February 2024 arXiv papers — page 155

David Sanchez-Jimenez, Fernando Buchon-Moragues, Jose M. Bravo, Juan V. Sanchez-Perez

The conservation and authentication of pictorial artworks is considered an important part of the preservation of the cultural heritage. The use of non-destructive testing allows the obtaining of accurate information about the state of pictorial artworks, without direct contact between the equipment used and the sample. In particular, the use of this kind of

Esther Ploeger, Wessel Poelman, Miryam de Lhoneux, Johannes Bjerva

The NLP research community has devoted increased attention to languages beyond English, resulting in considerable improvements for multilingual NLP. However, these improvements only apply to a small subset of the world's languages. Aiming to extend this, an increasing number of papers aspires to enhance generalizable multilingual performance across languages

Francesco Turro, Anthony Ciavarella, Xiaojun Yao

We perform a nonperturbative calculation of the shear viscosity for $(2+1)$-dimensional SU(2) gauge theory by using the lattice Hamiltonian formulation. The retarded Green's function of the stress-energy tensor is calculated from real time evolution via exact diagonalization of the lattice Hamiltonian with a local Hilbert space truncation, and the shear visc

Cary Malkiewich, Maru Sarazola

It is well-known that the stable model structure on symmetric spectra cannot be transferred from the one on sequential spectra through the forgetful functor. We use the fibrant transfer theorem of Guetta--Moser--Sarazola--Verdugo to show it can be transferred between fibrant objects, providing a new, short and conceptual proof of its existence.

Sarah Mason, Jack Xie

This article presents conditions under which the skewed version of immaculate noncommutative symmetric functions are nonzero. The work is motivated by the quest to determine when the matrix definition of a skew immaculate function aligns with the Hopf algberaic definition. We describe a necessary condition for a skew immaculate function to include a non-zero

Jamin Kidd, Ruiqi Zhang, Shao-Kai Jian, Jianwei Sun

The widely-used Kohn-Sham implementation of density functional theory (DFT) maps a system of interacting electrons onto an auxiliary non-interacting one and is presumably inaccurate for strongly correlated materials. We present a concrete benchmark for DFT by examining the electronic ground state phase diagram of a strongly interacting chain with uneven, non

Jérémy O'Byrne, Michael E. Cates

In this article, we analyze three classes of time-reversal of a Markov process with Gaussian noise on a manifold. We first unveil a commutativity constraint for the most general of these time-reversals to be well defined. Then we give a triad of necessary and sufficient conditions for the stochastic process to be time-reversible. While most reversibility con

Md Ferdous Pervej, Andreas F. Molisch

Backhaul traffic congestion caused by the video traffic of a few popular files can be alleviated by storing the to-be-requested content at various levels in wireless video caching networks. Typically, content service providers (CSPs) own the content, and the users request their preferred content from the CSPs using their (wireless) internet service providers

Anupam Kundu, Satya N. Majumdar, Gregory Schehr

We compute exactly the full distribution of the number $m$ of local minima in a one-dimensional landscape generated by a random walk or a L\'evy flight. We consider two different ensembles of landscapes, one with a fixed number of steps $N$ and the other till the first-passage time of the random walk to the origin. We show that the distribution of $m$ is dra

Vasco Cavina, Ariane Soret, Timur Aslyamov, Krzysztof Ptaszyński

We derive a systematic approach to the thermodynamics of quantum systems based on the underlying symmetry groups. We show that the entropy of a system can be described in terms of group-theoretical quantities that are largely independent of the details of its density matrix. We apply our technique to generic $N$ identical interacting $d$-level quantum system

Yihong Ma, Xiaobao Huang, Bozhao Nan, Nuno Moniz

The yield of a chemical reaction quantifies the percentage of the target product formed in relation to the reactants consumed during the chemical reaction. Accurate yield prediction can guide chemists toward selecting high-yield reactions during synthesis planning, offering valuable insights before dedicating time and resources to wet lab experiments. While

Leonardo S. V. Santos, Zhen-Peng Xu, Jyrki Piilo, Otfried Gühne

We present a framework for quantifying information flow within general quantum processes. For this purpose, we introduce the signaling power of quantum channels and discuss its relevant operational properties. This function supports extensions to higher-order maps, enabling the evaluation of information flow in general quantum causal networks and also proces

Mert Ketenci, Iñigo Urteaga, Victor Alfonso Rodriguez, Noémie Elhadad

We propose probabilistic Shapley inference (PSI), a novel probabilistic framework to model and infer sufficient statistics of feature attributions in flexible predictive models, via latent random variables whose mean recovers Shapley values. PSI enables efficient, scalable inference over input-to-output attributions, and their uncertainty, via a variational

