December 2023 arXiv papers — page 13

Sergey S. Boiko, Vladimir K. Dubovoy, Bernd Fritzsche, Bernd Kirstein

In this paper we would like to show the interrelation between the different mathematical theories concerning the Schur interpolation problem, contractions in Hilbert spaces, pseudocontinuation and Darlington synthesis. The main objects of this article are contractive functions holomorphic in the unit disc (Schur functions). Here they are considered, on the o

Vedant Motamarri, Campbell McLauchlan, Benjamin Béri

Symmetry Topological Field Theory (SymTFT) is a framework to capture universal features of quantum many-body systems by viewing them as a boundary of topological order in one higher dimension. This has yielded numerous insights in static low-energy settings. Here we study what SymTFT can reveal about nonequilibrium, focusing on one-dimensional (1D) periodica

Lukas Schickhofer, Chris G. Antonopoulos

Despite long-term research and development of modern shock absorbers, the effect of variations of several crucial material and model parameters still remains dubious. The goal of this work is therefore a study of the changes of shock absorber dynamics with respect to typical parameter ranges in a realistic model. We study the impact of shim properties, as we

Ying Wang, Tim G. J. Rudner, Andrew Gordon Wilson

Vision-language pretrained models have seen remarkable success, but their application to safety-critical settings is limited by their lack of interpretability. To improve the interpretability of vision-language models such as CLIP, we propose a multi-modal information bottleneck (M2IB) approach that learns latent representations that compress irrelevant info

Sanae Lotfi, Marc Finzi, Yilun Kuang, Tim G. J. Rudner

Modern language models can contain billions of parameters, raising the question of whether they can generalize beyond the training data or simply parrot their training corpora. We provide the first non-vacuous generalization bounds for pretrained large language models (LLMs), indicating that language models are capable of discovering regularities that genera

Jiasen Lu, Christopher Clark, Sangho Lee, Zichen Zhang

We present Unified-IO 2, the first autoregressive multimodal model that is capable of understanding and generating image, text, audio, and action. To unify different modalities, we tokenize inputs and outputs -- images, text, audio, action, bounding boxes, etc., into a shared semantic space and then process them with a single encoder-decoder transformer mode

AseshKrishna Datta, Sourov Roy, Abhijit Kumar Saha, Ananya Tapadar

The present study aims to unveil a scenario with a non-minimal secluded dark sector (DS) in an effective field theory (EFT) framework. To explore this, we have examined a suitable extension of the type-X Two Higgs Doublet Model (2HDM) as a potential origin for the secluded DS. The DS comprises a dark matter (DM) candidate and a mediator particle `$a$' and po

Volodymyr Bavula

A classification of multiplication modules over multiplication rings with finitely many minimal primes is obtained. A characterisation of multiplication rings with finitely many minimal primes is given via faithful, Noetherian, distributive modules. It is proven that for a multiplication ring with finitely many minimal primes every faithful, Noetherian, dist

Peter C. Rigby, Seth Rogers, Sadruddin Saleem, Parth Suresh

The code review team at Meta is continuously improving the code review process. To evaluate the new recommenders, we conduct three A/B tests which are a type of randomized controlled experimental trial. Expt 1. We developed a new recommender based on features that had been successfully used in the literature and that could be calculated with low latency. In

Gunshi Gupta, Tim G. J. Rudner, Rowan Thomas McAllister, Adrien Gaidon

Causal confusion is a phenomenon where an agent learns a policy that reflects imperfect spurious correlations in the data. Such a policy may falsely appear to be optimal during training if most of the training data contain such spurious correlations. This phenomenon is particularly pronounced in domains such as robotics, with potentially large gaps between t

Moran Koren

We study the problem of screening in decision-making processes under uncertainty, focusing on the impact of adding an additional screening stage, commonly known as a 'gatekeeper.' While our primary analysis is rooted in the context of job market hiring, the principles and findings are broadly applicable to areas such as educational admissions, healthcare pat

Rohan Joshi, Saikat Mondal, Souvik Bandyopadhyay, Sourav Bhattacharjee

Lindbladian formalism, as tuned to dissipative and open systems, has been all-pervasive to interpret non-equilibrium steady states of quantum many-body systems. We study the fate of free fermionic and superconducting phases in a dissipative one-dimensional Kitaev model - where the bath acts both as a source and a sink of fermionic particles with different co

Sachin Grover, Subramanya Hegde, Dileep P. Jatkar

We discuss the construction of duality defects in $c=24$ meromorphic CFTs that correspond to Niemeier lattices. We will illustrate our constructions for the $D_n$-type lattices. We will identify non-anomalous $\mathbb{Z}_2$ symmetries of these theories, and we show that on orbifolding with respect to these symmetries, these theories map to each other. We inv

