October 2023 arXiv papers — page 124

Xiaoyi Liu, Donald Marolf, Jorge E. Santos

Due to the conformal factor problem, the definition of the Euclidean gravitational path integral requires a non-trivial choice of contour. The present work examines a generalization of a recently proposed rule-of-thumb \cite{Marolf:2022ntb} for selecting this contour at quadratic order about a saddle. The original proposal depended on the choice of an indefi

Salvatore D. Pace, Chenchang Zhu, Agnès Beaudry, Xiao-Gang Wen

We study the nonlinear $\sigma$-model in ${(d+1)}$-dimensional spacetime with connected target space $K$ and show that, at energy scales below singular field configurations (such as vortices), it has an emergent non-invertible higher symmetry. The symmetry defects of the emergent symmetry are described by the $d$-representations of a discrete $d$-group $\mat

Gabriel E. Colon-Reyes, Ruth Kravis, Sunash Sharma, Duncan Callaway

In this work, we study fast time scale dynamic interactions between inverters, synchronous machines, and transmission lines. The overlapping time scales between inverter controls and electromagnetic phenomena idfentified in recent years has necessitated a re-evaluation of assumptions made in power system dynamics studies. We utilize an open-source modeling p

Jane Breen, Sooyeong Kim, Alexander Low Fung, Amy Mann

Kemeny's constant measures how fast a random walker moves around in a graph. Expressions for Kemeny's constant can be quite involved, and for this reason, many lines of research focus on graphs with structure that makes them amenable to more in-depth study (for example, regular graphs, acyclic graphs, and 1-connected graphs). In this article, we study Kemeny

Zhihao Tao, Zhaoyi Xu, Athina Petropulu

Time-modulated arrays (TMA) transmitting orthogonal frequency division multiplexing (OFDM) waveforms achieve physical layer security by allowing the signal to reach the legitimate destination undistorted, while making the signal appear scrambled in all other directions. In this paper, we examine how secure the TMA OFDM system is, and show that it is possible

Snehasis Bera, Sourav Das, Abhijit Banerjee

In this work, generalized hypergeometric functions for bicomplex argument is introduced and its convergence criteria is derived. Furthermore, integral representation of this function has been established. Moreover, quadratic transformation, differential relation, analyticity and contiguous relations of this function are derived. Additionally, applications in

Lucy Xiaoyang Shi, Yunfan Jiang, Jake Grigsby, Linxi "Jim" Fan

We present a new algorithm, Cross-Episodic Curriculum (CEC), to boost the learning efficiency and generalization of Transformer agents. Central to CEC is the placement of cross-episodic experiences into a Transformer's context, which forms the basis of a curriculum. By sequentially structuring online learning trials and mixed-quality demonstrations, CEC cons

Rainie Bozzai, Thomas Rothvoss

We apply the discrepancy method and a chaining approach to give improved bounds on the coreset complexity of a wide class of kernel functions. Our results give randomized polynomial time algorithms to produce coresets of size $O\big(\frac{\sqrt{d}}{\varepsilon}\sqrt{\log\log \frac{1}{\varepsilon}}\big)$ for the Gaussian and Laplacian kernels in the case that

Erik S. Sørensen

The screening of an impurity spin in the Kondo model occurs over a characteristic length scale $\xi_K$, that defines the size of the Kondo screening cloud or ``mist". The presence of such a length sc A consistent way to show the presence of the screening cloud is to demonstrate scaling in the spatial correlations depending on $r$, in terms of the single vari

Tal Nelken

In this thesis we study geometric branching operators on simplices in the (affine) Bruhat-Tits building associated to the symplectic group over a local field. We use these operators to study the simple random walk on the building's vertices. This work lays the foundations for studying the total-variation cutoff phenomenon for simple random walk on Ramanujan

Taro Kimura, Go Noshita

We explore the quantum algebraic formalism of the gauge origami system in $\mathbb{C}^{4}$, where D2/D4/D6/D8-branes are present. We demonstrate that the contour integral formulas have free field interpretations, leading to the operator formalism of $qq$-characters associated with each D-brane. The $qq$-characters of D2 and D4-branes correspond to screening

F. Haas, J. T. Mendonça, H. Terças

We study the dispersion properties of electron plasma waves, or plasmons, which can be excited in quantum plasmas in the nonlinear regime. In order to describe nonlinear electron response to finite amplitude plasmons, we apply the Volkov approach to non-relativistic electrons. For that purpose, we use the Schr\"odinger equation and describe the electron popu

Xi Jiang, Shinan Liu, Aaron Gember-Jacobson, Arjun Nitin Bhagoji

Datasets of labeled network traces are essential for a multitude of machine learning (ML) tasks in networking, yet their availability is hindered by privacy and maintenance concerns, such as data staleness. To overcome this limitation, synthetic network traces can often augment existing datasets. Unfortunately, current synthetic trace generation methods, whi

