May 2023 arXiv papers — page 155

Cosetta Baroni, Bo Huang, Isabella Fritsche, Erich Dobler

The notion of quasi-particles is essential for understanding the behaviour of complex many-body systems. A prototypical example of a quasi-particle, a polaron, is an impurity strongly interacting with a surrounding medium. Fermi polarons, created in a Fermi sea, provide a paradigmatic realization of this concept. As an inherent and important property such qu

Masaru Nakanotani, Lingling Zhao, Gary P. Zank

The transport of energetic particles in response to solar wind turbulence is important for space weather. To understand charged particle transport, it is usually assumed that the phase of the turbulence is randomly distributed (the random phase approximation) in quasi-linear theory and simulations. In this paper, we calculate the coherence index, $C_\phi$, o

Priyanka Kaswan, Sennur Ulukus

We consider a network of $n$ user nodes that receives updates from a source and employs an age-based gossip protocol for faster dissemination of version updates to all nodes. When a node forwards its packet to another node, the packet information gets mutated with probability $p$ during transmission, creating misinformation. The receiver node does not know w

Badih Ghazi, Pritish Kamath, Ravi Kumar, Raghu Meka

We introduce a new mechanism for stochastic convex optimization (SCO) with user-level differential privacy guarantees. The convergence rates of this mechanism are similar to those in the prior work of Levy et al. (2021); Narayanan et al. (2022), but with two important improvements. Our mechanism does not require any smoothness assumptions on the loss. Furthe

Paul B. Rimmer

I show that exoplanets can be used to test origins scenarios. Origins scenarios start with certain initial conditions, proceed via a network of chemical reactions and, if successful, result in a chemistry that is closer to a living system than the initial conditions. Exoplanet environments can be applied to test each of these three aspects of origins scenari

M. Nakanotani, G. P. Zank, L. -L. Zhao

Pickup ions (PUIs) play a crucial role in the heliosphere, contributing to the mediation of large-scale structures such as the distant solar wind, the heliospheric termination shock (HTS), and the heliopause. While magnetic reconnection is thought to be a common process in the heliosphere due to the presence of heliospheric current sheets, it is poorly under

Noam Soker

The Red Nova ZTF SLRN-2020 is the third transient event with properties that are compatible with the merger of a planet with a main sequence (or close to) star on a dynamical timescale. While the two first transient events occurred in young stellar objects, ZTF SLRN-2020 occurred in an old system. Nonetheless, I show that the three star-planet intermediate l

Jeremy M. Dover

A blocking semioval is a set of points in a projective plane that is both a blocking set (i.e., every line meets the set, but the set contains no line) and a semioval (i.e., there is a unique tangent line at each point). The smallest size of a blocking semioval is known for all finite projective planes of order less than 11; we investigate the situation in P

Jun Wang

Let $X$ be any smooth Deligne-Mumford stack with projective coarse moduli, and $Y$ be a smooth complete intersection in $X$ associated with a direct sum of semi-positive line bundles. We will introduce a useful and broad class known as admissible series for discussing quantum Lefschetz theorem. For any admissible series on the Givental's Lagrangian cone of $

Roman Remme, Tobias Kaczun, Maximilian Scheurer, Andreas Dreuw

Orbital-free density functional theory (OF-DFT) holds the promise to compute ground state molecular properties at minimal cost. However, it has been held back by our inability to compute the kinetic energy as a functional of the electron density only. We here set out to learn the kinetic energy functional from ground truth provided by the more expensive Kohn

Lakshmi Arbatti, Abhishek Hosamath, Vikram Ramanarayanan, Ira Shoulson

The USA Food and Drug Administration has accorded increasing importance to patient-reported problems in clinical and research settings. In this paper, we explore one of the largest online datasets comprising 170,141 open-ended self-reported responses (called "verbatims") from patients with Parkinson's (PwPs) to questions about what bothers them about their P

CMS Collaboration

A search for the rare $\eta$ $\to$ $\mu^+\mu^-\mu^+\mu^-$ double-Dalitz decay is performed using a sample of proton-proton collisions, collected by the CMS experiment at the CERN LHC with high-rate muon triggers in 2017-2018 and corresponding to an integrated luminosity of 101 fb$^{-1}$. A signal having a statistical significance well in excess of 5 standard

