March 2023 arXiv papers — page 85

Alexandros Stergiou, Nikos Deligiannis

The success of deep learning models has led to their adaptation and adoption by prominent video understanding methods. The majority of these approaches encode features in a joint space-time modality for which the inner workings and learned representations are difficult to visually interpret. We propose LEArned Preconscious Synthesis (LEAPS), an architecture-

David J. Benson

Let $G$ be a finite $p$-group, and $\alpha$ an automorphism of the group algebra ${\mathbb F}_pG$. Then $\alpha$ fixes the socle of ${\mathbb F}_pG$ pointwise. More generally, if $k$ is a field of characteristic $p$, and $\alpha$ is a $k$-algebra automorphism of $kG$, then $\alpha$ induces a linear action on the dimension subquotients of the group, and the a

Harris K. Armeniakos, Athanasios G. Kanatas, Harpreet S. Dhillon

A novel stochastic geometry framework is proposed in this paper to study the downlink coverage performance in a millimeter wave (mmWave) cellular network by jointly considering the polar coordinates of the Base Stations (BSs) with respect to the typical user located at the origin. Specifically, both the Euclidean and the angular distances of the BSs in a max

Masato Nagatsuka, Keita Sakai, Shoichi Sasaki

We present the numerical equivalence between the Wilson flow and stout-link smearing, both of which are known to be a relatively new technique for smoothing the gauge fields on the lattice. Although the conceptional correspondence between two methods was first pointed out by L\"uscher in his original paper [J. High Energy Phys.~08 (2010) 071], we provide a d

Atul Dixit, Bibekananda Maji, Akshaa Vatwani

For a fixed $z\in\mathbb{C}$ and a fixed $k\in\mathbb{N}$, let $\sigma_{z}^{(k)}(n)$ denote the sum of $z$-th powers of those divisors $d$ of $n$ whose $k$-th powers also divide $n$. This arithmetic function is a simultaneous generalization of the well-known divisor function $\sigma_z(n)$ as well as the divisor function $d^{(k)}(n)$ first studied by Wigert.

Nicolas Champagnat, Vincent Hass

In this article, a stochastic individual-based model describing Darwinian evolution of asexual, phenotypic trait-structured population, is studied. We consider a large population with constant population size characterised by a resampling rate modeling competition pressure driving selection and a mutation rate where mutations occur during life. In this model

Mathew Mithra Noel, Arindam Banerjee, Yug Oswal, Geraldine Bessie Amali D

All machine learning algorithms use a loss, cost, utility or reward function to encode the learning objective and oversee the learning process. This function that supervises learning is a frequently unrecognized hyperparameter that determines how incorrect outputs are penalized and can be tuned to improve performance. This paper shows that training speed and

Ilya Shapirovsky

We consider the bimodal language, where the first modality is interpreted by a binary relation in the standard way, and the second is interpreted by the relation of inequality. It follows from Hughes (1990), that in this language, non-$k$-colorability of a graph is expressible for every finite $k$. We show that modal logics of classes of non-$k$-colorable gr

Markus Hofbauer, Christoph Bachhuber, Christopher Kuhn, Sebastian Schwarz

Collaborative writing is essential for teams that create documents together. Creating documents in large-scale collaborations is a challenging task that requires an efficient workflow. The design of such a workflow has received comparatively little attention. Conventional solutions such as working on a single Microsoft Word document or a shared online docume

Johann Bouali

We introduce the definition of De Rham logarithmic classes. We show that the De Rham class of an algebraic cycle of a smooth algebraic variety over a field of characteristic zero is logarithmic and conversely that a logarithmic class of bidegree $(d,d)$ is the De Rham class of an algebraic cycle (of codimension $d$). We also give for smooth algebraic varieti

S. Kovalchuk, K. Greben, A. Kumar, S. Pessel

Excitons in bilayer transition metal dichalcogenides (2L-TMDs) are Coulomb-bound electron/hole pairs that can be viewed as broadly tunable analogs of atomic or molecular systems. Here, we study the properties of 2L-TMD excitons under strong electric field. To overcome the field limit, reached in previous experiments, we developed a new organic/inorganic mole

Nikhil Cherian Kurian, Varsha S, Abhijit Patil, Shashikant Khade

Semi-supervised learning (semi-SL) is a promising alternative to supervised learning for medical image analysis when obtaining good quality supervision for medical imaging is difficult. However, semi-SL assumes that the underlying distribution of unaudited data matches that of the few labeled samples, which is often violated in practical settings, particular

Eleonora Alfinito, Mariangela Ciccarese, Giuseppe Maruccio, Anna Grazia Monteduro

