May 2022 arXiv papers — page 87

Hector Gisbert

Dineutrino modes offer promising searches for new physics. The potential aspects of these modes are reviewed in detail. Performing a proper combination of them, novel tests of the SM symmetries are derived. Different phenomenological applications are worked out, including charm, beauty and kaons, which result in novel tests of lepton universality and charged

Jaume Ojer, Romualdo Pastor-Satorras

We study the effects of animal social networks with a weighted pattern of interactions on the flocking transition exhibited by models of self-organized collective motion. Considering a model representing dynamics on a one-dimensional substrate, application of a heterogeneous mean-field theory provides a phase diagram as function of the heterogeneity of the n

Yuchen Xing, Keping Qiu

We revisit the mass-size relation of molecular cloud structures based on the column density map of the Cygnus-X molecular cloud complex. We extract 135 column density peaks in Cygnus-X and analyze the column density distributions around these peaks. The averaged column density profiles, $N(R)$, around all the peaks can be well fitted with broken power-laws,

Vasudha Bhatnagar, Swagata Duari, S. K. Gupta

Discourse cohesion facilitates text comprehension and helps the reader form a coherent narrative. In this study, we aim to computationally analyze the discourse cohesion in scientific scholarly texts using multilayer network representation and quantify the writing quality of the document. Exploiting the hierarchical structure of scientific scholarly texts, w

Fynn Bachmann, Philipp Hennig, Dmitry Kobak

Scientific datasets often have hierarchical structure: for example, in surveys, individual participants (samples) might be grouped at a higher level (units) such as their geographical region. In these settings, the interest is often in exploring the structure on the unit level rather than on the sample level. Units can be compared based on the distance betwe

Pedro Antonino, Juliandson Ferreira, Augusto Sampaio, A. W. Roscoe

Smart contracts are the building blocks of the "code is law" paradigm: the smart contract's code indisputably describes how its assets are to be managed - once it is created, its code is typically immutable. Faulty smart contracts present the most significant evidence against the practicality of this paradigm; they are well-documented and resulted in assets

Manuel Bodirsky, Jakub Bulín, Florian Starke, Michael Wernthaler

We find an orientation of a tree with 20 vertices such that the corresponding fixed-template constraint satisfaction problem (CSP) is NP-complete, and prove that for every orientation of a tree with fewer vertices the corresponding CSP can be solved in polynomial time. We also compute the smallest tree that is NL-hard (assuming L is not NL), the smallest tre

Chetan Balwe, Amit Hogadi, Anand Sawant

We show that the sheaf of $\mathbb A^1$-connected components of a reductive algebraic group over a perfect field is strongly $\mathbb A^1$-invariant. As a consequence, torsors under such groups give rise to $\mathbb A^1$-fiber sequences. We also show that sections of $\mathbb A^1$-connected components of anisotropic, semisimple, simply connected algebraic gr

Edvard T. Musaev, Jeffrey P. Molina

We construct the full effective action including DBI and WZ terms for solitonic 5-branes covariant under T-duality. The result is a completion of results known in the literature to a full T-duality covariant expression. The covariant WZ action includes previously omitted R-R terms. The obtained full covariant effective action reproduces the one obtained by S

Haowei Wang, Ercong Zhang, Szu Hui Ng, Giulia Pedrielli

Bayesian optimization (BO) has been widely used in machine learning and simulation optimization. With the increase in computational resources and storage capacities in these fields, high-dimensional and large-scale problems are becoming increasingly common. In this study, we propose a model aggregation method in the Bayesian optimization (MamBO) algorithm fo

Mustafa Kaan Topaloglu, Banu Kabakulak

Textile industry is becoming a highly competitive area with the increase in demand for textile products. Since expanding the production capacity is not always feasible, optimizing the existing system is more practical. In particular, we consider a felt production system of a textile factory operating in Turkey in this study. We aim to minimize the production

Xinyin Ma, Xinchao Wang, Gongfan Fang, Yongliang Shen

Data-free knowledge distillation (DFKD) conducts knowledge distillation via eliminating the dependence of original training data, and has recently achieved impressive results in accelerating pre-trained language models. At the heart of DFKD is to reconstruct a synthetic dataset by inverting the parameters of the uncompressed model. Prior DFKD approaches, how

E. Bachelet, Y. Tsapras, Andrew Gould, R. A. Street

We report on the observations, analysis and interpretation of the microlensing event MOA-2019- BLG-008. The observed anomaly in the photometric light curve is best described through a binary lens model. In this model, the source did not cross caustics and no finite source effects were observed. Therefore the angular Einstein ring radius cannot be measured fr

