May 2023 arXiv papers — page 119

Laura Zani

The possibility of a dark sector weakly coupling to Standard Model (SM) particles through new light mediators is explored at the Belle II experiment. We present here results from three different searches, for a long-lived (pseudo)scalar particle in rare $B$ decays; for a di-tau resonance in four-muon final states, and the update on the search for a \zprime\

Lison Blondeau-Patissier, Pierre Clairambault, Lionel Vaux Auclair

We introduce a calculus of extensional resource terms. These are resource terms \`a la Ehrhard-Regnier, but in infinitely eta-long form. The calculus still retains a finite syntax and dynamics: in particular, we prove strong confluence and normalization. Then we define an extensional version of Taylor expansion, mapping ordinary lambda-terms to (possibly inf

Emilija Dzuverovic, Matteo Barigozzi

We introduce a HD DCC-HEAVY class of hierarchical-type factor models for high-dimensional covariance matrices, employing the realized measures built from higher-frequency data. The modelling approach features straightforward estimation and forecasting schemes, independent of the cross-sectional dimension of the assets under consideration, and accounts for so

Chunlan Ma, Ayyoob ImaniGooghari, Haotian Ye, Renhao Pei

While natural language processing tools have been developed extensively for some of the world's languages, a significant portion of the world's over 7000 languages are still neglected. One reason for this is that evaluation datasets do not yet cover a wide range of languages, including low-resource and endangered ones. We aim to address this issue by creatin

Ori Lahav, Brijesh Dongol, Heike Wehrheim

Rely-guarantee (RG) is a highly influential compositional proof technique for concurrent programs, which was originally developed assuming a sequentially consistent shared memory. In this paper, we first generalize RG to make it parametric with respect to the underlying memory model by introducing an RG framework that is applicable to any model axiomatically

C Dujardin, A. Garcia-Murillo, C. Pedrini, C. Madej

Many ultra-dense lutetium or gadolinium based compounds doped with Eu 3+ have been prepared. This paper reports on the major scintillation performances of these compounds. One of them (Lu 2 O 3 :Eu) is particularly promising and have been deposited on a screen. Performances of such a screen are presented.

Marián Fabian, Alexander Y. Kruger, Patrick Mehlitz

We revisit the decoupling approach widely used (often intuitively) in nonlinear analysis and optimization and initially formalized about a quarter of a century ago by Borwein & Zhu, Borwein & Ioffe and Lassonde. It allows one to streamline proofs of necessary optimality conditions and calculus relations, unify and simplify the respective statements, clarify

Steyn van Leeuwen, Alberto Pérez de Alba Ortíz, Marjolein Dijkstra

Boltzmann generators (BGs) are now recognized as forefront generative models for sampling equilibrium states of many-body systems in the canonical ensemble, as well as for calculating the corresponding Helmholtz free energy. Furthermore, BGs can potentially provide a notable improvement in efficiency compared to conventional techniques such as molecular dyna

Jonas Stein, Lukas Müller, Leonhard Hölscher, Georgios Chnitidis

The simulation of many industrially relevant physical processes can be executed up to exponentially faster using quantum algorithms. However, this speedup can only be leveraged if the data input and output of the simulation can be implemented efficiently. While we show that recent advancements for optimal state preparation can effectively solve the problem o

Arsham Mostaani, Thang X. Vu, Hamed Habibi, Symeon Chatzinotas

With countless promising applications in various domains such as IoT and industry 4.0, task-oriented communication design (TOCD) is getting accelerated attention from the research community. This paper presents a novel approach for designing scalable task-oriented quantization and communications in cooperative multi-agent systems (MAS). The proposed approach

You-Cheng Chou, Y. -P. Lee

This is the second part of our ongoing project on the relations between Gopakumar-Vafa BPS invariants (GV) and quantum K-theory (QK) on the Calabi--Yau threefolds (CY3). We show that on CY3 a genus zero quantum K-invariant can be written as a linear combination of a finite number of Gopakumar--Vafa invariants with coefficients from an explicit ``multiple cov

Klas Modin, Manolis Perrot

The two-dimensional (2-D) Euler equations of a perfect fluid possess a beautiful geometric description: they are reduced geodesic equations on the infinite-dimensional Lie group of symplectomorphims with respect to a right-invariant Riemannian metric. This structure enables insights to Eulerian and Lagrangian stability via sectional curvature and Jacobi equa

