text
null | inputs
dict | prediction
null | prediction_agent
null | annotation
list | annotation_agent
null | multi_label
bool 1
class | explanation
null | id
stringlengths 1
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{
"abstract": " In this paper, a theory of quandle rings is proposed for quandles analogous\nto the classical theory of group rings for groups, and interconnections between\nquandles and associated quandle rings are explored.\n",
"title": "Quandle rings"
}
| null | null | null | null | true | null |
3401
| null |
Default
| null | null |
null |
{
"abstract": " The polynomial eigenvalue problem arises in many applications and has\nreceived a great deal of attention over the last decade. The use of\nroot-finding methods to solve the polynomial eigenvalue problem dates back to\nthe work of Kublanovskaya (1969, 1970) and has received a resurgence due to the\nwork of Bini and Noferini (2013). In this paper, we present a method which uses\nLaguerre iteration for computing the eigenvalues of a matrix polynomial. An\neffective method based on the numerical range is presented for computing\ninitial estimates to the eigenvalues of a matrix polynomial. A detailed\nexplanation of the stopping criteria is given, and it is shown that under\nsuitable conditions we can guarantee the backward stability of the eigenvalues\ncomputed by our method. Then, robust methods are provided for computing both\nthe right and left eigenvectors and the condition number of each eigenpair.\nApplications for Hessenberg and tridiagonal matrix polynomials are given and we\nshow that both structures benefit from substantial computational savings.\nFinally, we present several numerical experiments to verify the accuracy of our\nmethod and its competitiveness for solving the roots of a polynomial and the\ntridiagonal eigenvalue problem.\n",
"title": "On the application of Laguerre's method to the polynomial eigenvalue problem"
}
| null | null | null | null | true | null |
3402
| null |
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| null | null |
null |
{
"abstract": " In this paper we study the Teichmüller harmonic map flow as introduced by\nRupflin and Topping [15]. It evolves pairs of maps and metrics $(u,g)$ into\nbranched minimal immersions, or equivalently into weakly conformal harmonic\nmaps, where $u$ maps from a fixed closed surface $M$ with metric $g$ to a\ngeneral target manifold $N$. It arises naturally as a gradient flow for the\nDirichlet energy functional viewed as acting on equivalence classes of such\npairs, obtained from the invariance under diffeomorphisms and conformal changes\nof the domain metric.\nIn the construction of a suitable inner product for the gradient flow a\nchoice of relative weight of the map tangent directions and metric tangent\ndirections is made, which manifests itself in the appearance of a coupling\nconstant $\\eta$ in the flow equations.\nWe study limits of the flow as $\\eta$ approaches 0, corresponding to slowing\ndown the evolution of the metric.\nWe first show that given a smooth harmonic map flow on a fixed time interval,\nthe Teichmüller harmonic map flows starting at the same initial data converge\nuniformly to the underlying harmonic map flow when $\\eta \\downarrow 0$.\nNext we consider a rescaling of time, which increases the speed of the map\nevolution while evolving the metric at a constant rate. We show that under\nappropriate topological assumptions, in the limit the rescaled flows converge\nto a unique flow through harmonic maps with the metric evolving in the\ndirection of the real part of the Hopf differential.\n",
"title": "Limiting Behaviour of the Teichmüller Harmonic Map Flow"
}
| null | null | null | null | true | null |
3403
| null |
Default
| null | null |
null |
{
"abstract": " In this note, we give a nature action of the modular group on the ends of the\ninfinite (p + 1)-cayley tree, for each prime p. We show that there is a unique\ninvariant probability measure for each p.\n",
"title": "Invariant measures for the actions of the modular group"
}
| null | null | null | null | true | null |
3404
| null |
Default
| null | null |
null |
{
"abstract": " In higher category theory, we use fibrations to model presheaves. In this\npaper we introduce a new method to build such fibrations. Concretely, for\nsuitable reflective subcategories of simplicial spaces, we build fibrations\nthat model presheaves valued in that subcategory. Using this we can build\nCartesian fibrations, but we can also model presheaves valued in Segal spaces.\nAdditionally, using this new approach, we define representable Cartesian\nfibrations, generalizing representable presheaves valued in spaces, and show\nthey have similar properties.\n",
"title": "Cartesian Fibrations and Representability"
}
| null | null |
[
"Mathematics"
] | null | true | null |
3405
| null |
Validated
| null | null |
null |
{
"abstract": " We have examined the effects of embedded pitch adapters on signal formation\nin n-substrate silicon microstrip sensors with data from beam tests and\nsimulation. According to simulation, the presence of the pitch adapter metal\nlayer changes the electric field inside the sensor, resulting in slowed signal\nformation on the nearby strips and a pick-up effect on the pitch adapter. This\ncan result in an inefficiency to detect particles passing through the pitch\nadapter region. All these effects have been observed in the beam test data.\n",
"title": "Signal coupling to embedded pitch adapters in silicon sensors"
}
| null | null | null | null | true | null |
3406
| null |
Default
| null | null |
null |
{
"abstract": " Star clusters interact with the interstellar medium (ISM) in various ways,\nmost importantly in the destruction of molecular star-forming clouds, resulting\nin inefficient star formation on galactic scales. On cloud scales, ionizing\nradiation creates \\hii regions, while stellar winds and supernovae drive the\nISM into thin shells. These shells are accelerated by the combined effect of\nwinds, radiation pressure and supernova explosions, and slowed down by gravity.\nSince radiative and mechanical feedback is highly interconnected, they must be\ntaken into account in a self-consistent and combined manner, including the\ncoupling of radiation and matter. We present a new semi-analytic\none-dimensional feedback model for isolated massive clouds ($\\geq\n10^5\\,M_{\\odot}$) to calculate shell dynamics and shell structure\nsimultaneously. It allows us to scan a large range of physical parameters (gas\ndensity, star formation efficiency, metallicity) and to estimate escape\nfractions of ionizing radiation $f_{\\rm{esc,i}}$, the minimum star formation\nefficiency $\\epsilon_{\\rm{min}}$ required to drive an outflow, and recollapse\ntime scales for clouds that are not destroyed by feedback. Our results show\nthat there is no simple answer to the question of what dominates cloud\ndynamics, and that each feedback process significantly influences the\nefficiency of the others. We find that variations in natal cloud density can\nvery easily explain differences between dense-bound and diffuse-open star\nclusters. We also predict, as a consequence of feedback, a $4-6$ Myr age\ndifference for massive clusters with multiple generations.\n",
"title": "Winds and radiation in unison: a new semi-analytic feedback model for cloud dissolution"
}
| null | null | null | null | true | null |
3407
| null |
Default
| null | null |
null |
{
"abstract": " We present a new method, called Analysis-of-marginal-Tail-Means (ATM), for\neffective robust optimization of discrete black-box problems. ATM has important\napplications to many real-world engineering problems (e.g., manufacturing\noptimization, product design, molecular engineering), where the objective to\noptimize is black-box and expensive, and the design space is inherently\ndiscrete. One weakness of existing methods is that they are not robust: these\nmethods perform well under certain assumptions, but yield poor results when\nsuch assumptions (which are difficult to verify in black-box problems) are\nviolated. ATM addresses this via the use of marginal tail means for\noptimization, which combines both rank-based and model-based methods. The\ntrade-off between rank- and model-based optimization is tuned by first\nidentifying important main effects and interactions, then finding a good\ncompromise which best exploits additive structure. By adaptively tuning this\ntrade-off from data, ATM provides improved robust optimization over existing\nmethods, particularly in problems with (i) a large number of factors, (ii)\nunordered factors, or (iii) experimental noise. We demonstrate the\neffectiveness of ATM in simulations and in two real-world engineering problems:\nthe first on robust parameter design of a circular piston, and the second on\nproduct family design of a thermistor network.\n",
"title": "Analysis-of-marginal-Tail-Means (ATM): a robust method for discrete black-box optimization"
}
| null | null | null | null | true | null |
3408
| null |
Default
| null | null |
null |
{
"abstract": " Shelf and coastal sea processes extend from the atmosphere through the water\ncolumn and into the sea bed. These processes are driven by physical, chemical,\nand biological interactions at local scales, and they are influenced by\ntransport and cross strong spatial gradients. The linkages between domains and\nmany different processes are not adequately described in current model systems.\nTheir limited integration level in part reflects lacking modularity and\nflexibility; this shortcoming hinders the exchange of data and model components\nand has historically imposed supremacy of specific physical driver models. We\nhere present the Modular System for Shelves and Coasts (MOSSCO,\nthis http URL), a novel domain and process coupling system\ntailored---but not limited--- to the coupling challenges of and applications in\nthe coastal ocean. MOSSCO builds on the existing coupling technology Earth\nSystem Modeling Framework and on the Framework for Aquatic Biogeochemical\nModels, thereby creating a unique level of modularity in both domain and\nprocess coupling; the new framework adds rich metadata, flexible scheduling,\nconfigurations that allow several tens of models to be coupled, and tested\nsetups for coastal coupled applications. That way, MOSSCO addresses the\ntechnology needs of a growing marine coastal Earth System community that\nencompasses very different disciplines, numerical tools, and research\nquestions.\n",
"title": "Modular System for Shelves and Coasts (MOSSCO v1.0) - a flexible and multi-component framework for coupled coastal ocean ecosystem modelling"
}
| null | null | null | null | true | null |
3409
| null |
Default
| null | null |
null |
{
"abstract": " The Giornata Sesta about the Force of Percussion is a relatively less known\nChapter from the Galileo's masterpiece \"Discourse about Two New Sciences\". It\nwas first published lately (1718), long after the first edition of the Two New\nSciences (1638) and Galileo's death (1642). The Giornata Sesta focuses on how\nto quantify the percussion force caused by a body in movement, and describes a\nvery interesting experiment known as \"the two-bucket experiment\". In this\npaper, we review this experiment reported by Galileo, develop a steady-state\ntheoretical model, and solve its transient form numerically; additionally, we\nreport the results from one real simplified analogous experiment. Finally, we\ndiscuss the conclusions drawn by Galileo -- correct, despite a probably\nunnoticeable imbalance --, showing that he did not report the thrust force\ncomponent in his setup -- which would be fundamental for the correct\ncalculation of the percussion force.\n",
"title": "How big was Galileo's impact? Percussion in the Sixth Day of the \"Two New Sciences\""
}
| null | null | null | null | true | null |
3410
| null |
Default
| null | null |
null |
{
"abstract": " A brief introduction to radar: principles, Doppler effect, antennas,\nwaveforms, power budget - and future radars. [13 pages]\n",
"title": "Radar, without tears"
}
| null | null | null | null | true | null |
3411
| null |
Default
| null | null |
null |
{
"abstract": " One of the challenges in computational acoustics is the identification of\nmodels that can simulate and predict the physical behavior of a system\ngenerating an acoustic signal. Whenever such models are used for commercial\napplications an additional constraint is the time-to-market, making automation\nof the sound design process desirable. In previous works, a computational sound\ndesign approach has been proposed for the parameter estimation problem\ninvolving timbre matching by deep learning, which was applied to the synthesis\nof pipe organ tones. In this work we refine previous results by introducing the\nformer approach in a multi-stage algorithm that also adds heuristics and a\nstochastic optimization method operating on objective cost functions based on\npsychoacoustics. The optimization method shows to be able to refine the first\nestimate given by the deep learning approach and substantially improve the\nobjective metrics, with the additional benefit of reducing the sound design\nprocess time. Subjective listening tests are also conducted to gather\nadditional insights on the results.\n",
"title": "A Multi-Stage Algorithm for Acoustic Physical Model Parameters Estimation"
}
| null | null | null | null | true | null |
3412
| null |
Default
| null | null |
null |
{
"abstract": " In this paper, we strengthen the splitting theorem proved in [14, 15] and\nprovide a different approach using ideas from the weak KAM theory.\n",
"title": "A Warped Product Splitting Theorem Through Weak KAM Theory"
}
| null | null | null | null | true | null |
3413
| null |
Default
| null | null |
null |
{
"abstract": " We present an approach for building an active agent that learns to segment\nits visual observations into individual objects by interacting with its\nenvironment in a completely self-supervised manner. The agent uses its current\nsegmentation model to infer pixels that constitute objects and refines the\nsegmentation model by interacting with these pixels. The model learned from\nover 50K interactions generalizes to novel objects and backgrounds. To deal\nwith noisy training signal for segmenting objects obtained by self-supervised\ninteractions, we propose robust set loss. A dataset of robot's interactions\nalong-with a few human labeled examples is provided as a benchmark for future\nresearch. We test the utility of the learned segmentation model by providing\nresults on a downstream vision-based control task of rearranging multiple\nobjects into target configurations from visual inputs alone. Videos, code, and\nrobotic interaction dataset are available at\nthis https URL\n",
"title": "Learning Instance Segmentation by Interaction"
}
| null | null | null | null | true | null |
3414
| null |
Default
| null | null |
null |
{