Wei Wan, Yuejin Zhang, Chenglong Bao, Bin Dong

The dynamic formulation of optimal transport has attracted growing interests in scientific computing and machine learning, and its computation requires to solve a PDE-constrained optimization problem. The classical Eulerian discretization based approaches suffer from the curse of dimensionality, which arises from the approximation of high-dimensional velocit

Liuyuan Wen, Xiaojian Du, Shuzhe Shi, Baoyi Chen

Color screening and parton inelastic scattering modify the heavy-quark antiquark potential in the medium that consists of particles from quantum chromodynamics (QCD), leading to suppression of quarkonium production in relativistic heavy-ion collisions. Due to small charm/anti-charm ($c\bar{c}$) pair production number in proton-nucleus (pA) collisions, the co

Moshe Babaioff, Uriel Feige

We consider fair allocation of a set $M$ of indivisible goods to $n$ equally-entitled agents, with no monetary transfers. Every agent $i$ has a valuation $v_i$ from some given class of valuation functions. A share $s$ is a function that maps a pair $(v_i,n)$ to a value, with the interpretation that if an allocation of $M$ to $n$ agents fails to give agent $i

Fahri Wisnu Murti, Samad Ali, George Iosifidis, Matti Latva-aho

One of the key benefits of virtualized radio access networks (vRANs) is network management flexibility. However, this versatility raises previously-unseen network management challenges. In this paper, a learning-based zero-touch vRAN orchestration framework (LOFV) is proposed to jointly select the functional splits and allocate the virtualized resources to m

Jan Maly, Simon Rey, Ulle Endriss, Martin Lackner

We introduce a family of normative principles to assess fairness in the context of participatory budgeting. These principles are based on the fundamental idea that budget allocations should be fair in terms of the resources invested into meeting the wishes of individual voters. This is in contrast to earlier proposals that are based on specific assumptions r

Tobias Fechter, Ilias Sachpazidis, Dimos Baltas

Deep learning advanced to one of the most important technologies in almost all medical fields. Especially in areas, related to medical imaging it plays a big role. However, in interventional radiotherapy (brachytherapy) deep learning is still in an early phase. In this review, first, we investigated and scrutinised the role of deep learning in all processes

Man Ho Chan, Shantanu Desai, Antonino Del Popolo

Recently, many studies seem to reveal the existence of some correlations between dark matter and baryonic matter. In particular, the unexpected tight Radial Acceleration Relation (RAR) discovered in rotating galaxies has caught much attention. The RAR suggests the existence of a universal and fundamental acceleration scale in galaxies, which seems to challen

Fangyuan Kong, Mingxi Li, Songwei Liu, Ding Liu

Deep learning based approaches has achieved great performance in single image super-resolution (SISR). However, recent advances in efficient super-resolution focus on reducing the number of parameters and FLOPs, and they aggregate more powerful features by improving feature utilization through complex layer connection strategies. These structures may not be

Ryoma Inoba, Kazuki Uchida, Yuto Iwasaki, Takayuki Nagata

This study proposes a method for predicting the wind direction against the simple automobile model (Ahmed model) and the surface pressure distributions on it by using data-driven optimized sparse pressure sensors. Positions of sparse pressure sensor pairs on the Ahmed model were selected for estimation of the yaw angle and reconstruction of pressure distribu

Shijie Bao, Qi'an Guan, Zhitong Mi, Zheng Yuan

In this article, we present characterizations of the concavity property of minimal $L^2$ integrals with negligible weights degenerating to linearity on the fibrations over open Riemann surfaces and the fibrations over products of open Riemann surfaces. As applications, we obtain characterizations of the holding of equality in optimal jets $L^2$ extension pro

E. Churazov, I. Khabibullin, A. M. Bykov, N. Lyskova

This is the second paper in a series of studies of the Coma cluster using the SRG/eROSITA X-ray data obtained during the calibration and performance verification phase of the mission. Here, we focus on the region adjacent to the radio source 1253+275 (radio relic, RR, hereafter). We show that the X-ray surface brightness exhibits its steepest gradient at $\s

Shoko Wakamiya, Toshiki Mera, Eiji Aramaki, Masaki Matsubara

A clinical study is often necessary for exploring important research questions; however, this approach is sometimes time and money consuming. Another extreme approach, which is to collect and aggregate opinions from crowds, provides a result drawn from the crowds' past experiences and knowledge. To explore a solution that takes advantage of both the rigid cl

