December 2024 arXiv papers — page 8

Mikhail Tikhomirov, Daniil Chernyshev

Rapid advancements of large language model (LLM) technologies led to the introduction of powerful open-source instruction-tuned LLMs that have the same text generation quality as the state-of-the-art counterparts such as GPT-4. While the emergence of such models accelerates the adoption of LLM technologies in sensitive-information environments the authors of

Jiayi Pan, Xingyao Wang, Graham Neubig, Navdeep Jaitly

We present SWE-Gym, the first environment for training real-world software engineering (SWE) agents. SWE-Gym contains 2,438 real-world Python task instances, each comprising a codebase with an executable runtime environment, unit tests, and a task specified in natural language. We use SWE-Gym to train language model based SWE agents, achieving up to 19% abso

Phuc Lam, Oanh Nguyen, Iris Yang

We analyze the Susceptible-Infected-Recovered-Susceptible (SIRS) process, a continuous-time Markov chain frequently employed in epidemiology to model the spread of infections on networks. In this framework, infections spread as infected vertices recover at rate 1, infect susceptible neighbors independently at rate $\lambda$, and recovered vertices become sus

Yong Xu

The evidence for the existence of dark matter (DM) is compelling, yet its nature remains elusive. A minimal scenario involves DM interacting solely through gravity. However, the detection would be extremely challenging. In the early Universe, such DM can be unavoidably generated via annihilation of particles in the standard model (SM) thermal plasma. It is k

Pak Hang Chris Lau, Kanji Nishii, Toshifumi Noumi

We elaborate on the effective field theory (EFT) construction for dissipative open systems coupled to dynamical gravity, in light of recent developments on the EFT of dissipative hydrodynamics (HydroEFT). Our construction is based on the Schwinger-Keldysh formalism and its symmetries as well as microscopic unitarity. A key aspect of dynamical gravity is that

Hadi Nahari, Thomas Strobl

The famous singular leaf decomposition $\mathcal{L}_{OH}$ of $\mathbb{R}^{16}\cong \mathbb{O}^2$ induced by the Hopf construction for octonions $\mathbb{O}$ has no known Lie group action generating it. In this article we construct a $\mathrm{G}_2$-equivariant Lie groupoid $\mathcal{G} \Rightarrow \mathbb{O}^{2}$ whose orbits coincide with $\mathcal{L}_{OH}$.

Dorothee Henke, Lasse Wulf

We introduce a new bilevel version of the classic shortest path problem and completely characterize its computational complexity with respect to several problem variants. In our problem, the leader and the follower each control a subset of the edges of a graph and together aim at building a path between two given vertices, while each of the two players minim

Inna Sysoeva

In this paper we study irreducible matrix representations of the welded braid group $WB_n$, also known as the group of conjugating automorphisms of a free group $F_n.$ We prove that $WB_n$ has no irreducible representations of dimension $r,$ where $2\leqslant r\leqslant n-2$ for $n\geqslant 5.$ We give complete classification of all extensions of irreducible

A. Tollardo, F. Cadini, M. Giglio, L. Lomazzi

Structural optimization is essential for designing safe, efficient, and durable components with minimal material usage. Traditional methods for vibration control often rely on active systems to mitigate unpredictable vibrations, which may lead to resonance and potential structural failure. However, these methods face significant challenges when addressing th

Mohammad Nadeem, Shahab Saquib Sohail, Erik Cambria, Björn W. Schuller

The advent of text-to-video generation models has revolutionized content creation as it produces high-quality videos from textual prompts. However, concerns regarding inherent biases in such models have prompted scrutiny, particularly regarding gender representation. Our study investigates the presence of gender bias in OpenAI's Sora, a state-of-the-art text

Sudipta Dhar, Botao Wang, Milena Horvath, Amit Vashisht

Anyons are low-dimensional quasiparticles that obey fractional statistics, hence interpolating between bosons and fermions. In two dimensions, they exist as elementary excitations of fractional quantum Hall states and they are believed to enable topological quantum computing. One-dimensional (1D) anyons have been theoretically proposed, but their experimenta

Fucheng Zhong, Nicola R. Napolitano, Caroline Heneka, Jens-Kristian Krogager

Classification of spectra (1) and anomaly detection (2) are fundamental steps to guarantee the highest accuracy in redshift measurements (3) in modern all-sky spectroscopic surveys. We introduce a new Galaxy Spectra Neural Network (GaSNet-III) model that takes advantage of generative neural networks to perform these three tasks at once with very high efficie