Francesco R. Ferraro, Alessio Mucciarelli, Barbara Lanzoni, Cristina Pallanca

Blue stragglers are anomalously luminous core hydrogen-burning stars formed through mass-transfer in binary/triple systems and stellar collisions. Their physical and evolutionary properties are largely unknown and unconstrained. Here we analyze 320 high-resolution spectra of blue stragglers collected in eight galactic globular clusters with different structu

Arcangelo Massari, Silvio Peroni, Francesca Tomasi, Ivan Heibi

In the realm of Digital Humanities, the management of cultural heritage metadata is pivotal for ensuring data trustworthiness. Provenance information - contextual metadata detailing the origin and history of data - plays a crucial role in this process. However, tracking provenance and changes in metadata using the Resource Description Framework (RDF) present

Patrick Hochstenbach, Jos De Roo, Ruben Verborgh

Logic can define how agents are provided or denied access to resources, how to interlink resources using mining processes and provide users with choices for possible next steps in a workflow. These decisions are for the most part hidden, internal to machines processing data. In order to exchange this internal logic a portable Web logic is required which the

Yihong Liu, Haotian Ye, Leonie Weissweiler, Philipp Wicke

Languages differ in how they divide up the world into concepts and words; e.g., in contrast to English, Swahili has a single concept for `belly' and `womb'. We investigate these differences in conceptualization across 1,335 languages by aligning concepts in a parallel corpus. To this end, we propose Conceptualizer, a method that creates a bipartite directed

Yuta Honshuku, Hiroshi Isakari

This paper presents a boundary element method (BEM) for computing the energy transmittance of a singly-periodic grating in 2D for a wide frequency band, which is of engineering interest in various fields with possible applications to acoustic metamaterial design. The proposed method is based on the Pad\'e approximants of the response. The high-order frequenc

Songning Lai, Jiakang Li, Guinan Guo, Xifeng Hu

Designing an effective representation learning method for multimodal sentiment analysis tasks is a crucial research direction. The challenge lies in learning both shared and private information in a complete modal representation, which is difficult with uniform multimodal labels and a raw feature fusion approach. In this work, we propose a deep modal shared

Eric T. Mortenson, Dilshod Urazov

Ramanujan's last letter to Hardy introduced the world to mock theta functions, and the mock theta function identities found in Ramanujan's lost notebook added to their intriguing nature. For example, we find the four tenth-order mock theta functions and their six identities. The six identities themselves are of a spectacular nature and were first proved by C

Vincent Pilaud, Francisco Santos, Günter M. Ziegler

We survey Jean-Louis Loday's vertex description of the associahedron, and its far reaching influence in combinatorics, discrete geometry and algebra. We present in particular four topics were it plays a central role: lattice congruences of the weak order and their quotientopes, cluster algebras and their generalized associahedra, nested complexes and their n

Daniel Funke, Nicolai Hüning, Peter Sanders

One established metric to classify the significance of a mountain peak is its isolation. It specifies the distance between a peak and the closest point of higher elevation. Peaks with high isolation dominate their surroundings and provide a nice view from the top. With the availability of worldwide Digital Elevation Models (DEMs), the isolation of all mounta

Manuel Friedrich, Manuel Seitz, Ulisse Stefanelli

In the stationary case, atomistic interaction energies can be proved to $\Gamma$-converge to classical elasticity models in the simultaneous atomistic-to-continuum and linearization limit [19],[40]. The aim of this note is that of extending the convergence analysis to the dynamic setting. Moving within the framework of [40], we prove that solutions of the eq

Jianying Wang, Tongliang Li, Haoze Song, Xinjun Yang

Cloud-native databases have become the de-facto choice for mission-critical applications on the cloud due to the need for high availability, resource elasticity, and cost efficiency. Meanwhile, driven by the increasing connectivity between data generation and analysis, users prefer a single database to efficiently process both OLTP and OLAP workloads, which

Daniel Speed, Wenyang Lyu, Roman Schubert

Gaussian quantum channels are well understood and have many applications, e.g., in Quantum Information Theory and in Quantum Optics. For more general quantum channels one can in general use semiclassical approximations or perturbation theory, but it is not easy to judge the accuracy of such methods. We study a relatively simple model case, where the quantum

Yahong Yang, Haizhao Yang, Yang Xiang

This paper addresses the problem of nearly optimal Vapnik--Chervonenkis dimension (VC-dimension) and pseudo-dimension estimations of the derivative functions of deep neural networks (DNNs). Two important applications of these estimations include: 1) Establishing a nearly tight approximation result of DNNs in the Sobolev space; 2) Characterizing the generaliz

