July 2022 arXiv papers — page 36

Oleksandr V. Vitiuk, Valery M. Pugatch, Kyrill A. Bugaev, Nazar S. Yakovenko

Here, we propose a novel approach to experimentally and theoretically study the properties of QCD matter under new extreme conditions, namely having an initial temperature over 300~MeV and baryonic charge density over three times the values of the normal nuclear density. According to contemporary theoretical knowledge, such conditions were not accessible dur

Yu-Ting Liu

I present a conjecture that all two-loop MHV amplitudes in planar $\mathcal{N} = 4$ super-Yang-Mills theory possess an antipodal symmetry when evaluated on parity-even kinematics. The symmetry acts as a change of basis on the symbol letters, followed by the antipode operation associated with the Hopf algebra structure of multiple polylogarithms. At the symbo

Md Mohaiminul Islam, Gedas Bertasius

This report describes our submission called "TarHeels" for the Ego4D: Object State Change Classification Challenge. We use a transformer-based video recognition model and leverage the Divided Space-Time Attention mechanism for classifying object state change in egocentric videos. Our submission achieves the second-best performance in the challenge. Furthermo

Dušan Joksimović, Sobhan Seyfaddini

We prove a H\"older-type inequality for Hamiltonian diffeomorphisms relating the $C^0$ norm, the $C^0$ norm of the derivative, and the Hofer/spectral norm. We obtain as a consequence that sufficiently fast convergence in Hofer/spectral metric forces $C^0$ convergence. The second theme of our paper is the study of pseudo-rotations that arise from the Anosov-K

Xingbo Fu, Binchi Zhang, Yushun Dong, Chen Chen

Graph machine learning has gained great attention in both academia and industry recently. Most of the graph machine learning models, such as Graph Neural Networks (GNNs), are trained over massive graph data. However, in many real-world scenarios, such as hospitalization prediction in healthcare systems, the graph data is usually stored at multiple data owner

Vašek Chvátal, Ida Kantor

In a metric space $M=(X,d)$, we say that $v$ is between $u$ and $w$ if $d(u,w)=d(u,v)+d(v,w)$. Taking all triples $\{u,v,w\}$ such that $v$ is between $u$ and $w$, one can associate a 3-uniform hypergraph with each finite metric space $M$. An effort to solve some basic open questions regarding finite metric spaces has motivated an endeavor to better understa

Yu-Yun Tseng, Alexander Bell, Danna Gurari

We introduce a few-shot localization dataset originating from photographers who authentically were trying to learn about the visual content in the images they took. It includes nearly 10,000 segmentations of 100 categories in over 4,500 images that were taken by people with visual impairments. Compared to existing few-shot object detection and instance segme

Izabella Laba, Itay Londner

We consider finite sets $A\subset\mathbb{Z}$ tiles the integers by translations. By periodicity, any such tiling is equivalent to a factorization $A\oplus B=\mathbb{Z}_M$ of a finite cyclic group. Building on por previous work, we prove that a tentative characterization of finite tiles proposed by Coven and Meyerowitz holds for all integer tilings of period

Hossein Mirzaee, Javad Peymanfard, Hamid Habibzadeh Moshtaghin, Hossein Zeinali

With the recent proliferation of open textual data on social media platforms, Emotion Detection (ED) from Text has received more attention over the past years. It has many applications, especially for businesses and online service providers, where emotion detection techniques can help them make informed commercial decisions by analyzing customers/users' feel

Daan Huybrechs, Lloyd N. Trefethen

We propose AAA rational approximation as a method for interpolating or approximating smooth functions from equispaced data samples. Although it is always better to approximate from large numbers of samples if they are available, whether equispaced or not, this method often performs impressively even when the sampling grid is fairly coarse. In most cases it g

Xiaojian Li, Jay Reiter, Shiang Tang, Napoleon Wang

We define and study a $p$-adic analogue of the incomplete gamma function related to Morita's $p$-adic gamma function. We also discuss a combinatorial identity related to the Artin-Hasse series, which is a special case of the exponential principle in combinatorics. From this we deduce a curious $p$-adic property of $|\mathrm{Hom} (G,S_n)|$ for a topologically

Zhi Li, Lu He, Huijuan Xu

Action understanding has evolved into the era of fine granularity, as most human behaviors in real life have only minor differences. To detect these fine-grained actions accurately in a label-efficient way, we tackle the problem of weakly-supervised fine-grained temporal action detection in videos for the first time. Without the careful design to capture sub