Lin Guan, Yifan Zhou, Denis Liu, Yantian Zha

Large-scale generative models are shown to be useful for sampling meaningful candidate solutions, yet they often overlook task constraints and user preferences. Their full power is better harnessed when the models are coupled with external verifiers and the final solutions are derived iteratively or progressively according to the verification feedback. In th

Esra Adiyeke, Yuanfang Ren, Benjamin Shickel, Matthew M. Ruppert

Background: Acute kidney injury (AKI), the decline of kidney excretory function, occurs in up to 18% of hospitalized admissions. Progression of AKI may lead to irreversible kidney damage. Methods: This retrospective cohort study includes adult patients admitted to a non-intensive care unit at the University of Pittsburgh Medical Center (UPMC) (n = 46,815) an

Luis A. Guardiola, Ana Meca, Justo Puerto

Production-inventory games were introduced in Guardiola et al. (2007) as a new class of totally balanced combinatorial optimization games. From among all core-allocations, the Owen point was proposed as a specifically appealing solution. In this paper we study some relationships of the class of production-inventory games and other classes of new and known ga

Sarath Sankar, Corentin Bertrand, Antoine Georges, Eran Sela

The Anderson overlap catastrophe (AOC) is a many-body effect arising as a result of a shakeup of a Fermi sea due to an abrupt change of a local potential, leading to a power-law dependence of the density of states on energy. Here we demonstrate that a standard quantum-dot detector can be employed as a highly tuneable probe of the AOC, where the power law can

David Sobrín-Hidalgo, Miguel A. González-Santamarta, Ángel M. Guerrero-Higueras, Francisco J. Rodríguez-Lera

This paper introduces a system designed to generate explanations for the actions performed by an autonomous robot in Human-Robot Interaction (HRI). Explainability in robotics, encapsulated within the concept of an eXplainable Autonomous Robot (XAR), is a growing research area. The work described in this paper aims to take advantage of the capabilities of Lar

Niklas Küchler, Jürgen Horbach

Computer simulations are used to study a three-dimensional polydisperse model glassformer in a replica-coupling setup where an attractive field $\propto - \varepsilon Q$ of strength $\varepsilon$ can adjust the similarity of the system to a fixed reference configuration with the overlap parameter $Q$. The polydispersity in the model enables the efficient use

Matteo Fornoni

We consider a non-local tumour growth model of phase-field type, describing the evolution of tumour cells through proliferation in presence of a nutrient. The model consists of a coupled system, incorporating a non-local Cahn-Hilliard equation for the tumour phase variable and a reaction-diffusion equation for the nutrient. First, we establish novel regulari

Declan Campbell, Sreejan Kumar, Tyler Giallanza, Thomas L. Griffiths

Humans possess a remarkable capacity to recognize and manipulate abstract structure, which is especially apparent in the domain of geometry. Recent research in cognitive science suggests neural networks do not share this capacity, concluding that human geometric abilities come from discrete symbolic structure in human mental representations. However, progres

Kyle Gannon

In an important (yet unpublished) research note, Ben Yaacov describes how to turn a global Keisler measures into a type over a monster model of the randomization. This transfer methods allow one to turn questions involving measures into those involving types (in continuous logic). Assuming that T is NIP, we show that the Morley product commutes with the tran

Christian Bargetz, Franz Luggin, Tommaso Russo

We use a special tiling for the hyperbolic $d$-space $\mathbb{H}^d$ for $d=2,3,4$ to construct an (almost) explicit isomorphism between the Lipschitz-free space $\mathcal{F}(\mathbb{H}^d)$ and $\mathcal{F}(P)\oplus\mathcal{F}(\mathcal{N})$ where $P$ is a polytope in $\mathbb{R}^d$ and $\mathcal{N}$ a net in $\mathbb{H}^d$ coming from the tiling. This implies

Brian Fitzgerald

The Information Systems (IS) and Software Engineering (SE) fields share a remarkable number of similarities in their historical evolution to date. These similarities are briefly outlined below. An analysis of 10 years (2001-2010) of publications in the primary journals in both fields also reveals a good deal of overlap in research topics. Given the challenge

Afsaneh Karbalaee, Somayeh Belbasi, Hanif Hadipour

Correlated phenomena such as magnetism and Mott phase are a very controversial issue in two-dimensional transition metal dichalcogenides (TMDCs). With the aim of finding the value of correlation strength and understanding the origin of ferromagnetic order in TMDCs, we first identify relevant low-energy degrees of freedom on both octahedral T and trigonal pri

