March 2024 arXiv papers — page 139

Kristína Kallová, Peter G. Boorman, Claudio Ricci

X-ray spectroscopy of heavily obscured Active Galactic Nuclei (AGN) offers a unique opportunity to study the circum-nuclear environment of accreting supermassive black holes (SMBHs). However, individual models describing the obscurer have unique parameter spaces that give distinct parameter posterior distributions when fit to the same data. To assess the imp

Neria Uzan, Nir Weinberger

We propose a game-based formulation for learning dimensionality-reducing representations of feature vectors, when only a prior knowledge on future prediction tasks is available. In this game, the first player chooses a representation, and then the second player adversarially chooses a prediction task from a given class, representing the prior knowledge. The

Shaltiel Shmidman, Avi Shmidman, Moshe Koppel, Reut Tsarfaty

Syntactic parsing remains a critical tool for relation extraction and information extraction, especially in resource-scarce languages where LLMs are lacking. Yet in morphologically rich languages (MRLs), where parsers need to identify multiple lexical units in each token, existing systems suffer in latency and setup complexity. Some use a pipeline to peel aw

James Brister, Longjie Ran, Zheng Sun

We investigate non-Abelian R-symmetries in $\mathcal{N}=1$ supersymmetric theory, where fields may transform under the R-symmetry in representations with dimension higher than one. While a continuous non-Abelian R-symmetry can always be decomposed to a $U(1)$ R-symmetry and non-R symmetries, there are non-trivial discrete non-Abelian R-symmetries that do not

Yoshikazu Terada

Numerous estimators have been proposed for factor analysis, and their statistical properties have been extensively studied. In the early 2000s, a novel matrix factorization-based approach, known as Matrix Decomposition Factor Analysis (MDFA), was introduced and has been actively developed in computational statistics. The MDFA estimator offers several advanta

Bosco Garcia-Archilla, Volker John, Julia Novo

This paper studies discretization of time-dependent partial differential equations (PDEs) by proper orthogonal decomposition reduced order models (POD-ROMs). Most of the analysis in the literature has been performed on fully-discrete methods using first order methods in time, typically the implicit Euler time integrator. Our aim is to show which kind of erro

Onur Celik, Aleksandar Taranovic, Gerhard Neumann

Reinforcement learning (RL) is a powerful approach for acquiring a good-performing policy. However, learning diverse skills is challenging in RL due to the commonly used Gaussian policy parameterization. We propose \textbf{Di}verse \textbf{Skil}l \textbf{L}earning (Di-SkilL\footnote{Videos and code are available on the project webpage: \url{https://alrhub.gi

Erdem Sucu, Ali Övgün

In this study, we explore the influence of quark-antiquark confinement on the deflection angle within the framework of nonlinear electrodynamic (NED) black holes. To achieve this, we establish the appropriate optical spacetime metric and subsequently determine the Gaussian optical curvature. Utilizing the Gauss-Bonnet theorem, we investigate the impact of qu

Leonie Weissweiler, Abdullatif Köksal, Hinrich Schütze

Argument Structure Constructions (ASCs) are one of the most well-studied construction groups, providing a unique opportunity to demonstrate the usefulness of Construction Grammar (CxG). For example, the caused-motion construction (CMC, ``She sneezed the foam off her cappuccino'') demonstrates that constructions must carry meaning, otherwise the fact that ``s

Satya N. Majumdar, Gregory Schehr

We compute the connected two-time correlator of the maximum $M_N(t)$ of $N$ independent Gaussian stochastic processes (GSP) characterised by a common correlation coefficient $\rho$ that depends on the two times $t_1$ and $t_2$. We show analytically that this correlator, for fixed times $t_1$ and $t_2$, decays for large $N$ as a power law $N^{-\gamma}$ (with

Gregor Bachmann, Vaishnavh Nagarajan

Can a mere next-token predictor faithfully model human intelligence? We crystallize this emerging concern and correct popular misconceptions surrounding it, and advocate a simple multi-token objective. As a starting point, we argue that the two often-conflated phases of next-token prediction -- autoregressive inference and teacher-forced training -- must be

Gabriele Perna, Chiara Testini, Angelo Ricciardone, Sabino Matarrese

Scalar-induced Gravitational Waves (SIGWs) represent a particular class of primordial signals which are sourced at second-order in perturbation theory whenever a scalar fluctuation of the metric is present. They form a guaranteed Stochastic Gravitational Wave Background (SGWB) that, depending on the amplification of primordial scalar fluctuations, can be det