Jinming Du, Yanqun Tang, Xizhang Wei, Jiaojiao Xiong

Integrated sensing and communication (ISAC) is considered as a promising solution for improving spectrum efficiency and relieving wireless spectrum congestion. This paper systematically introduces the evolutionary path of ISAC technologies, then sorts out and summarizes the current research status of ISAC resource allocation. From the perspective of differen

Lukas Stappen, Jeremy Dillmann, Serena Striegel, Hans-Jörg Vögel

This paper aims to serve as a comprehensive guide for researchers and practitioners, offering insights into the current state, potential applications, and future research directions for generative artificial intelligence and foundation models within the context of intelligent vehicles. As the automotive industry progressively integrates AI, generative artifi

Péter Boross, András Pályi

Topology-related ideas might lead to noise-resilient quantum computing. For example, it is expected that the slow spatial exchange (`braiding') of Majorana zero modes in superconductors yields quantum gates that are robust against disorder. Here, we report our numerical experiments, which describe the dynamics of a Majorana qubit built from quantum dots cont

Andrea Castagnetti, Alain Pegatoquet, Benoît Miramond

In recent years, Deep Convolutional Neural Networks (DCNNs) have outreached the performance of classical algorithms for image restoration tasks. However most of these methods are not suited for computational efficiency and are therefore too expensive to be executed on embedded and mobile devices. In this work we investigate Spiking Neural Networks (SNNs) for

Ryoya Yamasaki, Toshiyuki Tanaka

The mean shift (MS) algorithm seeks a mode of the kernel density estimate (KDE). This study presents a convergence guarantee of the mode estimate sequence generated by the MS algorithm and an evaluation of the convergence rate, under fairly mild conditions, with the help of the argument concerning the {\L}ojasiewicz inequality. Our findings extend existing o

Xin Xiao, Daiguo Zhou, Jiagao Hu, Yi Hu

Semantic segmentation has recently witnessed great progress. Despite the impressive overall results, the segmentation performance in some hard areas (e.g., small objects or thin parts) is still not promising. A straightforward solution is hard sample mining, which is widely used in object detection. Yet, most existing hard pixel mining strategies for semanti

L. X. Cui, Y-M. Du, C. P. Sun

Quantum technology has led to increasingly sophisticated and complex quantum devices. Assessing their reliability (quantum reliability) is an important issue. Although reliability theory for classical devices has been well developed in industry and technology, a suitable metric on quantum reliability and its loss has not been systematically investigated. Sin

Adam Gańczorz, Leszek Gąsieniec, Tomasz Jurdziński, Jakub Kowalski

The model of population protocols provides a universal platform to study distributed processes driven by pairwise interactions of anonymous agents. While population protocols present an elegant and robust model for randomized distributed computation, their efficiency wanes when tackling issues that require more focused communication or the execution of multi

Wenxuan Zou, Haiping Huang

Dynamical mean-field theory is a powerful physics tool used to analyze the typical behavior of neural networks, where neurons can be recurrently connected, or multiple layers of neurons can be stacked. However, it is not easy for beginners to access the essence of this tool and the underlying physics. Here, we give a pedagogical introduction of this method i

Mohammud Foondun, Davar Khoshnevisan, Eulalia Nualart

We consider the following stochastic heat equation \begin{equation*} \partial_t u(t\,,x) = \tfrac12 \partial^2_x u(t\,,x) + b(u(t\,,x)) + \sigma(u(t\,,x)) \dot{W}(t\,,x), \end{equation*} defined for $(t\,,x)\in(0\,,\infty)\times\mathbb{R}$, where $\dot{W}$ denotes space-time white noise. The function $\sigma$ is assumed to be positive, bounded, globally Lips

Yiheng Zhu, Zhenqiu Ouyang, Ben Liao, Jialu Wu

Molecular de novo design is a critical yet challenging task in scientific fields, aiming to design novel molecular structures with desired property profiles. Significant progress has been made by resorting to generative models for graphs. However, limited attention is paid to hierarchical generative models, which can exploit the inherent hierarchical structu

Zibin Zheng, Jianzhong Su, Jiachi Chen, David Lo

The Smart Contract Weakness Classification Registry (SWC Registry) is a widely recognized list of smart contract weaknesses specific to the Ethereum platform. Despite the SWC Registry not being updated with new entries since 2020, the sustained development of smart contract analysis tools for detecting SWC-listed weaknesses highlights their ongoing significa