Simon Thalabard, Alexei A. Mailybaev

The statistical behavior of scalars passively advected by random flows exhibits intermittency in the form of anomalous multiscaling, in many ways similar to the patterns commonly observed in incompressible high-Reynolds fluids. This similarity suggests a generic dynamical mechanism underlying intermittency, though its specific nature remains unclear. Scalar

Felipe Isaule

The functional renormalisation group (FRG) approach is employed to study Bose polarons at finite temperatures in the regime of strong attractive bath-impurity interactions. Both two- and three-dimensional configurations are considered. The appearance of two polaron quasiparticle branches at finite temperatures is revealed, consistent with recent findings by

Kaifei Kang, Yichen Qiu, Kenji Watanabe, Takashi Taniguchi

Quantum spin Hall (QSH) insulators are a topologically protected phase of matter in two dimensions that can support non-dissipative spin transport. A hallmark of the phase is a pair of helical edge states surrounding an insulating bulk. A higher (even) number of helical edge state pairs is usually not possible in real materials because spin mixing would gap

Xinyue Cao, Xiyu Zhang, Yuxin Cheng, Zhaoshuai Qi

Multi-instance registration is a challenging problem in computer vision and robotics, where multiple instances of an object need to be registered in a standard coordinate system. In this work, we propose the first iterative framework called instance-by-instance (IBI) for multi-instance 3D registration (MI-3DReg). It successively registers all instances in a

Pedro Meert, Horatiu Nastase

We consider rotational holographic transport in strongly coupled 2+1 dimensional systems, from the point of view of 3+1 dimensional gravity. We consider the moment of inertia $I$ as a kind of transport coefficient, identified with the moment of inertia of a charged rotating black hole in $AdS_4$ background. In the low-temperature region, we find the behaviou

Chengxi Li, Mikael Skoglund

In this paper, we consider a decentralized learning problem in the presence of stragglers. Although gradient coding techniques have been developed for distributed learning to evade stragglers, where the devices send encoded gradients with redundant training data, it is difficult to apply those techniques directly to decentralized learning scenarios. To deal

Mariana Frank, Chayan Majumdar, Poulose Poulose, Supriya Senapati

Alternative Left-Right Models offer an attractive option to left-right models. Emerging from $E_6$ grand unification, these models are consistent with light scalars which do not induce flavour-changing neutral currents due to the presence of exotic quarks. Here we investigate the signature at the LHC collider of the charged $W_R$ boson, which can be lighter

Edward M. Kober, Jacob P. Tavenner, Colin M. Adams, Nithin Mathew

Extracting relevant information from atomistic simulations relies on a complete and accurate characterization of atomistic configurations. We present a framework for characterizing atomistic configurations in terms of a complete and symmetry-adapted basis, referred to as strain functionals. In this approach a Gaussian kernel is used to map discrete atomic qu

Gábor Domokos, Alain Goriely, Ákos G. Horváth, Krisztina Regős

A central problem of geometry is the tiling of space with simple structures. The classical solutions, such as triangles, squares, and hexagons in the plane and cubes and other polyhedra in three-dimensional space are built with sharp corners and flat faces. However, many tilings in Nature are characterized by shapes with curved edges, non-flat faces, and few

V. A. Sirota, K. P. Zybin

We comment on the paper 'Saturation and Multifractality of Lagrangian and Eulerian Scaling Exponents in Three-Dimensional Turbulence' by D. Buaria and K.R. Sreenivasan. We point out some physical interpretation of the results discussed in the paper.

Samarjit Chakraborty, Sunil D. Maharaj, Sarbari Guha, Rituparno Goswami

We investigate the status of the gravitational arrow of time in the case of a spherical collapse of a fluid that conducts heat and radiates energy. In particular, we examine the results obtained by W. B. Bonnor in his 1985 paper where he found that the gravitational arrow of time was opposite to the thermodynamic arrow of time. The measure of gravitational e

Wolfgang Zirwas, Berthold Panzner, Rakash Sivasivaganesan, Brenda Vilas Boas

In this article, a novel approach for mobile radio communications is proposed and analysed, which is promising for future 6G cooperative distributed MIMO systems. The fundamental idea is a new mechanism namely start stop bit method, which transmits bit sequences as the start/stop bits of a synchronized counter instead of transmitting the full encoded bit seq

Calum Buchanan, Richard Danner

In this note, we characterize the products of simplicial generators for the Chow ring of a loopless matroid, extending a result of Backman, Eur, and Simpson. We prove that the stable intersection of a collection of tropical hyperplanes centered at the origin with the Bergman fan of a matroid is the Bergman fan of the dual of a certain Rado matroid.

