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A nanoring-rotaxane supramolecular assembly, with a Cy7 cyanine dye (hexamethylindotricarbocyanine) threaded along the axis of the nanoring, has been synthesized as a model for the energy transfer between the light harvesting complex LH1 and the reaction center in purple bacteria photosynthesis. The complex displays efficient energy transfer from the central cyanine dye to the surrounding zinc porphyrin nanoring. We present a theoretical model that reproduces the absorption spectrum of the nanoring and quantifies the excitonic coupling between the nanoring and the central dye, explaining the efficient energy transfer and elucidating the similarity with structurally related natural light harvesting systems. | physics |
We present a new constraint on the Lyman Continuum (LyC) escape fraction at z~1.3. We obtain deep, high sensitivity far-UV imaging with the Advanced Camera for Surveys (ACS) Solar Blind Channel (SBC) on the Hubble Space Telescope (HST), targeting 11 star-forming galaxies at 1.2<z<1.4. The galaxies are selected from the 3D-HST survey to have high H$\alpha$ equivalent width (EW) with EW > 190 \AA, low stellar mass (M* < 10^10 M_sun) and U-band magnitude of U<24.2. These criteria identify young, low metallicity star bursting populations similar to the primordial star-forming galaxies believed to have reionized the universe. We do not detect any LyC signal (with S/N >3) in the individual galaxies or in the stack in the far-UV images. We place $3\sigma$ limits on the relative escape fraction of individual galaxies to be f_{esc,rel}<[0.10-0.22] and a stacked $3\sigma$ limit of f_{esc,rel}<0.07. Comparing to the confirmed LyC emitters from the literature, the galaxies in our sample span similar ranges of various galaxy properties including stellar mass, dust attenuation, and star formation rate (SFR). In particular, we compare the distribution of H$\alpha$ and [OIII] EWs of confirmed LyC emitters and non-detections including the galaxies in this study. Finally, we discuss if a dichotomy seen in the distribution of H$\alpha$ EWs can perhaps distinguish the LyC emitters from the non-detections. | astrophysics |
Tagged kaon beams are attractive neutrino sources, which would provide flavor pure $\nu_e$-beams with exactly measured normalization. We point out that this also leads to an anti-tagged flavor pure $\nu_\mu$-beam, with equally well known normalization. Exposing a 1 kt liquid argon detector at a baseline of 1 km to this combination of unique beams allows to decisively test recent indications by IceCube and Neutrino-4 of sterile neutrino oscillations in the multi-eV range. | high energy physics phenomenology |
Strong and weak (1, 3) homotopies are equivalence relations on knot projections, defined by the first flat Reidemeister move and each of two different types of the third flat Reidemeister moves. In this paper, we introduce the cross chord number that is the minimal number of double points of chords of a chord diagram. Cross chord numbers induce a strong (1, 3) invariant. We show that Hanaki's trivializing number is a weak (1, 3) invariant. We give a complete classification of knot projections having trivializing number two up to the first flat Reidemeister moves using cross chord numbers and the positive resolutions of double points. Two knot projections with trivializing number two are both weak (1, 3) homotopy equivalent and strong (1, 3) homotopy equivalent if and only if they can be related by only the first flat Reidemeister moves. Finally, we determine the strong (1, 3) homotopy equivalence class containing the trivial knot projection and other classes of knot projections. | mathematics |
Higgsplosion is the mechanism that leads to exponentially growing decay rates of highly energetic particles into states with very high numbers of relatively soft Higgs bosons. In this paper we study quantum effects in the presence of Higgsplosion. First, we provide a non-perturbative definition of Higgsplosion as a resolved short-distance singularity of quantum propagators at distances shorter than the inverse Higgsplosion energy scale, $E_*$. We then consider quantum effects arising from loops in perturbation theory with these propagators on internal lines. When the loop momenta exceed the Higgsplosion scale $E_*$, the theory dynamics deviates from what is expected in the standard QFT settings without Higgsplosion. The UV divergences are automatically regulated by the Higgsplosion scale, leading to the change of slopes for the running couplings at the RG scales $\mu > E_*$. Thus, the theory becomes asymptotically safe. Further, we find that the finite parts are also modified and receive power-suppressed corrections in $1/E_*^2$. We use these results to compute a set of precision observables for the Higgsploding Standard Model. These and other precision observables could provide experimental evidence and tests for the existence of Higgsplosion in particle physics. | high energy physics phenomenology |
A signed graph is a pair $(G,\Sigma)$, where $G=(V,E)$ is a graph (in which parallel edges are permitted, but loops are not) with $V=\{1,\ldots,n\}$ and $\Sigma\subseteq E$. The edges in $\Sigma$ are called odd and the other edges of $E$ even. By $S(G,\Sigma)$ we denote the set of all symmetric $n\times n$ matrices $A=[a_{i,j}]$ with $a_{i,j}<0$ if $i$ and $j$ are adjacent and connected by only even edges, $a_{i,j}>0$ if $i$ and $j$ are adjacent and connected by only odd edges, $a_{i,j}\in \mathbb{R}$ if $i$ and $j$ are connected by both even and odd edges, $a_{i,j}=0$ if $i\not=j$ and $i$ and $j$ are non-adjacent, and $a_{i,i} \in \mathbb{R}$ for all vertices $i$. The parameters $M(G,\Sigma)$ and $\xi(G,\Sigma)$ of a signed graph $(G,\Sigma)$ are the largest nullity of any matrix $A\in S(G,\Sigma)$ and the largest nullity of any matrix $A\in S(G,\Sigma)$ that has the Strong Arnold Hypothesis, respectively. In a previous paper, we gave a characterization of signed graphs $(G,\Sigma)$ with $M(G,\Sigma)\leq 1$ and of signed graphs with $\xi(G,\Sigma)\leq 1$. In this paper, we characterize the $2$-connected signed graphs $(G,\Sigma)$ with $M(G,\Sigma)\leq 2$ and the $2$-connected signed graphs $(G,\Sigma)$ with $\xi(G,\Sigma)\leq 2$. | mathematics |
Demixing of multicomponent biomolecular systems via liquid-liquid phase separation (LLPS) has emerged as a potentially unifying mechanism governing the formation of several membrane-less intracellular organelles ("condensates"), both in the cytoplasm (e.g., stress granules) and in the nucleoplasm (e.g., nucleoli). While both in vivo experiments and studies of synthetic systems demonstrate that LLPS is strongly affected by the presence of a macromolecular elastic network, a fundamental understanding of the role of such networks on LLPS is still lacking. Here we show that, upon accounting for capillary forces responsible for network expulsion, small-scale heterogeneity of the network, and its nonlinear mechanical properties, an intriguing picture of LLPS emerges. Specifically, we predict that, in addition to the experimentally observed cavitated droplets which fully exclude the network, two other phases are thermodynamically possible: elastically arrested, size-limited droplets at the network pore scale, and network-including macroscopic droplets. In particular, pore size-limited droplets may emerge in chromatin networks, with implications for structure and function of nucleoplasmic condensates. | condensed matter |
This article derives lower bounds on the convergence rate of continuous-time gradient-based optimization algorithms. The algorithms are subjected to a time-normalization constraint that avoids a reparametrization of time in order to make the discussion of continuous-time convergence rates meaningful. We reduce the multi-dimensional problem to a single dimension, recover well-known lower bounds from the discrete-time setting, and provide insight into why these lower bounds occur. We present algorithms that achieve the proposed lower bounds, even when the function class under consideration includes certain nonconvex functions. | mathematics |
To achieve the further development of supercapacitors (SCs), which have intensively received attention as a next-generation energy storage system, the rational design of active electrode materials with electrochemically more favorable structure is one of the most important factors to improve the SC performance with high specific energy and power density. We propose and successfully grow copper sulfide (CuS) nanowires (NWs) as a chalcogenide-based electrode material directly on a Cu mesh current collector using the combination of a facile liquid-solid chemical oxidation process and an anion exchange reaction. We found that the as-prepared CuS NWs have well-arrayed structures with nanosized crystal grains, a high aspect ratio and density, as well as a good mechanical and electrical contact to the Cu mesh. The obtained CuS NW based electrodes, with additional binder- and conductive material-free, exhibit a much higher areal capacitance of 378.0 mF/cm2 and excellent cyclability of an approximately 90.2 percentage retention during 2000 charge/discharge cycles due to their unique structural, electrical, and electrochemical properties. Furthermore, for practical SC applications, an asymmetric supercapacitor is fabricated using active carbon as an anode and CuS NWs as a cathode, and exhibits the good capacitance retention of 91% during 2000 charge/discharge processes and the excellent volumetric energy density of 1.11 mW h/cm3 compared to other reported pseudo-capacitive SCs. | physics |
Saliency methods have emerged as a popular tool to highlight features in an input deemed relevant for the prediction of a learned model. Several saliency methods have been proposed, often guided by visual appeal on image data. In this work, we propose an actionable methodology to evaluate what kinds of explanations a given method can and cannot provide. We find that reliance, solely, on visual assessment can be misleading. Through extensive experiments we show that some existing saliency methods are independent both of the model and of the data generating process. Consequently, methods that fail the proposed tests are inadequate for tasks that are sensitive to either data or model, such as, finding outliers in the data, explaining the relationship between inputs and outputs that the model learned, and debugging the model. We interpret our findings through an analogy with edge detection in images, a technique that requires neither training data nor model. Theory in the case of a linear model and a single-layer convolutional neural network supports our experimental findings. | computer science |
Commercial Adaptive Cruise Control (ACC) systems are increasingly available as standard options in modern vehicles. At the same time, still little information is openly available on how these systems actually operate and how different is their behavior, depending on the vehicle manufacturer or model.T o reduce this gap, the present paper summarizes the main features of the openACC, an open-access database of different car-following experiments involving a total of 16 vehicles, 11 of which equipped with state-of-the-art commercial ACC systems. As more test campaigns will be carried out by the authors, OpenACC will evolve accordingly. The activity is performed within the framework of the openData policy of the European Commission Joint Research Centre with the objective to engage the whole scientific community towards a better understanding of the properties of ACC vehicles in view of anticipating their possible impacts on traffic flow and prevent possible problems connected to their widespread. A first preliminary analysis on the properties of the 11 ACC systems is conducted in order to showcase the different research topics that can be studied within this open science initiative. | electrical engineering and systems science |
We give theoretical predictions for the radio emission of a dark matter candidate annihilating into 2-lepton and 4-lepton final states. We then compare our results with the known radio measurements of the sky temperature as a function of the frequency. In particular, we calculate the radio emission for some dark matter candidates annihilating into intermediate bosons that subsequently decay into a 4-lepton channel with a thermal annihilation cross-section. We show that within the range of frequencies from $20\,{\rm MHz}$ to $5\,{\rm GHz}$, this channel can produce a stronger signature than direct annihilation into leptons. | high energy physics phenomenology |
A model of the three-dimensional rotating compressible Euler equations on the cubed sphere is presented. The model uses a mixed mimetic spectral element discretization which allows for the exact exchanges of kinetic, internal and potential energy via the compatibility properties of the chosen function spaces. A Strang carryover dimensional splitting procedure is used, with the horizontal dynamics solved explicitly and the vertical dynamics solved implicitly so as to avoid the CFL restriction of the vertical sound waves. The function spaces used to represent the horizontal dynamics are discontinuous across vertical element boundaries, such that each horizontal layer is solved independently so as to avoid the need to invert a global 3D mass matrix, while the function spaces used to represent the vertical dynamics are similarly discontinuous across horizontal element boundaries, allowing for the serial solution of the vertical dynamics independently for each horizontal element. The model is validated against standard test cases for baroclinic instability within an otherwise hydrostatically and geostrophically balanced atmosphere, and a non-hydrostatic gravity wave as driven by a temperature perturbation. | mathematics |
