April 2024 arXiv papers — page 162

Chenwei Xu, Yu-Chao Huang, Jerry Yao-Chieh Hu, Weijian Li

We introduce the \textbf{B}i-Directional \textbf{S}parse \textbf{Hop}field Network (\textbf{BiSHop}), a novel end-to-end framework for deep tabular learning. BiSHop handles the two major challenges of deep tabular learning: non-rotationally invariant data structure and feature sparsity in tabular data. Our key motivation comes from the recent established con

Q. Faure, A. Toschi, J. R. Soh, E. Lhotel

We report a resonant inelastic X-ray scattering study on a single crystal of a non-stoichiometric pyrochlore iridate Tb$_{2+x}$Ir$_{2-x}$O$_{7-y}$ ($x \simeq 0.25$) that magnetically orders at $T_{\rm{N}}\simeq 50$ K. We find that the strength of the spin-orbit coupling and the trigonal distortion of the IrO$_6$ octahedra are comparable with the ones obtaine

Jerry Yao-Chieh Hu, Pei-Hsuan Chang, Robin Luo, Hong-Yu Chen

We introduce an Outlier-Efficient Modern Hopfield Model (termed $\mathrm{OutEffHop}$) and use it to address the outlier inefficiency problem of {training} gigantic transformer-based models. Our main contribution is a novel associative memory model facilitating \textit{outlier-efficient} associative memory retrievals. Interestingly, this memory model manifest

Dennis Wu, Jerry Yao-Chieh Hu, Teng-Yun Hsiao, Han Liu

We propose a two-stage memory retrieval dynamics for modern Hopfield models, termed $\mathtt{U\text{-}Hop}$, with enhanced memory capacity. Our key contribution is a learnable feature map $\Phi$ which transforms the Hopfield energy function into kernel space. This transformation ensures convergence between the local minima of energy and the fixed points of r

César Galindo, Julia Plavnik, Eric C. Rowell

We construct all integral non-group-theoretical modular categories of dimension $p^2q^2$, where $p$ and $q$ are distinct prime numbers, establishing that a necessary and sufficient condition for their existence is that $p \mid q+1$, and their rank is $p^2 + \frac{q^2 - 1}{p}$.

C. B. Aberlé

Parametricity is a key metatheoretic property of type systems, which implies strong uniformity & modularity properties of the structure of types within systems possessing it. In recent years, various systems of dependent type theory have emerged with the aim of expressing such parametric reasoning in their internal logic, toward the end of solving various pr

Zhu-Xing Liang, Yi Liang

Since the discovery of pulsars, the rotating-lighthouse model has been the choice of model to explain the radiation pulsation of pulsars. After discovering that some main sequence stars (e.g., CU Virginis) and ultracool dwarfs (e.g., TVLM 513-46546) also behave like pulsars, the lighthouse model was again adopted to explain their pulse signals. Our research

Zahra Mousavi, Chadni Islam, Kristen Moore, Alsharif Abuadbba

The increasing trend of using Large Language Models (LLMs) for code generation raises the question of their capability to generate trustworthy code. While many researchers are exploring the utility of code generation for uncovering software vulnerabilities, one crucial but often overlooked aspect is the security Application Programming Interfaces (APIs). API

Akshat Pandey

In this short paper we make use of the recent covariant extension of the generalised uncertainty principle to study the corrections to the vacuum energy of the simplest scalar quantum field theory. We then calculate the modifications to the Casimir effect that such a correction to the vacuum energy would bring about. We emphasise that these corrections are i

Chris Vaisnor

The power of fuzz testing lies in its random, often brute-force, generation and execution of inputs to trigger unexpected behaviors and vulnerabilities in software applications. However, given the reality of infinite possible input sequences, pursuing all test combinations would not only be computationally expensive, but practically impossible. Approximate B

Bojan Arbutina, Surjit Wadhwa

Contact binaries are close binary systems in which both components fill their inner Roche lobes so that the stars are in direct contact and in potential mass and energy exchange. The most common such systems of low-mass are the so-called W UMa-type. In the last few years, there is a growing interest of the astronomical community in stellar mergers, primarily

Makesh Narsimhan Sreedhar, Traian Rebedea, Shaona Ghosh, Jiaqi Zeng

Recent advancements in instruction-tuning datasets have predominantly focused on specific tasks like mathematical or logical reasoning. There has been a notable gap in data designed for aligning language models to maintain topic relevance in conversations - a critical aspect for deploying chatbots to production. We introduce the CantTalkAboutThis dataset to

