February 2024 arXiv papers — page 32

Michal Wrona

Every CSP(B) for a finite structure B is either in P or it is NP-complete but the proofs of the finite-domain CSP dichotomy by Andrei Bulatov and Dimitryi Zhuk not only show the computational complexity separation but also confirm the algebraic tractability conjecture stating that tractability origins from a certain system of operations preserving B. The est

Tristan Kenneweg, Philip Kenneweg, Barbara Hammer

Retrieval Augmented Generation (RAG) systems have seen huge popularity in augmenting Large-Language Model (LLM) outputs with domain specific and time sensitive data. Very recently a shift is happening from simple RAG setups that query a vector database for additional information with every user input to more sophisticated forms of RAG. However, different con

Naicheng Guo, Hongwei Cheng, Qianqiao Liang, Linxun Chen

With the rapid development of Large Language Models (LLMs), various explorations have arisen to utilize LLMs capability of context understanding on recommender systems. While pioneering strategies have primarily transformed traditional recommendation tasks into challenges of natural language generation, there has been a relative scarcity of exploration in th

Thomas Dohmen, Georgios Gerasimou

We ask if participants in a choice experiment with repeated presentation of the same menus and no feedback provision: (i) exhibit overall behaviour that is consistent with ordinal and expected utility theory under *weak* preferences; (ii) become more consistent with the predictions of these theories under *strict* preferences.To answer these questions we des

Clement Mawby

I study several aspects of tests of macrorealism (MR), which for a given data set serves to give a quantitative signal of the presence of a specific notion of non-classical behaviour. The insufficiency of classical understanding underpins both the paradoxes of quantum mechanics, its future technological promise, and so these tests are of interest both founda

Bowei Tu

We consider the Cauchy problem of the three-dimensional parabolic-elliptic Patlak-Keller-Segel chemotactic model. The initial data is almost a Dirac measure supported on a straight line with mass less than $8\pi$. We prove that if the data is sufficiently close to the straight line, then global well-posedness holds. This result is parallel to the work on vor

Ilane Schroetter, Olivier Berné, Christine Joblin, Amélie Canin

Aromatic infrared bands (AIBs) are a set of broad emission bands at 3.3, 6.2, 7.7, 8.6, 11.2, and 12.7 $\mu$m, seen in the infrared spectra of most galaxies. With JWST, the 3.3 $\mu$m AIB can in principle be detected up to a redshift of $\sim$ 7. Relating the evolution of the 3.3 $\mu$m AIB to local physical properties of the ISM is thus of paramount importa

Hector Gramaglia

Computational interpretations of linear logic allow static control of memory resources: the data produced by the program are endowed through its type with attributes that determine its life cycle. This has promoted numerous investigations into safe introduction of in-place update. Various type systems have been proposed for this aim, but the memory managemen

Chad Henshaw, Megan Arogeti, Alice Heranval, Laura Cadonati

The gravitational wave signals produced by the coalescence of compact binaries progress through three stages: inspiral, merger, and postmerger. The evolution of their frequency follows a slow build up during the inspiral that peaks at merger, forming the characteristic "chirp" pattern in the signal's time-frequency map. Herein we introduce a framework for lo

Tianyu Zhang, Chengbin Hou, Rui Jiang, Xuegong Zhang

Node Importance Estimation (NIE) is a task of inferring importance scores of the nodes in a graph. Due to the availability of richer data and knowledge, recent research interests of NIE have been dedicating to knowledge graphs for predicting future or missing node importance scores. Existing state-of-the-art NIE methods train the model by available labels, a

Juho Hirvonen, Sara Ranjbaran

Stable matching is a fundamental problem studied both in economics and computer science. The task is to find a matching between two sides of agents that have preferences over who they want to be matched with. A matching is stable if no pair of agents prefer each other over their current matches. The deferred acceptance algorithm of Gale and Shapley solves th

Saak Gabriyelyan

In 1953, Grothendieck introduced and studied the Dunford--Pettis property (the $DP$ property) and the strict Dunford--Pettis property (the strict $DP$ property). The $DP$ property of order $p\in[1,\infty]$ for Banach spaces was introduced by Castillo and Sanchez in 1993. Being motivated by these notions, for $p,q\in[1,\infty]$, we define the strict Dunford--

Matúš Benko, Patrick Mehlitz

As a starting point of our research, we show that, for a fixed order $\gamma\geq 1$, each local minimizer of a rather general nonsmooth optimization problem in Euclidean spaces is either M-stationary in the classical sense (corresponding to stationarity of order $1$), satisfies stationarity conditions in terms of a coderivative construction of order $\gamma$