The present work investigates the relations between amplitude and type of collaboration (intramural, extramural domestic or international) and output of specialized versus diversified research. By specialized or diversified research, we mean within or beyond the author's dominant research topic. The field of observation is the scientific production over five years from about 23,500 academics. The analyses are conducted at the aggregate and disciplinary level. The results lead to the conclusion that in general, the output of diversified research is no more frequently the fruit of collaboration than is specialized research. At the level of the particular collaboration types, international collaborations weakly underlie the specialized kind of research output; on the contrary, extramural domestic and intramural collaborations are weakly associated with diversified research. While the weakness of association remains, exceptions are observed at the level of the individual disciplines. | computer science |
Information Theory (IT) has been used in Machine Learning (ML) from early days of this field. In the last decade, advances in Deep Neural Networks (DNNs) have led to surprising improvements in many applications of ML. The result has been a paradigm shift in the community toward revisiting previous ideas and applications in this new framework. Ideas from IT are no exception. One of the ideas which is being revisited by many researchers in this new era, is Information Bottleneck (IB); a formulation of information extraction based on IT. The IB is promising in both analyzing and improving DNNs. The goal of this survey is to review the IB concept and demonstrate its applications in deep learning. The information theoretic nature of IB, makes it also a good candidate in showing the more general concept of how IT can be used in ML. Two important concepts are highlighted in this narrative on the subject, i) the concise and universal view that IT provides on seemingly unrelated methods of ML, demonstrated by explaining how IB relates to minimal sufficient statistics, stochastic gradient descent, and variational auto-encoders, and ii) the common technical mistakes and problems caused by applying ideas from IT, which is discussed by a careful study of some recent methods suffering from them. | computer science |
We study a self-similar solution of the kinetic equation describing weak wave turbulence in Bose-Einstein condensates. This solution presumably corresponds to an asymptotic behavior of a spectrum evolving from a broad class of initial data, and it features a non-equilibrium finite-time condensation of the wave spectrum $n(\omega)$ at the zero frequency $\omega$. The self-similar solution is of the second kind, and it satisfies boundary conditions corresponding to a nonzero constant spectrum (with all its derivative being zero) at $\omega=0$ and a power-law asymptotic $n(\omega) \to \omega^{-x}$ at $\omega \to \infty \;\; x\in \mathbb{R}^+$. Finding it amounts to solving a nonlinear eigenvalue problem, i.e. finding the value $x^*$ of the exponent $x$ for which these two boundary conditions can be satisfied simultaneously. To solve this problem we develop a new high-precision algorithm based on Chebyshev approximations and double exponential formulas for evaluating the collision integral, as well as the iterative techniques for solving the integro-differential equation for the self-similar shape function. This procedures allow to achieve a solution with accuracy $\approx 4.7 \%$ which is realized for $x^* \approx 1.22$. | physics |
We consider a known sequence of dualities involving $4d$ ${\cal N}=1$ theories with $Spin(n)$ gauge groups and use it to construct a new sequence of models exhibiting IR symmetry enhancement. Then, motivated by the observed pattern of IR symmetries we conjecture six-dimensional theories the compactification of which on a Riemann surface yields the $4d$ sequence of models along with their symmetry enhancements, and put them to several consistency checks. | high energy physics theory |
Recent advancements in ultra-low-power machine learning (TinyML) hardware promises to unlock an entirely new class of smart applications. However, continued progress is limited by the lack of a widely accepted benchmark for these systems. Benchmarking allows us to measure and thereby systematically compare, evaluate, and improve the performance of systems and is therefore fundamental to a field reaching maturity. In this position paper, we present the current landscape of TinyML and discuss the challenges and direction towards developing a fair and useful hardware benchmark for TinyML workloads. Furthermore, we present our four benchmarks and discuss our selection methodology. Our viewpoints reflect the collective thoughts of the TinyMLPerf working group that is comprised of over 30 organizations. | computer science |
The off-shell Higgs production in pp -> ZZ at LHC provides at present the most direct measurement of the Higgs width in the absence of beyond the standard model contributions. Here, we analyze the impact of anomalous Z couplings to fermions on the Higgs width determination. We show that, despite these couplings being strongly constrained by the available electroweak precision data, they can substantially affect the Higgs width determination at the LHC Runs 2 and 3. Conversely, in larger integrated luminosities runs, such as those foreseen at the high luminosity LHC and high energy LHC setups, the effect of such anomalous interactions in the Higgs width measurement is minimal. | high energy physics phenomenology |
Lane-change maneuvers are commonly executed by drivers to follow a certain routing plan, overtake a slower vehicle, adapt to a merging lane ahead, etc. However, improper lane change behaviors can be a major cause of traffic flow disruptions and even crashes. While many rule-based methods have been proposed to solve lane change problems for autonomous driving, they tend to exhibit limited performance due to the uncertainty and complexity of the driving environment. Machine learning-based methods offer an alternative approach, as Deep reinforcement learning (DRL) has shown promising success in many application domains including robotic manipulation, navigation, and playing video games. However, applying DRL to autonomous driving still faces many practical challenges in terms of slow learning rates, sample inefficiency, and safety concerns. In this study, we propose an automated lane change strategy using proximal policy optimization-based deep reinforcement learning, which shows great advantages in learning efficiency while still maintaining stable performance. The trained agent is able to learn a smooth, safe, and efficient driving policy to make lane-change decisions (i.e. when and how) in a challenging situation such as dense traffic scenarios. The effectiveness of the proposed policy is validated by using metrics of task success rate and collision rate. The simulation results demonstrate the lane change maneuvers can be efficiently learned and executed in a safe, smooth, and efficient manner. | computer science |
In Bayesian semi-parametric analyses of time-to-event data, non-parametric process priors are adopted for the baseline hazard function or the cumulative baseline hazard function for a given finite partition of the time axis. However, it would be controversial to suggest a general guideline to construct an optimal time partition. While a great deal of research has been done to relax the assumption of the fixed split times for other non-parametric processes, to our knowledge, no methods have been developed for a gamma process prior, which is one of the most widely used in Bayesian survival analysis. In this paper, we propose a new Bayesian framework for proportional hazards models where the cumulative baseline hazard function is modeled a priori by a gamma process. A key feature of the proposed framework is that the number and position of interval cutpoints are treated as random and estimated based on their posterior distributions. | statistics |
Detections from the repeating fast radio burst FRB 121102 are clustered in time, noticeable even in the earliest repeat bursts. Recently, it was argued that the source activity is periodic, suggesting that the clustering reflected a not-yet-identified periodicity. We performed an extensive multi-wavelength campaign with the Effelsberg telescope, the Green Bank telescope and the Arecibo Observatory to shadow the Gran Telescope Canaria (optical), NuSTAR (X-ray) and INTEGRAL (gamma-ray). We detected 36 bursts with Effelsberg, one with a pulse width of 39\,ms, the widest burst ever detected from FRB 121102. With one burst detected during simultaneous NuSTAR observations, we place a 5-$\sigma$ upper limit of $5\times10^{47}$ erg on the 3--79\,keV energy of an X-ray burst counterpart. We tested the periodicity hypothesis using 165-hr of Effelsberg observations and find a periodicity of 161$\pm$5 days. We predict the source to be active from 2020-07-09 to 2020-10-14 and subsequently from 2020-12-17 to 2021-03-24. We compare the wait times between consecutive bursts within a single observation to Weibull and Poisson distributions. We conclude that the strong clustering was indeed a consequence of a periodic activity and show that if the few events with millisecond separation are excluded, the arrival times are Poisson distributed. We model the bursts' cumulative energy distribution with energies from ${\sim}10^{38}$-$10^{39}$ erg and find that it is well described by a power-law with slope of $\gamma=-1.1\pm 0.2$. We propose that a single power-law might be a poor descriptor of the data over many orders of magnitude. | astrophysics |
Cranes come in various sizes and designs to perform different tasks. Depending on their dynamic properties, they can be classified as gantry cranes and rotary cranes. In this paper we will focus on the so called 'knuckle boom' cranes which are among the most common types of rotary cranes. Compared with the other kinds of cranes (e.g. boom cranes, tower cranes, overhead cranes, etc), the study of knuckle cranes is still at an early stage and very few control strategies for this kind of crane have been proposed in the literature. Although fairly simple mechanically, from the control viewpoint the knuckle cranes present several challenges. A first result of this paper is to present for the first time a complete mathematical model for this kind of crane where it is possible to control the three rotations of the crane (known as luff, slew, and jib movement), and the cable length. The only simplifying assumption of the model is that the cable is considered rigid. On the basis of this model, we propose a nonlinear control law based on energy considerations which is able to perform position control of the crane while actively damping the oscillations of the load. The corresponding stability and convergence analysis is carefully proved using the LaSalle's invariance principle. The effectiveness of the proposed control approach has been tested in simulation with realistic physical parameters and in the presence of model mismatch. | electrical engineering and systems science |
End-user-devices in the current cellular ecosystem are prone to many different vulnerabilities across different generations and protocol layers. Fixing these vulnerabilities retrospectively can be expensive, challenging, or just infeasible. A pragmatic approach for dealing with such a diverse set of vulnerabilities would be to identify attack attempts at runtime on the device side, and thwart them with mitigating and corrective actions. Towards this goal, in the paper we propose a general and extendable approach called Phoenix for identifying n-day cellular network control-plane vulnerabilities as well as dangerous practices of network operators from the device vantage point. Phoenix monitors the device-side cellular network traffic for performing signature-based unexpected behavior detection through lightweight runtime verification techniques. Signatures in Phoenix can be manually-crafted by a cellular network security expert or can be automatically synthesized using an optional component of Phoenix, which reduces the signature synthesis problem to the language learning from the informant problem. Based on the corrective actions that are available to Phoenix when an undesired behavior is detected, different instantiations of Phoenix are possible: a full-fledged defense when deployed inside a baseband processor; a user warning system when deployed as a mobile application; a probe for identifying attacks in the wild. One such instantiation of Phoenix was able to identify all 15 representative n-day vulnerabilities and unsafe practices of 4G LTE networks considered in our evaluation with a high packet processing speed (~68000 packets/second) while inducing only a moderate amount of energy overhead (~4mW). | computer science |