Jie Pu, Kai-Jia Sun, Chun-Wang Ma, Lie-Wen Chen

The strange dibaryons $p\Omega$ ($^5\rm{S}_2$) and $\Omega\Omega$ ($^1\rm{S}_0$) are likely bound, existing either in molecular states like the deuteron or as more exotic compact six-quark states. Here, we investigate the production of these two dibaryons in Pb+Pb collisions at $\sqrt{s_{NN}}$=2.76 TeV at the CERN Large Hadron Collider (LHC) within a covaria

Bhaskar Dutta, Wei-Chih Huang, Doojin Kim, Jayden L. Newstead

We propose a new approach to search for light dark matter (DM), with keV-GeV mass, via inelastic nucleus scattering at large-volume neutrino detectors such as Borexino, DUNE, Super-K, Hyper-K, and JUNO. The approach uses inelastic nuclear scattering of cosmic-ray boosted DM, enabling a low background search for DM in these experiments. Large neutrino detecto

Ramtin Ehsani, Mia Mohammad Imran, Robert Zita, Kostadin Damevski

In the dynamic landscape of open source software (OSS) development, understanding and addressing incivility within issue discussions is crucial for fostering healthy and productive collaborations. This paper presents a curated dataset of 404 locked GitHub issue discussion threads and 5961 individual comments, collected from 213 OSS projects. We annotated the

Sven Gronauer, Tom Haider, Felippe Schmoeller da Roza, Klaus Diepold

Reinforcement learning algorithms need exploration to learn. However, unsupervised exploration prevents the deployment of such algorithms on safety-critical tasks and limits real-world deployment. In this paper, we propose a new algorithm called Ensemble Model Predictive Safety Certification that combines model-based deep reinforcement learning with tube-bas

Emanuela Barberis, Nebojsa Begovic, Nicholas Haubrich, Mikhail Ignatenko

Studies of Cathode Strip Chamber longevity, comparing Ar+CO2 gas mixtures with fractions of 5%, 2%, and 0% CF4, were performed using several small cathode strip prototype chambers. In each trial, a localized source of radiation was used to irradiate up to an accumulated charge of about 300 mC/cm. Additionally, longevity of a uniformly irradiated prototype op

Clément Lhoste, Emek Barış Küçüktabak, Lorenzo Vianello, Lorenzo Amato

In the control of lower-limb exoskeletons with feet, the phase in the gait cycle can be identified by monitoring the weight distribution at the feet. This phase information can be used in the exoskeleton's controller to compensate the dynamics of the exoskeleton and to assign impedance parameters. Typically the weight distribution is calculated using data fr

A. García-Yeguas, A. Sánchez-Alzola, L. De Siena, J. Prudencio

We present a P-wave scattering image of the volcanic structures under Tenerife Island using the autocorrelation functions of P-wave vertical velocity fluctuations. We have applied cluster analysis to total quality factor attenuation (Q inv t) and scattering quality factor attenuation (Q inv PSc) images to interpret the structures in terms of intrinsic and sc

Yichen Shi, Yuhao Gao, Yingxin Lai, Hongyang Wang

Multimodal large language models (MLLMs) have demonstrated strong capabilities in vision-related tasks, capitalizing on their visual semantic comprehension and reasoning capabilities. However, their ability to detect subtle visual spoofing and forgery clues in face attack detection tasks remains underexplored. In this paper, we introduce a benchmark, SHIELD,

Berivan Isik, Natalia Ponomareva, Hussein Hazimeh, Dimitris Paparas

Scaling laws provide important insights that can guide the design of large language models (LLMs). Existing work has primarily focused on studying scaling laws for pretraining (upstream) loss. However, in transfer learning settings, in which LLMs are pretrained on an unsupervised dataset and then finetuned on a downstream task, we often also care about the d

Joachim Pomper, Suchita Kulkarni

We consider pseudo Nambu-Goldstone bosons arising from Dirac fermions transforming in real representations of a confining gauge group as dark matter candidates. We consider a special case of two Dirac fermions and couple the resulting dark sector to the Standard Model using a vector mediator. Within this construction, we develop a consistent low energy effec

Curtis Taylor Peterson, Anna Hasenfratz

Common to many analysis pipelines in lattice gauge theory and the broader scientific discipline is the need to fit a semi-parametric model to data. We propose a fit method that utilizes a radial basis function network to approximate the non-parametric component of such models. The approximate parametric model is fit to data using the basin hopping global opt

Sumit Banik, Samuel Friot

Two recently developed techniques of analytic evaluation of multifold Mellin-Barnes (MB) integrals are presented. Both approaches rest on the definition of geometrical objets conveniently associated with the MB integrands, which can then be used along with multivariate residues analysis to derive series representations of the MB integrals. The first method i