The growing interest in bio-inspired materials is driven by the need for increasingly targeted and efficient devices that also have a low ecological impact. These devices often use specially developed materials (e.g., polymers, aptamers, monoclonal antibodies) capable of carrying out the process of recognizing and capturing a specific target in a similar way

Pierre Goux, Franz Glessgen, Enrico Gazzola, Mandeep Singh Reen

The ANNRI-Gd collaboration studied in detail the single $\gamma$-ray spectrum produced from the thermal neutron capture on $^{155}$Gd and $^{157}$Gd in our previous publications. Gadolinium targets were exposed to a neutron beam provided by the Japan Spallation Neutron Source (JSNS) in J-PARC, Japan. In the present analysis, one new additional coaxial german

Behrouz Ahadzadeh, Moloud Abdar, Fatemeh Safara, Abbas Khosravi

In this paper, a new feature selection algorithm, called SFE (Simple, Fast, and Efficient), is proposed for high-dimensional datasets. The SFE algorithm performs its search process using a search agent and two operators: non-selection and selection. It comprises two phases: exploration and exploitation. In the exploration phase, the non-selection operator pe

Hongyu Zhang, Ignacio E. Grossmann, Ken McKinnon, Brage Rugstad Knudsen

We propose the REORIENT (REnewable resOuRce Investment for the ENergy Transition) model for energy systems planning with the following novelties: (1) integrating capacity expansion, retrofit and abandonment planning, and (2) using multi-horizon stochastic mixed-integer linear programming with multi-timescale uncertainty. We apply the model to the European en

Anna B. A. Queiroz, Friedrich Anders, Cristina Chiappini, Arman Khalatyan

The Gaia mission has provided an invaluable wealth of astrometric data for more than a billion stars in our Galaxy. The synergy between Gaia astrometry, photometry, and spectroscopic surveys give us comprehensive information about the Milky Way. Using the Bayesian isochrone-fitting code StarHorse, we derive distances and extinctions for more than 10 million

Wen-Mei Li, Rui-Di Wang, Hao-Yu Wu, Xiao-Li Huang

Detecting the structure of spacetime with quantum technologies has always been one of the frontier topics of relativistic quantum information. Here, we analytically study the generation and redistribution of Gaussian entanglement of the scalar fields in an expanding spacetime. We consider a two-mode squeezed state via a Gaussian amplification channel that co

Xianxin Wu, Jiepeng Song, Shuai Zhang, Wenna Du

Exciton-polaritons resulting from the strong exciton-photon interaction stimulate the development of novel coherent light sources with low threshold, long range spatial, and temporal coherence to circumvent the ever increasing energy demands of optical communications. Polaritons from bound states in the continuum (BICs) are promising for Bose-Einstein conden

Daniel S. Barker, Daniel Carney, Thomas W. LeBrun, David C. Moore

Heat and pressure are ultimately transmitted via quantized degrees of freedom, like gas particles and phonons. While a continuous Brownian description of these noise sources is adequate to model measurements with relatively long integration times, sufficiently precise measurements can resolve the detailed time dependence coming from individual bath-system in

Piotr H. Chankowski, Jacek Wojtkiewicz, Szymon Augustynowicz

Recently we have computed the third order corrections to the ground state energy of the arbitrarily polarized diluted gas of spin 1/2 fermions interacting through a spin-independent repulsive two-body potential. Here we extend this result to the gas of spin $s$ fermions - a system the Hamiltonian of which has an accidental $SU(2s+1)$ symmetry - with arbitrar

A. Pepin, S. Léger, N. Beaudoin

Computing accurate splines of degree greater than three is still a challenging task in today's applications. In this type of interpolation, high-order derivatives are needed on the given mesh. As these derivatives are rarely known and are often not easy to approximate accurately, high-degree splines are difficult to obtain using standard approaches. In Beaud

Dongsheng Wang, Xu Jia, Yang Zhang, Xinyu Zhang

Event-based cameras are bio-inspired sensors that capture brightness change of every pixel in an asynchronous manner. Compared with frame-based sensors, event cameras have microsecond-level latency and high dynamic range, hence showing great potential for object detection under high-speed motion and poor illumination conditions. Due to sparsity and asynchron

Masakazu Ohno, Riki Ukyo, Tatsuya Amano, Hamada Rizk

The growing demand for intelligent environments unleashes an extraordinary cycle of privacy-aware applications that makes individuals' life more comfortable and safe. Examples of these applications include pedestrian tracking systems in large areas. Although the ubiquity of camera-based systems, they are not a preferable solution due to the vulnerability of

Gaultier Lambert, Thomas Leblé, Ofer Zeitouni

We derive the leading order asymptotics of the logarithmic potential of a two dimensional Coulomb gas at arbitrary positive temperature. The proof is based on precise evaluation of exponential moments, and the theory of Gaussian multiplicative chaos.