Yalin E. Sagduyu, Tugba Erpek, Yi Shi

This paper studies the poisoning attack and defense interactions in a federated learning (FL) system, specifically in the context of wireless signal classification using deep learning for next-generation (NextG) communications. FL collectively trains a global model without the need for clients to exchange their data samples. By leveraging geographically disp

Liman Wang, Hanyang Zhong

Inspired by human driving focus, this research pioneers networks augmented with Focusing Sampling, Partial Field of View Evaluation, Enhanced FPN architecture and Directional IoU Loss - targeted innovations addressing obstacles to precise lane detection for autonomous driving. Experiments demonstrate our Focusing Sampling strategy, emphasizing vital distant

Tim G. J. Rudner, Sanyam Kapoor, Shikai Qiu, Andrew Gordon Wilson

Parameter-space regularization in neural network optimization is a fundamental tool for improving generalization. However, standard parameter-space regularization methods make it challenging to encode explicit preferences about desired predictive functions into neural network training. In this work, we approach regularization in neural networks from a probab

Zheng Ding, Xuaner Zhang, Zhuowen Tu, Zhihao Xia

The inherent generative power of denoising diffusion models makes them well-suited for image restoration tasks where the objective is to find the optimal high-quality image within the generative space that closely resembles the input image. We propose a method to adapt a pretrained diffusion model for image restoration by simply adding noise to the input ima

Pujian Mao, Weicheng Zhao

In this paper, we provide a self-contained investigation of the Weyl double copy in the Newman-Penrose formalism. We examine the Weyl double copy constraints for the general asymptotically flat solution in the Newman-Unti gauge. We find that two transparent solutions of the asymptotic Weyl double copy constraints lead to truncated solutions for both lineariz

Ramona Ghilea, Islem Rekik

Learning from limited data has been extensively studied in machine learning, considering that deep neural networks achieve optimal performance when trained using a large amount of samples. Although various strategies have been proposed for centralized training, the topic of federated learning with small datasets remains largely unexplored. Moreover, in reali

Mathias Braun, Robert J. McCann

We describe a nonsmooth notion of globally hyperbolic, regular length metric spacetimes $(\mathrm{M},l)$. It is based on ideas of Kunzinger-S\"amann, but does not require Lipschitz continuity of causal curves. We study geodesics on $\mathrm{M}$ and the space of probability measures over $\mathrm{M}$ in detail. Furthermore, for such a spacetime endowed with a

Volodymyr Bavula

This paper consists of three parts: (I) To develop general theory of a (large) class of central simple finite dimensional algebras and answering some natural questions about them (that in general situation it is not even clear how to approach them, and the Brauer group is a step in the right directions), (II) To introduce and develop general theory of a larg

J. Doyne Farmer, John Geanakoplos, Matteo G. Richiardi, Miquel Montero

We present a thorough empirical study on real interest rates by also including risk aversion through the introduction of the market price of risk. With the view of complex systems science and its multidisciplinary approach, we use the theory of bond pricing to study the long term discount rate. Century-long historical records of 3 month bonds, 10 year bonds,

Chih-Cheng Chang, Li Su

Many deep learning models have achieved dominant performance on the offline beat tracking task. However, online beat tracking, in which only the past and present input features are available, still remains challenging. In this paper, we propose BEAt tracking Streaming Transformer (BEAST), an online joint beat and downbeat tracking system based on the streami

Emily R. Taylor, Samuel Yencho, L. H. Ford

The quantum fluctuations of fields can exhibit subtle correlations in space and time. As the interval between a pair of measurements varies, the correlation function can change sign, signaling a shift between correlation and anti-correlation. A numerical simulation of the fluctuations requires a knowledge of both the probability distribution and the correlat

Dibaloke Chanda, Saba Heidari Gheshlaghi, Nasim Yahya Soltani

Despite the success of graph neural networks (GNNs) in various domains, they exhibit susceptibility to adversarial attacks. Understanding these vulnerabilities is crucial for developing robust and secure applications. In this paper, we investigate the impact of test time adversarial attacks through edge perturbations which involve both edge insertions and de

M. B. Paranjape, Yash Saxena

We study numerically the existence in a false vacuum, of magnetic monopoles which are ``thin-walled'', \ie, which correspond to a spherical region of radius $R$ that is essentially trivial surrounded by a wall of thickness $\Delta\ll R$, hence the name thin wall, and finally an exterior region that essentially corresponds to a pure Abelian magnetic monopole.