Ugur Demir, Debesh Jha, Zheyuan Zhang, Elif Keles

Deployments of artificial intelligence in medical diagnostics mandate not just accuracy and efficacy but also trust, emphasizing the need for explainability in machine decisions. The recent trend in automated medical image diagnostics leans towards the deployment of Transformer-based architectures, credited to their impressive capabilities. Since the self-at

Saehan Jo, Immanuel Trummer

The advancement of Large Language Models (LLMs) has significantly boosted performance in natural language processing (NLP) tasks. However, the deployment of high-performance LLMs incurs substantial costs, primarily due to the increased number of parameters aimed at enhancing model performance. This has made the use of state-of-the-art LLMs more expensive for

J. S. Castellanos Durán, N. Milanovic, A. Korpi-Lagg, B. Löptien

We present a catalog that we named MODEST containing depth-dependent information on the atmospheric conditions inside sunspot groups of all types. The catalog is currently composed of 942 observations of 117 individual active regions with sunspots that cover all types of features observed in the solar photosphere. We use the SPINOR-2D code to perform spatial

Yuri V. Kovchegov, Ming Li

We derive the first-ever small-$x$ expression for the inclusive gluon production cross section in the central rapidity region of the longitudinally polarized proton-proton collisions. The cross section depends on the polarizations of both protons, therefore comprising the numerator of the longitudinal double-spin asymmetry $A_{LL}$ for the produced gluons. T

A. Durán, G. M. Muslu

The present paper is concerned with the existence of solitary wave solutions of Rosenau-type equations. By using two standard theories, Normal Form Theory and Concentration-Compactness Theory, some results of existence of solitary waves of three different forms are derived. The results depend on some conditions on the speed of the waves with respect to the p

Apatsara Sareeto, Jörg Koppitz

In the present paper, a submonoid of the well studied monoid $POI_n$ of all order-preserving partial injections on an $n$-element chain is studied. The set $IOF_n^{par}$ of all partial transformations in $POI_n$ which are fence-preserving as well as parity-preserving form a submonoid of $POI_n$. We describe the Green's relations and ideals of $IOF_n^{par}$.

Harshad Shirwadkar

The World Wide Web WWW has arguably been the most popular application of the Internet for years. Over a period of time, it has developed over the principles of host centric IP internet. However, the limitations of todays host centric IP internet have motivated many future internet architectures that are centered around alternate principals such as content an

Jeremy Quail

A positroid is an ordered matroid realizable by a real matrix with all nonnegative maximal minors. Postnikov gave a map from ordered matroids to Grassmann necklaces, for which there is a unique positroid in each fiber of the map. Here, we give forbidden minor characterizations of ternary and quaternary positroids. We show that a positroid is ternary if and o

Manan Tayal, Bhavya Giri Goswami, Karthik Rajgopal, Rajpal Singh

This work presents a unified approach for collision avoidance using Collision-Cone Control Barrier Functions (CBFs) in both ground (UGV) and aerial (UAV) unmanned vehicles. We propose a novel CBF formulation inspired by collision cones, to ensure safety by constraining the relative velocity between the vehicle and the obstacle to always point away from each

Nima Karimitari, William J. Baldwin, Evan W. Muller, Zachary J. L. Bare

Low dimensional hybrid organic-inorganic perovskites (HOIPs) represent a promising class of electronically active materials for both light absorption and emission. The design space of HOIPs is extremely large, since a diverse space of organic cations can be combined with different inorganic frameworks. This immense design space allows for tunable electronic

Guillaume Bellegarda, Milad Shafiee, Merih Ekin Özberk, Auke Ijspeert

Legged robots are becoming increasingly agile in exhibiting dynamic behaviors such as running and jumping. Usually, such behaviors are either optimized and engineered offline (i.e. the behavior is designed for before it is needed), either through model-based trajectory optimization, or through deep learning-based methods involving millions of timesteps of si

Siddhant Satyanaik, Aditya Murali, Deepak Alapatt, Xin Wang

Purpose: Advances in deep learning have resulted in effective models for surgical video analysis; however, these models often fail to generalize across medical centers due to domain shift caused by variations in surgical workflow, camera setups, and patient demographics. Recently, object-centric learning has emerged as a promising approach for improved surgi

Jialu Li, Jaemin Cho, Yi-Lin Sung, Jaehong Yoon

Recent text-to-image (T2I) generation models have demonstrated impressive capabilities in creating images from text descriptions. However, these T2I generation models often fall short of generating images that precisely match the details of the text inputs, such as incorrect spatial relationship or missing objects. In this paper, we introduce SELMA: Skill-Sp

