null | null | null | true | null |
13239
| null |
Default
| null | null |
null |
{
"abstract": " Revealing a community structure in a network or dataset is a central problem\narising in many scientific areas. The modularity function $Q$ is an established\nmeasure quantifying the quality of a community, being identified as a set of\nnodes having high modularity. In our terminology, a set of nodes with positive\nmodularity is called a \\textit{module} and a set that maximizes $Q$ is thus\ncalled \\textit{leading module}. Finding a leading module in a network is an\nimportant task, however the dimension of real-world problems makes the\nmaximization of $Q$ unfeasible. This poses the need of approximation techniques\nwhich are typically based on a linear relaxation of $Q$, induced by the\nspectrum of the modularity matrix $M$. In this work we propose a nonlinear\nrelaxation which is instead based on the spectrum of a nonlinear modularity\noperator $\\mathcal M$. We show that extremal eigenvalues of $\\mathcal M$\nprovide an exact relaxation of the modularity measure $Q$, however at the price\nof being more challenging to be computed than those of $M$. Thus we extend the\nwork made on nonlinear Laplacians, by proposing a computational scheme, named\n\\textit{generalized RatioDCA}, to address such extremal eigenvalues. We show\nmonotonic ascent and convergence of the method. We finally apply the new method\nto several synthetic and real-world data sets, showing both effectiveness of\nthe model and performance of the method.\n",
"title": "Community detection in networks via nonlinear modularity eigenvectors"
}
| null | null | null | null | true | null |
13240
| null |
Default
| null | null |
null |
{
"abstract": " We consider a variant of online convex optimization in which both the\ninstances (input vectors) and the comparator (weight vector) are unconstrained.\nWe exploit a natural scale invariance symmetry in our unconstrained setting:\nthe predictions of the optimal comparator are invariant under any linear\ntransformation of the instances. Our goal is to design online algorithms which\nalso enjoy this property, i.e. are scale-invariant. We start with the case of\ncoordinate-wise invariance, in which the individual coordinates (features) can\nbe arbitrarily rescaled. We give an algorithm, which achieves essentially\noptimal regret bound in this setup, expressed by means of a coordinate-wise\nscale-invariant norm of the comparator. We then study general invariance with\nrespect to arbitrary linear transformations. We first give a negative result,\nshowing that no algorithm can achieve a meaningful bound in terms of\nscale-invariant norm of the comparator in the worst case. Next, we compliment\nthis result with a positive one, providing an algorithm which \"almost\" achieves\nthe desired bound, incurring only a logarithmic overhead in terms of the norm\nof the instances.\n",
"title": "Scale-invariant unconstrained online learning"
}
| null | null |
[
"Computer Science",
"Statistics"
] | null | true | null |
13241
| null |
Validated
| null | null |
null |
{
"abstract": " We investigate the nature of the superconducting state in curved\nnanostructures with Rashba spin-orbit coupling (RSOC). In bent nanostructures\nwith inhomogeneous curvature we find a local enhancement or suppression of the\nsuperconducting order parameter, with the effect that can be tailored by tuning\neither the RSOC strength or the carrier density. Apart from the local\nsuperconducting spin-singlet amplitude control, the geometric curvature\ngenerates non-trivial textures of the spin-triplet pairs through a spatial\nvariation of the d-vector. By employing the representative case of an\nelliptically deformed quantum ring, we demonstrate that the amplitude of the\nd-vector strongly depends on the strength of the local curvature and it\ngenerally exhibits a three-dimensional profile whose winding is tied to that of\nthe single electron spin in the normal state. Our findings unveil novel paths\nto manipulate the quantum structure of the superconducting state in RSOC\nnanostructures through their geometry.\n",
"title": "Tuning Pairing Amplitude and Spin-Triplet Texture by Curving Superconducting Nanostructures"
}
| null | null |
[
"Physics"
] | null | true | null |
13242
| null |
Validated
| null | null |
null |
{
"abstract": " By means of first-principles calculations, we investigate the thermal\nproperties of silica as it evolves, under hydrostatic compression, from a\nstishovite phase into a CaCl$_2$-type structure. We compute the thermal\nconductivity tensor by solving the linearized Boltzmann transport equation\niteratively in a wide temperature range, using for this the pressure-dependent\nharmonic and anharmonic interatomic couplings obtained from first principles.\nMost remarkably, we find that, at low temperatures, SiO$_2$ displays a large\npeak in the in-plane thermal conductivity and a highly anisotropic behavior\nclose to the structural transformation. We trace back the origin of these\nfeatures by analyzing the phonon contributions to the conductivity. We discuss\nthe implications of our results in the general context of continuous structural\ntransformations in solids, as well as the potential geological interest of our\nresults for silica.\n",
"title": "Thermal conductivity changes across a structural phase transition: the case of high-pressure silica"
}
| null | null |
[
"Physics"
] | null | true | null |
13243
| null |
Validated
| null | null |
null |
{
"abstract": " A core technique used by popular proxy-based circumvention systems like Tor,\nPsiphon, and Lantern is to secretly share the IP addresses of circumvention\nproxies with the censored clients for them to be able to use such systems. For\ninstance, such secretly shared proxies are known as bridges in Tor. However, a\nkey challenge to this mechanism is the insider attack problem: censoring agents\ncan impersonate as benign censored clients in order to obtain (and then block)\nsuch secretly shared circumvention proxies.\nIn this paper, we perform a fundamental study on the problem of insider\nattack on proxy-based circumvention systems. We model the proxy distribution\nproblem using game theory, based on which we derive the optimal strategies of\nthe parties involved, i.e., the censors and circumvention system operators.\nThat is, we derive the optimal proxy distribution mechanism of a\ncircumvention system like Tor, against the censorship adversary who also takes\nhis optimal censorship strategies.\nThis is unlike previous works that design ad hoc mechanisms for proxy\ndistribution, against non-optimal censors.\nWe perform extensive simulations to evaluate our optimal proxy assignment\nalgorithm under various adversarial and network settings. Comparing with the\nstate-of-the-art prior work, we show that our optimal proxy assignment\nalgorithm has superior performance, i.e., better resistance to censorship even\nagainst the strongest censorship adversary who takes her optimal actions. We\nconclude with lessons and recommendation for the design of proxy-based\ncircumvention systems.\n",
"title": "Enemy At the Gateways: A Game Theoretic Approach to Proxy Distribution"
}
| null | null |
[
"Computer Science"
] | null | true | null |
13244
| null |
Validated
| null | null |
null |
{
"abstract": " We study the special fiber of the integral models for Shimura varieties of\nHodge type with parahoric level structure constructed by Kisin and Pappas in\n[KP]. We show that when the group is residually split, the points in the mod\n$p$ isogeny classes have the form predicted by the Langlands Rapoport\nconjecture in [LR].\nWe also verify most of the He-Rapoport axioms for these integral models\nwithout the residually split assumption. This allows us to prove that all\nNewton strata are non-empty for these models.\n",
"title": "Mod-$p$ isogeny classes on Shimura varieties with parahoric level structure"
}
| null | null | null | null | true | null |
13245
| null |
Default
| null | null |
null |
{
"abstract": " Bayesian optimization has been successful at global optimization of\nexpensive-to-evaluate multimodal objective functions. However, unlike most\noptimization methods, Bayesian optimization typically does not use derivative\ninformation. In this paper we show how Bayesian optimization can exploit\nderivative information to decrease the number of objective function evaluations\nrequired for good performance. In particular, we develop a novel Bayesian\noptimization algorithm, the derivative-enabled knowledge-gradient (dKG), for\nwhich we show one-step Bayes-optimality, asymptotic consistency, and greater\none-step value of information than is possible in the derivative-free setting.\nOur procedure accommodates noisy and incomplete derivative information, comes\nin both sequential and batch forms, and can optionally reduce the computational\ncost of inference through automatically selected retention of a single\ndirectional derivative. We also compute the d-KG acquisition function and its\ngradient using a novel fast discretization-free technique. We show d-KG\nprovides state-of-the-art performance compared to a wide range of optimization\nprocedures with and without gradients, on benchmarks including logistic\nregression, deep learning, kernel learning, and k-nearest neighbors.\n",
"title": "Bayesian Optimization with Gradients"
}
| null | null |
[
"Computer Science",
"Mathematics",
"Statistics"
] | null | true | null |
13246
| null |
Validated
| null | null |
null |
{