Harichandana B S S, Sumit Kumar, Manjunath Bhimappa Ujjinakoppa, Barath Raj Kandur Raja

Smartphones have become indispensable in our daily lives and can do almost everything, from communication to online shopping. However, with the increased usage, cybercrime aimed at mobile devices is rocketing. Smishing attacks, in particular, have observed a significant upsurge in recent years. This problem is further exacerbated by the perpetrator creating

Hauke Koehn, Henrik Rose, Peter T. H. Pang, Rahul Somasundaram

Through continuous progress in nuclear theory and experiment and an increasing number of neutron-star observations, a multitude of information about the equation of state (EOS) for matter at extreme densities is available. To constrain the EOS across its entire density range, this information needs to be combined consistently. However, the impact and model-d

Julius Schöning, Tim Wawer, Kai-Michael Griese

Applications such as ChatGPT and WOMBO Dream make it easy to inspire students without programming knowledge to use artificial intelligence (AI). Therefore, given the increasing importance of AI in all disciplines, innovative strategies are needed to educate students in AI without programming knowledge so that AI can be integrated into their study modules as

A. M. Derrico, M. Basini, V. Unikandanunni, J. R. Paudel

Ultrafast electric-field control of emergent electronic and magnetic states at oxide interfaces offers exciting prospects for the development of new generations of energy-efficient devices. Here, we demonstrate that the electronic structure and emergent ferromagnetic interfacial state in epitaxial LaNiO3/CaMnO3 superlattices can be effectively controlled usi

Juhyung Ha, Nian Wang, Surendra Maharjan, Xuhong Zhang

This study introduces the 3D Residual-in-Residual Dense Block GAN (3D RRDB-GAN) for 3D super-resolution for radiology imagery. A key aspect of 3D RRDB-GAN is the integration of a 2.5D perceptual loss function, which contributes to improved volumetric image quality and realism. The effectiveness of our model was evaluated through 4x super-resolution experimen

Pran Nath

While the standard model accurately describes data at the electroweak scale without inclusion of gravity, beyond the standard model physics is increasingly intertwined with gravitational phenomena and cosmology. Thus gravity mediated breaking of supersymmetry in supergravity models lead to sparticles masses, which are gravitational in origin, observable at T

Maciej Kucab, Michal Praszalowicz

We apply the Chiral Quark-Soliton Model used previously to describe baryons with one heavy quark to the case of heavy tetraquarks. We argue, that the model is insenstive to the nature of the heavy object bound by the soliton, i.e. to its mass and spin. Therefore, a heavy quark can be replaced by an anti-diquark without modifying the soliton background. Diqua

Daniel Bogdoll, Jing Qin, Moritz Nekolla, Ahmed Abouelazm

Reinforcement Learning is a highly active research field with promising advancements. In the field of autonomous driving, however, often very simple scenarios are being examined. Common approaches use non-interpretable control commands as the action space and unstructured reward designs which lack structure. In this work, we introduce Informed Reinforcement

Ibrokhimbek Akramov, Isroil A. Ikromov

In this paper, we consider estimates for the two-dimensional oscillatory integrals. The phase function of the oscillatory integrals is the linear perturbation of a function having $D$ type singularities. We consider estimates for the oscillatory integrals in terms of the Randol's type maximal functions. We obtain a sharp $L^p_{loc}$ estimates for the Randol'

Taylor Reynolds, Sarah Scheffler, Daniel J. Weitzner, Angelina Wu

There are two strategic and longstanding questions about cyber risk that organizations largely have been unable to answer: What is an organization's estimated risk exposure and how does its security compare with peers? Answering both requires industry-wide data on security posture, incidents, and losses that, until recently, have been too sensitive for organ

Juan Tenorio, Wilder Perez

In the dynamic landscape of continuous change, Machine Learning (ML) "nowcasting" models offer a distinct advantage for informed decision-making in both public and private sectors. This study introduces ML-based GDP growth projection models for monthly rates in Peru, integrating structured macroeconomic indicators with high-frequency unstructured sentiment v

Marco Ghimenti, Anna Maria Micheletti, Angela Pistoia

We consider the eigenvalues problem for the the fractional Laplacian in a bounded domain Omega with Dirichlet boundary condition. A recent result by Fall, Ghimenti, Micheletti and Pistoia (CVPDE (2023)) states that under generic small perturbations of the coefficient of the equation or of the domain Omega all the eigenvalues are simple. In this paper we give

