March 2023 arXiv papers — page 7

Valentin Boboc

We construct a Lefschetz exceptional collection of vector bundles in the bounded derived category of coherent sheaves of the adjoint/coadjoint Grassmannian of type $E_6$ of dimension $21$.

Feng-Ju Chang, Thejaswi Muniyappa, Kanthashree Mysore Sathyendra, Kai Wei

Personalization in multi-turn dialogs has been a long standing challenge for end-to-end automatic speech recognition (E2E ASR) models. Recent work on contextual adapters has tackled rare word recognition using user catalogs. This adaptation, however, does not incorporate an important cue, the dialog act, which is available in a multi-turn dialog scenario. In

Apurba Das

An averaging operator on an associative algebra $A$ is an algebraic abstraction of the time average operator on the space of real-valued functions defined in time-space. In this paper, we consider relative averaging operators on a bimodule $M$ over an associative algebra $A$. A relative averaging operator induces a diassociative algebra structure on the spac

Ravindra Bandara, Andrus Giraldo, Neil G. R. Broderick, Bernd Krauskopf

We study different types of solitons of a generalized nonlinear Schr\"odinger equation (GNLSE) that models optical pulses traveling down an optical waveguide with quadratic as well as quartic dispersion. A traveling-wave ansatz transforms this partial differential equation into a fourth-order nonlinear ordinary differential equation (ODE) that is Hamiltonian

Ashutosh Timilsina, Simone Silvestri

The sharing-economy-based business model has recently seen success in the transportation and accommodation sectors with companies like Uber and Airbnb. There is growing interest in applying this model to energy systems, with modalities like peer-to-peer (P2P) Energy Trading, Electric Vehicles (EV)-based Vehicle-to-Grid (V2G), Vehicle-to-Home (V2H), Vehicle-t

Bianca Viray

These lecture notes give an introduction to the Brauer-Manin obstruction to the existence of rational points, focusing on the interplay between theory and computation.

Monalisha Sharma, Rajat Kanti Nath

The non-commuting graph of a non-abelian group $G$ with center $Z(G)$ is a simple undirected graph whose vertex set is $G\setminus Z(G)$ and two vertices $x, y$ are adjacent if $xy \ne yx$. In this study, we compute Signless Laplacian spectrum and Signless Laplacian energy of non-commuting graphs of finite groups. We obtain several conditions such that the n

Florent Balacheff, Gil Solanes, Kroum Tzanev

In this paper we study certain variational aspects of the volume product functional restricted to the space of small projective deformations of a fixed convex body. In doing so, we provide a short proof of a theorem by Klartag: a strong version of the slicing conjecture implies the Mahler conjecture. We also exhibit an interesting family of critical convex b

Mohamed Tarek, Jose Storopoli, Casey Davis, Chris Elrod

This paper provides a comprehensive tutorial for Bayesian practitioners in pharmacometrics using Pumas workflows. We start by giving a brief motivation of Bayesian inference for pharmacometrics highlighting limitations in existing software that Pumas addresses. We then follow by a description of all the steps of a standard Bayesian workflow for pharmacometri

Santiago R. Simanca

We view all smooth metrics $g$ on a closed surface $\Sigma$ through their Nash isometric embeddings $f_g: (\Sigma,g) \rightarrow (\mathbb{S}^{\tilde{n}}, \tilde{g})$ into a standard sphere of large, but fixed, dimension $\tilde{n}$. We define the Willmore functional $\mathcal{W}_{f_g}$ over this space of metrics on $\Sigma$ in terms of the extrinsic quantiti

Jesús García-Davila, Jesús Leaños, Mario Lomelí-Haro, Luis Manuel Ríos-Castro

Let $P$ be a finite set of points in general position in the plane. The disjointness graph of segments $D(P)$ of $P$ is the graph whose vertices are all the closed straight line segments with endpoints in $P$, two of which are adjacent in $D(P)$ if and only if they are disjoint. As usual, we use $\chi(D(P))$ to denote the chromatic number of $D(P)$, and use

Chuanqing Xu, Kedeng Cheng, Yu Wang, Songbai Guo

Tuberculosis (TB) is an infectious disease transmitted through the respiratory system. China is one of the countries with a high burden of TB. Since 2004, an average of more than 800,000 cases of active TB have been reported each year in China. Analyzing the case data from 2004-2018, we find significant differences in TB incidence by age group. Therefore, th