Hamid Reza Naeij, Erfan Mahmoudi, Hossein Davoodi Yeganeh, Mohsen Akbari

Quantum computers can be used to calculate the electronic structure and estimate the ground state energy of many-electron molecular systems. In the present study, we implement the Variational Quantum Eigensolver (VQE) algorithm, as a hybrid quantum-classical algorithm to calculate the ground state energy of the molecules such as H3+, OH-, HF and BH3 in which

Raghavendra Selvan, Julian Schön, Erik B Dam

The accelerated development of machine learning methods, primarily deep learning, are causal to the recent breakthroughs in medical image analysis and computer aided intervention. The resource consumption of deep learning models in terms of amount of training data, compute and energy costs are known to be massive. These large resource costs can be barriers i

Rahel Rickenbach, Johannes Köhler, Anna Scampicchio, Melanie N. Zeilinger

The problem of coverage control, i.e., of coordinating multiple agents to optimally cover an area, arises in various applications. However, coverage applications face two major challenges: (1) dealing with nonlinear dynamics while respecting system and safety critical constraints, and (2) performing the task in an initially unknown environment. We solve the

Raúl Lara-Cabrera, Ángel González-Prieto, Diego Pérez-López, Diego Trujillo

Unsupervised machine learning lacks ground truth by definition. This poses a major difficulty when designing metrics to evaluate the performance of such algorithms. In sharp contrast with supervised learning, for which plenty of quality metrics have been studied in the literature, in the field of dimensionality reduction only a few over-simplistic metrics ha

Sandheep Ravishankar, Zhifa Liu, Yueming Wang, Thomas Kirchartz

A model is derived for the frequency- and time-domain opto-electronic response of perovskite solar cells (PSCs) that emphasizes the role of charge carrier exchange, .i.e. extraction and injection, from (to) the perovskite through the transport layer to (from) the collecting electrode. This process is described by a charge carrier exchange velocity that depen

Rosie Wood, Ondrej Masek, Valentina Erastova

Biochars have been attracting renewed attention as economical and environmentally friendly carbon sequestration materials with a diverse range of applications. However, experimental developments may be limited by the lack of molecular-level knowledge of the key interactions driving these applications. Molecular modelling techniques, such as molecular dynamic

Utkarsh Pratiush, Arshed Nabeel, Vishwesha Guttal, Prathosh AP

Collective motion is an ubiquitous phenomenon in nature, inspiring engineers, physicists and mathematicians to develop mathematical models and bio-inspired designs. Collective motion at small to medium group sizes ($\sim$10-1000 individuals, also called the `mesoscale'), can show nontrivial features due to stochasticity. Therefore, characterizing both the de

A. Coca, B. H. Tseng, W. Lin, B. Byrne

The schema-guided paradigm overcomes scalability issues inherent in building task-oriented dialogue (TOD) agents with static ontologies. Instead of operating on dialogue context alone, agents have access to hierarchical schemas containing task-relevant natural language descriptions. Fine-tuned language models excel at schema-guided dialogue state tracking (D

Claude Duhr, Chandrashekhar Kshirsagar

Recently a function was constructed that satisfies all known properties of a tree-level scattering of four massless scalars via the exchange of an infinite tower of particles with masses given by the non-trivial zeroes of the Riemann zeta function. A key ingredient in the construction is an even entire function whose only zeroes coincide with the non-trivial

R. B. Bapat, S. S. Saha, S. K. Panda

Let $\mathcal{H}$ be a connected $k$-uniform hypergraph on $n$ vertices and $m$ hyperedges. In [A.~Banerjee, On the spectrum of hypergraph, Linear Algebra and its Application, 614(2021), 82--110], Anirban Banerjee introduced a new adjacency matrix for hypergraphs. In this article we consider the corresponding signless Laplacian matrix $Q(\mathcal{H})$ and di

Mengyuan Jing, Yanmin Zhu, Tianzi Zang, Ke Wang

Deep learning-based recommender systems have achieved remarkable success in recent years. However, these methods usually heavily rely on labeled data (i.e., user-item interactions), suffering from problems such as data sparsity and cold-start. Self-supervised learning, an emerging paradigm that extracts information from unlabeled data, provides insights into

Maikel W. M. C. Bertens, Martijn J. H. Anthonissen, Jan H. M. ten Thije Boonkkamp, Wilbert L. IJzerman

