December 2020 arXiv papers — page 127

J. C. G. Henriques, M. F. C. Martins Quintela, N. M. R. Peres

In this paper we develop a fully microscopic theory of the polarizability of excitons in transition metal dichalcogenides. We apply our method to the description of the excitation $2$p dark states. These states are not observable in absorption experiments but can be excited in a pump-probe experiment. As an example we consider $2$p dark states in WSe\textsub

Pilar Hernández, Fernando Romero-López

We review recent progress in the study of the large $N_c$ limit of gauge theories from lattice simulations. The focus is not only the planar limit but also the size of ${\mathcal O}(N_c^{-1})$ corrections for values of $N_c\gtrsim 3$. Some concrete examples of the topics we include are tests of large-$N_c$ factorization, the topological susceptibility, the g

Abba M. Krieger, David Azriel, Adam Kapelner

We present a new experimental design procedure that divides a set of experimental units into two groups in order to minimize error in estimating an additive treatment effect. One concern is minimizing error at the experimental design stage is large covariate imbalance between the two groups. Another concern is robustness of design to misspecification in resp

Weixuan Lin, Eilyan Bitar

We consider the decentralized control of a discrete-time time-varying linear system subject to additive disturbances and polyhedral constraints on the state and input trajectories. The underlying system is composed of a finite collection of dynamically coupled subsystems, where each subsystem is assumed to have a dedicated local controller. The decentralizat

Mehrnaz Amjadi, Seyed Danial Mohseni Taheri, Theja Tulabandhula

Sequential recommendation systems model dynamic preferences of users based on their historical interactions with platforms. Despite recent progress, modeling short-term and long-term behavior of users in such systems is nontrivial and challenging. To address this, we present a solution enhanced by a knowledge graph called KATRec (Knowledge Aware aTtentive se

Aymene Mohammed Bouayed, Karim Atif, Rachid Deriche, Abdelhakim Saim

In this paper, we introduce a unique variant of the denoising Auto-Encoder and combine it with the perceptual loss to classify images in an unsupervised manner. The proposed method, called Pseudo Labelling, consists of first applying a randomly sampled set of data augmentation transformations to each training image. As a result, each initial image can be con

Jiunn-Kai Huang, Chenxi Feng, Madhav Achar, Maani Ghaffari

Sensor calibration, which can be intrinsic or extrinsic, is an essential step to achieve the measurement accuracy required for modern perception and navigation systems deployed on autonomous robots. To date, intrinsic calibration models for spinning LiDARs have been based on hypothesized based on their physical mechanisms, resulting in anywhere from three to

Alexander Belavin, Vladimir Belavin, Gleb Koshevoy

We consider the multiple Calaby-Yau (CY) mirror phenomenon which appears in Berglund-Hübsch-Krawitz (BHK) mirror symmetry. We show that for any pair of Calabi--Yau orbifolds that are BHK mirrors of a loop--chain type pair of Calabi--Yau manifolds in the same weighted projective space the periods of the holomorphic nonvanishing form coincide.

Wang Zhijian, Yao Qingmei

This paper investigates the reality and accuracy of evolutionary game dynamics theory in human game behavior experiments. In classical game theory, the central concept is Nash equilibrium, which reality and accuracy has been well known since the firstly illustration by the O'Neill game experiment in 1987. In game dynamics theory, the central approach is

Peng Wang, Gang Xin, Yuwei Jiao

In this letter, by establishing the Schr\"odinger equation of the optimization problem, the optimization problem is transformed into a constrained state quantum problem with the objective function as the potential energy. The mathematical relationship between the objective function and the wave function is established, and the quantum interpretation of the o

Ravi Sundaram, Anil Vullikanti, Haifeng Xu, Fan Yao

The study of strategic or adversarial manipulation of testing data to fool a classifier has attracted much recent attention. Most previous works have focused on two extreme situations where any testing data point either is completely adversarial or always equally prefers the positive label. In this paper, we generalize both of these through a unified framewo

Weihao Xia, Yujiu Yang, Jing-Hao Xue, Baoyuan Wu

In this work, we propose TediGAN, a novel framework for multi-modal image generation and manipulation with textual descriptions. The proposed method consists of three components: StyleGAN inversion module, visual-linguistic similarity learning, and instance-level optimization. The inversion module maps real images to the latent space of a well-trained StyleG

Klaus Thomsen

It is shown that for any infinite dimensional simple unital AF algebra A and any closed lower bounded set K of real numbers containing zero there is a flow on A for which the set of possible inverse temperatures is K.