"abstract": " Significant parts of the recent learning literature on stochastic\noptimization algorithms focused on the theoretical and practical behaviour of\nstochastic first order schemes under different convexity properties. Due to its\nsimplicity, the traditional method of choice for most supervised machine\nlearning problems is the stochastic gradient descent (SGD) method. Many\niteration improvements and accelerations have been added to the pure SGD in\norder to boost its convergence in various (strong) convexity setting. However,\nthe Lipschitz gradient continuity or bounded gradients assumptions are an\nessential requirement for most existing stochastic first-order schemes. In this\npaper novel convergence results are presented for the stochastic proximal point\nalgorithm in different settings. In particular, without any strong convexity,\nsmoothness or bounded gradients assumptions, we show that a slightly modified\nquadratic growth assumption is sufficient to guarantee for the stochastic\nproximal point $\\mathcal{O}\\left(\\frac{1}{k}\\right)$ convergence rate, in terms\nof the distance to the optimal set. Furthermore, linear convergence is obtained\nfor interpolation setting, when the optimal set of expected cost is included in\nthe optimal sets of each functional component.\n",
"title": "On convergence rate of stochastic proximal point algorithm without strong convexity, smoothness or bounded gradients"
}
| null | null |
[
"Computer Science",
"Statistics"
] | null | true | null |
3415
| null |
Validated
| null | null |
null |
{
"abstract": " This paper introduces a novel approach to texture synthesis based on\ngenerative adversarial networks (GAN) (Goodfellow et al., 2014). We extend the\nstructure of the input noise distribution by constructing tensors with\ndifferent types of dimensions. We call this technique Periodic Spatial GAN\n(PSGAN). The PSGAN has several novel abilities which surpass the current state\nof the art in texture synthesis. First, we can learn multiple textures from\ndatasets of one or more complex large images. Second, we show that the image\ngeneration with PSGANs has properties of a texture manifold: we can smoothly\ninterpolate between samples in the structured noise space and generate novel\nsamples, which lie perceptually between the textures of the original dataset.\nIn addition, we can also accurately learn periodical textures. We make multiple\nexperiments which show that PSGANs can flexibly handle diverse texture and\nimage data sources. Our method is highly scalable and it can generate output\nimages of arbitrary large size.\n",
"title": "Learning Texture Manifolds with the Periodic Spatial GAN"
}
| null | null | null | null | true | null |
3416
| null |
Default
| null | null |
null |
{
"abstract": " Analyzing the behaviour of a concurrent program is made difficult by the\nnumber of possible executions. This problem can be alleviated by applying the\ntheory of Mazurkiewicz traces to focus only on the canonical representatives of\nthe equivalence classes of the possible executions of the program. This paper\npresents a generic framework that allows to specify the possible behaviours of\nthe execution environment, and generate all Foata-normal executions of a\nprogram, for that environment, by discarding abnormal executions during the\ngeneration phase. The key ingredient of Mazurkiewicz trace theory, the\ndependency relation, is used in the framework in two roles: first, as part of\nthe specification of which executions are allowed at all, and then as part of\nthe normality checking algorithm, which is used to discard the abnormal\nexecutions. The framework is instantiated to the relaxed memory models of the\nSPARC hierarchy.\n",
"title": "Generating Representative Executions [Extended Abstract]"
}
| null | null | null | null | true | null |
3417
| null |
Default
| null | null |
null |
{
"abstract": " Extended strongly periodic links have been introduced by Przytycki and\nSokolov as a symmetric surgery presentation of three-manifolds on which the\nfinite cyclic group acts without fixed points. The purpose of this paper is to\nprove that the symmetry of these links is reflected by the first coefficients\nof the HOMFLYPT polynomial.\n",
"title": "Extended periodic links and HOMFLYPT polynomial"
}
| null | null | null | null | true | null |
3418
| null |
Default
| null | null |
null |
{
"abstract": " Over the past decade, the idea of smart homes has been conceived as a\npotential solution to counter energy crises or to at least mitigate its\nintensive destructive consequences in the residential building sector.\n",
"title": "Exploring Cross-Domain Data Dependencies for Smart Homes to Improve Energy Efficiency"
}
| null | null | null | null | true | null |
3419
| null |
Default
| null | null |
null |
{
"abstract": " Deep learning models can take weeks to train on a single GPU-equipped\nmachine, necessitating scaling out DL training to a GPU-cluster. However,\ncurrent distributed DL implementations can scale poorly due to substantial\nparameter synchronization over the network, because the high throughput of GPUs\nallows more data batches to be processed per unit time than CPUs, leading to\nmore frequent network synchronization. We present Poseidon, an efficient\ncommunication architecture for distributed DL on GPUs. Poseidon exploits the\nlayered model structures in DL programs to overlap communication and\ncomputation, reducing bursty network communication. Moreover, Poseidon uses a\nhybrid communication scheme that optimizes the number of bytes required to\nsynchronize each layer, according to layer properties and the number of\nmachines. We show that Poseidon is applicable to different DL frameworks by\nplugging Poseidon into Caffe and TensorFlow. We show that Poseidon enables\nCaffe and TensorFlow to achieve 15.5x speed-up on 16 single-GPU machines, even\nwith limited bandwidth (10GbE) and the challenging VGG19-22K network for image\nclassification. Moreover, Poseidon-enabled TensorFlow achieves 31.5x speed-up\nwith 32 single-GPU machines on Inception-V3, a 50% improvement over the\nopen-source TensorFlow (20x speed-up).\n",
"title": "Poseidon: An Efficient Communication Architecture for Distributed Deep Learning on GPU Clusters"
}
| null | null | null | null | true | null |
3420
| null |
Default
| null | null |
null |
{
"abstract": " We deduce a simple closed formula for illiquid corporate coupon bond prices\nwhen liquid bonds with similar characteristics (e.g. maturity) are present in\nthe market for the same issuer. The key model parameter is the\ntime-to-liquidate a position, i.e. the time that an experienced bond trader\ntakes to liquidate a given position on a corporate coupon bond.\nThe option approach we propose for pricing bonds' illiquidity is reminiscent\nof the celebrated work of Longstaff (1995) on the non-marketability of some\nnon-dividend-paying shares in IPOs. This approach describes a quite common\nsituation in the fixed income market: it is rather usual to find issuers that,\nbesides liquid benchmark bonds, issue some other bonds that either are placed\nto a small number of investors in private placements or have a limited issue\nsize.\nThe model considers interest rate and credit spread term structures and their\ndynamics. We show that illiquid bonds present an additional liquidity spread\nthat depends on the time-to-liquidate aside from credit and interest rate\nparameters. We provide a detailed application for two issuers in the European\nmarket.\n",
"title": "A closed formula for illiquid corporate bonds and an application to the European market"
}
| null | null |
[
"Quantitative Finance"
] | null | true | null |
3421
| null |
Validated
| null | null |
null |
{
"abstract": " Long linear codes constructed from toric varieties over finite fields, their\nmultiplicative structure and decoding. The main theme is the inherent\nmultiplicative structure on toric codes. The multiplicative structure allows\nfor \\emph{decoding}, resembling the decoding of Reed-Solomon codes and aligns\nwith decoding by error correcting pairs. We have used the multiplicative\nstructure on toric codes to construct linear secret sharing schemes with\n\\emph{strong multiplication} via Massey's construction generalizing the Shamir\nLinear secret sharing shemes constructed from Reed-Solomon codes. We have\nconstructed quantum error correcting codes from toric surfaces by the\nCalderbank-Shor-Steane method.\n",
"title": "Toric Codes, Multiplicative Structure and Decoding"
}
| null | null | null | null | true | null |
3422
| null |
Default
| null | null |
null |
{
"abstract": " Often the challenge associated with tasks like fraud and spam detection[1] is\nthe lack of all likely patterns needed to train suitable supervised learning\nmodels. In order to overcome this limitation, such tasks are attempted as\noutlier or anomaly detection tasks. We also hypothesize that out- liers have\nbehavioral patterns that change over time. Limited data and continuously\nchanging patterns makes learning significantly difficult. In this work we are\nproposing an approach that detects outliers in large data sets by relying on\ndata points that are consistent. The primary contribution of this work is that\nit will quickly help retrieve samples for both consistent and non-outlier data\nsets and is also mindful of new outlier patterns. No prior knowledge of each\nset is required to extract the samples. The method consists of two phases, in\nthe first phase, consistent data points (non- outliers) are retrieved by an\nensemble method of unsupervised clustering techniques and in the second phase a\none class classifier trained on the consistent data point set is ap- plied on\nthe remaining sample set to identify the outliers. The approach is tested on\nthree publicly available data sets and the performance scores are competitive.\n",
"title": "Outlier Detection by Consistent Data Selection Method"
}
| null | null | null | null | true | null |
3423
| null |
Default
| null | null |
null |
{
"abstract": " We construct firstly the complete list of five quantum deformations of $D=4$\ncomplex homogeneous orthogonal Lie algebra $\\mathfrak{o}(4;\\mathbb{C})\\cong\n\\mathfrak{o}(3;\\mathbb{C})\\oplus \\mathfrak{o}(3;\\mathbb{C})$, describing\nquantum rotational symmetry of four-dimensional complex space-time, in\nparticular we provide the corresponding universal quantum $R$-matrices. Further\napplying four possible reality conditions we obtain all sixteen Hopf-algebraic\nquantum deformations for the real forms of $\\mathfrak{o}(4;\\mathbb{C})$:\nEuclidean $\\mathfrak{o}(4)$, Lorentz $\\mathfrak{o}(3,1)$, Kleinian\n$\\mathfrak{o}(2,2)$ and quaternionic $\\mathfrak{o}^{\\star}(4)$. For\n$\\mathfrak{o}(3,1)$ we only recall well-known results obtained previously by\nthe authors, but for other real Lie algebras (Euclidean, Kleinian,\nquaternionic) as well as for the complex Lie algebra\n$\\mathfrak{o}(4;\\mathbb{C})$ we present new results.\n",
"title": "Basic quantizations of $D=4$ Euclidean, Lorentz, Kleinian and quaternionic $\\mathfrak{o}^{\\star}(4)$ symmetries"
}
| null | null | null | null | true | null |
3424
| null |
Default
| null | null |
null |
{
"abstract": " A method to control results of gradient descent unsupervised learning in a\ndeep neural network by using evolutionary algorithm is proposed. To process\ncrossover of unsupervisedly trained models, the algorithm evaluates pointwise\nfitness of individual nodes in neural network. Labeled training data is\nrandomly sampled and breeding process selects nodes by calculating degree of\ntheir consistency on different sets of sampled data. This method supervises\nunsupervised training by evolutionary process. We also introduce modified\nRestricted Boltzmann Machine which contains repulsive force among nodes in a\nneural network and it contributes to isolate network nodes each other to avoid\naccidental degeneration of nodes by evolutionary process. These new methods are\napplied to document classification problem and it results better accuracy than\na traditional fully supervised classifier implemented with linear regression\nalgorithm.\n",
"title": "Supervising Unsupervised Learning with Evolutionary Algorithm in Deep Neural Network"
}
| null | null |
[
"Statistics"
] | null | true | null |
3425
| null |
Validated
| null | null |
null |
{
"abstract": " Graphs (networks) are ubiquitous and allow us to model entities (nodes) and\nthe dependencies (edges) between them. Learning a useful feature representation\nfrom graph data lies at the heart and success of many machine learning tasks\nsuch as classification, anomaly detection, link prediction, among many others.\nMany existing techniques use random walks as a basis for learning features or\nestimating the parameters of a graph model for a downstream prediction task.\nExamples include recent node embedding methods such as DeepWalk, node2vec, as\nwell as graph-based deep learning algorithms. However, the simple random walk\nused by these methods is fundamentally tied to the identity of the node. This\nhas three main disadvantages. First, these approaches are inherently\ntransductive and do not generalize to unseen nodes and other graphs. Second,\nthey are not space-efficient as a feature vector is learned for each node which\nis impractical for large graphs. Third, most of these approaches lack support\nfor attributed graphs.\nTo make these methods more generally applicable, we propose a framework for\ninductive network representation learning based on the notion of attributed\nrandom walk that is not tied to node identity and is instead based on learning\na function $\\Phi : \\mathrm{\\rm \\bf x} \\rightarrow w$ that maps a node attribute\nvector $\\mathrm{\\rm \\bf x}$ to a type $w$. This framework serves as a basis for\ngeneralizing existing methods such as DeepWalk, node2vec, and many other\nprevious methods that leverage traditional random walks.\n",
"title": "Inductive Representation Learning in Large Attributed Graphs"
}
| null | null | null | null | true | null |
3426
| null |
Default
| null | null |
null |
{
"abstract": " Disk migration and high-eccentricity migration are two well-studied theories\nto explain the formation of hot Jupiters. The former predicts that these\nplanets can migrate up until the planet-star Roche separation ($a_{Roche}$) and\nthe latter predicts they will tidally circularize at a minimum distance of\n2$a_{Roche}$. Considering long-running radial velocity and transit surveys have\nidentified a couple hundred hot Jupiters to date, we can revisit the classic\nquestion of hot Jupiter formation in a data-driven manner. We approach this\nproblem using data from several exoplanet surveys (radial velocity, Kepler,\nHAT, and WASP) allowing for either a single population or a mixture of\npopulations associated with these formation channels, and applying a\nhierarchical Bayesian mixture model of truncated power laws of the form\n$x^{\\gamma-1}$ to constrain the population-level parameters of interest (e.g.,\nlocation of inner edges, $\\gamma$, mixture fractions). Within the limitations\nof our chosen models, we find the current radial velocity and Kepler sample of\nhot Jupiters can be well explained with a single truncated power law\ndistribution with a lower cutoff near 2$a_{Roche}$, a result that still holds\nafter a decade, and $\\gamma=-0.51\\pm^{0.19}_{0.20}$. However, the HAT and WASP\ndata show evidence for multiple populations (Bayes factor $\\approx 10^{21}$).\nWe find that $15\\pm^{9}_{6}\\%$ reside in a component consistent with disk\nmigration ($\\gamma=-0.04\\pm^{0.53}_{1.27}$) and $85\\pm^{6}_{9}\\%$ in one\nconsistent with high-eccentricity migration ($\\gamma=-1.38\\pm^{0.32}_{0.47}$).\nWe find no immediately strong connections with some observed host star\nproperties and speculate on how future exoplanet surveys could improve upon hot\nJupiter population inference.\n",