Jack Lashner, Joseph Seibert, Max Silva-Feaver, Tanay Bhandarkar

The Simons Observatory (SO) is a ground based Cosmic Microwave Background experiment that will be deployed to the Atacama Desert in Chile. SO will field over 60,000 transition edge sensor (TES) bolometers that will observe in six spectral bands between 27 GHz and 280 GHz with the goal of revealing new information about the origin and evolution of the univers

Fabrizio De Caro, Adam J. Collin, Alfredo Vaccaro

This paper explores the effectiveness of data-driven models to predict voltage excursion events in power systems using simple categorical labels. By treating the prediction as a categorical classification task, the workflow is characterized by a low computational and data burden. A proof-of-concept case study on a real portion of the Italian 150 kV sub-trans

Jhonatan Tavori, Hanoch Levy

In this study we analyze the evolution of the effective reproduction number, $R$, through a SIR spreading process in heterogeneous networks; Characterizing its decay process allows to analytically study the effects of countermeasures on the progress of the virus under heterogeneity, and to optimize their policies. A striking result of recent studies has show

Chenxu Liu, Karl Gebhardt, Erin Mentuch Cooper, Yechi Zhang

We present the LyA emission line luminosity function (LF) of the Active Galactic Nuclei (AGN) in the first release of the Hobby-Eberly Telescope Dark Energy Experiment Survey (HETDEX) AGN catalog (Liu et al. 2022, Paper I). The AGN are selected either by emission-line pairs characteristic of AGN or by single broad emission line, free of any photometric pre-s

Karen E. Smith, Adela Vraciu

We find a formula, in terms of n, d and p, for the value of the F-pure threshold for the generic homogeneous polynomial of degree d in n variables over an algebraically closed field of characteristic p. We also show that, in every characteristic p and for all d (greater than 3) not divisible by p, there always exist reduced polynomials of degree d whose F-pu

Konrad Waldorf

The classical Buscher rules describe T-duality for metrics and B-fields in a topologically trivial setting. On the other hand, topological T-duality addresses aspects of non-trivial topology while neglecting metrics and B-fields. In this article we develop a new unifying framework for both aspects.

Xuecheng Ye, Thomas Vojta

We study the absorbing-state phase transition in the one-dimensional contact process under the combined influence of spatial and temporal random disorders. We focus on situations in which the spatial and temporal disorders decouple. Couched in the language of epidemic spreading, this means that some spatial regions are, at all times, more favorable than othe

Ahmet Zahid Balcıoğlu, Oğuz Gürerk

There are a number of mathematical formalisms of the term "outlier" in statistics, though there is no consensus on what the right notion ought to be. Accordingly, we try to give a consistent and robust definition for a specific type of outliers defined via order statistics. Our approach is based on ratios of partial sums of order statistics to investigate th

Zhong-Cheng Xiang, Kaixuan Huang, Yu-Ran Zhang, Tao Liu

The quantum Hall effect, fundamental in modern condensed matter physics, continuously inspires new theories and predicts emergent phases of matter. Here we experimentally demonstrate three types of Chern insulators with synthetic dimensions on a programable 30-qubit-ladder superconducting processor. We directly measure the band structures of the 2D Chern ins

Ji-Chong Yang, Xiao-Ting Chang, Jian-Xing Chen

The effect of an external electric field on the quark matter is an important question due to the presence of strong electric fields in heavy ion collisions. In the lattice QCD approach, the case of a real electric field suffers from the `sign problem', and a classical electric field is often used similar as the case of chemical potential. Interestingly, in a

Zezhou Cheng, Menglei Chai, Jian Ren, Hsin-Ying Lee

Creating and editing the shape and color of 3D objects require tremendous human effort and expertise. Compared to direct manipulation in 3D interfaces, 2D interactions such as sketches and scribbles are usually much more natural and intuitive for the users. In this paper, we propose a generic multi-modal generative model that couples the 2D modalities and im

T. T. Saraiva, L. I. Baturina, A. A. Shanenko

Recently it has been demonstrated that the pair-exchange coupling of quasi-one-dimensional (Q1D) bands with conventional higher-dimensional bands in one multiband superconducting material can result in the formation of robust aggregate pair condensate. In particular, it has been found that the Q1D thermal pair fluctuations are suppressed in the presence of d