"abstract": " In this article we study the problem of fair division. In particular we study\na notion introduced by J. Barbanel that generalizes super envy-free fair\ndivision. We give a new proof of his result. Our approach allows us to give an\nexplicit bound for this kind of fair division. Furthermore, we also give a\ntheoretical answer to an open problem posed by Barbanel in 1996. Roughly\nspeaking, this question is: how can we decide if there exists a fair division\nsatisfying some inequalities constraints? Furthermore, when all the measures\nare given with piecewise constant density functions then we show how to\nconstruct effectively such a fair division.\n",
"title": "How to cut a cake with a gram matrix"
}
| null | null | null | null | true | null |
13247
| null |
Default
| null | null |
null |
{
"abstract": " In magnetic resonant coupling (MRC) enabled multiple-input multiple-output\n(MIMO) wireless power transfer (WPT) systems, multiple transmitters (TXs) each\nwith one single coil are used to enhance the efficiency of simultaneous power\ntransfer to multiple single-coil receivers (RXs) by constructively combining\ntheir induced magnetic fields at the RXs, a technique termed \"magnetic\nbeamforming\". In this paper, we study the optimal magnetic beamforming design\nin a multi-user MIMO MRC-WPT system. We introduce the multi-user power region\nthat constitutes all the achievable power tuples for all RXs, subject to the\ngiven total power constraint over all TXs as well as their individual peak\nvoltage and current constraints. We characterize each boundary point of the\npower region by maximizing the sum-power deliverable to all RXs subject to\ntheir minimum harvested power constraints. For the special case without the TX\npeak voltage and current constraints, we derive the optimal TX current\nallocation for the single-RX setup in closed-form as well as that for the\nmulti-RX setup. In general, the problem is a non-convex quadratically\nconstrained quadratic programming (QCQP), which is difficult to solve. For the\ncase of one single RX, we show that the semidefinite relaxation (SDR) of the\nproblem is tight. For the general case with multiple RXs, based on SDR we\nobtain two approximate solutions by applying time-sharing and randomization,\nrespectively. Moreover, for practical implementation of magnetic beamforming,\nwe propose a novel signal processing method to estimate the magnetic MIMO\nchannel due to the mutual inductances between TXs and RXs. Numerical results\nshow that our proposed magnetic channel estimation and adaptive beamforming\nschemes are practically effective, and can significantly improve the power\ntransfer efficiency and multi-user performance trade-off in MIMO MRC-WPT\nsystems.\n",
"title": "Magnetic MIMO Signal Processing and Optimization for Wireless Power Transfer"
}
| null | null |
[
"Computer Science"
] | null | true | null |
13248
| null |
Validated
| null | null |
null |
{
"abstract": " This work introduces a class of rejection-free Markov chain Monte Carlo\n(MCMC) samplers, named the Bouncy Hybrid Sampler, which unifies several\nexisting methods from the literature. Examples include the Bouncy Particle\nSampler of Peters and de With (2012), Bouchard-Cote et al. (2015) and the\nHamiltonian MCMC. Following the introduced general framework, we derive a new\nsampler called the Quadratic Bouncy Hybrid Sampler. We apply this novel sampler\nto the problem of sampling from a truncated Gaussian distribution.\n",
"title": "Bouncy Hybrid Sampler as a Unifying Device"
}
| null | null | null | null | true | null |
13249
| null |
Default
| null | null |
null |
{
"abstract": " At air-water interfaces, the Lifshitz interaction by itself does not promote\nice growth. On the contrary, we find that the Lifshitz force promotes the\ngrowth of an ice film, up to 1-8 nm thickness, near silica-water interfaces at\nthe triple point of water. This is achieved in a system where the combined\neffect of the retardation and the zero frequency mode influences the\nshort-range interactions at low temperatures, contrary to common understanding.\nCancellation between the positive and negative contributions in the Lifshitz\nspectral function is reversed in silica with high porosity. Our results provide\na model for how water freezes on glass and other surfaces.\n",
"title": "Lifshitz interaction can promote ice growth at water-silica interfaces"
}
| null | null | null | null | true | null |
13250
| null |
Default
| null | null |
null |
{
"abstract": " We study the following basic machine learning task: Given a fixed set of\n$d$-dimensional input points for a linear regression problem, we wish to\npredict a hidden response value for each of the points. We can only afford to\nattain the responses for a small subset of the points that are then used to\nconstruct linear predictions for all points in the dataset. The performance of\nthe predictions is evaluated by the total square loss on all responses (the\nattained as well as the hidden ones). We show that a good approximate solution\nto this least squares problem can be obtained from just dimension $d$ many\nresponses by using a joint sampling technique called volume sampling. Moreover,\nthe least squares solution obtained for the volume sampled subproblem is an\nunbiased estimator of optimal solution based on all n responses. This\nunbiasedness is a desirable property that is not shared by other common subset\nselection techniques.\nMotivated by these basic properties, we develop a theoretical framework for\nstudying volume sampling, resulting in a number of new matrix expectation\nequalities and statistical guarantees which are of importance not only to least\nsquares regression but also to numerical linear algebra in general. Our methods\nalso lead to a regularized variant of volume sampling, and we propose the first\nefficient algorithms for volume sampling which make this technique a practical\ntool in the machine learning toolbox. Finally, we provide experimental evidence\nwhich confirms our theoretical findings.\n",
"title": "Reverse iterative volume sampling for linear regression"
}
| null | null | null | null | true | null |
13251
| null |
Default
| null | null |
null |
{
"abstract": " Collecting labeled data is costly and thus a critical bottleneck in\nreal-world classification tasks. To mitigate this problem, we propose a novel\nsetting, namely learning from complementary labels for multi-class\nclassification. A complementary label specifies a class that a pattern does not\nbelong to. Collecting complementary labels would be less laborious than\ncollecting ordinary labels, since users do not have to carefully choose the\ncorrect class from a long list of candidate classes. However, complementary\nlabels are less informative than ordinary labels and thus a suitable approach\nis needed to better learn from them. In this paper, we show that an unbiased\nestimator to the classification risk can be obtained only from complementarily\nlabeled data, if a loss function satisfies a particular symmetric condition. We\nderive estimation error bounds for the proposed method and prove that the\noptimal parametric convergence rate is achieved. We further show that learning\nfrom complementary labels can be easily combined with learning from ordinary\nlabels (i.e., ordinary supervised learning), providing a highly practical\nimplementation of the proposed method. Finally, we experimentally demonstrate\nthe usefulness of the proposed methods.\n",
"title": "Learning from Complementary Labels"
}
| null | null | null | null | true | null |
13252
| null |
Default
| null | null |
null |
{
"abstract": " This letter presents a revised radiative transfer model for the infrared (IR)\nemission of active galactic nuclei (AGN). While current models assume that the\nIR is emitted from a dusty torus in the equatorial plane of the AGN, spatially\nresolved observations indicate that the majority of the IR emission from 100 pc\nin many AGN originates from the polar region, contradicting classical torus\nmodels. The new model CAT3D-WIND builds upon the suggestion that the dusty gas\naround the AGN consists of an inflowing disk and an outflowing wind. Here, it\nis demonstrated that (1) such disk+wind models cover overall a similar\nparameter range of observed spectral features in the IR as classical clumpy\ntorus models, e.g. the silicate feature strengths and mid-IR spectral slopes,\n(2) they reproduce the 3-5{\\mu}m bump observed in many type 1 AGN unlike torus\nmodels, and (3) they are able to explain polar emission features seen in IR\ninterferometry, even for type 1 AGN at relatively low inclination, as\ndemonstrated for NGC3783. These characteristics make it possible to reconcile\nradiative transfer models with observations and provide further evidence of a\ntwo-component parsec-scaled dusty medium around AGN: the disk gives rise to the\n3-5{\\mu}m near-IR component, while the wind produces the mid-IR emission. The\nmodel SEDs will be made available for download.\n",
"title": "Dusty winds in active galactic nuclei: reconciling observations with models"
}
| null | null | null | null | true | null |
13253
| null |
Default
| null | null |
null |
{
"abstract": " In this paper we find sufficient conditions for the continuity of the value\nof the utility maximization problem from terminal wealth with respect to the\nconvergence in distribution of the underlying processes. We provide several\nexamples which illustrate that without these conditions, we cannot generally\nexpect continuity to hold. Finally, we apply our results to the computation of\nthe minimum shortfall in the Heston model by building an appropriate lattice\napproximation.\n",