Madhuparna Das

In this article, we consider the weighted partition function $p_f(n)$ given by the generating series $\sum_{n=1}^{\infty} p_f(n)z^n = \prod_{n\in\mathbb{N}^{*}}(1-z^n)^{-f(n)}$, where we restrict the class of weight functions to strongly additive functions. Originally proposed in a paper by Yang, this problem was further examined by Debruyne and Tenenbaum fo

Li Gan

We derive explicit closed-form expressions for the generating function $C_N(A)$, which enumerates classical closed random walks on square and triangular lattices with $N$ steps and a signed area $A$, characterized by the number of moves in each hopping direction. This enumeration problem is mapped to the trace of powers of anisotropic Hofstadter-like Hamilto

Netanel Y. Tamir, Shir Amir, Ranel Itzhaky, Noam Atia

With rapid advancements in virtual reality (VR) headsets, effectively measuring stereoscopic quality of experience (SQoE) has become essential for delivering immersive and comfortable 3D experiences. However, most existing stereo metrics focus on isolated aspects of the viewing experience such as visual discomfort or image quality, and have traditionally fac

Leonid Petrov, Jeanne Scott

We study positivity and probabilistic properties arising from the Young--Fibonacci lattice $\mathbb{YF}$, a 1-differential poset on binary (Fibonacci) words of 1's and 2's, graded by digit sum. Building on Okada's theory of clone Schur functions (Trans. Amer. Math. Soc. 346 (1994), 549--568), we define clone coherent measures on $\mathbb{YF}$ that generate r

Eugenio Clerico

Hypothesis testing via e-variables can be framed as a sequential betting game, where a player each round picks an e-variable. A good player's strategy results in an effective statistical test that rejects the null hypothesis as soon as sufficient evidence arises. Building on recent advances, we address the question of restricting the pool of e-variables to s

Tim Tsz-Kit Lau, Weijian Li, Chenwei Xu, Han Liu

An appropriate choice of batch sizes in large-scale model training is crucial, yet it involves an intrinsic yet inevitable dilemma: large-batch training improves training efficiency in terms of memory utilization, while generalization performance often deteriorates due to small amounts of gradient noise. Despite this dilemma, the common practice of choosing

Ruixuan Liu, Toan Tran, Tianhao Wang, Hongsheng Hu

As large language models increasingly memorize web-scraped training content, they risk exposing copyrighted or private information. Existing protections require compliance from crawlers or model developers, fundamentally limiting their effectiveness. We propose ExpShield, a proactive self-guard that mitigates memorization while maintaining readability via in

Oscar Castillo-Felisola, Bastian Grez, Manuel Morocho-López, Jose Perdiguero

The polynomial affine model of gravity was proposed as an alternative to metric and metric-affine gravitational models. What at the beginning was thought as a source of unpredictability, the presence of many terms in the action, turned out to be a milestone, since it contains all possible combinations of the fields compatible with the covariance under diffeo

Xi Cen, Zichen Song

How to establish some specific quantitative weighted estimates for the generalized commutator of multilinear fractional singular integral operator $\mathcal{T}_{\eta}^{{\bf b}}$ is the focus of this paper, which is defined by $$\mathcal{T}_{\eta}^{{\bf b}}(\vec{f})(x):= \mathcal{T}_{\eta}\left((b_1(x) - b_1)^{\beta_1}f_1,\ldots,(b_m(x) - b_m)^{\beta_m}f_m\ri

James Cameron, Trung Chau, Sarasij Maitra, Tim Tribone

Each monomial ideal over a polynomial ring admits a free resolution which has the structure of a DG-algebra, namely, the Taylor resolution. A pivot resolution of a monomial ideal, which we introduce, is a resolution that is always shorter than the Taylor resolution (unless the Taylor resolution is as short as possible) but still retains a DG-algebra structur

Arya Bangun, Oleh Melnyk, Benjamin März

We investigate the eigenstructure of matrix formulations used for modeling scattering processes within materials in transmission electron microscopy. Dynamical scattering is crucial for describing the interaction between an electron wave and the material under investigation. Unlike the Bloch wave formulation, which defines the transmission function via the s

Ching-Feng Kung, Kao-Yueh Kuo, Ching-Yi Lai

Efficient and scalable decoding of quantum codes is essential for high-performance quantum error correction. In this work, we introduce Reliable Subset Reduction (RSR), a reliability-driven preprocessing framework that leverages belief propagation (BP) statistics to identify and remove highly reliable qubits, substantially reducing the effective problem size