Naomi A. Arnold, Raul J. Mondragon, Richard G. Clegg

Often, due to prohibitively large size or to limits to data collecting APIs, it is not possible to work with a complete network dataset and sampling is required. A type of sampling which is consistent with Twitter API restrictions is uniform edge sampling. In this paper, we propose a methodology for the recovery of two fundamental network properties from an

B. Shiralilou, G. Raaijmakers, B. Duboeuf, S. Nissanke

Detection of gravitational waves (GWs) from neutron star-black hole (NSBH) standard sirens can provide local measurements of the Hubble constant ($H_0$), regardless of the detection of an electromagnetic (EM) counterpart: The presence of matter terms in GWs breaks the degeneracy between mass parameters and redshift, allowing simultaneous measurement of both

Lorenzo Catani, Matthew Leifer, David Schmid, Robert W. Spekkens

Our article [arXiv:2111.13727(2021)] argues that the phenomenology of interference that is traditionally regarded as problematic does not, in fact, capture the essence of quantum theory -- contrary to the claims of Feynman and many others. It does so by demonstrating the existence of a physical theory, which we term the "toy field theory", that reproduces th

Bo Sun, Vladimir G. Kim, Noam Aigerman, Qixing Huang

This paper introduces a data-driven shape completion approach that focuses on completing geometric details of missing regions of 3D shapes. We observe that existing generative methods lack the training data and representation capacity to synthesize plausible, fine-grained details with complex geometry and topology. Our key insight is to copy and deform patch

Gaoang Wang, Yibing Zhan, Xinchao Wang, Mingli Song

Anomaly detection aims at identifying deviant samples from the normal data distribution. Contrastive learning has provided a successful way to sample representation that enables effective discrimination on anomalies. However, when contaminated with unlabeled abnormal samples in training set under semi-supervised settings, current contrastive-based methods ge

Borzoo Rassouli, Morteza Varasteh, Deniz Gunduz

Vertical federated learning is considered, where an active party, having access to true class labels, wishes to build a classification model by utilizing more features from a passive party, which has no access to the labels, to improve the model accuracy. In the prediction phase, with logistic regression as the classification model, several inference attack

Rigoberto Zelada

We utilize Gaussian measure preserving systems to prove the existence and genericity of Lebesgue measure preserving transformations $T:[0,1]\rightarrow [0,1]$ which exhibit both mixing and rigidity behavior along families of asymptotically linearly independent sequences. Let $\lambda_1,...,\lambda_N\in[0,1]$ and let $\phi_1,...,\phi_N:\mathbb N\rightarrow\ma

Paula Harder, Duncan Watson-Parris, Philip Stier, Dominik Strassel

Aerosol particles play an important role in the climate system by absorbing and scattering radiation and influencing cloud properties. They are also one of the biggest sources of uncertainty for climate modeling. Many climate models do not include aerosols in sufficient detail due to computational constraints. In order to represent key processes, aerosol mic

Dan Luo, Lixin Zou, Qingyao Ai, Zhiyu Chen

Unbiased Learning to Rank (ULTR) that learns to rank documents with biased user feedback data is a well-known challenge in information retrieval. Existing methods in unbiased learning to rank typically rely on click modeling or inverse propensity weighting (IPW). Unfortunately, the search engines are faced with severe long-tail query distribution, where neit

Vikram Nitin, Shubhi Asthana, Baishakhi Ray, Rahul Krishna

Microservices Architecture (MSA) has become a de-facto standard for designing cloud-native enterprise applications due to its efficient infrastructure setup, service availability, elastic scalability, dependability, and better security. Existing (monolithic) systems must be decomposed into microservices to harness these characteristics. Since manual decompos

Ashishi Puri, Sanjeev Kumar

This article introduces a new methodology for reconstructing the white matter fiber pathways of brain in diffusion MRI. Usually, the signal intensity values will be lesser in the direction of higher diffusivity. The proposed approach picks the diffusion sensitivity gradient directions (dSGD), where the signal intensities are diminutive. Considering these as

Büşra Marşan, Salih Furkan Akkurt, Muhammet Şen, Merve Gürbüz

In this study, we aim to offer linguistically motivated solutions to resolve the issues of the lack of representation of null morphemes, highly productive derivational processes, and syncretic morphemes of Turkish in the BOUN Treebank without diverging from the Universal Dependencies framework. In order to tackle these issues, new annotation conventions were

Ulysse Chabaud, Mattia Walschaers

Quantum computers promise to dramatically outperform their classical counterparts. However, the non-classical resources enabling such computational advantages are challenging to pinpoint, as it is not a single resource but the subtle interplay of many that can be held responsible for these potential advantages. In this work, we show that every bosonic quantu