Richard Nock, Ehsan Amid, Frank Nielsen, Alexander Soen

Most mathematical distortions used in ML are fundamentally integral in nature: $f$-divergences, Bregman divergences, (regularized) optimal transport distances, integral probability metrics, geodesic distances, etc. In this paper, we unveil a grounded theory and tools which can help improve these distortions to better cope with ML requirements. We start with

Joel Villatoro, Josu Amorebieta, Ángel Ortega-Gómez, José Enrique Antonio-López

The present work deals with a curvature sensor that consists of two segments of asymmetric multicore fiber (MCF) fusion spliced with standard single mode fiber (SMF). The MCF comprises three strongly coupled cores; one of such cores is at the geometrical center of the MCF. The two segments of MCF are short, have different lengths (less than 2 cm each), and a

Ashok Vardhan Makkuva, Marco Bondaschi, Adway Girish, Alliot Nagle

Attention-based transformers have achieved tremendous success across a variety of disciplines including natural languages. To deepen our understanding of their sequential modeling capabilities, there is a growing interest in using Markov input processes to study them. A key finding is that when trained on first-order Markov chains, transformers with two or m

Hao Wang, Lei Sha

Controllable text generation is a growing field within natural language generation (NLG) that focuses on producing text that meets specific constraints in real-world applications. Previous approaches, such as plug-and-play controllers (PPCs), aimed to steer the properties of generated text in a flexible manner. However, these methods often compromised the in

Wei Cheng, Jiahui Hong, Tianqi Shi

This is our first paper on the extension of our recent work on the Lax-Oleinik commutators and its applications to the intrinsic approach of propagation of singularities of the viscosity solutions of Hamilton-Jacobi equations. We reformulate Kantorovich-Rubinstein duality theorem in the theory of optimal transport in terms of abstract Lax-Oleinik operators,

Tarun Gupta, Wenbo Gong, Chao Ma, Nick Pawlowski

Recent advances in foundation models, especially in large multi-modal models and conversational agents, have ignited interest in the potential of generally capable embodied agents. Such agents will require the ability to perform new tasks in many different real-world environments. However, current foundation models fail to accurately model physical interacti

Marek Lewicki, Piotr Toczek, Ville Vaskonen

Slow first-order phase transitions generate large inhomogeneities that can lead to the formation of primordial black holes (PBHs). We show that the gravitational wave (GW) spectrum then consists of a primary component sourced by bubble collisions and a secondary one induced by large perturbations. The latter gives the dominant peak if $\beta/H_0 < 12$, impac

Andrea Bisoffi, Lidong Li, Claudio De Persis, Nima Monshizadeh

We consider the problem of designing a state-feedback controller for a linear system, based only on noisy input-state data. We focus on input-state data corrupted by measurement errors, which, albeit less investigated, are as relevant as process disturbances in applications. For energy and instantaneous bounds on these measurement errors, we derive linear ma

Matilde Gianocca

We prove $L^\infty$ and $W^{1,2}$ weighted Wente's inequalities. We prove in particular the critical case: for the $|x|^2$ weighted Wente's estimate the optimal weight is $|x|^2\log|x|$.

Sevgi Harman, Müge Kanuni, Guillermo Vera de Salas

In this paper, the quotient of a Leavitt path algebra of an arbitrary graph by an $I$-basic graded ideal, and the quotient of a Leavitt path algebra of a row-finite graph by an arbitrary graded ideal are considered. The result of the quotient of a Leavitt path algebra by an arbitrary graded ideal is extended by using the function $\varphi$. Examples are give

Yonggang Jin, Ge Zhang, Hao Zhao, Tianyu Zheng

Developing a generalist agent is a longstanding objective in artificial intelligence. Previous efforts utilizing extensive offline datasets from various tasks demonstrate remarkable performance in multitasking scenarios within Reinforcement Learning. However, these works encounter challenges in extending their capabilities to new tasks. Recent approaches int

Josu Amorebieta, Ángel Ortega-Gómez, Gaizka Durana, Rubén Fernández

We report on a compact, highly sensitive all-fiber accelerometer suitable for low frequency and low amplitude vibration sensing. The sensing elements in the device are two short segments of strongly coupled asymmetric multicore fiber (MCF) fusion spliced at 180{\deg} with respect to each other. Such segments of MCF are sandwiched between standard single mode

Raoni Arroyo, Lauro de Matos Nunes Filho, Frederik Moreira dos Santos

According to a particular interpretation of quantum mechanics, the causal role of human consciousness in the measuring process is called upon to solve a foundational problem called the "measurement problem". Traditionally, this interpretation is tied up with the metaphysics of substance dualism. As such, this interpretation of quantum mechanics inherits the