Prokopii A. Anempodistov

Recently it was shown that there is an anomalous singularity of propagators in spacetimes with horizons for thermal states with non--canonical temperatures. In this paper we extend these observations to the situation when the background geometry is given by the four--dimensional Schwarzschild and Reissner-Nordström black holes. Namely, we demonstrate that th

Yi Zhu, Shixin Xu, Robert S. Eisenberg, Huaxiong Huang

The accumulation of potassium in the narrow space outside nerve cells is a classical subject of biophysics that has received much attention recently. It may be involved in potassium accumulation \textcolor{black}{including} spreading depression, perhaps migraine and some kinds of epilepsy, even (speculatively) learning. Quantitative analysis is likely to hel

Ganesh Del Grosso, Georg Pichler, Pablo Piantanida

Power consumption data is very useful as it allows to optimize power grids, detect anomalies and prevent failures, on top of being useful for diverse research purposes. However, the use of power consumption data raises significant privacy concerns, as this data usually belongs to clients of a power company. As a solution, we propose a method to generate synt

Said El Manouni, Greta Marino, Patrick Winkert

In this paper we study double phase problems with nonlinear boundary condition and gradient dependence. Under quite general assumptions we prove existence results for such problems where the perturbations satisfy a suitable behavior in the origin and at infinity. Our proofs make use of variational tools, truncation techniques and comparison methods. The exis

Benjamin Maschler, Michael Weyrich

In this article, the concepts of transfer and continual learning are introduced. The ensuing review reveals promising approaches for industrial deep transfer learning, utilizing methods of both classes of algorithms. In the field of computer vision, it is already state-of-the-art. In others, e.g. fault prediction, it is barely starting. However, over all fie

Amir Rasouli, Mohsen Rohani, Jun Luo

Pedestrian behavior prediction is one of the major challenges for intelligent driving systems. Pedestrians often exhibit complex behaviors influenced by various contextual elements. To address this problem, we propose BiPed, a multitask learning framework that simultaneously predicts trajectories and actions of pedestrians by relying on multimodal data. Our

Mathias Augustin, Sarah Jenkins, Richard F. L. Evans, Kostya S. Novoselov

Merons are nontrivial topological spin textures highly relevant for many phenomena in solid state physics. Despite their importance, direct observation of such vortex quasiparticles is scarce and has been limited to a few complex materials. Here we show the emergence of merons and antimerons in recently discovered two-dimensional (2D) CrCl3 at zero magnetic

Omer Yair, Tomer Michaeli

Contrastive divergence (CD) learning is a classical method for fitting unnormalized statistical models to data samples. Despite its wide-spread use, the convergence properties of this algorithm are still not well understood. The main source of difficulty is an unjustified approximation which has been used to derive the gradient of the loss. In this paper, we

Hunyong Cho, Shannon T. Holloway, David J. Couper, Michael R. Kosorok

We propose a reinforcement learning method for estimating an optimal dynamic treatment regime for survival outcomes with dependent censoring. The estimator allows the failure time to be conditionally independent of censoring and dependent on the treatment decision times, supports a flexible number of treatment arms and treatment stages, and can maximize eith

Walid Aljoby, Xin Wang, Dinil Mon Divakaran, Tom Z. J. Fu

Continuing the current trend, Internet traffic is expected to grow significantly over the coming years, with video traffic consuming the biggest share. On the one hand, this growth poses challenges to access providers (APs), who have to upgrade their infrastructure to meet the growing traffic demands as well as find new ways to monetize their network resourc

Zewei Long, Liwei Che, Yaqing Wang, Muchao Ye

Federated learning (FL) has emerged as an effective technique to co-training machine learning models without actually sharing data and leaking privacy. However, most existing FL methods focus on the supervised setting and ignore the utilization of unlabeled data. Although there are a few existing studies trying to incorporate unlabeled data into FL, they all

Luchan Zhang, Xiaoxue Qin, Yang Xiang

In order to relieve the misfitting elastic energy, the hetero-interfaces become semicoherent by forming networks of dislocations. These microscopic structures strongly influence the materials properties associated with the development of advanced materials. We develop a continuum model for the dislocation structures of semicoherent interfaces. The classical

Teng Man, Herbert E. Huppert, Ling Li, Sergio Andres Galindo-Torres

In this letter, we focus on the size effect of granular column collapses, which are potentially connected to the dynamics of complex geophysical flows, even if the link between microscopic structures of granular assemblies and their macroscopic behaviors is still not well understood. Using the sphero-polyhedral discrete element method (DEM), we show that the