Munayim Dilxat, Liangyun Chen, Dong Liu

With the $\Omega$-operators for the Virasoro algebra \cite{BF} and the super Virasoro algebra in \cite{CL, CLL}, we get the $\Omega$-operators for the Ovsienko-Roger superalgebras in this paper and then use it to classify all simple cuspidal modules for the $\bZ$-graded and $\frac12\bZ$-graded Ovsienko-Roger superalgebras. By this result, we can easily class

A. Yanilmaz, M. Fidan, O. Unverdi, C. Celebi

We have fabricated 4-element Graphene/Silicon on Insulator (SOI) based Schottky barrier photodiode array ()PDA and investigated its optoelectronic device performance. In our device design, monolayer graphene is utilized as common electrode on lithographically defined linear array of n-type Si channels on SOI substrate. As revealed by wavelength resolved phot

Stephen DiAdamo, Bing Qi, Glen Miller, Ramana Kompella

Large-scale quantum networks with thousands of nodes require scalable network protocols and physical hardware to realize. In this work, we introduce packet switching as a new paradigm for quantum data transmission in both future and near-term quantum networks. We propose a classical-quantum data frame structure and explore methods of frame generation and pro

Masayuki Sugeta, Takeshi Mizushima, Satoshi Fujimoto

We propose the $2\pi$-periodic Aharonov-Bohm (AB) effect as a nonlocal probe of Majorana zero modes (MZMs) without the restriction of fermion parity. We demonstrate the enhancement of the AB effect, where the topological protection of MZMs yields amplified and robust Andreev reflection mediated by MZMs at multiple superconductor-normal metal junctions. We in

Y. X. Wang, J. S. Zhang, Y. T. Yan, J. J. Qiu

We carried out a cyanopolyyne line survey towards a large sample of HMSFRs using the Shanghai Tian Ma 65m Radio Telescope (TMRT). Our sample consisted of 123 targets taken from the TMRT C band line survey. It included three kinds of sources, namely those with detection of the 6.7 GHz CH3OH maser alone, with detection of the radio recombination line (RRL) alo

Mohamad Fathi, Stefan Hickel, Dirk Roekaerts

Accurate simulations of high-pressure transcritical fuel sprays are essential for the design and optimization of next-generation gas turbines, internal combustion engines, and liquid propellant rocket engines. Most important and challenging is the accurate modelling of complex real-gas effects in high-pressure environments, especially the hybrid subcritical-

Robert Cardona, Cédric Oms

Let $f$ be a Morse function on a closed surface $\Sigma$ such that zero is a regular value and such that $f$ admits neither positive minima nor negative maxima. In this expository note, we show that $\Sigma\times \mathbb{R}$ admits an $\mathbb{R}$-invariant contact form $\alpha=fdt+\beta$ whose characteristic foliation along the zero section is (negative) we

Lei Zhang, Yu Pan, Yi Liu, Qibin Zheng

In general, multiple domain cyberspace security assessments can be implemented by reasoning user's permissions. However, while existing methods include some information from the physical and social domains, they do not provide a comprehensive representation of cyberspace. Existing reasoning methods are also based on expert-given rules, resulting in inefficie

A. M. Shikin, T. P. Makarova, A. V. Eryzhenkov, D. Yu. Usachov

The experimentally measured angle-resolved photoemission dispersion maps for MnBi$_{2}$Te$_{4}$ samples, which show different energy gaps at the Dirac point (DP), are compared with the results of theoretical calculations to find the conditions for the best agreement between theory and experiment. We have analyzed different factors which influence the Dirac g

Walter Didimo, Michael Kaufmann, Giuseppe Liotta, Giacomo Ortali

A planar orthogonal drawing of a planar 4-graph G (i.e., a planar graph with vertex-degree at most four) is a crossing-free drawing that maps each vertex of G to a distinct point of the plane and each edge of $G$ to a sequence of horizontal and vertical segments between its end-points. A longstanding open question in Graph Drawing, dating back over 30 years,

Xinyuan Zhu, Yang Zhang, Fuli Feng, Xun Yang

Recommender systems suffer from confounding biases when there exist confounders affecting both item features and user feedback (e.g., like or not). Existing causal recommendation methods typically assume confounders are fully observed and measured, forgoing the possible existence of hidden confounders in real applications. For instance, product quality is a

Zdeněk Dvořák, Bojan Mohar

For an abelian group $\Gamma$, a graph $G$ is said to be $\Gamma$-flow-critical if $G$ does not admit a nowhere-zero $\Gamma$-flow, but for each edge $e\in E(G)$, the contraction $G/e$ has a nowhere-zero $\Gamma$-flow. A bound on the density of $Z_3$-flow-critical graphs drawn on a fixed surface is obtained, generalizing the planar case of the bound on the d