Yuanbo Yang, Jiahao Shao, Xinyang Li, Yujun Shen

In this work, we introduce Prometheus, a 3D-aware latent diffusion model for text-to-3D generation at both object and scene levels in seconds. We formulate 3D scene generation as multi-view, feed-forward, pixel-aligned 3D Gaussian generation within the latent diffusion paradigm. To ensure generalizability, we build our model upon pre-trained text-to-image ge

A. Bermudez Martinez, F. Hautmann, L. Keersmaekers, A. Lelek

The evolution of transverse momentum dependent (TMD) distributions in Quantum Chromodynamics (QCD) can be formulated in a parton branching (PB) framework. We show that next-to-next-to-leading-logarithm (NNLL) accuracy can be achieved in this framework by using the concept of soft-gluon physical coupling. We present results for the TMD distributions and for t

Missipsa Aissaoui, Charlie Kahloun, Oguz Umut Salman, Sylvain Queyreau

Avalanche-like plastic bursts in crystalline materials follow power law statistics, but the scaling exponents and cutoff parameters vary widely in the literature ($\alpha$ ranging from 1 to 2.2), hindering predictive modeling. Since distributions do not follow Gaussian behavior, the average of plastic kinetics is not correctly defined. Larger-scale models th

Sergei G. Ovchinnikov

We complete the classification of all smooth 4-dimensional Kahler geometries admitting a twistor (conformal Killing-Yano) 2-form invariant under a 2-torus action. We establish that there are six geometrically distinct families, and we provide them in a simple form amenable to calculations and compute their curvature. We also find that for toric geometries th

Jonas Berx, Prashant Singh, Karel Proesmans

Individual components such as cells, particles, or agents within a larger system often require detailed understanding of their relative position to act accordingly, enabling the system as a whole to function in an organised and efficient manner. Through the concept of positional information, such components are able to specify their position in order to, e.g

Pengwei Zhao, Gang v. Chen

The mutual feedback between quantum condensed matter and cold atom physics has been quite fruitful throughout history and continues to inspire ongoing research. Motivated by the recent activities on the quantum simulation of topological orders among the ultracold Rydberg atom arrays, we consider the possibility of searching for topological orders among the d

William G. P. Mayner, Bjørn Erik Juel, Giulio Tononi

Integrated information theory (IIT) argues that the substrate of consciousness is a maximally irreducible complex of units. Together, subsets of the complex specify a cause-effect structure, composed of distinctions and their relations, which accounts in full for the quality of experience. The feeling of a specific experience is also its meaning for the subj

Changhwan Kim, Min Young Jung, Yeong Gwang Khim, Kyeong Jun Lee

Sr-doped nickelate, Nd1-xSrxNiO3 (NSNO), perovskite thin films and Ruddlesden-Popper (RP) phases are actively investigated because of their physical properties, such as the metal-insulator transition and superconductivity. However, achieving epitaxial growth of NSNO perovskite and RP phase films in a sputtering system is challenging compared to pulsed laser

Ivo Dell'Ambrogio, Rubén Martos

We study stratification, that is the classification of localizing tensor ideal subcategories by geometric means, in the context of Kasparov's equivariant KK-theory of C*-algebras. We introduce a straightforward countable analog of the notion of stratification by Balmer-Favi supports and conjecture that it holds for the equivariant bootstrap subcategory of ev

Mustafa Mullahasanoglu, Ali Mert T. Yetkin, Reyhan Yumusak

The computation of the partition function of supersymmetric gauge theories on compact manifolds can be reduced to matrix integrals by using the supersymmetric localization technique. Such matrix integrals in the case of three-dimensional supersymmetric gauge theories on lens space can be expressed in terms of hyperbolic hypergeometric integrals. By studying

António Antunes, Connor Behan

Coupling $N$ large $m$ minimal models and flowing to IR fixed points is a systematic way to build new classes of compact unitary 2d CFTs which are likely to be irrational, and potentially have a positive Virasoro twist gap above the vaccuum. In this paper, we build on the construction of [1], establishing that, for spins less than 10, additional currents tra

Tianyu Fu, Tengxuan Liu, Qinghao Han, Guohao Dai

The increasing demand to process long and high-resolution videos significantly burdens Large Vision-Language Models (LVLMs) due to the enormous number of visual tokens. Existing token reduction methods primarily prune tokens based on importance metrics, such as cumulative attention scores. However, even important tokens may exhibit high redundancy caused by

Toukir Ahammed, Moumita Asad, Kazi Sakib

The Fourth Industrial Revolution (4IR) is transforming industries and economies worldwide, presenting both opportunities and challenges for Small and Medium Enterprises (SMEs) and employment. This study qualitatively explores the impact of 4IR on the SME sector in Bangladesh. Initially, secondary data sources are reviewed to establish the context and to prep