Jianwei Huang, Vinod Yegneswaran, Phillip Porras, Guofei Gu

Smartphone-based contact-tracing applications are at the epicenter of the global fight against the Covid-19 pandemic. While governments and healthcare agencies are eager to mandate the deployment of such applications en-masse, they face increasing scrutiny from the popular press, security companies, and human rights watch agencies that fear the exploitation

P. S. Howe, U. Lindström

Superconformal geometries in spacetime dimensions $D=3,4,{5}$ and $6$ are discussed in terms of local supertwistor bundles over standard superspace. These natually admit superconformal connections as matrix-valued one-forms. In order to make contact with the standard superspace formalism it is shown that one can always choose gauges in which the scale parts

Meirav Amram, Cheng Gong, Uriel Sinichkin, Sheng-Li Tan

In this paper we consider the Galois covers of algebraic surfaces of degree 6, with all associated planar degenerations. We compute the fundamental groups of those Galois covers, using their degeneration. We show that for 8 types of degenerations the fundamental group of the Galois cover is non-trivial and for 20 types it is trivial. Moreover, we compute the

Dahvyd Wing, Guy Ohad, Jonah B. Haber, Marina R. Filip

Accurate prediction of fundamental band gaps of crystalline solid state systems entirely within density functional theory is a long standing challenge. Here, we present a simple and inexpensive method that achieves this by means of non-empirical optimal tuning of the parameters of a screened range-separated hybrid functional. The tuning involves the enforcem

Alexander Fengler, Peter Jung, Giuseppe Caire

In this work we treat the unsourced random access problem on a Rayleigh block-fading AWGN channel with multiple receive antennas. Specifically, we consider the slowly fading scenario where the coherence block-length is large compared to the number of active users and the message can be transmitted in one coherence block. Unsourced random access refers to a f

Emma Horton, Alexander R. Watson

Growth-fragmentation processes model systems of cells that grow continuously over time and then fragment into smaller pieces. Typically, on average, the number of cells in the system exhibits asynchronous exponential growth and, upon compensating for this, the distribution of cell sizes converges to an asymptotic profile. However, the long-term stochastic be

Yakov Babichenko, Inbal Talgam-Cohen, Konstantin Zabarnyi

Bayesian persuasion is the study of information sharing policies among strategic agents. A prime example is signaling in online ad auctions: what information should a platform signal to an advertiser regarding a user when selling the opportunity to advertise to her? Practical considerations such as preventing discrimination, protecting privacy or acknowledgi

Bobing Ye, Xuefeng Zhang, Yanwei Ding, Yunhe Meng

In future geocentric space-based gravitational-wave observatory missions, eclipses due to passing through the Moon's and Earth's shadows can negatively impact the sciencecraft's thermal stability and steady power supply. The occurrence should be reduced as much as possible in orbit design. In regard to TianQin's circular high orbits, we tackl

Yasmina Becis-Aubry

This contribution proposes a recursive, computationally efficient, ready-to-use, online method for the ellipsoidal state characterization for linear discrete-time models with additive unknown disturbances vectors (bounded by known possibly degenerate zonotopes) corrupting both the state difference equation and the sporadic measurement vectors, which are expr

Gongjun Choi, Tsutomu T. Yanagida, Norimi Yokozaki

A keV-scale gravitino arsing from a minimal supersymmetric (SUSY) Standard Model (MSSM) is an interesting possibility since the small scale problems that $Λ$CDM model encounters in the modern cosmology could be alleviated with the keV-scale gravitino serving as the warm dark matter (WDM). Such a light gravitino asks for a low scale supersymmetry (SUSY) break

Zehui Gong, Dong Li

It is a common practice to exploit pyramidal feature representation to tackle the problem of scale variation in object instances. However, most of them still predict the objects in a certain range of scales based solely or mainly on a single-level representation, yielding inferior detection performance. To this end, we propose a novel adaptive feature select

Xuefeng Zhang, Chengjian Luo, Lei Jiao, Bobing Ye

TianQin is a proposed space gravitational-wave detection mission using circular high Earth orbits. The geocentric concept has raised questions about the disturbing effect of the nearby gravity field of the Earth-Moon system on the highly-sensitive intersatellite ranging measurements. Here we examine the issue through high precision numerical orbit simulation

Philipp Strasberg, María García Díaz, Andreu Riera-Campeny

We study entropy production in nanoscale devices, which are coupled to finite heat baths. This situation is of growing experimental relevance, but most theoretical approaches rely on a formulation of the second law valid only for infinite baths. We fix this problem by pointing out that already Clausius' paper from 1865 contains an adequate formulation of the