Saltanat Kenzhebayeva, Saken Toktarbay, Arman Tursunov, Martin Kološ

Magnetic fields surrounding black holes are responsible for various astrophysical phenomena related to accretion processes and relativistic jets. Depending on the source, the configuration of the field lines may differ significantly, affecting the trajectories of charged particles and the corresponding observables. Usually, the magnetic fields around black h

Ruoyu P. T. Wang

This expository note, written for the proceedings of ICCM 2023, presents recent work [arXiv:2004.13894]. We particularly prove an Carleman estimate on conic manifolds, using a multiple-weight Carleman argument.

Nanfang Jiao, Shupei Lin, Delong Feng, Yong He

Direct optical detection and imaging of single nanoparticles on substrate in wide field underpin vast applications across different research fields. However, the speckles originating from the unavoidable random surface undulations of the substrate ultimately limit the size of the decipherable nanoparticles by the current optical techniques, including the ult

S. Bagnulo, J. Farihi, J. D. Landstreet, C. Folsom

Dynamically active planetary systems orbit a significant fraction of white dwarf stars. These stars often exhibit surface metals accreted from debris disks, which are detected through infrared excess or transiting structures. However, the full journey of a planetesimal from star-grazing orbit to final dissolution in the host star is poorly understood. Here,

Franco Flandoli, Marco Rehmeier

This note is devoted to a discussion of the potential links and differences between three topics: regularization by noise, convex integration, spontaneous stochasticity. All of them deal with the effect on large scales of a small-scale perturbation of fluid dynamic equations. The effects sometimes have something in common, like convex integration and spontan

Or Hadas, Yohai Kaspi

Extratropical storms dominate midlatitude climate and weather and are known to grow baroclinicaly and decay barotropicaly. Traditionally, quantitative climatic measures of storm growth have been mostly based on Eulerian measures, taking into account the mean state of the atmosphere and how those affect eddy growth, but they do not consider the Lagrangian gro

J. Möser, H. Popli, T. H. Tennahewa, T. Biktagirov

Paramagnetic point defects in silicon provide qubits that could open up pathways towards silicon-technology based, low-cost, room-temperature (RT) quantum sensing. The silicon dangling bond (db) is a natural candidate, given its sub-nanometer localization and direct involvement in spin-dependent charge-carrier recombination, allowing for electrical spin read

Jifa Jiang, Jian Wang, Jianliang Zhai, Tusheng Zhang

In this paper, we first provide a criterion on uniform large deviation principles (ULDP) of stochastic differential equations under Lyapunov conditions on the coefficients, which can be applied to stochastic systems with coefficients of polynomial growth and possible degenerate driving noises. In the second part, using the ULDP criterion we preclude the conc

Linxuan Song, Feng Zhou, Hang Li, Bei Ding

The recent discoveries of surperisingly large anomalous Hall effect in chiral antiderromagnets have triggered extensive research efforts in various fields, ranging from topological condensed-matter physics to antiferromagnetic spintronics, and energy harvesting technology. However, such AHE-hosting antiferromagnetic materials are rare in nature. Herein, we d

Paul Lartaud, Philippe Humbert, Josselin Garnier

Sequential design is a highly active field of research in active learning which provides a general framework for designing computer experiments with limited computational budgets. It aims to create efficient surrogate models to replace complex computer codes. Some sequential design strategies can be understood within the Stepwise Uncertainty Reduction (SUR)

Ulrich J. Lorenz

Microsecond time-resolved cryo-electron microscopy has emerged as a novel approach for directly observing proteins dynamics. By providing microsecond temporal and near-atomic spatial resolution, it has the potential to elucidate a wide range of dynamics that were previously inaccessible and therefore, to significantly advance our understanding of protein fun

Kacper Koteras, Sebastian Biesenkamp, Paolo Barone, Zoran Mazej

The crystal structure of KAgF3 was studied by powder neutron diffraction. KAgF3 exhibits at all temperatures an orthorhombic symmetry in space group Pnma that allows for several distortions with respect to the ideal cubic perovskite structure. At all temperatures there is a strong splitting of Ag-F distances parallel to the a,c planes that documents alternat

Matteo Caldana, Paola F. Antonietti, Luca Dede'