Jordy Van Landeghem, Rubén Tito, Łukasz Borchmann, Michał Pietruszka

We call on the Document AI (DocAI) community to reevaluate current methodologies and embrace the challenge of creating more practically-oriented benchmarks. Document Understanding Dataset and Evaluation (DUDE) seeks to remediate the halted research progress in understanding visually-rich documents (VRDs). We present a new dataset with novelties related to ty

François-Xavier Schmider, Lyu Abe, Abdelkrim Agabi, Philippe Bendjoya

On December 2021, a new camera box for two-colour simultaneous visible photometry was successfully installed on the ASTEP telescope at the Concordia station in Antarctica. The new focal box offers increased capabilities for the ASTEP+ project. The opto-mechanical design of the camera was described in a previous paper. Here, we focus on the laboratory tests o

Okan Günel, Özgür Sarıoğlu

We revisit the Kerr black hole as cast in the Boyer-Lindquist, Kerr-Schild and Weyl canonical coordinates, and calculate its total mass/energy and total angular momentum by using linearized gravity along with its background Killing isometries. We argue that the integration of the relevant gravitational flux does not depend on the geometry of the closed and s

Reece D. Shaw, Alex E. Jones, Patrick Yard, Anthony Laing

The heralded generation of entangled states underpins many photonic quantum technologies. As quantum error correction thresholds are determined by underlying physical noise mechanisms, a detailed and faithful characterization of resource states is required. Non-computational leakage, e.g. more than one photon occupying a dual-rail encoded qubit, is an error

Nam Nguyen

Biomarker discovery is a challenging task due to the massive search space. Quantum computing and quantum Artificial Intelligence (quantum AI) can be used to address the computational problem of biomarker discovery tasks. We propose a Quantum Neural Networks (QNNs) architecture to discover biomarkers for input activation pathways. The Maximum Relevance, Minim

Hideo Kozono, Yutaka Terasawa, Yuta Wakasugi

We study the stationary Navier--Stokes equations in the region between two rotating concentric cylinders. We first prove that, under the small Reynolds number, if the fluid is axisymmetric and if its velocity is sufficiently small in the $L^\infty$-norm, then it is necessarily a generalized Taylor-Couette flow which is a new exact solution of the Navier--Sto

Zhenxiao Zhu, Linyun Yang, Jien Wu, Yan Meng

The Bloch band theory and Brillouin zone (BZ) that characterize wave behaviors in periodic mediums are two cornerstones of contemporary physics ranging from condensed matter to topological physics. Recent theoretical breakthrough revealed that, under the projective symmetry algebra enforced by artificial gauge fields, the usual two-dimensional (2D) BZ (orien

Matteo Casati, Danda Zhang

In a recent series of papers by Lou et al., it was conjectured that higher dimensional integrable equations may be constructed by utilizing some conservation laws of (1 + 1)-dimensional systems. We prove that the deformation algorithm introduced in arXiv:2211.06844, applied to Lax integrable $(1+1)$-dimensional systems, produces Lax integrable higher imensio

Antonio Ferrer-Sánchez, José D. Martín-Guerrero, Roberto Ruiz de Austri, Alejandro Torres-Forné

We present a novel methodology based on Physics-Informed Neural Networks (PINNs) for solving systems of partial differential equations admitting discontinuous solutions. Our method, called Gradient-Annihilated PINNs (GA-PINNs), introduces a modified loss function that requires the model to partially ignore high-gradients in the physical variables, achieved b

Luigi Montoro, Luigi Muglia, Berardino Sciunzi

Solutions to $p$-Laplace equations are not, in general, of class $C^2$. The study of Sobolev regularity of the second derivatives is, therefore, a crucial issue. An important contribution by Cianchi and Maz'ya shows that, if the source term is in $L^2$, then the field $|\nabla u|^{p-2}\nabla u$ is in $W^{1,2}$. The $L^2$-regularity of the source term is also

Bojie Shen, Zhe Chen, Muhammad Aamir Cheema, Daniel D. Harabor

Multi-Agent Path Finding (MAPF) is an important core problem for many new and emerging industrial applications. Many works appear on this topic each year, and a large number of substantial advancements and performance improvements have been reported. Yet measuring overall progress in MAPF is difficult: there are many potential competitors, and the computatio

Anita Kumari, Vasu Dev, Vishwa Pal

We numerically and experimentally study the autofocusing and self-healing of partially blocked circular Airy derivative beams (CADBs). The CADB consists of multiple rings, and partial blocking of CADB with different kinds is achieved by using symmetric and asymmetric binary amplitude masks, enabling blocking of inner/outer rings and sectorially. The CADB blo