Andrew J. E. Rowberg, Sai Mu, Chris G. Van de Walle

Wurtzite LaN (wz-LaN) is a semiconducting nitride with favorable piezoelectric and ferroelectric properties, making it promising for applications in electronics. We use first-principles density functional theory with a hybrid functional to investigate several features that are key for its use in heterostructures. First, for the purposes of growing wz-LaN on

Lior Siag, Shahaf S. Shperberg, Ariel Felner, Nathan R. Sturtevant

Parallelization and External Memory (PEM) techniques have significantly enhanced the capabilities of search algorithms when solving large-scale problems. Previous research on PEM has primarily centered on unidirectional algorithms, with only one publication on bidirectional PEM that focuses on the meet-in-the-middle (MM) algorithm. Building upon this foundat

Linus Zwaka

Sequence alignment is a cornerstone of bioinformatics, widely used to identify similarities between DNA, RNA, and protein sequences and studying evolutionary relationships and functional properties. The Needleman-Wunsch algorithm remains a robust and accurate method for global sequence alignment. However, its computational complexity, O(mn), poses significan

KuanChao Chu, Yi-Pei Chen, Hideki Nakayama

Controlling diversity in LLM-agent simulations is essential for balancing stability in structured tasks with variability in open-ended interactions. However, we observe that dialogue diversity tends to degrade over long-term simulations. To explore the role of prompt design in this phenomenon, we modularized the utterance generation prompt and found that red

Shaul Katznelson, Shai Levy, Alexey Gorlach, Nathan Regev

Scintillation, the process of converting high-energy radiation to detectable visible light, is pivotal in advanced technologies spanning from medical diagnostics to fundamental scientific research. Despite significant advancements toward faster and more efficient scintillators, there remains a fundamental limit arising from the intrinsic properties of scinti

Charles L. Fefferman, Jacob Shapiro, Michael I. Weinstein

We present new results on quantum tunneling between deep potential wells, in the presence of a strong constant magnetic field. We construct a family of double well potentials containing examples for which the low-energy eigenvalue splitting vanishes, and hence quantum tunneling is eliminated. Further, by deforming within this family, the magnetic ground stat

Jae Youn Ahn, Himchan Jeong, Mario V. Wüthrich

State-space models are popular models in econometrics. Recently, these models have gained some popularity in the actuarial literature. The best known state-space models are of Kalman-filter type. These models are so-called parameter-driven because the observations do not impact the state-space dynamics. A second less well-known class of state-space models ar

Gabriel R. Bengochea, Ernesto F. Eiroa, Griselda Figueroa-Aguirre

In this article, we construct a broad family of spacetimes with spherically symmetric thin shells in unimodular gravity. We present the framework for the analysis of the dynamical stability of the configurations under perturbations preserving the symmetry. In particular, we consider two different scenarios in which the non-conservation of the energy-momentum

Pinku Routaray, Vishal Parmar, H. C. Das, Bharat Kumar

We study the interaction between dark matter (DM) and highly magnetized neutron stars (NSs), focusing on how DM particle mass, mass fraction, and magnetic field (MF) strength affect NS structure and stability. We consider self-interacting, nonannihilating, asymmetric fermionic DM that couples to NSs only through gravitational interaction. Using the Quantum M

Andrew P. Kels

The quasi-classical expansion of a multicomponent spin solution of the star-star relation with hyperbolic Boltzmann weights is investigated. The equations obtained in a quasi-classical limit provide n-1-component extensions of certain scalar 5-point equations (corresponding to n=2) that were previously investigated by the author in the context of integrabili

Saiedeh Akbari, Cristian F. Nino, Omkar Sudhir Patil, Warren E. Dixon

Controlling nonlinear stochastic dynamical systems involves substantial challenges when the dynamics contain unknown and unstructured nonlinear state-dependent terms. For such complex systems, deep neural networks can serve as powerful black box approximators for the unknown drift and diffusion processes. Recent developments construct Lyapunov-based deep neu

Luis Daniel Abreu, Franz Luef, Mohammed Ziyat

We consider the Fock space weighted by $e^{-\alpha |z|^{2}}$, of entire and quasi-periodic (modulo a weight dependent on $\nu $) functions on ${C}$. The quotient space $\mathbb{C}/\mathbb{Z}$, called `The flat cylinder', is represented by the vertical strip $[0,1)\times \mathbb{R}$, which tiles ${C}$ by ${Z}$-translations and is therefore a fundamental domai