M. Massardi, M. Bonato, M. Lopez-Caniego, V. Galluzzi

The \textit{Herschel} Astrophysical Terahertz Large Area Survey (H-ATLAS), that has covered about 642 sq. deg. in 5 bands from 100 to 500 $\mu\rm m$, allows a blind flux-limited selection of blazars at sub-mm wavelengths. However, blazars constitute a tiny fraction of H-ATLAS sources and therefore identifying them is not a trivial task. Using the data on kno

Rafael Kiesel, Pietro Totis, Angelika Kimmig

Quantitative extensions of logic programming often require the solution of so called second level inference tasks, i.e., problems that involve a third operation, such as maximization or normalization, on top of addition and multiplication, and thus go beyond the well-known weighted or algebraic model counting setting of probabilistic logic programming under

Terry Lyons, Andrew D. McLeod

In this paper we develop the Greedy Recombination Interpolation Method (GRIM) for finding sparse approximations of functions initially given as linear combinations of some (large) number of simpler functions. In a similar spirit to the CoSaMP algorithm, GRIM combines dynamic growth-based interpolation techniques and thinning-based reduction techniques. The d

Weifeng Zhu, Meixia Tao, Yunfeng Guan

This letter considers temporal-correlated massive access, where each device, once activated, is likely to transmit continuously over several consecutive frames. Motivated by that the device activity at each frame is correlated to not only its previous frame but also its next frame, we propose a double-sided information (DSI) aided joint activity detection an

Shibo Feng, Chunyan Miao, Ke Xu, Jiaxiang Wu

The probability prediction of multivariate time series is a notoriously challenging but practical task. On the one hand, the challenge is how to effectively capture the cross-series correlations between interacting time series, to achieve accurate distribution modeling. On the other hand, we should consider how to capture the contextual information within ti

Michele Graffeo

Let $\rho:\mathbb{Z}/k \mathbb{Z}\rightarrow \text{SL}(2,\mathbb{C})$ be a representation of a finite abelian group and let $\Theta^{\text{gen}}\subset \text{Hom}_\mathbb{Z}(R(\mathbb{Z}/k\mathbb{Z}),\mathbb{Q})$ be the space of generic stability conditions on the set of $G$-constellations. We provide a combinatorial description of all the chambers $C\subset

Roberto Cartas-Fuentevilla, Manuel de la Cruz, Alfredo Herrera-Aguilar, Jhony A. Herrera-Mendoza

By starting from a Perelman entropy functional and considering the Ricci-DeTurck flow equations we analyze the behaviour of Einstein-Hilbert and Einstein-Proca theories with Lifshitz geometry as functions of a flow parameter. In the former case, we found one consistent fixed point that represents flat space-time as the flow parameter tends to infinity. Massi

Maarten Solleveld

Graded Hecke algebras can be constructed geometrically, with constructible sheaves and equivariant cohomology. The input consists of a complex reductive group G (possibly disconnected) and a cuspidal local system on a nilpotent orbit for a Levi subgroup of G. We prove that every such "geometric" graded Hecke algebra is naturally isomorphic to the endomorphis

Y. B. Shi, K. L. Zhang, Z. Song

Non-equilibrium state can exhibit the same macroscopic properties, such as conductivity or superconductivity, as a static state when they share the identical average of an observable over a period of time. We investigate the quench dynamics of a Kitaev chain by introducing two kinds of order parameters which relate to two channels of pairing, local pair in r

Anand Jerry George, Clément L. Canonne

We consider the problem of robustly testing the norm of a high-dimensional sparse signal vector under two different observation models. In the first model, we are given $n$ i.i.d. samples from the distribution $\mathcal{N}\left(\theta,I_d\right)$ (with unknown $\theta$), of which a small fraction has been arbitrarily corrupted. Under the promise that $\|\the

Juan P. Garrahan, Chokri Manai, Simone Warzel

We study the fluctuations of time-additive random observables in the stochastic dynamics of a system of $N$ non-interacting Ising spins. We mainly consider the case of all-to-all dynamics where transitions are possible between any two spin configurations with uniform rates. We show that the cumulant generating function of the time-integral of a normally dist

Ratul Das Chaudhury, C. Matthew Leister, Birendra Rai

When can an interest group exploit polarization between political parties to its advantage? Building upon Battaglini and Patacchini (2018), we study a model where an interest group credibly promises payments to legislators conditional on voting for its preferred policy. A legislator can be directly susceptible to other legislators and value voting like them.