Yirui Wang, Qinji Yu, Ke Yan, Haoshen Li

Lymph node (LN) assessment is a critical, indispensable yet very challenging task in the routine clinical workflow of radiology and oncology. Accurate LN analysis is essential for cancer diagnosis, staging, and treatment planning. Finding scatteredly distributed, low-contrast clinically relevant LNs in 3D CT is difficult even for experienced physicians under

E. W. D. Dantas, G. Alencar, I. Guedes, Milko Estrada

In this work, we utilize the dynamic invariant method to obtain a solution for the time-dependent Schr\"odinger equation, aiming to explore the quantum theory of a $p$-form gauge field propagating in $D$-dimensional de Sitter spacetimes. Thus, we present a generalization, through the use of $p$-form gauge fields, of the quantization procedure for the scalar,

Zhangdie Yuan, Eric Chamoun, Rami Aly, Chenxi Whitehouse

This paper introduces PRobELM (Plausibility Ranking Evaluation for Language Models), a benchmark designed to assess language models' ability to discern more plausible from less plausible scenarios through their parametric knowledge. While benchmarks such as TruthfulQA emphasise factual accuracy or truthfulness, and others such as COPA explore plausible scena

Hendrik J. Brockmann, Letao Huang, Felix Hainer, Danyellen Galindo

Quantum chemical methods and time-resolved laser spectroscopy are employed to elucidate ultrafast charge separation processes in triphenylamine (TPA) derivatives upon photoexcitation. When changing the ambient solvent from generic ones to those capable of accepting electrons, such as chloroform, a vastly extended and multifaceted photochemistry is observed.

Nirmalie Wiratunga, Ramitha Abeyratne, Lasal Jayawardena, Kyle Martin

Retrieval-Augmented Generation (RAG) enhances Large Language Model (LLM) output by providing prior knowledge as context to input. This is beneficial for knowledge-intensive and expert reliant tasks, including legal question-answering, which require evidence to validate generated text outputs. We highlight that Case-Based Reasoning (CBR) presents key opportun

Brian Y. Cho, Daniel S. Esser, Jordan Thompson, Bao Thach

Tendon-driven continuum robots have been gaining popularity in medical applications due to their ability to curve around complex anatomical structures, potentially reducing the invasiveness of surgery. However, accurate modeling is required to plan and control the movements of these flexible robots. Physics-based models have limitations due to unmodeled effe

James T. Wheeler

Ehlers, Pirani, and Schild argued that measurements of null and timelike geodesics yield Weyl and projective connections, respectively, with compatibility in the lightlike limit giving an integrable Weyl connection. Their conclusions hold only for a 4-dim representation of the conformal connection on the null cone, and by restricting reparameterizations of t

Xiaoyan Zhou, Anil Ufuk Batmaz, Adam S. Williams, Dylan Schreiber

Immersive environments enable users to engage in embodied interaction, enhancing the sensemaking processes involved in completing tasks such as immersive analytics. Previous comparative studies on immersive analytics using augmented and virtual realities have revealed that users employ different strategies for data interpretation and text-based analytics dep

Sabee Grewal, Vishnu Iyer, William Kretschmer, Daniel Liang

We define a quantum learning task called agnostic tomography, where given copies of an arbitrary state $\rho$ and a class of quantum states $\mathcal{C}$, the goal is to output a succinct description of a state that approximates $\rho$ at least as well as any state in $\mathcal{C}$ (up to some small error $\varepsilon$). This task generalizes ordinary quantu

Dibyayan Chakraborty, Yann Vaxès

For an integer $k\geq 1$, the objective of \textsc{$k$-Geodesic Center} is to find a set $\mathcal{C}$ of $k$ isometric paths such that the maximum distance between any vertex $v$ and $\mathcal{C}$ is minimised. Introduced by Gromov, \emph{$\delta$-hyperbolicity} measures how treelike a graph is from a metric point of view. Our main contribution in this pape

Akaki Tikaradze

In this paper we fully solve the Morita equivalence problem for symplectic reflection algebras associated to direct products of finite subgroups of $SL_2(\mathbb{C})$. Namely, given a pair of such symplectic reflection algebras $H_c, H_{c'}$,then $H_c$ is Morita equivalent to $H_c'$ if and only if they are related by a standard Morita equivalence. We also es

Peng Zheng, Nahom Worku, Marlena Bannick, Joseph Dielemann

Benchmarking tools, including stochastic frontier analysis (SFA), data envelopment analysis (DEA), and its stochastic extension (StoNED) are core tools in economics used to estimate an efficiency envelope and production inefficiencies from data. The problem appears in a wide range of fields -- for example, in global health the frontier can quantify efficienc