Ming-xing Luo, Tong-Zhi Yang, Hua Xing Zhu, Yu Jiao Zhu

In this paper we calculate analytically the perturbative matching coefficients for unpolarized quark and gluon Transverse-Momentum-Dependent (TMD) Parton Distribution Functions (PDFs) and Fragmentation Functions (FFs) through Next-to-Next-to-Next-to-Leading Order (N$^3$LO) in QCD. The N$^3$LO TMD PDFs are calculated by solving a system of differential equati

Abdullah Abuolaim, Mauricio Delbracio, Damien Kelly, Michael S. Brown

Recent work has shown impressive results on data-driven defocus deblurring using the two-image views available on modern dual-pixel (DP) sensors. One significant challenge in this line of research is access to DP data. Despite many cameras having DP sensors, only a limited number provide access to the low-level DP sensor images. In addition, capturing traini

Kentaro Ueda, Hikaru Fukuda, Ryoma Kaneko, Jun Fujioka

We study possible Weyl semimetals of strongly-correlated electrons by investigating magnetotransport properties in pyrochlore R2Ir2O7 (R=rare-earth ions), choosing three types of R ions to design the exchange coupling scheme between R 4f and Ir 5d moments; non-magnetic Eu (4f6), isotropic Gd (4f7), and anisotropic Tb (4f8). In the doping-induced semimetallic

Lev Beklemishev, Anna Dmitrieva, Johann A. Makowsky

We provide a variant of an axiomatization of elementary geometry based on logical axioms in the spirit of Huzita--Justin axioms for the Origami constructions. We isolate the fragments corresponding to natural classes of Origami constructions such as Pythagorean, Euclidean, and full Origami constructions. The sets of Origami constructible points for each of t

Olga Borysenko, Oleksandr Borysenko

It is proved the existence and uniqueness of the global positive solution to the system of stochastic differential equations describing a non-autonomous stochastic predator-prey model with a modified version of Leslie-Gower and Holling-type II functional response disturbed by white noise, centered and non-centered Poisson noises. We obtain sufficient conditi

Gianluca Mastrantonio

GPS technology is currently easily accessible to researchers, and many animal movement datasets are available. Two of the main features that a model which describes an animal's path can possess are directional persistence and attraction to a point in space. In this work, we propose a new approach that can have both characteristics. Our proposal is a hidden M

Q. Z. Li, S. Shallcross, J. K. Dewhurst, S. Sharma

The coupling of laser light to matter can exert sub-cycle coherent control over material properties, with optically induced currents and magnetism shown to be controllable on ultrafast femtosecond time scales. Here, by employing laser light consisting of both linear and circular pulses, we show that charge of specified spin and crystal momentum can be create

Damian Osajda, Motiejus Valiunas

A simplicial graph is said to be (coarsely) Helly if any collection of pairwise intersecting balls has non-empty (coarse) intersection. (Coarsely) Helly groups are groups acting geometrically on (coarsely) Helly graphs. Our main result is that finitely generated groups that are hyperbolic relative to (coarsely) Helly subgroups are themselves (coarsely) Helly

Jia-Qi Yang, Xiang Li, Shuguang Han, Tao Zhuang

Conversion rate (CVR) prediction is one of the most critical tasks for digital display advertising. Commercial systems often require to update models in an online learning manner to catch up with the evolving data distribution. However, conversions usually do not happen immediately after a user click. This may result in inaccurate labeling, which is called d

Meir Shimon

The apparent missing mass in galaxies and galaxy clusters, commonly viewed as evidence for dark matter, could possibly originate from gradients in the gravitational coupling parameter, $G$, and active gravitational mass, $M_{act}$, rather than hypothetical beyond-the-standard-model particles. We argue that in (the weak field limit of) a Weyl-invariant extens

Lifeng Wang, Yu Duan, Yun Lai, Shizhuo Mu

This paper studies the vehicle platooning system based on vehicle-to-infrastructure (V2I) communication, where all the vehicles in the platoon upload their driving state information to the roadside unit (RSU), and RSU makes the platoon control decisions with the assistance of edge computing. By addressing the delay concern, a platoon control approach is prop

Sahar Yousefi, Hessam Sokooti, Mohamed S. Elmahdy, Irene M. Lips

Manual or automatic delineation of the esophageal tumor in CT images is known to be very challenging. This is due to the low contrast between the tumor and adjacent tissues, the anatomical variation of the esophagus, as well as the occasional presence of foreign bodies (e.g. feeding tubes). Physicians therefore usually exploit additional knowledge such as en