Christian Drago, John Sipe

We present a theoretical analysis of two-photon absorption of classical and squeezed light valid when one-photon absorption to an intermediate state is either resonant or far-detuned from resonance, and in both the low and high intensity regimes. In this paper we concentrate on continuous-wave excitation, although the approach we develop is more general. We

Roberta Filippucci, Yuhua Sun, Yadong Zheng

In this article we study local and global properties of positive solutions of $-\Delta_mu=|u|^{p-1}u+M|\nabla u|^q$ in a domain $\Omega$ of $\mathbb R^N$, with $m>1$, $p,q>0$ and $M\in\mathbb R$. Following some ideas used in \cite{BV,Vron1}, and by using a direct Bernstein method combined with Keller-Osserman's estimate, we obtain several a priori estimates

Marvin Gerlach

Modern advances in particle physics depend strongly on the usage of reliable computer programs. In this context two issues become important: The usage of powerful algorithms to handle the amount of evaluated data properly, and a software architecture capable to overcome the problems of maintainability and extendability. We present our approach to such a comp

Pengcheng Yan, Qizhi Teng, Xiaohai He, Zhenchuan Ma

Digital modeling of the microstructure is important for studying the physical and transport properties of porous media. Multiscale modeling for porous media can accurately characterize macro-pores and micro-pores in a large-FoV (field of view) high-resolution three-dimensional pore structure model. This paper proposes a multiscale reconstruction algorithm ba

Mazen Alamir

In this paper, a methodology is proposed that enables to analyze the sensitivity of the outcome of a therapy to unavoidable high dispersion of the patient specific parameters on one hand and to the choice of the parameters that define the drug delivery feedback strategy on the other hand. More precisely, a method is given that enables to extract and rank the

Unnikrishnan R Nair, Sarthak Sharma, Udit Singh Parihar, Midhun S Menon

We present the first prize solution to NeurIPS 2021 - AWS Deepracer Challenge. In this competition, the task was to train a reinforcement learning agent (i.e. an autonomous car), that learns to drive by interacting with its environment, a simulated track, by taking an action in a given state to maximize the expected reward. This model was then tested on a re

Chen-Kai Lin, Bow-Yaw Wang

FreeRTOS is a real-time operating system with configurable scheduling policies. Its portability and configurability make FreeRTOS one of the most popular real-time operating systems for embedded devices. We formally analyze the FreeRTOS scheduler on ARM Cortex-M4 processor in this work. Specifically, we build a formal model for the FreeRTOS ARM Cortex-M4 por

Ekta U. Samani, Ashis G. Banerjee

Recognition of occluded objects in unseen indoor environments is a challenging problem for mobile robots. This work proposes a new slicing-based topological descriptor that captures the 3D shape of object point clouds to address this challenge. It yields similarities between the descriptors of the occluded and the corresponding unoccluded objects, enabling o

Sebastien Andreina, Lorenzo Alluminio, Giorgia Azzurra Marson, Ghassan Karame

The wide success of Bitcoin has led to a huge surge of alternative cryptocurrencies (altcoins). Most altcoins essentially fork Bitcoin's code with minor modifications, such as the number of coins to be minted, the block size, and the block generation time. As such, they are often deemed identical to Bitcoin in terms of security, robustness, and maturity. In

Ruan van der Merwe, Gregory Newman, Etienne Barnard

Pretraining methods are typically compared by evaluating the accuracy of linear classifiers, transfer learning performance, or visually inspecting the representation manifold's (RM) lower-dimensional projections. We show that the differences between methods can be understood more clearly by investigating the RM directly, which allows for a more detailed comp

Ján Koloda, Jürgen Seiler, André Kaup, Victoria Sánchez

The purpose of signal extrapolation is to estimate unknown signal parts from known samples. This task is especially important for error concealment in image and video communication. For obtaining a high quality reconstruction, assumptions have to be made about the underlying signal in order to solve this underdetermined problem. Among existent reconstruction

Zuheng Xu, Naitong Chen, Trevor Campbell

This work presents mixed variational flows (MixFlows), a new variational family that consists of a mixture of repeated applications of a map to an initial reference distribution. First, we provide efficient algorithms for i.i.d. sampling, density evaluation, and unbiased ELBO estimation. We then show that MixFlows have MCMC-like convergence guarantees when t