Caleb Sullivan, Pubudu Senanayake, Michael J. Plank

Accounting for population age structure and age-specific contact patterns is crucial for accurate modelling of human infectious disease dynamics and impact. A common approach is to use contact matrices, which estimate the number of contacts between individuals of different ages. These contact matrices are frequently based on data collected from populations w

Nhat A. Nghiem, Tzu-Chieh Wei

Nonlinear equations are challenging to solve due to their inherently nonlinear nature. As analytical solutions typically do not exist, numerical methods have been developed to tackle their solutions. In this article, we give a quantum algorithm for solving a system of nonlinear algebraic equations, in which each equation is a multivariate polynomial of known

Otacilio B. L. Neto, Michela Mulas, Francesco Corona

This work proposes a policy learning algorithm for seeking generalised feedback Nash equilibria (GFNE) in $N_P$-player noncooperative dynamic games. We consider linear-quadratic games with stochastic dynamics and design a best-response dynamics in which players update and broadcast a parametrisation of their state-feedback policies. Our approach leverages th

Damián H. Zanette, Inés Samengo

The Central Limit Theorem states that, in the limit of a large number of terms, an appropriately scaled sum of independent random variables yields another random variable whose probability distribution tends to a stable distribution. The condition of independence, however, only holds in real systems as an approximation. To extend the theorem to more general

Lenin M. Flores Ramírez, Leon P. J. Kamp, Herman J. H. Clercx, Matias Duran-Matute

We report on an investigation of the vertical transport of tracer particles released within a shallow, continuously-forced flow by means of numerical simulations. The investigation is motivated by the shallow flows encountered in many environmental situations and inspired by the laboratory experiments conducted in electromagnetically forced shallow fluid lay

Pierre Amenoagbadji, Sonia Fliss, Patrick Joly

We are interested in the Helmholtz equation in a junction of two periodic half-spaces. When the overall medium is periodic in the direction of the interface, Fliss and Joly (2019) proposed a method which consists in applying a partial Floquet-Bloch transform along the interface, to obtain a family of waveguide problems parameterized by the Floquet variable.

Anindita Nath, Savannah Mwesigwa, Yulin Dai, Xiaoqian Jiang

Summary: The vast generation of genetic data poses a significant challenge in efficiently uncovering valuable knowledge. Introducing GENEVIC, an AI-driven chat framework that tackles this challenge by bridging the gap between genetic data generation and biomedical knowledge discovery. Leveraging generative AI, notably ChatGPT, it serves as a biologist's 'cop

Zhiyue Zhang, Yao Zhao, Yanxun Xu

In applications such as biomedical studies, epidemiology, and social sciences, recurrent events often co-occur with longitudinal measurements and a terminal event, such as death. Therefore, jointly modeling longitudinal measurements, recurrent events, and survival data while accounting for their dependencies is critical. While joint models for the three comp

Chun-Hui Liu, Fu Li, Shengwang Du, Jianming Wen

In recent years, significant progress has been made in utilizing the divergence of spectrum response rate at the exceptional point (EP) for sensing in classical systems, while the use and characterization of quantum EPs for sensing have been largely unexplored. For a quantum EP sensor, an important issue is the relation between the order of the quantum EP an

Jorge Luis Miró-Zárate, Felipe Cervantes-Sodi, Milton Carlos Elias-Espinosa, Skarleth García-Trujillo

Incorporating a monolayer of WS$_2$ via interface engineering enhances the overall physical properties of a FAPbI3 perovskite based heterostructure. FAPbI$_3$/WS$_2$/TiO$_2$/ITO and FAPbI$_3$/TiO$_2$/ITO heterostructures were analyzed by UV-Vis spectroscopy, X-ray diffraction, scanning electron microscopy and atomic force microscopy. The configuration with W

Georg Bergner, Stefano Piemonte, Mithat Ünsal

We present our investigations of SU($N$) adjoint QCD in two dimensions with one Majorana fermion on the lattice. We determine the relevant parameter range for the simulations with Wilson fermions and present results for Polyakov loop, chiral condensate, and string tension. In the theory with massive fermions, all observables we checked show qualitative agree

Mukund Telukunta, Sukruth Rao, Gabriella Stickney, Venkata Sriram Siddardh Nadendla

Modern kidney placement incorporates several intelligent recommendation systems which exhibit social discrimination due to biases inherited from training data. Although initial attempts were made in the literature to study algorithmic fairness in kidney placement, these methods replace true outcomes with surgeons' decisions due to the long delays involved in