A least-squares method for solving the hyperbolic Monge-Amp\`ere equation with transport boundary condition is introduced. The method relies on an iterative procedure for the gradient of the solution, the so-called mapping. By formulating error functionals for the interior domain, the boundary, both separately and as linear combination, three minimization pr

Markus Reiter-Haas, Alexander Ertl, Kevin Innerebner, Elisabeth Lex

This paper presents the winning system for the zero-shot Spanish framing detection task, which also achieves competitive places in eight additional languages. The challenge of the framing detection task lies in identifying a set of 14 frames when only a few or zero samples are available, i.e., a multilingual multi-label few- or zero-shot setting. Our develop

Taiwang Deng, Dongming She

Given a split classical group of symplectic type and a split general linear group over a local field $F$, we use Langlands-Shahidi method to construct their Rankin-Selberg local $\gamma$-factors and prove the corresponding analytic stability for generic representations. The idea generalizes the work of J. Cogdell, F. Shahidi, T.-L. Tsai in 2017 and D. She in

Gavin A. L. Coleman, Richard P. Nelson, Amaury H. M. J. Triaud

Numerous circumbinary planets have been discovered in surveys of transiting planets. Often, these planets are found to orbit near to the zone of dynamical instability, close to the central binary. The existence of these planets has been explained by hydrodynamical simulations that show that migrating circumbinary planets, embedded in circumbinary discs, halt

Marcella Anselmo, Giuseppa Castiglione, Manuela Flores, Dora Giammarresi

The hypercube of dimension n is the graph whose vertices are the 2^n binary words of length n, and there is an edge between two of them if they have Hamming distance 1. We consider an edit distance based on swaps and mismatches, to which we refer as tilde-distance, and define the tilde-hypercube with edges linking words at tilde-distance 1. Then, we introduc

Pietro Valigi, Izaak Neri, Chiara Cammarota

We study the spectral properties of sparse random graphs with different topologies and type of interactions, and their implications on the stability of complex systems, with particular attention to ecosystems. Specifically, we focus on the behaviour of the leading eigenvalue in different type of random matrices (including interaction matrices and Jacobian-li

Jnanadeva Maharana

Production of exotic states at LHC is considered in the large radius compactification scenario. We envisage a five dimensional theory for a scalar field in five dimensional flat spacetime. It is compactified on a circle, $S^1$, with radius, $R$. The radius is assumed to be in TeV scale appealing to LRC hypothesis. The production of Kaluza-Klein states whose

Enrique Artal Bartolo, José Ignacio Cogolludo-Agustín, Jorge Martín-Morales

This paper deals with cyclic covers of a large family of rational normal surfaces that can also be described as quotients of a product, where the factors are cyclic covers of algebraic curves. We use a generalization of Esnault-Viehweg method to show that the action of the monodromy on the first Betti group of the covering (and its Hodge structure) splits as

Sho Ejiri, Shou Yoshikawa

In this paper, we prove that a smooth projective globally $F$-split variety with numerically flat tangent bundle is an \'etale quotient of an ordinary abelian variety. We also show its logarithmic analog, which contains a characterization of toric varieties. We further prove that, without assumption of global $F$-splitting, a smooth projective separably rati

Doğanalp Ergenç, Florian Schneider, Peter Kling, Mathias Fischer

Modern mission-critical systems (MCS) are increasingly softwarized and interconnected. As a result, their complexity increased, and so their vulnerability against cyber-attacks. The current adoption of virtualization and service-oriented architectures (SOA) in MCSs provides additional flexibility that can be leveraged to withstand and mitigate attacks, e.g.,

Shreyash Mishra, S Suryavardan, Parth Patwa, Megha Chakraborty

Memes are the new-age conveyance mechanism for humor on social media sites. Memes often include an image and some text. Memes can be used to promote disinformation or hatred, thus it is crucial to investigate in details. We introduce Memotion 3, a new dataset with 10,000 annotated memes. Unlike other prevalent datasets in the domain, including prior iteratio

Matthew G. Smith, Graham M. Gibson, Andreas Link, Anand Raghavan

Flow-Induced Self-Assembly (FISA) is the phenomena of particle chaining in viscoelastic fluids while experiencing shear flow. FISA has a large number of applications across many fields including material science, food processing and biomedical engineering. Nonetheless, this phenomena is currently not fully understood and little has been done in literature so

Huaiyu Jian, Xianduo Wang

We introduce the concept of k-strictly convexity to describe the accurate convexity of convex domains some directions of which boundary may be flat. Basing this accurate convexity, we construct sub-solutions the Dirichlet problem for some degenerate-singular Monge-Amp\`ere type equations and prove the sharp boundary estimates for convex viscosity solutions o