Four new relations have been found between the Stirling numbers of first and second kind. They are derived directly from recently published relations. | mathematics |
Properties of 2-adic valuation sequences for general quadratic polynomials with integer coefficients are determined directly from the coefficients. These properties include boundedness or unboundedness, periodicity, and valuations at terminating nodes. We completely describe the periodic sequences in the bounded case. Throughout, we frame results in terms of trees and sequences. | mathematics |
Machine learning has become a major field of research in order to handle more and more complex image detection problems. Among the existing state-of-the-art CNN models, in this paper a region-based, fully convolutional network, for fast and accurate object detection has been proposed based on the experimental results. Among the region based networks, ResNet is regarded as the most recent CNN architecture which has obtained the best results at ImageNet Large-Scale Visual Recognition Challenge (ILSVRC) in 2015. Deep residual networks (ResNets) can make the training process faster and attain more accuracy compared to their equivalent conventional neural networks. Being motivated with such unique attributes of ResNet, this paper evaluates the performance of fine-tuned ResNet for object classification of our weeds dataset. The dataset of farm land weeds detection is insufficient to train such deep CNN models. To overcome this shortcoming, we perform dropout techniques along with deep residual network for reducing over-fitting problem as well as applying data augmentation with the proposed ResNet to achieve a significant outperforming result from our weeds dataset. We achieved better object detection performance with Region-based Fully Convolutional Networks (R-FCN) technique which is latched with our proposed ResNet-101. | computer science |
A two-type version of the frog model on $\mathbb{Z}^d$ is formulated, where active type $i$ particles move according to lazy random walks with probability $p_i$ of jumping in each time step ($i=1,2$). Each site is independently assigned a random number of particles. At time 0, the particles at the origin are activated and assigned type 1 and the particles at one other site are activated and assigned type 2, while all other particles are sleeping. When an active type $i$ particle moves to a new site, any sleeping particles there are activated and assigned type $i$, with an arbitrary tie-breaker deciding the type if the site is hit by particles of both types in the same time step. We show that the event $G_i$ that type $i$ activates infinitely many particles has positive probability for all $p_1,p_2\in(0,1]$ ($i=1,2$). Furthermore, if $p_1=p_2$, then the types can coexist in the sense that $\mathbb{P}(G_1\cap G_2)>0$. We also formulate several open problems. For instance, we conjecture that, when the initial number of particles per site has a heavy tail, the types can coexist also when $p_1\neq p_2$. | mathematics |
Inspired by a new compilation of strong lensing systems, which consist of 204 points in the redshift range $0.0625< z_{l} < 0.958$ for the lens and $0.196< z_{s} < 3.595$ for the source, we constrain three models that generate a late cosmic acceleration: the $\omega$-cold dark matter model, the Chevallier-Polarski-Linder and the Jassal-Bagla-Padmanabhan parametrizations. Our compilation contains only those systems with early type galaxies acting as lenses, with spectroscopically measured stellar velocity dispersions, estimated Einstein radius, and both the lens and source redshifts. We assume an axially symmetric mass distribution in the lens equation, using a correction to alleviate differences between the measured velocity dispersion ($\sigma$) and the dark matter halo velocity dispersion ($\sigma_{DM}$) as well as other systematic errors that may affect the measurements. We have considered different sub-samples to constrain the cosmological parameters of each model. Additionally, we generate a mock data of SLS to asses the impact of the chosen mass profile on the accuracy of Einstein radius estimation. Our results show that cosmological constraints are very sensitive to the selected data: some cases show convergence problems in the estimation of cosmological parameters (e.g. systems with observed distance ratio $D^{obs}<0.5$), others show high values for the chi-square function (e.g. systems with a lens equation $D^{obs} >1$ or high velocity dispersion $\sigma > 276$ km s$^{-1}$). However, we obtained a fiduciary sample with 143 systems which improves the constraints on each tested cosmological model. | astrophysics |
We demonstrate the existence of localized states in close vicinity of a linear defect in graphene. These states have insulating or conducting character. Insulating states form a flat band, while conducting states present a slowdown of the group velocity which is not originated by many-body interactions and it is controlled by the interface properties. For appropriate boundary conditions, the conducting states exhibit momentum-valley locking and protection from backscattering effects. These findings provide a contribution to the recent discussion on the origin of correlated phases in graphene. | condensed matter |
The charge of microparticles immersed in the dc discharge of the Plasmakristall-4 experimental facility has been estimated using the particle velocities from experiments performed on Earth and under microgravity conditions on the International Space Station. The theoretical model used for these estimates is based on the balance of the forces acting on a single particle in the discharge. The model takes into account the radial dependence of the discharge parameters and describes reasonably well the experimental measurements. | physics |
We give a global formulation of the coupling of four-dimensional scalar sigma models to Abelian gauge fields for the generalized situation when the "duality structure" of the Abelian gauge theory is described by a flat symplectic vector bundle $(\mathcal{S},D,\omega)$ defined over the scalar manifold $\mathcal{M}$. The construction uses a taming of $(\mathcal{S}, \omega)$, which encodes globally the inverse gauge couplings and theta angles of the "twisted" Abelian gauge theory in a manner that makes no use of duality frames. We show that global solutions of the equations of motion of such models give classical locally geometric U-folds. We also describe the groups of duality transformations and scalar-electromagnetic symmetries arising in such models, which involve lifting isometries of $\mathcal{M}$ to a particular class of flat automorphisms of the bundle $\mathcal{S}$ and hence differ from expectations based on local analysis. The appropriate version of the Dirac quantization condition involves a discrete local system defined over $\mathcal{M}$ and gives rise to a smooth bundle of polarized Abelian varieties, endowed with a flat symplectic connection. This shows that a generalization of part of the mathematical structure familiar from $\mathcal{N}=2$ supergravity is already present in such purely bosonic models, without any coupling to fermions and hence without any supersymmetry. | high energy physics theory |
Recent studies have suggested that low-energy cosmic rays (CRs) may be accelerated inside molecular clouds by the shocks associated with star formation. We use a Monte Carlo transport code to model the propagation of CRs accelerated by protostellar accretion shocks through protostellar cores. We calculate the CR attenuation and energy losses and compute the resulting flux and ionization rate as a function of both radial distance from the protostar and angular position. We show that protostellar cores have non-uniform CR fluxes that produce a broad range of CR ionization rates, with the maximum value being up to two orders of magnitude higher then the radial average at a given distance. In particular, the CR flux is focused in the direction of the outflow cavity, creating a 'flashlight' effect and allowing CRs to leak out of the core. The radially averaged ionization rates are less than the measured value for the Milky Way of $\zeta \approx 10^{-16} \rm s^{-1}$; however, within $r \approx 0.03$ pc from the protostar, the maximum ionization rates exceed this value. We show that variation in the protostellar parameters, particularly in the accretion rate, may produce ionization rates that are a couple of orders of magnitude higher or lower than our fiducial values. Finally, we use a statistical method to model unresolved sub-grid magnetic turbulence in the core. We show that turbulence modifies the CR spectrum and increases the uniformity of the CR distribution but does not significantly affect the resulting ionization rates. | astrophysics |
This paper is concerned with a thermomechanical model describing phase separation phenomena in terms of the entropy balance and equilibrium equations for the microforces. The related system is highly nonlinear and admits singular potentials in the phase equation. Both the viscous and the non-viscous cases are considered in the Cahn--Hilliard relations characterizing the phase dynamics. The entropy balance is written in terms of the absolute temperature and of its logarithm, appearing under time derivative. The initial and boundary value problem is considered for the system of partial differential equations. The existence of a global solution is proved via some approximations involving Yosida regularizations and a suitable time discretization. | mathematics |
Here we consider the possible bulk and shear moduli of planar polycrystals built from a single crystal in various orientations. Previous work gave a complete characterization for crystals with orthotropic symmetry. Specifically, bounds were derived separately on the effective bulk and shear moduli, thus confining the effective moduli to lie within a rectangle in the (bulk, shear) plane. It was established that every point in this rectangle could be realized by an appropriate hierarchical laminate microgeometry, with the crystal taking different orientations in the layers, and the layers themselves being in different orientations. The bounds are easily extended to crystals with no special symmetry, but the path to constructing microgeometries that achieve every point in the rectangle defined by the bounds is considerably more difficult. We show that the two corners of the box having minimum bulk modulus are always attained by hierarchical laminates. For the other two corners we present algorithms for generating hierarchical laminates that attain them. Numerical evidence strongly suggests that the corner having maximum bulk and maximum shear modulus is always attained. For the remaining corner, with maximum bulk modulus and minimum shear modulus, it is not yet clear whether the algorithm always succeeds, and hence whether all points in the rectangle are always attained. The microstructures we use are hierarchical laminate geometries that at their core have a self-similar microstructure, in the sense that the microstructure on one length scale is a rotation and rescaling of that on a smaller length scale. | mathematics |
The lattice studies in QCD demonstrate the nontrivial localization behavior of the eigenmodes of the 4D Euclidean Dirac operator considered as Hamiltonian of $4+1$ dimensional disordered system. We use the holographic viewpoint to provide the conjectural explanation of these properties. The delocalization of all modes in the confined phase is related to the $\theta=\pi$ - like phenomena when the domain walls between degenerated vacua are possible. It is conjectured that the localized modes separated by mobility edge from the rest of the spectrum in deconfined QCD correspond to the near-horizon region in the holographic dual. | high energy physics theory |
Enhanced Coulomb interactions in monolayer transition metal dichalcogenides cause tightly bound electron-hole pairs (excitons) which dominate their linear and nonlinear optical response. The latter includes bleaching, energy renormalizations, and higher-order Coulomb correlation effects like biexcitons and excitation-induced dephasing (EID). While the first three are extensively studied, no theoretical footing for EID in exciton dominated semiconductors is available so far. In this study, we present microscopic calculations based on excitonic Heisenberg equations of motion and identify the coupling of optically pumped excitons to exciton-exciton scattering continua as the leading mechanism responsible for an optical power dependent linewidth broadening (EID) and sideband formation. Performing time-, momentum-, and energy-resolved simulations, we quantitatively evaluate the EID for the most common monolayer transition metal dichalcogenides and find an excellent agreement with recent experiments. | condensed matter |