Elham Amin Mansour, Ozan Unal, Suman Saha, Benjamin Bejar

The increasing relevance of panoptic segmentation is tied to the advancements in autonomous driving and AR/VR applications. However, the deployment of such models has been limited due to the expensive nature of dense data annotation, giving rise to unsupervised domain adaptation (UDA). A key challenge in panoptic UDA is reducing the domain gap between a labe

Shaoor Munir, Konrad Kollnig, Anastasia Shuba, Zubair Shafiq

This Article examines Google's dominance of the browser market, highlighting how Google's Chrome browser plays a critical role in reinforcing Google's dominance in other markets. While Google portrays Chrome as a neutral platform built on open-source technologies, this Article shows that Chrome is instrumental in Google's strategy to reinforce its dominance

Carlos Floyd, Aaron R. Dinner, Suriyanarayanan Vaikuntanathan

Standard approaches to controlling dynamical systems involve biologically implausible steps such as backpropagation of errors or intermediate model-based system representations. Recent advances in machine learning have shown that "imperfect" feedback of errors during training can yield test performance that is similar to using full backpropagated errors, pro

Liliana Rivera Sandoval, Diogo Belloni, Miriam Ramos Arevalo

Based on the current detectable cataclysmic variable (CV) population in Galactic globular clusters (GCs), we show that there is not a clear relation between the number of sources per unit of mass and the stellar encounter rate, the cluster mass, or the cluster central density. If any, only in the case of core-collapsed GCs could there be an anticorrelation w

Mónica Rico Martínez, Juan Carlos Vesga Ferreira, Joel Carroll Vargas, María Consuelo Rodríguez Niño

The equitable distribution of resources in a network is a complex process, considering that not all nodes have the same requirements, and the In-Band On-Channel (IBOC) hybrid transmission system is no exception. The IBOC system utilizes a hybrid in-band transmission to simultaneously broadcast analog and digital audio over the FM band. This article proposes

Dongwei Jiang, Jingyu Zhang, Orion Weller, Nathaniel Weir

Can LLMs consistently improve their previous outputs for better results? For this to be true, LLMs would need to be better at discriminating among previously-generated alternatives, than generating initial responses. We explore the validity of this hypothesis in practice. We first formulate a unified framework that allows us to compare the generative and dis

Scott Delhommer, Domonkos F. Vamossy

This paper presents quasi-experimental research examining the effect of both local and state anti-discrimination laws on sexual orientation on the labor supply and wages of lesbian, gay, and bisexual (LGB) workers. To do so, we use the American Community Survey data on household composition to infer sexual orientation and combine this with a unique panel dat

Andrej Kolar-Požun, Mitja Jančič, Miha Rot, Gregor Kosec

When solving partial differential equations on scattered nodes using the Radial Basis Function-generated Finite Difference (RBF-FD) method, one of the parameters that must be chosen is the stencil size. Focusing on Polyharmonic Spline RBFs with monomial augmentation, we observe that it affects the approximation accuracy in a particularly interesting way - th

Domonkos F. Vamossy

I explore the relationship between investor emotions expressed on social media and asset prices. The field has seen a proliferation of models aimed at extracting firm-level sentiment from social media data, though the behavior of these models often remains uncertain. Against this backdrop, my study employs EmTract, an open-source emotion model, to test wheth

Rogerio Deienno, David Nesvorny, Matthew S. Clement, William F. Bottke

The main asteroid belt (MAB) is known to be primarily composed of objects from two distinct taxonomic classes, generically defined here as S- and C-complex. The former probably originated from the inner solar system (interior to Jupiter's orbit), while the latter probably from the outer solar system. Following this definition, (4) Vesta, a V-type residing in

Justin Sitler, Srikarran Sowrirajan, Brendan Englot, Long Wang

In an effort to lower the barrier to entry in underwater manipulation, this paper presents an open-source, user-friendly framework for bimanual teleoperation of a light-duty underwater vehicle-manipulator system (UVMS). This framework allows for the control of the vehicle along with two manipulators and their end-effectors using two low-cost haptic devices.