Finite element-based high-order solvers of conservation laws offer large accuracy but face challenges near discontinuities due to the Gibbs phenomenon. Artificial viscosity is a popular and effective solution to this problem based on physical insight. In this work, we present a physics-informed machine learning algorithm to automate the discovery of artifici

Zhiding Liu, Jiqian Yang, Mingyue Cheng, Yucong Luo

Recent efforts have been dedicated to enhancing time series forecasting accuracy by introducing advanced network architectures and self-supervised pretraining strategies. Nevertheless, existing approaches still exhibit two critical drawbacks. Firstly, these methods often rely on a single dataset for training, limiting the model's generalizability due to the

Katarína Osvaldová, Lukáš Gajdošech, Viktor Kocur, Martin Madaras

The goal of this paper is to assess the impact of noise in 3D camera-captured data by modeling the noise of the imaging process and applying it on synthetic training data. We compiled a dataset of specifically constructed scenes to obtain a noise model. We specifically model lateral noise, affecting the position of captured points in the image plane, and axi

Yong Zheng, Rongbo Wu, Yuan Ren, Rui Bao

Photonic neural networks (PNNs) have emerged as a promising platform to address the energy consumption issue that comes with the advancement of artificial intelligence technology, and thin film lithium niobate (TFLN) offers an attractive solution as a material platform mainly for its combined characteristics of low optical loss and large electro-optic (EO) c

Shakul Awasthi, Sreedhar B. Dutta

Periodically driven thermodynamic systems support stable non-equilibrium oscillating states with properties drastically different from equilibrium. They exhibit even more exotic features for low viscous drives, which is a regime that is hard to probe due to singular behavior of the underlying Langevin dynamics near vanishing viscosity. We propose a method, b

Renato Huzak, Hildeberto Jardón-Kojakhmetov, Christian Kuehn

In this paper, we study ergodic properties of the slow relation function (or entry-exit function) in planar slow-fast systems. It is well known that zeros of the slow divergence integral associated with canard limit periodic sets give candidates for limit cycles. We present a new approach to detect the zeros of the slow divergence integral by studying the st

Arvind Arun Dev, Florencia Sacarelli, G Bagheri, Aleena Joseph

Ferrofluids kept in place by permanent magnet quadrupoles can act as liquid walls to surround a second non-magnetic inside, resulting in a liquid fluidic channel with diameter size ranging from mm down to less than 10 micrometer. Micro particle tracking velocimetry (micro PTV) experiments and modeling show that near ideal plug flow is possible in such liquid

Huy N. Chau, Duy Nguyen, Thai Nguyen

This paper investigates short-term behaviors of implied volatility of derivatives written on indexes in equity markets when the index processes are constructed by using a ranking procedure. Even in simple market settings where stock prices follow geometric Brownian motion dynamics, the ranking mechanism can produce the observed term structure of at-the-money

Georg Pichler, Marco Romanelli, Divya Prakash Manivannan, Prashanth Krishnamurthy

We introduce a formal statistical definition for the problem of backdoor detection in machine learning systems and use it to analyze the feasibility of such problems, providing evidence for the utility and applicability of our definition. The main contributions of this work are an impossibility result and an achievability result for backdoor detection. We sh

Fan Jiang, Tom Drummond, Trevor Cohn

Cross-lingual open domain question answering (CLQA) is a complex problem, comprising cross-lingual retrieval from a multilingual knowledge base, followed by answer generation in the query language. Both steps are usually tackled by separate models, requiring substantial annotated datasets, and typically auxiliary resources, like machine translation systems t

Yu. L. Bolotin, V. V. Yanovsky

The cosmographic approach is used to determine the parameters of the Barrow entropic dark energy model. The model parameters are expressed through the current kinematic characteristics of Universe expansion.

Juyeon Ko, Inho Kong, Dogyun Park, Hyunwoo J. Kim

Semantic image synthesis (SIS) is a task to generate realistic images corresponding to semantic maps (labels). However, in real-world applications, SIS often encounters noisy user inputs. To address this, we propose Stochastic Conditional Diffusion Model (SCDM), which is a robust conditional diffusion model that features novel forward and generation processe

Markus Bibinger, Nikolaus Hautsch, Alexander Ristig

We propose methods to infer jumps of a semi-martingale, which describes long-term price dynamics, based on discrete, noisy, high-frequency observations. Different to the classical model of additive, centered market microstructure noise, we consider one-sided microstructure noise for order prices in a limit order book. We develop methods to estimate, locate a

Jean-Marie Chauvet

The Tulving Test was designed to investigate memory performance in recognition and recall tasks. Its results help assess the relevance of the "Synergistic Ecphory Model" of memory and similar RK paradigms in human performance. This paper starts investigating whether the more than forty-year-old framework sheds some light on LLMs' acts of remembering.