Tianhao Qi, Shancheng Fang, Yanze Wu, Hongtao Xie

The diffusion-based text-to-image model harbors immense potential in transferring reference style. However, current encoder-based approaches significantly impair the text controllability of text-to-image models while transferring styles. In this paper, we introduce DEADiff to address this issue using the following two strategies: 1) a mechanism to decouple t

Justin Engelmann, Diana Moukaddem, Lucas Gago, Niall Strang

Purpose: To investigate whether Fractal Dimension (FD)-based oculomics could be used for individual risk prediction by evaluating repeatability and robustness. Methods: We used two datasets: Caledonia, healthy adults imaged multiple times in quick succession for research (26 subjects, 39 eyes, 377 colour fundus images), and GRAPE, glaucoma patients with base

Ge Lei, Ronan Docherty, Samuel J. Cooper

Large Language Models (LLMs) have garnered considerable interest due to their impressive natural language capabilities, which in conjunction with various emergent properties make them versatile tools in workflows ranging from complex code generation to heuristic finding for combinatorial problems. In this paper we offer a perspective on their applicability t

Thomas Lam

We define and study the face stratification of the m=2 amplituhedron. We show that the face poset is an upper order ideal in the face poset of the totally nonnegative Grassmannian. Our construction is consistent with earlier work of Lukowski, and we confirm various predictions of Lukowski.

Yuting Zhang, Hao Lu, Xin Liu, Yingcong Chen

Remote photoplethysmography (rPPG) is a promising technology that captures physiological signals from face videos, with potential applications in medical health, emotional computing, and biosecurity recognition. The demand for rPPG tasks has expanded from demonstrating good performance on intra-dataset testing to cross-dataset testing (i.e., domain generaliz

Xinyao Li, Yuke Li, Zhekai Du, Fengling Li

Large vision-language models (VLMs) like CLIP have demonstrated good zero-shot learning performance in the unsupervised domain adaptation task. Yet, most transfer approaches for VLMs focus on either the language or visual branches, overlooking the nuanced interplay between both modalities. In this work, we introduce a Unified Modality Separation (UniMoS) fra

Tomasz Kochanek

For a discrete group $G$, we consider certain ideals $\mathcal{I}\subset c_0(G)$ of sequences with prescribed rate of convergence to zero. We show that the equality between the full group C$^\ast$-algebra of $G$ and the C$^\ast$-completion $\mathrm{C}_{\mathcal{I}}^\ast(G)$ in the sense of Brown and Guentner implies that $G$ is amenable.

Zheng Zhou, Xu-Yang Hou, Xin Wang, Jia-Chen Tang

The quantum geometric tensor (QGT) reveals local geometric properties and associated topological information of quantum states. Here a generalization of the QGT to mixed quantum states at finite temperatures based on the Sj$\ddot{\text{o}}$qvist distance is developed. The resulting Sj$\ddot{\text{o}}$qvist QGT is invariant under gauge transformations of indi

Chunchen Xu, Xiao Ge

The anthropocentric cultural idea that humans are active agents exerting control over their environments has been largely normalized and inscribed in practices, policies, and products of contemporary industrialized societies. This view underlies a human-ecology relationship based on resource and knowledge extraction. To create a more sustainable and equitabl

Lang Tong, Xinyi Wang, Qing Zhao

Purpose:This article advocates for the development of a next-generation grid monitoring and control system designed for future grids dominated by inverter-based resources. Leveraging recent progress in generative artificial intelligence (AI), machine learning, and networking technology, we develop a physics-based AI foundation model with high-resolution sync

Simon Schneider, Alexander Bakhtin, Xiaozhou Li, Jacopo Soldani

Architecture recovery tools help software engineers obtain an overview of their software systems during all phases of the software development lifecycle. This is especially important for microservice applications because their distributed nature makes it more challenging to oversee the architecture. Various tools and techniques for this task are presented in

Qing Xiao, Siyeop Yoon, Hui Ren, Matthew Tivnan

Alzheimer's Disease (AD) is a neurodegenerative condition characterized by diverse progression rates among individuals, with changes in cortical thickness (CTh) closely linked to its progression. Accurately forecasting CTh trajectories can significantly enhance early diagnosis and intervention strategies, providing timely care. However, the longitudinal data

Tomasz Kochanek

We study operator semigroups in the Calkin algebra $\mathcal{Q}(\mathcal{H})$, represented as a subalgebra of the algebra of bounded linear operators on a Hilbert space via one of `canonical' Calkin's representations. Using the BDF theory, we associate with any normal $C_0$-semigroup $(q(t))_{t\geq 0}$ in $\mathcal{Q}(\mathcal{H})$ an extension $\Gamma\in\ma