Pooja Kumari Gupta, Sampreet Kalita, Amarendra K. Sarma

In this work, we study the phenomena of quantum interference assisted magnon blockade and magnon antibunching in a weakly interacting hybrid ferromagnet-superconductor system. The magnon excitations in two yttrium iron garnet spheres are indirectly coupled to a superconducting qubit through microwave cavity modes of two mutually perpendicular cavities. We fi

Daisuke Murakami, Narumasa Tsutsumida, Takahiro Yoshida, Tomoki Nakaya

Although geographically weighted Poisson regression (GWPR) is a popular regression for spatially indexed count data, its development is relatively limited compared to that found for linear geographically weighted regression (GWR), where many extensions (e.g., multiscale GWR, scalable GWR) have been proposed. The weak development of GWPR can be attributed to

Michael Krivelevich

A crown with $k$ spikes is an edge-disjoint union of a cycle $C$ and a matching $M$ of size $k$ such that each edge of $M$ has exactly one vertex in common with $C$. We prove that if $G$ is an $(n,d,\lambda)$-graph with $\lambda/d\le 0.001$ and $d$ is large enough, then $G$ contains a crown on $n$ vertices with $\lfloor n/2\rfloor$ spikes. As a consequence,

Dimitar Mihaylov, Jaime González González

Collider experiments provide an opportunity to produce particles at close distances and momenta. The measured correlation functions between particles can provide information on both the effective emission source and the interaction potential. In recent years, experiments at the LHC have shown that precision studies of the strong interaction are possible usin

Jingyi Gao, Naomichi Hatano

We put forward four schemes of coupled-qubit quantum Otto machine, a generalization of the single-qubit quantum Otto machine, based on work and heat transfer between an internal system consisting of a coupled pair of qubits and an external environment consisting of two heat baths and two work storages. The four schemes of our model are defined by the positio

Chun Yang Tan, Kazuhiko Kawamoto, Hiroshi Kera

In recent years, there has been growing concern over the vulnerability of convolutional neural networks (CNNs) to image perturbations. However, achieving general robustness against different types of perturbations remains challenging, in which enhancing robustness to some perturbations (e.g., adversarial perturbations) may degrade others (e.g., common corrup

Aritra K. Mukhopadhyay, Peter Schmelcher, Benno Liebchen

It is well known that periodic potentials can be used to induce freezing and melting in colloids. Here, we transfer this concept to active systems and find the emergence of a so-far unknown active matter phase in between the frozen solid-like phase and the molten phase. This phase of "active adaptolates" adopts the geometry of the underlying lattice like the

Harshank Shrotriya, Wen Wei Ho

We study the role of global system topology in governing deep thermalization, the relaxation of a local subsystem towards a maximally-entropic, uniform distribution of post-measurement states, upon observing the complementary subsystem in a local basis. Concretely, we focus on a class of (1+1)d systems exhibiting 'maximally-chaotic' dynamics, and consider ho

Artem Ageev, Antoine Kaufmann

Programmable packet-processing pipelines are a core building block of modern SmartNICs and switches, yet their design requires navigating intertwined trade-offs among program feasibility, hardware cost, and system-level performance. Existing approaches rely on proxy metrics such as stage or ALU count, which often mispredict capability and end-to-end behavior

Arun Jambulapati, Victor Reis, Kevin Tian

Discrepancy theory provides powerful tools for producing higher-quality objects which "beat the union bound" in fundamental settings throughout combinatorics and computer science. However, this quality has often come at the price of more expensive algorithms. We introduce a new framework for bridging this gap, by allowing for the efficient implementation of

Mariia Zyrianova, Dmytro Kalpakchi, Johan Boye

When training and evaluating machine reading comprehension models, it is very important to work with high-quality datasets that are also representative of real-world reading comprehension tasks. This requirement includes, for instance, having questions that are based on texts of different genres and require generating inferences or reflecting on the reading

Sebastian Berndt, Hauke Brinkop, Klaus Jansen, Matthias Mnich

Mixed-integer linear programming (MILP) is at the core of many advanced algorithms for solving fundamental problems in combinatorial optimization. The complexity of solving MILPs directly correlates with their support size, which is the minimum number of non-zero integer variables in an optimal solution. A hallmark result by Eisenbrand and Shmonin (Oper. Res