Ksenia A. Khudiakova, Jan Maas, Francesco Pedrotti

We prove upper bounds on the $L^\infty$-Wasserstein distance from optimal transport between strongly log-concave probability densities and log-Lipschitz perturbations. In the simplest setting, such a bound amounts to a transport-information inequality involving the $L^\infty$-Wasserstein metric and the relative $L^\infty$-Fisher information. We show that thi

Walker Melton, Atul Sharma, Andrew Strominger

Celestial MHV amplitudes are comprised of non-distributional leaf amplitudes associated to an AdS$_3$ leaf of a foliation of flat spacetime. It is shown here that the leaf amplitudes are governed by the same infinite-dimensional soft `$S$-algebra' as their celestial counterparts. Moreover, taking the soft limit of the smooth three-point MHV leaf amplitude yi

M. Dror, Luis A. Guardiola, Ana Meca, Justo Puerto

Consider a set N of n (>1) stores with single-item and single-period nondeterministic demands like in a classic newsvendor setting with holding and penalty costs only. Assume a risk-pooling single-warehouse centralized inventory ordering option. Allocation of costs in the centralized inventory ordering corresponds to modelling it as a cooperative cost game w

Ana Carolina Alves, André Ferreira, Gijs Luijten, Jens Kleesiek

Medical imaging faces challenges such as limited spatial resolution, interference from electronic noise and poor contrast-to-noise ratios. Photon Counting Computed Tomography (PCCT) has emerged as a solution, addressing these issues with its innovative technology. This review delves into the recent developments and applications of PCCT in pre-clinical resear

Mark Skandera

We state combinatorial formulas for hyperoctahedral group ($\mathfrak B_n$) character evaluations of the form $\chi( {{\widetilde C}_w}^{\negthickspace\negthickspace BC}\negthickspace(1))$, where ${{\widetilde C}_w}^{\negthickspace\negthickspace BC}\negthickspace(1) \in \Bbb Z[\mathfrak B_n]$ is a type-BC Kazhdan-Lusztig basis element, with $w \in \mathfrak

W. Oliveira dos Santos, E. R. Bezerra de Mello

Here we analyze the expectation value of the fermionic condensate and the energy-momentum tensor associated with a massive charged fermionic quantum field with a nonzero chemical potential propagating in a magnetic-flux-carrying cosmic string in thermal equilibrium at finite temperature $T$. The expectation values of the fermionic condensate and the energy-m

Noëlie Cherrier, Baptiste Rérolle, Martin Graive, Amir Dib

A reliable and accurate knowledge of the ridership in public transportation networks is crucial for public transport operators and public authorities to be aware of their network's use and optimize transport offering. Several techniques to estimate ridership exist nowadays, some of them in an automated manner. Among them, Automatic Passenger Counting (APC) s

Sandipp Krishnan Ravi, Yigitcan Comlek, Arjun Pathak, Vipul Gupta

With the advent of artificial intelligence and machine learning, various domains of science and engineering communities have leveraged data-driven surrogates to model complex systems through fusing numerous sources of information (data) from published papers, patents, open repositories, or other resources. However, not much attention has been paid to the dif

Fernando Moreno, Gonzalo Tancredi, Adriano Campo Bagatin

On 2022 September 26th, 23:14 UT the NASA/DART (Double Asteroid Redirection Test) spacecraft successfully impacted Dimorphos, the secondary component of the binary (65803) Didymos system, demonstrating asteroid orbit deflection for the first time. A large amount of debris, consisting on a wide size frequency distribution of particulates (from micron-sized du

Herwig Hauser, Jiayue Qi, Josef Schicho

This is an expository paper. The geometry of phylogenetic trees is used to present in an accessible and pleasant fashion the results of Deligne, Mumford, and Knudsen about the moduli space of n distinct points on the projective line and its compactification, the moduli space of n-pointed stable curves of genus zero.

Zi-Kui Liu

Today's thermodynamics is largely based on the combined law for equilibrium systems and statistical mechanics derived by Gibbs in 1873 and 1901, respectively, while irreversible thermodynamics for nonequilibrium systems resides essentially on the Onsager Theorem as a separate branch of thermodynamics developed in 1930s. Between them, quantum mechanics was in

Haseeb ur Rahman Abbasi, Zeeshan Rashid, Muhammad Majid, Syed Muhammad Anwar

Emotion recognition (ER) technology is an integral part for developing innovative applications such as drowsiness detection and health monitoring that plays a pivotal role in contemporary society. This study delves into ER using electroencephalography (EEG), within immersive virtual reality (VR) environments. There are four main stages in our proposed method