Josef Pradler

Recently it has been suggested that thermal bremsstrahlung emission, when it decouples prior to recombination, creates an excess over the Planck cosmic microwave background spectrum at sub-GHz frequencies. Remarkable by itself, this would also explain a long-standing unexplained deficit in the predictions of the extragalactic radio background. In this brief

Ziming Wang, Shuang Lian, Yuhao Zhang, Xiaoxin Cui

Spiking neural networks (SNNs) operating with asynchronous discrete events show higher energy efficiency with sparse computation. A popular approach for implementing deep SNNs is ANN-SNN conversion combining both efficient training of ANNs and efficient inference of SNNs. However, the accuracy loss is usually non-negligible, especially under a few time steps

Zhuoran Geng, Ilari J. Maasilta

It is not widely appreciated that an acoustic wave can "jump" or "tunnel" across a vacuum gap between two piezoelectric solids, nor has the general case been formulated or studied in detail. Here, we remedy that situation, by presenting a general formalism and approach to study such an acoustic tunneling effect between two arbitrarily oriented anisotropic pi

Hong Wang, Yuexiang Li, Deyu Meng, Yefeng Zheng

Inspired by the great success of deep neural networks, learning-based methods have gained promising performances for metal artifact reduction (MAR) in computed tomography (CT) images. However, most of the existing approaches put less emphasis on modelling and embedding the intrinsic prior knowledge underlying this specific MAR task into their network designs

Ivan P. Costa e Silva, Jose Luis Flores, Jonatan Herrera

We identify certain general geometric conditions on a foliation of a spacetime (M,g) by timelike curves that will impede the existence of null geodesic lines, especially if (M,g) possesses a compact Cauchy hypersurface. The absence of such lines, in turn, yields well-known restrictions on the geometry of cosmological spacetimes, in the context of Bartnik's s

B. F. Farrell, P. J. Ioannou, M. -A. Nikolaidis

In wall-bounded shear flow the primary coherent structure is the streamwise roll and streak (R-S). Absent of an associated instability the R-S has been ascribed to non-normality mediated interaction between the mean flow and perturbations. This interaction may occur either directly due to excitation of a transiently growing perturbation or indirectly due to

Karol Gietka

In quantum metrology, one typically creates correlations among atoms or photons to enhance measurement precision. Here, we show how one can use other excitations to perform quantum-enhanced measurements on the example of center-of-mass excitations of a spin-orbit coupled Bose-Einstein condensate and a Coulomb crystal. We also present a method to simulate a h

Anselmo Ferreira, Changcheng Chen, Mauro Barni

Nowadays, 2D barcodes have been widely used for advertisement, mobile payment, and product authentication. However, in applications related to product authentication, an authentic 2D barcode can be illegally copied and attached to a counterfeited product in such a way to bypass the authentication scheme. In this paper, we employ a proprietary 2D barcode patt

Lingwei Zhu, Zheng Chen, Eiji Uchibe, Takamitsu Matsubara

The recently successful Munchausen Reinforcement Learning (M-RL) features implicit Kullback-Leibler (KL) regularization by augmenting the reward function with logarithm of the current stochastic policy. Though significant improvement has been shown with the Boltzmann softmax policy, when the Tsallis sparsemax policy is considered, the augmentation leads to a

Haozhe Liu, Haoqin Ji, Yuexiang Li, Nanjun He

Deep convolutional neural network (CNN) based models are vulnerable to the adversarial attacks. One of the possible reasons is that the embedding space of CNN based model is sparse, resulting in a large space for the generation of adversarial samples. In this study, we propose a method, denoted as Dynamic Feature Aggregation, to compress the embedding space

Emilian M. Nica, Sheng Ran, Lin Jiao, Qimiao Si

Symmetry breaking beyond a global U(1) phase is the key signature of unconventional superconductors. As prototypical strongly correlated materials, heavy-fermion metals provide ideal platforms for realizing unconventional superconductivity. In this article, we review heavy-fermion superconductivity, with a focus on those materials with multiple superconducti

Subhankar Bera, Shashank Gupta, A. S. Majumdar

We Haar uniformly generate random states of various ranks and study their performance in an entanglement-based quantum key distribution (QKD) task. In particular, we analyze the efficacy of random two-qubit states in realizing device-independent (DI) QKD. We first find the normalized distribution of entanglement and Bell-nonlocality which are the key resourc

Tianxiang Gao, Hongyang Gao

Implicit deep learning has recently become popular in the machine learning community since these implicit models can achieve competitive performance with state-of-the-art deep networks while using significantly less memory and computational resources. However, our theoretical understanding of when and how first-order methods such as gradient descent (GD) con