Ulf Lindström

It is shown how extended supersymmetry realised directly on the (2,2) semichiral superfields of a symplectic sigma model gives rise to a geometry on the doubled tangent bundle consisting of two Yano F structures on an almost para-hermitian manifold. Closure of the algebra and invariance of the action is discussed in this framework and integrability of the F

Lorenzo Catani, Matthew Leifer, Giovanni Scala, David Schmid

Uncertainty relations express limits on the extent to which the outcomes of distinct measurements on a single state can be made jointly predictable. The existence of nontrivial uncertainty relations in quantum theory is generally considered to be a way in which it entails a departure from the classical worldview. However, this perspective is undermined by th

Rocío Cotta Antúnez, Michael W. Levin

Transportation contributes a substantial fraction of all greenhouse gas emissions. One approach for reducing such emissions is to modify vehicles' route choices to minimize their fuel consumption or emission, which is known as eco-routing. Most eco-routing is based on vehicles choosing routes that minimize their individual fuel consumption or emissions. The

Dirk Pauly, Michael Schomburg

We show that the biharmonic Hilbert complex with mixed boundary conditions on bounded strong Lipschitz domains is closed and compact. The crucial results are compact embeddings which follow by abstract arguments using functional analysis together with particular regular decompositions. Higher Sobolev order results are also proved. This paper extends recent r

Edward Gillman, Federico Carollo, Igor Lesanovsky

Central to the field of quantum machine learning is the design of quantum perceptrons and neural network architectures. A key question in this regard is the impact of quantum effects on the way in which such models process information. Here, we approach this question by establishing a connection between $(1+1)D$ quantum cellular automata, which implement a d

Haobing Liu, Yanmin Zhu, Chunyang Wang, Jianyu Ding

Behavior prediction based on historical behavioral data have practical real-world significance. It has been applied in recommendation, predicting academic performance, etc. With the refinement of user data description, the development of new functions, and the fusion of multiple data sources, heterogeneous behavioral data which contain multiple types of beha

Xiaomin Chen

Inspired by the study of $V$-static manifold about classification, in this article, we apply the recent results obtained by Freitas and Gomes (Compact gradient Einstein-type manifolds with boundary, 2022) to prove the rigidity results for compact gradient Einstein-type manifolds with nonempty boundary and constant scalar curvature under some suitable pinchin

Isabel Dias, Ricardo Rei, Patrícia Pereira, Luisa Coheur

In this paper, we propose an end-to-end sentiment-aware conversational agent based on two models: a reply sentiment prediction model, which leverages the context of the dialogue to predict an appropriate sentiment for the agent to express in its reply; and a text generation model, which is conditioned on the predicted sentiment and the context of the dialogu

Charles Schaff, Matthew R. Walter

A robot's ability to complete a task is heavily dependent on its physical design. However, identifying an optimal physical design and its corresponding control policy is inherently challenging. The freedom to choose the number of links, their type, and how they are connected results in a combinatorial design space, and the evaluation of any design in that sp

Yong Cai, Ji Xu, Shuai Zhao, Siyi Zhou

Explorations of the violation of null energy condition (NEC) in cosmology could enrich our understanding of the very early universe and the related gravity theories. Although a fully stable NEC violation can be realized in the ``beyond Horndeski'' theory, it remains an open question whether a violation of the NEC is allowed by some fundamental properties of

Prashanth Venkataraman

With the inexorable digitalisation of the modern world, every subset in the field of technology goes through major advancements constantly. One such subset is digital images which are ever so popular. Images can not always be as visually pleasing or clear as you would want them to be and are often distorted or obscured with noise. A number of techniques to e

Shuai Shen, Wanhua Li, Zheng Zhu, Yueqi Duan

Talking head synthesis is an emerging technology with wide applications in film dubbing, virtual avatars and online education. Recent NeRF-based methods generate more natural talking videos, as they better capture the 3D structural information of faces. However, a specific model needs to be trained for each identity with a large dataset. In this paper, we pr

Ramneet Kaur, Kaustubh Sridhar, Sangdon Park, Susmit Jha

Machine learning models are prone to making incorrect predictions on inputs that are far from the training distribution. This hinders their deployment in safety-critical applications such as autonomous vehicles and healthcare. The detection of a shift from the training distribution of individual datapoints has gained attention. A number of techniques have be