Anna Fischer, Toby Severs Millard, Xiaofei Xiao, T. V. Raziman

Surface lattice resonance (SLR) lasers, where gain is supplied by a thin film active material and the feedback comes from multiple scattering by plasmonic nanoparticles, have shown both low threshold lasing and tunability of the angular and spectral emission. However, typically used materials such as organic dyes and QD films suffer from photo-degradation wh

Ryan Wong, Nikita Kim, Kevin Higgs, Sapan Agarwal

As the amount of data produced in society continues to grow at an exponential rate, modern applications are incurring significant performance and energy penalties due to high data movement between the CPU and memory/storage. While processing in main memory can alleviate these penalties, it is becoming increasingly difficult to keep large datasets entirely in

Hui-hui Miao, Yuri Igorevich Ozhigov

A distributed computing approach to solve the curse of dimensionality, caused by the complex quantum system modeling, is discussed. With the help of Cannon's algorithm, the distributed computing transformation of numerical method for simulating quantum unitary evolution is achieved. Based on the Tavis-Cummings model, a large number of atoms are added into th

Lena Zellinger, Andreas Stephan, Benjamin Roth

Knowledge graph embeddings (KGEs) were originally developed to infer true but missing facts in incomplete knowledge repositories. In this paper, we link knowledge graph completion and counterfactual reasoning via our new task CFKGR. We model the original world state as a knowledge graph, hypothetical scenarios as edges added to the graph, and plausible chang

Alberto Testoni, Juell Sprott, Sandro Pezzelle

While human speakers use a variety of different expressions when describing the same object in an image, giving rise to a distribution of plausible labels driven by pragmatic constraints, the extent to which current Vision & Language Large Language Models (VLLMs) can mimic this crucial feature of language use is an open question. This applies to common, ever

Vemund Falch, Jeroen Danon, Alireza Qaiumzadeh, Arne Brataas

We investigate the impact of spin torque and spin pumping on the surface magnon polariton dispersion in a antiferromagnetic insulator-semiconductor heterostructure. In the bilayer system, the surface magnon polaritons conventionally couple to the plasma-oscillations in the semiconductor via electromagnetic fields. Additionally, magnons in the antiferromagnet

Jack S. Keeler, Mark G. Blyth

Two-dimensional free-surface flow over localised topography is examined with the emphasis on the stability of hydraulic-fall solutions. A Gaussian topography profile is assumed with a positive or negative amplitude modelling a bump or a dip, respectively. Steady hydraulic-fall solutions to the full incompressible, irrotational Euler equations are computed, a

Yanming Liu, Xinyue Peng, Tianyu Du, Jianwei Yin

Large language models (LLMs) have achieved commendable accomplishments in various natural language processing tasks. However, LLMs still encounter significant challenges when dealing with complex scenarios involving multiple entities. These challenges arise from the presence of implicit relationships that demand multi-step reasoning. In this paper, we propos

Daniel Latta-Lin, Sofia Isadora Padilla Munoz

Subsequence Dynamic Time Warping (sDTW) is the metric of choice when performing many sequence matching and alignment tasks. While sDTW is flexible and accurate, it is neither simple nor fast to compute; significant research effort has been spent devising parallel implementations on the GPU that leverage efficient memory access and computation patterns, as we

Jean-François Aujol, Charles Dossal, Hippolyte Labarrière, Aude Rondepierre

When considering the minimization of a quadratic or strongly convex function, it is well known that first-order methods involving an inertial term weighted by a constant-in-time parameter are particularly efficient (see Polyak [32], Nesterov [28], and references therein). By setting the inertial parameter according to the condition number of the objective fu

Aude Gehrmann-De Ridder, Christian T Preuss, Daniel Reichelt, Steffen Schumann

We present resummed predictions at next-to-leading logarithmic accuracy matched to the exact next-to-leading order results for a set of classical event-shape observables in hadronic Higgs decays, i.e., for the channels $H\to gg$ and $H\to b\bar{b}$. We furthermore consider soft-drop grooming of the hadronic final states and derive corresponding $\text{NLO}+\

Mei Ting Mak, Denis Sergeev, Nathan Mayne, Nahum Banks

Using a 3D General Circulation Model, the Unified Model, we present results from simulations of a tidally-locked TRAPPIST-1e with varying carbon dioxide CO2 and methane CH4 gas concentrations, and their corresponding prescribed spherical haze profiles. Our results show that the presence of CO2 leads to a warmer atmosphere globally due to its greenhouse effec