Daniel Alpay, Palle Jorgensen

We consider, and make precise, a certain extension of the Radon-Nikodym derivative operator, to functions which are additive, but not necessarily sigma-additive, on a subset of a given sigma-algebra. We give applications to probability theory; in particular, to the study of $\mu$-Brownian motion, to stochastic calculus via generalized It\^o-integrals, and th

Sen Yang

Using Bloch-Ogus theorem and Chern character from K-theory to cyclic homology, we answer a question of Green and Griffiths on extending Bloch formula. Moreover, we construct a map from local Hilbert functor to local cohomology. With suitable assumptions, we use this map to answer a question of Bloch on constructing a natural transformation from local Hilbert

Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao

Adversarial purification refers to a class of defense methods that remove adversarial perturbations using a generative model. These methods do not make assumptions on the form of attack and the classification model, and thus can defend pre-existing classifiers against unseen threats. However, their performance currently falls behind adversarial training meth

Fei Huang, Hao Zhou, Yang Liu, Hang Li

Non-autoregressive Transformers (NATs) significantly reduce the decoding latency by generating all tokens in parallel. However, such independent predictions prevent NATs from capturing the dependencies between the tokens for generating multiple possible translations. In this paper, we propose Directed Acyclic Transfomer (DA-Transformer), which represents the

Bo-Yong Chen

In this note, we prove an $L^2$ Hartogs-type extension theorem for unbounded domains.

Samira Sahar Jamil, P Christopher Staecker, Danish Ali

Discrete cubical homology arose as the homology theory associated with discrete cubical homotopy theory. Despite the combinatorial nature of this homology, its computation has posed a significant challenge to the researchers in the field. This paper focuses on determining the discrete cubical homology of $c_1$-digital images, which are subgraphs of the integ

Saumya Chaturvedi, Zilong Liu, Vivek Ashok Bohara, Anand Srivastava

Sparse Code Multiple Access (SCMA) is a disruptive code-domain non-orthogonal multiple access (NOMA) scheme to enable \color{black}future massive machine-type communication networks. As an evolved variant of code division multiple access (CDMA), multiple users in SCMA are separated by assigning distinctive sparse codebooks (CBs). Efficient multiuser detectio

David Callan

We give a simple proof that the the number of Dyck paths of semilength $n$ with $i$ returns to ground level and $j$ peaks is the generalized Narayana number $\frac{i}{n} \binom{n}{j} \binom{n - i - 1}{j - i}$.

Li Zhang

This tutorial provides a comprehensive and in-depth view of the research on procedures, primarily in Natural Language Processing. A procedure is a sequence of steps intended to achieve some goal. Understanding procedures in natural language has a long history, with recent breakthroughs made possible by advances in technology. First, we discuss established ap

Masumi Shimojo, Kazumasa Iwai

Monitoring observations of solar microwave fluxes and their polarization began in Japan during the 1950s at Toyokawa and Mitaka. At present (April 2022), monitoring observations continue with the Nobeyama Radio Polarimeters (NoRP) at the Nobeyama campus of the National Astronomical Observatory of Japan (NAOJ). In this paper, we present a brief history of the

Atharv Sardesai, Hatim Piplodwala, Sidhant Hargunani, Swarnim Sonawane

The Payment Switch is an integral component of all modern payment and banking systems in India. The NPCI currently provides a simulator to test payment switches. However, this system has a few disadvantages viz. it lacks an API, it requires manual generation of each test case and during high server loads, the testing process may take a long time. Currently t

Mike Wu, Will McTighe

The paper introduces a new type of constant function market maker, the constant power root market marker. We show that the constant sum (used by mStable), constant product (used by Uniswap and Balancer), constant reserve (HOLD-ing), and constant harmonic mean trading functions are special cases of the constant power root trading function. We derive the value

Suik Cheon, Gil Young Cho, Ki-Seok Kim, Hyun-Woo Lee

The chiral anomaly may be realized in condensed matter systems with pairs of Weyl points. Here we show that the chiral anomaly can be realized in diverse noncentrosymmetric systems even without Weyl point pairs when spin-orbit coupling induces nonzero Berry curvature flux through Fermi surfaces. This motivates the condensed matter chiral anomaly to be interp

Takeharu Matsuda, Kohsuke Tsukui, Satoshi Ii

Meshless methods inherently do not require mesh topologies and are practically used for solving continuum equations. However, these methods generally tend to have a higher computational load than conventional mesh-based methods because calculation stencils for spatial discretization become large. In this study, a novel approach for the use of compact stencil