Moritz Reintjes, Adhiraj Chaddha

Zero viscosity limits are central to the study of classical shock waves. By identifying the correct physical (Lax admissible) shocks, they are a cornerstone in the design of analytical and numerical schemes. For relativistic fluid flow, however, the underlying dissipation mechanism, based on the Euclidean Laplace operator (so-called ``artificial viscosity'')

Li-Ming Cao, Liang-Bi Wu, Yu-Sen Zhou

We study the quasinormal modes of Boulware-Deser-Wheeler black hole in Einstein-Gauss-Bonnet gravity theory within the hyperboloidal framework. The effective potentials for the test Klein-Gordon field and gravitational perturbations of scalar, vector, and tensor types are thoroughly investigated and put into several typical classes. The effective potentials

Danial Elyassirad, Benyamin Gheiji, Mahsa Vatanparast, Amir Mahmoud Ahmadzadeh

Gliomas are the most common cause of mortality among primary brain tumors. Molecular markers, including Isocitrate Dehydrogenase (IDH) and O[6]-methylguanine-DNA methyltransferase (MGMT) influence treatment responses and prognosis. Deep learning (DL) models may provide a non-invasive method for predicting the status of these molecular markers. To achieve non

Daniel Glazer, Austin Joyce, Maria J. Rodriguez, Luca Santoni

We study the scalar tidal responses of spinning higher-dimensional black holes, and their effective field theory description. After constructing the effective field theory of a spinning point particle in general dimension, we apply this theory to match the scalar responses of a variety of black hole solutions. In addition to the five-dimensional Myers--Perry

Edwin Beggs, Xiao Han, Shahn Majid

We introduce a theory of $*$-structures for bialgebroids and Hopf algebroids over a $*$-algebra, defined in such a way that the relevant category of (co)modules is a bar category. We show that if $H$ is a Hopf $*$-algebra then the action Hopf algebroid $A\# H$ associated to a braided-commutative algebra in the category of $H$-crossed modules is a full $*$-Ho

Reza Azadeh

Multi-Agent Reinforcement Learning (MARL) approaches have emerged as popular solutions to address the general challenges of cooperation in multi-agent environments, where the success of achieving shared or individual goals critically depends on the coordination and collaboration between agents. However, existing cooperative MARL methods face several challeng

Rinat Kagirov

We present a stable cosmological model of a closed universe in the presence of conventional scalar field. The stability of the model and absence of singularity is ensured by spatial curvature without the need for additional peculiar matter. We reconstruct the Lagrangian and numerically compute observational predictions, including the number of e-folds, the s

Masaya Fujioka, Mihiro Hoshino, Suguru Iwasaki, Katsuhiro Nomura

Oxyhydrides represent a new class of functional materials, yet the synthesis of dense polycrystals or single-crystals suitable for transport studies remains a significant challenge due to hydrogen desorption at elevated temperatures. The co-diffusion of oxygen and hydrogen in densely sintered BaTiO3 enables the topochemical formation of millimeter-scale bulk

Sourav Paul, Anant Vijay Varma, Yogesh N. Joglekar, Sourin Das

We investigate a ''quantum microscope'' for qubits based on nonlinear discrete-time chaotic dynamics, which exponentially amplifies the initially small fidelity of a pair of states to a large saturation value ( $\sim$ 1/2), thereby pushing the Helstrom bound to more accessible values. We show that Bell-type temporal correlations can capture even the minutest

Nicolas Reategui, Roman Pletka, Dionysios Diamantopoulos

Ransomware represents a pervasive threat, traditionally countered at the operating system, file-system, or network levels. However, these approaches often introduce significant overhead and remain susceptible to circumvention by attackers. Recent research activity started looking into the detection of ransomware by observing block IO operations. However, thi

Gianluca Cuffaro, Christopher A. Fuchs

Finding ways to quantify magic is an important problem in quantum information theory. Recently Leone, Oliviero and Hamma introduced a class of magic measures for qubits, the stabilizer entropies of order $\alpha$, to aid in studying nonstabilizer resource theory. This suggests a way to search for those states that are as distinct as possible from the stabili

Mariia Baidachna, Rey Guadarrama, Gopal Ramesh Dahale, Tom Magorsch

Diffusion models have demonstrated remarkable success in image generation, but they are computationally intensive and time-consuming to train. In this paper, we introduce a novel diffusion model that benefits from quantum computing techniques in order to mitigate computational challenges and enhance generative performance within high energy physics data. The

Charles J. Edelson, Paul Smith, Sima Setayeshgar, William Bialek

To make efficient use of limited physical resources, the brain must match its coding and computational strategies to the statistical structure of input signals. An attractive testing ground for these principles is the problem of motion estimation in the fly visual system: we understand the optics of the compound eye, have a quantitative description of input