Aaron W. Messerla

The topology of the Bowditch boundary of a relatively hyperbolic group pair gives information about relative splittings of the group. It is therefore interesting to ask if there is generic behavior of this boundary. The purpose of this article is to show that in the case of a non-abelian free group with cyclic peripheral structure, there is not a generic cas

Zhengyuan Yang, Jianfeng Wang, Linjie Li, Kevin Lin

We introduce ``Idea to Image,'' a system that enables multimodal iterative self-refinement with GPT-4V(ision) for automatic image design and generation. Humans can quickly identify the characteristics of different text-to-image (T2I) models via iterative explorations. This enables them to efficiently convert their high-level generation ideas into effective T

Lingfeng Shen, Aayush Mishra, Daniel Khashabi

The emergence of In-Context Learning (ICL) in LLMs remains a remarkable phenomenon that is partially understood. To explain ICL, recent studies have created theoretical connections to Gradient Descent (GD). We ask, do such connections hold up in actual pre-trained language models? We highlight the limiting assumptions in prior works that make their setup con

Bichen Zhang, Pai Peng, Aditya Paul, Jeff D. Thompson

Scalable classical controllers are a key component of future fault-tolerant quantum computers. Neutral atom quantum computers leverage commercially available optoelectronic devices for generating large-scale tweezer arrays and performing parallel readout, but implementing massively parallel, locally-addressed gate operations is an open challenge. In this wor

Neema Jakisa Owor, Hang Du, Abdulateef Daud, Armstrong Aboah

The Pavement Condition Index (PCI) is a widely used metric for evaluating pavement performance based on the type, extent and severity of distresses detected on a pavement surface. In recent times, significant progress has been made in utilizing deep-learning approaches to automate PCI estimation process. However, the current approaches rely on at least two s

Yifei Zhang, James Song, Siyi Gu, Tianxu Jiang

Explainable AI (XAI) has gained significant attention for providing insights into the decision-making processes of deep learning models, particularly for image classification tasks through visual explanations visualized by saliency maps. Despite their success, challenges remain due to the lack of annotated datasets and standardized evaluation pipelines. In t

Gianluca Bertaina, Cecilia Clivati, Simone Donadello, Carlo Liorni

The impact of noise sources in real-world implementations of Twin-Field Quantum Key Distribution (TF-QKD) protocols is investigated, focusing on phase noise from photon sources and connecting fibers. This work emphasizes the role of laser quality, network topology, fiber length, arm balance, and detector performance in determining key rates. Remarkably, it r

Seulki Chung

This paper uses standard and penalized logistic regression models to predict the Great Recession and the Covid-19 recession in the US in real time. It examines the predictability of various macroeconomic and financial indicators with respect to the NBER recession indicator. The findings strongly support the use of penalized logistic regression models in rece

Maxwell Crouse, Ibrahim Abdelaziz, Ramon Astudillo, Kinjal Basu

Autonomous, goal-driven agents powered by LLMs have recently emerged as promising tools for solving challenging problems without the need for task-specific finetuned models that can be expensive to procure. Currently, the design and implementation of such agents is ad hoc, as the wide variety of tasks that LLM-based agents may be applied to naturally means t

Mengyi Shan, Brian Curless, Ira Kemelmacher-Shlizerman, Steve Seitz

We present a system that automatically brings street view imagery to life by populating it with naturally behaving, animated pedestrians and vehicles. Our approach is to remove existing people and vehicles from the input image, insert moving objects with proper scale, angle, motion, and appearance, plan paths and traffic behavior, as well as render the scene

Aritra Sinha, Marek M. Rams, Jacek Dziarmaga

The Minimally Entangled Typical Thermal States (METTS) are an ensemble of pure states, equivalent to the Gibbs thermal state, that can be efficiently represented by tensor networks. In this article, we use the Projected Entangled Pair States (PEPS) ansatz as to represent METTS on a two-dimensional (2D) lattice. While Matrix Product States (MPS) are less effi

Anna Andreychenko, Viktoriia Korzhuk, Stanislav Kondratenko, Polina Cheraneva

Currently, there are many difficulties regarding the interoperability of medical data and related population data sources. These complications get in the way of the generation of high-quality data sets at city, region and national levels. Moreover, the collection of datasets within large medical centers is feasible due to own IT departments whereas the colle

Hussein Nassar, Andrew Weber

We argue that the standard classification of isometric deformations into infinitesimal v.s. finite is inadequate for the study of compliant shell mechanisms. Indeed, many compliant shells, particularly ones that are periodically corrugated, exhibit low-energy deformations that are far too large to be infinitesimally isometric and far too rich to be finitely