Tian-Xiao He

We define the $m$th-order Eulerian numbers with a combinatorial interpretation. The recurrence relation of the $m$th-order Eulerian numbers, the row generating function and the row sums of the $m$th-order Eulerian triangle are presented. We also define the $m$th-order Eulerian fraction and its alternative form. Some properties of the $m$th-order Eulerian fra

Aniruddha Samanta, M. Rajesh Kannan

A complex unit gain graph ($ \mathbb{T} $-gain graph), $ \Phi=(G, \varphi) $ is a graph where the gain function $ \varphi $ assigns a unit complex number to each orientation of an edge of $ G $ and its inverse is assigned to the opposite orientation. The associated adjacency matrix $ A(\Phi) $ is defined canonically. The energy $ \mathcal{E}(\Phi) $ of a $ \

Isaac R. Wang, Xun-Jie Xu

Neutrinos are often considered as a portal to new physics beyond the Standard Model (SM) and might possess phenomenologically interesting interactions with dark matter (DM). This paper examines the cosmological imprints of DM that interacts with and is produced from SM neutrinos at temperatures below the MeV scale. We take a model-independent approach to com

Mingchen Xia

We define the basic pluripotential-theoretic operations in terms of the transcendental theory of non-Archimedean metrics introduced in \cite{DXZ23}. In particular, we establish that the analogue of Boucksom--Jonsson's envelope conjecture holds in our theory.

John Keiser, Daniel Lemire

JSON is a popular standard for data interchange on the Internet. Ingesting JSON documents can be a performance bottleneck. A popular parsing strategy consists in converting the input text into a tree-based data structure -- sometimes called a Document Object Model or DOM. We designed and implemented a novel JSON parsing interface -- called On-Demand -- that

Kam Cheong Au, Steven Charlton, Michael E. Hoffman

We establish an identity amongst certain differential operators applied to a formal power-series. As a corollary we obtain an explicit depth reduction result for alternating MZV's of the form $\zeta(1,\ldots,1,\overline{2m})$, which resolves a conjecture posed earlier by the third author.

Guangyi Liu, Christoforos Somarakis, Nader Motee

This paper establishes and explores a framework to analyze the risk of cascading failures in a platoon of autonomous vehicles, accounting for communication time-delays and input uncertainty. Our proposed framework yields closed-form expressions for cascading collisions, which we quantify using the coherent Average Value-at-Risk ($\AVAR$) to assess the cascad

Abhinav Anand, Kenneth R. Brown

One promising application of near-term quantum devices is to prepare trial wavefunctions using short circuits for solving different problems via variational algorithms. For this purpose, we introduce a new circuit design that combines graph-based diagonalization circuits with arbitrary single-qubit rotation gates to get Hamiltonian-based graph states ans\"at

Volodymyr Bavula

The aim of the paper is to start to develop the most general theory of localizations/inversion. Several new concepts are introduced and studied.

Jeehoon Park, Junyeong Park

We describe the primitive middle-dimensional cohomology $\mathbb{H}$ of a compact simplicial toric complete intersection variety in terms of a twisted de Rham complex. Then this enables us to construct a concrete algorithm of formal flat $F$-manifold structures on $\mathbb{H}$ in the Calabi-Yau case by using the techniques of \cite{Park23}, which turn the tw

Padmaksha Roy, Tyler Cody, Himanshu Singhal, Kevin Choi

Zero-day anomaly detection is critical in industrial applications where novel, unforeseen threats can compromise system integrity and safety. Traditional detection systems often fail to identify these unseen anomalies due to their reliance on in-distribution data. Domain generalization addresses this gap by leveraging knowledge from multiple known domains to

Xueliang Wu, Zhixiang Hu, David Graf, Yu Liu

We report a comprehensive study of magnetotransport properties, angle-resolved photoemission spectroscopy (ARPES), and density functional theory (DFT) calculations on self-flux grown LaAuSb$_2$ single crystals. Resistivity and Hall measurements reveal a charge density wave (CDW) transition at 77 K. MR and de Haas-Van Alphen (dHvA) measurements indicate that

Jiawei Ren, Liang Pan, Jiaxiang Tang, Chi Zhang

4D content generation has achieved remarkable progress recently. However, existing methods suffer from long optimization times, a lack of motion controllability, and a low quality of details. In this paper, we introduce DreamGaussian4D (DG4D), an efficient 4D generation framework that builds on Gaussian Splatting (GS). Our key insight is that combining expli

Dario Stein, Sam Staton

We spell out the paradigm of exact conditioning as an intuitive and powerful way of conditioning on observations in probabilistic programs. This is contrasted with likelihood-based scoring known from languages such as Stan. We study exact conditioning in the cases of discrete and Gaussian probability, presenting prototypical languages for each case and givin