Lara Bossinger, Man-Wai Cheung, Timothy Magee, Alfredo Nájera Chávez

Let $Y$ be a (partial) minimal model of a scheme $V$ with a cluster structure. Under natural assumptions, for every choice of seed we associate a Newton--Okounkov body to every divisor on $Y$ supported on $Y \setminus V$ and show that these Newton--Okounkov bodies are positive sets in the sense of Gross, Hacking, Keel and Kontsevich \cite{GHKK}. This constru

Miguel Herranz, Clara Pedrosa, Daniel Martinez-Fernandez, Katerina Foteinopoulou

Through extensive molecular simulations we determine a phase diagram of attractive, flexible polymer chains in two and three dimensions. A surprisingly rich collection of distinct crystal morphologies appear, which can be finely tuned through the range of attraction. In three dimensions these include the face centered cubic, hexagonal close packed, simple he

Oleg Y. Imanuvilov, M. Yamamoto

We consider initial boundary value problems with the homogeneous Neumann boundary condition. Given an initial value, we establish the uniqueness in determining a spatially varying coefficient of zeroth-order term by a single measurement of Dirichlet data on an arbitrarily chosen subboundary. The uniqueness holds in a subdomain where the initial value is posi

Jan Ole Ernst, Juan-Rafael Alvarez, Thomas D. Barrett, Axel Kuhn

Photonic qubits play an instrumental role in the development of advanced quantum technologies, including quantum networking, boson sampling and measurement based quantum computing. A promising framework for the deterministic production of indistinguishable single photons is an atomic emitter coupled to a single mode of a high finesse optical cavity. Polarisa

I. A. Yakunin, E. A. Semenko, I. I. Romanyuk, A. V. Moiseeva

The paper presents the first results of the ongoing spectropolarimetric monitoring of magnetic fields of stars, whose chemically peculiar nature has been previously revealed with the 1-m SAO RAS telescope. We selected the sample candidates using the photometric data of the Kepler and TESS space missions. The efficiency of the method of searching for new CP s

Oscar Fuentes-Muñoz, Daniel J. Scheeres, Davide Farnocchia, Ryan S. Park

The catalog of km-sized near-Earth objects (NEOs) is nearly complete. Typical impact monitoring analyses search for possible impacts over the next 100 years and none of the km-sized objects represent an impact threat over that time interval. Assessing the impact risk over longer time scales is a challenge since orbital uncertainties grow. To overcome this li

Friedemann Queisser, Konstantin Krutitsky, Patrick Navez, Ralf Schützhold

Via the hierarchy of correlations, we study doublon-holon pair creation in the Mott state of the Fermi-Hubbard model induced by a time-dependent electric field. Special emphasis is placed on the analogy to electron-positron pair creation from the vacuum in quantum electrodynamics (QED). We find that the accuracy of this analogy depends on the spin structure

Matthew Daws, Jacek Krajczok, Christian Voigt

We study the Haagerup--Kraus approximation property for locally compact quantum groups, generalising and unifying previous work by Kraus--Ruan and Crann. Along the way we discuss how multipliers of quantum groups interact with the $\mathrm{C}^*$-algebraic theory of locally compact quantum groups. Several inheritance properties of the approximation property a

Ian Ball

This note shows that in Bauer's maximum principle, the assumed convexity of the objective function can be relaxed to quasiconvexity.

Thomas A. Schmidt, Ayşe Yıltekin-Karataş

In 1979, for each signature for Fuchsian groups of the first kind, Bowen and Series constructed an explicit fundamental domain for one group of the signature, and from this a function on $\mathbb S^1$ tightly associated with this group. In general, their fundamental domain enjoys what has since been called the `extension property'. We determine the exact set

Shubhanshu Shekhar, Ziyu Xu, Zachary C. Lipton, Pierre J. Liang

We introduce the notion of a risk-limiting financial auditing (RLFA): given $N$ transactions, the goal is to estimate the total misstated monetary fraction~($m^*$) to a given accuracy $\epsilon$, with confidence $1-\delta$. We do this by constructing new confidence sequences (CSs) for the weighted average of $N$ unknown values, based on samples drawn without

Mandana Mirbakhsh

Over the past half-century, the combination of technology and innovation has been developed to manage the negative impact of synthetic fertilizer on land ecosystems to identify the limitations of sustainability and optimize agricultural systems. The application of nano-fertilizers has achieved considerable interest due to their significant role as environmen

Teodor Rares Begu

Artificial Intelligence has gained a lot of traction in the recent years, with machine learning notably starting to see more applications across a varied range of fields. One specific machine learning application that is of interest to us is that of software safety and security, especially in the context of parallel programs. The issue of being able to detec