George Ellis, Carole Bloch

Significant challenges exist globally regarding literacy teaching and learning. To address these challenges, key features of how the brain works should be taken into account. First, perception is an active process based in detection of errors in hierarchical predictions of sensory data and action outcomes. Reading is a particular case of this non-linear pred

G. Carlet, J. van de Leur, H. Posthuma, S. Shadrin

We consider the Dubrovin--Frobenius manifold of rank $2$ whose genus expansion at a special point controls the enumeration of a higher genera generalization of the Catalan numbers, or, equivalently, the enumeration of maps on surfaces, ribbon graphs, Grothendieck's dessins d'enfants, strictly monotone Hurwitz numbers, or lattice points in the moduli

Julien Korinman

We provide finite presentations for stated skein algebras and deduce that those algebras are Koszul and that they are isomorphic to the quantum moduli algebras appearing in lattice gauge field theory, generalizing previous results of Bullock, Frohman, Kania-Bartoszynska and Faitg.

Defang Chen, Jian-Ping Mei, Yuan Zhang, Can Wang

Knowledge distillation is a technique to enhance the generalization ability of a student model by exploiting outputs from a teacher model. Recently, feature-map based variants explore knowledge transfer between manually assigned teacher-student pairs in intermediate layers for further improvement. However, layer semantics may vary in different neural network

David Ellis

In this very short paper, we point out that the average overlap density of a union-closed family $\mathcal{F}$ of subsets of $\{1,2,\ldots,n\}$ may be as small as $\Theta((\log \log |\mathcal{F}|)/(\log |\mathcal{F}|))$, for infinitely many positive integers $n$.

Xiaotong Guo, Qiusheng Gu, Nan Ding, Xiaoling Yu

Even in deep X-ray surveys, Compton-thick active galactic nuclei (CT AGNs, ${\rm N_H} \geqslant 1.5~\times~10^{24}~{\rm cm}^{-2}$) are difficult to be identified due to X-ray flux suppression and their complex spectral shape. However, the study of CT AGNs is vital for understanding the rapid growth of black holes and the origin of cosmic X-ray background. In

Kaushal K. Kesharpu, Vladislav D. Kochev, Pavel D. Grigoriev

In highly anisotropic organic superconductor (TMTSF)$_2$ClO$_4$, superconducting (SC) phase coexists with metallic and spin density wave phases in the form of domains. Using the Maxwell-Garnett approximation (MGA), we calculate the volume ratio and estimate the shape of these embedded SC domains from resistivity data at various temperature and anion disorder

Bartłomiej Bosek, Jarosław Grytczuk, Grzegorz Gutowski, Oriol Serra

Let $\Gamma$ be an Abelian group and let $G$ be a simple graph. We say that $G$ is $\Gamma$-colorable if for some fixed orientation of $G$ and every edge labeling $\ell:E(G)\rightarrow \Gamma$, there exists a vertex coloring $c$ by the elements of $\Gamma$ such that $c(y)-c(x)\neq \ell(e)$, for every edge $e=xy$ (oriented from $x$ to $y$). Langhede and Thoma

Beatriz Pascual-Escudero, Linard Hoessly

Exact results for product-form stationary distributions of Markov chains are of interest in different fields. In stochastic reaction networks (CRNs), stationary distributions are mostly known in special cases where they are of product-form. However, there is no full characterization of the classes of networks whose stationary distributions have product-form.

Yuye Wang, Shuwen Zeng, Aurelian Crunteanu, Zhenming Xie

Detection of small cancer biomarkers with low molecular weight and a low concentration range has always been challenging yet urgent in many clinical applications such as diagnosing early-stage cancer, monitoring treatment and detecting relapse. Here, a highly enhanced plasmonic biosensor that can overcome this challenge using atomically thin two-dimensional

Hao Wu, Peizhen Xu, Xin Guo, Pan Wang

The ability to generate a laser field with ultratight spatial confinement is important for pushing the limit of optical science and technology. Although plasmon lasers can offer sub-diffraction-confined laser fields, it is restricted by a trade-off between optical confinement and loss of free-electron oscillation in metals. We show here an all-dielectric nan

Marco Comunità, Dan Stowell, Joshua D. Reiss

Despite the popularity of guitar effects, there is very little existing research on classification and parameter estimation of specific plugins or effect units from guitar recordings. In this paper, convolutional neural networks were used for classification and parameter estimation for 13 overdrive, distortion and fuzz guitar effects. A novel dataset of proc