Kaifeng Cui, Jose Valencia, Kevin T. Boyce, David R. Leibrandt

In quantum logic spectroscopy (QLS), one species of trapped ion is used as a sensor to detect the state of an otherwise inaccessible ion species. This extends precision measurements to a broader class of atomic and molecular systems for applications like atomic clocks and tests of fundamental physics. Here, we develop a new technique based on a Schr\"{o}ding

Nicholas Synovic, Matt Hyatt, Rohan Sethi, Sohini Thota

Software metrics capture information about software development processes and products. These metrics support decision-making, e.g., in team management or dependency selection. However, existing metrics tools measure only a snapshot of a software project. Little attention has been given to enabling engineers to reason about metric trends over time -- longitu

Nicolas Couture, Wei Cui, Markus Lippl, Rachel Ostic

Slow motion movies are not only fascinating to watch, they also allow us to see intricate details of the mechanical dynamics of complex phenomena. If the images in each frame are replaced by terahertz (THz) waves, such movies can monitor low-energy resonances and reveal fast structural or chemical transitions. Here, we combine THz spectroscopy as a non-invas

Rohan Bavishi, Harshit Joshi, José Pablo Cambronero Sánchez, Anna Fariha

Most users of low-code platforms, such as Excel and PowerApps, write programs in domain-specific formula languages to carry out nontrivial tasks. Often users can write most of the program they want, but introduce small mistakes that yield broken formulas. These mistakes, which can be both syntactic and semantic, are hard for low-code users to identify and fi

Olivier Bordellès

In this note, we provide an explicit upper bound for $h_K \mathcal{R}_K d_K^{-1/2}$ which depends on an effective constant in the error term of the Ideal Theorem.

Chang Tian, Wenpeng Yin, Marie-Francine Moens

A dialogue policy module is an essential part of task-completion dialogue systems. Recently, increasing interest has focused on reinforcement learning (RL)-based dialogue policy. Its favorable performance and wise action decisions rely on an accurate estimation of action values. The overestimation problem is a widely known issue of RL since its estimate of t

See Hian Lee, Feng Ji, Wee Peng Tay

Heterogeneous graphs have multiple node and edge types and are semantically richer than homogeneous graphs. To learn such complex semantics, many graph neural network approaches for heterogeneous graphs use metapaths to capture multi-hop interactions between nodes. Typically, features from non-target nodes are not incorporated into the learning procedure. Ho

Hamid Al-Saqban, Giovanni Forni

We show that a central limit theorem holds for exterior powers of the Kontsevich-Zorich (KZ) cocycle. In particular, we show that, under the hypothesis that the top Lyapunov exponent on the exterior power is simple, a central limit theorem holds for the lift of the (leafwise) hyperbolic Brownian motion to any strongly irreducible, symplectic, $\text{SL}(2,\m

Lei Zhang, Guanyu Gao, Huaizheng Zhang

Data drift is a thorny challenge when deploying person re-identification (ReID) models into real-world devices, where the data distribution is significantly different from that of the training environment and keeps changing. To tackle this issue, we propose a federated spatial-temporal incremental learning approach, named FedSTIL, which leverages both lifelo

Mayank Pandey, Victor Y. Wang, Max Wenqiang Xu

We prove that the $k$-th positive integer moment of partial sums of Steinhaus random multiplicative functions over the interval $(x, x+H]$ matches the corresponding Gaussian moment, as long as $H\ll x/(\log x)^{2k^2+2+o(1)}$ and $H$ tends to infinity with $x$. We show that properly normalized partial sums of typical multiplicative functions arising from real

Qian Li, Franck Multon, Adnane Boukhayma

We explore a new strategy for few-shot novel view synthesis based on a neural light field representation. Given a target camera pose, an implicit neural network maps each ray to its target pixel's color directly. The network is conditioned on local ray features generated by coarse volumetric rendering from an explicit 3D feature volume. This volume is built

Derya Malak

We employ grant-based access with retransmissions for multiple users with small payloads, particularly at low spectral efficiency (SE). The radio resources are allocated via NOMA in the time into $T$ slots and frequency dimensions, with a measure of non-orthogonality $\eta$. Retransmissions are stored in a receiver buffer with a finite size $C_{\sf buf}$ and

Maria Mannone, Juan Sebastián Arias-Valero

In physics, timbre is a complex phenomenon, like color. Musical timbres are given by the superposition of sinusoidal signals, corresponding to longitudinal acoustic waves. Colors are produced by the superposition of transverse electromagnetic waves in the domain of visible light. Regarding human perception, specific timbre variations provoke effects similar