Li Chen, Zheng Ge, Su-Jian Niu, Yin-Hai Li

Four wave mixing (FWM) is an important way to generate supercontinuum and frequency combs in the mid-infrared band. Here, we obtain simultaneous synthetic FWM in the visible and mid-infrared bands by cascading quadratic nonlinear processes in a periodically poled lithium niobate crystal (PPLN), which has a 110dB(at 3000nm) higher conversion efficiency than t

Zach Goldthorpe

We provide a functorial presentation of the $(\infty, 1)$-category of sheaves of $(n, r)$-categories for all $-2 \leq n\leq\infty$ and $0 \leq r\leq n+2$ based on complete Segal space objects. In this definition, the equivalences of sheaves of $(\infty, \infty)$-categories are defined inductively, so we also provide a localisation at the coinductive equivale

Raül Espejo-Boix

Nowadays there is a large number of non-classical logics, each one best suited for reasoning about some issues in abstract fields, such as linguistics or epistemology, among others. Proving interesting properties for each one of them supposes a big workload for logicians and computer scientists. We want an approach into this problematic that is modular. To a

Bhavya Vasudeva, Deqing Fu, Tianyi Zhou, Elliott Kau

Transformers achieve state-of-the-art accuracy and robustness across many tasks, but an understanding of their inductive biases and how those biases differ from other neural network architectures remains elusive. In this work, we identify the sensitivity of the model to token-wise random perturbations in the input as a unified metric which explains the induc

Hongyaoxing Gu

In recent years, the fervent demand for computational power across various domains has prompted hardware manufacturers to introduce specialized computing hardware aimed at enhancing computational capabilities. Particularly, the utilization of tensor hardware supporting low precision has gained increasing prominence in scientific research. However, the use of

L. Magazzù, E. Paladino, M. Grifoni

We apply the Nakajima-Zwanzig approach to open quantum systems to study steady-state transport across generic multi-level junctions coupled to bosonic or fermionic reservoirs. The method allows for a unified diagrammatic formulation in Liouville space, with diagrams being classified according to an expansion in the coupling strength between the reservoirs an

Alfredo D. Millano, K. Dialektopoulos, N. Dimakis, A. Giacomini

We explore the phase-space of homogeneous and anisotropic spacetimes within symmetric teleparallel $f(Q)$-gravity. Specifically, we consider the Kantowski-Sachs and locally rotational Bianchi III geometries to describe the physical space. By analyzing the phase-space, we reconstruct the cosmological history dictated by $f(Q)$-gravity and comment about the th

Benjamin Monmege, Julie Parreaux, Pierre-Alain Reynier

Weighted Timed Games (WTG for short) are the most widely used model to describe controller synthesis problems involving real-time issues. The synthesized strategies rely on a perfect measure of time elapse, which is not realistic in practice. In order to produce strategies tolerant to timing imprecisions, we rely on a notion of robustness first introduced fo

Huiwen Yang, Xiaomeng Chen, Lingying Huang, Subhrakanti Dey

Over-the-air aggregation has attracted widespread attention for its potential advantages in task-oriented applications, such as distributed sensing, learning, and consensus. In this paper, we develop a communication-efficient distributed average consensus protocol by utilizing over-the-air aggregation, which exploits the superposition property of wireless ch

Alexander V. Gheorghiu, Tao Gu, David J. Pym

A short essay presenting the State-Effect Interpretation of natural deduction rules as an explanatory framework for recent developments in proof-theoretic semantics.

A. Pizzetti, N. Torres-Alba, S. Marchesi, J. Buchner

We present the multi-epoch analysis of 13 variable, nearby (z<0.1), Compton-thin (22<logN_H<24) active galactic nuclei (AGN) selected from the 105-month BAT catalog. Analyzing all available archival soft and hard X-ray observations, we investigate the line-of-sight hydrogen column density (N_H) variability on timescales ranging from a few days to approximate

Amit Dawadi, Arshad Kudrolli

We investigate the crumpling of a sheet as it is repeatedly crushed onto itself by rolling it into a cylinder and twisting it axially while allowing the end-to-end length to evolve freely. As deduced from its plastic deformations, the sheet creases and collapses into structures which repeat and sharpen over hundreds of cycles to a remarkable degree before fo

Katsumi Kina

We study the $\mthbb{Q}$-vector space generated by the double zeta values with character of conductor $4$. For this purpose, we define associated double Eisenstein series and investigate their relation with modular forms of level $4$.