Xu Pan, Aaron Philip, Ziqian Xie, Odelia Schwartz

Self-attention in vision transformers is often thought to perform perceptual grouping where tokens attend to other tokens with similar embeddings, which could correspond to semantically similar features of an object. However, attending to dissimilar tokens can be beneficial by providing contextual information. We propose to analyze the query-key interaction

Juanwu Lu, Can Cui, Yunsheng Ma, Aniket Bera

Safety and robustness are crucial factors in developing trustworthy autonomous vehicles. One essential aspect of addressing these factors is to equip vehicles with the capability to predict future trajectories for all moving objects in the surroundings and quantify prediction uncertainties. In this paper, we propose the Sequential Neural Variational Agent (S

Maria Loseva, Alexandr Prishlyak, Kateryna Semenovych, Yuliia Volianiuk

We describe all possible topological structures of Morse flows and typical one-parametric gradient bifurcation on the M\"obius strip in the case that the number of singular point of flows is at most six. To describe structures, we use the separatrix diagrams of flows. The saddle-node bifurcation is specified by selecting a separatrix in the diagram of the Mo

Lemei Zhang, Peng Liu, Yashar Deldjoo, Yong Zheng

The emergence of Large Language Models (LLMs) has achieved tremendous success in the field of Natural Language Processing owing to diverse training paradigms that empower LLMs to effectively capture intricate linguistic patterns and semantic representations. In particular, the recent "pre-train, prompt and predict" training paradigm has attracted significant

Chin Tseng, Arran Zeyu Wang, Ghulam Jilani Quadri, Danielle Albers Szafir

Existing guidelines for categorical color selection are heuristic, often grounded in intuition rather than empirical studies of readers' abilities. While design conventions recommend palettes maximize hue differences, more recent exploratory findings indicate other factors, such as lightness, may play a role in effective categorical palette design. We conduc

Jie Yao, Edward Valachovic

Electric generation and consumption are an essential component of contemporary living, influencing diverse facets of our daily routines, convenience, and economic progress. There is a high demand for characterizing the periodic pattern of electricity consumption. VBPBB employs a bandpass filter aligned to retain the frequency of a PC component and eliminatin

Kaique Matias de Andrade Roberto, Hugo Luiz Mariano

In this ongoing work, we extend to a class of well-behaved pre-special hyperfields the work of J. Min\'a\v c and Spira (\cite{minac1996witt}) that describes a (pro-2)-group of a field extension that encodes the quadratic form theory of a given field $F$: in \cite{adem1999cohomology} it is shown that its associated cohomology ring contains a copy of the cohom

Sabyasachi Sahoo, Mostafa ElAraby, Jonas Ngnawe, Yann Pequignot

Test Time Adaptation (TTA) addresses the problem of distribution shift by adapting a pretrained model to a new domain during inference. When faced with challenging shifts, most methods collapse and perform worse than the original pretrained model. In this paper, we find that not all layers are equally receptive to the adaptation, and the layers with the most

Muqiao Huang, Ruodu Wang

We establish a profound connection between coherent risk measures, a prominent object in quantitative finance, and uniform integrability, a fundamental concept in probability theory. Instead of working with absolute values of random variables, which is convenient in studying integrability, we work directly with random loses and gains, which have clear financ

Niklas Scheuler, Patric Rommel, Jörg Main, Pavel A. Belov

Rydberg excitons are the solid-state analog of Rydberg atoms and can, e.g., for cuprous oxide, easily reach a large size in the region of $\mu$m for principal quantum numbers up to $n=25$. The fabrication of quantum well-like structures in the crystal leads to quantum confinement effects and opens the possibility to study a crossover from three-dimensional t

André Achim

Blind factor recovery follows from the principle that the signal of variables exclusive to a factor can be combined in a contrast (weighted sum) that cancels their factor contributions, leaving only a compound of the variables unique variances. Successful contrasts, uncorrelated with any remaining variable, become the signature of factors with at least two u

Nataliya Goncharuk, Michael Yampolsky

Authomorphic or $s$-measures for circle diffeomorphisms were introduced by R.Douady and J.-C. Yoccoz in 1999. They have multiple applications in circle dynamics, with the case $s=-1$ being particularly important for describing conjugacy classes. In arxiv:2306.13524, E. de Faria, P. Guarino and B. Nussenzveig proved existence and uniqueness of automorphic $s$

Theodoros Papanikolaou, Shreya Banerjee, Yi-Fu Cai, Salvatore Capozziello

We present a novel model-independent generic mechanism for primordial black hole formation within the context of non-singular matter bouncing cosmology. In particular, considering a short duration transition from the matter contracting phase to the Hot Big Bang expanding Universe, we find naturally enhanced curvature perturbations on very small scales which

Simon Weber, Barış Zöngür, Nikita Araslanov, Daniel Cremers

Hierarchy is a natural representation of semantic taxonomies, including the ones routinely used in image segmentation. Indeed, recent work on semantic segmentation reports improved accuracy from supervised training leveraging hierarchical label structures. Encouraged by these results, we revisit the fundamental assumptions behind that work. We postulate and