Ioannis Vasileios Chremos, Heeseung Bang, Aditya Dave, Viet-Anh Le

In this paper, we present a study of a mobility game with uncertainty in the decision-making of travelers and incorporate prospect theory to model travel behavior. We formulate a mobility game that models how travelers distribute their traffic flows in a transportation network with splittable traffic, utilizing the Bureau of Public Roads function to establis

Jin Liu, Xi Wang, Xiaomeng Fu, Yesheng Chai

One-shot talking head generation has received growing attention in recent years, with various creative and practical applications. An ideal natural and vivid generated talking head video should contain natural head pose changes. However, it is challenging to map head pose sequences from driving audio since there exists a natural gap between audio-visual moda

Shengxuan Ding, Mohamed Abdel-Aty, Natalia Barbour, Dongdong Wang

Vehicles equipped with automated driving capabilities have shown potential to improve safety and operations. Advanced driver assistance systems (ADAS) and automated driving systems (ADS) have been widely developed to support vehicular automation. Although the studies on the injury severity outcomes that involve automated vehicles are ongoing, there is limite

Heeseung Bang, Andreas A. Malikopoulos

This paper addresses the challenge of generating optimal vehicle flow at the macroscopic level. Although several studies have focused on optimizing vehicle flow, little attention has been given to ensuring it can be practically achieved. To overcome this issue, we propose a route-recovery and eco-driving strategy for connected and automated vehicles (CAVs) t

Yasmen Wahba, Nazim Madhavji, John Steinbacher

For large-scale IT corpora with hundreds of classes organized in a hierarchy, the task of accurate classification of classes at the higher level in the hierarchies is crucial to avoid errors propagating to the lower levels. In the business world, an efficient and explainable ML model is preferred over an expensive black-box model, especially if the performan

Mehdi Molaei, Steven A. Redford, Wen-hung Chou, Danielle Scheff

From flocks of birds to biomolecular assemblies, systems in which many individual components independently consume energy to perform mechanical work exhibit a wide array of striking behaviors. Methods to quantify the dynamics of these so called active systems generally aim to extract important length or time scales from experimental fields. Because such meth

Marina M. Romanova, Alexander V. Koldoba, Galina V. Ustyugova, Dong Lai

We carry out hydrodynamical simulations to study the eccentricity growth of a 1-30 Jupiter mass planet located inside the fixed cavity of a protoplanetary disc. The planet exchanges energy and angular momentum with the disc at resonant locations, and its eccentricity grows due to Lindblad resonances. We observe several phases of eccentricity growth where dif

Yuang Ai, Xiaoqiang Zhou, Huaibo Huang, Lei Zhang

Unsupervised Domain Adaptation (UDA) can effectively address domain gap issues in real-world image Super-Resolution (SR) by accessing both the source and target data. Considering privacy policies or transmission restrictions of source data in practical scenarios, we propose a SOurce-free Domain Adaptation framework for image SR (SODA-SR) to address this issu

Zann Koh, Yan Qin, Yong Liang Guan, Chau Yuen

The ability to predict traffic flow over time for crowded areas during rush hours is increasingly important as it can help authorities make informed decisions for congestion mitigation or scheduling of infrastructure development in an area. However, a crucial challenge in traffic flow forecasting is the slow shifting in temporal peaks between daily and weekl

Chen Gao, Liqun Zhang, Chuankai Zhao

Considering the boundary layer problem in the case of two-dimensional flow past a wedge with the wedge angle $\varphi=\pi\frac{2m}{m+1}$, Oleinik and Samokhin obtained the local well-posedness results for $m \geq 1$. In this paper, we establish the existence and uniqueness of classical solutions to the Prandtl systems for arbitrary $m>0$, which solves the st

Jia Li, Yunfei Zhao, Yongmin Li, Ge Li

Large Language Models (LLMs) have shown great success in code generation. LLMs take as the input a prompt and output the code. A key question is how to make prompts (i.e., Prompting Techniques). Existing prompting techniques are designed for natural language generation and have low accuracy in code generation. In this paper, we propose a new prompting techni

Jinxin Wang, Jiang Hu, Shixiang Chen, Zengde Deng

We focus on a class of non-smooth optimization problems over the Stiefel manifold in the decentralized setting, where a connected network of $n$ agents cooperatively minimize a finite-sum objective function with each component being weakly convex in the ambient Euclidean space. Such optimization problems, albeit frequently encountered in applications, are qu

Cheng Zhu, Ying Tan, Shuqi Yang, Jiaqing Miao

The available evidence suggests that dynamic functional connectivity (dFC) can capture time-varying abnormalities in brain activity in resting-state cerebral functional magnetic resonance imaging (rs-fMRI) data and has a natural advantage in uncovering mechanisms of abnormal brain activity in schizophrenia(SZ) patients. Hence, an advanced dynamic brain netwo