Arno Frauenfelder, Adrian Wiltz, Dimos V. Dimarogonas

This paper proposes a controller for safe lane change manoeuvres of autonomous vehicles using high-order control barrier and Lyapunov functions. The inputs are calculated using a quadratic program (CLF-CBF-QP) which admits short calculation times. The controller allows for adaptive cruise control, lane following, lane switching and ensures collision avoidanc

Yichen Qin

In this article, we study a family of motives $\mathrm{M}_{n+1}^k$ associated with the symmetric power of Kloosterman sheaves, as constructed by Fres\'an, Sabbah, and Yu. They demonstrated that for $n=1$, the motivic $L$-functions of $\mathrm{M}_{2}^k$ extend meromorphically to $\mathbb{C}$ and satisfy the functional equations conjectured by Broadhurst and R

Mihir Vahanwala

We consider the following Markov Reachability decision problems that view Markov Chains as Linear Dynamical Systems: given a finite, rational Markov Chain, source and target states, and a rational threshold, does the probability of reaching the target from the source at the $n^{th}$ step: (i) equal the threshold for some $n$? (ii) cross the threshold for som

Joseph R. Masiero, Maxime Devogele, Isabella Macias, Joahan Castaneda Jaimes

Polarization phase-curve measurements provide a unique constraint on the surface properties of asteroids that are complementary to those from photometry and spectroscopy, and have led to the identification of the ``Barbarian'' asteroids as a class of objects with highly unusual surfaces. We present new near-infrared polarimetric observations of six Barbarian

Kayla J. Rodriguez, Nickolas H. Pilgram, Daniel S. Barker, Stephen P. Eckel

We simulate the capture process of MgF molecules into a frequency-chirped molecular MOT. Our calculations show that by chirping the frequency, the MOT capture velocity is increased by about of factor of 4 to 80 m/s, allowing for direct loading from a two-stage cryogenic buffer gas beam source. Moreover, we simulate the effect of this frequency chirp for mole

Wiem Abderrahim, Osama Amin, Basem Shihada

Terrestrial data centers suffer from a growing carbon footprint that could contribute with $14\%$ to global CO2 emissions by 2040. High Altitude Platform (HAP) is a promising airborne technology that can unleash the computing frontier in the stratospheric range by hosting a flying data center. HAP systems can endorse the sustainable green operation of data c

Tomer Bucher, Harel Nahari, Hanan Herzig Sheinfux, Ron Ruimy

Accessing the low-energy non-equilibrium dynamics of materials and their polaritons with simultaneous high spatial and temporal resolution has been a bold frontier of electron microscopy in recent years. One of the main challenges lies in the ability to retrieve extremely weak signals while simultaneously disentangling amplitude and phase information. Here,

Jimeng Shi, Rukmangadh Myana, Vitalii Stebliankin, Azam Shirali

Accurate time series forecasting is a fundamental challenge in data science. It is often affected by external covariates such as weather or human intervention, which in many applications, may be predicted with reasonable accuracy. We refer to them as predicted future covariates. However, existing methods that attempt to predict time series in an iterative ma

Haoran Chen, Junren Shi

We study superconductivity in the superionic phase of the clathrate hydride Li$_2$MgH$_{16}$, where hydrogen ions diffuse among the lattice formed by lithium and magnesium ions. By employing the stochastic path-integral approach, we non-perturbatively take into account the effects of quantum diffusion and anharmonic vibrations. Our calculations reveal strong

Gabriele Di Antonio, Gianni Valerio Vinci, Luciano Pietronero, Marco Alberto Javarone

Taking informed decisions, namely acting rationally, is an individual attitude of paramount relevance in nature and human societies. In this work, we study how rationality spreads in a community. To this end, through an agent-based model, we analyse the dynamics of a population whose individuals, endowed with a rational attitude controlled by a numerical par

Sebastian J. Szybka, Syed U. Naqvi

We demonstrate the existence of chaotic geodesics for the Einstein-Rosen standing gravitational waves. The complex dynamics of massive test particles are governed by a chaotic heteroclinic network. We present the fractal associated with the system under investigation. Gravitational standing waves produce intricate patterns through test particles in a vague a

Minh N. Bùi, Patrick L. Combettes

We first present an abstract principle for the interchange of infimization and integration over spaces of mappings taking values in topological spaces. New conditions on the underlying space and the integrand are then introduced to convert this principle into concrete scenarios that are shown to capture those of various existing interchange rules. These resu