Nicusor Arsene

The presence of hadronic sub-showers causes azimuthal non-uniformity in the particle distributions on the ground in vertical air showers. The $LCm$ parameter, which quantifies the non-uniformity of the signal recorded in detectors located at a given distance on a ring around the shower axis, has been successfully introduced as a gamma/hadron discriminator at

Suresh Kumarasamy, Malay Banerjee, Vaibhav Varshney, Manish Dev Shrimali

Hidden attractors are present in many nonlinear dynamical systems and are not associated with equilibria, making them difficult to locate. Recent studies have demonstrated methods of locating hidden attractors, but the route to these attractors is still not fully understood. In this letter, we present the route to hidden attractors in systems with stable equ

Ayman Zahr, Balazs Matuz, Gianluigi Liva

A class of rate-adaptive protograph MacKay-Neal (MN) codes is introduced and analyzed. The code construction employs an outer distribution matcher (DM) to adapt the rate of the scheme. The DM is coupled with an inner protograph-based low-density parity-check (LDPC) code, whose base matrix is optimized via density evolution analysis to approach the Shannon li

Bruce Merry

We present an implementation of a channelizer (F-engine) running on a Graphics Processing Unit (GPU). While not the first GPU implementation of a channelizer, we have put significant effort into optimizing the implementation. We are able to process four antennas each with 2 Gsample/s, 10-bit dual-polarized input and 8-bit output, on a single commodity GPU. T

Marco Flaim, Christian Scharrer

The aim of this paper is to give an upper bound for the intrinsic diameter of a surface with boundary immersed in a conformally flat three dimensional Riemannian manifold in terms of the integral of the mean curvature and of the length of its boundary. Of particular interest is the application of the inequality to minimal surfaces in the three-sphere and in

Savvas Papaioannou, Panayiotis Kolios, Georgios Ellinas

This work proposes a novel distributed control framework in which a team of pursuer agents equipped with a radio jamming device cooperate in order to track and radio-jam a rogue target in 3D space, with the ultimate purpose of disrupting its communication and navigation circuitry. The target evolves in 3D space according to a stochastic dynamical model and i

P. Hennebelle, U. Lebreuilly

Alfv\'en waves are fundamental magnetized modes which play an important role in the dynamics of magnetized flows such as the interstellar medium (ISM). In weakly ionised medium, their propagation critically depends on the ionisation rate but also on the charge carriers which, depending on gas density can be ions, electrons or dust grains. The latter in parti

A. Cesmelioglu, J. J. Lee, S. Rhebergen

We present a strongly conservative and pressure-robust hybridizable discontinuous Galerkin method for the coupled time-dependent Navier-Stokes and Darcy problem. We show existence and uniqueness of a solution and present an optimal a priori error analysis for the fully discrete problem when using Backward Euler time stepping. The theoretical results are veri

Timo Kreimeier, Sebastian Pokutta, Andrea Walther, Zev Woodstock

We propose an algorithm which appears to be the first bridge between the fields of conditional gradient methods and abs-smooth optimization. Our problem setting is motivated by various applications that lead to nonsmoothness, such as $\ell_1$ regularization, phase retrieval problems, or ReLU activation in machine learning. To handle the nonsmoothness in our

Y. S. Hung, S. P. Miao

We consider two models which couple derivatives of the inflaton to ordinary matter, both to fermions and to scalars. Such couplings induce changes to the inflaton kinetic energy, analogous to the cosmological Coleman-Weinberg potentials which come from nonderivative couplings. Our purpose is to investigate whether these quantum-induced K-Essence models can p

Yue Li, Lei Wang, Junjie Li, Jincheng Wang

We present a new phase-field formulation for the non-equilibrium interface kinetics. The diffuse interface is considered an integral of numerous representative volume elements (RVEs), in which there is a two-phase mixture with two conserved and two non-conserved concentration fields. This particular way of separating concentration fields leads to two distinc

Sándor Z. Kiss, Csaba Sándor

Let $k\ge 2$ be an integer and let $A$ be a set of nonnegative integers. For a $k$-tuple of positive integers $\underline{\lambda} = (\lambda_{1}, \dots{} ,\lambda_{k})$ with $1 \le \lambda_{1} < \lambda_{2} < \dots{} < \lambda_{k}$, we define the additive representation function $R_{A,\underline{\lambda}}(n) = |\{(a_{1}, \dots{} ,a_{k})\in A^{k}: \lambda_{1

Daniel J. Trosten, Sigurd Løkse, Robert Jenssen, Michael C. Kampffmeyer

Self-supervised learning is a central component in recent approaches to deep multi-view clustering (MVC). However, we find large variations in the development of self-supervision-based methods for deep MVC, potentially slowing the progress of the field. To address this, we present DeepMVC, a unified framework for deep MVC that includes many recent methods as