Tianrui Guan, Aswath Muthuselvam, Montana Hoover, Xijun Wang

We present CrossLoc3D, a novel 3D place recognition method that solves a large-scale point matching problem in a cross-source setting. Cross-source point cloud data corresponds to point sets captured by depth sensors with different accuracies or from different distances and perspectives. We address the challenges in terms of developing 3D place recognition m

S. Ohkubo, Y. Hirabayashi

In the evaluation of the half-life of the neutrinoless double-$\beta$ decay ($0\nu\beta\beta$) of a doubly closed-subshell nucleus $^{96}$Zr, the structure of the nucleus $^{96}$Mo is essentially important. The $\alpha$-clustering aspects of $^{96}$Mo are investigated for the first time. By studying the nuclear rainbows in $\alpha$ scattering from $^{92}$Zr

Marissa Connor, Bruno Olshausen, Christopher Rozell

When interacting in a three dimensional world, humans must estimate 3D structure from visual inputs projected down to two dimensional retinal images. It has been shown that humans use the persistence of object shape over motion-induced transformations as a cue to resolve depth ambiguity when solving this underconstrained problem. With the aim of understandin

Chao Liang, Radu Saghin, Fan Yang, Jiagang Yang

For a class of robustly transitive diffeomorphisms on $\mathbb T^4$ introduced by Shub in [24], satisfying an additional bunching condition, we show that there exits a $C^2$ open and $C^r$ dense subset $\mathcal U^r$, $2\leq r\leq\infty$, such that any two hyperbolic points of $g\in \mathcal U^r$ with stable index $2$ are homoclinically related. As a consequ

Gengxin Liu, Qian Sun, Haibin Huang, Chongyang Ma

Given a 3D object, kinematic motion prediction aims to identify the mobile parts as well as the corresponding motion parameters. Due to the large variations in both topological structure and geometric details of 3D objects, this remains a challenging task and the lack of large scale labeled data also constrain the performance of deep learning based approache

E. J. Kolmes, M. E. Mlodik, N. J. Fisch

We extend the single-fluid solvability conditions to include plasma systems at arbitrary $\beta$ with arbitrary flows and external forcing terms. This treatment includes both the isotropic and the anisotropic cases. The generalized conditions that result can be used to generate certain classes of single-fluid equilibria.

Reo Adachi

The dynamical $\Phi^4_3$ equation is a singular SPDE and has important applications in physics. In this paper, we consider the equation by approximating the Laplacian instead of the noise or the cubic term as in previous studies. By using a good transformation as in [JP21], we show that the approximating equation is locally well-posed and that its solution c

Wei-Ting Kao, Chien-Ying Huang, Tung-Ju Tsai, Shih-Hsuan Chen

Quantum networks comprised of entangled end nodes serve stronger than the classical correlation for unparalleled quantum internet applications. However, practical quantum networking is affected by noise, which at its worst, causes end nodes to be described by pre-existing classical data. In such untrusted networks, determining quantum network fidelity and ge

Jingwen Feng, Feng Yang, Cai Cheng, Yin Huang

In this work, we study the strong decays of the newly observed $\Omega^{*}_c(3185)$ and $\Omega^{*}_c(3327)$ assuming that $\Omega^{*}_c(3185)$ and $\Omega^{*}_c(3327)$ as $S$-wave $D\Xi$ and $D^{*}\Xi$ molecular state, respectively. Since the $\Omega_c^{*}$ was observed in the $\Xi_c^{+}K^{-}$ invariant mass distributions, the partial decay width of $\Omega

Shaohan Chen, Di Fan, Chuanhou Gao

Blast furnace modeling and control is one of the important problems in the industrial field, and the black-box model is an effective mean to describe the complex blast furnace system. In practice, there are often different learning targets, such as safety and energy saving in industrial applications, depending on the application. For this reason, this paper

Yilang Zhang, Bingcong Li, Shijian Gao, Georgios B. Giannakis

Meta-learning owns unique effectiveness and swiftness in tackling emerging tasks with limited data. Its broad applicability is revealed by viewing it as a bi-level optimization problem. The resultant algorithmic viewpoint however, faces scalability issues when the inner-level optimization relies on gradient-based iterations. Implicit differentiation has been