"title": "Evidence for Two Hot Jupiter Formation Paths"
}
| null | null | null | null | true | null |
3427
| null |
Default
| null | null |
null |
{
"abstract": " The combination of photometry, spectroscopy and spectropolarimetry of the\nchemically peculiar stars often aims to study the complex physical phenomena\nsuch as stellar pulsation, chemical inhomogeneity, magnetic field and their\ninterplay with stellar atmosphere and circumstellar environment. The prime\nobjective of the present study is to determine the atmospheric parameters of a\nset of Am stars to understand their evolutionary status. Atmospheric abundances\nand basic parameters are determined using full spectrum fitting technique by\ncomparing the high-resolution spectra to the synthetic spectra. To know the\nevolutionary status we derive the effective temperature and luminosity from\ndifferent methods and compare them with the literature. The location of these\nstars in the H-R diagram demonstrate that all the sample stars are evolved from\nthe Zero-Age-Main-Sequence towards Terminal-Age-Main-Sequence and occupy the\nregion of $\\delta$ Sct instability strip. The abundance analysis shows that the\nlight elements e.g. Ca and Sc are underabundant while iron peak elements such\nas Ba, Ce etc. are overabundant and these chemical properties are typical for\nAm stars. The results obtained from the spectropolarimetric analysis shows that\nthe longitudinal magnetic fields in all the studied stars are negligible that\ngives further support their Am class of peculiarity.\n",
"title": "High-resolution Spectroscopy and Spectropolarimetry of Selected Delta Scuti Pulsating Variables"
}
| null | null | null | null | true | null |
3428
| null |
Default
| null | null |
null |
{
"abstract": " A new majority and minority voted redundancy (MMR) scheme is proposed that\ncan provide the same degree of fault tolerance as N-modular redundancy (NMR)\nbut with fewer function units and a less sophisticated voting logic. Example\nNMR and MMR circuits were implemented using a 32/28nm CMOS process and\ncompared. The results show that MMR circuits dissipate less power, occupy less\narea, and encounter less critical path delay than the corresponding NMR\ncircuits while providing the same degree of fault tolerance. Hence the MMR is a\npromising alternative to the NMR to efficiently implement high levels of\nredundancy in safety-critical applications.\n",
"title": "Majority and Minority Voted Redundancy for Safety-Critical Applications"
}
| null | null |
[
"Computer Science"
] | null | true | null |
3429
| null |
Validated
| null | null |
null |
{
"abstract": " We present a tight analysis for the well-studied randomized 3-majority\ndynamics of stabilizing consensus, hence answering the main open question of\nBecchetti et al. [SODA'16].\nConsider a distributed system of n nodes, each initially holding an opinion\nin {1, 2, ..., k}. The system should converge to a setting where all\n(non-corrupted) nodes hold the same opinion. This consensus opinion should be\n\\emph{valid}, meaning that it should be among the initially supported opinions,\nand the (fast) convergence should happen even in the presence of a malicious\nadversary who can corrupt a bounded number of nodes per round and in particular\nmodify their opinions. A well-studied distributed algorithm for this problem is\nthe 3-majority dynamics, which works as follows: per round, each node gathers\nthree opinions --- say by taking its own and two of other nodes sampled at\nrandom --- and then it sets its opinion equal to the majority of this set; ties\nare broken arbitrarily, e.g., towards the node's own opinion.\nBecchetti et al. [SODA'16] showed that the 3-majority dynamics converges to\nconsensus in O((k^2\\sqrt{\\log n} + k\\log n)(k+\\log n)) rounds, even in the\npresence of a limited adversary. We prove that, even with a stronger adversary,\nthe convergence happens within O(k\\log n) rounds. This bound is known to be\noptimal.\n",
"title": "Tight Analysis for the 3-Majority Consensus Dynamics"
}
| null | null | null | null | true | null |
3430
| null |
Default
| null | null |
null |
{
"abstract": " Using state-of-the-art techniques combining imaging methods and\nhigh-throughput genomic mapping tools leaded to the significant progress in\ndetailing chromosome architecture of various organisms. However, a gap still\nremains between the rapidly growing structural data on the chromosome folding\nand the large-scale genome organization. Could a part of information on the\nchromosome folding be obtained directly from underlying genomic DNA sequences\nabundantly stored in the databanks? To answer this question, we developed an\noriginal discrete double Fourier transform (DDFT). DDFT serves for the\ndetection of large-scale genome regularities associated with domains/units at\nthe different levels of hierarchical chromosome folding. The method is\nversatile and can be applied to both genomic DNA sequences and corresponding\nphysico-chemical parameters such as base-pairing free energy. The latter\ncharacteristic is closely related to the replication and transcription and can\nalso be used for the assessment of temperature or supercoiling effects on the\nchromosome folding. We tested the method on the genome of Escherichia coli K-12\nand found good correspondence with the annotated domains/units established\nexperimentally. As a brief illustration of further abilities of DDFT, the study\nof large-scale genome organization for bacteriophage PHIX174 and bacterium\nCaulobacter crescentus was also added. The combined experimental, modeling, and\nbioinformatic DDFT analysis should yield more complete knowledge on the\nchromosome architecture and genome organization.\n",
"title": "Large-scale chromosome folding versus genomic DNA sequences: A discrete double Fourier transform technique"
}
| null | null | null | null | true | null |
3431
| null |
Default
| null | null |
null |
{
"abstract": " According to the theory of urban scaling, urban indicators scale with city\nsize in a predictable fashion. In particular, indicators of social and economic\nproductivity are expected to have a superlinear relation. This behavior was\nverified for many urban systems, but recent findings suggest that this pattern\nmay not be valid for England and Wales (E&W), where income has a linear\nrelation with city size. This finding raises the question of whether the cities\nof E&W exhibit any superlinear relation with respect to quantities such as the\nlevel of education and occupational groups. In this paper, we evaluate the\nscaling of educational and occupational groups of E&W to see if we can detect\nsuperlinear relations in the number of educated and better-paid persons. As E&W\nmay be unique in its linear scaling of income, we complement our analysis by\ncomparing it to the urban system of the United States (US), a country for which\nsuperlinear scaling of income has already been demonstrated. To make the two\nurban systems comparable, we define the urban systems of both countries using\nthe same method and test the sensitivity of our results to changes in the\nboundaries of cities. We find that cities of E&W exhibit patterns of\nsuperlinear scaling with respect to education and certain categories of\nbetter-paid occupations. However, the tendency of such groups to have\nsuperlinear scaling seems to be more consistent in the US. We show that while\nthe educational and occupational distributions of US cities can partly explain\nthe superlinear scaling of earnings, the distribution leads to a linear scaling\nof earnings in E&W.\n",
"title": "Superlinear scaling in the urban system of England of Wales. A comparison with US cities"
}
| null | null | null | null | true | null |
3432
| null |
Default
| null | null |
null |
{
"abstract": " Living cells move thanks to assemblies of actin filaments and myosin motors\nthat range from very organized striated muscle tissue to disordered\nintracellular bundles. The mechanisms powering these disordered structures are\ndebated, and all models studied so far predict that they are contractile. We\nreexamine this prediction through a theoretical treatment of the interplay of\nthree well-characterized internal dynamical processes in actomyosin bundles:\nactin treadmilling, the attachement-detachment dynamics of myosin and that of\ncrosslinking proteins. We show that these processes enable an extensive control\nof the bundle's active mechanics, including reversals of the filaments'\napparent velocities and the possibility of generating extension instead of\ncontraction. These effects offer a new perspective on well-studied in vivo\nsystems, as well as a robust criterion to experimentally elucidate the\nunderpinnings of actomyosin activity.\n",
"title": "Extensile actomyosin?"
}
| null | null |
[
"Physics"
] | null | true | null |
3433
| null |
Validated
| null | null |
null |
{
"abstract": " There is an increasing interest in exploiting mobile sensing technologies and\nmachine learning techniques for mental health monitoring and intervention.\nResearchers have effectively used contextual information, such as mobility,\ncommunication and mobile phone usage patterns for quantifying individuals' mood\nand wellbeing. In this paper, we investigate the effectiveness of neural\nnetwork models for predicting users' level of stress by using the location\ninformation collected by smartphones. We characterize the mobility patterns of\nindividuals using the GPS metrics presented in the literature and employ these\nmetrics as input to the network. We evaluate our approach on the open-source\nStudentLife dataset. Moreover, we discuss the challenges and trade-offs\ninvolved in building machine learning models for digital mental health and\nhighlight potential future work in this direction.\n",
"title": "Towards Deep Learning Models for Psychological State Prediction using Smartphone Data: Challenges and Opportunities"
}
| null | null |
[
"Computer Science",
"Statistics"
] | null | true | null |
3434
| null |
Validated
| null | null |
null |
{
"abstract": " Cardiac indices estimation is of great importance during identification and\ndiagnosis of cardiac disease in clinical routine. However, estimation of\nmultitype cardiac indices with consistently reliable and high accuracy is still\na great challenge due to the high variability of cardiac structures and\ncomplexity of temporal dynamics in cardiac MR sequences. While efforts have\nbeen devoted into cardiac volumes estimation through feature engineering\nfollowed by a independent regression model, these methods suffer from the\nvulnerable feature representation and incompatible regression model. In this\npaper, we propose a semi-automated method for multitype cardiac indices\nestimation. After manual labelling of two landmarks for ROI cropping, an\nintegrated deep neural network Indices-Net is designed to jointly learn the\nrepresentation and regression models. It comprises two tightly-coupled\nnetworks: a deep convolution autoencoder (DCAE) for cardiac image\nrepresentation, and a multiple output convolution neural network (CNN) for\nindices regression. Joint learning of the two networks effectively enhances the\nexpressiveness of image representation with respect to cardiac indices, and the\ncompatibility between image representation and indices regression, thus leading\nto accurate and reliable estimations for all the cardiac indices.\nWhen applied with five-fold cross validation on MR images of 145 subjects,\nIndices-Net achieves consistently low estimation error for LV wall thicknesses\n(1.44$\\pm$0.71mm) and areas of cavity and myocardium (204$\\pm$133mm$^2$). It\noutperforms, with significant error reductions, segmentation method (55.1% and\n17.4%) and two-phase direct volume-only methods (12.7% and 14.6%) for wall\nthicknesses and areas, respectively. These advantages endow the proposed method\na great potential in clinical cardiac function assessment.\n",
"title": "Direct Multitype Cardiac Indices Estimation via Joint Representation and Regression Learning"
}
| null | null | null | null | true | null |
3435
| null |
Default
| null | null |
null |
{
"abstract": " We characterize certain noncommutative domains in terms of noncommutative\nholomorphic equivalence via a pseudometric that we define in purely algebraic\nterms. We prove some properties of this pseudometric and provide an application\nto free probability.\n",
"title": "Noncommutative hyperbolic metrics"
}
| null | null | null | null | true | null |
3436
| null |
Default
| null | null |
null |
{
"abstract": " We consider the problem of estimating a regression function in the common\nsituation where the number of features is small, where interpretability of the\nmodel is a high priority, and where simple linear or additive models fail to\nprovide adequate performance. To address this problem, we present Maximum\nVariance Total Variation denoising (MVTV), an approach that is conceptually\nrelated both to CART and to the more recent CRISP algorithm, a state-of-the-art\nalternative method for interpretable nonlinear regression. MVTV divides the\nfeature space into blocks of constant value and fits the value of all blocks\njointly via a convex optimization routine. Our method is fully data-adaptive,\nin that it incorporates highly robust routines for tuning all hyperparameters\nautomatically. We compare our approach against CART and CRISP via both a\ncomplexity-accuracy tradeoff metric and a human study, demonstrating that that\nMVTV is a more powerful and interpretable method.\n",
"title": "Interpretable Low-Dimensional Regression via Data-Adaptive Smoothing"
}
| null | null |
[
"Statistics"
] | null | true | null |
3437
| null |
Validated
| null | null |
null |
{
"abstract": " Chimera states, namely complex spatiotemporal patterns that consist of\ncoexisting domains of spatially coherent and incoherent dynamics, are\ninvestigated in a network of coupled identical oscillators. These intriguing\nspatiotemporal patterns were first reported in nonlocally coupled phase\noscillators, and it was shown that such mixed type behavior occurs only for\nspecific initial conditions in nonlocally and globally coupled networks. The\ninfluence of initial conditions on chimera states has remained a fundamental\nproblem since their discovery. In this report, we investigate the robustness of\nchimera states together with incoherent and coherent states in dependence on\nthe initial conditions. For this, we use the basin stability method which is\nrelated to the volume of the basin of attraction, and we consider nonlocally\nand globally coupled time-delayed Mackey-Glass oscillators as example.\nPreviously, it was shown that the existence of chimera states can be\ncharacterized by mean phase velocity and a statistical measure, such as the\nstrength of incoherence, by using well prepared initial conditions. Here we\nshow further how the coexistence of different dynamical states can be\nidentified and quantified by means of the basin stability measure over a wide\nrange of the parameter space.\n",
"title": "Basin stability for chimera states"
}
| null | null | null | null | true | null |
3438
| null |
Default
| null | null |
null |
{