Jie Yang, Ailing Zeng, Ruimao Zhang, Lei Zhang

This work aims to address an advanced keypoint detection problem: how to accurately detect any keypoints in complex real-world scenarios, which involves massive, messy, and open-ended objects as well as their associated keypoints definitions. Current high-performance keypoint detectors often fail to tackle this problem due to their two-stage schemes, under-e

Taoran Yi, Jiemin Fang, Junjie Wang, Guanjun Wu

In recent times, the generation of 3D assets from text prompts has shown impressive results. Both 2D and 3D diffusion models can help generate decent 3D objects based on prompts. 3D diffusion models have good 3D consistency, but their quality and generalization are limited as trainable 3D data is expensive and hard to obtain. 2D diffusion models enjoy strong

Guanjun Wu, Taoran Yi, Jiemin Fang, Lingxi Xie

Representing and rendering dynamic scenes has been an important but challenging task. Especially, to accurately model complex motions, high efficiency is usually hard to guarantee. To achieve real-time dynamic scene rendering while also enjoying high training and storage efficiency, we propose 4D Gaussian Splatting (4D-GS) as a holistic representation for dy

Matteo Tagliazucchi, Matteo Braglia, Fabio Finelli, Mauro Pieroni

Gravitational Waves (GW) sourced by second-order primordial curvature fluctuations are among the favored models fitting the recent pulsar timing array (PTA) measurement of a stochastic GW background (SGWB). We study how spectral distortions (SDs) and anisotropies of the cosmic microwave background (CMB) can constrain such scalar fluctuations. Whereas COBE FI

Thomas C. Gehrman, Barmak Shams Es Haghi, Kuver Sinha, Tao Xu

We outline a new production mechanism for dark matter that we dub "recycling": dark sector particles are kinematically trapped in the false vacuum during a dark phase transition; the false pockets collapse into primordial black holes (PBHs), which ultimately evaporate before Big Bang Nucleosynthesis (BBN) to reproduce the dark sector particles. The requireme

Jun Toshikawa, Stijn Wuyts, Nobunari Kashikawa, Chengze Liu

We present a protocluster search covering $z\sim3$ to $z\sim5$ based on the combination of the Hyper SuprimeCam Subaru Strategic Programme and the CFHT Large Area $U$-band Deep Survey. We identify about 30 protocluster candidates per unit redshift over the $\sim25\,\mathrm{deg^2}$ area of the Deep/Ultra-Deep layer. Protocluster candidates are selected as reg

Niklas Garner, Surya Raghavendran, Brian R. Williams

We propose a method for extracting the Higgs and Coulomb branches of a three-dimensional N = 4 quantum field theory from the algebra of local operators in its holomorphic-topological twist using the formalism of raviolo vertex algebras. Our construction parallels that of the chiral ring and twisted chiral ring of an N = 2 superconformal vertex operator algeb

Inwon Kang, Sikai Ruan, Tyler Ho, Jui-Chien Lin

Finding preferences expressed in natural language is an important but challenging task. State-of-the-art(SotA) methods leverage transformer-based models such as BERT, RoBERTa, etc. and graph neural architectures such as graph attention networks. Since Large Language Models (LLMs) are equipped to deal with larger context lengths and have much larger model siz

Dmitrii Diakonov

The Euclidean path integral is compared to the thermal (canonical) partition function in curved static space-times. It is shown that if spatial sections are non-compact and there is no Killing horizon, the logarithms of these two quantities differ only by a term proportional to the inverse temperature, that arises from the vacuum energy. When spatial section

David Gobrecht, S. Rasoul Hashemi, John M. C. Plane, Stefan T. Bromley

Spinel (MgAl$_{2}$O$_{4}$) and krotite (CaAl$_{2}$O$_{4}$) are alternative candidates to alumina (Al$_2$O$_3$) as primary dust condensates in the atmospheres of oxygen-rich evolved stars. Moreover, spinel was proposed as a potential carrier of the circumstellar 13 $\mu$m feature. However, the formation of nucleating spinel clusters is challenging; in particu

Asma Karami, Adam Reddy, Hussein Nassar

We find a closed-form expression for the Poisson's coefficient of curved-crease variants of the ``Miura ori'' origami tessellation. This is done by explicitly constructing a continuous one-parameter family of isometric piecewise-smooth surfaces that describes the action of folding out of a reference state. The response of the tessellations in bending is inve

Dominic Breit, Prince Romeo Mensah, Thamsanqa Castern Moyo

We consider a viscous incompressible fluid interacting with a linearly elastic shell of Koiter type which is located at some part of the boundary. Recently models with stochastic perturbation in the shell equation have been proposed in the literature but only analysed in simplified cases. We investigate the full model with transport noise, where (a part of)