Federico Pasqualotto, Yakov Shlapentokh-Rothman, Maxime Van de Moortel

We study the massive scalar field equation $\Box_g \phi = m^2 \phi$ on a stationary and spherically symmetric black hole $g$ (including in particular the Schwarzschild and Reissner--Nordstr\"om black holes in the full sub-extremal range) for solutions $\phi$ projected on a fixed spherical harmonic. Our problem involves the scattering of an attractive long-ra

Yongzhen Wang, Xuefeng Yan, Yanbiao Niu, Lina Gong

Rainy weather significantly deteriorates the visibility of scene objects, particularly when images are captured through outdoor camera lenses or windshields. Through careful observation of numerous rainy photos, we have found that the images are generally affected by various rainwater artifacts such as raindrops, rain streaks, and rainy haze, which impact th

Laixiang Qin, Chunlai Li, Ziang Xie, Yiqun Wei

Recently, short channel effects (SCE) and power consumption dissipation problems pose big challenges which need imperative actions to be taken to deal with for field effect transistor to further scale down as semiconductor technology enters into sub-10nm technology node. From 3nm technology node and beyond, gate all around field effect transistor steps onto

Yuxuan Shi, Hongbo Cheng

We research on the neutrino pair annihilation $\nu+\overline{\nu}\longrightarrow e^{-}+e^{+}$ around a massive source in asymptotic safety. Since neutrinos and photons have the same geodesic equation around black holes, we can estimate the radius where the neutrinos will be released by obtaining a series of trajectory curves with various correction values $\

Guiqiang Wang, Dehua Kong, Wei Tang, Jie Fang

Cold atmospheric plasma (CAP) displays antimicrobial, antitumor, and antiviral properties, while the underlying mechanism is seldom clearly elucidated. In this work, we employed CAP with air-feeding gas to directly inactivate SARS-CoV-2. The results indicate that the typical SARS-CoV-2 morphological spikes disappeared after plasma treatment and the proteosom

Ye Tian, Yuqi Gu, Yang Feng

Representation multi-task learning (MTL) has achieved tremendous success in practice. However, the theoretical understanding of these methods is still lacking. Most existing theoretical works focus on cases where all tasks share the same representation, and claim that MTL almost always improves performance. Nevertheless, as the number of tasks grows, assumin

Tao Bai, Chen Chen, Lingjuan Lyu, Jun Zhao

Recent studies show that models trained by continual learning can achieve the comparable performances as the standard supervised learning and the learning flexibility of continual learning models enables their wide applications in the real world. Deep learning models, however, are shown to be vulnerable to adversarial attacks. Though there are many studies o

Takuya Mizoguchi, Seiji Matsumoto, Minoru Biyajima

Using the two-component model, we analyze Bose-Einstein correlations in pp collisions at the center-of-mass energy of 13 TeV, measured by the CMS Collaboration at the LHC, and compare results with the $\tau$-model. We utilize data described by the double ratios with an average pair transverse momentum $0\le k_T\le 1.0$ GeV and six intervals described by the

Vudtiwat Ngampruetikorn, David J. Schwab

The information bottleneck (IB) method offers an attractive framework for understanding representation learning, however its applications are often limited by its computational intractability. Analytical characterization of the IB method is not only of practical interest, but it can also lead to new insights into learning phenomena. Here we consider a genera

Jean Lévine

In this article, we introduce the notion of differential flatness by pure prolongation: loosely speaking, a system admits this property if, and only if, there exists a pure prolongation of finite order such that the prolonged system is feedback linearizable. We obtain Lie-algebraic necessary and sufficient conditions for a general nonlinear multi-input syste

Guohao Li, Hasan Abed Al Kader Hammoud, Hani Itani, Dmitrii Khizbullin

The rapid advancement of chat-based language models has led to remarkable progress in complex task-solving. However, their success heavily relies on human input to guide the conversation, which can be challenging and time-consuming. This paper explores the potential of building scalable techniques to facilitate autonomous cooperation among communicative agen

Ashna Gulati, Tara Murphy, David L. Kaplan, Roberto Soria

We present a systematic search for radio counterparts of novae using the Australian Square Kilometer Array Pathfinder (ASKAP). Our search used the Rapid ASKAP Continuum Survey, which covered the entire sky south of declination $+41^{\circ}$ ($\sim34,000$ square degrees) at a central frequency of 887.5 MHz, the Variables and Slow Transients Pilot Survey, whic

Nathan Musoke, Emily Kendall, Mateja Gosenca, Lillian Guo

In this Working Paper we analyse computational strategies for using aggregated spatio-temporal population data acquired from telecommunications networks to infer travel and movement patterns between geographical regions. Specifically, we focus on hour-by-hour cellphone counts for the SA-2 geographical regions covering the whole of New Zealand. This Working P