Maxim Lyutikov

We provide an overview of various mechanisms, and corresponding powers, of precursor emission to compacts' mergers to be detected by LIGO-Virgo-KAGRA (LVK) collaboration. Expected peak powers, $\leq 10^{43}$ erg s$^{-1}$, are not sufficiently high to be detected by all-sky high-energy satellites (unless beamed). The best chance is the detection of possible c

Dipankar Chakrabarti, Poonam Choudhary, Bheemsehan Gurjar, Tanmay Maji

Using a recently developed light-front spectator model that incorporates gluon, where the light-front wave functions are modeled from the soft-wall AdS/QCD prediction, we examine the leading twist gluon generalized parton distributions (GPDs) inside the proton. We derive the chirally even and odd distributions by using the overlap representation of the light

Shweta Sharma, Praveen C. Srivastava

In the present work, beta-decay properties such as $\log ft$ values and half-lives have been systematically studied corresponding to Ba isotopes using large-scale shell-model calculations. An extensive comparison of beta decay results corresponding to $^{141}$Ba$\rightarrow$ $^{141}$La using shell-model calculations is made with the recently available experi

Zhenning Li, Hao Yu

Predicting the trajectories of surrounding agents is still considered one of the most challenging tasks for autonomous driving. In this paper, we introduce a multi-modal trajectory prediction framework based on the transformer network. The semantic maps of each agent are used as inputs to convolutional networks to automatically derive relevant contextual inf

Jiaohong Shu, Xinxin Zhao, Weiqin Fan, Lili Wang

We establish the map between symmetries and orbital rules to realize tunable band gap in quantum anomalous Hall effect material. This band gap is determined by the SOC between local orbitals associated with band crossing, which is constrained by at least one of lattice symmetries. The band gap could be turned on/off by breaking or keeping corresponding latti

David Hartmann, José Renato Laranjeira de Pereira, Chiara Streitbörger, Bettina Berendt

The European legislature has proposed the Digital Services Act (DSA) and Artificial Intelligence Act (AIA) to regulate platforms and Artificial Intelligence (AI) products. We review to what extent third-party audits are part of both laws and how is access to information on models and the data provided. By considering the value of third-party audits and third

Junzhe Chen, Xuming Hu, Shuodi Liu, Shiyu Huang

Recent advancements in large language models (LLMs) have revealed their potential for achieving autonomous agents possessing human-level intelligence. However, existing benchmarks for evaluating LLM Agents either use static datasets, potentially leading to data leakage or focus only on single-agent scenarios, overlooking the complexities of multi-agent inter

A. Albert, S. Alves, M. André, M. Ardid

High-energy neutrinos could be produced in the interaction of charged cosmic rays with matter or radiation surrounding astrophysical sources. To look for transient sources associated with neutrino emission, a follow-up program of neutrino alerts has been operating within the ANTARES Collaboration since 2009. This program, named TAToO, has triggered robotic o

Ziqiao Kong, Shaohua Li, Heqing Huang, Zhendong Su

Sanitizers provide robust test oracles for various software vulnerabilities. Fuzzing on sanitizer-enabled programs has been the best practice to find software bugs. Since sanitizers need to heavily instrument a target program to insert run-time checks, sanitizer-enabled programs have much higher overhead compared to normally built programs. In this paper, we

Nicolas Huynh, Jeroen Berrevoets, Nabeel Seedat, Jonathan Crabbé

Identification and appropriate handling of inconsistencies in data at deployment time is crucial to reliably use machine learning models. While recent data-centric methods are able to identify such inconsistencies with respect to the training set, they suffer from two key limitations: (1) suboptimality in settings where features exhibit statistical independe

Mohammad R. Garousi

In this study, we thoroughly investigate the covariant and $B$-field gauge invariant odd-parity NS-NS couplings at order $\alpha'^3$, while considering the removal of field redefinitions, Bianchi identities, and total derivative freedoms. Our comprehensive analysis reveals the existence of 477 independent couplings. To establish a specific basis, we construc

Anusuiya Baishya, Apurba Das

The notion of a matched pair of Lie algebras was introduced in the study of Lie bialgebras and Poisson-Lie groups. In this paper, we introduce representations and cohomology of a matched pair of Lie algebras. We show that there is a morphism from the cohomology of a Lie bialgebra to the cohomology of the corresponding matched pair of Lie algebras. Our cohomo