M. Abu-Saleem, H. S. Vieira, L. H. C. Borges

In this paper, we examine the role played by topology, and some specific boundary conditions as well, on the physics of a higher-dimensional black hole. We analyze the line element of a five-dimensional non-extremal Reissner-Nordstr\"{o}m black hole to obtain a new family of subspaces that are types of strong retractions and deformations, and then we extend

Alejandro Díaz-Caro, Gilles Dowek, Malena Ivnisky, Octavio Malherbe

We present a polymorphic linear lambda-calculus as a proof language for second-order intuitionistic linear logic. The calculus includes addition and scalar multiplication, enabling the proof of a linearity result at the syntactic level.

Niklas Garner, Surya Raghavendran, Brian R. Williams

We show that the action of residual supersymmetries in holomorphic-topological twists of $N = 2$ theories in three dimensions naturally extends to the action of certain infinite dimensional Lie superalgebras. We demonstrate this in a range of examples, including $N = 4$ Yang-Mills theories and superconformal Chern-Simons theories, describing how the symmetri

Balaji Srinivasan, Anubhav Sinha

The present work examines the effect of the velocity profile on primary breakup of liquid jets emanating from fuel injectors. Direct Numerical Simulation (DNS) is used to simulate liquid jet breakup. Different velocity profiles are imposed on the liquid and their effect on breakup is examined. It is a common practice in the literature to use flat or uniform

Panagiotis Koutsogiannakis, Diego Misseroni, Davide Bigoni, Francesco Dal Corso

An elastic rod, straight in its undeformed state, has a mass attached at one end and a variable length, due to a constraint at the other end by a frictionless sliding sleeve. The constraint is arranged with the sliding direction parallel to a gravity field, in a way that the rod can freely slip inside of the sleeve, when the latter is not moving. In this cas

Yuhan Helena Liu, Aristide Baratin, Jonathan Cornford, Stefan Mihalas

In theoretical neuroscience, recent work leverages deep learning tools to explore how some network attributes critically influence its learning dynamics. Notably, initial weight distributions with small (resp. large) variance may yield a rich (resp. lazy) regime, where significant (resp. minor) changes to network states and representation are observed over t

Francesco Toschi, Benedikt Maier, Greta Heine, Torben Ferber

Ultra-sensitive cryogenic calorimeters have become a favored technology with widespread application where eV-scale energy resolutions are needed. In this article, we characterize the performance of an X-ray magnetic microcalorimeter (MMC) using a Fe-55 source. Employing an optimum filter-based amplitude estimation and energy reconstruction, we demonstrate th

Yu Song, Santiago Miret, Huan Zhang, Bang Liu

We propose an instruction-based process for trustworthy data curation in materials science (MatSci-Instruct), which we then apply to finetune a LLaMa-based language model targeted for materials science (HoneyBee). MatSci-Instruct helps alleviate the scarcity of relevant, high-quality materials science textual data available in the open literature, and HoneyB

Md Manjurul Ahsan

Divorce is one of the most common social issues in developed countries like in the United States. Almost 50% of the recent marriages turn into an involuntary divorce or separation. While it is evident that people vary to a different extent, and even over time, an incident like Divorce does not interrupt the individual's daily activities; still, Divorce has a

M. P. Morales Rodríguez, O. S. Magaña-Loaiza, B. Perez-Garcia, L. M. Nieto Calzada

Large quantum photonic systems hold promise for surpassing classical computational limits, yet their state preparation remains a challenge. We propose an alternative approach to study multiparticle dynamics by mapping the excitation mode of these systems to physical properties of the Laguerre-Gauss modes. We construct coherent states establishing a direct li

Henry Hu

We consider the Laguerre Unitary Ensemble (LUE), the set of $n\times n$ sample covariance matrices $M = \frac{1}{n}X^*X$ where the $m\times n$ ($n \le m$) matrix $X$ has i.i.d. standard complex Gaussian entries. In particular we are concerned with the case where $\alpha := m - n$ is fixed, in which case the limiting eigenvalue density has a hard edge at $0$.