David S. Kammer, Gregory C. McLaskey, Rachel E. Abercrombie, Jean-Paul Ampuero

Earthquakes are rupture-like processes that propagate along tectonic faults and cause seismic waves. The propagation speed and final area of the rupture, which determine an earthquake's potential impact, are directly related to the nature and quantity of the energy dissipation involved in the rupture process. Here we present the challenges associated with de

Filippo Campagnaro, Matin Ghalkhani, Riccardo Tumiati, Federico Marin

Monitoring the coastal area of the Venice Lagoon is of significant importance. While the impact of global warming is felt worldwide, coastal and littoral regions bear the brunt more prominently. These areas not only face the threat of rising sea levels but also contend with the escalating occurrence of seaquakes and floods. Additionally, the intricate ecosys

Yichuan Li, Xiyao Ma, Sixing Lu, Kyumin Lee

Large Language models (LLMs) have demonstrated impressive in-context learning (ICL) capabilities, where a LLM makes predictions for a given test input together with a few input-output pairs (demonstrations). Nevertheless, the inclusion of demonstrations leads to a quadratic increase in the computational overhead of the self-attention mechanism. Existing solu

Nicole M. Braunscheidel, Arnab Bachhar, Nicholas J. Mayhall

The task of computing wavefunctions that are accurate, yet simple enough mathematical objects to use for reasoning has long been a challenge in quantum chemistry. The difficulty in drawing physical conclusions from a wavefunction is often related to the generally large number of configurations with similar weights. In Tensor Product Selected CI, we use a loc

Jiahe Li, Jiawei Zhang, Xiao Bai, Jin Zheng

Radiance fields have demonstrated impressive performance in synthesizing novel views from sparse input views, yet prevailing methods suffer from high training costs and slow inference speed. This paper introduces DNGaussian, a depth-regularized framework based on 3D Gaussian radiance fields, offering real-time and high-quality few-shot novel view synthesis a

Bastiaan Cnossen, Rune Haugseng, Tobias Lenz, Sil Linskens

We prove that commutative semirings in a cartesian closed presentable $\infty$-category, as defined by Groth, Gepner, and Nikolaus, are equivalent to product-preserving functors from the $(2,1)$-category of bispans of finite sets. In other words, we identify the latter as the Lawvere theory for commutative semirings in the $\infty$-categorical context. This

Sabrina Goellner, Marina Tropmann-Frick, Bostjan Brumen

Our research endeavors to advance the concept of responsible artificial intelligence (AI), a topic of increasing importance within EU policy discussions. The EU has recently issued several publications emphasizing the necessity of trust in AI, underscoring the dual nature of AI as both a beneficial tool and a potential weapon. This dichotomy highlights the u

L. Magazzù, E. Paladino, M. Grifoni

Heat transport in the quantum Rabi model at weak interaction with the heat baths is controlled by the qubit-oscillator coupling. Universality of the linear conductance versus the temperature is found for $T\lesssim T_K$, with $T_K$ a coupling-dependent Kondo-like temperature. At low temperature, coherent heat transfer via virtual processes yields a $\sim T^3

Jiahui Zhang, Fangneng Zhan, Muyu Xu, Shijian Lu

3D Gaussian splatting has achieved very impressive performance in real-time novel view synthesis. However, it often suffers from over-reconstruction during Gaussian densification where high-variance image regions are covered by a few large Gaussians only, leading to blur and artifacts in the rendered images. We design a progressive frequency regularization (

Alexios Lekidis, Vasileios Mavroeidis, Konstantinos Fysarakis

The threat landscape of industrial infrastructures has expanded exponentially over the last few years. Such infrastructures include services such as the smart meter data exchange that should have real-time availability. Smart meters constitute the main component of the Advanced Metering Infrastructure, and their measurements are also used as historical data

Saunak Bhattacharjee

Let $f(x, y) \in \mathbb{Z}[x, y]$ be a cubic form with non-zero discriminant, and for each integer $m \in \mathbb{Z}$, let, $N_{f}(m)=\#\left\{(x, y) \in \mathbb{Z}^{2}: f(x, y)=m\right\} $. In 1983, Silverman proved that $N_{f}(m)>\Omega\left((\log |m|)^{3 / 5}\right)$ when $f(x, y)=x^{3}+y^{3}$. In this paper, we obtain an explicit bound for $N_f(m)$, nam

Jean V. Alves, Diogo Leitão, Sérgio Jesus, Marco O. P. Sampaio

Learning to defer (L2D) aims to improve human-AI collaboration systems by learning how to defer decisions to humans when they are more likely to be correct than an ML classifier. Existing research in L2D overlooks key real-world aspects that impede its practical adoption, namely: i) neglecting cost-sensitive scenarios, where type I and type II errors have di