Sander Vandenhaute, Tom Braeckevelt, Pieter Dobbelaere, Massimo Bocus

The efficiency of atomic simulations of materials and molecules can rapidly deteriorate when large free energy barriers exist between local minima. We propose smooth basin classification, a universal method to define reaction coordinates based on the internal feature representation of a graph neural network. We achieve high data efficiency by exploiting thei

E. Nasedkin, P. Mollière, S. Lacour, M. Nowak

With four companions at separations from 16 to 71 au, HR 8799 is a unique target for direct imaging, presenting an opportunity for the comparative study of exoplanets with a shared formation history. Combining new VLTI/GRAVITY observations obtained within the ExoGRAVITY program with archival data, we perform a systematic atmospheric characterisation of all f

Anli du Preez, Peter A. Beling, Tyler Cody

The machine learning formulation of online learning is incomplete from a systems theoretic perspective. Typically, machine learning research emphasizes domains and tasks, and a problem solving worldview. It focuses on algorithm parameters, features, and samples, and neglects the perspective offered by considering system structure and system behavior or dynam

Noah Golowich, Ankur Moitra, Dhruv Rohatgi

Supervised learning is often computationally easy in practice. But to what extent does this mean that other modes of learning, such as reinforcement learning (RL), ought to be computationally easy by extension? In this work we show the first cryptographic separation between RL and supervised learning, by exhibiting a class of block MDPs and associated decodi

Carlo Ciccarella, Robert C. Dalang, Laura Vinckenbosch

We develop a mathematical model for sailboat navigation that captures the essential features of the problem and can provide insights that might not be available otherwise. In our model, the motion of the sailboat, which would travel at speed $v>0$ in a constant wind, is the solution of a system of two stochastic differential equations driven by a Brownian mo

Christian Olivera, Marielle Simon

This paper considers a large class of nonlinear integro-differential scalar equations which involve an anomalous diffusion (e.g. driven by a fractional Laplacian) and a non-local singular convolution kernel. Each of those singular equations is obtained as the macroscopic limit of an interacting particle system modeled as N coupled stochastic differential equ

Roberta De Viti, Pierfrancesco Ingo, Isaac Sheff, Peter Druschel

Many online services rely on self-reported locations of user devices like smartphones. To mitigate harm from falsified self-reported locations, the literature has proposed location proof services (LPSs), which provide proof of a device's location by corroborating its self-reported location using short-range radio contacts with either trusted infrastructure o

Davide Bove, Lukas Panzer

Embedded and Internet-of-Things (IoT) devices are ubiquitous today, and the uprising of several botnets based on them (e.g., Mirai, Ripple20) raises issues about the security of such devices. Especially low-power devices often lack support for modern system security measures, such as stack integrity, Non-eXecutable bits or strong cryptography. In this work,

Clément Dupont

Mixed Tate motives are central objects in the study of cohomology groups of algebraic varieties and their arithmetic invariants. They also play a crucial role in a wide variety of questions related to multiple zeta values and polylogarithms, algebraic K-theory, hyperbolic geometry, and particle physics among others. This survey article is an introduction to

Tyler Cody, Bingtong Li, Peter A. Beling

This paper addresses the urgent need for messaging standards in the operational test and evaluation (T&E) of machine learning (ML) applications, particularly in edge ML applications embedded in systems like robots, satellites, and unmanned vehicles. It examines the suitability of the IEEE Standard 1671 (IEEE Std 1671), known as the Automatic Test Markup Lang

Kaique Matias de Andrade Roberto, Hugo Luiz mariano

We build on previous work on multirings (\cite{roberto2021quadratic}) that provides generalizations of the available abstract quadratic forms theories (special groups and real semigroups) to the context of multirings (\cite{marshall2006real}, \cite{ribeiro2016functorial}). Here we raise one step in this generalization, introducing the concept of pre-special

Godofredo Iommi, Mario Ponce

We define an odometer in the Baire space. That is the non-compact space of one sided sequences of natural numbers. We go on to prove that it is topologically conjugated to the dyadic odometer restricted to an appropriate non-compact subset of the space of one sided sequences on two symbols. We extend the action of the odometer to finite words. It turns out t

Ala' Alalabi, Kirsten Morris

Finite-time linear-quadratic control of partial differential-algebraic equations (PDAEs) is considered. The discussion is restricted to those that are radial with index $0$; this corresponds to a nilpotency degree of 1. We establish the existence of a unique minimizing optimal control. A projection is used to derive a system of differential Riccati-like equa

Sergio Giardino

This paper establishes the basis of the quaternionic differential geometry ($\mathbbm H$DG) initiated in a previous article. The usual concepts of curves and surfaces are generalized to quaternionic constraints, as well as the curvature and torsion concepts, differential forms, directional derivatives and the structural equations. The analogy between the qua