Nasr Ahmed, Anirudh Pradhan, Archana Dixit

A cyclic flat universe with quintom behaviour and future big rip has been presented in the framework of Rastall gravity, which is an extension of the standard $\Lambda$CDM model. The Hubble parameter oscillates periodically between positive and negative values from one cycle to the next. Cosmic transit has been simulated through an oscillating time-dependent

Yuan-Hao Jiang, Ruijia Li, Yizhou Zhou, Changyong Qi

The development of large language models has ushered in new paradigms for education. This paper centers on the multi-Agent system in education and proposes the von Neumann multi-Agent system framework. It breaks down each AI Agent into four modules: control unit, logic unit, storage unit, and input-output devices, defining four types of operations: task deco

Yifei Huang, Jilan Xu, Baoqi Pei, Yuping He

We introduce Vinci, a real-time embodied smart assistant built upon an egocentric vision-language model. Designed for deployment on portable devices such as smartphones and wearable cameras, Vinci operates in an "always on" mode, continuously observing the environment to deliver seamless interaction and assistance. Users can wake up the system and engage in

Qingyan Bai, Hao Ouyang, Yinghao Xu, Qiuyu Wang

As a verified need, consistent editing across in-the-wild images remains a technical challenge arising from various unmanageable factors, like object poses, lighting conditions, and photography environments. Edicho steps in with a training-free solution based on diffusion models, featuring a fundamental design principle of using explicit image correspondence

Daniel Maienshein

In the theory of viscosity solutions for second-order, degenerate elliptic PDEs, the Ishii-Lions method is a commonly used strategy, and the theorem of sums is the main analytical tool. As noted by Porretta and Priola, uniformly elliptic PDEs admit a version of the theorem of sums without the squared term due to a compactness argument. Here, we introduce a l

Xingqin Lin

The 3rd Generation Partnership Project (3GPP) evolution of mobile communication technologies from 5G to 6G has been a transformative journey spanning a decade, shaped by six releases from Release 15 to Release 20. This article provides a retrospective of this evolution, highlighting the technical advancements, challenges, and milestones that have defined the

Nazanin Ahmadi, Shupeng Wang, George Karniadakis

We present a novel method to improve pharmacokinetics modeling, an essential step of drug development. Conventional models frequently fail to fully represent the intricacies of drug absorption and distribution, which limits their predictive abilities required for personalized treatment strategies. Our methodology introduces two innovations to enhance modelin

Alexander Hock, Sergey Shadrin, Raimar Wulkenhaar

We prove that meromorphic differentials $ω^{(0)}_n(z_1,...,z_n)$ which are recursively generated by an involution identity are symmetric in all their arguments $z_1,...,z_n$. The proof involves an intriguing combinatorial identity between integer partitions into given number of parts.

Jacek Gulgowski, Adam Kwela, Jacek Tryba

Recently we have presented a unified approach to two classes of Banach spaces defined by means of variations (Waterman spaces and Chanturia classes), utilizing the concepts from the theory of ideals on the set of natural numbers. We defined correspondence between an ideal on the set of natural numbers, a certain sequence space and related space of functions

Eduard Emelyanov, Nazife Erkursun-Ozcan, Svetlana Gorokhova

We study relatively uniformly continuous operator semigroups on ordered vector spaces and extend several recent results obtained by M. Kramar Fijavz, M. Kandic, M. Kaplin, and J. Gluck in the vector lattice setting to ordered vector spaces with generating cones.

Kasturie D. Jatkar, Tien-Tien Yeh, Matteo Pancaldi, Stefano Bonetti

We developed a phase correction method for broadband terahertz time-domain spectroscopy in reflection geometry, which allows us to obtain quantitative and accurate values for the complex refractive index of materials. The process is analytical, based on the Kramers-Kronig relations, and does not require any computationally intensive algorithms. We validate i

Yang Yang, Chen Cheng, Yunhao Fan, Gia-Wei Chern

The phase ordering kinetics of emergent orders in correlated electron systems is a fundamental topic in non-equilibrium physics, yet it remains largely unexplored. The intricate interplay between quasiparticles and emergent order-parameter fields could lead to unusual coarsening dynamics that is beyond the standard theories. However, accurate treatment of bo

Francesco Aldo Venturelli, Sreetama Das, Filippo Caruso

The quantum approximate optimization algorithm (QAOA) is a variational quantum algorithm (VQA) ideal for noisy intermediate-scale quantum (NISQ) processors, and is highly successful in solving combinatorial optimization problems (COPs). It has been observed that the optimal parameters obtained from one instance of a COP can be transferred to another instance