Volodymur Bavula

The set of minimal primes of a ring is a very important set as far the spectrum of a ring is concerned as every prime contains a minimal prime. So, knowing the minimal primes is the first (important and difficult) step in describing the spectrum. In the algebraic geometry, the minimal primes of the algebra of regular functions on an algebraic variety determi

Venkatesan Guruswami, Karthik C. S., Pasin Manurangsi, Xuandi Ren

Recently, Ohsaka [STACS'23] put forth the Reconfiguration Inapproximability Hypothesis (RIH), which roughly asserts that there is some $\epsilon>0$ such that given as input a $k$-CSP instance (for some constant $k$) over some constant sized alphabet, and two satisfying assignments $\psi_s$ and $\psi_t$, it is PSPACE-hard to find a sequence of assignments sta

Alexander Dunlap, Lenya Ryzhik

We study a voting model on a branching Brownian motion process on $\mathbb{R}$ in which the diffusivity of each child particle is increased from that of the parent by a factor of $\gamma>1$. The probability distribution of the overall vote is given in terms of the solution to a nonlocal nonlinear PDE. We exhibit conditions on the nonlinearity such that the l

Hee-Joong Chung, Dohyeong Kim, Minhyong Kim, Jeehoon Park

The notion of {\em entanglement entropy} in quantum mechanical systems is an important quantity, which measures how much a physical state is entangled in a composite system. Mathematically, it measures how much the state vector is not decomposable as elements in the tensor product of two Hilbert spaces. In this paper, we seek its arithmetic avatar: the theor

Filippo Mazzoli, Gabriele Viaggi

We investigate properties of the pseudo-Riemannian volume, entropy, and diameter for convex cocompact representations $\rho : \Gamma \to \mathrm{SO}(p,q+1)$ of closed $p$-manifold groups. In particular: We provide a uniform lower bound of the product entropy times volume that depends only on the geometry of the abstract group $\Gamma$. We prove that the entr

Masanori Hanada, Hiroki Ohata, Hidehiko Shimada, Hiromasa Watanabe

We describe how the general mechanism of partial deconfinement applies to large-$N$ QCD and the partially-deconfined phase inevitably appears between completely-confined and completely-deconfined phases. Furthermore, we propose how the partial deconfinement can be observed in the real-world QCD with SU(3) gauge group. We propose the relationship between the

Jiawei Ren, Mingyuan Zhang, Cunjun Yu, Xiao Ma

Generating animation of physics-based characters with intuitive control has long been a desirable task with numerous applications. However, generating physically simulated animations that reflect high-level human instructions remains a difficult problem due to the complexity of physical environments and the richness of human language. In this paper, we prese

Alexandre Marcowith

These lectures address the effects of Cosmic Rays over macro-instabilities which develop in the interstellar medium and the micro-instabilities the particles are able to trigger themselves. The lectures are centered on the derivation of linear growth rates but also discuss some numerical simulations addressing the issue of magnetic field saturation. A partic

Yifan Bai, Zeyang Zhao, Yihong Gong, Xing Wei

We present ARTrackV2, which integrates two pivotal aspects of tracking: determining where to look (localization) and how to describe (appearance analysis) the target object across video frames. Building on the foundation of its predecessor, ARTrackV2 extends the concept by introducing a unified generative framework to "read out" object's trajectory and "rete

Barak Gabai, Amit Sever, De-liang Zhong

The expectation value of a smooth conformal line defect in a CFT is a conformal invariant functional of its path in space-time. For example, in large $N$ holographic theories, these fundamental observables are dual to the open string partition function in AdS. In this paper, we develop a bootstrap method for studying them and apply it to conformal line defec

Mark Kelbert, Harold A. Moreno-Franco

We study the problem of optimal risk policies and dividend strategies for an insurance company operating under the constraint that the timing of shareholder payouts is governed by the arrival times of a Poisson process. Concurrently, risk control is continuously managed through proportional reinsurance. Our analysis confirms the optimality of a periodic-clas

Raphael Steiner

The Odd Hadwiger's conjecture, formulated by Gerards and Seymour in 1995, is a substantial strengthening of Hadwiger's famous coloring conjecture from 1943. We investigate whether the hierarchy of topological lower bounds on the chromatic number, introduced by Matou\v{s}ek and Ziegler (2003) and refined recently by Daneshpajouh and Meunier (2023), forms a po