Siqi Zheng, Hongbin Suo, Qian Chen

Speaker embedding has been a fundamental feature for speaker-related tasks such as verification, clustering, and diarization. Traditionally, speaker embeddings are represented as fixed vectors in high-dimensional space. This could lead to biased estimations, especially when handling shorter utterances. In this paper we propose to represent a speaker utteranc

Zipeng Wu, Shi-Yao Hou, Chao Zhang, Lvzhou Li

Quantum query complexity plays an important role in studying quantum algorithms, which captures the most known quantum algorithms, such as search and period finding. A query algorithm applies $U_tO_x\cdots U_1O_xU_0$ to some input state, where $O_x$ is the oracle dependent on some input variable $x$, and $U_i$s are unitary operations that are independent of

Mohamed A. Abd-Elmagid, Harpreet S. Dhillon

We study a general setting of status updating systems in which a set of source nodes provide status updates about some physical process(es) to a set of monitors. The freshness of information available at each monitor is quantified in terms of the Age of Information (AoI), and the vector of AoI processes at the monitors (or equivalently the age vector) models

Arnab Char, T. Karthick

For a graph $G$, let $\chi(G)$ ($\omega(G)$) denote its chromatic (clique) number. A $P_2+P_3$ is the graph obtained by taking the disjoint union of a two-vertex path $P_2$ and a three-vertex path $P_3$. A $\bar{P_2+P_3}$ is the complement graph of a $P_2+P_3$. In this paper, we study the class of ($P_2+P_3$, $\bar{P_2+P_3}$)-free graphs and show that every

Yen-Ting Lin, Hui-Chi Kuo, Ze-Song Xu, Ssu Chiu

This paper introduces Miutsu, National Taiwan University's Alexa Prize TaskBot, which is designed to assist users in completing tasks requiring multiple steps and decisions in two different domains -- home improvement and cooking. We overview our system design and architectural goals, and detail the proposed core elements, including question answering, task

Youfa Li, Hongfei Wang, Deguang Han

Analytic signals constitute a class of signals that are widely applied in time-frequency analysis such as extracting instantaneous frequency (IF) or phase derivative in the characterization of ultrashort laser pulse. The purpose of this paper is to investigate the phase retrieval (PR) problem for analytic signals in $\mathbb{C}^{N}$ by short-time Fourier tra

Thai Van Nguyen, Xincheng Dai, Ibrahim Khan, Ruck Thawonmas

This paper presents a deep reinforcement learning agent (AI) that uses sound as the input on the DareFightingICE platform at the DareFightingICE Competition in IEEE CoG 2022. In this work, an AI that only uses sound as the input is called blind AI. While state-of-the-art AIs rely mostly on visual or structured observations provided by their environments, lea

Lingwei Zhu, Zheng Chen, Eiji Uchibe, Takamitsu Matsubara

Maximum Tsallis entropy (MTE) framework in reinforcement learning has gained popularity recently by virtue of its flexible modeling choices including the widely used Shannon entropy and sparse entropy. However, non-Shannon entropies suffer from approximation error and subsequent underperformance either due to its sensitivity or the lack of closed-form policy

Shakil M. Khan

Inspired by a novel action-theoretic formalization of actual cause, Khan and Lesp\'erance (2021) recently proposed a first account of causal knowledge that supports epistemic effects, models causal knowledge dynamics, and allows sensing actions to be causes of observed effects. To date, no other study has looked specifically at these issues. But their formal

Ionut Chifan, Daniel Drimbe, Adrian Ioana

We prove that every separable tracial von Neumann algebra embeds into a II$_1$ factor with property (T) which can be taken to have trivial outer automorphism and fundamental groups. We also establish an analogous result for the trivial extension over a non-atomic probability space of every countable p.m.p. equivalence relation. These results are obtained by

Hengwei Zhang, Hua Yang, Haitao Wang, Zhigang Wang

The booming of electric vehicles demands efficient battery disassembly for recycling to be environment-friendly. Due to the unstructured environment and high uncertainties, battery disassembly is still primarily done by humans, probably assisted by robots. It is highly desirable to design autonomous solutions to improve work efficiency and lower human risks

Jeongrak Son, Peter Talkner, Juzar Thingna

The charging of a quantum battery by a four-stroke quantum machine that works either as an engine or a refrigerator is investigated. The presented analysis provides the energetic behavior of the combined system in terms of the heat and workflows of the machine, the average, and variance of the battery's energy as well as the coherent and incoherent parts of