We propose a new parton theory of the hole-doped cuprates, describing the evolution from the pseudogap metal with small Fermi surfaces to the conventional Fermi liquid with a large Fermi surface. We introduce 2 ancilla qubits per square lattice site, and employ them to obtain a variational wavefunction of a fractionalized Fermi liquid for the pseudogap metal state. We propose a multi-layer Hamiltonion for the cuprates, with the electrons residing in the 'physical' layer, and the ancilla qubits in two 'hidden' layers: the hidden layers can be decoupled from the physical layer by a canonical transformation which leaves the hidden layers in a trivial gapped state. This Hamiltonian yields an emergent gauge theory which describes not only the fractionalized Fermi liquid, but also the conventional Fermi liquid, and possible exotic intermediate phases and critical points. The fractionalized Fermi liquid has hole pockets with quasiparticle weight which is large only on "Fermi arcs", and fermionic spinon excitations which carry charges of the emergent gauge fields. | condensed matter |
The quantum mechanical properties of the strongly non-linear quantum oscillator in the Poeschl Teller model are considered. In the first place, the energy spectrum and its dependence upon the confinement parameter i.e., the width of the box are studied. Moreover, on the grounds of the Hellman Feynman theorem the pressure operator in this model is obtained and along with the energy spectrum is studied in two main approximations: the particle in the box and linear harmonic oscillator for large and low values of the main quantum number; the critical value is also evaluated. Semi-classical approximation as well as perturbation theory for the Poeschl Teller are also considered. The results obtained here are intended for future thermodynamic calculations: first of all, for the generalization of the well known Bloch result for the linear harmonic oscillator in the thermostat. To this end, the density matrix for the Poeschl Teller oscillator will be calculated and the full Carnot cycle conducted. | quantum physics |
Context. 55 Cnc e is a transiting super-Earth orbiting a solar-like star with an orbital period of 17.7 hours. In 2011, using the MOST space telescope, a quasi-sinusoidal modulation in flux was detected with the same period as the planetary orbit. The amplitude of this modulation was too large to be explained as the change in light reflected or emitted by the planet. Aims. The MOST telescope continued to observe 55 Cnc e for a few weeks per year over five years, covering 143 individual transits. This paper presents the analysis of the observed phase modulation throughout these observations and a search for the secondary eclipse of the planet. Methods. The most important source of systematic noise in MOST data is due to stray-light reflected from the Earth, which is modulated with both the orbital period of the satellite and the Earth's rotation period. We present a new technique to deal with this source of noise, which we combined with standard detrending procedures for MOST data. We then performed Markov Chain Monte Carlo analyses of the detrended light curves, modeling the planetary transit and phase modulation. Results. We find phase modulations similar to those seen in 2011 in most of the subsequent years; however, the amplitude and phase of maximum light are seen to vary from 113 to 28 ppm and from 0.1 to 3.8 rad. The secondary eclipse is not detected, but we constrain the geometric albedo of the planet to less than 0.47 (2$\sigma$). Conclusions. While we cannot identify a single origin of the observed optical modulation, we propose a few possible scenarios. Those include star-planet interaction or the presence of a transiting circumstellar torus of dust. However, a detailed interpretation of these observations is limited by their photometric precision. Additional observations at optical wavelengths could contribute to uncovering the underlying physical processes. | astrophysics |
With the popularity and development of the wearable devices such as smartphones, human activity recognition (HAR) based on sensors has become as a key research area in human computer interaction and ubiquitous computing. The emergence of deep learning leads to a recent shift in the research of HAR, which requires massive strictly labeled data. In comparison with video data, activity data recorded from accelerometer or gyroscope is often more difficult to interpret and segment. Recently, several attention mechanisms are proposed to handle the weakly labeled human activity data, which do not require accurate data annotation. However, these attention-based models can only handle the weakly labeled dataset whose sample includes one target activity, as a result it limits efficiency and practicality. In the paper, we propose a recurrent attention networks (RAN) to handle sequential weakly labeled multi-activity recognition and location tasks. The model can repeatedly perform steps of attention on multiple activities of one sample and each step is corresponding to the current focused activity. The effectiveness of the RAN model is validated on a collected sequential weakly labeled multi-activity dataset and the other two public datasets. The experiment results show that our RAN model can simultaneously infer multi-activity types from the coarse-grained sequential weak labels and determine specific locations of every target activity with only knowledge of which types of activities contained in the long sequence. It will greatly reduce the burden of manual labeling. | electrical engineering and systems science |
The observability of a dynamical system is affected by the presence of external inputs, either known (such as control actions) or unknown (disturbances). Inputs of unknown magnitude are especially detrimental for observability, and they also complicate its analysis. Hence the availability of computational tools capable of analysing the observability of nonlinear systems with unknown inputs has been limited until lately. Two symbolic algorithms based on differential geometry, ORC-DF and FISPO, have been recently proposed for this task, but their critical analysis and comparison is still lacking. Here we perform an analytical comparison of both algorithms and evaluate their performance on a set of problems, discussing their strengths and limitations. Additionally, we use these analyses to provide insights about certain aspects of the relationship between inputs and observability. We find that, while ORC-DF and FISPO follow a similar approach, they differ in key aspects that can have a substantial influence on their applicability and computational cost. The FISPO algorithm is more generally applicable, since it can analyse any nonlinear ODE model. The ORC-DF algorithm analyses models that are affine in the inputs, and if those models have known inputs it is sometimes more efficient. Thus, the optimal choice of a method depends on the characteristics of the problem under consideration. To facilitate the use of both algorithms we implement the ORC-DF algorithm in a new version of STRIKE-GOLDD, a MATLAB toolbox for structural identifiability and observability analysis. Since this software tool already had an implementation of the FISPO algorithm, the new release allows modellers and model users the convenience of choosing between different algorithms in a single tool, without changing the coding of their model. | electrical engineering and systems science |
Quality control (QC) of medical images is essential to ensure that downstream analyses such as segmentation can be performed successfully. Currently, QC is predominantly performed visually at significant time and operator cost. We aim to automate the process by formulating a probabilistic network that estimates uncertainty through a heteroscedastic noise model, hence providing a proxy measure of task-specific image quality that is learnt directly from the data. By augmenting the training data with different types of simulated k-space artefacts, we propose a novel cascading CNN architecture based on a student-teacher framework to decouple sources of uncertainty related to different k-space augmentations in an entirely self-supervised manner. This enables us to predict separate uncertainty quantities for the different types of data degradation. While the uncertainty measures reflect the presence and severity of image artefacts, the network also provides the segmentation predictions given the quality of the data. We show models trained with simulated artefacts provide informative measures of uncertainty on real-world images and we validate our uncertainty predictions on problematic images identified by human-raters. | electrical engineering and systems science |
The gamma model is a generalized linear model for gamma-distributed outcomes. The model is widely applied in psychology, ecology or medicine. In this paper we focus on gamma models having a linear predictor without intercept. For a specific scenario sets of locally D- and A-optimal designs are to be developed. Recently, Gaffke et al. (2018) established a complete class and an essentially complete class of designs for gamma models to obtain locally D-optimal designs. However to extend this approach to gamma model without an intercept term is complicated. To solve that further techniques have to be developed in the current work. Further, by a suitable transformation between gamma models with and without intercept optimality results may be transferred from one model to the other. Additionally by means of The General Equivalence Theorem optimality can be characterized for multiple regression by a system of polynomial inequalities which can be solved analytically or by computer algebra. By this necessary and sufficient conditions on the parameter values can be obtained for the local D-optimality of particular designs. The robustness of the derived designs with respect to misspecifications of the initial parameter values is examined by means of their local D-efficiencies. | mathematics |
We show in this article that depending on the flow conditions the same fluid can be considered as a perfect fluid or on the contrary as viscous fluid. These properties are addressed by emptying a tank. we show that we pass from one regime to another by just changing the length of the outlet tube of the tank is drained. This change of regime takes place in accordance with a criterion defined in the theoretical part. | physics |
Generating realistic images from scene graphs asks neural networks to be able to reason about object relationships and compositionality. As a relatively new task, how to properly ensure the generated images comply with scene graphs or how to measure task performance remains an open question. In this paper, we propose to harness scene graph context to improve image generation from scene graphs. We introduce a scene graph context network that pools features generated by a graph convolutional neural network that are then provided to both the image generation network and the adversarial loss. With the context network, our model is trained to not only generate realistic looking images, but also to better preserve non-spatial object relationships. We also define two novel evaluation metrics, the relation score and the mean opinion relation score, for this task that directly evaluate scene graph compliance. We use both quantitative and qualitative studies to demonstrate that our pro-posed model outperforms the state-of-the-art on this challenging task. | computer science |
A large fraction of accreting black hole and neutron stars systems present clear evidence of the reprocessing of X-rays in the atmosphere of an optically-thick accretion disk. The main hallmarks of X-ray reflection include fluorescent K-shell emission lines from iron ($\sim 6.4-6.9$ keV), the absorption iron K-edge ($\sim 7-9$ keV), and a broad featureless component known as the Compton hump ($\sim 20-40$ keV). This Compton hump is produced as the result of the scattering of high-energy photons ($E \gtrsim 10$ keV) of the relatively colder electrons ($T_e \sim 10^5-10^7$ K) in the accretion disk, in combination with photoelectric absorption from iron. The treatment of this process in most current models of ionized X-ray reflection has been done using an approximated Gaussian redistribution kernel. This approach works sufficiently well up to $\sim100$ keV, but it becomes largely inaccurate at higher energies and at relativistic temperatures ($T_e\sim10^9$ K). We present new calculations of X-ray reflection using a modified version of our code XILLVER, including an accurate solution for Compton scattering of the reflected unpolarized photons in the disk atmosphere. This solution takes into account quantum electrodynamic and relativistic effects allowing the correct treatment of high photon energies and electron temperatures. We show new reflection spectra computed with this model, and discuss the improvements achieved in the reproducing the correct shape of the Compton hump, the discrepancies with previous calculations, and the expected impact of these new models in the interpretation of observational data. | astrophysics |
We investigate the dynamical properties of one-dimensional dissipative Fermi-Hubbard models, which are described by the Lindblad master equations with site-dependent jump operators. The corresponding non-Hermitian effective Hamiltonians with pure loss terms possess parity-time ($\mathcal{PT}$) symmetry if we compensate the system additionally an overall gain term. By solving the two-site Lindblad equation with fixed dissipation exactly, we find that the dynamics of rescaled density matrix shows an instability as the interaction increases over a threshold, which can be equivalently described in the scheme of non-Hermitian effective Hamiltonians. This instability is also observed in multi-site systems and closely related to the $\mathcal{PT}$ symmetry breaking accompanied by appearance of complex eigenvalues of the effective Hamiltonian. Moreover, we unveil that the dynamical instability of the anti-ferromagnetic Mott phase comes from the $\mathcal{PT}$ symmetry breaking in highly excited bands, although the low-energy effective model of the non-Hermitian Hubbard model in the strongly interacting regime is always Hermitian. We also provide a quantitative estimation of the time for the observation of dynamical $\mathcal{PT}$ symmetry breaking which could be probed in experiments. | condensed matter |