"abstract": " Technologies have become important part of our lives. The steps for\nintroducing ICTs in education vary from country to country. The Republic of\nMacedonia has invested with a lot in installment of hardware and software in\neducation and in teacher training. This research was aiming to determine the\nsituation of usage of databases of digital educational materials and to define\nrecommendation for future improvements. Teachers from urban schools were\ninterviewed with a questionnaire. The findings are several: only part of the\ninterviewed teachers had experience with databases of educational materials;\nall teachers still need capacity building activities focusing exactly on the\nuse and benefits from databases of educational materials; preferably capacity\nbuilding materials to be in Macedonian language; technical support and\nupgrading of software and materials should be performed on a regular basis.\nMost of the findings can be applied at both national and international level -\nwith all this implemented, application of ICT in education will have much\nbigger positive impact.\n",
"title": "On the Usage of Databases of Educational Materials in Macedonian Education"
}
| null | null | null | null | true | null |
3439
| null |
Default
| null | null |
null |
{
"abstract": " We study the neural-linear bandit model for solving sequential\ndecision-making problems with high dimensional side information. Neural-linear\nbandits leverage the representation power of deep neural networks and combine\nit with efficient exploration mechanisms, designed for linear contextual\nbandits, on top of the last hidden layer. Since the representation is being\noptimized during learning, information regarding exploration with \"old\"\nfeatures is lost. Here, we propose the first limited memory neural-linear\nbandit that is resilient to this phenomenon, which we term catastrophic\nforgetting. We evaluate our method on a variety of real-world data sets,\nincluding regression, classification, and sentiment analysis, and observe that\nour algorithm is resilient to catastrophic forgetting and achieves superior\nperformance.\n",
"title": "Deep Neural Linear Bandits: Overcoming Catastrophic Forgetting through Likelihood Matching"
}
| null | null | null | null | true | null |
3440
| null |
Default
| null | null |
null |
{
"abstract": " We present two-dimensional hydrodynamical simulations of pairs of planets\nmigrating simultaneously in the Type I regime in a protoplanetary disc.\nConvergent migration naturally leads to the trapping of these planets in\nmean-motion resonances. Once in resonance the planets' eccentricity grows\nrapidly, and disc-planet torques cause the planets to escape resonance on a\ntime-scale of a few hundred orbits. The effect is more pronounced in highly\nviscous discs, but operates efficiently even in inviscid discs. We attribute\nthis resonance-breaking to overstable librations driven by moderate\neccentricity damping, but find that this mechanism operates differently in\nhydrodynamic simulations than in previous analytic calculations. Planets\nescaping resonance in this manner can potentially explain the observed paucity\nof resonances in Kepler multi-transiting systems, and we suggest that\nsimultaneous disc-driven migration remains the most plausible means of\nassembling tightly-packed planetary systems.\n",
"title": "Breaking mean-motion resonances during Type I planet migration"
}
| null | null | null | null | true | null |
3441
| null |
Default
| null | null |
null |
{
"abstract": " First-passage times in random walks have a vast number of diverse\napplications in physics, chemistry, biology, and finance. In general,\nenvironmental conditions for a stochastic process are not constant on the time\nscale of the average first-passage time, or control might be applied to reduce\nnoise. We investigate moments of the first-passage time distribution under a\ntransient describing relaxation of environmental conditions. We solve the\nLaplace-transformed (generalized) master equation analytically using a novel\nmethod that is applicable to general state schemes. The first-passage time from\none end to the other of a linear chain of states is our application for the\nsolutions. The dependence of its average on the relaxation rate obeys a power\nlaw for slow transients. The exponent $\\nu$ depends on the chain length $N$\nlike $\\nu=-N/(N+1)$ to leading order. Slow transients substantially reduce the\nnoise of first-passage times expressed as the coefficient of variation (CV),\neven if the average first-passage time is much longer than the transient. The\nCV has a pronounced minimum for some lengths, which we call resonant lengths.\nThese results also suggest a simple and efficient noise control strategy, and\nare closely related to the timing of repetitive excitations, coherence\nresonance and information transmission by noisy excitable systems. A resonant\nnumber of steps from the inhibited state to the excitation threshold and slow\nrecovery from negative feedback provide optimal timing noise reduction and\ninformation transmission.\n",
"title": "The Stretch to Stray on Time: Resonant Length of Random Walks in a Transient"
}
| null | null | null | null | true | null |
3442
| null |
Default
| null | null |
null |
{
"abstract": " Video prediction has been an active topic of research in the past few years.\nMany algorithms focus on pixel-level predictions, which generates results that\nblur and disintegrate within a few frames. In this project, we use a\nhierarchical approach for long-term video prediction. We aim at estimating\nhigh-level structure in the input frame first, then predict how that structure\ngrows in the future. Finally, we use an image analogy network to recover a\nrealistic image from the predicted structure. Our method is largely adopted\nfrom the work by Villegas et al. The method is built with a combination of\nLSTMs and analogy-based convolutional auto-encoder networks. Additionally, in\norder to generate more realistic frame predictions, we also adopt adversarial\nloss. We evaluate our method on the Penn Action dataset, and demonstrate good\nresults on high-level long-term structure prediction.\n",
"title": "Hierarchical Model for Long-term Video Prediction"
}
| null | null | null | null | true | null |
3443
| null |
Default
| null | null |
null |
{
"abstract": " In this paper we cluster 330 classical music pieces collected from MusicNet\ndatabase based on their musical note sequence. We use shingling and chord\ntrajectory matrices to create signature for each music piece and performed\nspectral clustering to find the clusters. Based on different resolution, the\noutput clusters distinctively indicate composition from different classical\nmusic era and different composing style of the musicians.\n",
"title": "Classical Music Clustering Based on Acoustic Features"
}
| null | null | null | null | true | null |
3444
| null |
Default
| null | null |
null |
{
"abstract": " For random quantum spin models, the strong disorder perturbative expansion of\nthe Local Integrals of Motion (LIOMs) around the real-spin operators is\nrevisited. The emphasis is on the links with other properties of the\nMany-Body-Localized phase, in particular the memory in the dynamics of the\nlocal magnetizations and the statistics of matrix elements of local operators\nin the eigenstate basis. Finally, this approach is applied to analyze the\nMany-Body-Localization transition in a toy model studied previously from the\npoint of view of the entanglement entropy.\n",
"title": "Many-Body-Localization : Strong Disorder perturbative approach for the Local Integrals of Motion"
}
| null | null | null | null | true | null |
3445
| null |
Default
| null | null |
null |
{
"abstract": " We introduce a semi-supervised discrete choice model to calibrate discrete\nchoice models when relatively few requests have both choice sets and stated\npreferences but the majority only have the choice sets. Two classic\nsemi-supervised learning algorithms, the expectation maximization algorithm and\nthe cluster-and-label algorithm, have been adapted to our choice modeling\nproblem setting. We also develop two new algorithms based on the\ncluster-and-label algorithm. The new algorithms use the Bayesian Information\nCriterion to evaluate a clustering setting to automatically adjust the number\nof clusters. Two computational studies including a hotel booking case and a\nlarge-scale airline itinerary shopping case are presented to evaluate the\nprediction accuracy and computational effort of the proposed algorithms.\nAlgorithmic recommendations are rendered under various scenarios.\n",
"title": "Semi-supervised Learning for Discrete Choice Models"
}
| null | null | null | null | true | null |
3446
| null |
Default
| null | null |
null |
{
"abstract": " Mean motion commensurabilities in multi-planet systems are an expected\noutcome of protoplanetary disk-driven migration, and their relative dearth in\nthe observational data presents an important challenge to current models of\nplanet formation and dynamical evolution. One natural mechanism that can lead\nto the dissolution of commensurabilities is stochastic orbital forcing, induced\nby turbulent density fluctuations within the nebula. While this process is\nqualitatively promising, the conditions under which mean motion resonances can\nbe broken are not well understood. In this work, we derive a simple analytic\ncriterion that elucidates the relationship among the physical parameters of the\nsystem, and find the conditions necessary to drive planets out of resonance.\nSubsequently, we confirm our findings with numerical integrations carried out\nin the perturbative regime, as well as direct N-body simulations. Our\ncalculations suggest that turbulent resonance disruption depends most\nsensitively on the planet-star mass ratio. Specifically, for a disk with\nproperties comparable to the early solar nebula with $\\alpha=0.01$, only planet\npairs with cumulative mass ratios smaller than\n$(m_1+m_2)/M\\lesssim10^{-5}\\sim3M_{\\oplus}/M_{\\odot}$ are susceptible to\nbreaking resonance at semi-major axis of order $a\\sim0.1\\,$AU. Although\nturbulence can sometimes compromise resonant pairs, an additional mechanism\n(such as suppression of resonance capture probability through disk\neccentricity) is required to adequately explain the largely non-resonant\norbital architectures of extrasolar planetary systems.\n",
"title": "An Analytic Criterion for Turbulent Disruption of Planetary Resonances"
}
| null | null | null | null | true | null |
3447
| null |
Default
| null | null |
null |
{
"abstract": " In van der Waals heterostructures, the periodic potential from the Moiré\nsuperlattice can be used as a control knob to modulate the electronic structure\nof the constituent materials. Here we present a nanoscale angle-resolved\nphotoemission spectroscopy (Nano-ARPES) study of transferred graphene/h-BN\nheterostructures with two different stacking angles of 2.4° and 4.3°\nrespectively. Our measurements reveal six replicas of graphene Dirac cones at\nthe superlattice Brillouin zone (SBZ) centers. The size of the SBZ and its\nrelative rotation angle to the graphene BZ are in good agreement with Moiré\nsuperlattice period extracted from atomic force microscopy (AFM) measurements.\nComparison to epitaxial graphene/h-BN with 0° stacking angles suggests\nthat the interaction between graphene and h-BN decreases with increasing\nstacking angle.\n",
"title": "Electronic structure of transferred graphene/h-BN van der Waals heterostructures with nonzero stacking angles by nano-ARPES"
}
| null | null | null | null | true | null |
3448
| null |
Default
| null | null |
null |
{
"abstract": " We conjecture that bounded generalised polynomial functions cannot be\ngenerated by finite automata, except for the trivial case when they are\nultimately periodic.\nUsing methods from ergodic theory, we are able to partially resolve this\nconjecture, proving that any hypothetical counterexample is periodic away from\na very sparse and structured set.\nIn particular, we show that for a polynomial $p(n)$ with at least one\nirrational coefficient (except for the constant one) and integer $m\\geq 2$, the\nsequence $\\lfloor p(n) \\rfloor \\bmod{m}$ is never automatic.\nWe also prove that the conjecture is equivalent to the claim that the set of\npowers of an integer $k\\geq 2$ is not given by a generalised polynomial.\n",
"title": "Automatic sequences and generalised polynomials"
}
| null | null | null | null | true | null |
3449
| null |
Default
| null | null |
null |
{
"abstract": " We will give general sufficient conditions under which a controller achieves\nrobust regulation for a boundary control and observation system. Utilizing\nthese conditions we construct a minimal order robust controller for an\narbitrary order impedance passive linear port-Hamiltonian system. The\ntheoretical results are illustrated with a numerical example where we implement\na controller for a one-dimensional Euler-Bernoulli beam with boundary controls\nand boundary observations.\n",
"title": "Robust Regulation of Infinite-Dimensional Port-Hamiltonian Systems"
}
| null | null | null | null | true | null |
3450
| null |
Default
| null | null |
null |
{
"abstract": " We provide a mathematical analysis of a thermo-diffusive combustion model of\nlean spray flames, for which we prove the existence of travelling waves. In the\nhigh activation energy singular limit we show the existence of two distinct\ncombustion regimes with a sharp transition -- the diffusion limited regime and\nthe vaporisation controlled regime. The latter is specific to spray flames with\nslow enough vaporisation. We give a complete characterisation of these regimes,\nincluding explicit velocities, profiles, and upper estimate of the size of the\ninternal combustion layer. Our model is on the one hand simple enough to allow\nfor explicit asymptotic limits and on the other hand rich enough to capture\nsome particular aspects of spray combustion. Finally, we briefly discuss the\ncases where the vaporisation is infinitely fast, or where the spray is\npolydisperse.\n",
"title": "Existence of travelling waves and high activation energy limits for a onedimensional thermo-diffusive lean spray flame model"
}
| null | null |
[
"Mathematics"
] | null | true | null |
3451
| null |
Validated
| null | null |
null |
{
"abstract": " We consider the motion of small bodies in general relativity. The key result\ncaptures a sense in which such bodies follow timelike geodesics (or, in the\ncase of charged bodies, Lorentz-force curves). This result clarifies the\nrelationship between approaches that model such bodies as distributions\nsupported on a curve, and those that employ smooth fields supported in small\nneighborhoods of a curve. This result also applies to \"bodies\" constructed from\nwave packets of Maxwell or Klein-Gordon fields. There follows a simple and\nprecise formulation of the optical limit for Maxwell fields.\n",
"title": "The Motion of Small Bodies in Space-time"
}
| null | null | null | null | true | null |
3452
| null |
Default
| null | null |
null |
{