Jake Langham, Andrew J. Hogg

When turbulent flow is laden with negatively buoyant particles, their mean distribution over the direction of gravity can induce stable density gradients that penalize turbulent fluctuations. This effect is studied numerically for shear-driven flow with dilute non-inertial sediment. The turbulent dynamics and sediment transport depend critically on particle

Vikram Nitin, Anne Mulhern, Sanjay Arora, Baishakhi Ray

The Rust programming language is becoming increasingly popular among systems programmers due to its efficient performance and robust memory safety guarantees. Rust employs an ownership model to ensure this guarantee by allowing each value to be owned by only one identifier at a time. Additionally, it introduces the concept of borrowing and lifetimes to enabl

Chongying Dong, Li Ren, Chao Yang

In this article, we investigate Hopf actions on vertex algebras. Our first main result is that every finite-dimensional Hopf algebra that inner faithfully acts on a given \pi_2-injective vertex algebra must be a group algebra. Secondly, under suitable assumptions, we establish a Schur-Weyl type duality for semisimple Hopf actions on Hopf modules of vertex al

Gao Yu Lee, Tanmoy Dam, Md Meftahul Ferdaus, Daniel Puiu Poenar

Recent advancements have significantly improved the efficiency and effectiveness of deep learning methods for imagebased remote sensing tasks. However, the requirement for large amounts of labeled data can limit the applicability of deep neural networks to existing remote sensing datasets. To overcome this challenge, fewshot learning has emerged as a valuabl

Hussein Nassar

A \emph{surface of translation} is a sum $(u,v)\mapsto\gt\alpha(u)+\gt\beta(v)$ of two space curves: a \emph{path} $\gt\alpha$ and a \emph{profile} $\gt\beta$. A fundamental problem of differential geometry and shell theory is to determine the ways in which surfaces deform isometrically, i.e., by bending without stretching. Here, we explore how surfaces of t

Claudio Bonati, Andrea Pelissetto, Ettore Vicari

We consider multicomponent Abelian Higgs (AH) gauge theories with multiparameter scalar quartic potentials that are extensions, with a smaller global symmetry group, of $SU(N)$-invariant AH theories. In particular, we consider an AH model with a two-parameter scalar potential and $SO(N)$ global symmetry. We discuss the renormalization-group flow of the $SO(N

A. J. Castro-Tirado, Rahul Gupta, S. B. Pandey, A. Nicuesa Guelbenzu

Dark GRBs constitute a significant fraction of the GRB population. In this paper, we present the multiwavelength analysis of an intense two-episodic GRB 150309A observed early on to ~114 days post-burst. Despite the strong gamma-ray emission, no optical afterglow was detected for this burst. However, we discovered near-infrared afterglow ($K_{\rm S}$-band),

Maribel Hernández, Celia Escamilla-Rivera

An explanation of the nature of dark energy has been treated in extra dimensions within the scheme of string theory. One of the most successful models is inspired by the Dvali-Gabadadze-Porrati (DGP) model, in which the universe is a 4-dimensional brane embedded in a 5-dimensional Minkowski space-time. In this landscape, the study of the evolution of the nor

Steffen Wolf, Manan Lalit, Henry Westmacott, Katie McDole

Segmentation of objects in microscopy images is required for many biomedical applications. We introduce object-centric embeddings (OCEs), which embed image patches such that the spatial offsets between patches cropped from the same object are preserved. Those learnt embeddings can be used to delineate individual objects and thus obtain instance segmentations

E. Pasatembou, C. F. A. Baynham, O. Buchmüller, D. Evans

Long-baseline atom interferometers, such as the one to be built by the AION collaboration, require ultra-cold atomic clouds. These are produced by trapping the atoms in Magneto-Optical Traps (MOTs) using high-power, narrow-linewidth lasers. We report on the laser and optical master-slave injection locked system used to address the 1S0 - 3P1 strontium transit

Declan Daly, Stephen J. DeVience, Emma Huckestein, John W. Blanchard

Nitrogen vacancy (NV) centers in diamond enable nuclear magnetic resonance (NMR) spectroscopy of samples at the nano- and micron scales. However, at typical tesla-scale NMR magnetic field strengths, NV-NMR protocols become difficult to implement due to the challenge of driving fast NV pulse sequences sensitive to nuclear Larmor frequencies above a few megahe

Adam Reddy, Asma Karami, Hussein Nassar

Shell mechanisms are patterned surface-like structures with compliant deformation modes that allow them to change shape drastically. Examples include many origami and kirigami tessellations as well as other periodic truss mechanisms. The deployment paths of a shell mechanism are greatly constrained by the inextensibility of the constitutive material locally,

Nathan Fradet, Nicolas Gutowski, Fabien Chhel, Jean-Pierre Briot

Symbolic music is widely used in various deep learning tasks, including generation, transcription, synthesis, and Music Information Retrieval (MIR). It is mostly employed with discrete models like Transformers, which require music to be tokenized, i.e., formatted into sequences of distinct elements called tokens. Tokenization can be performed in different wa

Pengyu Wang, Zhichen Ren

Automatic analysis for modern Chinese has greatly improved the accuracy of text mining in related fields, but the study of ancient Chinese is still relatively rare. Ancient text division and lexical annotation are important parts of classical literature comprehension, and previous studies have tried to construct auxiliary dictionary and other fused knowledge