"title": "Continuity of Utility Maximization under Weak Convergence"
}
| null | null |
[
"Quantitative Finance"
] | null | true | null |
13254
| null |
Validated
| null | null |
null |
{
"abstract": " Education is increasingly being framed by a competence mindset; the value of\nknowledge lies much more in competence performativity and innovation than in\nsimply knowing. Reaching such competency in areas such as astronomy and physics\nhas long been known to be challenging. The movement from everyday conceptions\nof the world around us to a disciplinary interpretation is fraught with\npitfalls and problems. Thus, what underpins the characteristics of the\ndisciplinary trajectory to competence becomes an important educational\nconsideration. In this article we report on a study involving what students and\nlecturers discern from the same disciplinary semiotic resource. We use this to\npropose an Anatomy of Disciplinary Discernment (ADD), a hierarchy of what is\nfocused on and how it is interpreted in an appropriate, disciplinary manner, as\nan overarching fundamental aspect of disciplinary learning. Students and\nlecturers in astronomy and physics were asked to describe what they could\ndiscern from a video simulation of travel through our Galaxy and beyond. 137\npeople from nine countries participated. The descriptions were analysed using a\nhermeneutic interpretive study approach. The analysis resulted in the\nformulation of five qualitatively different categories of discernment; the ADD,\nreflecting a view of participants' competence levels. The ADD reveals four\nincreasing levels of disciplinary discernment: Identification, Explanation,\nAppreciation, and Evaluation. This facilitates the identification of a clear\nrelationship between educational level and the level of disciplinary\ndiscernment. The analytical outcomes of the study suggest how teachers of\nscience, after using the ADD to assess the students disciplinary knowledge, may\nattain new insights into how to create more effective learning environments by\nexplicitly crafting their teaching to support the crossing of boundaries in the\nADD model.\n",
"title": "Introducing the anatomy of disciplinary discernment: an example from astronomy"
}
| null | null | null | null | true | null |
13255
| null |
Default
| null | null |
null |
{
"abstract": " This article represents a first step toward understanding the long time\ndynamics of solutions for the Benjamin-Ono equation. While this problem is\nknown to be both completely integrable and globally well-posed in $L^2$, much\nless seems to be known concerning its long time dynamics. Here, we prove that\nfor small localized data the solutions have (nearly) dispersive dynamics almost\nglobally in time. An additional objective is to revisit the $L^2$ theory for\nthe Benjamin-Ono equation and provide a simpler, self-contained approach.\n",
"title": "Well-posedness and dispersive decay of small data solutions for the Benjamin-Ono equation"
}
| null | null | null | null | true | null |
13256
| null |
Default
| null | null |
null |
{
"abstract": " We present in this paper a new algorithm for urban traffic light control with\nmixed traffic (communicating and non communicating vehicles) and mixed\ninfrastructure (equipped and unequipped junctions). We call equipped junction\nhere a junction with a traffic light signal (TLS) controlled by a road side\nunit (RSU). On such a junction, the RSU manifests its connectedness to equipped\nvehicles by broadcasting its communication address and geographical\ncoordinates. The RSU builds a map of connected vehicles approaching and leaving\nthe junction. The algorithm allows the RSU to select a traffic phase, based on\nthe built map. The selected traffic phase is applied by the TLS; and both\nequipped and unequipped vehicles must respect it. The traffic management is in\nfeedback on the traffic demand of communicating vehicles. We simulated the\nvehicular traffic as well as the communications. The two simulations are\ncombined in a closed loop with visualization and monitoring interfaces. Several\nindicators on vehicular traffic (mean travel time, ended vehicles) and IEEE\n802.11p communication performances (end-to-end delay, throughput) are derived\nand illustrated in three dimension maps. We then extended the traffic control\nto a urban road network where we also varied the number of equipped junctions.\nOther indicators are shown for road traffic performances in the road network\ncase, where high gains are experienced in the simulation results.\n",
"title": "A vehicle-to-infrastructure communication based algorithm for urban traffic control"
}
| null | null |
[
"Computer Science",
"Mathematics"
] | null | true | null |
13257
| null |
Validated
| null | null |
null |
{
"abstract": " We consider the problem of finding a proper confidence interval for the mean\nbased on a single observation from a normal distribution with both mean and\nvariance unknown. Portnoy (2017) characterizes the scale-sign invariant rules\nand shows that the Hunt-Stein construction provides a randomized invariant rule\nthat improves on any given randomized rule in the sense that it has greater\nminimal coverage among all procedures with a fixed expected length.\nMathematical results here provide a specific mixture of two non-randomized\ninvariant rules that achieve the minimax optimality. A multivariate confidence\nset based on a single observation vector is also developed.\n",
"title": "Some Theorems on Optimality of a Single Observation Confidence Interval for the Mean of a Normal Distribution"
}
| null | null | null | null | true | null |
13258
| null |
Default
| null | null |
null |
{
"abstract": " We investigated the reliability and applicability of so-called magnetic force\nlinear response method to calculate spin-spin interaction strengths from\nfirst-principles. We examined the dependence on the numerical parameters\nincluding the number of basis orbitals and their cutoff radii within\nnon-orthogonal LCPAO (linear combination of pseudo-atomic orbitals) formalism.\nIt is shown that the parameter dependence and the ambiguity caused by these\nchoices are small enough in comparison to the other computation approach and\nexperiments. Further, we tried to pursue the possible extension of this\ntechnique to a wider range of applications. We showed that magnetic force\ntheorem can provide the reasonable estimation especially for the case of\nstrongly localized moments even when the ground state configuration is unknown\nor the total energy value is not accessible. The formalism is extended to carry\nthe orbital resolution from which the matrix form of the magnetic coupling\nconstant is calculated. From the applications to Fe-based superconductors\nincluding LaFeAsO, NaFeAs, BaFe$_2$As$_2$ and FeTe, the distinctive\ncharacteristics of orbital-resolved interactions are clearly noticed in between\nsingle-stripe pnictides and double-stripe chalcogenides.\n",
"title": "Reliability and applicability of magnetic force linear response theory: Numerical parameters, predictability, and orbital resolution"
}
| null | null |
[
"Physics"
] | null | true | null |
13259
| null |
Validated
| null | null |
null |
{
"abstract": " Probabilistic timed automata (PTAs) are timed automata (TAs) extended with\ndiscrete probability distributions.They serve as a mathematical model for a\nwide range of applications that involve both stochastic and timed behaviours.\nIn this work, we consider the problem of model-checking linear\n\\emph{dense-time} properties over {PTAs}. In particular, we study linear\ndense-time properties that can be encoded by TAs with infinite acceptance\ncriterion.First, we show that the problem of model-checking PTAs against\ndeterministic-TA specifications can be solved through a product construction.\nBased on the product construction, we prove that the computational complexity\nof the problem with deterministic-TA specifications is EXPTIME-complete. Then\nwe show that when relaxed to general (nondeterministic) TAs, the model-checking\nproblem becomes undecidable.Our results substantially extend state of the art\nwith both the dense-time feature and the nondeterminism in TAs.\n",
"title": "Verifying Probabilistic Timed Automata Against Omega-Regular Dense-Time Properties"
}
| null | null | null | null | true | null |
13260
| null |
Default
| null | null |
null |
{
"abstract": " In this paper, we give some counting results on integer polynomials of fixed\ndegree and bounded height whose distinct non-zero roots are multiplicatively\ndependent. These include sharp lower bounds, upper bounds and asymptotic\nformulas for various cases, although in general there is a logarithmic gap\nbetween lower and upper bounds.\n",
"title": "On the number of integer polynomials with multiplicatively dependent roots"
}
| null | null | null | null | true | null |
13261
| null |
Default
| null | null |
null |
{
"abstract": " In this paper, we obtain a class of Virasoro modules by taking tensor\nproducts of the irreducible Virasoro modules $\\Omega(\\lambda,\\alpha,h)$ defined\nin \\cite{CG}, with irreducible highest weight modules $V(\\theta,h)$ or with\nirreducible Virasoro modules Ind$_{\\theta}(N)$ defined in \\cite{MZ2}. We obtain\nthe necessary and sufficient conditions for such tensor product modules to be\nirreducible, and determine the necessary and sufficient conditions for two of\nthem to be isomorphic. These modules are not isomorphic to any other known\nirreducible Virasoro modules.\n",
"title": "New irreducible tensor product modules for the Virasoro algebra"
}
| null | null | null | null | true | null |