Omer Dunay, Daniel Cheng, Adam Tait, Parth Thakkar

CodeCompose is an AI-assisted code authoring tool powered by large language models (LLMs) that provides inline suggestions to 10's of thousands of developers at Meta. In this paper, we present how we scaled the product from displaying single-line suggestions to multi-line suggestions. This evolution required us to overcome several unique challenges in improv

Michael De'Shazer

This study consists of a novel approach toward the analysis of court judgments spanning five countries, including the United States, the United Kingdom, Rwanda, Sweden and Hong Kong. This study also explores the intersection of the latest advancements in artificial intelligence (AI) and legal analysis, emphasizing the role of AI (specifically generative AI)

Zhuoran Zheng, Chen Wu

Currently, Transformer is the most popular architecture for image dehazing, but due to its large computational complexity, its ability to handle long-range dependency is limited on resource-constrained devices. To tackle this challenge, we introduce the U-shaped Vision Mamba (UVM-Net), an efficient single-image dehazing network. Inspired by the State Space S

Javier Cabello Sánchez, Juan Antonio Fernández Torvisco, Mariano R. Arias

There are a couple of purposes in this paper: to study a problem of approximation with exponential functions and to show its relevance for the economic science. We present results that completely solve the problem of the best approximation by means of exponential functions and we will be able to determine what kind of data is suitable to be fitted. Data will

Sumedh Vangara

Strongly interacting electron systems can provide insight into quantum many-body phenomena, such as Mott insulating behavior and spin liquidity, facilitating semiconductor optimization. The Fermi-Hubbard model is the prototypical model used to study such systems. Recent research, however, has shown that the extended Fermi-Hubbard model, which accounts for lo

Yasmine Kalboussi, Baptiste Delatte, Sarra Bira, Kassiogé Dembele

Superconducting qubits have arisen as a leading technology platform for quantum computing which is on the verge of revolutionizing the world's calculation capacities. Nonetheless, the fabrication of computationally reliable qubit circuits requires increasing the quantum coherence lifetimes, which are predominantly limited by the dissipations of two-level sys

J. Redondo, M. P. Peiró-Torres, C. Llinares, J. M. Bravo

There are several international standards that define the way to evaluate the attenuation capacity of noise reducing devices, by single-number quantities representing airborne sound insulation and insertion loss. These two single-value ratings define the quality and performance of acoustic barriers, the former being related to intrinsic and the latter to bot

Claus Lammerzahl, Sebastian Ulbricht

Motivated by the similarity of the mathematical structure of Einstein's General Relativity in its weak field limit and of Maxwell's theory of electrodynamics it is shown that there are gravitational analogues of the Josephson effect and the quantum Hall effect. These effects can be combined to derive a gravitational analogue of the quantum/electric metrologi

Qiyuan Chen, Ke Ye

We establish a lower bound for the complexity of multiplying two skew polynomials. The lower bound coincides with the upper bound conjectured by Caruso and Borgne in 2017, up to a log factor. We present algorithms for three special cases, indicating that the aforementioned lower bound is quasi-optimal. In fact, our lower bound is quasi-optimal in the sense o

David M. Soares, L. H. C. Borges, G. Dallabona, L. C. T. Brito

This paper investigates certain aspects of the CPT-odd photon sector of the minimal Standard Model Extension (SME) in the presence of a perfectly conducting plate (perfect mirror). The considered sector is described by Carroll-Field-Jackiw (CFJ) electrodynamics, where Lorentz violation is due to the presence of a single background vector denoted as $\left(k_

Gabriele Giacomini, Wei Chen, Gabriele D'Amen, Enrico Rossi

Low-Gain Avalanche Diodes are a type of silicon Avalanche Photo-Diodes originally developed for the fast detection of minimum ionizing particles in high-energy physics experiments. Thanks to their fast timing performance, the Low-Gain Avalanche Diode paradigm enables detectors to accurately measure minimum ionizing particles with a timing resolution of a few

Francesco Petiziol

We show that non-Abelian anyons can emerge from an Abelian topologically ordered system subject to local time-periodic driving. This is illustrated with the toric-code model, as the canonical representative of a broad class of Abelian topological spin liquids. The Abelian anyons in the toric code include fermionic and bosonic quasiparticle excitations which

Amir Dib, Noëlie Cherrier, Martin Graive, Baptiste Rérolle

In a transport network, the onboard occupancy is key for gaining insights into travelers' habits and adjusting the offer. Traditionally, operators have relied on field studies to evaluate ridership of a typical workday. However, automated fare collection (AFC) and automatic passenger counting (APC) data, which provide complete temporal coverage, are often av