Felipe Tobar, Arnaud Robert, Jorge F. Silva

Let us consider the deconvolution problem, that is, to recover a latent source $x(\cdot)$ from the observations $\mathbf{y} = [y_1,\ldots,y_N]$ of a convolution process $y = x\star h + \eta$, where $\eta$ is an additive noise, the observations in $\mathbf{y}$ might have missing parts with respect to $y$, and the filter $h$ could be unknown. We propose a nove

Mihir Vahanwala

Linear Recurrence Sequences (LRS) are a fundamental mathematical primitive for a plethora of applications such as the verification of probabilistic systems, model checking, computational biology, and economics. Positivity (are all terms of the given LRS non-negative?) and Ultimate Positivity (are all but finitely many terms of the given LRS non-negative?) ar

Davide Vadacchino

One of the most direct predictions of QCD is the existence of color-singlet states called Glueballs, which emerge as a consequence of the gluon field self-interactions. Despite the outstanding success of QCD as a theory of the strong interaction and decades of experimental and theoretical efforts, all but the most basic properties of Glueballs are still bein

Hezhen Hu, Weichao Zhao, Wengang Zhou, Houqiang Li

Hand gesture serves as a crucial role during the expression of sign language. Current deep learning based methods for sign language understanding (SLU) are prone to over-fitting due to insufficient sign data resource and suffer limited interpretability. In this paper, we propose the first self-supervised pre-trainable SignBERT+ framework with model-aware han

Anajak Phonchantuek, Pichet Vanichchapongjaroen

In this paper, we present double dimensional reduction of the complete M5-brane action in the Sen formalism of self-dual form. Although in this formalism the gravity couples to the independent pseudo-$2$-form and pseudo-$3$-form fields in a non-standard and very complicated way, the double dimensional reduction on the complete action can be carried out. This

Paweł Dłotko, Jan Felix Senge, Anastasios Stefanou

Mutations of genetic sequences are often accompanied by their recombinations, known as phylogenetic networks. These networks are typically reconstructed from coalescent processes that may arise from optimal merging or fitting together a given set of phylogenetic trees. Nakhleh formulated the phylogenetic network reconstruction problem (PNRP): Given a family

Mingxu Tao, Yansong Feng, Dongyan Zhao

Position embeddings, encoding the positional relationships among tokens in text sequences, make great contributions to modeling local context features in Transformer-based pre-trained language models. However, in Extractive Question Answering, position embeddings trained with instances of varied context lengths may not perform well as we expect. Since the em

Souvick Ghosh, Satanu Ghosh, Chirag Shah

Conversational search systems can improve user experience in digital libraries by facilitating a natural and intuitive way to interact with library content. However, most conversational search systems are limited to performing simple tasks and controlling smart devices. Therefore, there is a need for systems that can accurately understand the user's informat

F. Coppini, P. M. Santini

The Ablowitz-Ladik equations, hereafter called $AL_+$ and $AL_-$, are distinguished integrable discretizations of respectively the focusing and defocusing nonlinear Schr\"odinger (NLS) equations. In this paper we first study the modulation instability of the homogeneous background solutions of $AL_{\pm}$ in the periodic setting, showing in particular that th

Andrei Potapov, Mikhail Kurenkov, Pavel Karpyshev, Evgeny Yudin

Visual localization is a fundamental task for a wide range of applications in the field of robotics. Yet, it is still a complex problem with no universal solution, and the existing approaches are difficult to scale: most state-of-the-art solutions are unable to provide accurate localization without a significant amount of storage space. We propose a hierarch

Jan Wingenbach, Stefan Schumacher, Xuekai Ma

Exceptional points (EPs) with their intriguing spectral topology have attracted considerable attention in a broad range of physical systems, with potential sensing applications driving much of the present research in this field. Here we theoretically demonstrate the realization of EPs in a system with significant nonlinearity, a non-equilibrium exciton-polar

Sergii Grytsiuk, Mikhail I. Katsnelson, Erik G. C. P. van Loon, Malte Rösner

The Hubbard model provides an idealized description of electronic correlations in solids. Despite its simplicity, the model features a competition between several different phases that have made it one of the most studied systems in theoretical physics. Real materials usually deviate from the ideal of the Hubbard model in several ways, but the monolayer of N

Fabian Retkowski

With the explosive growth of textual information, summarization systems have become increasingly important. This work aims to concisely indicate the current state of the art in abstractive text summarization. As part of this, we outline the current paradigm shifts towards pre-trained encoder-decoder models and large autoregressive language models. Additional