13262
| null |
Default
| null | null |
null |
{
"abstract": " It has previously been shown that a dye-filled microcavity can produce a\nBose-Einstein condensate of photons. Thermalization of photons is possible via\nrepeated absorption and re-emission by the dye molecules. In this paper, we\ntheoretically explore the behavior of the polarization of light in this system.\nWe find that in contrast to the near complete thermalization between different\nspatial modes of light, thermalization of polarization states is expected to\ngenerally be incomplete. We show that the polarization degree changes\nsignificantly from below to above threshold, and explain the dependence of\npolarization on all relevant material parameters.\n",
"title": "Polarization dynamics in a photon BEC"
}
| null | null | null | null | true | null |
13263
| null |
Default
| null | null |
null |
{
"abstract": " Background: Ab initio many-body methods whose numerical cost scales\npolynomially with the number of particles have been developed over the past\nfifteen years to tackle closed-shell mid-mass nuclei. Open-shell nuclei have\nbeen further addressed by implementing variants based on the concept of\nspontaneous symmetry breaking (and restoration).\nPurpose: In order to access the spectroscopy of open-shell nuclei more\nsystematically while controlling the numerical cost, we design a novel\nmany-body method that combines the merit of breaking and restoring symmetries\nwith those brought about by low-rank individual excitations.\nMethods: The recently proposed truncated configuration-interaction method\nbased on optimized symmetry-broken and -restored states is extended to the\nz-signature symmetry associated with a discrete subgroup of SU(2). The\nhighly-truncated N-body Hilbert subspace within which the Hamiltonian is\ndiagonalized is spanned by a z-signature broken and restored Slater determinant\nvacuum and associated low-rank excitations.\nResults: The proposed method provides an excellent reproduction of the\nground-state energy and of low-lying excitation energies of various\nz-signatures and total angular momenta. In doing so, the successive benefits of\n(i) breaking the symmetry, (ii) restoring the symmetry, (iii) including\nlow-rank particle-hole excitations and (iv) optimizing the amount by which the\nunderlying vacuum breaks the symmetry are illustrated.\nConclusions: The numerical cost of the newly designed variational method is\npolynomial with respect to the system size. The present study confirms the\nresults obtained previously for the attractive pairing Hamiltonian in\nconnection with the breaking and restoration of U(1) global gauge symmetry.\nThese two studies constitute a strong motivation to apply this method to\nrealistic nuclear Hamiltonians.\n",
"title": "Combining symmetry breaking and restoration with configuration interaction: extension to z-signature symmetry in the case of the Lipkin Model"
}
| null | null | null | null | true | null |
13264
| null |
Default
| null | null |
null |
{
"abstract": " In this paper, the existence, the uniqueness and estimates of solution to the\nintegral Cauchy problem for linear and nonlinear abstract wave equations are\nproved. The equation includes a linear operator A defined in a Banach space E,\nin which by choosing E and A we can obtain numerous classis of nonlocal initial\nvalue problems for wave equations which occur in a wide variety of physical\nsystems.\n",
"title": "Nonlocal Cauchy problems for wave equations and applications"
}
| null | null |
[
"Mathematics"
] | null | true | null |
13265
| null |
Validated
| null | null |
null |
{
"abstract": " We propose a gradient-based method for quadratic programming problems with a\nsingle linear constraint and bounds on the variables. Inspired by the GPCG\nalgorithm for bound-constrained convex quadratic programming [J.J. Moré and\nG. Toraldo, SIAM J. Optim. 1, 1991], our approach alternates between two phases\nuntil convergence: an identification phase, which performs gradient projection\niterations until either a candidate active set is identified or no reasonable\nprogress is made, and an unconstrained minimization phase, which reduces the\nobjective function in a suitable space defined by the identification phase, by\napplying either the conjugate gradient method or a recently proposed spectral\ngradient method. However, the algorithm differs from GPCG not only because it\ndeals with a more general class of problems, but mainly for the way it stops\nthe minimization phase. This is based on a comparison between a measure of\noptimality in the reduced space and a measure of bindingness of the variables\nthat are on the bounds, defined by extending the concept of proportioning,\nwhich was proposed by some authors for box-constrained problems. If the\nobjective function is bounded, the algorithm converges to a stationary point\nthanks to a suitable application of the gradient projection method in the\nidentification phase. For strictly convex problems, the algorithm converges to\nthe optimal solution in a finite number of steps even in case of degeneracy.\nExtensive numerical experiments show the effectiveness of the proposed\napproach.\n",
"title": "A two-phase gradient method for quadratic programming problems with a single linear constraint and bounds on the variables"
}
| null | null |
[
"Mathematics"
] | null | true | null |
13266
| null |
Validated
| null | null |
null |
{
"abstract": " Let $A$ be an abelian variety defined over a global function field $F$ of\npositive characteristic $p$ and let $K/F$ be a $p$-adic Lie extension with\nGalois group $G$. We provide a formula for the Euler characteristic\n$\\chi(G,Sel_A(K)_p)$ of the $p$-part of the Selmer group of $A$ over $K$. In\nthe special case $G=\\mathbb{Z}_p^d$ and $A$ a constant ordinary variety, using\nAkashi series, we show how the Euler characteristic of the dual of $Sel_A(K)_p$\nis related to special values of a $p$-adic $\\mathcal{L}$-function.\n",
"title": "Euler characteristic and Akashi series for Selmer groups over global function fields"
}
| null | null |
[
"Mathematics"
] | null | true | null |
13267
| null |
Validated
| null | null |
null |
{
"abstract": " We study Swendsen--Wang dynamics for the critical $q$-state Potts model on\nthe square lattice. For $q=2,3,4$, where the phase transition is continuous,\nthe mixing time $t_{\\textrm{mix}}$ is expected to obey a universal power-law\nindependent of the boundary conditions. On the other hand, for large $q$, where\nthe phase transition is discontinuous, the authors recently showed that\n$t_{\\textrm{mix}}$ is highly sensitive to boundary conditions:\n$t_{\\textrm{mix}} \\geq \\exp(cn)$ on an $n\\times n$ box with periodic boundary,\nyet under free or monochromatic boundary conditions, $t_{\\textrm{mix}}\n\\leq\\exp(n^{o(1)})$.\nIn this work we classify this effect under boundary conditions that\ninterpolate between these two (torus vs. free/monochromatic). Specifically, if\none of the $q$ colors is red, mixed boundary conditions such as\nred-free-red-free on the 4 sides of the box induce $t_{\\textrm{mix}} \\geq\n\\exp(cn)$, yet Dobrushin boundary conditions such as red-red-free-free, as well\nas red-periodic-red-periodic, induce sub-exponential mixing.\n",
"title": "The effect of boundary conditions on mixing of 2D Potts models at discontinuous phase transitions"
}
| null | null | null | null | true | null |
13268
| null |
Default
| null | null |
null |
{
"abstract": " The question of the number of thermodynamic states present in the\nlow-temperature phase of the three-dimensional Edwards-Anderson Ising spin\nglass is addressed by studying spin and link overlap distributions using\npopulation annealing Monte Carlo simulations. We consider overlaps between\nsystems with the same boundary condition-which are the usual quantities\nmeasured-and also overlaps between systems with different boundary conditions,\nboth for the full systems and also within a smaller window within the system.\nOur results appear to be fully compatible with a single pair of pure states\nsuch as in the droplet/scaling picture. However, our results for whether or not\ndomain walls induced by changing boundary conditions are space filling or not\nare also compatible with scenarios having many thermodynamic states, such as\nthe chaotic pairs picture and the replica symmetry breaking picture. The\ndiffering results for spin overlaps in same and different boundary conditions\nsuggest that finite-size effects are very large for the system sizes currently\naccessible in low-temperature simulations.\n",
"title": "Number of thermodynamic states in the three-dimensional Edwards-Anderson spin glass"
}
| null | null | null | null | true | null |
13269
| null |
Default
| null | null |
null |
{
"abstract": " Auxetic materials are of great engineering interest not only because of their\nfascinating negative Poisson's ratio, but also due to their increased toughness\nand indentation resistance. These materials are typically synthesized polyester\nfoams with a very heterogeneous structure, but the role of disorder in auxetic\nbehavior is not fully understood. Here, we provide a systematic theoretical and\nexperimental investigation in to the effect of disorder on the mechanical\nproperties of a paradigmatic auxetic lattice with a re-entrant hexagonal\ngeometry. We show that disorder has a marginal effect on the Poisson's ratio\nunless the lattice topology is altered, and in all cases examined the disorder\npreserves the auxetic characteristics. Depending on the direction of loading\napplied to these disordered auxetic lattices, either brittle or ductile failure\nis observed. It is found that brittle failure is associated with a\ndisorder-dependent tensile strength, whereas in ductile failure disorder does\nnot affect strength. Our work thus provides general guidelines to optimize\nelasticity and strength of disordered auxetic metamaterials.\n",