Tiejun Li, Tiannan Xiao, Guoguo Yang

We revisited the central limit theorem (CLT) for stochastic gradient descent (SGD) type methods, including the vanilla SGD, momentum SGD and Nesterov accelerated SGD methods with constant or vanishing damping parameters. By taking advantage of Lyapunov function technique and $L^p$ bound estimates, we established the CLT under more general conditions on learn

Daniel Eckhoff, Royce Ng, Alvaro Cassinelli

In this paper we introduce novel Virtual Reality (VR) and Augmented Reality (AR) treatments to improve the psychological well being of patients in palliative care, based on interviews with a clinical psychologist who has successfully implemented VR assisted interventions on palliative care patients in the Hong Kong hospital system. Our VR and AR assisted int

Yaomin Huang, Xinmei Liu, Yichen Zhu, Zhiyuan Xu

Detecting 3D objects from point clouds is a practical yet challenging task that has attracted increasing attention recently. In this paper, we propose a Label-Guided auxiliary training method for 3D object detection (LG3D), which serves as an auxiliary network to enhance the feature learning of existing 3D object detectors. Specifically, we propose two novel

Lei Hu, Guyue Li, Xuewen Qian, Derrick Wing Kwan Ng

Reconfigurable intelligent surface (RIS) is a promising technique to enhance the performance of physical-layer key generation (PKG) due to its ability to smartly customize the radio environments. Existing RIS-assisted PKG methods are mainly based on the idealistic assumption of an independent and identically distributed (i.i.d.) channel model at both the tra

Fan Zhang, Jiayin Gu, H. T. Quan

We analytically calculate the cumulant generating function of energy and particle transport in an open 1D Kitaev chain by utilizing the Keldysh technique. The joint distribution of particle and energy currents obeys different fluctuation relations in different regions of the parameter space as a result of $U$(1) symmetry breaking and energy conservation. We

Ze-Rui Liang, De-Liang Yao

A unified formulation of one-loop tensor integrals is proposed for systematical calculations of finite volume corrections. It is shown that decomposition of the one-loop tensor integrals into a series of tensors accompanied by tensor coefficients is feasible, if a unit space-like four vector $n^\mu$, originating from the discretization effects at finite volu

Qinggang Sun, Kejun Wang

The separation of single-channel underwater acoustic signals is a challenging problem with practical significance. Few existing studies focus on the source separation problem with unknown numbers of signals, and how to evaluate the performance of the systems is not yet clear. In this paper, a deep learning-based simultaneous separating solution with a fixed

Dwarikanath Mahapatra

State of the art magnetic resonance (MR) image super-resolution methods (ISR) using convolutional neural networks (CNNs) leverage limited contextual information due to the limited spatial coverage of CNNs. Vision transformers (ViT) learn better global context that is helpful in generating superior quality HR images. We combine local information of CNNs and g

João Gouveia, Bruno F. Lourenço

We analyze self-dual polyhedral cones and prove several properties about their slack matrices. In particular, we show that self-duality is equivalent to the existence of a positive semidefinite (PSD) slack. Beyond that, we show that if the underlying cone is irreducible, then the corresponding PSD slacks are not only doubly nonnegative matrices (DNN) but are

Y. Cheng, Tao Liu, David J. Hill, Xue Lyu

This paper proposes a new distributed consensus-based control method for voltage and frequency control of fully inverter-based islanded microgrids (MGs). The proposed method includes the active power sharing in voltage control to improve the reactive power sharing accuracy and thus generalizes some existing secondary frequency and voltage control methods. Fi

Paolo Lipparini

A specialization semilattice is a structure which can be embedded into $(\mathcal P(X), \cup, \sqsubseteq )$, where $X$ is a topological space, $ x \sqsubseteq y$ means $x \subseteq Ky$, for $x,y \subseteq X$, and $K$ is closure in $X$. Specialization semilattices and posets appear as auxiliary structures in many disparate scientific fields, even unrelated t

Ruhao Wan, Yang Li, Shixin Zhu

MDS self-dual codes have nice algebraic structures and are uniquely determined by lengths. Recently, the construction of MDS self-dual codes of new lengths has become an important and hot issue in coding theory. In this paper, we develop the existing theory and construct six new classes of MDS self-dual codes. Together with our constructions, the proportion