Ali Beikmohammadi, Sindri Magnússon

In recent years, reinforcement learning (RL) has emerged as a popular approach for solving sequence-based tasks in machine learning. However, finding suitable alternatives to RL remains an exciting and innovative research area. One such alternative that has garnered attention is the Non-Axiomatic Reasoning System (NARS), which is a general-purpose cognitive

Julia Stadler, Fabian Schmidt, Martin Reinecke

Cosmology inference of galaxy clustering at the field level with the EFT likelihood in principle allows for extracting all non-Gaussian information from quasi-linear scales, while robustly marginalizing over any astrophysical uncertainties. A pipeline in this spirit is implemented in the \texttt{LEFTfield} code, which we extend in this work to describe the c

Xiaotao Hu, Zhewei Huang, Ailin Huang, Jun Xu

The performance of video prediction has been greatly boosted by advanced deep neural networks. However, most of the current methods suffer from large model sizes and require extra inputs, e.g., semantic/depth maps, for promising performance. For efficiency consideration, in this paper, we propose a Dynamic Multi-scale Voxel Flow Network (DMVFN) to achieve be

Alexander Hepburn, Valero Laparra, Raúl Santos-Rodriguez, Jesús Malo

Previously, Barlow and Attneave hypothesised a link between biological vision and information maximisation. Following Shannon, information was defined using the probability of natural images. Several physiological and psychophysical phenomena have been derived from principles like info-max, efficient coding, or optimal denoising. However, it remains unclear

Bartosz Piotrowski, Ramon Fernández Mir, Edward Ayers

We introduce a machine-learning-based tool for the Lean proof assistant that suggests relevant premises for theorems being proved by a user. The design principles for the tool are (1) tight integration with the proof assistant, (2) ease of use and installation, (3) a lightweight and fast approach. For this purpose, we designed a custom version of the random

Javier Aramayona, Federico Cantero Morán, Víctor Carmona, Javier J. Gutiérrez

Action operads and cloning systems are, respectively, the main ingredients in two approaches for axiomatically constructing Thompson-like groups due to Thumann and Witzel-Zaremsky. In this paper, we prove that action operads are equivalent to cloning systems that admit a certain extra structure, and which we call bilateral cloning systems. In addition, we de

Maki Takeuchi, Takanao Tsuyuki, Hikaru Uchida

We study the generation number of massless fermions in compactifications recently found in heterotic supergravity. The internal spaces are products of two-dimensional spaces of constant curvature, and the standard embedding is not assumed. The generation number is constrained by the equations of motion and the Bianchi identity. In the case that the Euler cha

Daniele Baieri, Stefano Esposito, Filippo Maggioli, Emanuele Rodolà

Representing 3D surfaces as level sets of continuous functions over $\mathbb{R}^3$ is the common denominator of neural implicit representations, which recently enabled remarkable progress in geometric deep learning and computer vision tasks. In order to represent 3D motion within this framework, it is often assumed (either explicitly or implicitly) that the

Devavrat Tomar, Guillaume Vray, Behzad Bozorgtabar, Jean-Philippe Thiran

Most recent test-time adaptation methods focus on only classification tasks, use specialized network architectures, destroy model calibration or rely on lightweight information from the source domain. To tackle these issues, this paper proposes a novel Test-time Self-Learning method with automatic Adversarial augmentation dubbed TeSLA for adapting a pre-trai

Donglin Wang, Oneza Saraci, Raja R. Sattiraju, Qiuheng Zhou

With technology and societal development, the 5th generation wireless communication (5G) contributes significantly to different societies like industries or academies. Vehicle-to-Everything (V2X) communication technology has been one of the leading services for 5G which has been applied in vehicles. It is used to exchange their status information with other

Andrea Marini

Phonon properties of realistic materials are routinely calculated within the Density Functional Perturbation Theory\,(DFPT). This is a semi--classical approach where the atoms are assumed to oscillate along classical trajectories immersed in the electronic Kohn--Sham density, treated quantistically. In this work I demonstrate that, in metals, non--adiabatic

Youssef Azouzi, Mohamed Amine Ben Amor, Dorsaf Cherif, Marwa Masmoudi

We extend the concept of conditional supremum to the measure-free setting of Riesz spaces via the conditional expectation operator. We explore its properties and show how this tool is crucial in generalizing various results across multiple disciplines to the framework of Riesz spaces. Among other applications, we utilize this concept in finance to derive cha