"title": "Mechanics of disordered auxetic metamaterials"
}
| null | null |
[
"Physics"
] | null | true | null |
13270
| null |
Validated
| null | null |
null |
{
"abstract": " Through experiments and numerical simulations we explore the behavior of rf\nSQUID (radio frequency superconducting quantum interference device)\nmetamaterials, which show extreme tunability and nonlinearity. The emergent\nelectromagnetic properties of this metamaterial are sensitive to the degree of\ncoherent response of the driven interacting SQUIDs. Coherence suffers in the\npresence of disorder, which is experimentally found to be mainly due to a dc\nflux gradient. We demonstrate methods to recover the coherence, specifically by\nvarying the coupling between the SQUID meta-atoms and increasing the\ntemperature or the amplitude of the applied rf flux.\n",
"title": "Coherent Oscillations of Driven rf SQUID Metamaterials"
}
| null | null | null | null | true | null |
13271
| null |
Default
| null | null |
null |
{
"abstract": " We construct a cosection localized virtual structure sheaf when a\nDeligne-Mumford stack is equipped with a perfect obstruction theory and a\ncosection of the obstruction sheaf.\n",
"title": "Localizing virtual structure sheaves by cosections"
}
| null | null | null | null | true | null |
13272
| null |
Default
| null | null |
null |
{
"abstract": " The Column Subset Selection Problem provides a natural framework for\nunsupervised feature selection. Despite being a hard combinatorial optimization\nproblem, there exist efficient algorithms that provide good approximations. The\ndrawback of the problem formulation is that it incorporates no form of\nregularization, and is therefore very sensitive to noise when presented with\nscarce data. In this paper we propose a regularized formulation of this\nproblem, and derive a correct greedy algorithm that is similar in efficiency to\nexisting greedy methods for the unregularized problem. We study its adequacy\nfor feature selection and propose suitable formulations. Additionally, we\nderive a lower bound for the error of the proposed problems. Through various\nnumerical experiments on real and synthetic data, we demonstrate the\nsignificantly increased robustness and stability of our method, as well as the\nimproved conditioning of its output, all while remaining efficient for\npractical use.\n",
"title": "Regularized Greedy Column Subset Selection"
}
| null | null | null | null | true | null |
13273
| null |
Default
| null | null |
null |
{
"abstract": " In this paper we introduce an algorithm to determine the equivalence of five\ndimensional spacetimes, which generalizes the Karlhede algorithm for four\ndimensional general relativity. As an alternative to the Petrov type\nclassification, we employ the alignment classification to algebraically\nclassify the Weyl tensor. To illustrate the algorithm we discuss three\nexamples: the singly rotating Myers-Perry solution, the Kerr (anti) de Sitter\nsolution, and the rotating black ring solution. We briefly discuss some\napplications of the Cartan algorithm in five dimensions.\n",
"title": "The Cartan Algorithm in Five Dimensions"
}
| null | null | null | null | true | null |
13274
| null |
Default
| null | null |
null |
{
"abstract": " We study a model introduced by Perthame and Vauchelet that describes the\ngrowth of a tumor governed by Brinkman's Law, which takes into account friction\nbetween the tumor cells. We adopt the viscosity solution approach to establish\nan optimal uniform convergence result of the tumor density as well as the\npressure in the incompressible limit. The system lacks standard maximum\nprinciple, and thus modification of the usual approach is necessary.\n",
"title": "Uniform convergence for the incompressible limit of a tumor growth model"
}
| null | null |
[
"Mathematics"
] | null | true | null |
13275
| null |
Validated
| null | null |
null |
{
"abstract": " The solution space of many classical optimization problems breaks up into\nclusters which are extensively distant from one another in the Hamming metric.\nHere, we show that an analogous quantum clustering phenomenon takes place in\nthe ground state subspace of a certain quantum optimization problem. This\ninvolves extending the notion of clustering to Hilbert space, where the\nclassical Hamming distance is not immediately useful. Quantum clusters\ncorrespond to macroscopically distinct subspaces of the full quantum ground\nstate space which grow with the system size. We explicitly demonstrate that\nsuch clusters arise in the solution space of random quantum satisfiability\n(3-QSAT) at its satisfiability transition. We estimate both the number of these\nclusters and their internal entropy. The former are given by the number of\nhardcore dimer coverings of the core of the interaction graph, while the latter\nis related to the underconstrained degrees of freedom not touched by the\ndimers. We additionally provide new numerical evidence suggesting that the\n3-QSAT satisfiability transition may coincide with the product satisfiability\ntransition, which would imply the absence of an intermediate entangled\nsatisfiable phase.\n",
"title": "Clustering in Hilbert space of a quantum optimization problem"
}
| null | null | null | null | true | null |
13276
| null |
Default
| null | null |
null |
{
"abstract": " Echo chambers, i.e., situations where one is exposed only to opinions that\nagree with their own, are an increasing concern for the political discourse in\nmany democratic countries. This paper studies the phenomenon of political echo\nchambers on social media. We identify the two components in the phenomenon: the\nopinion that is shared ('echo'), and the place that allows its exposure\n('chamber' --- the social network), and examine closely at how these two\ncomponents interact. We define a production and consumption measure for\nsocial-media users, which captures the political leaning of the content shared\nand received by them. By comparing the two, we find that Twitter users are, to\na large degree, exposed to political opinions that agree with their own. We\nalso find that users who try to bridge the echo chambers, by sharing content\nwith diverse leaning, have to pay a 'price of bipartisanship' in terms of their\nnetwork centrality and content appreciation. In addition, we study the role of\n'gatekeepers', users who consume content with diverse leaning but produce\npartisan content (with a single-sided leaning), in the formation of echo\nchambers. Finally, we apply these findings to the task of predicting partisans\nand gatekeepers from social and content features. While partisan users turn out\nrelatively easy to identify, gatekeepers prove to be more challenging.\n",
"title": "Political Discourse on Social Media: Echo Chambers, Gatekeepers, and the Price of Bipartisanship"
}
| null | null | null | null | true | null |
13277
| null |
Default
| null | null |
null |
{
"abstract": " Applying a many mode Floquet formalism for magnetically trapped atoms\ninteracting with a polychromatic rf-field, we predict a large two photon\ntransition probability in the atomic system of cold $^{87}Rb$ atoms. The\nphysical origin of this enormous increase in the two photon transition\nprobability is due to the formation of avoided crossings between eigen-energy\nlevels originating from different Floquet sub-manifolds and redistribution of\npopulation in the resonant intermediate levels to give rise to the resonance\nenhancement effect. Other exquisite features of the studied atom-field\ncomposite system include the splitting of the generated avoided crossings at\nthe strong field strength limit and a periodic variation of the single and two\nphoton transition probabilities with the mode separation frequency of the\npolychromatic rf-field. This work can find applications to characterize\nproperties of cold atom clouds in the magnetic traps using rf-spectroscopy\ntechniques.\n",
"title": "Resonance enhancement of two photon absorption by magnetically trapped atoms in strong rf-fields"
}
| null | null | null | null | true | null |
13278
| null |
Default
| null | null |
null |
{
"abstract": " IC883 is a luminous infrared galaxy (LIRG) classified as a starburst-active\ngalactic nucleus (AGN) composite. In a previous study we detected a\nlow-luminosity AGN (LLAGN) radio candidate. Here we report on our radio\nfollow-up at three frequencies which provides direct and unequivocal evidence\nof the AGN activity in IC883. Our analysis of archival X-ray data, together\nwith the detection of a transient radio source with luminosity typical of\nbright supernovae, give further evidence of the ongoing star formation\nactivity, which dominates the energetics of the system. At sub-parsec scales,\nthe radio nucleus has a core-jet morphology with the jet being a newly ejected\ncomponent showing a subluminal proper motion of 0.6c-1c. The AGN contributes\nless than two per cent of the total IR luminosity of the system. The\ncorresponding Eddington factor is ~1E-3, suggesting this is a low-accretion\nrate engine, as often found in LLAGNs. However, its high bolometric luminosity\n(~10E44erg/s) agrees better with a normal AGN. This apparent discrepancy may\njust be an indication of the transition nature of the nucleus from a system\ndominated by star-formation, to an AGN-dominated system. The nucleus has a\nstrongly inverted spectrum and a turnover at ~4.4GHz, thus qualifying as a\ncandidate for the least luminous (L_5.0GHz ~ 6.3E28erg/s/Hz) and one of the\nyoungest (~3000yr) gigahertz-peaked spectrum (GPS) sources. If the GPS origin\nfor the IC883 nucleus is confirmed, then advanced mergers in the LIRG category\nare potentially key environments to unveil the evolution of GPS sources into\nmore powerful radio galaxies.\n",