Daniele Bartolucci, Aleks Jevnikar, Jiaming Jin, Chang-Shou Lin

In this note we show non-degeneracy and uniqueness results for solutions of Toda systems associated to general simple Lie algebras with multiple singular sources on bounded domains. The argument is based on spectral properties of Cartan matrices and eigenvalue analysis of linearized Liouville-type problems. This seems to be the first result for this class of

Jesse Read

In multi-label learning, a particular case of multi-task learning where a single data point is associated with multiple target labels, it was widely assumed in the literature that, to obtain best accuracy, the dependence among the labels should be explicitly modeled. This premise led to a proliferation of methods offering techniques to learn and predict labe

G. Arunkumar, Peter J. Cameron, T. Kavaskar, T. Tamizh Chelvam

The zero-divisor graph of a finite commutative ring with unity is the graph whose vertex set is the set of zero-divisors in the ring, with $a$ and $b$ adjacent if $ab=0$. We show that the class of zero-divisor graphs is universal, in the sense that every finite graph is isomorphic to an induced subgraph of a zero-divisor graph. This remains true for various

O. B. Kauffmann, O. Ilbert, J. R. Weaver, H. J. McCracken

This paper presents a new search for $z\geq7.5$ galaxies using the COSMOS2020 photometric catalogues. Finding galaxies at the reionization epoch through deep imaging surveys remains observationally challenging. The larger area covered by ground-based surveys like COSMOS enables the discovery of the brightest galaxies at these high redshifts. Covering $1.4$de

Sanjib Sharma, Joss Bland-Hawthorn, Joseph Silk, Celine Boehm

A change in the mass of the Galaxy with time will leave its imprint on the motions of the stars, with stars having radially outward (mass loss) or inward (mass accretion) bulk motions. Here we test the feasibility of using the mean radial motion of stars in the stellar halo to constrain the rate of change of mass in the Galaxy, for example, due to decay of d

A. K. Rao, R. P. Malik

For the St$\ddot u$ckelberg-modified massive Abelian 3-form theory in any arbitrary D-dimension of spacetime, we show that its classical gauge symmetry transformations are generated by the first-class constraints. We establish that the Noether conserved charge (corresponding to the local gauge symmetry transformations) is same as the standard form of the gen

András Attila Sulyok, Kristóf Karacs

Partially Observable Markov Decision Process (POMDP) is a framework applicable to many real world problems. In this work, we propose an approach to solve POMDPs with multimodal belief by relying on a policy that solves the fully observable version. By defininig a new, mixture value function based on the value function from the fully observable variant, we ca

Qian Chen, Guo-Liang Ma

Higher-order cumulants of the distributions of conserved charges, such as net-baryon number, are sensitive to the quantum chromodynamics(QCD) phase transition and the QCD critical point. We calculate the cumulants and correlation functions of proton, antiproton, and net-proton multiplicity distributions in Au+Au collisions at $\sqrt{s_{NN}} = 7.7$ GeV using

Yating Wang, Wing Tat Leung, Guang Lin

In this work, we propose an adaptive sparse learning algorithm that can be applied to learn the physical processes and obtain a sparse representation of the solution given a large snapshot space. Assume that there is a rich class of precomputed basis functions that can be used to approximate the quantity of interest. We then design a neural network architect

Shigui Li, Linzhang Lu, Xing Qiu, Zhen Chen

Bi-quadratic programming over unit spheres is a fundamental problem in quantum mechanics introduced by pioneer work of Einstein, Schr\"odinger, and others. It has been shown to be NP-hard; so it must be solve by efficient heuristic algorithms such as the block improvement method (BIM). This paper focuses on the maximization of bi-quadratic forms, which leads

Yukiko Kato

We examined a four-valued logic method for state settings in conflict resolution models. Decision-making models of conflict resolution, such as game theory and graph model for conflict resolution (GMCR), assume the description of a state to be the outcome of a combination of strategies or the consequence of option selection by the decision-makers. However, f

Erhan Bayraktar, Shuoqing Deng, Dominykas Norgilas

For two measures $\mu$ and $\nu$ that are in convex-decreasing order, Nutz and Stebegg (Canonical supermartingale couplings, Ann. Probab., 46(6):3351--3398, 2018) studied the optimal transport problem with supermartingale constraints and introduced two canonical couplings, namely the increasing and decreasing transport plans, that are optimal for a large cla