Nazanin Dehghan, Alessio D'Errico, Francesco Di Colandrea, Ebrahim Karimi

The complete measurement of the quantum state of two correlated photons requires reconstructing the amplitude and phase of the biphoton wavefunction. We show how, by means of spatially resolved single photon detection, one can infer the spatial structure of bi-photons generated by spontaneous parametric down conversion. In particular, a spatially resolved an

Muhammad Saif Ullah Khan, Muhammad Ferjad Naeem, Federico Tombari, Luc Van Gool

We present a novel LLM-based pipeline for creating contextual descriptions of human body poses in images using only auxiliary attributes. This approach facilitates the creation of the MPII Pose Descriptions dataset, which includes natural language annotations for 17,367 images containing people engaged in 410 distinct activities. We demonstrate the effective

Kedar Karhadkar, Erin George, Michael Murray, Guido Montúfar

The problem of benign overfitting asks whether it is possible for a model to perfectly fit noisy training data and still generalize well. We study benign overfitting in two-layer leaky ReLU networks trained with the hinge loss on a binary classification task. We consider input data that can be decomposed into the sum of a common signal and a random noise com

Joaquim Comas, Adria Ruiz, Federico Sukno

Recent advances in remote heart rate measurement, motivated by data-driven approaches, have notably enhanced accuracy. However, these improvements primarily focus on recovering the rPPG signal, overlooking the implicit challenges of estimating the heart rate (HR) from the derived signal. While many methods employ the Fast Fourier Transform (FFT) for HR estim

Omar Momen

Linear sequences of words are implicitly represented in our brains by hierarchical structures that organize the composition of words in sentences. Linguists formalize different frameworks to model this hierarchy; two of the most common syntactic frameworks are Constituency and Dependency. Constituency represents sentences as nested groups of phrases, while d

Nikos Papanikolaou, Thomas Speck

We study Active Model B+, a scalar field theory extending the paradigmatic Model B for equilibrium coexistence through including terms that do not arise from an underlying free energy functional and thus break detailed balance. In the first part of the manuscript, we provide a pedagogical and self-contained introduction to one-loop dynamic renormalization. W

Dingrong Wang, Soheil Azadvar, Jon Heiselman, Xiajun Jiang

The surgical environment imposes unique challenges to the intraoperative registration of organ shapes to their preoperatively-imaged geometry. Biomechanical model-based registration remains popular, while deep learning solutions remain limited due to the sparsity and variability of intraoperative measurements and the limited ground-truth deformation of an or

Liangkun Yu, Xiang Sun, Rana Albelaihi, Chaeeun Park

Federated Learning (FL) revolutionizes collaborative machine learning among Internet of Things (IoT) devices by enabling them to train models collectively while preserving data privacy. FL algorithms fall into two primary categories: synchronous and asynchronous. While synchronous FL efficiently handles straggler devices, it can compromise convergence speed

Thomas Kropfreiter, Jason L. Williams, Florian Meyer

In many multiobject tracking applications, including radar and sonar tracking, after prefiltering the received signal, measurement data is typically structured in cells. The cells, e.g., represent different range and bearing values. However, conventional multiobject tracking methods use so-called point measurements. Point measurements are provided by a prepr

Gang Liao, Ye Liu, Yonghua Ding, Le Cai

The ubiquity of variable-length integers in data storage and communication necessitates efficient decoding techniques. In this paper, we present SFVInt, a simple and fast approach to decode the prevalent Little Endian Base-128 (LEB128) varints. Our approach effectively utilizes the Bit Manipulation Instruction Set 2 (BMI2) in modern Intel and AMD processors,

Wanshun Li, Hui-hui Miao, Yuri Igorevich Ozhigov

A general scheme is given for supercomputer simulation of quantum processes, which are described by various modifications of finite-dimensional cavity quantum electrodynamics models, including Jaynes-Cummings-Hubbard model and Tavis-Cummings-Hubbard model. Conclusions and recommendations are illustrated using two examples: approximate model of hydrogen bondi

Ákos K. Matszangosz, Matthias Wendt

We investigate the existence of 4-torsion in the integral cohomology of oriented Grassmannians. We prove a general criterion for the appearance of 4-torsion classes based on (twisted) Steenrod squares and show that there are many cases where this criterion is satisfied for minimal-degree anomalous classes, assuming a conjecture on the characteristic rank. We