"title": "Unveiling the AGN in IC 883: discovery of a parsec-scale radio jet"
}
| null | null | null | null | true | null |
13279
| null |
Default
| null | null |
null |
{
"abstract": " Random key graphs were introduced to study various properties of the\nEschenauer-Gligor key predistribution scheme for wireless sensor networks\n(WSNs). Recently this class of random graphs has received much attention in\ncontexts as diverse as recommender systems, social network modeling, and\nclustering and classification analysis. This paper is devoted to analyzing\nvarious properties of random key graphs. In particular, we establish a zero-one\nlaw for the the existence of triangles in random key graphs, and identify the\ncorresponding critical scaling. This zero-one law exhibits significant\ndifferences with the corresponding result in Erdos-Renyi (ER) graphs. We also\ncompute the clustering coefficient of random key graphs, and compare it to that\nof ER graphs in the many node regime when their expected average degrees are\nasymptotically equivalent. For the parameter range of practical relevance in\nboth wireless sensor network and social network applications, random key graphs\nare shown to be much more clustered than the corresponding ER graphs. We also\nexplore the suitability of random key graphs as small world models in the sense\nof Watts and Strogatz.\n",
"title": "Counting triangles, tunable clustering and the small-world property in random key graphs (Extended version)"
}
| null | null | null | null | true | null |
13280
| null |
Default
| null | null |
null |
{
"abstract": " We study convergence rates of variational posterior distributions for\nnonparametric and high-dimensional inference. We formulate general conditions\non prior, likelihood, and variational class that characterize the convergence\nrates. Under similar \"prior mass and testing\" conditions considered in the\nliterature, the rate is found to be the sum of two terms. The first term stands\nfor the convergence rate of the true posterior distribution, and the second\nterm is contributed by the variational approximation error. For a class of\npriors that admit the structure of a mixture of product measures, we propose a\nnovel prior mass condition, under which the variational approximation error of\nthe generalized mean-field class is dominated by convergence rate of the true\nposterior. We demonstrate the applicability of our general results for various\nmodels, prior distributions and variational classes by deriving convergence\nrates of the corresponding variational posteriors.\n",
"title": "Convergence Rates of Variational Posterior Distributions"
}
| null | null | null | null | true | null |
13281
| null |
Default
| null | null |
null |
{
"abstract": " Eclipsing binaries remain crucial objects for our understanding of the\nuniverse. In particular, those that are components of multiple systems can help\nus solve the problem of the formation of these systems. Analysis of the radial\nvelocities together with the light curve produced for the first time precise\nphysical parameters of the components of the multiple systems V773 Cas, QS Aql,\nand BR Ind. Their visual orbits were also analyzed, which resulted in slightly\nimproved orbital elements. What is typical for all these systems is that their\nmost dominant source is the third distant component. The system V773 Cas\nconsists of two similar G1-2V stars revolving in a circular orbit and a more\ndistant component of the A3V type. Additionally, the improved value of parallax\nwas calculated to be 17.6 mas. Analysis of QS Aql resulted in the following:\nthe inner eclipsing pair is composed of B6V and F1V stars, and the third\ncomponent is of about the B6 spectral type. The outer orbit has high\neccentricity of about 0.95, and observations near its upcoming periastron\npassage between the years 2038 and 2040 are of high importance. Also, the\nparallax of the system was derived to be about 2.89 mas, moving the star much\ncloser to the Sun than originally assumed. The system BR Ind was found to be a\nquadruple star consisting of two eclipsing K dwarfs orbiting each other with a\nperiod of 1.786 days; the distant component is a single-lined spectroscopic\nbinary with an orbital period of about 6 days. Both pairs are moving around\neach other on their 148 year orbit.\n",
"title": "V773 Cas, QS Aql, and BR Ind: Eclipsing Binaries as Parts of Multiple Systems"
}
| null | null |
[
"Physics"
] | null | true | null |
13282
| null |
Validated
| null | null |
null |
{
"abstract": " A delayed-acceptance version of a Metropolis--Hastings algorithm can be\nuseful for Bayesian inference when it is computationally expensive to calculate\nthe true posterior, but a computationally cheap approximation is available; the\ndelayed-acceptance kernel targets the same posterior as its parent\nMetropolis-Hastings kernel. Although the asymptotic variance of any functional\nof the chain cannot be less than that obtained using its parent, the average\ncomputational time per iteration can be much smaller and so for a given\ncomputational budget the delayed-acceptance kernel can be more efficient.\nWhen the asymptotic variance of all $L^2$ functionals of the chain is finite,\nthe kernel is said to be variance bounding. It has recently been noted that a\ndelayed-acceptance kernel need not be variance bounding even when its parent\nis. We provide sufficient conditions for inheritance: for global algorithms,\nsuch as the independence sampler, the error in the approximation should be\nbounded; for local algorithms, two alternative sets of conditions are provided.\nAs a by-product of our initial, general result we also supply sufficient\nconditions on any pair of proposals such that, for any shared target\ndistribution, if a Metropolis-Hastings kernel using one of the proposals is\nvariance bounding then so is the Metropolis-Hastings kernel using the other\nproposal.\n",
"title": "Variance bounding of delayed-acceptance kernels"
}
| null | null | null | null | true | null |
13283
| null |
Default
| null | null |
null |
{
"abstract": " For a $C^*$-algebra $A$ and a set $X$ we give a Stinespring-type\ncharacterisation of the completely positive Schur $A$-multipliers on\n$K(\\ell^2(X))\\otimes A$. We then relate them to completely positive Herz-Schur\nmultipliers on $C^*$-algebraic crossed products of the form\n$A\\rtimes_{\\alpha,r} G$, with $G$ a discrete group, whose various versions were\nconsidered earlier by Anantharaman-Delaroche, Bédos and Conti, and Dong and\nRuan. The latter maps are shown to implement approximation properties, such as\nnuclearity or the Haagerup property, for $A\\rtimes_{\\alpha,r} G$.\n",
"title": "Positive Herz-Schur multipliers and approximation properties of crossed products"
}
| null | null | null | null | true | null |
13284
| null |
Default
| null | null |
null |
{
"abstract": " This paper presents a bias-variance tradeoff of graph Laplacian regularizer,\nwhich is widely used in graph signal processing and semi-supervised learning\ntasks. The scaling law of the optimal regularization parameter is specified in\nterms of the spectral graph properties and a novel signal-to-noise ratio\nparameter, which suggests selecting a mediocre regularization parameter is\noften suboptimal. The analysis is applied to three applications, including\nrandom, band-limited, and multiple-sampled graph signals. Experiments on\nsynthetic and real-world graphs demonstrate near-optimal performance of the\nestablished analysis.\n",
"title": "Bias-Variance Tradeoff of Graph Laplacian Regularizer"
}
| null | null |
[
"Computer Science",
"Statistics"
] | null | true | null |
13285
| null |
Validated
| null | null |
null |
{
"abstract": " We propose in this paper a novel approach to tackle the problem of mode\ncollapse encountered in generative adversarial network (GAN). Our idea is\nintuitive but proven to be very effective, especially in addressing some key\nlimitations of GAN. In essence, it combines the Kullback-Leibler (KL) and\nreverse KL divergences into a unified objective function, thus it exploits the\ncomplementary statistical properties from these divergences to effectively\ndiversify the estimated density in capturing multi-modes. We term our method\ndual discriminator generative adversarial nets (D2GAN) which, unlike GAN, has\ntwo discriminators; and together with a generator, it also has the analogy of a\nminimax game, wherein a discriminator rewards high scores for samples from data\ndistribution whilst another discriminator, conversely, favoring data from the\ngenerator, and the generator produces data to fool both two discriminators. We\ndevelop theoretical analysis to show that, given the maximal discriminators,\noptimizing the generator of D2GAN reduces to minimizing both KL and reverse KL\ndivergences between data distribution and the distribution induced from the\ndata generated by the generator, hence effectively avoiding the mode collapsing\nproblem. We conduct extensive experiments on synthetic and real-world\nlarge-scale datasets (MNIST, CIFAR-10, STL-10, ImageNet), where we have made\nour best effort to compare our D2GAN with the latest state-of-the-art GAN's\nvariants in comprehensive qualitative and quantitative evaluations. The\nexperimental results demonstrate the competitive and superior performance of\nour approach in generating good quality and diverse samples over baselines, and\nthe capability of our method to scale up to ImageNet database.\n",