Matheus Brito, Vyjayanthi Chari

We study the family of irreducible modules for quantum affine $\lie{sl}_{n+1}$ whose Drinfeld polynomials are supported on just one node of the Dynkin diagram. We identify all the prime modules in this family and prove a unique factorization theorem. The Drinfeld polynomials of the prime modules encode information coming from the points of reducibility of te

Herbert Batte, Mahadi Ddamulira, Juma Kasozi, Florian Luca

Let $ \{F_n\}_{n\ge 0} $ be the sequence of Fibonacci numbers and let $p$ be a prime. For an integer $c$ we write $m_{F,p}(c)$ for the number of distinct representations of $c$ as $F_k-p^\ell$ with $k\ge 2$ and $\ell\ge 0$. We prove that $m_{F,p}(c)\le 4$.

Praveen Kumar, Sudhan Majhi, Subhabrata Paul

This letter proposes a direct construction for cross Z-complementary sets (CZCSs) with flexible lengths and a large zero correlation zone (ZCZ). CZCS is an extension of the cross Z-complementary pair (CZCP). The maximum possible ZCZ width of a CZCP is half of its sequence length. In this letter, for the first time, a generalized Boolean function based constr

Nikolay Kuznetsov

We consider the $m$-dimensional modified Helmholtz equation and establish two relations between its solutions in a bounded domain and harmonic functions. Both relations essentially rely on properties of the Newtonian potential. Some other characteristics of these solutions are also obtained.

Taeho Shin, Dongjun Lee, Dongwhee Kim, Gaeryun Sung

This paper presents an automatic layout generation framework in advanced CMOS technologies. The framework extends the template-and-grid-based layout generation methodology with the following additional techniques applied to produce optimal layouts more effectively. First, layout templates and grids are dynamically created and adjusted during runtime to serve

Nikolaos Tsilivis, Jingtong Su, Julia Kempe

We introduce a meta-learning algorithm for adversarially robust classification. The proposed method tries to be as model agnostic as possible and optimizes a dataset prior to its deployment in a machine learning system, aiming to effectively erase its non-robust features. Once the dataset has been created, in principle no specialized algorithm (besides stand

Alessio Sampieri, Guido D'Amely, Andrea Avogaro, Federico Cunico

Pushing back the frontiers of collaborative robots in industrial environments, we propose a new Separable-Sparse Graph Convolutional Network (SeS-GCN) for pose forecasting. For the first time, SeS-GCN bottlenecks the interaction of the spatial, temporal and channel-wise dimensions in GCNs, and it learns sparse adjacency matrices by a teacher-student framewor

Tarek A. Elsayed

We introduce a novel technique for efficiently cooling many-body quantum systems with unknown Hamiltonians down to their ground states with a high fidelity. The technique involves initially applying a strong external field followed by a sequence of single-degree-of-freedom (single-qubit) measurements and radiofrequency (RF) pulses to polarize the system alon

Eyal Naor, Itai Antebi, Shai Bagon, Michal Irani

Videos obtained by rolling-shutter (RS) cameras result in spatially-distorted frames. These distortions become significant under fast camera/scene motions. Undoing effects of RS is sometimes addressed as a spatial problem, where objects need to be rectified/displaced in order to generate their correct global shutter (GS) frame. However, the cause of the RS e

Xianqi He, Lin Yang, Chao Lu, Zirui Li

In urban environments, the complex and uncertain intersection scenarios are challenging for autonomous driving. To ensure safety, it is crucial to develop an adaptive decision making system that can handle the interaction with other vehicles. Manually designed model-based methods are reliable in common scenarios. But in uncertain environments, they are not r

Najma Taimoor, Semeen Rehman

This paper presents a verification-based methodology to validate the model of personalized health conditions. The model identifies the values that may result in unsafe, un-reachable, in-exhaustive, and overlapping states that otherwise threaten patients' life by producing false alarms by accepting suspicious behaviour of the target health condition. Contempo

Xuqian Ren, Yifan Liu

Previous harmonization methods focus on adjusting one inharmonious region in an image based on an input mask. They may face problems when dealing with different perturbations on different semantic regions without available input masks. To deal with the problem that one image has been pasted with several foregrounds coming from different images and needs to h

Shu-Min Wu, Chun-Xu Wang, Dan-Dan Liu, Xiao-Li Huang

We study the quantum coherence in de Sitter space for the bipartite system of Alice and Bob who initially share an entangled state between the two modes of a free massive scalar field. It is shown that the space-curvature effect can produce both local coherence and correlated coherence, leading to the increase of the total coherence of the bipartite system.