Niklas Kueper, Su Kyoung Kim, Elsa Andrea Kirchner

Background: For an individualized support of patients during rehabilitation, learning of individual machine learning models from the human electroencephalogram (EEG) is required. Our approach allows labeled training data to be recorded without the need for a specific training session. For this, the planned exoskeleton-assisted rehabilitation enables bilatera

Bo-Yong Chen, John Erik Fornæss, Jujie Wu

We study the density of functions which are holomorphic in a neighbourhood of the closure $\overline{\Omega}$ of a bounded non-smooth pseudoconvex domain $\Omega$, in the Bergman space $ H^2(\Omega ,\varphi)$ with a plurisubharmonic weight $\varphi$. As an application, we show that the Hartogs domain $$ \Omega _\alpha : = \{(z,w) \in D\times \C: |w|< \delta^

Zhefei Tian, Guang Zhao, Linghui Wu, Zhenyu Zhang

The particle identification (PID) of hadrons plays a crucial role in particle physics experiments, especially in flavor physics and jet tagging. The cluster-counting method, which measures the number of primary ionizations in gaseous detectors, is a promising breakthrough in PID. However, developing an effective reconstruction algorithm for cluster counting

Mengbang Zou, Weisi Guo, Bailu Jin

Strong structural controllability (SSC) guarantees networked system with linear-invariant dynamics controllable for all numerical realizations of parameters. Current research has established algebraic and graph-theoretic conditions of SSC for zero/nonzero or zero/nonzero/arbitrary structure. One relevant practical problem is how to fully control the system w

Pierre Béjot

In this article, we present an efficient numerical model able to solve the vectorial nonlinear pulse propagation equation in circularly symmetric multimode waveguides. The algorithm takes advantage of the conservation of total angular momentum of light upon propagation and takes into account the vectorial nature of the propagating modes, making it particular

Tapender, Surender Verma, Sanjeev Kumar

We examine the Scotogenic model employing the TM$_2$ mixing matrix, $U_{\text{TM}_2}$, for neutrinos and parameterize the Yukawa coupling matrix $y$ based on the diagonalization condition for the neutrino mass matrix, $m_{\nu}$. Our investigation centers on analyzing the relic density of cold dark matter ($\Omega h^2$) and possible lepton flavor violation (L

Marco Bochicchio, Elisabetta Pallante

We revisit a low-energy theorem (LET) of NSVZ type in SU($N$) QCD with $N_f$ massless quarks derived in [1] by implementing it in dimensional regularization. The LET relates $n$-point correlators in the lhs to $n+1$-point correlators with the extra insertion of Tr$F^2$ at zero momentum in the rhs. First, we demonstrate that, for $2$-point correlators of an o

Yuxia Guo, Shengyu Wu, TingFeng Yuan

We consider the following elliptic system with Neumann boundary: \begin{equation} \begin{cases} -\Delta u + \mu u=v^p, &\hbox{in } \Omega, \\-\Delta v + \mu v=u^q, &\hbox{in } \Omega, \\\frac{\partial u}{\partial n} = \frac{\partial v}{\partial n} = 0, &\hbox{on } \partial\Omega, \\u>0,v>0, &\hbox{in } \Omega, \end{cases} \end{equation} where $\Omega \subset

Antonio David Bastida Zamora, Ljubomir Budinski, Ossi Niemimäki, Valtteri Lahtinen

This study presents a novel quantum algorithm for lattice gas automata simulation with a single time step, demonstrating logarithmic complexity in terms of $CX$ gates. The algorithm is composed of three main steps: collision, mapping, and propagation. A computational complexity analysis and a comparison using different error rates and number of shots are pro

José Carlos Bellido, Carlos Mora-Corral, Hidde Schönberger

We address the study of nonlocal gradients defined through general radial kernels $\rho$. Our investigation focuses on the properties of the associated function spaces, which depend on the characteristics of the kernel function. Specifically, even with minimal assumptions on $\rho$, we establish Poincar\'e inequalities and compact embeddings into Lebesgue sp

Ahmad Saeed, Haasha Bin Atif, Usman Habib, Mohsin Bilal

Precise aircraft recognition in low-resolution remote sensing imagery is a challenging yet crucial task in aviation, especially combat identification. This research addresses this problem with a novel, scalable, and AI-driven solution. The primary hurdle in combat identification in remote sensing imagery is the accurate recognition of Novel/Unknown types of

Ana-Maria Acu, Heiner Gonska

Extending an earlier estimate for the degree of approximation of overiterated univariate Bernstein operators towards the same operator of degree one, it is shown that an analogous result holds in the $d$-variate case. The method employed can be carried over to many other cases and is not restricted to Bernstein-type or similar methods.