Katherine Goode, Daniel Ries, Kellie McClernon

The 2022 National Defense Strategy of the United States listed climate change as a serious threat to national security. Climate intervention methods, such as stratospheric aerosol injection, have been proposed as mitigation strategies, but the downstream effects of such actions on a complex climate system are not well understood. The development of algorithm

Jiaming Hu, Shrutheesh R. Iyer, Henrik I. Christensen

Due to their complexity, foliated structure problems often pose intricate challenges to task and motion planning in robotics manipulation. To counter this, our study presents the ``Foliated Repetition Roadmap.'' This roadmap assists task and motion planners by transforming the complex foliated structure problem into a more accessible graph format. By leverag

Niven Achenjang

Let $K$ be the function field of a smooth curve $B$ over a finite field $k$ of arbitrary characteristic. We prove that the average size of the $2$-Selmer groups of elliptic curves $E/K$ is at most $1+2\zeta_B(2)\zeta_B(10)$, where $\zeta_B$ is the zeta function of the curve $B$. In particular, in the limit as $q=\#k\to\infty$ (with the genus $g(B)$ fixed), w

Benjamin Jourdain, Kexin Shao

In this note, we complete the analysis of the Martingale Wasserstein Inequality started in arXiv:2011.11599 by checking that this inequality fails in dimension $d\ge 2$ when the integrability parameter $\rho$ belongs to $[1,2)$ while a stronger Maximal Martingale Wasserstein Inequality holds whatever the dimension $d$ when $\rho\ge 2$.

Seungone Kim, Jamin Shin, Yejin Cho, Joel Jang

Recently, using a powerful proprietary Large Language Model (LLM) (e.g., GPT-4) as an evaluator for long-form responses has become the de facto standard. However, for practitioners with large-scale evaluation tasks and custom criteria in consideration (e.g., child-readability), using proprietary LLMs as an evaluator is unreliable due to the closed-source nat

A. N. Ormondroyd, W. J. Handley, M. P. Hobson, A. N. Lasenby

We provide a nested sampling analysis of the combination of CMB lensing experiments with other cosmological measurements. Nested samples can be used to compute global consistency statistics between datasets. This is demonstrated for CMB lensing and Baryon Acoustic Oscillations which are uncorrelated, and the correlated case between ACT DR6 and NPIPE lensing.

Julian Schulz, Georg von Freymann

A light beam carrying orbital angular momentum (OAM) is characterized by a helical phase-front that winds around the center of the beam. These beams have unique properties that have found numerous applications. In the field of data transmission, they represent a degree of freedom that could potentially increase capacity by a factor of several distinct OAM mo

Cristina Gava, Aron Vekassy, Matthew Cavorsi, Stephanie Gil

We introduce the concept of community consensus in the presence of malicious agents using a well-known median-based consensus algorithm. We consider networks that have multiple well-connected regions that we term communities, characterized by specific robustness and minimum degree properties. Prior work derives conditions on properties that are necessary and

Yuanchun Shen, Ruotong Liao, Zhen Han, Yunpu Ma

While multi-modal models have successfully integrated information from image, video, and audio modalities, integrating graph modality into large language models (LLMs) remains unexplored. This discrepancy largely stems from the inherent divergence between structured graph data and unstructured text data. Incorporating graph knowledge provides a reliable sour

Alexandr Kostochka, Jingwei Xu, Xuding Zhu

A graph $G$ is $(1,3)$-colorable if its vertices can be partitioned into subsets $V_1$ and $V_2$ so that every vertex in $G[V_1]$ has degree at most $1$ and every vertex in $G[V_2]$ has degree at most $3$. We prove that every graph with maximum average degree at most 28/9 is $(1, 3)$-colorable.

Thomas Krämer, Marco Maculan

We prove the Shafarevich conjecture for very irregular varieties of dimension less than half the dimension of their Albanese variety, subject to some mild numerical conditions. Our proof relies on the Lawrence-Venkatesh method as in the work of Lawrence-Sawin, together with the big monodromy criterion from our work with Javanpeykar and Lehn.