Marcello Poletti

A brief philosophical inquiry into the foundations of quantum mechanics is presented here. In particular, the direct relationship between granularity, discontinuity, and the presence of quantum effects will be argued. Furthermore, an "interpretation of relational interpretation" will be supported, which, in combination with the problem of logical undecidabil

Takeshi Fukumoto, Ken Yamamoto, Makoto Katsura, Hiroaki Katsuragi

We experimentally investigate the dynamics of a sphere rolling up a granular slope. During the rolling-up motion, the sphere experiences slipping and penetration (groove formation) on the surface of the granular layer. The former relates to the stuck motion of the rolling sphere, and the latter causes energy dissipation due to the deformation of the granular

David J. Nott, Christopher Drovandi, David T. Frazier

Bayesian inference is a powerful tool for combining information in complex settings, a task of increasing importance in modern applications. However, Bayesian inference with a flawed model can produce unreliable conclusions. This review discusses approaches to performing Bayesian inference when the model is misspecified, where by misspecified we mean that th

Emmanuel Bauer, Dominik Stammbach, Nianlong Gu, Elliott Ash

This paper tackles the task of legal extractive summarization using a dataset of 430K U.S. court opinions with key passages annotated. According to automated summary quality metrics, the reinforcement-learning-based MemSum model is best and even out-performs transformer-based models. In turn, expert human evaluation shows that MemSum summaries effectively ca

Rinaldo M. Colombo, Vincent Perrollaz, Abraham Sylla

Recently, results regarding the Inverse Design problem for Conservation Laws and Hamilton-Jacobi equations with space-dependent convex fluxes were obtaine. More precisely, characterizations of attainable sets and the set of initialdata evolving at a prescribed time into a prescribed profile were obtained. Here, wepresent an explicit example that underlines d

Dongmei Han, Na Wang, Meihong Wang, Xiaolong Su

The optical cat state, known as the superposition of coherent states, has broad applications in quantum computation and quantum metrology. Increasing the number of optical cat states is crucial to implement complex quantum information tasks based on them. Here, we prepare two optical cat states simultaneously based on a nondegenerate optical parametric ampli

Goro Akagi, Giulio Schimperna

This paper is concerned with a parabolic evolution equation of the form $A(u_t) + B(u) = f$, settled in a smooth bounded domain of ${\bf R}^d$, $d \geq 1$, and complemented with the initial conditions and with (for simplicity) homogeneous Dirichlet boundary conditions. Here, $-B$ stands for a diffusion operator, possibly nonlinear, which may range in a very

Wen Liu, Jinsong Zhao, Tieyan Wang, Xiangcheng Dong

Determining the mechanism responsible for the plasma heating and particle acceleration is a fundamental problem in the study of the heliosphere. Due to efficient wave-particle interactions of ion-scale waves with charged particles, these waves are widely believed to be a major contributor to ion energization, and their contribution considerably depends on th

Samuel Daudin, François Delarue, Joe Jackson

The goal of this work is to obtain optimal rates for the convergence problem in mean field control. Our analysis covers cases where the solutions to the limiting problem may not be unique nor stable. Equivalently the value function of the limiting problem might not be differentiable on the entire space. Our main result is then to derive sharp rates of conver

Hajime Fujita

In this paper we study dually flat spaces arising from Delzant polytopes equipped with a symplectic potential together with their corresponding toric K\"ahler manifolds as their torifications.We introduce a dually flat structure and the associated Bregman divergence on the boundary from the viewpoint of toric K\"ahler geometry. We show a continuity and a gen

Sean Dewar, Derek Kitson

We characterise rigid graphs for cylindrical normed spaces $Z=X\oplus_\infty \mathbb{R}$ where $X$ is a finite dimensional real normed linear space and $Z$ is endowed with the product norm. In particular, we obtain purely combinatorial characterisations of minimal rigidity for a large class of 3-dimensional cylindrical normed spaces; for example, when $X$ is

Kunyu Peng, Di Wen, David Schneider, Jiaming Zhang

Domain adaptation is essential for activity recognition to ensure accurate and robust performance across diverse environments, sensor types, and data sources. Unsupervised domain adaptation methods have been extensively studied, yet, they require large-scale unlabeled data from the target domain. In this work, we focus on Few-Shot Domain Adaptation for Activ

Mnacho Echenim, Nicolas Peltier

We establish various complexity results for the entailment problem between formulas in Separation Logic with user-defined predicates denoting recursive data structures. The considered fragments are characterized by syntactic conditions on the inductive rules that define the semantics of the predicates. We focus on so-called P-rules, which are similar to (but