Katerina Nik, Keisuke Takasao

We study Brakke's mean curvature flow with obstacles and with a right-angle boundary condition. Assuming that the obstacles have $C^{1,1}$-boundaries we prove that a weak solution exists globally in time. To show the existence we apply the phase-field method and thus investigate the singular limit of the Allen-Cahn equation with forcing term and homogeneous

Rinsuke Yamada, Takuya Nomoto, Atsushi Miyake, Toshihiro Terakawa

The thermoelectric Nernst effect of solids converts heat flow to beneficial electronic voltages. Here, using a correlated topological semimetal with high carrier mobility $\mu$ in presence of magnetic fluctuations, we demonstrate an enhancement of the Nernst effect close to a magnetic phase transition. A magnetic instability in NdAlSi modifies the carrier re

Ben Adcock, Simone Brugiapaglia, Nick Dexter, Sebastian Moraga

Learning approximations to smooth target functions of many variables from finite sets of pointwise samples is an important task in scientific computing and its many applications in computational science and engineering. Despite well over half a century of research on high-dimensional approximation, this remains a challenging problem. Yet, significant advance

James D. Shemilt, Alex Horsley, Jim M. Wild, Oliver E. Jensen

Airway constriction and blockage in obstructive lung diseases cause ventilation heterogeneity and create barriers to effective drug deposition. Established computational particle-deposition models have not accounted for these impacts of disease. We present a new particle-deposition model that calculates ventilation based on the resistance of each airway, suc

Ege C. Kaya, Abolfazl Hashemi

In this work, we treat the problem of multi-task submodular optimization from the perspective of local distributional robustness within the neighborhood of a reference distribution which assigns an importance score to each task. We initially propose to introduce a relative-entropy regularization term to the standard multi-task objective. We then demonstrate

Adriano A. Batista, Raoni S. N. Moreira, A. A. Lisboa de Souza

Here we investigate white noise squeezing in the frequency domain of classical parametrically-driven resonators with added noise. We use Green's functions to analyse the response of resonators to added noise. In one approach, we obtain the Green's function approximately using the first-order averaging method, while in the second approach, exactly, using Floq

Navnath Daundkar

We introduce and study the sequential analogue of Grant's parametrized topological complexity of group epimorphisms, which generalizes the sequential topological complexity of groups. We derive bounds for sequential parametrized topological complexity based on the cohomological dimension of certain subgroups, thereby extending the corresponding bounds for se

Ulrich Langer, Richard Löscher, Olaf Steinbach, Huidong Yang

We propose, analyze, and test new robust iterative solvers for systems of linear algebraic equations arising from the space-time finite element discretization of reduced optimality systems defining the approximate solution of hyperbolic distributed, tracking-type optimal control problems with both the standard $L^2$ and the more general energy regularization

Marija Dimitrijević Ćirić, Tajron Jurić, Nikola Konjik, Andjelo Samsarov

Within the framework of noncommutative (NC) deformation of gauge field theory by the angular twist, we first rederive the NC scalar and gauge field model from our previous papers and then generalize it to the second order in the Seiberg-Witten (SW) map. It turns out that SW expansion is finite and that it ceases at the second order in the deformation paramet

Afonso Oliveira, Nuno Fachada, João P. Matos-Carvalho

The integration of data science into Geographic Information Systems (GIS) has facilitated the evolution of these tools into complete spatial analysis platforms. The adoption of machine learning and big data techniques has equipped these platforms with the capacity to handle larger amounts of increasingly complex data, transcending the limitations of more tra

Chunxiao Li, Charlie Liu, Jonathan Chung, Zhengyang Lu

Restart policy is an important technique used in modern Conflict-Driven Clause Learning (CDCL) solvers, wherein some parts of the solver state are erased at certain intervals during the run of the solver. In most solvers, variable activities are preserved across restart boundaries, resulting in solvers continuing to search parts of the assignment tree that a

Raphael Yuster

An edge-colored rooted directed tree (aka arborescence) is path-monochromatic if every path in it is monochromatic. Let $k,\ell$ be positive integers. For a tournament $T$, let $f_T(k)$ be the largest integer such that every $k$-edge coloring of $T$ has a path-monochromatic subtree with at least $f_T(k)$ vertices and let $f_T(k,\ell)$ be the restriction to s