Manuel M. Müller, Henry W. J. Reeve, Timothy I. Cannings, Richard J. Samworth

Given a sample of covariate-response pairs, we consider the subgroup selection problem of identifying a subset of the covariate domain where the regression function exceeds a pre-determined threshold. We introduce a computationally-feasible approach for subgroup selection in the context of multivariate isotonic regression based on martingale tests and multip

Nikolay Zherdev, Mikhail Kurenkov, Kristina Belikova, Dzmitry Tsetserukou

In this paper, we propose a novel approach to wheeled robot navigation through an environment with movable obstacles. A robot exploits knowledge about different obstacle classes and selects the minimally invasive action to perform to clear the path. We trained a convolutional neural network (CNN), so the robot can classify an RGB-D image and decide whether t

Anastasiia Grishina, Max Hort, Leon Moonen

The use of modern Natural Language Processing (NLP) techniques has shown to be beneficial for software engineering tasks, such as vulnerability detection and type inference. However, training deep NLP models requires significant computational resources. This paper explores techniques that aim at achieving the best usage of resources and available information

Erlang Surya, Lutz Warnke, Emily Zhu

We consider two variants of the induced subgraph isomorphism problem for two independent binomial random graphs with constant edge-probabilities p_1,p_2. In particular, (i) we prove a sharp threshold result for the appearance of G_{n,p_1} as an induced subgraph of G_{N,p_2}, (ii) we show two-point concentration of the size of the maximum common induced subgr

Sercan Çıkıntoğlu

Neutron stars might have multipole magnetic fields as implied by recent observations of pulsars. The presence of the quadrupole field might have an effect on the interaction between the disc and the neutron star depending on the location of the inner radius of the disc and the strength of the quadrupole field. For a quadrudipole stellar field, we calculate t

Roland Kuhn, Hernán Melgratti, Emilio Tuosto

Peer-to-peer systems are the most resilient form of distributed computing, but the design of robust protocols for their coordination is difficult. This makes it hard to specify and reason about global behaviour of such systems. This paper presents swarm protocols to specify such systems from a global viewpoint. Swarm protocols are projected to machines, that

Erik Buhmann, Sascha Diefenbacher, Engin Eren, Frank Gaede

Simulating showers of particles in highly-granular detectors is a key frontier in the application of machine learning to particle physics. Achieving high accuracy and speed with generative machine learning models would enable them to augment traditional simulations and alleviate a major computing constraint. This work achieves a major breakthrough in this ta

David Nunez, Malcom Smith, Boris Bellalta

Multi-Access Point Coordination (MAPC) will be a key feature in next generation Wi-Fi 8 networks. MAPC aims to improve the overall network performance by allowing Access Points (APs) to share time, frequency and/or spatial resources in a coordinated way, thus alleviating inter-AP contention and enabling new multi-AP channel access strategies. This paper intr

Markus Diehl, Riccardo Nagar, Peter Ploessl, Frank J. Tackmann

Double parton distributions are the nonperturbative ingredients needed for computing double parton scattering processes in hadron-hadron collisions. They describe a variety of correlations between two partons in a hadron and depend on a large number of variables, including two independent renormalization scales. This makes it challenging to compute their sca

Evgeney Bogatyrev, Ivan Molodetskikh, Dmitriy Vatolin

In recent years, there has been significant interest in Super-Resolution (SR), which focuses on generating a high-resolution image from a low-resolution input. Deep learning-based methods for super-resolution have been particularly popular and have shown impressive results on various benchmarks. However, research indicates that these methods may not perform

Jeremy Costello, Marek Z. Reformat

We apply reinforcement learning techniques to topic modeling by replacing the variational autoencoder in ProdLDA with a continuous action space reinforcement learning policy. We train the system with a policy gradient algorithm REINFORCE. Additionally, we introduced several modifications: modernize the neural network architecture, weight the ELBO loss, use c

Noam Zilberstein, Angelina Saliling, Alexandra Silva

Separation logic's compositionality and local reasoning properties have led to significant advances in scalable static analysis. But program analysis has new challenges -- many programs display computational effects and, orthogonally, static analyzers must handle incorrectness too. We present Outcome Separation Logic (OSL), a program logic that is sound for

Runze Zhang, Robert Black, Debashish Sur, Parisa Karimi

Electrochemical Impedance Spectroscopy (EIS) is a powerful tool for electrochemical analysis; however, its data can be challenging to interpret. Here, we introduce a new open-source tool named AutoEIS that assists EIS analysis by automatically proposing statistically plausible equivalent circuit models (ECMs). AutoEIS does this without requiring an exhaustiv