Céline van Valkenhoef, Catherine Schuman, Philip Walther

The human brain has inspired novel concepts complementary to classical and quantum computing architectures, such as artificial neural networks and neuromorphic computers, but it is not clear how their performances compare. Here we report a new methodological framework for benchmarking cognitive performance based on solving computational problems with increas

Aximu Yuemaier, Xiaogang Chen, Xingyu Qian, Longfei Liang

Target tracking and trajectory modeling have important applications in surveillance video analysis and have received great attention in the fields of road safety and community security. In this work, we propose a lightweight real-time video analysis scheme that uses a model learned from motion patterns to monitor the behavior of objects, which can be used fo

Egor Illarionov, Rainer Arlt

French astronomer Honor\'e Flaugergues compiled astronomical observations in a series of hand-written notebooks for 1782$\unicode{x2013}$1830, which are preserved at Paris Observatory. We reviewed these manuscripts and encoded the records that contain sunspot measurements into a numerical table for further analysis. All measurements are timings and we found

Gilles Dowek, Ying Jiang

We give a new proof of a theorem of Mints that the positive fragment of minimal predicate logic is decidable. The idea of the proof is to replace the eigenvariable condition of sequent calculus by an appropriate scoping mechanism. The algorithm given by this proof seems to be more practical than that given by the original proof. A naive implementation is giv

Francesco Conti, Gianna Paulin, Angelo Garofalo, Davide Rossi

Emerging Artificial Intelligence-enabled Internet-of-Things (AI-IoT) System-on-a-Chip (SoC) for augmented reality, personalized healthcare, and nano-robotics need to run many diverse tasks within a power envelope of a few tens of mW over a wide range of operating conditions: compute-intensive but strongly quantized Deep Neural Network (DNN) inference, as wel

Simone Tedeschi, Johan Bos, Thierry Declerck, Jan Hajic

In the last five years, there has been a significant focus in Natural Language Processing (NLP) on developing larger Pretrained Language Models (PLMs) and introducing benchmarks such as SuperGLUE and SQuAD to measure their abilities in language understanding, reasoning, and reading comprehension. These PLMs have achieved impressive results on these benchmark

Devis Tuia, Konrad Schindler, Begüm Demir, Xiao Xiang Zhu

Earth observation (EO) is a prime instrument for monitoring land and ocean processes, studying the dynamics at work, and taking the pulse of our planet. This article gives a bird's eye view of the essential scientific tools and approaches informing and supporting the transition from raw EO data to usable EO-based information. The promises, as well as the cur

Bérénice Grec, Srboljub Simic

The paper studies a higher-order diffusion model of Maxwell-Stefan kind. The model is based upon higher-order moment equations of kinetic theory of mixtures, which include viscous dissipation in the model. Governing equations are analyzed in a scaled form, which introduces the proper orders of magnitude of each term. In the socalled diffusive scaling, the Ma

Kento Yasuda, Yuto Hosaka, Shigeyuki Komura

Among several models for microswimmers, the three-sphere microswimmer proposed by Najafi and Golestanian captures the essential mechanism for the locomotion of a microswimmer in a viscous fluid. Owing to its simplicity and flexibility, the original three-sphere model has been extended and generalized in various ways to discuss new swimming mechanisms of micr

Vasu Dev, Vishwa Pal

Discrete vortex, formed by a one-dimensional (1D) ring array of lasers, contains high output power as compared to a conventional continuous vortex, therefore, has attracted considerable interest due to widespread applications in various fields. We present a method for probing the magnitude and sign of the topological charge (TC) of an unknown discrete vortex

Florian Schintke, Ninon De Mecquenem, David Frantz, Vanessa Emanuela Guarino

Porting a scientific data analysis workflow (DAW) to a cluster infrastructure, a new software stack, or even only a new dataset with some notably different properties is often challenging. Despite the structured definition of the steps (tasks) and their interdependencies during a complex data analysis in the DAW specification, relevant assumptions may remain

Ding-Jiun Huang, Yu-Ting Kao, Tieh-Hung Chuang, Ya-Chun Tsai

In recent years, several video quality assessment (VQA) methods have been developed, achieving high performance. However, these methods were not specifically trained for enhanced videos, which limits their ability to predict video quality accurately based on human subjective perception. To address this issue, we propose a stack-based framework for VQA that o

Shunlin Huang, Ning Zhang, Xu Lu, Jun Liu

Light carrying orbital angular momentum (OAM) holds unique properties and boosts myriad applications in diverse fields from micro- to macro-world. Endeavors have been made to manipulate the OAM in order to generate on-demand structured light and to explore novel properties of light. However, the generation of an ultrafast wave packet carrying numerous vortic