Cicely Motamedi, Karen Sauer

We show, theoretically and experimentally, how the absolute orientation and polarization state of radio-frequency (RF) magnetic fields in a transverse 2D plane can be uniquely determined using two optically pumped atomic magnetometers. In addition, the output signals from these quantum sensors can be readily expressed as a magnetic Jones vector. This composi

Nathan A. Keane, Sourabh V. Apte, Suhas S. Jain, Makrand A. Khanwale

The predictive capability of two way--coupled point-particle Euler-Lagrange model in accurately capturing particle-flow interactions under grid refinement, wherein the particle size can be comparable to the grid size, is systematically evaluated. Two situations are considered, (i) uniform flow over a stationary particle, and (ii) decaying isotropic turbulenc

Vesa Kaarnioja, Frances Y. Kuo, Ian H. Sloan

We describe a fast method for solving elliptic partial differential equations (PDEs) with uncertain coefficients using kernel interpolation at a lattice point set. By representing the input random field of the system using the model proposed by Kaarnioja, Kuo, and Sloan (SIAM J.~Numer.~Anal.~2020), in which a countable number of independent random variables

Juliana Pedrotti, Thaísa Tamusiunas

Given a Galois extension $R^{\beta} \subset R$, where $\beta$ is an action of a finite groupoid on a noncommutative ring, we present some conditions to the Galois map be injective.

Beatrice-Helen Vritsiou

It is shown that every not-necessarily symmetric convex body $K$ in ${\mathbb R}^n$ has an affine image $\tilde{K}$ of $K$ such that the covering numbers of $\tilde{K}$ by growing dilates of the unit Euclidean ball, as well as those of the unit Euclidean ball by growing dilates of $\tilde{K}$, decrease in a regular way. This extends to the non-symmetric case

Yu. S. Lutostansky, A. N. Fazliakhmetov, G. A. Koroteev, V. N. Tikhonov

The process of neutrino interaction with $^{98}$Mo and $^{100}$Mo isotopes is studied taking into consideration the effect of charge-exchange resonances. The experimental data on the strength functions $S(E)$ obtained in charge-exchange reactions $(p; n)$ and $(^3\mathrm{He}, t)$ and the strength functions $S(E)$ calculated within the theory of finite Fermi

Inigo Incer, Apurva Badithela, Josefine Graebener, Piergiuseppe Mallozzi

Contract-based design is a method to facilitate modular system design. While there has been substantial progress on the theory of contracts, there has been less progress on scalable algorithms for the algebraic operations in this theory. In this paper, we present: 1) principles to implement a contract-based design tool at scale and 2) Pacti, a tool that can

Masaomi Yamaguchi, Nobukazu Yoshioka

To realize reliable quantum software, techniques to automatically ensure the quantum software's correctness have recently been investigated. However, they primarily focus on fixed quantum circuits rather than the procedure of building quantum circuits. Despite being a common approach, the correctness of building circuits using different parameters following

Elia Zanoni, Thomas Theurer, Gilad Gour

Using local operations and classical communication (LOCC), entanglement can be manipulated but not created. However, entanglement can be embezzled. In this work, we completely characterize universal embezzling families and demonstrate how this singles out the original family introduced by van Dam and Hayden. To achieve this, we first give a full characteriza

Mohammad Khodadad, Morteza Rezanejad, Ali Shiraee Kasmaee, Kaleem Siddiqi

The analysis of 3D point clouds has diverse applications in robotics, vision and graphics. Processing them presents specific challenges since they are naturally sparse, can vary in spatial resolution and are typically unordered. Graph-based networks to abstract features have emerged as a promising alternative to convolutional neural networks for their analys

Bahman Kalantari

Building on a classification of zeros of cubic equations due to the $12$-th century Persian mathematician Sharaf al-Din Tusi, together with Smale's theory of {\it point estimation}, we derive an efficient recipe for computing high-precision approximation to a real root of an arbitrary real cubic equation. First, via reversible transformations we reduce any r

Feiyang Zhao, Itai Gurvich, John Hasenbein

We re-visit the global - relative to control policies - stability of multiclass queueing networks. In these, as is known, it is generally insufficient that the nominal utilization at each server is below 100%. Certain policies, although work conserving, may destabilize a network that satisfies the nominal-load conditions; additional conditions on the primiti

Saber Elsayed

The popularity of generative text AI tools in answering questions has led to concerns regarding their potential negative impact on students' academic performance and the challenges that educators face in evaluating student learning. To address these concerns, this paper introduces an evolutionary approach that aims to identify the best set of Bloom's taxonom