Shunichiro Kinoshita

It has been known that warped-product spacetimes such as spherically symmetric ones admit the Kodama vector. This vector provides a locally conserved current made by contraction of the Einstein tensor, even though there is no Killing vector. In addition, a quasilocal mass, Birkhoff's theorem and various properties are closely related to the Kodama vector. Re

Nikos G. Evgenidis, Nikos A. Mitsiou, Vasiliki I. Koutsioumpa, Sotiris A. Tegos

This paper focuses on the latest research and innovations in fundamental next-generation multiple access (NGMA) techniques and the coexistence with other key technologies for the sixth generation (6G) of wireless networks. In more detail, we first examine multi-access edge computing (MEC), which is critical to meeting the growing demand for data processing a

Nils W. Schween, Brian Reville

The transport of charged particles or photons in a scattering medium can be modelled with a Boltzmann equation. The mathematical treatment for scattering in such scenarios is often simplified if evaluated in a frame where the scattering centres are, on average, at rest. It is common therefore, to use a mixed coordinate system, wherein space and time are meas

Han Liu, Liantang Li

Language model intelligence is revolutionizing the way we program materials simulations. However, the diversity of simulation scenarios renders it challenging to precisely transform human language into a tailored simulator. Here, using three functionalized types of language model, we propose a language-to-simulation (Lang2Sim) framework that enables interact

A Mani

A teacher's knowledge base consists of knowledge of mathematics content, knowledge of student epistemology, and pedagogical knowledge. It has severe implications on the understanding of student's knowledge of content, and the learning context in general. The necessity to formalize the different content knowledge in approximate senses is recognized in the edu

Martin Wahl

Given i.i.d. observations uniformly distributed on a closed manifold $\mathcal{M}\subseteq \mathbb{R}^p$, we study the spectral properties of the associated empirical graph Laplacian based on a Gaussian kernel. Our main results are non-asymptotic error bounds, showing that the eigenvalues and eigenspaces of the empirical graph Laplacian are close to the eige

Rosalia Tufano, Antonio Mastropaolo, Federica Pepe, Ozren Dabić

Large Language Models (LLMs) have gained significant attention in the software engineering community. Nowadays developers have the possibility to exploit these models through industrial-grade tools providing a handy interface toward LLMs, such as OpenAI's ChatGPT. While the potential of LLMs in assisting developers across several tasks has been documented in

Jin Ding, Jie-Chao Zhao, Yong-Zhi Sun, Ping Tan

Deep convolutional neural networks (DCNN for short) are vulnerable to examples with small perturbations. Improving DCNN's robustness is of great significance to the safety-critical applications, such as autonomous driving and industry automation. Inspired by the principal way that human eyes recognize objects, i.e., largely relying on the shape features, thi

Pritha Paul, Chris Clarkson, Roy Maartens

Recent measurements of the 4-point correlation function in large-scale galaxy surveys have found apparent evidence of parity violation in the distribution of galaxies. This cannot happen via dynamical gravitational effects in general relativity. If such a violation arose from physics in the early Universe it could indicate important new physics beyond the st

Emily Beatty, Daniel Stilck França

Optimal transport provides a powerful mathematical framework with applications spanning numerous fields. A cornerstone within this domain is the $p$-Wasserstein distance, which serves to quantify the cost of transporting one probability measure to another. While recent attempts have sought to extend this measure to the realm of quantum states, existing defin

Li-Na Hu, Hong-Hao Fan, Orkash Amat, Suo Tang

Spin effect on the pair production under circularly polarized fields are investigated. Significantly different from what momentum spirals caused by two counter-rotating fields with a time delay, we find for the first time that the spirals can also be induced due to the particles spin effect even if in a single field. We further examine the bichromatic combin

Cécile Bouette, Laura Luzzi, Ligong Wang

We study the fundamental limits of covert communications over general memoryless additive-noise channels. We assume that the legitimate receiver and the eavesdropper share the same channel and therefore see the same outputs. Under mild integrability assumptions, we find a general upper bound on the square-root scaling constant, which only involves the varian