Tracking a horizon in seismic images or 3D volumes is an integral part of seismic interpretation. The last few decades saw progress in using neural networks for this task, starting from shallow networks for 1D traces, to deeper convolutional neural networks for large 2D images. Because geological structures are intrinsically 3D, we hope to see improved horizon tracking by training networks on 3D seismic data cubes. While there are some 3D convolutional neural networks for various seismic interpretation tasks, they are restricted to shallow networks or relatively small 3D inputs because of memory limitations. The required memory for the network states and weights increases with network depth. We present a fully reversible network for horizon tracking that has a memory requirement that is independent of network depth. To tackle memory issues regarding the network weights, we use layers that train in a factorized form directly. Therefore, we can maintain a large number of network channels while keeping the number of convolutional kernels low. We use the saved memory to increase the input size of the data by order of magnitude such that the network can better learn from large structures in the data. A field data example verifies the proposed network structure is suitable for seismic horizon tracking. | physics |
We derive analytical results on energy spectral phase transitions and deformations in the simplest model of one-dimensional lattice displaying the non-Hermitian skin effect, namely the Hatano-Nelson model with unidirectional hopping, under on-site potential uncorrelated disorder in complex energy plane. While the energy spectrum under open boundary conditions (OBC) exactly reproduces the distribution of on-site potential disorder, the energy spectrum under periodic boundary conditions (PBC) undergoes spectral deformations, from one or more closed loops in the fully delocalized phase, with no overlap with the OBC spectrum, to a mixed spectrum (closed loops and some OBC energies) in the mobility edge phase, to a complete collapse toward the OBC spectrum in the bulk localized phase. Such transitions are observed as the strength of disorder is increased. Depending on the kind of disorder, different interesting behaviors are found. In particular, for continuous disorder with a radial distribution in complex energy plane it is shown that in the delocalized phase the energy spectrum under PBC is locked and fully insensitive to disorder, while transition to the bulk localized phase is signaled by the change of a topological winding number. When the disorder is described by a discrete distribution, the bulk localization transition never occurs, while topological phase transitions associated to PBC energy spectral splittings can be observed. | condensed matter |
We present a rapid design methodology that combines automated hyper-parameter tuning with semi-supervised training to build highly accurate and robust models for voice commands classification. Proposed approach allows quick evaluation of network architectures to fit performance and power constraints of available hardware, while ensuring good hyper-parameter choices for each network in real-world scenarios. Leveraging the vast amount of unlabeled data with a student/teacher based semi-supervised method, classification accuracy is improved from 84% to 94% in the validation set. For model optimization, we explore the hyper-parameter space through population based training and obtain an optimized model in the same time frame as it takes to train a single model. | electrical engineering and systems science |
When frying potato snacks, it is typically observed that the dough, which is submerged in hot oil, after some critical time increases its buoyancy and floats to the surface. The lift-off time is a useful metric in ensuring that the snacks are properly cooked. Here we propose a multiphase mathematical model for the frying of potato snacks, where water inside the dough is evaporated from both the top and bottom surfaces of the snack at two receding evaporation fronts. The vapour created at the top of the snack bubbles away to the surface, whereas the vapour released from the bottom surface forms a buoyant blanket layer. By asymptotic analysis, we show that the model simplifies to solving a one-dimensional Stefan problem in the snack coupled to a thin-film equation in the vapour blanket through a non-linear boundary condition. Using our mathematical model, we predict the change in the snack density as a function of time, and investigate how lift-off time depends on the different parameters of the problem. | physics |
High magnetic field transport measurements and ab initio calculations on the layered superconductor TaSe3 have provided compelling evidences for the existence of a three-dimensional strong topological insulator state. Longitudinal magnetotransport measurements up to ~ 33 T unveiled striking Shubnikov-de Hass oscillations with two fundamental frequencies at 100 T and 175 T corresponding to a nontrivial electron Fermi pocket at the B point and a nontrivial hole Fermi pocket at the {\Gamma} point respectively in the Brillouin zone. However, calculations revealed one more electron pocket at the B point, which was not detected by the magnetotransport measurements, presumably due to the limited carrier momentum relaxation time. Angle dependent quantum oscillations by rotating the sample with respect to the magnetic field revealed clear changes in the two fundamental frequencies, indicating anisotropic electronic Fermi pockets. The ab initio calculations gave the topological Z2 invariants of (1; 100) and revealed a single Dirac cone on the (1 0 -1) surface at the X point with helical spin texture at a constant-energy contour, suggesting a strong topological insulator state. The results demonstrate TaSe3 an excellent platform to study the interplay between topological phase and superconductivity and a promising system for the exploration of topological superconductivity. | condensed matter |
We report that LAMOST-HVS1 is a massive hyper-runaway subgiant star with mass of 8.3 Msun and super-Solar metallicity, ejected from the inner stellar disk of the Milky Way $\sim$ 33 Myr ago with the intrinsic ejection velocity of $568^{+19}_{-17}$ km/s (corrected for the streaming motion of the disk), based on the proper motion data from Gaia Data Release 2 (DR2) and high-resolution spectroscopy. The extremely large ejection velocity indicates that this star was not ejected by the supernova explosion of the binary companion. Rather, it was probably ejected by a 3- or 4-body dynamical interaction with more massive objects in a high-density environment. Such a high-density environment may be attained at the core region of a young massive cluster with mass of $\gtrsim 10^4$ Msun. The ejection agent that took part in the ejection of LAMOST-HVS1 may well be an intermediate mass black hole ($\gtrsim$ 100 Msun), a very massive star ($\gtrsim$ 100 Msun), or multiple ordinary massive stars ($\gtrsim$ 30 Msun). Based on the flight time and the ejection location of LAMOST-HVS1, we argue that its ejection agent or its natal star cluster is currently located near the Norma spiral arm. The natal star cluster of LAMOST-HVS1 may be an undiscovered young massive cluster near the Norma spiral arm. | astrophysics |
We present the first sentence simplification model that learns explicit edit operations (ADD, DELETE, and KEEP) via a neural programmer-interpreter approach. Most current neural sentence simplification systems are variants of sequence-to-sequence models adopted from machine translation. These methods learn to simplify sentences as a byproduct of the fact that they are trained on complex-simple sentence pairs. By contrast, our neural programmer-interpreter is directly trained to predict explicit edit operations on targeted parts of the input sentence, resembling the way that humans might perform simplification and revision. Our model outperforms previous state-of-the-art neural sentence simplification models (without external knowledge) by large margins on three benchmark text simplification corpora in terms of SARI (+0.95 WikiLarge, +1.89 WikiSmall, +1.41 Newsela), and is judged by humans to produce overall better and simpler output sentences. | computer science |
We construct the multi-variable realizations of the $W_{1+\infty}$ algebra such that they lead to the $W_{1+\infty}$ $n$-algebra. Based on our realizations of the $W_{1+\infty}$ algebra, we derive the $W_{1+\infty}$ constraints for the hermitian one-matrix model. The constraint operators yield not only the $W_{1+\infty}$ algebra but also the closed $W_{1+\infty}$ $n$-algebra. | high energy physics theory |
The analysis of the radial distribution function of a system provides a possible procedure for uncovering interaction rules between individuals out of collective movement patterns. This approach from classical statistical mechanics has revealed recently the existence of a universal scaling in systems of pedestrians, provided the potential of interaction $V(\tau)$ is conveniently defined in the space of the times-to-collision $\tau$ [Phys. Rev. Lett. \textbf{113}, 238701 (2014)]. Here we significantly extend this result by comparing numerically the performance of completely different rules of self-avoidance in bidirectional systems and proving that all of them collapse to a common scaling both in the disordered phase ($V(\tau) \sim \tau^{-2}$) and in the lane-formation regime ($V(\tau) \sim \tau^{-1}$), so suggesting that these scalings represent actually a universal feature of any self-avoiding bidirectional flow. | condensed matter |
Candogan et al. (2011) provide an orthogonal direct-sum decomposition of finite games into potential, harmonic and nonstrategic components. In this paper we study the issue of decomposing games that are strategically equivalent from a game-theoretical point of view, for instance games obtained via transformations such as duplications of strategies or positive affine mappings of of payoffs. We show the need to define classes of decompositions to achieve commutativity of game transformations and decompositions. | computer science |
Given a class of $q$-local Hamiltonians, is it possible to find a simple variational state whose energy is a finite fraction of the ground state energy in the thermodynamic limit? Whereas product states often provide an affirmative answer in the case of bosonic (or qubit) models, we show that Gaussian states fail dramatically in the fermionic case, like for the Sachdev-Ye-Kitaev (SYK) models. This prompts us to propose a new class of wavefunctions for SYK models inspired by the variational coupled cluster algorithm. We introduce a static ("0+0D") large-$N$ field theory to study the energy, two-point correlators, and entanglement properties of these states. Most importantly, we demonstrate a finite disorder-averaged approximation ratio of $r \approx 0.62$ between the variational and ground state energy of SYK for $q=4$. Moreover, the variational states provide an exact description of spontaneous symmetry breaking in a related two-flavor SYK model. | condensed matter |
Bulk-boundary correspondence is an important feature of the gapped topological states of quantum matter. We study the behavior of the Majorana zero modes (MZMs) at quantum criticality and also observe that all quantum critical lines can not host MZMs. We characterize different quantum critical lines based on the presence of MZMs on it and also raise question of the validity of the conventional bulk-boundary correspondence (BBC). We find the appearance of anomalous bulkboundary correspondence (ABBC) at the criticality and also find a topological quantum phase transition along a quantum critical line. We observe a minimum principle of topological invariant number at the quantum critical lines seperated by the two different regions with different topological invariant numbers. We argue that the presence of of MZM at the quantum critical lines is a very good platform for topological quantum computation. Finally we generalize the appearance of ABBC for the further longer range coupling. This work provide a new perspective for the topological state of quantum matter. | condensed matter |
Elucidating versatile configurations of spiral folding, and investigating the deployment performance is of relevant interest to extend the applicability of deployable membranes towards large-scale and functional configurations. In this paper we propose new schemes to package flat and curved membranes of finite thickness by using multiple spirals, whose governing equations render folding lines by juxtaposing spirals and by accommodating membrane thickness. Our experiments using a set of topologically distinct flat and curved membranes deployed by tensile forces applied in the radial and circumferential directions have shown that (1) the multi-spiral approach with prismatic folding lines offered the improved deployment performance, and (2) the deployment of curved surfaces progresses rapidly within a finite load domain. Furthermore, we confirmed the high efficiency of membranes folded by multi-spiral patterns. From viewpoints of configuration and deployment performance, the multi-spiral approach is potential to extend the versatility and maneuverability of spiral folding mechanisms. | condensed matter |