Peng Jin, Hao Li, Zesen Cheng, Kehan Li

Existing text-video retrieval solutions are, in essence, discriminant models focused on maximizing the conditional likelihood, i.e., p(candidates|query). While straightforward, this de facto paradigm overlooks the underlying data distribution p(query), which makes it challenging to identify out-of-distribution data. To address this limitation, we creatively

Sung Mook Lee, Tanmoy Modak, Kin-ya Oda, Tomo Takahashi

The general scalar-tensor theory that includes all the dimension-four terms has parameter regions that can produce successful inflation consistent with cosmological observations. This theory is in fact the same as the Higgs-Starobinsky inflation, when the scalar is identified with the Standard Model Higgs boson. We consider possible dimension-six operators c

Xin Zhang, Nick Houston, Tianjun Li

A number of nuclear decay anomalies have been reported in the literature, which purport to show periodic variations in the decay rates of certain radioisotopes. If these reports reflect reality, they would necessitate a seismic shift in our understanding of fundamental physics. We provide the first mechanism to explain these findings, via the misalignment me

Xiuding Cai, Jiao Chen, Yaoyao Zhu, Beimin Wang

Automated anesthesia promises to enable more precise and personalized anesthetic administration and free anesthesiologists from repetitive tasks, allowing them to focus on the most critical aspects of a patient's surgical care. Current research has typically focused on creating simulated environments from which agents can learn. These approaches have demonst

Hongbin Wang

Reduction of high-loop Feynman integrals is one of the main tasks in scatting amplitude. In this paper, a new representation of Feynman integrals proposed by Chen in [1,2] is considered. We combined Chen's method with "syzygy" trick to simplify the IBP relations, and successfully canceled the dimensional shift and the unwanted doubled propagators. Moreover,

Hao Liu, Alex Havrilla, Rongjie Lai, Wenjing Liao

Autoencoders have demonstrated remarkable success in learning low-dimensional latent features of high-dimensional data across various applications. Assuming that data are sampled near a low-dimensional manifold, we employ chart autoencoders, which encode data into low-dimensional latent features on a collection of charts, preserving the topology and geometry

Adele Valpreda, Jacobus M. Sturm, Andrey Yakshin, Marcelo Ackermann

We investigate the use of Low Energy Ion Scattering (LEIS) to characterize buried interfaces of ultra-thin films. LEIS spectra contain depth-resolved information in the so-called sub-surface signal. However, the exact correlation between the sub-surface signal and the depth composition is still unknown. For this reason, LEIS spectra so far only provided qual

Zhanchi Wang, Nikolaos M. Freris, Xi Wei

Realizing a soft manipulator with biologically comparable flexibility and versatility often requires careful selection of materials and actuation, as well as attentive design of its structure, perception, and control. Here, we report a new class of soft robots (SpiRobs) that morphologically replicates the logarithmic spiral pattern observed in natural append

Alexander Kobelski, Pavel Osinenko, Stefan Streif

Traction parameters, that characterize the ground-wheel contact dynamics, are the central factor in the energy efficiency of vehicles. To optimize fuel consumption, reduce wear of tires, increase productivity etc., knowledge of current traction parameters is unavoidable. Unfortunately, these parameters are difficult to measure and require expensive force and

David Samuel, Andrey Kutuzov, Lilja Øvrelid, Erik Velldal

While modern masked language models (LMs) are trained on ever larger corpora, we here explore the effects of down-scaling training to a modestly-sized but representative, well-balanced, and publicly available English text source -- the British National Corpus. We show that pre-training on this carefully curated corpus can reach better performance than the or

Xingxing Wei, Bangzheng Pu, Shiji Zhao, Chen Chi

The advancement of deep learning has facilitated the integration of Artificial Intelligence (AI) into clinical practices, particularly in computer-aided diagnosis. Given the pivotal role of medical images in various diagnostic procedures, it becomes imperative to ensure the responsible and secure utilization of AI techniques. However, the unauthorized utiliz

Jungin Park, Jiyoung Lee, Kwanghoon Sohn

In this paper, we efficiently transfer the surpassing representation power of the vision foundation models, such as ViT and Swin, for video understanding with only a few trainable parameters. Previous adaptation methods have simultaneously considered spatial and temporal modeling with a unified learnable module but still suffered from fully leveraging the re

Xiaoling He, Tianyu Xu, Yun Yu, Anosha Karamat

\begin{abstract} Using the Keeton and Petters approach, we determine the deflection angle. We also investigate the motion of photons around a parameterized black hole in the presence of non-magnetized cold plasma by using a new ray-tracing algorithm. In spherically symmetric spacetime, we examine the influence of the plasma by applying the Hamiltonian equati

Jianyang Gao, Cheng Long

Approximate K nearest neighbor (AKNN) search is a fundamental and challenging problem. We observe that in high-dimensional space, the time consumption of nearly all AKNN algorithms is dominated by that of the distance comparison operations (DCOs). For each operation, it scans full dimensions of an object and thus, runs in linear time wrt the dimensionality.