Daniel C. Hackett, Dimitra A. Pefkou, Phiala E. Shanahan

The gravitational form factors (GFFs) of a hadron encode fundamental aspects of its structure, including its shape and size as defined from e.g., its energy density. This work presents a determination of the flavor decomposition of the GFFs of the proton from lattice QCD, in the kinematic region $0\leq -t\leq 2~\text{GeV}^2$. The decomposition into up-, down

Mohit Chandra, Anush Mattapalli, Munmun De Choudhury

The proliferation of online misinformation has emerged as one of the biggest threats to society. Considerable efforts have focused on building misinformation detection models, still the perils of misinformation remain abound. Mitigating online misinformation and its ramifications requires a holistic approach that encompasses not only an understanding of its

Mansi Padave, Sanchayeeta Borthakur, Hansung B. Gim, David Thilker

We explore the growth of the stellar disks in 14 nearby spiral galaxies as part of the Deciphering the Interplay between the Interstellar medium, Stars, and the Circumgalactic medium (DIISC) survey. We study the radial distribution of specific star formation rates (sSFR) and investigate the ratio of the difference in the outer and inner sSFR ($\Delta_{sSFR}~

Alan J. Cain, António Malheiro, Tânia Paulista

Cameron, et al. determined the maximum size of a null subsemigroup of the full transformation semigroup $\mathcal{T}(X)$ on a finite set $X$ and provided a description of the null semigroups that achieve that size. In this paper we extend the results on null semigroups (which are commutative) to commutative nilpotent semigroups. Using a mixture of algebraic

Liheng Yao, Robert L. Jack

We investigate the nucleation dynamics of the three-dimensional random field Ising model (RFIM) under an external field. We use umbrella sampling to compute the free-energy cost of a critical nucleus, and use forward flux sampling for the direct estimation of nucleation rates. For moderate to strong disorder, our results indicate that the size of the nucleat

Arthur Chatton, Michèle Bally, Renée Lévesque, Ivana Malenica

Obtaining continuously updated predictions is a major challenge for personalised medicine. Leveraging combinations of parametric regressions and machine learning approaches, the personalised online super learner (POSL) can achieve such dynamic and personalised predictions. We adapt POSL to predict a repeated continuous outcome dynamically and propose a new w

Pan Chen, Yanheng Ding, Qi Guo, Huayang Wang

In this paper, we investigate the nonrelativistic limit of normalized solutions to a nonlinear Dirac equation as given below: \begin{equation*} \begin{cases} &-i c\sum\limits_{k=1}^3\alpha_k\partial_k u +mc^2 \beta {u}- \Gamma * (K |{u}|^\kappa) K|{u}|^{\kappa-2}{u}- P |{u}|^{s-2}{u}=\omega {u}, \\ &\displaystyle\int_{\mathbb{R}^3}\vert u \vert^2 dx =1. \end

Jérôme Dorignac, Fred Geniet, Estelle Pitard

We address the question of the time needed by $N$ particles, initially located on the first sites of a finite 1D lattice of size $L$, to exit that lattice when they move according to a TASEP transport model. Using analytical calculations and numerical simulations, we show that when $N \ll L$, the mean exit time of the particles is asymptotically given by $T_

E. M. Osenkov, O. V. Pochinka

In this paper, we consider a class of Morse-Smale diffeomorphisms defined on a closed 3-manifold (non-necessarily orientable) under the assumption that all their saddle points have the same dimension of the unstable manifolds. The simplest example of such diffeomorphisms is the well-known ``source-sink'' or ``north pole - south pole'' diffeomorphism, whose n

Siyuan Cheng, Bozhong Tian, Qingbin Liu, Xi Chen

In this paper, we focus on editing Multimodal Large Language Models (MLLMs). Compared to editing single-modal LLMs, multimodal model editing is more challenging, which demands a higher level of scrutiny and careful consideration in the editing process. To facilitate research in this area, we construct a new benchmark, dubbed MMEdit, for editing multimodal LL

Junaid Majeed Bhat

The conductance at the band edges of one-dimensional fermionic wires, with $N$ sites, has been shown to have subdiffusive $(1/N^2)$ behavior. We investigate this issue in two-dimensional fermionic wires described by a hopping model on an $N_x\times N_y$ rectangular lattice comprised of vertical chains with a Hermitian intra-chain and inter-chain hopping matr

Wayne Lin, Georgios Piliouras, Ryann Sim, Antonios Varvitsiotis

As quantum processors advance, the emergence of large-scale decentralized systems involving interacting quantum-enabled agents is on the horizon. Recent research efforts have explored quantum versions of Nash and correlated equilibria as solution concepts of strategic quantum interactions, but these approaches did not directly connect to decentralized adapti

Naoki Imai, Hiroki Kato, Alex Youcis

For the integral canonical model $\mathscr{S}_{\mathsf{K}^p}$ of a Shimura variety $\mathrm{Sh}_{\mathsf{K}_0\mathsf{K}^p}(\mathbf{G},\mathbf{X})$ of abelian type at hyperspecial level $K_0=\mathcal{G}(\mathbb{Z}_p)$, we construct a prismatic $F$-gauge model for the `universal' $\mathcal{G}(\mathbb{Z}_p)$-local system on $\mathrm{Sh}_{\mathsf{K}_0\mathsf{K}^