This paper considers the dominant dynamical, thermal and rotational balances within the solar convection zone. The reasoning is such that: Coriolis forces balance pressure gradients. Background vortex stretching, baroclinic torques and nonlinear advection balance jointly. Turbulent fluxes convey what part of the solar luminosity that radiative diffusion cannot. These four relations determine estimates for the dominant length scales and dynamical amplitudes strictly in terms of known physical quantities. We predict that the dynamical Rossby number for convection is less than unity below the near-surface shear layer, indicating strong rotational constraint. We also predict a characteristic convection length scale of roughly 30 Mm throughout much of the convection zone. These inferences help explain recent observations that reveal weak flow amplitudes at 100-200 Mm scales. | astrophysics |
Cumulative entropy regularization introduces a regulatory signal to the reinforcement learning (RL) problem that encourages policies with high-entropy actions, which is equivalent to enforcing small deviations from a uniform reference marginal policy. This has been shown to improve exploration and robustness, and it tackles the value overestimation problem. It also leads to a significant performance increase in tabular and high-dimensional settings, as demonstrated via algorithms such as soft Q-learning (SQL) and soft actor-critic (SAC). Cumulative entropy regularization has been extended to optimize over the reference marginal policy instead of keeping it fixed, yielding a regularization that minimizes the mutual information between states and actions. While this has been initially proposed for Markov Decision Processes (MDPs) in tabular settings, it was recently shown that a similar principle leads to significant improvements over vanilla SQL in RL for high-dimensional domains with discrete actions and function approximators. Here, we follow the motivation of mutual-information regularization from an inference perspective and theoretically analyze the corresponding Bellman operator. Inspired by this Bellman operator, we devise a novel mutual-information regularized actor-critic learning (MIRACLE) algorithm for continuous action spaces that optimizes over the reference marginal policy. We empirically validate MIRACLE in the Mujoco robotics simulator, where we demonstrate that it can compete with contemporary RL methods. Most notably, it can improve over the model-free state-of-the-art SAC algorithm which implicitly assumes a fixed reference policy. | computer science |
The motion of the baryonic components of the Milky Way is governed by both luminous and dark matter content of the Galaxy. Thus, the dynamics of the Milky Way globular clusters can be used as tracers to infer the mass model of the Galaxy up to a large radius. In this work, we use the directly observable line-of-sight velocities to test if the dynamics of the globular cluster population is consistent with an assumed axisymmetric gravitational potential of the Milky Way. For this, we numerically compute the phase space distribution of the globular cluster population where the orbits are either oriented randomly or co-/counter- rotating with respect to the stellar disk. Then we compare the observed position and line-of-sight velocity distribution of $\sim$ 150 globular clusters with that of the models. We found that, for the adopted mass model, the co-rotating scenario is the favored model based on various statistical tests. We do the analysis with and without the GCs associated to the progenitors of early merger events. This analysis can be extended in the near future to include precise and copious data to better constrain the Galactic potential up to a large radius. | astrophysics |
Let $\mathcal{E}$ be the set of endomorphisms of the $n$-torus. We exhibit an example of a map such that is robustly transitive if $\mathcal{E}$ is endowed with the $C^2$ topology but is not robustly transitive if $\mathcal{E}$ is endowed with the $C^1$ topology. | mathematics |
We analyze the curriculum of the early common-years of engineering in our institute using tools of statistical physics of complex networks. Naturally, a course programme is structured in a networked form (temporal dependency and prerequisites). In this approach, each topic within each programme is associated with a node, which in turn is joined by links representing the dependence of a topic for the understanding of another in a different discipline. As a course programme is a time-dependent structure, we propose a simple model to assign links between nodes, taking into account only two ingredients of the teaching-learning process: recursiveness and accumulation of knowledge. Since we already know the programmes, our objective is to verify if the proposed model is able to capture their particularities and to identify implications of different sequencing on the student learning in the early years of engineering degrees. Our model can be used as a systematic tool assisting the construction of a more interdisciplinary curriculum, articulating between disciplines of the undergraduate early-years in exact sciences. | physics |
In various extensions of the Standard Model of particle physics, and intriguingly even in the three-generation Standard Model without neutrino masses, neutrinos are allowed to have very tiny electric charges. After a review of the theoretical scenarios that allow the emergence of such charges, we discuss the existing observational limits and we derive new stringent direct upper bounds for the charges of the muon and tau neutrinos. We also point out a flavor-universal lower bound on neutrino charges which is obtained from the weak gravity conjecture, that is based on the hypothesis that gravity is the weakest force. We finally present a new flavor-universal upper bound on neutrino charges based on astrophysical observations of Magnetars. | high energy physics phenomenology |
Majorly classical Active Learning (AL) approach usually uses statistical theory such as entropy and margin to measure instance utility, however it fails to capture the data distribution information contained in the unlabeled data. This can eventually cause the classifier to select outlier instances to label. Meanwhile, the loss associated with mislabeling an instance in a typical classification task is much higher than the loss associated with the opposite error. To address these challenges, we propose a Cost-Based Bugdet Active Learning (CBAL) which considers the classification uncertainty as well as instance diversity in a population constrained by a budget. A principled approach based on the min-max is considered to minimize both the labeling and decision cost of the selected instances, this ensures a near-optimal results with significantly less computational effort. Extensive experimental results show that the proposed approach outperforms several state-of -the-art active learning approaches. | computer science |
Negative binomial regression is commonly employed to analyze overdispersed count data. With small to moderate sample sizes, the maximum likelihood estimator of the dispersion parameter may be subject to a significant bias, that in turn affects inference on mean parameters. This paper proposes inference for negative binomial regression based on adjustments of the score function aimed at mean and median bias reduction. The resulting estimating equations are similar to those available for improved inference in generalized linear models and, in particular, can be solved using a suitable extension of iterative weighted least squares. Simulation studies show a remarkable performance of the new methods, which are also found to solve in many cases numerical problems of maximum likelihood estimates. The methods are illustrated and evaluated using two case studies: an Ames salmonella assay data set and data on epileptic seizures. Inference based on adjusted scores turns out to be generally preferable to explicit bias correction. | statistics |
Monolayer transition metal dichalcogenides (TMDCs) are two-dimensional (2D) materials with many potential applications. Chemical vapour deposition (CVD) is a promising method to synthesize these materials. However, CVD-grown materials generally have poorer quality than mechanically exfoliated ones and contain more defects due to the difficulties in controlling precursors' distribution and concentration during growth where solid precursors are used. Here, we propose to use thiol as a liquid precursor for CVD growth of high quality and uniform 2D MoS2. Atomic-resolved structure characterizations indicate that the concentration of sulfur vacancies in the MoS2 grown from thiol is the lowest among all reported CVD samples. Low temperature spectroscopic characterization further reveals the ultrahigh optical quality of the grown MoS2. Density functional theory simulations indicate that thiol molecules could interact with sulfur vacancies in MoS2 and repair these defects during the growth of MoS2, resulting in high quality MoS2. This work provides a facile and controllable method for the growth of high-quality 2D materials with ultralow sulfur vacancies and high optical quality, which will benefit their optoelectronic applications. | condensed matter |
One of the keys to the realization of Quantum Anomalous Hall effect (QAHE) is long range ferromagnetism, which is only experimentally realized in Cr or V doped (Bi,Sb)2Te3 system. Both elements are 3d transition metals and 4d transition metals are found to be ineffective to produce long range ferromagnetism in Bi2Se3. Still, whether long range ferromagnetism can be realized by magnetic doping of 4d elements is an open question. Based on density functional theory calculations, we predict that long range ferromagnetism can be realized in Mo doped Bi2Te3 and Sb2Te3, which are semiconducting. The coupling strength is comparable with that of Cr doped Bi2Te3 and Sb2Te3. Therefore, Mo doped Bi2Te3 and Sb2Te3 or their alloys can be new systems to realize diluted magnetic semiconductors and QAHE. | condensed matter |
This study demonstrates that a space charge layer is formed on dislocation during mechanical deformation at elevated temperature. High density of dislocation lines is generated in bulk single crystalline Y2O3 stabilized ZrO2 (YSZ) by uniaxial compression at elevated temperature. The creation of dislocation is proven with transmission electron microscopy (TEM). Then, energy-dispersive X-ray spectroscopy (EDS) and electron energy loss spectroscopy (EELS) are used to explore the changes in the composition on and away from the dislocation lines. Also, it is clarified that segregation of dopant atoms (yttrium) on the dislocation line is induced by high temperature annealing. Comparing the compositional variations with and without thermal annealing, we study the space charge layer formed on dislocation lines in a doped system. | condensed matter |
We describe the use of laser-enhanced etching of fused silica in order to build multi-layer ion traps. This technique offers high precision of both machining and alignment of adjacent wafers. As examples of designs taking advantage of this possibility, we describe traps for realizing two key elements of scaling trapped ion systems. The first is a trap for a cavity-QED interface between single ions and photons, in which the fabrication allows shapes that provide good electro-static shielding of the ion from charge build-up on the mirror surfaces. The second incorporates two X-junctions allowing two-dimensional shuttling of ions. Here we are able to investigate designs which explore a trade-off between pseudo-potential barriers and confinement at the junction center. In both cases we illustrate the design constraints arising from the fabrication. | physics |
Let $G$ be a symplectic or special orthogonal group, let $H$ be a connected reductive subgroup of $G$, and let $X$ be a flag variety of $G$. We classify all triples $(G,H,X)$ such that the natural action of $H$ on $X$ is spherical. For each of these triples, we determine the restrictions to $H$ of all irreducible representations of $G$ realized in spaces of sections of homogeneous line bundles on $X$. | mathematics |
Deep neural networks (DNNs) have achieved superior performance in various prediction tasks, but can be very vulnerable to adversarial examples or perturbations. Therefore, it is crucial to measure the sensitivity of DNNs to various forms of perturbations in real applications. We introduce a novel perturbation manifold and its associated influence measure to quantify the effects of various perturbations on DNN classifiers. Such perturbations include various external and internal perturbations to input samples and network parameters. The proposed measure is motivated by information geometry and provides desirable invariance properties. We demonstrate that our influence measure is useful for four model building tasks: detecting potential 'outliers', analyzing the sensitivity of model architectures, comparing network sensitivity between training and test sets, and locating vulnerable areas. Experiments show reasonably good performance of the proposed measure for the popular DNN models ResNet50 and DenseNet121 on CIFAR10 and MNIST datasets. | statistics |