"abstract": " Impervious surface area is a direct consequence of the urbanization, which\nalso plays an important role in urban planning and environmental management.\nWith the rapidly technical development of remote sensing, monitoring urban\nimpervious surface via high spatial resolution (HSR) images has attracted\nunprecedented attention recently. Traditional multi-classes models are\ninefficient for impervious surface extraction because it requires labeling all\nneeded and unneeded classes that occur in the image exhaustively. Therefore, we\nneed to find a reliable one-class model to classify one specific land cover\ntype without labeling other classes. In this study, we investigate several\none-class classifiers, such as Presence and Background Learning (PBL), Positive\nUnlabeled Learning (PUL), OCSVM, BSVM and MAXENT, to extract urban impervious\nsurface area using high spatial resolution imagery of GF-1, China's new\ngeneration of high spatial remote sensing satellite, and evaluate the\nclassification accuracy based on artificial interpretation results. Compared to\ntraditional multi-classes classifiers (ANN and SVM), the experimental results\nindicate that PBL and PUL provide higher classification accuracy, which is\nsimilar to the accuracy provided by ANN model. Meanwhile, PBL and PUL\noutperforms OCSVM, BSVM, MAXENT and SVM models. Hence, the one-class\nclassifiers only need a small set of specific samples to train models without\nlosing predictive accuracy, which is supposed to gain more attention on urban\nimpervious surface extraction or other one specific land cover type.\n",
"title": "Extracting urban impervious surface from GF-1 imagery using one-class classifiers"
}
| null | null | null | null | true | null |
3453
| null |
Default
| null | null |
null |
{
"abstract": " We study the problem% \\[ -\\Delta v+\\lambda v=| v| ^{p-2}v\\text{ in }\\Omega\n,\\text{\\qquad}v=0\\text{ on $\\partial\\Omega$},\\text{ }% \\] for\n$\\lambda\\in\\mathbb{R}$ and supercritical exponents $p,$ in domains of the form%\n\\[ \\Omega:=\\{(y,z)\\in\\mathbb{R}^{N-m-1}\\times\\mathbb{R}^{m+1}:(y,| z|\n)\\in\\Theta\\}, \\] where $m\\geq1,$ $N-m\\geq3,$ and $\\Theta$ is a bounded domain\nin $\\mathbb{R}% ^{N-m}$ whose closure is contained in\n$\\mathbb{R}^{N-m-1}\\times(0,\\infty)$. Under some symmetry assumptions on\n$\\Theta$, we show that this problem has infinitely many solutions for every\n$\\lambda$ in an interval which contains $[0,\\infty)$ and $p>2$ up to some\nnumber which is larger than the $(m+1)^{st}$ critical exponent\n$2_{N,m}^{\\ast}:=\\frac{2(N-m)}{N-m-2}$. We also exhibit domains with a\nshrinking hole, in which there are a positive and a nodal solution which\nconcentrate on a sphere, developing a single layer that blows up at an\n$m$-dimensional sphere contained in the boundary of $\\Omega,$ as the hole\nshrinks and $p\\rightarrow2_{N,m}^{\\ast}$ from above. The limit profile of the\npositive solution, in the transversal direction to the sphere of concentration,\nis a rescaling of the standard bubble, whereas that of the nodal solution is a\nrescaling of a nonradial sign-changing solution to the problem% \\[ -\\Delta u=|\nu| ^{2_{n}^{\\ast}-2}u,\\text{\\qquad}u\\in D^{1,2}(\\mathbb{R}^{n}), \\] where\n$2_{n}^{\\ast}:=\\frac{2n}{n-2}$ is the critical exponent in dimension\n$n.$\\medskip\n",
"title": "Positive and nodal single-layered solutions to supercritical elliptic problems above the higher critical exponents"
}
| null | null | null | null | true | null |
3454
| null |
Default
| null | null |
null |
{
"abstract": " PCA is a classical statistical technique whose simplicity and maturity has\nseen it find widespread use as an anomaly detection technique. However, it is\nlimited in this regard by being sensitive to gross perturbations of the input,\nand by seeking a linear subspace that captures normal behaviour. The first\nissue has been dealt with by robust PCA, a variant of PCA that explicitly\nallows for some data points to be arbitrarily corrupted, however, this does not\nresolve the second issue, and indeed introduces the new issue that one can no\nlonger inductively find anomalies on a test set. This paper addresses both\nissues in a single model, the robust autoencoder. This method learns a\nnonlinear subspace that captures the majority of data points, while allowing\nfor some data to have arbitrary corruption. The model is simple to train and\nleverages recent advances in the optimisation of deep neural networks.\nExperiments on a range of real-world datasets highlight the model's\neffectiveness.\n",
"title": "Robust, Deep and Inductive Anomaly Detection"
}
| null | null |
[
"Computer Science",
"Statistics"
] | null | true | null |
3455
| null |
Validated
| null | null |
null |
{
"abstract": " End user privacy is a critical concern for all organizations that collect,\nprocess and store user data as a part of their business. Privacy concerned\nusers, regulatory bodies and privacy experts continuously demand organizations\nprovide users with privacy protection. Current research lacks an understanding\nof organizational characteristics that affect an organization's motivation\ntowards user privacy. This has resulted in a \"one solution fits all\" approach,\nwhich is incapable of providing sustainable solutions for organizational issues\nrelated to user privacy. In this work, we have empirically investigated 40\ndiverse organizations on their motivations and approaches towards user privacy.\nResources such as newspaper articles, privacy policies and internal privacy\nreports that display information about organizational motivations and\napproaches towards user privacy were used in the study. We could observe\norganizations to have two primary motivations to provide end users with privacy\nas voluntary driven inherent motivation, and risk driven compliance motivation.\nBuilding up on these findings we developed a taxonomy of organizational privacy\napproaches and further explored the taxonomy through limited exclusive\ninterviews. With his work, we encourage authorities and scholars to understand\norganizational characteristics that define an organization's approach towards\nprivacy, in order to effectively communicate regulations that enforce and\nencourage organizations to consider privacy within their business practices.\n",
"title": "Understanding Organizational Approach towards End User Privacy"
}
| null | null | null | null | true | null |
3456
| null |
Default
| null | null |
null |
{
"abstract": " We study the orbital properties of dark matter haloes by combining a spectral\nmethod and cosmological simulations of Milky Way-sized galaxies. We compare the\ndynamics and orbits of individual dark matter particles from both hydrodynamic\nand $N$-body simulations, and find that the fraction of box, tube and resonant\norbits of the dark matter halo decreases significantly due to the effects of\nbaryons. In particular, the central region of the dark matter halo in the\nhydrodynamic simulation is dominated by regular, short-axis tube orbits, in\ncontrast to the chaotic, box and thin orbits dominant in the $N$-body run. This\nleads to a more spherical dark matter halo in the hydrodynamic run compared to\na prolate one as commonly seen in the $N$-body simulations. Furthermore, by\nusing a kernel based density estimator, we compare the coarse-grained\nphase-space densities of dark matter haloes in both simulations and find that\nit is lower by $\\sim0.5$ dex in the hydrodynamic run due to changes in the\nangular momentum distribution, which indicates that the baryonic process that\naffects the dark matter is irreversible. Our results imply that baryons play an\nimportant role in determining the shape, kinematics and phase-space density of\ndark matter haloes in galaxies.\n",
"title": "Baryonic impact on the dark matter orbital properties of Milky Way-sized haloes"
}
| null | null | null | null | true | null |
3457
| null |
Default
| null | null |
null |
{
"abstract": " In this paper we are concerned with the analysis of heavy-tailed data when a\nportion of the extreme values is unavailable. This research was motivated by an\nanalysis of the degree distributions in a large social network. The degree\ndistributions of such networks tend to have power law behavior in the tails. We\nfocus on the Hill estimator, which plays a starring role in heavy-tailed\nmodeling. The Hill estimator for this data exhibited a smooth and increasing\n\"sample path\" as a function of the number of upper order statistics used in\nconstructing the estimator. This behavior became more apparent as we\nartificially removed more of the upper order statistics. Building on this\nobservation we introduce a new version of the Hill estimator. It is a function\nof the number of the upper order statistics used in the estimation, but also\ndepends on the number of unavailable extreme values. We establish functional\nconvergence of the normalized Hill estimator to a Gaussian process. An\nestimation procedure is developed based on the limit theory to estimate the\nnumber of missing extremes and extreme value parameters including the tail\nindex and the bias of Hill's estimator. We illustrate how this approach works\nin both simulations and real data examples.\n",
"title": "Extreme Value Analysis Without the Largest Values: What Can Be Done?"
}
| null | null |
[
"Mathematics"
] | null | true | null |
3458
| null |
Validated
| null | null |
null |
{
"abstract": " Studying the internal structure of complex samples with light is an important\ntask, but a difficult challenge due to light scattering. While the complex\noptical distortions induced by multiple scattering can be effectively undone\nwith the knowledge of the medium's scattering-matrix, this matrix is generally\nunknown, and cannot be measured with high resolution without the presence of\nfluorescent or absorbing probes at all points of interest. To overcome these\nlimitations, we introduce here the concept of the acousto-optic transmission\nmatrix (AOTM). Taking advantage of the near scattering-free propagation of\nultrasound in complex samples, we noninvasively measure an\nultrasonically-encoded, spatially-resolved, optical scattering-matrix. We\ndemonstrate that a singular value decomposition analysis of the AOTM, acquired\nusing a single or multiple ultrasonic beams, allows controlled optical focusing\nbeyond the acoustic diffraction limit in scattering media. Our approach\nprovides a generalized framework for analyzing acousto-optical experiments, and\nfor noninvasive, high-resolution study of complex media.\n",
"title": "Controlling light in complex media beyond the acoustic diffraction-limit using the acousto-optic transmission matrix"
}
| null | null | null | null | true | null |
3459
| null |
Default
| null | null |
null |
{
"abstract": " We verify a conjecture of Perelman, which states that there exists a\ncanonical Ricci flow through singularities starting from an arbitrary compact\nRiemannian 3-manifold. Our main result is a uniqueness theorem for such flows,\nwhich, together with an earlier existence theorem of Lott and the second named\nauthor, implies Perelman's conjecture. We also show that this flow through\nsingularities depends continuously on its initial condition and that it may be\nobtained as a limit of Ricci flows with surgery.\nOur results have applications to the study of diffeomorphism groups of three\nmanifolds --- in particular to the Generalized Smale Conjecture --- which will\nappear in a subsequent paper.\n",
"title": "Uniqueness and stability of Ricci flow through singularities"
}
| null | null | null | null | true | null |
3460
| null |
Default
| null | null |
null |
{
"abstract": " Hyperuniform geometries feature correlated disordered topologies which follow\nfrom a tailored k-space design. Here we study gold plasmonic hyperuniform\nmetasurfaces and we report evidence of the effectiveness of k-space engineering\non both light scattering and light emission experiments. The metasurfaces\npossess interesting directional emission properties which are revealed by\nmomentum spectroscopy as diffraction and fluorescence emission rings at\nsize-specific k-vectors. The opening of these rotational-symmetric patterns\nscales with the hyperuniform correlation length parameter as predicted via the\nspectral function method.\n",
"title": "Reciprocal space engineering with hyperuniform gold metasurfaces"
}
| null | null |
[
"Physics"
] | null | true | null |
3461
| null |
Validated
| null | null |
null |
{
"abstract": " This paper proposes a new loss using short-time Fourier transform (STFT)\nspectra for the aim of training a high-performance neural speech waveform model\nthat predicts raw continuous speech waveform samples directly. Not only\namplitude spectra but also phase spectra obtained from generated speech\nwaveforms are used to calculate the proposed loss. We also mathematically show\nthat training of the waveform model on the basis of the proposed loss can be\ninterpreted as maximum likelihood training that assumes the amplitude and phase\nspectra of generated speech waveforms following Gaussian and von Mises\ndistributions, respectively. Furthermore, this paper presents a simple network\narchitecture as the speech waveform model, which is composed of uni-directional\nlong short-term memories (LSTMs) and an auto-regressive structure. Experimental\nresults showed that the proposed neural model synthesized high-quality speech\nwaveforms.\n",
"title": "STFT spectral loss for training a neural speech waveform model"
}
| null | null | null | null | true | null |
3462
| null |
Default
| null | null |
null |
{
"abstract": " We study continuum Schrödinger operators on the real line whose potentials\nare comprised of two compactly supported square-integrable functions\nconcatenated according to an element of the Fibonacci substitution subshift\nover two letters. We show that the Hausdorff dimension of the spectrum tends to\none in the small-coupling and high-energy regimes, regardless of the shape of\nthe potential pieces.\n",
"title": "Spectral Properties of Continuum Fibonacci Schrödinger Operators"
}
| null | null |
[
"Mathematics"
] | null | true | null |
3463
| null |
Validated
| null | null |
null |
{
"abstract": " The log-det distance between two aligned DNA sequences was introduced as a\ntool for statistically consistent inference of a gene tree under simple\nnon-mixture models of sequence evolution. Here we prove that the log-det\ndistance, coupled with a distance-based tree construction method, also permits\nconsistent inference of species trees under mixture models appropriate to\naligned genomic-scale sequences data. Data may include sites from many genetic\nloci, which evolved on different gene trees due to incomplete lineage sorting\non an ultrametric species tree, with different time-reversible substitution\nprocesses. The simplicity and speed of distance-based inference suggests\nlog-det based methods should serve as benchmarks for judging more elaborate and\ncomputationally-intensive species trees inference methods.\n",
"title": "Species tree inference from genomic sequences using the log-det distance"
}
| null | null | null | null | true | null |
3464
| null |
Default
| null | null |
null |
{