Kaan Gokcesu, Hakan Gokcesu

We investigate the nonlinear regression problem under L2 loss (square loss) functions. Traditional nonlinear regression models often result in non-convex optimization problems with respect to the parameter set. We show that a convex nonlinear regression model exists for the traditional least squares problem, which can be a promising towards designing more co

Zachary Bogorad, Peter W. Graham, Giorgio Gratta

Significant effort has been devoted to searching for new fundamental forces of nature. At short length scales (below approximately 10 nm), the strongest experimental constraints come from neutron scattering from individual nuclei in gases. The leading experiments at longer length scales instead measure forces between macroscopic test masses. We propose a hyb

Lecheng Zheng, Dawei Zhou, Hanghang Tong, Jiejun Xu

There have been tremendous efforts over the past decades dedicated to the generation of realistic graphs in a variety of domains, ranging from social networks to computer networks, from gene regulatory networks to online transaction networks. Despite the remarkable success, the vast majority of these works are unsupervised in nature and are typically trained

Samuel Riedel, Matheus Cavalcante, Renzo Andri, Luca Benini

Shared L1 memory clusters are a common architectural pattern (e.g., in GPGPUs) for building efficient and flexible multi-processing-element (PE) engines. However, it is a common belief that these tightly-coupled clusters would not scale beyond a few tens of PEs. In this work, we tackle scaling shared L1 clusters to hundreds of PEs while supporting a flexible

Andrew Arrasmith, Andrew Patterson, Alice Boughton, Marco Paini

The approximate state estimation and the closely related classical shadows methods allow for the estimation of complicated observables with relatively few shots. As these methods make use of random measurements that can symmetrise the effect of readout errors, they have been shown to permit simplified approaches to readout error mitigation which require only

Athina Markopoulou, Rahmadi Trimananda, Hao Cui

Apps and devices (mobile devices, web browsers, IoT, VR, voice assistants, etc.) routinely collect user data, and send them to first- and third-party servers through the network. Recently, there is a lot of interest in (1) auditing the actual data collection practices of those systems; and also in (2) checking the consistency of those practices against the s

Danijela Damjanovic, Amie Wilkinson, Disheng Xu

We prove several rigidity results about the centralizer of a smooth diffeomorphism, concentrating on two families of examples: diffeomorphisms with transitive centralizer, and perturbations of isometric extensions of Anosov diffeomorphisms of nilmanifolds. We classify all smooth diffeomorphisms with transitive centralizer: they are exactly the maps that pres

A. Castro-Ginard, A. G. A. Brown, Z. Kostrzewa-Rutkowska, T. Cantat-Gaudin

Understanding which sources are present in an astronomical catalogue and which are not is crucial for the accurate interpretation of astronomical data. In particular, for the multidimensional Gaia data, filters and cuts on different parameters or measurements introduces a selection function that may unintentionally alter scientific conclusions in subtle ways

Henry C. Fitzhugh, James W. Furness, Mark R. Pederson, Juan E. Peralta

Multi-center transition metal complexes (MCTMs) with magnetically interacting ions have been proposed as components for information processing devices and storage units. For any practical application of MCTMs as magnetic units, it is crucial to characterize their magnetic behavior, and in particular the isotropic magnetic exchange coupling, J, between its ma

David Nesvorny, Fernando V. Roig, David Vokrouhlicky, William F. Bottke

The lunar crater record features $\sim 50$ basins. The radiometric dating of Apollo samples indicates that the Imbrium basin formed relatively late -- from the planet formation perspective -- some $\simeq 3.9$ Ga. Here we develop a dynamical model for impactors in the inner solar system to provide context for the interpretation of the lunar crater record. Th

Zhe Liu, Zhou Chen, Qi Wang, Sheng Zhang

Untrained Neural Network Prior (UNNP) based algorithms have gained increasing popularity in tomographic imaging, as they offer superior performance compared to hand-crafted priors and do not require training. UNNP-based methods usually rely on deep architectures which are known for their excellent feature extraction ability compared to shallow ones. Contrary

Kamyar Saeedi, Stephanie Simmons, Jeff Z. Salvail, Phillip Dluhy

Quantum memories capable of storing and retrieving coherent information for extended times at room temperature would enable a host of new technologies. Electron and nuclear spin qubits using shallow neutral donors in semiconductors have been studied extensively but are limited to low temperatures ($\le$10 K); however, the nuclear spins of ionized donors have