"title": "Dual Discriminator Generative Adversarial Nets"
}
| null | null | null | null | true | null |
13286
| null |
Default
| null | null |
null |
{
"abstract": " The community detection problem for graphs asks one to partition the n\nvertices V of a graph G into k communities, or clusters, such that there are\nmany intracluster edges and few intercluster edges. Of course this is\nequivalent to finding a permutation matrix P such that, if A denotes the\nadjacency matrix of G, then PAP^T is approximately block diagonal. As there are\nk^n possible partitions of n vertices into k subsets, directly determining the\noptimal clustering is clearly infeasible. Instead one seeks to solve a more\ntractable approximation to the clustering problem. In this paper we reformulate\nthe community detection problem via sparse solution of a linear system\nassociated with the Laplacian of a graph G and then develop a two-stage\napproach based on a thresholding technique and a compressive sensing algorithm\nto find a sparse solution which corresponds to the community containing a\nvertex of interest in G. Crucially, our approach results in an algorithm which\nis able to find a single cluster of size n_0 in O(nlog(n)n_0) operations and\nall k clusters in fewer than O(n^2ln(n)) operations. This is a marked\nimprovement over the classic spectral clustering algorithm, which is unable to\nfind a single cluster at a time and takes approximately O(n^3) operations to\nfind all k clusters. Moreover, we are able to provide robust guarantees of\nsuccess for the case where G is drawn at random from the Stochastic Block\nModel, a popular model for graphs with clusters. Extensive numerical results\nare also provided, showing the efficacy of our algorithm on both synthetic and\nreal-world data sets.\n",
"title": "A Compressive Sensing Approach to Community Detection with Applications"
}
| null | null | null | null | true | null |
13287
| null |
Default
| null | null |
null |
{
"abstract": " Uncertainty quantification is a critical missing component in radio\ninterferometric imaging that will only become increasingly important as the\nbig-data era of radio interferometry emerges. Since radio interferometric\nimaging requires solving a high-dimensional, ill-posed inverse problem,\nuncertainty quantification is difficult but also critical to the accurate\nscientific interpretation of radio observations. Statistical sampling\napproaches to perform Bayesian inference, like Markov Chain Monte Carlo (MCMC)\nsampling, can in principle recover the full posterior distribution of the\nimage, from which uncertainties can then be quantified. However, traditional\nhigh-dimensional sampling methods are generally limited to smooth (e.g.\nGaussian) priors and cannot be used with sparsity-promoting priors. Sparse\npriors, motivated by the theory of compressive sensing, have been shown to be\nhighly effective for radio interferometric imaging. In this article proximal\nMCMC methods are developed for radio interferometric imaging, leveraging\nproximal calculus to support non-differential priors, such as sparse priors, in\na Bayesian framework. Furthermore, three strategies to quantify uncertainties\nusing the recovered posterior distribution are developed: (i) local\n(pixel-wise) credible intervals to provide error bars for each individual\npixel; (ii) highest posterior density credible regions; and (iii) hypothesis\ntesting of image structure. These forms of uncertainty quantification provide\nrich information for analysing radio interferometric observations in a\nstatistically robust manner.\n",
"title": "Uncertainty quantification for radio interferometric imaging: I. proximal MCMC methods"
}
| null | null | null | null | true | null |
13288
| null |
Default
| null | null |
null |
{
"abstract": " Complex statistical machine learning models are increasingly being used or\nconsidered for use in high-stakes decision-making pipelines in domains such as\nfinancial services, health care, criminal justice and human services. These\nmodels are often investigated as possible improvements over more classical\ntools such as regression models or human judgement. While the modeling approach\nmay be new, the practice of using some form of risk assessment to inform\ndecisions is not. When determining whether a new model should be adopted, it is\ntherefore essential to be able to compare the proposed model to the existing\napproach across a range of task-relevant accuracy and fairness metrics. Looking\nat overall performance metrics, however, may be misleading. Even when two\nmodels have comparable overall performance, they may nevertheless disagree in\ntheir classifications on a considerable fraction of cases. In this paper we\nintroduce a model comparison framework for automatically identifying subgroups\nin which the differences between models are most pronounced. Our primary focus\nis on identifying subgroups where the models differ in terms of\nfairness-related quantities such as racial or gender disparities. We present\nexperimental results from a recidivism prediction task and a hypothetical\nlending example.\n",
"title": "Fairer and more accurate, but for whom?"
}
| null | null |
[
"Computer Science",
"Statistics"
] | null | true | null |
13289
| null |
Validated
| null | null |
null |
{
"abstract": " This article is motivated by soccer positional passing networks collected\nacross multiple games. We refer to these data as replicated spatial passing\nnetworks---to accurately model such data it is necessary to take into account\nthe spatial positions of the passer and receiver for each passing event. This\nspatial registration and replicates that occur across games represent key\ndifferences with usual social network data. As a key step before investigating\nhow the passing dynamics influence team performance, we focus on developing\nmethods for summarizing different team's passing strategies. Our proposed\napproach relies on a novel multiresolution data representation framework and\nPoisson nonnegative block term decomposition model, which automatically\nproduces coarse-to-fine low-rank network motifs. The proposed methods are\napplied to detailed passing record data collected from the 2014 FIFA World Cup.\n",
"title": "Multiresolution Tensor Decomposition for Multiple Spatial Passing Networks"
}
| null | null | null | null | true | null |
13290
| null |
Default
| null | null |
null |
{
"abstract": " We study the problem of initiation of excitation waves in the FitzHugh-Nagumo\nmodel. Our approach follows earlier works and is based on the idea of\napproximating the boundary between basins of attraction of propagating waves\nand of the resting state as the stable manifold of a critical solution. Here,\nwe obtain analytical expressions for the essential ingredients of the theory by\nsingular perturbation using two small parameters, the separation of time scales\nof the activator and inhibitor, and the threshold in the activator's kinetics.\nThis results in a closed analytical expression for the strength-duration curve.\n",
"title": "Fast-slow asymptotic for semi-analytical ignition criteria in FitzHugh-Nagumo system"
}
| null | null |
[
"Physics"
] | null | true | null |
13291
| null |
Validated
| null | null |
null |
{
"abstract": " We aim to use statistical analysis of a large number of various galaxies to\nprobe, model, and understand relations between different galaxy properties and\nmagnetic fields. We have compiled a sample of 55 galaxies including low-mass\ndwarf and Magellanic-types, normal spirals and several massive starbursts, and\napplied principal component analysis (PCA) and regression methods to assess the\nimpact of various galaxy properties on the observed magnetic fields. According\nto PCA the global galaxy parameters (like HI, H2, and dynamical mass, star\nformation rate (SFR), near-infrared luminosity, size, and rotational velocity)\nare all mutually correlated and can be reduced to a single principal component.\nFurther PCA performed for global and intensive (not size related) properties of\ngalaxies (such as gas density, and surface density of the star formation rate,\nSSFR), indicates that magnetic field strength B is connected mainly to the\nintensive parameters, while the global parameters have only weak relationships\nwith B. We find that the tightest relationship of B is with SSFR, which is\ndescribed by a power-law with an index of 0.33+-0.03. The observed weaker\nassociations of B with galaxy dynamical mass and the rotational velocity we\ninterpret as indirect ones, resulting from the observed connection of the\nglobal SFR with the available total H2 mass in galaxies. Using our sample we\nconstructed a diagram of B across the Hubble sequence which reveals that high\nvalues of B are not restricted by the Hubble type. However, weaker fields\nappear exclusively in later Hubble types and B as low as about 5muG is not seen\namong typical spirals. The processes of generation of magnetic field in the\ndwarf and Magellanic-type galaxies are similar to those in the massive spirals\nand starbursts and are mainly coupled to local star-formation activity\ninvolving the small-scale dynamo mechanism.\n",
"title": "What drives galactic magnetism?"