We study the $\bar K p \to Y K\bar K \pi$ reactions with $\bar K = \bar K^0, K^-$ and $Y=\Sigma^0, \Sigma^+, \Lambda$, in the region of $K\bar K \pi$ invariant masses of $1200-1550$ MeV. The strong coupling of the $f_1(1285)$ resonance to $K^* \bar K$ makes the mechanism based on $K^*$ exchange very efficient to produce this resonance observed in the $K\bar K \pi$ invariant mass distribution. In addition, in all the reactions one observes an associated peak at $1420$ MeV which comes from the $K^* \bar K$ decay mode of the $f_1(1285)$ when the $K^*$ is placed off shell at higher invariant masses. We claim this to be the reason for the peak of the $K^* \bar K$ distribution seen in the experiments which has been associated to the "$f_1(1420)$" resonance. | high energy physics phenomenology |
Group testing is an efficient method for testing a large population to detect infected individuals. In this paper, we consider an efficient adaptive two stage group testing scheme. Using a straightforward analysis, we characterize the efficiency of several two stage group testing algorithms. We determine how to pick the parameters of the tests optimally for three schemes with different types of randomization, and show that the performance of two stage testing depends on the type of randomization employed. Seemingly similar randomization procedures lead to different expected number of tests to detect all infected individuals, we determine what kinds of randomization are necessary to achieve optimal performance. We further show that in the optimal setting, our testing scheme is robust to errors in the input parameters. | statistics |
Variable selection, or more generally, model reduction is an important aspect of the statistical workflow aiming to provide insights from data. In this paper, we discuss and demonstrate the benefits of using a reference model in variable selection. A reference model acts as a noise-filter on the target variable by modeling its data generating mechanism. As a result, using the reference model predictions in the model selection procedure reduces the variability and improves stability leading to improved model selection performance. Assuming that a Bayesian reference model describes the true distribution of future data well, the theoretically preferred usage of the reference model is to project its predictive distribution to a reduced model leading to projection predictive variable selection approach. Alternatively, reference models may also be used in an ad-hoc manner in combination with common variable selection methods. In several numerical experiments, we investigate the performance of the projective prediction approach as well as alternative variable selection methods with and without reference models. Our results indicate that the use of reference models generally translates into better and more stable variable selection. Additionally, we demonstrate that the projection predictive approach shows superior performance as compared to alternative variable selection methods independently of whether or not they use reference models. | statistics |
We apply the derivative expansion of the effective action in the exact renormalization group equation up to fourth order to the $Z_2$ and $O(N)$ symmetric scalar models in $d=3$ Euclidean dimensions. We compute the critical exponents $\nu$, $\eta$ and $\omega$ using polynomial expansion in the field. We obtain our predictions for the exponents employing two regulators widely used in ERG computations. We apply Wynn's epsilon algorithm to improve the predictions for the critical exponents, extrapolating beyond the next-to-next-to-leading order prediction of the derivative expansion. | high energy physics theory |
The dynamics of a cosmological (de)confinement phase transition is studied in nearly conformally invariant field theories, where confinement is predominantly spontaneously generated and associated with a light "dilaton" field. We show how the leading contribution to the transition rate can be computed within the dilaton effective theory. In the context of Composite Higgs theories, we demonstrate that a simple scenario involving two renormalization-group fixed points can make the transition proceed much more rapidly than in the minimal scenario, thereby avoiding excessive dilution of matter abundances generated before the transition. The implications for gravitational wave phenomenology are discussed. In general, we find that more (less) rapid phase transitions are associated with weaker (stronger) gravitational wave signals. The various possible features of the strongly coupled composite Higgs phase transition discussed here can be concretely modeled at weak coupling within the AdS/CFT dual Randall-Sundrum extra-dimensional description, which offers important insights into the nature of the transition and its theoretical control. These aspects will be presented in a companion paper. | high energy physics phenomenology |
In the integral Khovanov homology of links, the presence of odd torsion is rare. Homologically thin links, that is links whose Khovanov homology is supported on two adjacent diagonals, are known to only contain $\mathbb{Z}_2$ torsion. In this paper, we prove a local version of this result. If the Khovanov homology of a link is supported in two adjacent diagonals over a range of homological gradings and the Khovanov homology satisfies some other mild restrictions, then the Khovanov homology of that link has only $\mathbb{Z}_2$ torsion over that range of homological gradings. These conditions are then shown to be met by an infinite family of 3-braids, strictly containing all 3-strand torus links, thus giving a partial answer to Sazdanovic and Przytycki's conjecture that 3-braids have only $\mathbb{Z}_2$ torsion in Khovanov homology. We also give explicit computations of integral Khovanov homology for all links in this family. | mathematics |
A three-dimensional (3D) photonic band gap crystal is an ideal tool to completely inhibit the local density of optical states (LDOS) at every position in the crystal throughout the band gap. This notion, however, pertains to ideal infinite crystals, whereas any real crystal device is necessarily finite. This raises the question as to how the LDOS in the gap depends on the position and orientation inside a finite-size crystal. Therefore, we employ rigorous numerical calculations using finite-difference time-domain (FDTD) simulations of 3D silicon inverse woodpile crystals filled with air or with toluene, as previously studied in experiments. We find that the LDOS versus position decreases exponentially into the bulk of the crystal. From the dependence on dipole orientation, we infer that the characteristic LDOS decay length $\ell_{\rho}$ is mostly related to far-field dipolar radiation effects, whereas the prefactor is mostly related to near-field dipolar effects. The LDOS decay length has a remarkably similar magnitude as the Bragg length for directional transport, which suggests that the LDOS in the crystal is dominated by vacuum states that tunnel from the closest interface towards the position of interest. Our work leads to design rules for applications of 3D photonic band gaps in emission control and lighting, quantum information processing, and in photovoltaics. | physics |
Layered van-der-Waals 2D magnetic materials are of great interest in fundamental condensed-matter physics research, as well as for potential applications in spintronics and device physics. We present neutron powder diffraction data using new ultra-high-pressure techniques to measure the magnetic structure of Mott-insulating 2D honeycomb antiferromagnet FePS$_3$ at pressures up to 183 kbar and temperatures down to 80 K. These data are complemented by high-pressure magnetometry and reverse Monte Carlo modeling of the spin configurations. As pressure is applied, the previously-measured ambient-pressure magnetic order switches from an antiferromagnetic to a ferromagnetic interplanar interaction, and from 2D-like to 3D-like character. The overall antiferromagnetic structure within the $ab$ planes, ferromagnetic chains antiferromagnetically coupled, is preserved, but the magnetic propagation vector is altered from $(0\:1\:\frac{1}{2})$ to $(0\:1\:0)$, a halving of the magnetic unit cell size. At higher pressures, coincident with the second structural transition and the insulator-metal transition in this compound, we observe a suppression of this long-range-order and emergence of a form of magnetic short-range order which survives above room temperature. Reverse Monte Carlo fitting suggests this phase to be a short-ranged version of the original ambient pressure structure - with a return to antiferromagnetic interplanar correlations. The persistence of magnetism well into the HP-II metallic state is an observation in seeming contradiction with previous x-ray spectroscopy results which suggest a spin-crossover transition. | condensed matter |
In this paper, we investigate the decay properties of the thermoelastic Timoshenko system with past history in the whole space where the thermal effects are given by Cattaneo and Fourier laws. We obtain that both systems, Timoshenko-Fourier and Timoshenko-Cattaneo, have the same rate of decay $(1 + t)^{-1/8}$ and satisfy the regularity-loss type property. Moreover, for the Cattaneo case, we show that the decay rate depends of a new condition on the wave speed of propagation $\chi_{0,\tau}$. This new condition has been recently introduced to study the asymptotic behavior in bounded domains, see for instance [5] and [27]. We found that this number also plays an important role in unbounded situation, affecting the decay rate of the solution. | mathematics |
Adding to the literature on the data-driven detection of bid-rigging cartels, we propose a novel approach based on deep learning (a subfield of artificial intelligence) that flags cartel participants based on their pairwise bidding interactions with other firms. More concisely, we combine a so-called convolutional neural network for image recognition with graphs that in a pairwise manner plot the normalized bid values of some reference firm against the normalized bids of any other firms participating in the same tenders as the reference firm. Based on Japanese and Swiss procurement data, we construct such graphs for both collusive and competitive episodes (i.e when a bid-rigging cartel is or is not active) and use a subset of graphs to train the neural network such that it learns distinguishing collusive from competitive bidding patterns. We use the remaining graphs to test the neural network's out-of-sample performance in correctly classifying collusive and competitive bidding interactions. We obtain a very decent average accuracy of around 90% or slightly higher when either applying the method within Japanese, Swiss, or mixed data (in which Swiss and Japanese graphs are pooled). When using data from one country for training to test the trained model's performance in the other country (i.e. transnationally), predictive performance decreases (likely due to institutional differences in procurement procedures across countries), but often remains satisfactorily high. All in all, the generally quite high accuracy of the convolutional neural network despite being trained in a rather small sample of a few 100 graphs points to a large potential of deep learning approaches for flagging and fighting bid-rigging cartels. | statistics |
By $B=B(x^{(0)};R)$ we denote the Euclidean ball in ${\mathbb R}^n$ given by the inequality $\|x-x^{(0)}\|\leq R$. Here $x^{(0)}\in{\mathbb R}^n, R>0$, $\|x\|:=\left(\sum_{i=1}^n x_i^2\right)^{1/2}$. We mean by $C(B)$ the space of continuous functions $f:B\to{\mathbb R}$ with the norm $\|f\|_{C(B)}:=\max_{x\in B}|f(x)|$ and by $\Pi_1\left({\mathbb R}^n\right)$ the set of polynomials in $n$ variables of degree $\leq 1$, i.e., linear functions on ${\mathbb R}^n$. Let $x^{(1)}, \ldots, x^{(n+1)}$ be the vertices of $n$-dimensional nondegenerate simplex $S\subset B$. The interpolation projector $P:C(B)\to \Pi_1({\mathbb R}^n)$ corresponding to $S$ is defined by the equalities $Pf\left(x^{(j)}\right)=f\left(x^{(j)}\right).$ We obtain the formula to compute the norm of $P$ as an operator from $C(B)$ into $C(B)$ via $x^{(0)}$, $R$ and coefficients of basic Lagrange polynomials of $S$. In more details we study the case when $S$ is a regular simplex inscribed into $B_n=B(0,1)$. | mathematics |
We revamp the existing theory of Euler class groups and present them in as much generality as possible. We remark on two results of Asok-Fasel and indicate some improvements. | mathematics |