Boris S. Kerner

We have found that a variety of phase transitions occurring between three traffic phases (free flow (F), synchronized flow (S), and wide moving jam (J)) determine the spatiotemporal dynamics of traffic consisting of 100% automated-driving vehicles moving on a two-lane road with an on-ramp bottleneck. This means that three-phase traffic theory is a common fra

Chinmay Rane, Kanishka Tyagi, Sanjeev Malalur, Yash Shinge

Linear transformation of the inputs alters the training performance of feed-forward networks that are otherwise equivalent. However, most linear transforms are viewed as a pre-processing operation separate from the actual training. Starting from equivalent networks, it is shown that pre-processing inputs using linear transformation are equivalent to multiply

Manuel Ferreira-Junior, Jessica T. S. Reinaldo, Telmo M. Silva Filho, Eufrasio A. Lima Neto

Item response theory aims to estimate respondent's latent skills from their responses in tests composed of items with different levels of difficulty. Several models of item response theory have been proposed for different types of tasks, such as binary or probabilistic responses, response time, multiple responses, among others. In this paper, we propose a ne

Sergey Sergeev

There is a sub-class of the solutions to Quantum Tetrahedron Equation related to the algebraical Pentagon Equation. The Quantum Tetrahedron Equation defines an evolution operator in wholly discrete three dimensional space-time. In this paper we establish the Liouville integrability of one particular quantum evolution model/classical integrable model on cubic

Sergey Sergeev

The Rogers-Ramanujan identity for $\!\!\phantom{|}_1\psi_1$ $$ \sum_{n\in\mathbb{Z}} \frac{(a;q)_n}{(b;q)_n} z^n\;=\; \frac{(q,b/a,az,q/az;q)_\infty}{(b,q/a,z,b/az;q)_\infty} $$ can be classified as one related to the Bethe Ansatz for ``chain length $N=1$, ground state XXZ model with an arbitrary negative spin''.

Hasin Rehana, Nur Bengisu Çam, Mert Basmaci, Jie Zheng

Detecting protein-protein interactions (PPIs) is crucial for understanding genetic mechanisms, disease pathogenesis, and drug design. However, with the fast-paced growth of biomedical literature, there is a growing need for automated and accurate extraction of PPIs to facilitate scientific knowledge discovery. Pre-trained language models, such as generative

Nicholas Meisburger, Vihan Lakshman, Benito Geordie, Joshua Engels

Efficient large-scale neural network training and inference on commodity CPU hardware is of immense practical significance in democratizing deep learning (DL) capabilities. Presently, the process of training massive models consisting of hundreds of millions to billions of parameters requires the extensive use of specialized hardware accelerators, such as GPU

Sergey Sergeev

In this paper we discuss an example of classical integrable equation with rather unusual `B'-type Kadomtsev-Petviashvili (KP) soliton hierarchy.

Sergey Sergeev

We study the modular pair of $TQ$ equations for the quantum $\sin$-Gordon model in the framework of non-compact $\mathcal{U}_{q,q^*}(\widehat{sl}_2)$. We assume some conjectures for the thermodynamic limit allowing one to obtain its ground state.

Enrico Tapavicza, Trevor Reutershan, Travis Thompson

We present a method to simulate ultrafast pump-probe time-resolved circular dichroism (TRCD) spectra based on time-dependent density functional theory trajectory surface hopping. The method is applied to simulate the TRCD spectrum along the photoinduced ring-opening of provitamin D. Simulations reveal that the initial decay of the signal is due to excited st

Yang Liu, Antonio Padilla, Francisco G. Pedro

We consider a wide class of four-dimensional effective field theories in which gravity is coupled to multiple four-forms and their dual scalar fields, with membrane sources charged under the corresponding three-form potentials. Four-form flux, quantised in units of the membrane charges, generically generates a landscape of vacua with a range of values for th

Andrés Larraín-Hubach, Jacob Shapiro

We prove an explicit weighted estimate for the semiclassical Schr\"odinger operator $P = - h^2 \partial^2_x + V(x;h)$ on $L^2(\mathbb{R})$, with $V(x;h)$ a finite signed measure, and where $h >0$ is the semiclassical parameter. The proof is a one dimensional instance of the spherical energy method, which has been used to prove Carleman estimates in higher di

Himani Sharma, Adam Sikora

We consider the setting of manifolds with ends which are obtained by compact perturbation (gluing) of ends of the form $\mathbb{R}^{n_i}\times \mathcal{M}_i$. We investigate family of vertical resolvent $\{\sqrt{t}\nabla(1+t\Delta)^{-m}\}_{t>0}$ where $m\geq1$. We show that the family is uniformly continuous on all $L^p$ for $1\le p \le \min_{i}n_i$. Interes