Umar Marikkar, A. S. Jameel Hassan, Mihitha S. Maithripala, Roshan I. Godaliyadda

The integration of renewable resources has increased in power generation as a means to reduce the fossil fuel usage and mitigate its adverse effects on the environment. However, renewables like solar energy are stochastic in nature due to its high dependency on weather patterns. This uncertainty vastly diminishes the benefit of solar panel integration and in

Jin-woo Lee, Jaehoon Oh, Sungsu Lim, Se-Young Yun

Federated learning has emerged as a new paradigm of collaborative machine learning; however, many prior studies have used global aggregation along a star topology without much consideration of the communication scalability or the diurnal property relied on clients' local time variety. In contrast, ring architecture can resolve the scalability issue and even

Turgay Pamuklu, Melike Erol-Kantarci, Cem Ersoy

With the growing momentum around Open RAN (O-RAN) initiatives, performing dynamic Function Splitting (FS) in disaggregated and virtualized Radio Access Networks (vRANs), in an efficient way, is becoming highly important. An equally important efficiency demand is emerging from the energy consumption dimension of the RAN hardware and software. Supplying the RA

Saeed Fakhry, Javad T. Firouzjaee, Mehrdad Farhoudi

We have studied the merger rate of primordial black holes (PBHs) in the ellipsoidal-collapse model of halo to explain the dark matter abundance by the PBH merger estimated from the gravitational waves detections via the Advanced LIGO (aLIGO) detectors. We have indicated that the PBH merger rate within each halo for the ellipsoidal models is more significant

Yury Demidovich, Maksim Zhukovskii

The clique chromatic number of a graph is the minimum number of colors required to assign to its vertex set so that no inclusion maximal clique is monochromatic. McDiarmid, Mitsche and Pra\l at proved that the clique chromatic number of the binomial random graph $G\left(n,\frac{1}{2}\right) $ is at most $\left(\frac{1}{2}+o(1)\right)\log_2n$ with high probab

Wei Wang, Xiaofu Xiong, Yufei He, Jian Hu

Mobile energy resources (MERs) have been shown to boost DS resilience effectively in recent years. In this paper, we propose a novel idea, the separable mobile energy storage system (SMESS), as an attempt to further extend the flexibility of MER applications. "Separable" denotes that the carrier and the energy storage modules are treated as independent parts

Kunal Pratap Singh, Suvaansh Bhambri, Byeonghwi Kim, Roozbeh Mottaghi

Performing simple household tasks based on language directives is very natural to humans, yet it remains an open challenge for AI agents. The 'interactive instruction following' task attempts to make progress towards building agents that jointly navigate, interact, and reason in the environment at every step. To address the multifaceted problem, we propose a

Xingyu Gao, Siddhant Pandey, Mehran Kianinia, Jonghoon Ahn

Optically active spin defects in wide-bandgap materials have many potential applications in quantum information and quantum sensing. Spin defects in two-dimensional layered van der Waals materials are just emerging to be investigated. Here we demonstrate that optically-addressable spin ensembles in hexagonal boron nitride (hBN) can be generated by femtosecon

Rui Fan, Li Wang, Mohammud Junaid Bocus, Ioannis Pitas

As an important component of autonomous systems, autonomous car perception has had a big leap with recent advances in parallel computing architectures. With the use of tiny but full-feature embedded supercomputers, computer stereo vision has been prevalently applied in autonomous cars for depth perception. The two key aspects of computer stereo vision are sp

Xingyu Gao, Chinmay Khandekar, Zubin Jacob, Tongcang Li

Spin and orbital angular momentum of light plays a central role in quantum nanophotonics as well as topological electrodynamics. Here, we show that the thermal radiation from finite-sized bodies comprising of nonreciprocal magneto-optical materials can exert a spin torque even in global thermal equilibrium. Moving beyond the paradigm of near-field heat trans

Charles Hellaby, Robert G. Buckley

Recent work on the Szekeres inhomogeneous cosmological models uncovered a surprising rotation effect. Hellaby showed that the angular $(θ, ϕ)$ coordinates do not have a constant orientation, while Buckley and Schlegel provided explicit expressions for the rate of rotation from shell to shell, as well as the rate of tilt when the 3-space is embedded in a flat

Mao-Sen Qin, Peng-Fei Zhu, Xing-Guo Ye, Wen-Zheng Xu

The electronic topology is generally related to the Berry curvature, which can induce the anomalous Hall effect in time-reversal symmetry breaking systems. Intrinsic monolayer transition metal dichalcogenides possesses two nonequivalent K and K' valleys, having Berry curvatures with opposite signs, and thus vanishing anomalous Hall effect in this system.