Yilin Wang, Nan Cao, Teng Zhang, Xuanhua Shi

Optimal margin Distribution Machine (ODM) is a newly proposed statistical learning framework rooting in the novel margin theory, which demonstrates better generalization performance than the traditional large margin based counterparts. Nonetheless, it suffers from the ubiquitous scalability problem regarding both computation time and memory as other kernel m

Shuo Xin, Jie Ren

Scalar field should have no spin angular momentum according to conventional understandings in classical field theory. Yet, recent studies demonstrate the undoubted existence of wave spin endowed by acoustic and elastic longitudinal waves, which are of irrotational curl-free nature without vorticity and can be described by scalar fields. Here, to solve this s

Shengnan An, Zeqi Lin, Qiang Fu, Bei Chen

Compositional generalization--understanding unseen combinations of seen primitives--is an essential reasoning capability in human intelligence. The AI community mainly studies this capability by fine-tuning neural networks on lots of training samples, while it is still unclear whether and how in-context learning--the prevailing few-shot paradigm based on lar

Junqing Huang, Haihui Wang, Michael Ruzhansky

We present a semi-sparsity model for 3D triangular mesh denoising, which is motivated by the success of semi-sparsity regularization in image processing applications. We demonstrate that such a regularization model can be also applied for graphic processing and gives rise to similar simultaneous-fitting results in preserving sharp features and piece-wise smo

Theodoros E. Kavvathas, George C. Konstantopoulos, Charalambos Konstantinou

In this paper, a novel distributed controller for multimachine power systems is proposed to guarantee grid frequency restoration and accurate real and reactive power sharing among the generator units, while maintaining the generator inputs (mechanical torque and field excitation voltage) within given bounds. The boundedness of the controller outputs (generat

Xiao-Tian Zhang, Yong Hao Gao, Gang Chen

In the recent years, the thermal Hall transport has risen as an important diagnosis of the physical properties of the elementary excitations in various quantum materials, especially among the Mott insulating systems where the electronic transports are often featureless. Here we review the recent development of thermal Hall effects in quantum magnets where al

Sudipta Das

A viable approach towards Quantum Gravity is the Doubly Special Relativity (DSR) framework in which an observer-independent finite energy upper bound (or a finite smallest length scale) appears quite naturally. In this work, we have studied the thermodynamic properties of an ideal gas in a specific DSR framework, known as the Magueijo-Smolin (MS) Model. We u

Zenan Xu, Xiaojun Meng, Yasheng Wang, Qinliang Su

Multimodal abstractive summarization for videos (MAS) requires generating a concise textual summary to describe the highlights of a video according to multimodal resources, in our case, the video content and its transcript. Inspired by the success of the large-scale generative pre-trained language model (GPLM) in generating high-quality textual content (e.g.

M. A. Cordiner, N. X. Roth, S. N. Milam, G. Villanueva

Gas-phase molecules in cometary atmospheres (comae) originate primarily from (1) outgassing by the nucleus, (2) sublimation of icy grains in the near-nucleus coma, and (3) coma (photo-)chemical processes. However, the majority of cometary gases observed at radio wavelengths have yet to be mapped, so their production/release mechanisms remain uncertain. Here

Hao-Ning Wu, Xiaoming Yuan

We present a novel spectral method for the Allen-Cahn equation on spheres, eliminating the reliance on conventional quadrature exactness conditions. By replacing these conditions with a restricted isometry relation derived from Marcinkiewicz--Zygmund quadrature systems, our method achieves precise control over quadrature errors for polynomial integrands. Thi

Yulai Zhao, Zhuoran Yang, Zhaoran Wang, Jason D. Lee

Policy optimization methods with function approximation are widely used in multi-agent reinforcement learning. However, it remains elusive how to design such algorithms with statistical guarantees. Leveraging a multi-agent performance difference lemma that characterizes the landscape of multi-agent policy optimization, we find that the localized action value

Aristotelis Panagiotopoulos, George Sparling, Marios Christodoulou

The quest for complete observables in general relativity has been a longstanding open problem. We employ methods from descriptive set theory to show that no complete observable on rich enough collections of spacetimes is Borel definable. In fact, we show that it is consistent with the Zermelo-Fraenkel and Dependent Choice axioms that no complete observable f