Timothy Redgrave, Colton Crum

Neural networks have been proven to be both highly effective within computer vision, and highly vulnerable to adversarial attacks. Consequently, as the use of neural networks increases due to their unrivaled performance, so too does the threat posed by adversarial attacks. In this work, we build towards addressing the challenge of adversarial robustness by e

Matthias Eisenmann, Annika Reinke, Vivienn Weru, Minu Dietlinde Tizabi

International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from these competitions. Do they really generate scientific progress? What are common and successful participation strategies? What makes a solution

Dániel Gerbner, Hilal Hama Karim

Given graphs $H$ and $F$, $\mathrm{ex}(n,H,F)$ denotes the largest number of copies of $H$ in $F$-free $n$-vertex graphs. Let $\chi(H)<\chi(F)=r+1$. We say that $H$ is $F$-Tur\'an-stable if the following holds. For any $\varepsilon>0$ there exists $\delta>0$ such that if an $n$-vertex $F$-free graph $G$ contains at least $\mathrm{ex}(n,H,F)-\delta n^{|V(H)|}

Fengjiao Zou, Jennifer Ogle, Weimin Jin, Patrick Gerard

One of the main challenges autonomous vehicles (AVs) will face is interacting with pedestrians, especially at unmarked midblock locations where the right-of-way is unspecified. This study investigates pedestrian crossing behavior given different roadway centerline features (i.e., undivided, two-way left-turn lane (TWLTL), and median) and various AV operation

Steve Hanneke, Shay Moran, Vinod Raman, Unique Subedi

We study multiclass classification in the agnostic adversarial online learning setting. As our main result, we prove that any multiclass concept class is agnostically learnable if and only if its Littlestone dimension is finite. This solves an open problem studied by Daniely, Sabato, Ben-David, and Shalev-Shwartz (2011,2015) who handled the case when the num

Sergey Sergeev

In this paper we discuss some properties of Baxter's TQ equation for the eight-vertex elliptic Sklyanin algebra it its compact representation based on the elliptic Gamma-functions. As the main result, we establish the structure of the spectrum of the corresponding quantum integrable model.

Arnaud Carignan-Dugas, Dar Dahlen, Ian Hincks, Egor Ospadov

Quantum computers are inhibited by physical errors that occur during computation. For this reason, the development of increasingly sophisticated error characterization and error suppression techniques is central to the progress of quantum computing. Error distributions are considerably influenced by the precise gate scheduling across the entire quantum proce

Changho Shin, Sonia Cromp, Dyah Adila, Frederic Sala

Weak supervision enables efficient development of training sets by reducing the need for ground truth labels. However, the techniques that make weak supervision attractive -- such as integrating any source of signal to estimate unknown labels -- also entail the danger that the produced pseudolabels are highly biased. Surprisingly, given everyday use and the

Haoyu Wu, Alexandros Graikos, Dimitris Samaras

Neural rendering of implicit surfaces performs well in 3D vision applications. However, it requires dense input views as supervision. When only sparse input images are available, output quality drops significantly due to the shape-radiance ambiguity problem. We note that this ambiguity can be constrained when a 3D point is visible in multiple views, as is th

Stefan Friedl, Kenan İnce

We will explain the relationship between one of the most beautiful theorems in topology, namely Fenn's Table Theorem, and one of the most famous open problems in topology, namely the Square Peg Problem.

Shih-Hong Huang, Chieh-Yang Huang, Ya-Fang Lin, Ting-Hao 'Kenneth' Huang

The proliferation of automated conversational systems such as chatbots, spoken-dialogue systems, and smart speakers, has significantly impacted modern digital life. However, these systems are primarily designed to provide answers to well-defined questions rather than to support users in exploring complex, ill-defined questions. In this paper, we aim to push

Michael Correll

Univariate visualizations like histograms, rug plots, or box plots provide concise visual summaries of distributions. However, each individual visualization may fail to robustly distinguish important features of a distribution, or provide sufficient information for all of the relevant tasks involved in summarizing univariate data. One solution is to juxtapos

Purvish Jajal, Wenxin Jiang, Arav Tewari, Erik Kocinare

Software engineers develop, fine-tune, and deploy deep learning (DL) models using a variety of development frameworks and runtime environments. DL model converters move models between frameworks and to runtime environments. Conversion errors compromise model quality and disrupt deployment. However, the failure characteristics of DL model converters are unkno