}
| null | null |
[
"Physics"
] | null | true | null |
13292
| null |
Validated
| null | null |
null |
{
"abstract": " The regular separability problem asks, for two given languages, if there\nexists a regular language including one of them but disjoint from the other.\nOur main result is decidability, and PSpace-completeness, of the regular\nseparability problem for languages of one counter automata without zero tests\n(also known as one counter nets). This contrasts with undecidability of the\nregularity problem for one counter nets, and with undecidability of the regular\nseparability problem for one counter automata, which is our second result.\n",
"title": "Regular Separability of One Counter Automata"
}
| null | null | null | null | true | null |
13293
| null |
Default
| null | null |
null |
{
"abstract": " Support vector data description (SVDD) is a machine learning technique that\nis used for single-class classification and outlier detection. The idea of SVDD\nis to find a set of support vectors that defines a boundary around data. When\ndealing with online or large data, existing batch SVDD methods have to be rerun\nin each iteration. We propose an incremental learning algorithm for SVDD that\nuses the Gaussian kernel. This algorithm builds on the observation that all\nsupport vectors on the boundary have the same distance to the center of sphere\nin a higher-dimensional feature space as mapped by the Gaussian kernel\nfunction. Each iteration involves only the existing support vectors and the new\ndata point. Moreover, the algorithm is based solely on matrix manipulations;\nthe support vectors and their corresponding Lagrange multiplier $\\alpha_i$'s\nare automatically selected and determined in each iteration. It can be seen\nthat the complexity of our algorithm in each iteration is only $O(k^2)$, where\n$k$ is the number of support vectors. Experimental results on some real data\nsets indicate that FISVDD demonstrates significant gains in efficiency with\nalmost no loss in either outlier detection accuracy or objective function\nvalue.\n",
"title": "Fast Incremental SVDD Learning Algorithm with the Gaussian Kernel"
}
| null | null |
[
"Statistics"
] | null | true | null |
13294
| null |
Validated
| null | null |
null |
{
"abstract": " When comparing two distributions, it is often helpful to learn at which\nquantiles or values there is a statistically significant difference. This\nprovides more information than the binary \"reject\" or \"do not reject\" decision\nof a global goodness-of-fit test. Framing our question as multiple testing\nacross the continuum of quantiles $\\tau\\in(0,1)$ or values $r\\in\\mathbb{R}$, we\nshow that the Kolmogorov--Smirnov test (interpreted as a multiple testing\nprocedure) achieves strong control of the familywise error rate. However, its\nwell-known flaw of low sensitivity in the tails remains. We provide an\nalternative method that retains such strong control of familywise error rate\nwhile also having even sensitivity, i.e., equal pointwise type I error rates at\neach of $n\\to\\infty$ order statistics across the distribution. Our one-sample\nmethod computes instantly, using our new formula that also instantly computes\ngoodness-of-fit $p$-values and uniform confidence bands. To improve power, we\nalso propose stepdown and pre-test procedures that maintain control of the\nasymptotic familywise error rate. One-sample and two-sample cases are\nconsidered, as well as extensions to regression discontinuity designs and\nconditional distributions. Simulations, empirical examples, and code are\nprovided.\n",
"title": "Comparing distributions by multiple testing across quantiles or CDF values"
}
| null | null |
[
"Mathematics",
"Statistics"
] | null | true | null |
13295
| null |
Validated
| null | null |
null |
{
"abstract": " We investigate the effect of the Dzyaloshinskii Moriya interaction (DMI) on\nmagnetic domain nucleation in a ferromagnetic thin film with perpendicular\nmagnetic anisotropy. We propose an extended droplet model to determine the\nnucleation field as a function of the in-plane field. The model can explain the\nexperimentally observed nucleation in a CoNi microstrip with the interfacial\nDMI. The results are also reproduced by micromagnetic simulation based on the\nstring model. The electrical measurement method proposed in this study can be\nwidely used to quantitatively determine the DMI energy density.\n",
"title": "Magnetic droplet nucleation with homochiral Neel domain wall"
}
| null | null | null | null | true | null |
13296
| null |
Default
| null | null |
null |
{
"abstract": " Random forests perform bootstrap-aggregation by sampling the training samples\nwith replacement. This enables the evaluation of out-of-bag error which serves\nas a internal cross-validation mechanism. Our motivation lies in using the\nunsampled training samples to improve each decision tree in the ensemble. We\nstudy the effect of using the out-of-bag samples to improve the generalization\nerror first of the decision trees and second the random forest by post-pruning.\nA preliminary empirical study on four UCI repository datasets show consistent\ndecrease in the size of the forests without considerable loss in accuracy.\n",
"title": "Cost-complexity pruning of random forests"
}
| null | null | null | null | true | null |
13297
| null |
Default
| null | null |
null |
{
"abstract": " Aims: Recent observations have challenged our understanding of rotational\nmixing in massive stars by revealing a population of fast-rotating objects with\napparently normal surface nitrogen abundances. However, several questions have\narisen because of a number of issues, which have rendered a reinvestigation\nnecessary; these issues include the presence of numerous upper limits for the\nnitrogen abundance, unknown multiplicity status, and a mix of stars with\ndifferent physical properties, such as their mass and evolutionary state, which\nare known to control the amount of rotational mixing. Methods: We have\ncarefully selected a large sample of bright, fast-rotating early-type stars of\nour Galaxy (40 objects with spectral types between B0.5 and O4). Their\nhigh-quality, high-resolution optical spectra were then analysed with the\nstellar atmosphere modelling codes DETAIL/SURFACE or CMFGEN, depending on the\ntemperature of the target. Several internal and external checks were performed\nto validate our methods; notably, we compared our results with literature data\nfor some well-known objects, studied the effect of gravity darkening, or\nconfronted the results provided by the two codes for stars amenable to both\nanalyses. Furthermore, we studied the radial velocities of the stars to assess\ntheir binarity. Results: This first part of our study presents our methods and\nprovides the derived stellar parameters, He, CNO abundances, and the\nmultiplicity status of every star of the sample. It is the first time that He\nand CNO abundances of such a large number of Galactic massive fast rotators are\ndetermined in a homogeneous way.\n",
"title": "Chemical abundances of fast-rotating massive stars. I. Description of the methods and individual results"
}
| null | null |
[
"Physics"
] | null | true | null |
13298
| null |
Validated
| null | null |
null |
{
"abstract": " Recent experiments suggest that the interplay between cells and the mechanics\nof their substrate gives rise to a diversity of morphological and migrational\nbehaviors. Here, we develop a Cellular Potts Model of polarizing cells on a\nvisco-elastic substrate. We compare our model with experiments on endothelial\ncells plated on polyacrylamide hydrogels to constrain model parameters and test\npredictions. Our analysis reveals that morphology and migratory behavior are\ndetermined by an intricate interplay between cellular polarization and\nsubstrate strain gradients generated by traction forces exerted by cells\n(self-haptotaxis).\n",
"title": "Morphology and Motility of Cells on Soft Substrates"
}
| null | null | null | null | true | null |
13299
| null |
Default
| null | null |
null |
{
"abstract": " We introduce PVSC-DTM (Parallel Vectorized Stencil Code for Dirac and\nTopological Materials), a library and code generator based on a domain-specific\nlanguage tailored to implement the specific stencil-like algorithms that can\ndescribe Dirac and topological materials such as graphene and topological\ninsulators in a matrix-free way. The generated hybrid-parallel (MPI+OpenMP)\ncode is fully vectorized using Single Instruction Multiple Data (SIMD)\nextensions. It is significantly faster than matrix-based approaches on the node\nlevel and performs in accordance with the roofline model. We demonstrate the\nchip-level performance and distributed-memory scalability of basic building\nblocks such as sparse matrix-(multiple-) vector multiplication on modern\nmulticore CPUs. As an application example, we use the PVSC-DTM scheme to (i)\nexplore the scattering of a Dirac wave on an array of gate-defined quantum\ndots, to (ii) calculate a bunch of interior eigenvalues for strong topological\ninsulators, and to (iii) discuss the photoemission spectra of a disordered Weyl\nsemimetal.\n",
"title": "A domain-specific language and matrix-free stencil code for investigating electronic properties of Dirac and topological materials"
}
| null | null |
[
"Computer Science",
"Physics"
] | null | true | null |
13300
| null |
Validated
| null | null |
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