Andrew Mitchell

We consider word complexity and topological entropy for random substitution subshifts. In contrast to previous work, we do not assume that the underlying random substitution is compatible. We show that the subshift of a primitive random substitution has zero topological entropy if and only if it can be obtained as the subshift of a deterministic substitution

Xuehao Zhou, Mingyang Zhang, Yi Zhou, Zhizheng Wu

This paper presents an accented text-to-speech (TTS) synthesis framework with limited training data. We study two aspects concerning accent rendering: phonetic (phoneme difference) and prosodic (pitch pattern and phoneme duration) variations. The proposed accented TTS framework consists of two models: an accented front-end for grapheme-to-phoneme (G2P) conve

Arthur Blanc-Renaudie

We study the random directed graph $\vec G(n,p)$ in which each of the $n(n-1)$ possible directed edges are present with probability $p$. We show that in the critical window the longest self avoiding oriented paths in $\vec G(n,p)$ have length $O_{\mathbb{P}}(n^{1/3})$ so $\vec G(n,p)$ has diameter $O_{\mathbb{P}}(n^{1/3})$.

J. O. Gonzalez-Hernandez, Jonathan Marino, Ted Rogers, Brandon Velasco

We use Monte Carlo techniques to simulate an organized prediction competition between a group of a scientific experts acting under the influence of a ``self-governing'' prediction reward algorithm. Our aim is to illustrate the advantages of a specific type of reward distribution rule that is designed to address some of the limitations of traditional forecast

Lukas Lundgren, Murtazo Nazarov

This paper introduces a formulation of the variable density incompressible Navier-Stokes equations by modifying the nonlinear terms in a consistent way. For Galerkin discretizations, the formulation leads to full discrete conservation of mass, squared density, momentum, angular momentum and kinetic energy without the divergence-free constraint being strongly

Ning Bian, Hongyu Lin, Peilin Liu, Yaojie Lu

Social cognitive theory explains how people learn and acquire knowledge through observing others. Recent years have witnessed the rapid development of large language models (LLMs), which suggests their potential significance as agents in the society. LLMs, as AI agents, can observe external information, which shapes their cognition and behaviors. However, th

Tasmeen Zaman Ornee, Yin Sun

We study a sampling and transmission scheduling problem for multi-source remote estimation, where a scheduler determines when to take samples from multiple continuous-time Gauss-Markov processes and send the samples over multiple channels to remote estimators. The sample transmission times are i.i.d. across samples and channels. The objective of the schedule

Weiqi Wang, Tianqing Fang, Baixuan Xu, Chun Yi Louis Bo

Commonsense reasoning, aiming at endowing machines with a human-like ability to make situational presumptions, is extremely challenging to generalize. For someone who barely knows about "meditation," while is knowledgeable about "singing," he can still infer that "meditation makes people relaxed" from the existing knowledge that "singing makes people relaxed

Maximilian Balthasar Mansky, Victor Ramos Puigvert, Santiago Londoño Castillo, Claudia Linnhoff-Popien

We review the staircase algorithm to decompose the exponential of a generalized Pauli matrix and we propose two alternative recursive methods which offer more efficient quantum circuits. The first algorithm we propose, defined as the inverted staircase algorithm, is more efficient in comparison to the standard staircase algorithm in the number of one-qubit g

Michael J. Larsen, Pham Huu Tiep

We extend to alternating groups $A_n$ several results about symmetric groups asserting that under various conditions on a conjugacy class, or more generally, a normal subset, $C$ of $S_n$, we have $C^2 \supseteq A_n\setminus\{1\}$

Angela A. Albanese, José Bonet, Werner J. Ricker

The generalized Ces\`aro operators $C_t$, for $t\in [0,1]$, were first investigated in the 1980's. They act continuously in many classical Banach sequence spaces contained in $\mathbb{C}^{\mathbb{N}_0}$, such as $\ell^p$, $c_0$, $c$, $bv_0$, $bv$ and, as recently shown, \cite{CR4}, also in the discrete Ces\`aro spaces $ces(p)$ and their (isomorphic) dual spa

Erfan Momeni Yazdi, Markku Mäkitalo, Julius Ikkala, Pekka Jääskeläinen

Many graphics rendering algorithms used in both real-time games and virtual reality applications can get performance boosts by temporally reusing previous computations. However, algorithms based on temporal reuse are typically measured using trivial benchmarks with very limited dynamic features. To this end, in [1] we presented TauBench 1.0, a benchmark desi