Tomonari Mizoguchi, Tohru Koma

We study edge modes in topological semimetals which have an energy band structure of ordinary semimetals but can be characterized by a Chern number. More specifically, we focus on a Qi-Wu-Zhang-type square-lattice model and a Haldane-type honeycomb model, both of which exhibit antichiral edge modes whose wave packets propagate in the same direction at both p

Younjin Kim

A subset $A$ of the $k$-dimensional grid $\{1,2, \cdots, N\}^k$ is called $k$-dimensional corner-free if it does not contain a set of points of the form $\{ a \} \cup \{ a + de_i : 1 \leq i \leq k \}$ for some $a \in \{1,2, \cdots, N\}^k$ and $d > 0$, where $e_1,e_2, \cdots, e_k$ is the standard basis of $\mathbb{R}^k$. We define the maximum size of a $k$-di

Zhenisbek Tagay, Fahad Mahmood, Anaelle Legros, Tarapada Sarkar

Although cuprate superconductors have been intensively studied for the past decades, there is no consensus regarding the microscopic origin of their superconductivity. In this work, we measure the low-energy electrodynamic response of slightly underdoped and overdoped La$_{2-x}$Ce$_x$CuO$_4$ thin films using time-domain terahertz (THz) spectroscopy to determ

Jiti Gao, Fei Liu, Bin Peng, Yayi Yan

In this paper, we investigate binary response models for heterogeneous panel data with interactive fixed effects by allowing both the cross-sectional dimension and the temporal dimension to diverge. From a practical point of view, the proposed framework can be applied to predict the probability of corporate failure, conduct credit rating analysis, etc. Theor

Ya Feng, Henan Li, Taiki Inoue, Shohei Chiashi

The synthesis of one-dimensional van der Waals heterostructures was realized recently, which opens up new possibilities for prospective applications in electronics and optoelectronics. The even reduced dimension will enable novel properties and further miniaturization beyond the capabilities of its two-dimensional counterparts have revealed. The natural dopi

Peng Xiao, Samuel Cheng

In federated learning, models trained on local clients are distilled into a global model. Due to the permutation invariance arises in neural networks, it is necessary to match the hidden neurons first when executing federated learning with neural networks. Through the Bayesian nonparametric framework, Probabilistic Federated Neural Matching (PFNM) matches an

Zhihao Peng, Yuheng Jia, Hui Liu, Junhui Hou

Deep subspace clustering networks have attracted much attention in subspace clustering, in which an auto-encoder non-linearly maps the input data into a latent space, and a fully connected layer named self-expressiveness module is introduced to learn the affinity matrix via a typical regularization term (e.g., sparse or low-rank). However, the adopted regula

Behrooz Tahmasebi, Derek Lim, Stefanie Jegelka

While message passing Graph Neural Networks (GNNs) have become increasingly popular architectures for learning with graphs, recent works have revealed important shortcomings in their expressive power. In response, several higher-order GNNs have been proposed that substantially increase the expressive power, albeit at a large computational cost. Motivated by

Zhuoning Yuan, Yan Yan, Milan Sonka, Tianbao Yang

Deep AUC Maximization (DAM) is a new paradigm for learning a deep neural network by maximizing the AUC score of the model on a dataset. Most previous works of AUC maximization focus on the perspective of optimization by designing efficient stochastic algorithms, and studies on generalization performance of large-scale DAM on difficult tasks are missing. In t

Joshua Ball

Convolutional neural networks (CNNs) have been successful in representing the fully-connected inferencing ability perceived to be seen in the human brain: they take full advantage of the hierarchy-style patterns commonly seen in complex data and develop more patterns using simple features. Countless implementations of CNNs have shown how strong their ability

Tian-Xing Bai, Chun-Gui Duan

The Drell-Yan process for proton incident on nuclei is an excellent place for deeply studying the parton propagation in a nucleus. By means of the nuclear parton distributions determined only with lepton-nuclear deep inelastic scattering experimental data and the analytic parameterization of quenching weight based on BDMPS formalism, a phenomenological analy

Ahmed Kord, Andrea Alu

In this paper, we discuss recent progress in magnet-free non-reciprocal structures based on a synthetic form of angular momentum bias imparted via spatiotemporal modulation. We discuss how such components can support metrics of performance comparable with traditional magnetic-biased ferrite devices, while at the same time offering distinct advantages in term

Fabien Pazuki, Niclas Technau, Martin Widmer

We construct fields of algebraic numbers that have the Lehmer property but not the Bogomolov property. This answers a recent implicit question of Pengo and the first author.