Christos Pervolianakis

We consider an optimal control problem on a bounded domain $\Omega\subset\mathbb{R}^2,$ governed by a parabolic convection--diffusion--reaction equation with pointwise control constraints. We follow the optimize--then--discretize approach, in which the state and co-state variables are discretized using the piecewise linear finite element method. For stabiliz

Wenhao Zhuang, Yuyi Mao

Mobile edge computing (MEC) has empowered mobile devices (MDs) in supporting artificial intelligence (AI) applications through collaborative efforts with proximal MEC servers. Unfortunately, despite the great promise of device-edge cooperative AI inference, data privacy becomes an increasing concern. In this paper, we develop a privacy-aware multi-device coo

Yushun Zhang, Dmitry Rybin, Zhi-Quan Luo

In modern engineering scenarios, there is often a strict upper bound on the number of algorithm iterations that can be performed within a given time limit. This raises the question of optimal algorithmic configuration for a fixed and finite iteration budget. In this work, we introduce the framework of finite horizon optimization, which focuses on optimizing

Przemysław Berk, Krzysztof Frączek, Frank Trujillo

We introduce a novel method for proving ergodicity for skew products of interval exchange transformations (IETs) with piecewise smooth cocycles having singularities at the ends of exchanged intervals. This approach is inspired by Borel-Cantelli-type arguments from Fayad and Lema\'nczyk (2006). The key innovation of our method lies in its applicability to sin

Mahesh K. N. Balasubramanian, Anindya Banerjee, Matthew Buican, Zhihao Duan

Any local unitary 3d $\mathcal{N}=4$ superconformal field theory (SCFT) has a corresponding "universal" relevant deformation that takes it to a gapped phase. This deformation preserves all continuous internal symmetries, $\mathcal{S}$, and therefore also preserves any 't Hooft anomalies supported purely in $\mathcal{S}$. We describe the resulting phase diagr

Ehsan Latif, Xiaoming Zhai

The integration of Artificial Intelligence (AI) in education requires scalable and efficient frameworks that balance performance, adaptability, and cost. This paper addresses these needs by proposing a shared backbone model architecture enhanced with lightweight LoRA adapters for task-specific fine-tuning, targeting the automated scoring of student responses

Ben Currie, Evgeny Kozik

The fractional quantum Hall (FQH) effect arises from strong electron correlations in a quantising magnetic field, and features exotic emergent phenomena such as electron fractionalisation. Using the diagrammatic Monte Carlo approach with the combinatorial summation (CoS) algorithm, we obtain results with controlled accuracy for the microscopic model of inter

Siyang Wang, Feng Zhao

Generative models trained on extensive high-quality datasets effectively capture the structural and statistical properties of clean images, rendering them powerful priors for transforming degraded features into clean ones in image restoration. VAR, a novel image generative paradigm, surpasses diffusion models in generation quality by applying a next-scale pr

Wenjun Yu, Xiaogang Li, Qi Zhao, Xiao Yuan

Quantum computers can efficiently simulate Lindbladian dynamics, enabling powerful applications in open system simulation, thermal and ground-state preparation, autonomous quantum error correction, dissipative engineering, and more. Despite the abundance of well-established algorithms for closed-system dynamics, simulating open quantum systems on digital qua

Yihan Wang, Yiwei Lu, Xiao-Shan Gao, Gautam Kamath

Availability attacks, or unlearnable examples, are defensive techniques that allow data owners to modify their datasets in ways that prevent unauthorized machine learning models from learning effectively while maintaining the data's intended functionality. It has led to the release of popular black-box tools (e.g., APIs) for users to upload personal data and

Mariano Guerrero Perez, Keegan Walkup, Jordan Chapman, Pranshu Bhaumik

Vacancy-cluster color centers in lithium fluoride have been studied in detail both theoretically and experimentally for over a century, giving rise to various applications in solid-state lasers, broadband photonic devices, and radiation dosimeters. These color centers are also attractive candidate platforms for applications in quantum information science, du

Jiazheng Xu, Yu Huang, Jiale Cheng, Yuanming Yang

Visual generative models have achieved remarkable progress in synthesizing photorealistic images and videos, yet aligning their outputs with human preferences across critical dimensions remains a persistent challenge. Though reinforcement learning from human feedback offers promise for preference alignment, existing reward models for visual generation face l