Laura Didyk, Brayden Yarish, Michael A. Beck, Christopher P. Bidinosti

Learning curves are a measure for how the performance of machine learning models improves given a certain volume of training data. Over a wide variety of applications and models it was observed that learning curves follow -- to a large extent -- a power law behavior. This makes the performance of different models for a given task somewhat predictable and ope

Daniel Monclair

We study the geometry of a weak Riemannian metric on the infinite dimensional manifold of compact spacelike Cauchy hypersurfaces in a globally hyperbolic spacetime. We show that the geodesic distance (i.e. the infimum of lengths of paths between two given points) is positive, and that the sectional curvature is well defined and non-positive.

Sonaldeep Halder, Anish Dey, Chinmay Shrikhande, Rahul Maitra

The development of various dynamic ansatz-constructing techniques has ushered in a new era, rendering the practical exploitation of Noisy Intermediate-Scale Quantum (NISQ) hardware for molecular simulations increasingly viable. However, they exhibit substantial measurement costs during their execution. This work involves the development of a novel protocol t

Maurice Chiodo, Dennis Müller, Rehan Shah

The resources compiled in this document provide an approach to embed and teach Ethics in Mathematics at the undergraduate level. We provide mathematical exercises and homework problems that teach students ethical awareness and transferable skills, for many of the standard courses in the first and second years of a university degree in mathematics or related

Olivier Compte

We propose a belief-formation model where agents attempt to discriminate between two theories, and where the asymmetry in strength between confirming and disconfirming evidence tilts beliefs in favor of theories that generate strong (and possibly rare) confirming evidence and weak (and frequent) disconfirming evidence. In our model, limitations on informatio

Rui Zhao, Yuchao Gu, Jay Zhangjie Wu, David Junhao Zhang

Large-scale pre-trained diffusion models have exhibited remarkable capabilities in diverse video generations. Given a set of video clips of the same motion concept, the task of Motion Customization is to adapt existing text-to-video diffusion models to generate videos with this motion. For example, generating a video with a car moving in a prescribed manner

Max Morrison, Pranav Pawar, Nathan Pruyne, Jennifer Cole

The prominence of a spoken word is the degree to which an average native listener perceives the word as salient or emphasized relative to its context. Speech prominence estimation is the process of assigning a numeric value to the prominence of each word in an utterance. These prominence labels are useful for linguistic analysis, as well as training automate

Hussein Nassar, Phillip Brucks

Willis elasticity is an effective medium theory for linearly elastic composites that incorporates an unusual coupling between stress and velocity, as well as between momentum and strain. Interest in the theory peaked following the discovery that its formulation is invariant under curvilinear changes of coordinates and that, consequently, it can be used to in

Chengcheng Zhao, Xiangqi Liu, Jinjin Wang, Chunqiang Xu

Recently PdTe was identified as a spin-orbit coupled topological Dirac semimetal and was claimed to exhibit both bulk-nodal and surface-nodeless superconducting gaps. Here we report the ultralow-temperature thermal conductivity measurements on PdTe single crystals with $T_c$ = 4.5 K to investigate its superconducting gap structure. It is found that the resid

Yongchao Zhou, Kaifeng Lyu, Ankit Singh Rawat, Aditya Krishna Menon

Speculative decoding (SD) accelerates large language model inference by employing a faster draft model for generating multiple tokens, which are then verified in parallel by the larger target model, resulting in the text generated according to the target model distribution. However, identifying a compact draft model that is well-aligned with the target model

Giulio Romani

We study the existence of positive solutions for a class of systems which strongly couple a quasilinear Schr\"odinger equation driven by a weighted $N$-Laplace operator and without the mass term, and a higher-order fractional Poisson equation. Since the system is considered in $\mathbb R^N$, the limiting case for the Sobolev embedding, we consider nonlineari

Runxue Bao, Yiming Sun, Yuhe Gao, Jindong Wang

The application of transfer learning, leveraging knowledge from source domains to enhance model performance in a target domain, has significantly grown, supporting diverse real-world applications. Its success often relies on shared knowledge between domains, typically required in these methodologies. Commonly, methods assume identical feature and label space

Xuebing Hao, Shuai Yang, Baode Li

Let $0<\alpha<1$. We obtain the boundedness of the discrete fractional Hardy-Littlewood maximal operators ${\mathcal M}_\alpha$ on discrete weighted Lebesgue spaces. From this and a discrete version of Whitney decomposition theorem, we deduce the boundedness of the discrete Riesz potentials $I_\alpha$ on discrete weighted Lebesgue spaces. The boundedness of