Yannis Papaphilippou

The goal of this contribution is to introduce the Hamiltonian formalism of theoretical mechanics for analysing motion in generic linear and non-linear dynamical systems, including particle accelerators. This framework allows the derivation and integration of equations of motion, in order to describe the particle trajectory evolution with respect to time. Fir

Mahmoud Tahmasebi, Saif Huq, Kevin Meehan, Marion McAfee

We introduce Double Cost Volume Stereo Matching Network(DCVSMNet) which is a novel architecture characterised by by two small upper (group-wise) and lower (norm correlation) cost volumes. Each cost volume is processed separately, and a coupling module is proposed to fuse the geometry information extracted from the upper and lower cost volumes. DCVSMNet is a

Marcin J. Schroeder

The article has as its main objective the identification of fundamental epistemological obstacles in the study of information related to unnecessary methodological assumptions and the demystification of popular beliefs in the fundamental divisions of the aspects of information that can be understood as Bachelardian rupture of epistemological obstacles. These

Vipul Raheja, Dimitris Alikaniotis, Vivek Kulkarni, Bashar Alhafni

We introduce mEdIT, a multi-lingual extension to CoEdIT -- the recent state-of-the-art text editing models for writing assistance. mEdIT models are trained by fine-tuning multi-lingual large, pre-trained language models (LLMs) via instruction tuning. They are designed to take instructions from the user specifying the attributes of the desired text in the for

Bogdan Damski

The Proca theory of the real massive vector field admits non-equilibrium solutions, where the asymptotic dynamics of the electric field is dominated by the periodically oscillating Coulomb component. We discuss how such field configurations are seen in different reference frames, where we find an intriguing spatial pattern of the vector field and the electro

Jorge L. Ocampo-Espindola, István Z. Kiss, Christian Bick, Kyle C. A. Wedgwood

Coupled oscillator networks often display transitions between qualitatively different phase-locked solutions -- such as synchrony and rotating wave solutions -- following perturbation or parameter variation. In the limit of weak coupling, these transitions can be understood in terms of commonly studied phase approximations. As the coupling strength increases

Khai Jiet Liong, Hongqiu Wu, Hai Zhao

Pre-trained language models (PLMs) are shown to be vulnerable to minor word changes, which poses a big threat to real-world systems. While previous studies directly focus on manipulating word inputs, they are limited by their means of generating adversarial samples, lacking generalization to versatile real-world attack. This paper studies the basic structure

Thierry Lecroq

String matching is the problem of finding all the occurrences of a pattern in a text. It has been intensively studied and the Boyer-Moore string matching algorithm is probably one of the most famous solution to this problem. This algorithm uses two precomputed shift tables called the good-suffix table and the bad-character table. The good-suffix table is tri

Ali Bemani, Nassar Ksairi, Marios Kountouris

Integrated sensing and communications (ISAC) is regarded as a key technology in next-generation (6G) mobile communication systems. Affine frequency division multiplexing (AFDM) is a recently proposed waveform that achieves optimal diversity gain in high mobility scenarios and has appealing properties in high-frequency communication. In this letter, we presen

Raphael Patrick Prager, Heike Trautmann

Exploratory landscape analysis and fitness landscape analysis in general have been pivotal in facilitating problem understanding, algorithm design and endeavors such as automated algorithm selection and configuration. These techniques have largely been limited to search spaces of a single domain. In this work, we provide the means to compute exploratory land

Alberto Dennunzio, Enrico Formenti, Luciano Margara, Sara Riva

Endowing the set of functional graphs (FGs) with the sum (disjoint union of graphs) and product (standard direct product on graphs) operations induces on FGs a structure of a commutative semiring R. The operations on R can be naturally extended to the set of univariate polynomials R[X] over R. This paper provides a polynomial time algorithm for deciding if e

Katarzyna Kowalska, Michał Pilipczuk

We study parameterized and approximation algorithms for a variant of Set Cover, where the universe of elements to be covered consists of points in the plane and the sets with which the points should be covered are segments. We call this problem Segment Set Cover. We also consider a relaxation of the problem called $\delta$-extension, where we need to cover t

Chen-Yu Liu, En-Jui Kuo, Chu-Hsuan Abraham Lin, Sean Chen

In recent years, advanced deep neural networks have required a large number of parameters for training. Therefore, finding a method to reduce the number of parameters has become crucial for achieving efficient training. This work proposes a training scheme for classical neural networks (NNs) that utilizes the exponentially large Hilbert space of a quantum sy