Jinyu Han, Xiangde Zhu, Jianfeng Zhang, Shu Cai

We report the first observation of a pressure-induced transition from a superconducting (SC) to an insulating (I) phase in single-crystal Ba1-xKxBiO3 (x = 0.4, 0.43, 0.52, and 0.58) superconductors. X-ray diffraction measurements conducted at 20 K reveal a direct relationship between this SC-I transition and a pressure-induced distortion of crystal structure

Bireswar Das, Dhara Thakkar

For a finite group $G$, the size of a minimum generating set of $G$ is denoted by $d(G)$. Given a finite group $G$ and an integer $k$, deciding if $d(G)\leq k$ is known as the minimum generating set (MIN-GEN) problem. A group $G$ of order $n$ has generating set of size $\lceil \log_p n \rceil$ where $p$ is the smallest prime dividing $n=|G|$. This fact is us

Zihao Wang, Lei Wu

In this paper, we provide a theoretical analysis of the inductive biases in convolutional neural networks (CNNs). We start by examining the universality of CNNs, i.e., the ability to approximate any continuous functions. We prove that a depth of $\mathcal{O}(\log d)$ suffices for deep CNNs to achieve this universality, where $d$ in the input dimension. Addit

Shahram Mohsenipour

We prove an infinitary version of the Brauer-Schur theorem.

Naoko Wakijo

We determine the adjoint Reidemeister torsion of a $3$-manifold obtained by some Dehn surgery along $K$, where $K$ is either the figure-eight knot or the $5_2$-knot. As in a vanishing conjecture, we consider a similar conjecture and show that the conjecture holds for the 3-manifold.

Zhiqiang Miao, Enping Zhou, Ang Li

The investigation of the phase state of dense matter is hindered by complications of first-principle nonperturbative quantum chromodynamics. By performing the first consistent general-relativistic calculations of tidal-excited g-mode of neutron stars with a first-order strong interaction phase transition in the high-density core, we demonstrate that gravitat

Bao-Ming Xu

Quantum coherence will undoubtedly play a fundamental role in understanding the dynamics of quantum many-body systems, thereby to reveal its genuine contribution is of great importance. In this paper, we specialize our discussions on the one-dimensional transverse field quantum Ising model initialized in the coherent Gibbs state, and investigate the effects

Vincent Rivasseau

In this paper we construct cumulants for stable random matrix models with single trace interactions of arbitrarily high even order. We obtain explicit and convergent expansions for it and we prove that it is an analytic function inside a cardioid domain in the complex plane. We also prove their Borel-LeRoy summability at the origin of the coupling constant.

Gongwei Liu, Mengyun Yin, Suxia Xia

In this paper, we investigate the initial boundary value problem of the following nonlinear extensible beam equation with nonlinear damping term $$u_{t t}+\Delta^2 u-M\left(\|\nabla u\|^2\right) \Delta u-\Delta u_t+\left|u_t\right|^{r-1} u_t=|u|^{p-1} u$$ which was considered by Yang et al. (Advanced Nonlinear Studies 2022; 22:436-468). We consider the probl

Shoukang Chang, Wei Ye, Xuan Rao, Huan Zhang

Thermometry is a fundamental parameter estimation problem which is crucial in the development process of natural sciences. One way to solve this problem is to the extensive used local thermometry theory, which makes use of the classical and quantum Cram\'er-Rao bound as benchmarks of thermometry precision. However, such a thermometry theory can only be used

Abdul Rehman Khan, Asifullah Khan

Since their emergence, Convolutional Neural Networks (CNNs) have made significant strides in medical image analysis. However, the local nature of the convolution operator may pose a limitation for capturing global and long-range interactions in CNNs. Recently, Transformers have gained popularity in the computer vision community and also in medical image segm

Josep Batle, Adam Bednorz

We present a null witness of the dimension of a quantum system, discriminating real, complex and classical spaces, based on equality due to linear independence. The witness involves only a single measurement with sufficiently many outcomes and prepared input states. In addition, for intermediate dimensions, the witness bounds saturate for a family of equiang

Meng Yao, Xueou Feng, Qiyue Yin

Some standardized environments have been designed for partially observable multi-agent cooperation, but we find most current environments are synchronous, whereas real-world agents often have their own action spaces leading to asynchrony. Furthermore, fixed agents number limits the scalability of action space, whereas in reality agents number can change resu