Alexander V. Poshakinskiy, Alexander N. Poddubny

Quantum correlations between distant particles remain enigmatic since the birth of quantum mechanics. Here we predict a novel kind of bound quantum state in the simplest one-dimensional setup of two interacting particles in a box. Paradoxically, two entangled particles become localized at the opposite edges of the box even though their interactions at large

M V Sangaranarayanan

The zero-field partition function of two-dimensional nearest neighbor Ising models of square lattices is derived in terms of the generalized hypergeometric series by evaluating the integral in the exact solution of Onsager. An approximate equation for the partition function in terms of Chebyshev polynomials is also provided.

Davide Perego

In [BBM21], Belk, Bleak and Matucci proved that hyperbolic groups can be seen as subgroups of the rational group. In order to do so, they associated a tree of atoms to each hyperbolic group. Not so many connections between this tree and the literature on hyperbolic groups were known. In this paper, we prove an atom-version of the fellow traveler property and

Kristoffer Simula, Ilja Makkonen

Certain point defects in solids can efficiently be used as qubits for applications in quantum technology. They have spin states that are initializable, readable, robust, and can be manipulated optically. New theoretical methods are needed to find the best host materials and defect configurations. Most methods proposed so far rely either on cluster models or

Mikel Cortes-Goicoechea, Tarun Mohandas-Daryanani, Jose Luis Muñoz-Tapia, Leonardo Bautista-Gomez

Like most modern blockchain networks, Ethereum has relied on economic incentives to promote honest participation in the chain's consensus. The distributed character of the platform, together with the "randomness" or "luck" factor that both proof of work (PoW) and proof of stake (PoS) provide when electing the next block proposer, pushed the industry to model

Zhengbo Wang, Jian Liang, Zilei Wang, Tieniu Tan

Zero-shot learning (ZSL) aims to recognize unseen classes by generalizing the relation between visual features and semantic attributes learned from the seen classes. A recent paradigm called transductive zero-shot learning further leverages unlabeled unseen data during training and has obtained impressive results. These methods always synthesize unseen featu

Tom Claeys, Gabriel Glesner, Giulio Ruzza, Sofia Tarricone

We study J\'anossy densities of a randomly thinned Airy kernel determinantal point process. We prove that they can be expressed in terms of solutions to the Stark and cylindrical Korteweg-de Vries equations; these solutions are Darboux tranformations of the simpler ones related to the gap probability of the same thinned Airy point process. Moreover, we prove

Mario Reis, Yongqiang Cheng, Antonio M. dos Santos

This article describes a mean-field theoretical model for Spin-Crossover (SCO) materials and explores its implications. It is based on a simple Hamiltonian that yields the high spin molar fraction as a function of temperature and pressure, as well as a temperature-pressure phase diagram for the SCO transition. In order to test the model, we apply it to the g

Yun-Cheng Tsai, Jiun-Yu Huang, Da-Ru Chiou

As blockchain technology continues to gain attention, there is a growing need to make it more accessible to young learners in K-12 education. However, the technical complexity and lack of accessible tools have been identified as significant barriers to adoption. Our paper proposes a new method for empowering NFTs by continuously updating their metadata using

Takuma Masuda, Masaki Kobayashi, Koji Yatani

Photoemission spectroscopy, an experimental method based on the photoelectric effect, is now an indispensable technique used in various fields such as materials science, life science, medicine, and nanotechnology. However, part of the experimental process of photoemission spectroscopy relies on experience and intuition, which is difficult to understand for n

Zhihao Ouyang, Hubing Xiao, Jianzhen Chen, Anton A. Strigachev

The `blazar sequence' has been proposed for more than 20 years, yet its nature is still unclear. In this work, for the first time, we expand this topic to the TeV band by using a sample of 58 TeV blazars including 48 blazars in the quiescent state and 21 blazars in the flaring state. We investigate the correlation between the TeV luminosity, which has been c

Qianying Hu, Zhen Zhan, Huiying Cui, Yalei Zhang

Rydberg excitons, the solid-state counterparts of Rydberg atoms, have sparked considerable interest in harnessing their quantum application potentials, whereas a major challenge is realizing their spatial confinement and manipulation. Lately, the rise of two-dimensional moir\'e superlattices with highly tunable periodic potentials provides a possible pathway