"abstract": " In this paper we focus on the construction of numerical schemes for nonlinear\nFokker-Planck equations that preserve the structural properties, like non\nnegativity of the solution, entropy dissipation and large time behavior. The\nmethods here developed are second order accurate, they do not require any\nrestriction on the mesh size and are capable to capture the asymptotic steady\nstates with arbitrary accuracy. These properties are essential for a correct\ndescription of the underlying physical problem. Applications of the schemes to\nseveral nonlinear Fokker-Planck equations with nonlocal terms describing\nemerging collective behavior in socio-economic and life sciences are presented.\n",
"title": "Structure preserving schemes for nonlinear Fokker-Planck equations and applications"
}
| null | null | null | null | true | null |
3465
| null |
Default
| null | null |
null |
{
"abstract": " There are several different modalities, e.g., surgery, chemotherapy, and\nradiotherapy, that are currently used to treat cancer. It is common practice to\nuse a combination of these modalities to maximize clinical outcomes, which are\noften measured by a balance between maximizing tumor damage and minimizing\nnormal tissue side effects due to treatment. However, multi-modality treatment\npolicies are mostly empirical in current practice, and are therefore subject to\nindividual clinicians' experiences and intuition. We present a novel\nformulation of optimal multi-modality cancer management using a finite-horizon\nMarkov decision process approach. Specifically, at each decision epoch, the\nclinician chooses an optimal treatment modality based on the patient's observed\nstate, which we define as a combination of tumor progression and normal tissue\nside effect. Treatment modalities are categorized as (1) Type 1, which has a\nhigh risk and high reward, but is restricted in the frequency of administration\nduring a treatment course, (2) Type 2, which has a lower risk and lower reward\nthan Type 1, but may be repeated without restriction, and (3) Type 3, no\ntreatment (surveillance), which has the possibility of reducing normal tissue\nside effect at the risk of worsening tumor progression. Numerical simulations\nusing various intuitive, concave reward functions show the structural insights\nof optimal policies and demonstrate the potential applications of using a\nrigorous approach to optimizing multi-modality cancer management.\n",
"title": "A Markov decision process approach to optimizing cancer therapy using multiple modalities"
}
| null | null | null | null | true | null |
3466
| null |
Default
| null | null |
null |
{
"abstract": " A great deal of effort has gone into trying to model social influence ---\nincluding the spread of behavior, norms, and ideas --- on networks. Most models\nof social influence tend to assume that individuals react to changes in the\nstates of their neighbors without any time delay, but this is often not true in\nsocial contexts, where (for various reasons) different agents can have\ndifferent response times. To examine such situations, we introduce the idea of\na timer into threshold models of social influence. The presence of timers on\nnodes delays the adoption --- i.e., change of state --- of each agent, which in\nturn delays the adoptions of its neighbors. With a homogeneous-distributed\ntimer, in which all nodes exhibit the same amount of delay, adoption delays are\nalso homogeneous, so the adoption order of nodes remains the same. However,\nheterogeneously-distributed timers can change the adoption order of nodes and\nhence the \"adoption paths\" through which state changes spread in a network.\nUsing a threshold model of social contagions, we illustrate that heterogeneous\ntimers can either accelerate or decelerate the spread of adoptions compared to\nan analogous situation with homogeneous timers, and we investigate the\nrelationship of such acceleration or deceleration with respect to timer\ndistribution and network structure. We derive an analytical approximation for\nthe temporal evolution of the fraction of adopters by modifying a pair\napproximation of the Watts threshold model, and we find good agreement with\nnumerical computations. We also examine our new timer model on networks\nconstructed from empirical data.\n",
"title": "Complex Contagions with Timers"
}
| null | null | null | null | true | null |
3467
| null |
Default
| null | null |
null |
{
"abstract": " We study conditional independence relationships for random networks and their\ninterplay with exchangeability. We show that, for finitely exchangeable network\nmodels, the empirical subgraph densities are maximum likelihood estimates of\ntheir theoretical counterparts. We then characterize all possible Markov\nstructures for finitely exchangeable random graphs, thereby identifying a new\nclass of Markov network models corresponding to bidirected Kneser graphs. In\nparticular, we demonstrate that the fundamental property of dissociatedness\ncorresponds to a Markov property for exchangeable networks described by\nbidirected line graphs. Finally we study those exchangeable models that are\nalso summarized in the sense that the probability of a network only depends\nonthe degree distribution, and identify a class of models that is dual to the\nMarkov graphs of Frank and Strauss (1986). Particular emphasis is placed on\nstudying consistency properties of network models under the process of forming\nsubnetworks and we show that the only consistent systems of Markov properties\ncorrespond to the empty graph, the bidirected line graph of the complete graph,\nand the complete graph.\n",
"title": "Random Networks, Graphical Models, and Exchangeability"
}
| null | null |
[
"Mathematics",
"Statistics"
] | null | true | null |
3468
| null |
Validated
| null | null |
null |
{
"abstract": " A current-aided inertial navigation framework is proposed for small\nautonomous underwater vehicles in long-duration operations (> 1 hour), where\nneither frequent surfacing nor consistent bottom-tracking are available. We\ninstantiate this concept through mid-depth, underwater navigation. This\nstrategy mitigates dead-reckoning uncertainty of a traditional inertial\nnavigation system by comparing the estimate of local, ambient flow velocity\nwith preloaded ocean current maps. The proposed navigation system is\nimplemented through a marginalized particle filter where the vehicle's states\nare sequentially tracked along with sensor bias and local turbulence that is\nnot resolved by general flow prediction. The performance of the proposed\napproach is first analyzed through Monte Carlo simulations in two artificial\nbackground flow fields, resembling real-world ocean circulation patterns,\nsuperposed with smaller-scale, turbulent components with Kolmogorov energy\nspectrum. The current-aided navigation scheme significantly improves the\ndead-reckoning performance of the vehicle even when unresolved, small-scale\nflow perturbations are present. For a 6-hour navigation with an\nautomotive-grade inertial navigation system, the current-aided navigation\nscheme results in positioning estimates with under 3% uncertainty per distance\ntraveled (UDT) in a turbulent, double-gyre flow field, and under 7.3% UDT in a\nturbulent, meandering jet flow field. Further evaluation with field test data\nand actual ocean simulation analysis demonstrates consistent performance for a\n6-hour mission, positioning result with under 25% UDT for a 24-hour navigation\nwhen provided direct heading measurements, and terminal positioning estimate\nwith 16% UDT at the cost of increased uncertainty at an early stage of the\nnavigation.\n",
"title": "Long-Term Inertial Navigation Aided by Dynamics of Flow Field Features"
}
| null | null | null | null | true | null |
3469
| null |
Default
| null | null |
null |
{
"abstract": " In February 2016, World Health Organization declared the Zika outbreak a\nPublic Health Emergency of International Concern. With developing evidence it\ncan cause birth defects, and the Summer Olympics coming up in the worst\naffected country, Brazil, the virus caught fire on social media. In this work,\nuse Zika as a case study in building a tool for tracking the misinformation\naround health concerns on Twitter. We collect more than 13 million tweets --\nspanning the initial reports in February 2016 and the Summer Olympics --\nregarding the Zika outbreak and track rumors outlined by the World Health\nOrganization and Snopes fact checking website. The tool pipeline, which\nincorporates health professionals, crowdsourcing, and machine learning, allows\nus to capture health-related rumors around the world, as well as clarification\ncampaigns by reputable health organizations. In the case of Zika, we discover\nan extremely bursty behavior of rumor-related topics, and show that, once the\nquestionable topic is detected, it is possible to identify rumor-bearing tweets\nusing automated techniques. Thus, we illustrate insights the proposed tools\nprovide into potentially harmful information on social media, allowing public\nhealth researchers and practitioners to respond with a targeted and timely\naction.\n",
"title": "Catching Zika Fever: Application of Crowdsourcing and Machine Learning for Tracking Health Misinformation on Twitter"
}
| null | null |
[
"Computer Science"
] | null | true | null |
3470
| null |
Validated
| null | null |
null |
{
"abstract": " The low-energy constants, namely the spin stiffness $\\rho_s$, the staggered\nmagnetization density ${\\cal M}_s$ per area, and the spinwave velocity $c$ of\nthe two-dimensional (2D) spin-1 Heisenberg model on the square and rectangular\nlattices are determined using the first principles Monte Carlo method. In\nparticular, the studied models have antiferromagnetic couplings $J_1$ and $J_2$\nin the spatial 1- and 2-directions, respectively. For each considered\n$J_2/J_1$, the aspect ratio of the corresponding linear box sizes $L_2/L_1$\nused in the simulations is adjusted so that the squares of the two spatial\nwinding numbers take the same values. In addition, the relevant finite-volume\nand -temperature predictions from magnon chiral perturbation theory are\nemployed in extracting the numerical values of these low-energy constants. Our\nresults of $\\rho_{s1}$ are in quantitative agreement with those obtained by the\nseries expansion method over a broad range of $J_2/J_1$. This in turn provides\nconvincing numerical evidence for the quantitative correctness of our approach.\nThe ${\\cal M}_s$ and $c$ presented here for the spatially anisotropic models\nare new and can be used as benchmarks for future related studies.\n",
"title": "Monte Carlo determination of the low-energy constants for a two-dimensional spin-1 Heisenberg model with spatial anisotropy"
}
| null | null | null | null | true | null |
3471
| null |
Default
| null | null |
null |
{
"abstract": " Political and social polarization are a significant cause of conflict and\npoor governance in many societies, thus understanding their causes is of\nconsiderable importance. Here we demonstrate that shifts in socialization\nstrategy similar to political polarization and/or identity politics could be a\nconstructive response to periods of apparent economic decline. We start from\nthe observation that economies, like ecologies are seldom at equilibrium.\nRather, they often suffer both negative and positive shocks. We show that even\nwhere in an expanding economy, interacting with diverse out-groups can afford\nbenefits through innovation and exploration, if that economy contracts, a\nstrategy of seeking homogeneous groups can be important to maintaining\nindividual solvency. This is true even where the expected value of out group\ninteraction exceeds that of in group interactions. Our account unifies what\nwere previously seen as conflicting explanations: identity threat versus\neconomic anxiety. Our model indicates that in periods of extreme deprivation,\ncooperation with diversity again becomes the best (in fact, only viable)\nstrategy. However, our model also shows that while polarization may increase\ngradually in response to shifts in the economy, gradual decrease of\npolarization may not be an available strategy; thus returning to previous\nlevels of cooperation may require structural change.\n",
"title": "Explaining Parochialism: A Causal Account for Political Polarization in Changing Economic Environments"
}
| null | null |
[
"Quantitative Biology",
"Quantitative Finance"
] | null | true | null |
3472
| null |
Validated
| null | null |
null |
{
"abstract": " Despite decades of inquiry, the origin of giant planets residing within a few\ntenths of an astronomical unit from their host stars remains unclear.\nTraditionally, these objects are thought to have formed further out before\nsubsequently migrating inwards. However, the necessity of migration has been\nrecently called into question with the emergence of in-situ formation models of\nclose-in giant planets. Observational characterization of the transiting\nsub-sample of close-in giants has revealed that \"warm\" Jupiters, possessing\norbital periods longer than roughly 10 days more often possess close-in,\nco-transiting planetary companions than shorter period \"hot\" Jupiters, that are\nusually lonely. This finding has previously been interpreted as evidence that\nsmooth, early migration or in situ formation gave rise to warm Jupiter-hosting\nsystems, whereas more violent, post-disk migration pathways sculpted hot\nJupiter-hosting systems. In this work, we demonstrate that both classes of\nplanet may arise via early migration or in-situ conglomeration, but that the\nenhanced loneliness of hot Jupiters arises due to a secular resonant\ninteraction with the stellar quadrupole moment. Such an interaction tilts the\norbits of exterior, lower mass planets, removing them from transit surveys\nwhere the hot Jupiter is detected. Warm Jupiter-hosting systems, in contrast,\nretain their coplanarity due to the weaker influence of the host star's\nquadrupolar potential relative to planet-disk interactions. In this way, hot\nJupiters and warm Jupiters are placed within a unified theoretical framework\nthat may be readily validated or falsified using data from upcoming missions\nsuch as TESS.\n",
"title": "A Secular Resonant Origin for the Loneliness of Hot Jupiters"
}
| null | null |
[
"Physics"
] | null | true | null |
3473
| null |
Validated
| null | null |
null |
{
"abstract": " Several applications of slicing require a program to be sliced with respect\nto more than one slicing criterion. Program specialization, parallelization and\ncohesion measurement are examples of such applications. These applications can\nbenefit from an incremental static slicing method in which a significant extent\nof the computations for slicing with respect to one criterion could be reused\nfor another. In this paper, we consider the problem of incremental slicing of\nfunctional programs. We first present a non-incremental version of the slicing\nalgorithm which does a polyvariant analysis 1 of functions. Since polyvariant\nanalyses tend to be costly, we compute a compact context-independent summary of\neach function and then use this summary at the call sites of the function. The\nconstruction of the function summary is non-trivial and helps in the\ndevelopment of the incremental version. The incremental method, on the other\nhand, consists of a one-time pre-computation step that uses the non-incremental\nversion to slice the program with respect to a fixed default slicing criterion\nand processes the results further to a canonical form. Presented with an actual\nslicing criterion, the incremental step involves a low-cost computation that\nuses the results of the pre-computation to obtain the slice. We have\nimplemented a prototype of the slicer for a pure subset of Scheme, with pairs\nand lists as the only algebraic data types. Our experiments show that the\nincremental step of the slicer runs orders of magnitude faster than the\nnon-incremental version. We have also proved the correctness of our incremental\nalgorithm with respect to the non-incremental version.\n",