Tim Chan, Andrei Constantin

The contextual fraction introduced by Abramsky and Brandenburger defines a quantitative measure of contextuality associated with empirical models, i.e. tables of probabilities of measurement outcomes in experimental scenarios. In this paper we define an entanglement monotone relying on the contextual fraction. We first show that any separable state is necess

N K Sagar Reddy, Neeraj Kasera, Avinash Thakur

Our research focuses on the analysis and improvement of the Graph-based Relation Inference Transformer (GRIT), which serves as an important benchmark in the field. We conduct a comprehensive ablation study using the PISC-fine dataset, to find and explore improvement in efficiency and performance of GRITv2. Our research has provided a new state-of-the-art rel

Jiaan Qi, Zhi-Hai Liu, Hongqi Xu

The prospect of large-scale quantum computation with an integrated chip of spin qubits is imminent as technology improves. This invites us to think beyond the traditional 2-qubit-gate framework and consider a naturally supported ``instruction set'' of multi-qubit gates. In this work, we systematically study such a family of multi-qubit gates implementable ov

Hirofumi Takesue

The preferential treatment of in-group members is widely observed. This study examines this phenomenon in the domain of cooperation in social dilemmas using evolutionary agent-based models that consider the role of partner selection. The model considers a repeated prisoner's dilemma game, in which agents belong to one of two groups that are distinguished by

Tiancheng Zhao, Peng Liu, Xuan He, Lu Zhang

End-to-end transformer-based detectors (DETRs) have shown exceptional performance in both closed-set and open-vocabulary object detection (OVD) tasks through the integration of language modalities. However, their demanding computational requirements have hindered their practical application in real-time object detection (OD) scenarios. In this paper, we scru

Shuqi He, Haonan Yao, Luyan Jiang, Kaiwen Li

Tangible interfaces in mixed reality (MR) environments allow for intuitive data interactions. Tangible cubes, with their rich interaction affordances, high maneuverability, and stable structure, are particularly well-suited for exploring multi-dimensional data types. However, the design potential of these cubes is underexplored. This study introduces a desig

Debarshi Kundu, Archisman Ghosh, Srinivasan Ekambaram, Jian Wang

We show that protein sequences can be thought of as sentences in natural language processing and can be parsed using the existing Quantum Natural Language framework into parameterized quantum circuits of reasonable qubits, which can be trained to solve various protein-related machine-learning problems. We classify proteins based on their subcellular location

Julian Schwarting, Fabian Holzberger, Markus Muhr, Martin Renz

Rupture of intracranial aneurysms results in severe subarachnoidal hemorrhage, which is associated with high morbidity and mortality. Neurointerventional occlusion of the aneurysm through coiling has evolved to a therapeutical standard. The choice of the specific coil has an important influence on secondary regrowth requiring retreatment. Aneurysm occlusion

Abhishek Hanchate, Himanshu Balhara, Vishal S. Chindepalli, Satish T. S. Bukkapatnam

We present HiRA-Pro, a novel procedure to align, at high spatio-temporal resolutions, multimodal signals from real-world processes and systems that exhibit diverse transient, nonlinear stochastic dynamics, such as manufacturing machines. It is based on discerning and synchronizing the process signatures of salient kinematic and dynamic events in these dispar

Franco Parlamento, Flavio Previale

On the ground of a general theorem concerning the admissibility of the structural rules in sequent calculi with additional atomic rules, we develop a proof theoretic analysis for several extensions of the ${\bf G3[mic]}$ sequent calculi with rules for equality, including the one originally proposed by H.Wang. In the classical case we relate our results with

Shaobing Yuan, Changkai Luo, Zezhou Hu, Zhenyu Zhang

Incorporating first-order QED effects, we explore the shadows of Kerr-Newman black holes with a magnetic charge through the numerical backward ray-tracing method. Our investigation accounts for both the direct influence of the electromagnetic field on light rays and the distortion of the background spacetime metric due to QED corrections. We notice that the

Tauheed Khan Mohd, Ahmad Y Javaid

Interactions with electronic devices are changing in our daily lives. The day-to-day development brings curiosity to recent technology and challenges its use. The gadgets are becoming cumbersome, and their usage frustrates a segment of society. In specific scenarios, the user cannot use the modalities because of the challenges that bring in, e.g., the usage

Jorn van Kampen, Mauro Moriggi, Francesco Braghin, Mauro Salazar

This paper presents model predictive control strategies for battery electric endurance race cars accounting for interactions with the competitors. In particular, we devise an optimization framework capturing the impact of the actions of the ego vehicle when interacting with competitors in a probabilistic fashion, jointly accounting for the optimal pit stop d