J. Mark Keil, Debajyoti Mondal

A disk graph is an intersection graph of disks in $\mathbb{R}^2$. Determining the computational complexity of finding a maximum clique in a disk graph is a long-standing open problem. In 1990, Clark, Colbourn, and Johnson gave a polynomial-time algorithm for computing a maximum clique in a unit disk graph. However, finding a maximum clique when disks are of

Abdullah Al Maruf, Anamika Dubey, Sandip Roy

A network-level small-signal model is developed for lossy microgrids, which considers coupled angle and voltage dynamics of inverter-based microgrids and uses a more general framework of droop controls in the inverter. It is shown that when relative resistances of the lines in the microgrid are reasonably consistent and differences of voltage angles across t

Soumyadeep Chaudhuri, Frank Ferrari

Within the path integral formalism, we compute the disk partition functions of two dimensional Liouville and JT quantum gravity theories coupled to a matter CFT of central charge $c$, with cosmological constant $\Lambda$, in the limit $c\rightarrow -\infty$, $|\Lambda|\rightarrow\infty$, for fixed $\Lambda/c$ and fixed and finite disk boundary length $\ell$,

Friedrich Eisenbrand, Lars Rohwedder, Karol Węgrzycki

We consider the problem of finding a basis of a matroid with weight exactly equal to a given target. Here weights can be discrete values from $\{-\Delta,\ldots,\Delta\}$ or more generally $m$-dimensional vectors of such discrete values. We resolve the parameterized complexity completely, by presenting an FPT algorithm parameterized by $\Delta$ and $m$ for ar

Ernesto Estevez-Rams, K. Garcia-Medina, B. Aragon-Fernandez

Dynamical systems can be analyzed as computational devices capable of performing information processing. In coupled oscillators, enlarged capabilities are expected when the set of units is formed by subsets with collective behaviour within them but weak correlation between the subsets. A system of non-linear oscillators weakly coupled in the phase approximat

Kaustubh Dhole, Eugene Agichtein

Query Reformulation(QR) is a set of techniques used to transform a user's original search query to a text that better aligns with the user's intent and improves their search experience. Recently, zero-shot QR has been shown to be a promising approach due to its ability to exploit knowledge inherent in large language models. By taking inspiration from the suc

Mahjabin Nahar, Haeseung Seo, Eun-Ju Lee, Aiping Xiong

The widespread adoption and transformative effects of large language models (LLMs) have sparked concerns regarding their capacity to produce inaccurate and fictitious content, referred to as `hallucinations'. Given the potential risks associated with hallucinations, humans should be able to identify them. This research aims to understand the human perception

Shahar Hod

It has recently been proved that a simple generalization of electromagnetism, referred to as quasitopological electromagnetic field theory, is characterized by the presence of dyonic black-hole solutions of the Einstein field equations that, in certain parameter regions, are characterized by four horizons. In the present compact paper we reveal the existence

Alex Costanzino, Pierluigi Zama Ramirez, Mirko Del Moro, Agostino Aiezzo

Anomaly Detection and Segmentation (AD&S) is crucial for industrial quality control. While existing methods excel in generating anomaly scores for each pixel, practical applications require producing a binary segmentation to identify anomalies. Due to the absence of labeled anomalies in many real scenarios, standard practices binarize these maps based on som

Carlotta Giannelli, Sofia Imperatore, Lisa Maria Kreusser, Estefanía Loayza-Romero

We present a generalized formulation for reweighted least squares approximations. The goal of this article is twofold: firstly, to prove that the solution of such problem can be expressed as a convex combination of certain interpolants when the solution is sought in any finite-dimensional vector space; secondly, to provide a general strategy to iteratively u

Qianwen Zhao, Rajarshi Roy, Chad Spurlock, Kevin Lister

Recently, there has been a growing interest in rescue robots due to their vital role in addressing emergency scenarios and providing crucial support in challenging or hazardous situations where human intervention is difficult. However, very few of these robots are capable of actively engaging with humans and undertaking physical manipulation tasks. This limi

Ege C. Kaya, Michael Hibbard, Takashi Tanaka, Ufuk Topcu

We study a pair of budget- and performance-constrained weak-submodular maximization problems. For computational efficiency, we explore the use of stochastic greedy algorithms which limit the search space via random sampling instead of the standard greedy procedure which explores the entire feasible search space. We propose a pair of stochastic greedy algorit

Vage Karakhanyan, Thierry Grosjean

Research at the frontier between optics and magnetism is revealing a wealth of innovative phenomena and avenues of exploration. Optical waves are demonstrating the capacity to induce ultrafast magnetism, while optical analogs of magnetic states, such as magnetic skyrmions, offer the prospect of novel spin-optical states. In this paper, we strengthen the syne