Xavier Blot, Alexandr Buryak

The notion of a quantum tau-function for a natural quantization of the KdV hierarchy was introduced in a work of Dubrovin, Gu\'er\'e, Rossi, and the second author. A certain natural choice of a quantum tau-function was then described by the first author, the coefficients of the logarithm of this series are called the quantum intersection numbers. Because of

Yongxin Xu, Shangshang Wang, Hengquan Guo, Xin Liu

Online task scheduling serves an integral role for task-intensive applications in cloud computing and crowdsourcing. Optimal scheduling can enhance system performance, typically measured by the reward-to-cost ratio, under some task arrival distribution. On one hand, both reward and cost are dependent on task context (e.g., evaluation metric) and remain black

Onur Ayan, Nikolaos Pappas, Miguel Angel Gutierrez Estevez, Xueli An

Networked control systems (NCSs), which are feedback control loops closed over a communication network, have been a popular research topic over the past decades. Numerous works in the literature propose novel algorithms and protocols with joint consideration of communication and control. However, the vast majority of the recent research results, which have s

Morten Nielsen

Given a matrix-weight $W$ in the Muckenhoupt class $\mathbf{A}_p(\mathbb{R}^n)$, $1\leq p<\infty$, we introduce corresponding vector-valued continuous and discrete $\alpha$-modulation spaces $M^{s,\alpha}_{p,q}(W)$ and $m^{s,\alpha}_{p,q}(W)$ and prove their equivalence through the use of adapted tight frames. Compatible notions of molecules and almost diago

Mikhail Piotrovich, Serguei Krasnikov, Stanislava Buliga, Tinatin Natsvlishvili

The existence of even the simplest magnetized wormholes may lead to observable consequences. In the case where both the wormhole and the magnetic field around its mouths are static and spherically symmetric, and gas in the region near the wormhole falls radially into it, the former's spectrum contains bright cyclotron or synchrotron lines due to the interact

Yihan Wang, Zhouxing Shi, Andrew Bai, Cho-Jui Hsieh

Although many large language models (LLMs) have been trained to refuse harmful requests, they are still vulnerable to jailbreaking attacks which rewrite the original prompt to conceal its harmful intent. In this paper, we propose a new method for defending LLMs against jailbreaking attacks by ``backtranslation''. Specifically, given an initial response gener

Peiling Yi, Arkaitz Zubiaga

Swear words are a common proxy to collect datasets with cyberbullying incidents. Our focus is on measuring and mitigating biases derived from spurious associations between swear words and incidents occurring as a result of such data collection strategies. After demonstrating and quantifying these biases, we introduce ID-XCB, the first data-independent debias

Zihan Zhang, Meng Fang, Ling Chen

Adaptive retrieval-augmented generation (ARAG) aims to dynamically determine the necessity of retrieval for queries instead of retrieving indiscriminately to enhance the efficiency and relevance of the sourced information. However, previous works largely overlook the evaluation of ARAG approaches, leading to their effectiveness being understudied. This work

Yiyang Wang

We study the compatibility of the formal degree conjecture and the parabolic induction process in the simplest nontrivial case for quasi-split $p$-adic groups. For a generic discrete series $\pi$ induced from an irreducible supercuspidal $\sigma$ of a maximal Levi subgroup, we compute the quotient $d(\pi)/d(\sigma)$ of formal degrees under some assumptions.

Jakub Kudela, Ladislav Dobrovsky

Surrogate-assisted evolutionary algorithms (SAEAs) are recently among the most widely studied methods for their capability to solve expensive real-world optimization problems. However, the development of new methods and benchmarking with other techniques still relies almost exclusively on artificially created problems. In this paper, we use two real-world co

Moritz Flüchter, Steffen Lindner, Lukas Osswald, Jérôme Arnaud

Modern industrial networks transport both best-effort and real-time traffic. Time-Sensitive Networking (TSN) was introduced by the IEEE TSN Task Group as an enhancement to Ethernet to provide high quality of service (QoS) for real-time traffic. In a TSN network, applications signal their QoS requirements to the network before transmitting data. The network t

Yashuai Cao, Hetong Wang, Tiejun Lv, Wei Ni

Intelligent reflecting surface (IRS) is a potential candidate for massive multiple-input multiple-output (MIMO) 2.0 technology due to its low cost, ease of deployment, energy efficiency and extended coverage. This chapter investigates the slot-by-slot IRS reflection pattern design and two-timescale reflection pattern design schemes, respectively. For the slo