"title": "An Incremental Slicing Method for Functional Programs"
}
| null | null |
[
"Computer Science"
] | null | true | null |
3474
| null |
Validated
| null | null |
null |
{
"abstract": " Physicists at the Large Hadron Collider (LHC) rely on detailed simulations of\nparticle collisions to build expectations of what experimental data may look\nlike under different theory modeling assumptions. Petabytes of simulated data\nare needed to develop analysis techniques, though they are expensive to\ngenerate using existing algorithms and computing resources. The modeling of\ndetectors and the precise description of particle cascades as they interact\nwith the material in the calorimeter are the most computationally demanding\nsteps in the simulation pipeline. We therefore introduce a deep neural\nnetwork-based generative model to enable high-fidelity, fast, electromagnetic\ncalorimeter simulation. There are still challenges for achieving precision\nacross the entire phase space, but our current solution can reproduce a variety\nof particle shower properties while achieving speed-up factors of up to\n100,000$\\times$. This opens the door to a new era of fast simulation that could\nsave significant computing time and disk space, while extending the reach of\nphysics searches and precision measurements at the LHC and beyond.\n",
"title": "Accelerating Science with Generative Adversarial Networks: An Application to 3D Particle Showers in Multi-Layer Calorimeters"
}
| null | null | null | null | true | null |
3475
| null |
Default
| null | null |
null |
{
"abstract": " We study ancient Khmer ephemerides described in 1910 by the French engineer\nFaraut, in order to determine whether they rely on observations carried out in\nCambodia. These ephemerides were found to be of Indian origin and have been\nadapted for another longitude, most likely in Burma. A method for estimating\nthe date and place where the ephemerides were developed or adapted is described\nand applied.\n",
"title": "A study of ancient Khmer ephemerides"
}
| null | null | null | null | true | null |
3476
| null |
Default
| null | null |
null |
{
"abstract": " Model-based compression is an effective, facilitating, and expanded model of\nneural network models with limited computing and low power. However,\nconventional models of compression techniques utilize crafted features [2,3,12]\nand explore specialized areas for exploration and design of large spaces in\nterms of size, speed, and accuracy, which usually have returns Less and time is\nup. This paper will effectively analyze deep auto compression (ADC) and\nreinforcement learning strength in an effective sample and space design, and\nimprove the compression quality of the model. The results of compression of the\nadvanced model are obtained without any human effort and in a completely\nautomated way. With a 4- fold reduction in FLOP, the accuracy of 2.8% is higher\nthan the manual compression model for VGG-16 in ImageNet.\n",
"title": "Auto Deep Compression by Reinforcement Learning Based Actor-Critic Structure"
}
| null | null | null | null | true | null |
3477
| null |
Default
| null | null |
null |
{
"abstract": " Matrix factorisation methods decompose multivariate observations as linear\ncombinations of latent feature vectors. The Indian Buffet Process (IBP)\nprovides a way to model the number of latent features required for a good\napproximation in terms of regularised reconstruction error. Previous work has\nfocussed on latent feature vectors with independent entries. We extend the\nmodel to include nondiagonal latent covariance structures representing\ncharacteristics such as smoothness. This is done by . Using simulations we\ndemonstrate that under appropriate conditions a smoothness prior helps to\nrecover the true latent features, while denoising more accurately. We\ndemonstrate our method on a real neuroimaging dataset, where computational\ntractability is a sufficient challenge that the efficient strategy presented\nhere is essential.\n",
"title": "Infinite Sparse Structured Factor Analysis"
}
| null | null | null | null | true | null |
3478
| null |
Default
| null | null |
null |
{
"abstract": " Developers often try to find occurrences of a certain term in a software\nsystem. Traditionally, a text search is limited to static source code files. In\nthis paper, we introduce a simple approach, RuntimeSearch, where the given term\nis searched in the values of all string expressions in a running program. When\na match is found, the program is paused and its runtime properties can be\nexplored with a traditional debugger. The feasibility and usefulness of\nRuntimeSearch is demonstrated on a medium-sized Java project.\n",
"title": "RuntimeSearch: Ctrl+F for a Running Program"
}
| null | null |
[
"Computer Science"
] | null | true | null |
3479
| null |
Validated
| null | null |
null |
{
"abstract": " A new method to improve the accuracy and efficiency of characteristic mode\n(CM) decomposition for perfectly conducting bodies is presented. The method\nuses the expansion of the Green dyadic in spherical vector waves. This\nexpansion is utilized in the method of moments (MoM) solution of the electric\nfield integral equation to factorize the real part of the impedance matrix. The\nfactorization is then employed in the computation of CMs, which improves the\naccuracy as well as the computational speed. An additional benefit is a rapid\ncomputation of far fields. The method can easily be integrated into existing\nMoM solvers. Several structures are investigated illustrating the improved\naccuracy and performance of the new method.\n",
"title": "Accurate and Efficient Evaluation of Characteristic Modes"
}
| null | null | null | null | true | null |
3480
| null |
Default
| null | null |
null |
{
"abstract": " We examine the growth and evolution of quenched galaxies in the Mufasa\ncosmological hydrodynamic simulations that include an evolving halo mass-based\nquenching prescription, with galaxy colours computed accounting for\nline-of-sight extinction to individual star particles. Mufasa reproduces the\nobserved present-day red sequence reasonably well, including its slope,\namplitude, and scatter. In Mufasa, the red sequence slope is driven entirely by\nthe steep stellar mass-stellar metallicity relation, which independently agrees\nwith observations. High-mass star-forming galaxies blend smoothly onto the red\nsequence, indicating the lack of a well-defined green valley at M*>10^10.5 Mo.\nThe most massive galaxies quench the earliest and then grow very little in mass\nvia dry merging; they attain their high masses at earlier epochs when cold\ninflows more effectively penetrate hot halos. To higher redshifts, the red\nsequence becomes increasingly contaminated with massive dusty star-forming\ngalaxies; UVJ selection subtly but effectively separates these populations. We\nthen examine the evolution of the mass functions of central and satellite\ngalaxies split into passive and star-forming via UVJ. Massive quenched systems\nshow good agreement with observations out to z~2, despite not including a rapid\nearly quenching mode associated with mergers. However, low-mass quenched\ngalaxies are far too numerous at z<1 in Mufasa, indicating that Mufasa strongly\nover-quenches satellites. A challenge for hydrodynamic simulations is to devise\na quenching model that produces enough early massive quenched galaxies and\nkeeps them quenched to z=0, while not being so strong as to over-quench\nsatellites; Mufasa's current scheme fails at the latter.\n",
"title": "MUFASA: The assembly of the red sequence"
}
| null | null |
[
"Physics"
] | null | true | null |
3481
| null |
Validated
| null | null |
null |
{
"abstract": " We study $SU(2)$ calorons, also known as periodic instantons, and consider\ninvariance under isometries of $S^1\\times\\mathbb{R}^3$ coupled with a\nnon-spatial isometry called the rotation map. In particular, we investigate the\nfixed points under various cyclic symmetry groups. Our approach utilises a\nconstruction akin to the ADHM construction of instantons -- what we call the\nmonad matrix data for calorons -- derived from the work of Charbonneau and\nHurtubise. To conclude, we present an example of how investigating these\nsymmetry groups can help to construct new calorons by deriving Nahm data in the\ncase of charge $2$.\n",
"title": "Symmetric calorons and the rotation map"
}
| null | null |
[
"Mathematics"
] | null | true | null |
3482
| null |
Validated
| null | null |
null |
{
"abstract": " Natural disasters can have catastrophic impacts on the functionality of\ninfrastructure systems and cause severe physical and socio-economic losses.\nGiven budget constraints, it is crucial to optimize decisions regarding\nmitigation, preparedness, response, and recovery practices for these systems.\nThis requires accurate and efficient means to evaluate the infrastructure\nsystem reliability. While numerous research efforts have addressed and\nquantified the impact of natural disasters on infrastructure systems, typically\nusing the Monte Carlo approach, they still suffer from high computational cost\nand, thus, are of limited applicability to large systems. This paper presents a\ndeep learning framework for accelerating infrastructure system reliability\nanalysis. In particular, two distinct deep neural network surrogates are\nconstructed and studied: (1) A classifier surrogate which speeds up the\nconnectivity determination of networks, and (2) An end-to-end surrogate that\nreplaces a number of components such as roadway status realization,\nconnectivity determination, and connectivity averaging. The proposed approach\nis applied to a simulation-based study of the two-terminal connectivity of a\nCalifornia transportation network subject to extreme probabilistic earthquake\nevents. Numerical results highlight the effectiveness of the proposed approach\nin accelerating the transportation system two-terminal reliability analysis\nwith extremely high prediction accuracy.\n",
"title": "Deep Learning for Accelerated Reliability Analysis of Infrastructure Networks"
}
| null | null | null | null | true | null |
3483
| null |
Default
| null | null |
null |
{
"abstract": " The Simultaneous Localization And Mapping (SLAM) problem has been well\nstudied in the robotics community, especially using mono, stereo cameras or\ndepth sensors. 3D depth sensors, such as Velodyne LiDAR, have proved in the\nlast 10 years to be very useful to perceive the environment in autonomous\ndriving, but few methods exist that directly use these 3D data for odometry. We\npresent a new low-drift SLAM algorithm based only on 3D LiDAR data. Our method\nrelies on a scan-to-model matching framework. We first have a specific sampling\nstrategy based on the LiDAR scans. We then define our model as the previous\nlocalized LiDAR sweeps and use the Implicit Moving Least Squares (IMLS) surface\nrepresentation. We show experiments with the Velodyne HDL32 with only 0.40%\ndrift over a 4 km acquisition without any loop closure (i.e., 16 m drift after\n4 km). We tested our solution on the KITTI benchmark with a Velodyne HDL64 and\nranked among the best methods (against mono, stereo and LiDAR methods) with a\nglobal drift of only 0.69%.\n",
"title": "IMLS-SLAM: scan-to-model matching based on 3D data"
}
| null | null | null | null | true | null |
3484
| null |
Default
| null | null |
null |
{
"abstract": " We study an asynchronous online learning setting with a network of agents. At\neach time step, some of the agents are activated, requested to make a\nprediction, and pay the corresponding loss. The loss function is then revealed\nto these agents and also to their neighbors in the network. When activations\nare stochastic, we show that the regret achieved by $N$ agents running the\nstandard online Mirror Descent is $O(\\sqrt{\\alpha T})$, where $T$ is the\nhorizon and $\\alpha \\le N$ is the independence number of the network. This is\nin contrast to the regret $\\Omega(\\sqrt{N T})$ which $N$ agents incur in the\nsame setting when feedback is not shared. We also show a matching lower bound\nof order $\\sqrt{\\alpha T}$ that holds for any given network. When the pattern\nof agent activations is arbitrary, the problem changes significantly: we prove\na $\\Omega(T)$ lower bound on the regret that holds for any online algorithm\noblivious to the feedback source.\n",
"title": "Cooperative Online Learning: Keeping your Neighbors Updated"
}
| null | null |
[
"Computer Science",
"Statistics"
] | null | true | null |
3485
| null |
Validated
| null | null |
null |
{
"abstract": " Convolutional neural networks (CNNs) have massively impacted visual\nrecognition in 2D images, and are now ubiquitous in state-of-the-art\napproaches. CNNs do not easily extend, however, to data that are not\nrepresented by regular grids, such as 3D shape meshes or other graph-structured\ndata, to which traditional local convolution operators do not directly apply.\nTo address this problem, we propose a novel graph-convolution operator to\nestablish correspondences between filter weights and graph neighborhoods with\narbitrary connectivity. The key novelty of our approach is that these\ncorrespondences are dynamically computed from features learned by the network,\nrather than relying on predefined static coordinates over the graph as in\nprevious work. We obtain excellent experimental results that significantly\nimprove over previous state-of-the-art shape correspondence results. This shows\nthat our approach can learn effective shape representations from raw input\ncoordinates, without relying on shape descriptors.\n",
"title": "FeaStNet: Feature-Steered Graph Convolutions for 3D Shape Analysis"
}
| null | null |
[
"Computer Science"
] | null | true | null |
3486
| null |
Validated
| null | null |
null |
{
"abstract": " We study Brauer's long-standing $k(B)$-conjecture on the number of characters\nin $p$-blocks for finite quasi-simple groups and show that their blocks do not\noccur as a minimal counterexample for $p\\ge5$ nor in the case of abelian\ndefect. For $p=3$ we obtain that the principal 3-blocks do not provide minimal\ncounterexamples. We also determine the precise number of irreducible characters\nin unipotent blocks of classical groups for odd primes.\n",
"title": "On a minimal counterexample to Brauer's $k(B)$-conjecture"
}
| null | null | null | null | true | null |
3487
| null |
Default
| null | null |
null |
{