Bachir Bekka

Let $G= N\rtimes H$ be a locally compact group which is a semi-direct product of a closed normal subgroup $N$ and a closed subgroup $H.$ The Bohr compactification ${\rm Bohr}(G)$ and the profinite completion ${\rm Prof}(G)$ of $G$ are, respectively, isomorphic to semi-direct products $ Q_1 \rtimes {\rm Bohr}(H)$ and $ Q_2 \rtimes {\rm Prof}(H)$ for appropria

R. Merlin

The classical motion of a one-dimensional chain of atoms coupled through a specific force function that depends on position shows features very similar to the Wannier-Stark problem of a quantum particle under the combined effects of a periodic lattice potential and a constant electric field. Both problems exhibit localized modes and a ladder of equally-space

Kiril Bangachev, Guy Bresler

A random algebraic graph is defined by a group $G$ with a uniform distribution over it and a connection $\sigma:G\longrightarrow[0,1]$ with expectation $p,$ satisfying $\sigma(g)=\sigma(g^{-1}).$ The random graph $\mathsf{RAG}(n,G,p,\sigma)$ with vertex set $[n]$ is formed as follows. First, $n$ independent vectors $x_1,\ldots,x_n$ are sampled uniformly from

Wei Li, Xiangxu Meng, Chuhao Chen, Jianing Chen

Recently, significant advancements have been made in time-series forecasting research, with an increasing focus on analyzing the nature of time-series data, e.g, channel-independence (CI) and channel-dependence (CD), rather than solely focusing on designing sophisticated forecasting models. However, current research has primarily focused on either CI or CD i

Sanjay Kumar, Stanzin Dolkar

In this paper, we study the bicomplex version of the Paley-Weiner theorem and the Cauchy integral formula in the upper half-plane.

Takumi Ohmura, Katsuaki Asano, Kosuke Nishiwaki, Mami Machida

We present magnetohydrodynamic simulations of a jet-wind interaction in a galaxy cluster and the radio to gamma-ray and the neutrino emissions from this "head-tail galaxy". Our simulation follows the evolution of cosmic-ray (CR) particle spectra with energy losses and the stochastic turbulence acceleration. We find that the reacceleration is essential to exp

Hunter McNichols, Mengxue Zhang, Andrew Lan

Automated feedback as students answer open-ended math questions has significant potential in improving learning outcomes at large scale. A key part of automated feedback systems is an error classification component, which identifies student errors and enables appropriate, predefined feedback to be deployed. Most existing approaches to error classification us

Daniel A. Ramras

Given a locally finite cover of a simplicial complex by subcomplexes, Bj\"orner's version of the Nerve Theorem provides conditions under which the homotopy groups of the nerve agree with those of the original complex through a range of dimensions. We extend this result to covers of CW complexes by subcomplexes and to open covers of arbitrary topological spac

Martin Gruber, Gordon Fraser

Flaky tests obstruct software development, and studying and proposing mitigations against them has therefore become an important focus of software engineering research. To conduct sound investigations on test flakiness, it is crucial to have large, diverse, and unbiased datasets of flaky tests. A common method to build such datasets is by rerunning the test

Sai Aparna Aketi, Abolfazl Hashemi, Kaushik Roy

Decentralized learning enables the training of deep learning models over large distributed datasets generated at different locations, without the need for a central server. However, in practical scenarios, the data distribution across these devices can be significantly different, leading to a degradation in model performance. In this paper, we focus on desig

Edgar Assing

In this note we prove Sarnak's (spherical) density hypothesis for the full discrete spectrum of the quotients $\Gamma_{\textrm{pa}}(q)\backslash \textrm{Sp}_4(\mathbb{R})$, where $\Gamma_{\textrm{pa}}(q)$ are paramodular groups with square-free level $q$. To derive this estimate we upgrade a density estimate established via the (pre)-Kuznetsov formula, which

Tao Gong, Chengqi Lyu, Shilong Zhang, Yudong Wang

We present a vision and language model named MultiModal-GPT to conduct multi-round dialogue with humans. MultiModal-GPT can follow various instructions from humans, such as generating a detailed caption, counting the number of interested objects, and answering general questions from users. MultiModal-GPT is parameter-efficiently fine-tuned from OpenFlamingo,

Zerong Zheng, Xiaochen Zhao, Hongwen Zhang, Boning Liu

We present AvatarReX, a new method for learning NeRF-based full-body avatars from video data. The learnt avatar not only provides expressive control of the body, hands and the face together, but also supports real-time animation and rendering. To this end, we propose a compositional avatar representation, where the body, hands and the face are separately mod