Christopher Vega, Shubhra Deb Paul, Patanjali SLPSK, Swarup Bhunia

Physically Unclonable Functions (PUFs) are used for securing electronic devices across the implementation spectrum ranging from Field Programmable Gate Array (FPGA) to system on chips (SoCs). However, existing PUF implementations often suffer from one or more significant deficiencies: (1) significant design overhead; (2) difficulty to configure and integrate

Xuejiao Tang, Liuhua Zhang, Wenbin Zhang, Xin Huang

Breast cancer is the second leading cause of cancer-related death after lung cancer in women. Early detection of breast cancer in X-ray mammography is believed to have effectively reduced the mortality rate. However, a relatively high false positive rate and a low specificity in mammography technology still exist. In this work, a computer-aided automatic mam

Ido Frenkel, Avi Niv

Thermodynamics is accepted as a universal truth, encompassing all macroscopic objects. Therefore, it is surprising to find that, within our current understanding, the photovoltaic effect has so far eluded the first and second laws of thermodynamics. The inconsistency emerges from the fact that photovoltaics obey a distinct law of detailed balance1. Since rad

Gianluca Rizzi, Geralf Hütter, Angela Madeo, Patrizio Neff

We consider the cylindrical bending problem for an infinite plate as modelled with a family of generalized continuum models, including the micromorphic approach. The models allow to describe length scale effects in the sense that thinner specimens are comparatively stiffer. We provide the analytical solution for each case and exhibit the predicted bending st

Daniel Yarnell, Xian Wang

Automated captioning of photos is a mission that incorporates the difficulties of photo analysis and text generation. One essential feature of captioning is the concept of attention: how to determine what to specify and in which sequence. In this study, we leverage the Object Relation using adversarial robust cut algorithm, that grows upon this method by spe

Nishant Kumar, Stefan Gumhold

Image fusion helps in merging two or more images to construct a more informative single fused image. Recently, unsupervised learning based convolutional neural networks (CNN) have been utilized for different types of image fusion tasks such as medical image fusion, infrared-visible image fusion for autonomous driving as well as multi-focus and multi-exposure

Dhasarathy Parthasarathy, Anton Johansson

Since the behavior of a neural network model is adversely affected by a lack of diversity in training data, we present a method that identifies and explains such deficiencies. When a dataset is labeled, we note that annotations alone are capable of providing a human interpretable summary of sample diversity. This allows explaining any lack of diversity as th

Sergey V Kutsaev, Alex Krasnok, Sergey N. Romanenko, Alexander Yu. Smirnov

Modern photonic and quantum technologies demand reciprocity breaking, e.g., isolators, full-duplex systems, noise isolation in quantum computers, motivating searching for practical approaches beyond magnet-based devices. This work overviews the up-and-coming advances in optical nonreciprocity, including new materials (Weyl semimetals, topological insulators,

Joschua Dilly

In this thesis the creation of nonlinear interference noise (NLIN) in the context of impairment aware flexible optical networks is investigated to estimate transmission quality. In particular, the nonlinear interference of neighboring channels (interferer) during transmission on a channel under test is studied. The modulation format of the interferer, the ac

Purvi Goel, Loudon Cohen, James Guesman, Vikas Thamizharasan

Reconstructing object geometry and material from multiple views typically requires optimization. Differentiable path tracing is an appealing framework as it can reproduce complex appearance effects. However, it is difficult to use due to high computational cost. In this paper, we explore how to use differentiable ray tracing to refine an initial coarse mesh

Yossi Rozantsev

Let $G=(V,E)$ be a simple graph with maximum degree $d$. For an integer $k\in\mathbb{N}$, the $k$-disc of a vertex $v\in V$ is defined as the rooted subgraph of $G$ that is induced by all vertices whose distance to $v$ is at most $k$. The $k$-disc frequency distribution vector of $G$, denoted by $\text{freq}_{k}(G)$, is a vector indexed by all isomorphism ty

Tobias Rindlisbacher

O(N)-symmetric lattice scalar fields are considered, coupled to a chemical potential and source terms. At the example of N=2, it is shown that such systems can even in (0+1) dimensions produce infinite-range correlations and a non-zero vacuum expectation value whenever the chemical potential assumes certain discrete values. Different mechanisms for how the l