"abstract": " The Sloan Digital Sky Survey (SDSS) is the first dense redshift survey\nencompassing a volume large enough to find the best analytic probability\ndensity function that fits the galaxy Counts-in-Cells distribution $f_V(N)$,\nthe frequency distribution of galaxy counts in a volume $V$. Different analytic\nfunctions have been previously proposed that can account for some of the\nobserved features of the observed frequency counts, but fail to provide an\noverall good fit to this important statistical descriptor of the galaxy\nlarge-scale distribution. Our goal is to find the probability density function\nthat better fits the observed Counts-in-Cells distribution $f_V(N)$. We have\nmade a systematic study of this function applied to several samples drawn from\nthe SDSS. We show the effective ways to deal with incompleteness of the sample\n(masked data) in the calculation of $f_V(N)$. We use LasDamas simulations to\nestimate the errors in the calculation. We test four different distribution\nfunctions to find the best fit: the Gravitational Quasi-Equilibrium\ndistribution, the Negative Binomial Distribution, the Log Normal distribution\nand the Log Normal Distribution including a bias parameter. In the two latter\ncases, we apply a shot-noise correction to the distributions assuming the local\nPoisson model. We show that the best fit for the Counts-in-Cells distribution\nfunction is provided by the Negative Binomial distribution. In addition, at\nlarge scales the Log Normal distribution modified with the inclusion of the\nbias term also performs a satisfactory fit of the empirical values of $f_V(N)$.\nOur results demonstrate that the inclusion of a bias term in the Log Normal\ndistribution is necessary to fit the observed galaxy Count-in-Cells\ndistribution function.\n",
"title": "The best fit for the observed galaxy Counts-in-Cell distribution function"
}
| null | null |
[
"Physics"
] | null | true | null |
3488
| null |
Validated
| null | null |
null |
{
"abstract": " We compare a global high resolution resistive magnetohydrodynamics (MHD)\nsimulation of Earth's magnetosphere with observations from the Magnetospheric\nMultiscale (MMS) constellation for a southward IMF magnetopause crossing during\nOctober 16, 2015 that was previously identified as an electron diffusion region\n(EDR) event. The simulation predicts a complex time-dependent magnetic topology\nconsisting of multiple separators and flux ropes. Despite the topological\ncomplexity, the predicted distance between MMS and the primary separator is\nless than 0.5 Earth radii. These results suggest that global magnetic topology,\nrather than local magnetic geometry alone, determines the location of the\nelectron diffusion region at the dayside magnetopause.\n",
"title": "Separator Reconnection at Earth's Dayside Magnetopause: MMS Observations Compared to Global Simulations"
}
| null | null |
[
"Physics"
] | null | true | null |
3489
| null |
Validated
| null | null |
null |
{
"abstract": " Algorithms for detecting communities in complex networks are generally\nunsupervised, relying solely on the structure of the network. However, these\nmethods can often fail to uncover meaningful groupings that reflect the\nunderlying communities in the data, particularly when those structures are\nhighly overlapping. One way to improve the usefulness of these algorithms is by\nincorporating additional background information, which can be used as a source\nof constraints to direct the community detection process. In this work, we\nexplore the potential of semi-supervised strategies to improve algorithms for\nfinding overlapping communities in networks. Specifically, we propose a new\nmethod, based on label propagation, for finding communities using a limited\nnumber of pairwise constraints. Evaluations on synthetic and real-world\ndatasets demonstrate the potential of this approach for uncovering meaningful\ncommunity structures in cases where each node can potentially belong to more\nthan one community.\n",
"title": "Semi-Supervised Overlapping Community Finding based on Label Propagation with Pairwise Constraints"
}
| null | null | null | null | true | null |
3490
| null |
Default
| null | null |
null |
{
"abstract": " This paper investigates reverse auctions that involve continuous values of\ndifferent types of goods, general nonconvex constraints, and second stage\ncosts. We seek to design the payment rules and conditions under which\ncoalitions of participants cannot influence the auction outcome in order to\nobtain higher collective utility. Under the incentive-compatible\nVickrey-Clarke-Groves mechanism, we show that coalition-proof outcomes are\nachieved if the submitted bids are convex and the constraint sets are of a\npolymatroid-type. These conditions, however, do not capture the complexity of\nthe general class of reverse auctions under consideration. By relaxing the\nproperty of incentive-compatibility, we investigate further payment rules that\nare coalition-proof without any extra conditions on the submitted bids and the\nconstraint sets. Since calculating the payments directly for these mechanisms\nis computationally difficult for auctions involving many participants, we\npresent two computationally efficient methods. Our results are verified with\nseveral case studies based on electricity market data.\n",
"title": "Designing Coalition-Proof Reverse Auctions over Continuous Goods"
}
| null | null | null | null | true | null |
3491
| null |
Default
| null | null |
null |
{
"abstract": " In deterministic optimization, line searches are a standard tool ensuring\nstability and efficiency. Where only stochastic gradients are available, no\ndirect equivalent has so far been formulated, because uncertain gradients do\nnot allow for a strict sequence of decisions collapsing the search space. We\nconstruct a probabilistic line search by combining the structure of existing\ndeterministic methods with notions from Bayesian optimization. Our method\nretains a Gaussian process surrogate of the univariate optimization objective,\nand uses a probabilistic belief over the Wolfe conditions to monitor the\ndescent. The algorithm has very low computational cost, and no user-controlled\nparameters. Experiments show that it effectively removes the need to define a\nlearning rate for stochastic gradient descent.\n",
"title": "Probabilistic Line Searches for Stochastic Optimization"
}
| null | null |
[
"Computer Science",
"Statistics"
] | null | true | null |
3492
| null |
Validated
| null | null |
null |
{
"abstract": " Hydrogen (H)-doped LaFeAsO is a prototypical iron-based superconductor.\nHowever, its phase diagram extends beyond the standard framework, where a\nsuperconducting (SC) phase follows an antiferromagnetic (AF) phase upon carrier\ndoping; instead, the SC phase is sandwiched between two AF phases appearing in\nlightly and heavily H-doped regimes. We performed nuclear magnetic resonance\n(NMR) measurements under pressure, focusing on the second AF phase in the\nheavily H-doped regime. The second AF phase is strongly suppressed when a\npressure of 3.0 GPa is applied, and apparently shifts to a highly H-doped\nregime, thereby a \"bare\" quantum critical point (QCP) emerges. A quantum\ncritical regime emerges in a paramagnetic state near the QCP, however, the\ninfluence of the AF critical fluctuations to the SC phase is limited in the\nnarrow doping regime near the QCP. The optimal SC condition ($T_c \\sim$ 48 K)\nis unaffected by AF fluctuations.\n",
"title": "Quantum Phase transition under pressure in a heavily hydrogen-doped iron-based superconductor LaFeAsO"
}
| null | null | null | null | true | null |
3493
| null |
Default
| null | null |
null |
{
"abstract": " We consider co-rotational wave maps from (1+3)-dimensional Minkowski space\ninto the three-sphere. This model exhibits an explicit blowup solution and we\nprove the asymptotic nonlinear stability of this solution in the whole space\nunder small perturbations of the initial data. The key ingredient is the\nintroduction of a novel coordinate system that allows one to track the\nevolution past the blowup time and almost up to the Cauchy horizon of the\nsingularity. As a consequence, we also obtain a result on continuation beyond\nblowup.\n",
"title": "Hyperboloidal similarity coordinates and a globally stable blowup profile for supercritical wave maps"
}
| null | null | null | null | true | null |
3494
| null |
Default
| null | null |
null |
{
"abstract": " We consider a closed chain of even number of Majorana zero modes with\nnearest-neighbour couplings which are different site by site generically, thus\nno any crystal symmetry. Instead, we demonstrate the possibility of an emergent\nsupersymmetry (SUSY), which is accompanied by gapless Fermionic excitations. In\nparticular, the condition can be easily satisfied by tuning only one coupling,\nregardless of how many other couplings are there. Such a system can be realized\nby four Majorana modes on two parallel Majorana nanowires with their ends\nconnected by Josephson junctions and bodies connected by an external\nsuperconducting ring. By tuning the Josephson couplings with a magnetic flux\n$\\Phi$ through the ring, we get the gapless excitations at $\\Phi_{SUSY}=\\pm\nf\\Phi_0$ with $\\Phi_0= hc/2e$, which is signaled by a zero-bias conductance\npeak in tunneling conductance. We find this $f$ generally a fractional number\nand oscillating with increasing Zeeman fields that parallel to the nanowires,\nwhich provide a unique experimental signature for the existence of Majorana\nmodes.\n",
"title": "Supersymmetry in Closed Chains of Coupled Majorana Modes"
}
| null | null | null | null | true | null |
3495
| null |
Default
| null | null |
null |
{
"abstract": " We construct non-semisimple $2+1$-TQFTs yielding mapping class group\nrepresentations in Lyubashenko's spaces. In order to do this, we first\ngeneralize Beliakova, Blanchet and Geer's logarithmic Hennings invariants based\non quantum $\\mathfrak{sl}_2$ to the setting of finite-dimensional\nnon-degenerate unimodular ribbon Hopf algebras. The tools used for this\nconstruction are a Hennings-augmented Reshetikhin-Turaev functor and modified\ntraces. When the Hopf algebra is factorizable, we further show that the\nuniversal construction of Blanchet, Habegger, Masbaum and Vogel produces a\n$2+1$-TQFT on a not completely rigid monoidal subcategory of cobordisms.\n",
"title": "Renormalized Hennings Invariants and 2+1-TQFTs"
}
| null | null | null | null | true | null |
3496
| null |
Default
| null | null |
null |
{
"abstract": " Deep Reinforcement Learning (RL) recently emerged as one of the most\ncompetitive approaches for learning in sequential decision making problems with\nfully observable environments, e.g., computer Go. However, very little work has\nbeen done in deep RL to handle partially observable environments. We propose a\nnew architecture called Action-specific Deep Recurrent Q-Network (ADRQN) to\nenhance learning performance in partially observable domains. Actions are\nencoded by a fully connected layer and coupled with a convolutional observation\nto form an action-observation pair. The time series of action-observation pairs\nare then integrated by an LSTM layer that learns latent states based on which a\nfully connected layer computes Q-values as in conventional Deep Q-Networks\n(DQNs). We demonstrate the effectiveness of our new architecture in several\npartially observable domains, including flickering Atari games.\n",
"title": "On Improving Deep Reinforcement Learning for POMDPs"
}
| null | null | null | null | true | null |
3497
| null |
Default
| null | null |
null |
{
"abstract": " Games of timing aim to determine the optimal defense against a strategic\nattacker who has the technical capability to breach a system in a stealthy\nfashion. Key questions arising are when the attack takes place, and when a\ndefensive move should be initiated to reset the system resource to a known safe\nstate.\nIn our work, we study a more complex scenario called Time-Based Security in\nwhich we combine three main notions: protection time, detection time, and\nreaction time. Protection time represents the amount of time the attacker needs\nto execute the attack successfully. In other words, protection time represents\nthe inherent resilience of the system against an attack. Detection time is the\nrequired time for the defender to detect that the system is compromised.\nReaction time is the required time for the defender to reset the defense\nmechanisms in order to recreate a safe system state.\nIn the first part of the paper, we study the VERIS Community Database (VCDB)\nand screen other data sources to provide insights into the actual timing of\nsecurity incidents and responses. While we are able to derive distributions for\nsome of the factors regarding the timing of security breaches, we assess the\nstate-of-the-art regarding the collection of timing-related data as\ninsufficient.\nIn the second part of the paper, we propose a two-player game which captures\nthe outlined Time-Based Security scenario in which both players move according\nto a periodic strategy. We carefully develop the resulting payoff functions,\nand provide theorems and numerical results to help the defender to calculate\nthe best time to reset the defense mechanism by considering protection time,\ndetection time, and reaction time.\n",
"title": "When to Invest in Security? Empirical Evidence and a Game-Theoretic Approach for Time-Based Security"
}
| null | null |
[
"Computer Science"
] | null | true | null |
3498
| null |
Validated
| null | null |
null |
{
"abstract": " Humans are not only adept in recognizing what class an input instance belongs\nto (i.e., classification task), but perhaps more remarkably, they can imagine\n(i.e., generate) plausible instances of a desired class with ease, when\nprompted. Inspired by this, we propose a framework which allows transforming\nCascade-Correlation Neural Networks (CCNNs) into probabilistic generative\nmodels, thereby enabling CCNNs to generate samples from a category of interest.\nCCNNs are a well-known class of deterministic, discriminative NNs, which\nautonomously construct their topology, and have been successful in giving\naccounts for a variety of psychological phenomena. Our proposed framework is\nbased on a Markov Chain Monte Carlo (MCMC) method, called the\nMetropolis-adjusted Langevin algorithm, which capitalizes on the gradient\ninformation of the target distribution to direct its explorations towards\nregions of high probability, thereby achieving good mixing properties. Through\nextensive simulations, we demonstrate the efficacy of our proposed framework.\n",
"title": "Converting Cascade-Correlation Neural Nets into Probabilistic Generative Models"
}
| null | null | null | null | true | null |
3499
| null |
Default
| null | null |
null |
{
"abstract": " A new semiclassical \"divide-and-conquer\" method is presented with the aim of\ndemonstrating that quantum dynamics simulations of high dimensional molecular\nsystems are doable. The method is first tested by calculating the quantum\nvibrational power spectra of water, methane, and benzene - three molecules of\nincreasing dimensionality for which benchmark quantum results are available -\nand then applied to C60, a system characterized by 174 vibrational degrees of\nfreedom. Results show that the approach can accurately account for quantum\nanharmonicities, purely quantum features like overtones, and the removal of\ndegeneracy when the molecular symmetry is broken.\n",
"title": "Semiclassical \"Divide-and-Conquer\" Method for Spectroscopic Calculations of High Dimensional Molecular Systems"
}
| null | null | null | null | true | null |
3500
| null |
Default
| null | null |
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