Qiang Wen, Mingshuai Xu, Haocheng Zhong

In the context of the AdS$_3$/CFT$_2$, the boundary causal development and the entanglement wedge of any boundary spacelike interval can be mapped to a thermal CFT$_2$ and a Rindler $\widetilde{\text{AdS}_3}$ respectively via certain boundary and bulk Rindler transformations. Nevertheless, the Rindler mapping is not confined in the entanglement wedges. While

Ehsan Latif, Ying Chen, Xiaoming Zhai, Yue Yin

This paper provides a comprehensive review of the design and implementation of automatically generated assessment reports (AutoRs) for formative use in K-12 Science, Technology, Engineering, and Mathematics (STEM) classrooms. With the increasing adoption of technology-enhanced assessments, there is a critical need for human-computer interactive tools that ef

Tomohiro Asano, Yuichi Ike

We give an affirmative answer to the rectangular peg problem for a large class of continuous Jordan curves that contains all rectifiable curves and Stromquist's locally monotone curves. Our proof is based on microlocal sheaf theory and inspired by recent work of Greene and Lobb.

Marta Cipriani, Lorenzo Di Rocco, Maria Puopolo, Marco Alfò

Enhancing reproducibility and data accessibility is essential to scientific research. However, ensuring data privacy while achieving these goals is challenging, especially in the medical field, where sensitive data are often commonplace. One possible solution is to use synthetic data that mimic real-world datasets. This approach may help to streamline therap

Jan Behrends, Benjamin Béri

We consider the surface code under errors featuring both coherent and incoherent components and study the coherence of the corresponding logical noise channel and how this impacts information-theoretic measures of code performance, namely coherent information and quantum relative entropy. Using numerical simulations and developing a phenomenological field th

Rui-Jun Huang, Dong-Shan Jian, Yan-Qing Ma, Dao-Ming Mu

We propose a novel method, called the dimension-changing transformation (DCT), to compute one-loop Feynman integrals and recently introduced fixed-branch integrals to arbitrary orders in $\epsilon$. The DCT relates one-loop Feynman integrals or fixed-branch integrals in one spacetime dimension to their corresponding quantities with auxiliary mass in any othe

Li-Hong Huang, Rui-Jun Huang, Yan-Qing Ma

We introduce a novel structure for Feynman integrals, reformulating them as integrals over a small set of parameters with a fully controllable integrand. The integrand closely resembles one-loop Feynman integrals, and they are very easy to handle. Remarkably, the number of remaining integration parameters is independent of the number of external legs and sma

Thomas P. Zollo, Nikita Rajaneesh, Richard Zemel, Talia B. Gillis

Generative AI (GenAI) models present new challenges in regulating against discriminatory behavior. In this paper, we argue that GenAI fairness research still has not met these challenges; instead, a significant gap remains between existing bias assessment methods and regulatory goals. This leads to ineffective regulation that can allow deployment of reported

Yuyang Zhou, Guang Cheng, Kang Du, Zihan Chen

The rapid evolution of cloud computing technologies and the increasing number of cloud applications have provided numerous benefits in our daily lives. However, the diversity and complexity of different components pose a significant challenge to cloud security, especially when dealing with sophisticated and advanced cyberattacks such as Denial of Service (Do

Anuk Dayaprema, Alex Waldron

We prove parabolic versions of several known gap theorems in classical Yang-Mills theory. On an $\mathrm{SU}(r)$-bundle of charge $\kappa$ over the 4-sphere, we show that the space of all connections with Yang-Mills energy less than $4 \pi^2 \left( |\kappa| + 2 \right)$ deformation-retracts under Yang-Mills flow onto the space of instantons, allowing us to s

Jianda Du, Senwei Liang, Chunmei Wang

Modeling and forecasting the spread of infectious diseases is essential for effective public health decision-making. Traditional epidemiological models rely on expert-defined frameworks to describe complex dynamics, while neural networks, despite their predictive power, often lack interpretability due to their ``black-box" nature. This paper introduces the F

María Eugenia Cejas, Ricardo G. Durán

Given a bounded domain $\O$ and $f$ of zero integral, the existence of a vector fields $\u$ vanishing on $\partial\O$ and satisfying $\d\u=f$ has been widely studied because of its connection with many important problems. It is known that for $f\in L^p(\O)$, $1<p<\infty$, there exists a solution $\u\in W^{1,p}_0(\O)$, and also that an analogous result is not

Craig E. DeForest, Nicholas F. Erickson, Matthew N. Beasley, Steven N. Osterman

We present a first-principles analytic treatment of modern multi-vane occulters in circular (coronagraph) and linear (heliospheric imager) geometry, develop a simplified theory that is useful for designing and predicting their performance, explain certain visual artifacts, and explore the performance limits of multi-vane occulters. Multi-vane occulters are c