An axion-like field comprising $\sim 10\%$ of the energy density of the universe near matter-radiation equality is a candidate to resolve the Hubble tension; this is the "early dark energy" (EDE) model. However, as shown in Hill et al. (2020), the model fails to simultaneously resolve the Hubble tension and maintain a good fit to both cosmic microwave background (CMB) and large-scale structure (LSS) data. Here, we use redshift-space galaxy clustering data to sharpen constraints on the EDE model. We perform the first EDE analysis using the full-shape power spectrum likelihood from the Baryon Oscillation Spectroscopic Survey (BOSS), based on the effective field theory (EFT) of LSS. The inclusion of this likelihood in the EDE analysis yields a $25\%$ tighter error bar on $H_0$ compared to primary CMB data alone, yielding $H_0 = 68.54^{+0.52}_{-0.95}$ km/s/Mpc ($68\%$ CL). In addition, we constrain the maximum fractional energy density contribution of the EDE to $f_{\rm EDE} < 0.072$ ($95\%$ CL). We explicitly demonstrate that the EFT BOSS likelihood yields much stronger constraints on EDE than the standard BOSS likelihood. Including further information from photometric LSS surveys,the constraints narrow by an additional $20\%$, yielding $H_0 = 68.73^{+0.42}_{-0.69}$ km/s/Mpc ($68\%$ CL) and $f_{\rm EDE}<0.053$ ($95\%$ CL). These bounds are obtained without including local-universe $H_0$ data, which is in strong tension with the CMB and LSS, even in the EDE model. We also refute claims that MCMC analyses of EDE that omit SH0ES from the combined dataset yield misleading posteriors. Finally, we demonstrate that upcoming Euclid/DESI-like spectroscopic galaxy surveys can greatly improve the EDE constraints. We conclude that current data preclude the EDE model as a resolution of the Hubble tension, and that future LSS surveys can close the remaining parameter space of this model. | astrophysics |
In this paper we prove, for G a connected reductive algebraic group satisfying a technical assumption, that the Satake category of G (with coefficients in a finite field, a finite extension of Q_l, or the ring of integers of such a field) can be described via Iwahori-Whittaker perverse sheaves on the affine Grassmannian. As an application, we confirm a conjecture of Juteau-Mautner-Williamson describing the tilting objects in the Satake category. | mathematics |
Graph representation learning is an important task with applications in various areas such as online social networks, e-commerce networks, WWW, and semantic webs. For unsupervised graph representation learning, many algorithms such as Node2Vec and Graph-SAGE make use of "negative sampling" and/or noise contrastive estimation loss. This bears similar ideas to contrastive learning, which "contrasts" the node representation similarities of semantically similar (positive) pairs against those of negative pairs. However, despite the success of contrastive learning, we found that directly applying this technique to graph representation learning models (e.g., graph convolutional networks) does not always work. We theoretically analyze the generalization performance and propose a light-weight regularization term that avoids the high scales of node representations' norms and the high variance among them to improve the generalization performance. Our experimental results further validate that this regularization term significantly improves the representation quality across different node similarity definitions and outperforms the state-of-the-art methods. | computer science |
Understanding thermal transport through nanoscale van der Waals interfaces is vital for addressing thermal management challenges in nanoelectronic devices. In this work, the interfacial thermal conductance (GCA) between copper phthalocyanine (CuPc) nanoribbons is reported to be on the order of 10^5 Wm-2K-1 at 300 K, which is over two orders of magnitude lower than the value predicted by molecular dynamics (MD) simulations for a perfectly smooth interface between two parallelly aligned CuPc nanoribbons. Further MD simulations and contact mechanics analysis reveal that surface roughness can significantly reduce the adhesion energy and effective contact area between CuPc nanoribbons, and thus result in an ultralow GCA. In addition, the adhesion energy at the interface also depends on the stacking configuration of two CuPc nanoribbons, which may also contribute to the observed ultralow GCA. | physics |
Dual-energy computed tomography has great potential in material characterization and identification, whereas the reconstructed material-specific images always suffer from magnified noise and beam hardening artifacts. In this study, a data-driven approach using dual interactive Wasserstein generative adversarial networks is proposed to improve the material decomposition accuracy. Specifically, two interactive generators are used to synthesize the corresponding material images and different loss functions for training the decomposition model are incorporated to preserve texture and edges in the generated images. Besides, a selector is employed to ensure the modelling ability of two generators. The results from both the simulation phantoms and real data demonstrate the advantages of this method in suppressing the noise and beam hardening artifacts. | physics |
Pattern formation analysis of eco-epidemiological models with cannibalism and disease has been less explored in the literature. Therefore, motivated by this, we have proposed a diffusive eco-epidemiological model and performed pattern formation analysis in the model system. Sufficient conditions for local asymptotic stability and global asymptotic stability for the constant positive steady state are obtained by linearization and Lyapunov function technique. A priori estimate for the positive steady state is obtained for the nonexistence of the nonconstant positive solution using Cauchy and Poincar\'e inequality. The existence of the nonconstant positive steady states is studied using Leray-Schauder degree theory. The importance of the diffusive coefficients which are responsible for the appearance of stationary patterns is observed. Pattern formation is done using numerical simulation. Further, the effect of the cannibalism and disease are observed on the dynamics of the proposed model system. The movements of prey and susceptible predator plays a significant role in pattern formation. These movements cause stationary and non-stationary patterns. It is observed that an increment in the movement of the susceptible predator as well as cannibalistic attack rate converts non-Turing patterns to Turing patterns. Lyapunov spectrum is calculated for quantification of stable and unstable dynamics. Non-Turing patterns obtained with parameter set having unstable limit cycle are more interesting and realistic than stationary patterns. Stationary and non-stationary non-Turing patterns are obtained. | mathematics |
We classify AdS$_3$ solutions preserving $\mathcal{N}=(8,0)$ supersymmetry in ten and eleven dimensions and find the local form of each of them. These include the AdS$_3\times$S$^6$ solution of \cite{Dibitetto:2018ftj} and the embeddings of AdS$_3$ into AdS$_4\times$S$^7$, AdS$_5\times$S$^5$, AdS$_7/\mathbb{Z}_k\times$S$^4$ and its IIA reduction within AdS$_7$. More interestingly we find solutions preserving the superconformal algebras $\mathfrak{f}_4$, $\mathfrak{su}(1,1|4)$, $\mathfrak{osp}(4^*|4)$ on certain squashings of the 7-sphere. These solutions asymptote to AdS$_4\times$S$^7$ and are promising candidates for holographic duals to defects in Chern-Simons matter theories. | high energy physics theory |
Diamond quantum processors consisting of a nitrogen-vacancy (NV) centre and surrounding nuclear spins have been the key to significant advancements in room-temperature quantum computing, quantum sensing and microscopy. The optimisation of these processors is crucial for the development of large-scale diamond quantum computers and the next generation of enhanced quantum sensors and microscopes. Here, we present a full model of multi-qubit diamond quantum processors and develop a semi-analytical method for designing gate pulses. This method optimises gate speed and fidelity in the presence of random control errors and is readily compatible with feedback optimisation routines. We theoretically demonstrate infidelities approaching $\sim 10^{-5}$ for single-qubit gates and established evidence that this can also be achieved for a two-qubit CZ gate. Consequently, our method reduces the effects of control errors below the errors introduced by hyperfine field misalignment and the unavoidable decoherence that is intrinsic to the processors. Having developed this optimal control, we simulated the performance of a diamond quantum processor by computing quantum Fourier transforms. We find that the simulated diamond quantum processor is able to achieve fast operations with low error probability. | quantum physics |
We consider topologically twisted $\mathcal{N}=2$, $SU(2)$ gauge theory with a massive adjoint hypermultiplet on a smooth, compact four-manifold $X$. A consistent formulation requires coupling the theory to a ${\rm Spin}^c$ structure, which is necessarily non-trivial if $X$ is non-spin. We derive explicit formulae for the topological correlation functions when $b_2^+\geq 1$. We demonstrate that, when the ${\rm Spin}^c$ structure is canonically determined by an almost complex structure and the mass is taken to zero, the path integral reproduces known results for the path integral of the $\mathcal{N}=4$ gauge theory with Vafa-Witten twist. On the other hand, we reproduce results from Donaldson-Witten theory after taking a suitable infinite mass limit. The topological correlators are functions of the UV coupling constant $\tau_{\rm uv}$ and we confirm that they obey the expected $S$-duality transformation laws. The holomorphic part of the partition function is a generating function for the Euler numbers of the matter (or obstruction) bundle over the instanton moduli space. For $b_2^+=1$, we derive a non-holomorphic contribution to the path integral, such that the partition function and correlation functions are mock modular forms rather than modular forms. We comment on the generalization of this work to the large class of $\mathcal{N}=2$ theories of class $S$. | high energy physics theory |
The universality of the QCD equation of state near the critical point is expressed by mapping pressure as a function of temperature $T$ and baryon chemical potential $\mu$ in QCD to Gibbs free energy as a function of reduced temperature $r$ and magnetic field $h$ in the Ising model. The mapping parameters are, in general, not universal, i.e., determined by details of the microscopic dynamics, rather than by symmetries and long-distance dynamics. In this paper we point out that in the limit of small quark masses, when the critical point is close to the tricritical point, the mapping parameters show universal dependence on the quark mass $m_q$. In particular, the angle between the $r=0$ and $h=0$ lines in the $(\mu,T)$ plane vanishes as $m_q^{2/5}$. We discuss possible phenomenological consequences of these findings. | high energy physics phenomenology |
Beam steering device such as optical phased array (OPA) is a key component in applications of solid-state Lidar and wireless communication. The traditional single-layer optical phased array (OPA) results in a significant energy loss due to the substrate leakage caused by the downward coupling from the grating coupler structure. In this work we have investigated a structure based on multi-layers Si3N4/SiO2 platform that can form a 3-D OPA to emit the light from the edge of the device with high efficiency, a 2-D converged out-coupling beam will be end-fired to the air. The high efficiency and wide horizontal beam steering are demonstrated numerically, the influence of vertical cross-talk, the delay length, number of waveguide layers, and the fabrication feasibility are also discussed. | physics |
We present the complete azimuthal asymmetries at leading twist in terms of fragmentation functions in dihadron production semi-inclusive electron positron annihilation process. When the non-trivial $\theta$ vacuum is taken into consideration, the parity symmetry of quantum chromodynamics is violated. As a consequence of the $local$ $\mathcal{P}$-odd effects, $\mathcal{P}$-odd fragmentation functions would contribute to the azimuthal asymmetries. Azimuthal asymmetry coming from two interference terms with opposite signs vanishes when sum over many events. This symmetry only survives on the event-by-event basis. Azimuthal asymmetry coming from two interference terms with same signs survives and can be measured to extract the $\mathcal{P}$-odd fragmentation functions. We also present the hadron polarizations. | high energy physics phenomenology |
Trapped atomic ions embedded in optical cavities are a promising platform to enable long-distance quantum networks and their most far-reaching applications. Here we achieve and analyze photon indistinguishability in a telecom-converted ion-cavity system. First, two-photon interference of cavity photons at their ion-resonant wavelength is observed and found to reach the limits set by spontaneous emission. Second, this limit is shown to be preserved after a two-step frequency conversion replicating a distributed scenario, in which the cavity photons are converted to the telecom C band and then back to the original wavelength. The achieved interference visibility and photon efficiency would allow for the distribution and practical verification of entanglement between ion-qubit registers separated by several tens of kilometers. | quantum physics |
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