Dhamar S. Astilla, Sujoy K. Modak, Enrique Salazar

We further investigate novel features of the $T-$vacuum state, originally defined in the context of quantum field theory in a (1+1) dimensional radiation dominated universe [Modak, JHEP 12, 031 (2020)]. Here we extend the previous work to a realistic (3+1) dimensional set up and show that $T-$vacuum gives rise to an anisotropic particle creation phenomena in

Volodymyr Bavula

Goldie's Theorem implies that a semiprime left Goldie ring is embeddable into a semisimple Artinian ring. On the other hand, there are domains that are not embeddable into division rings. A criterion for a semiprime ring being embeddable into a semisimple Artinian ring is given. Three types of embeddings of semiprime rings into semisimple Artinian rings are

Nathanael L. Ackerman, Cameron E. Freer, Younesse Kaddar, Jacek Karwowski

We study semantic models of probabilistic programming languages over graphs, and establish a connection to graphons from graph theory and combinatorics. We show that every well-behaved equational theory for our graph probabilistic programming language corresponds to a graphon, and conversely, every graphon arises in this way. We provide three constructions f

Lara B. Anderson, James Gray, Magdalena Larfors

Calabi-Yau (CY) manifolds play a ubiquitous role in string theory. As a supersymmetry-preserving choice for the 6 extra compact dimensions of superstring compactifications, these spaces provide an arena in which to explore the rich interplay between physics and geometry. These lectures will focus on compact CY manifolds and the long standing problem of deter

Beata E. Kowal, Krzysztof M. Graczyk, Artur M. Ankowski, Rwik Dharmapal Banerjee

Employing the neural network framework, we obtain empirical fits to the electron-scattering cross sections for carbon over a broad kinematic region, extending from the quasielastic peak through resonance excitation to the onset of deep-inelastic scattering. We consider two different methods of obtaining such model-independent parametrizations and the corresp

Zhe Li, Ren-You Zhang, Shu-Xiang Li, Xiao-Feng Wang

We present a comprehensive analytic calculation of the next-to-next-to-leading order $\text{QCD} \otimes \text{EW}$ corrections to $Z$-boson pair production at electron-positron colliders. The two-loop master integrals essential to this calculation are evaluated using the differential equation method. In this work, we detail the formulation and solution of t

Pauline Leung, Zhuan Pei

Evidence on the effectiveness of retraining U.S. unemployed workers primarily comes from evaluations of training programs, which represent one narrow avenue for skill acquisition. We use high-quality records from Ohio and a matching method to estimate the effects of retraining, broadly defined as enrollment in postsecondary institutions. Our simple method br

Haitao Jiang, Lin Ge, Yuhe Gao, Jianian Wang

Large Language Models (LLMs) have shown their success in language understanding and reasoning on general topics. However, their capability to perform inference based on user-specified structured data and knowledge in corpus-rare concepts, such as causal decision-making is still limited. In this work, we explore the possibility of fine-tuning an open-sourced

João Lourenço

We derive a Serre presentation of distribution algebras of loop groups in characteristic $p$ and apply it to give a new proof of the normality of Schubert varieties inside parahoric affine Grassmannians, for all connected reductive groups whose fundamental group is $p$-torsion free.

Zengzhi Wang, Xuefeng Li, Rui Xia, Pengfei Liu

High-quality, large-scale corpora are the cornerstone of building foundation models. In this work, we introduce MathPile, a diverse and high-quality math-centric corpus comprising about 9.5 billion tokens. Throughout its creation, we adhered to the principle of "less is more", firmly believing in the supremacy of data quality over quantity, even in the pre-t

V. M. Khatsymovsky

An attempt to directly use the synchronous gauge ($g_{0 \lambda} = - \delta_{0 \lambda}$) in perturbative gravity leads to a singularity at $p_0 = 0$ in the graviton propagator. This is similar to the singularity in the propagator for Yang-Mills fields $A^a_\lambda$ in the temporal gauge ($A^a_0 = 0$). There the singularity was softened, obtaining this gauge

Haisong Liu, Yang Chen, Haiguang Wang, Zetong Yang

Occupancy prediction plays a pivotal role in autonomous driving. Previous methods typically construct dense 3D volumes, neglecting the inherent sparsity of the scene and suffering from high computational costs. To bridge the gap, we introduce a novel fully sparse occupancy network, termed SparseOcc. SparseOcc initially reconstructs a sparse 3D representation

Houlun Chen, Xin Wang, Hong Chen, Zihan Song

Temporal Sentence Grounding (TSG), which aims to localize moments from videos based on the given natural language queries, has attracted widespread attention. Existing works are mainly designed for short videos, failing to handle TSG in long videos, which poses two challenges: i) complicated contexts in long videos require temporal reasoning over longer mome

Ziyu Wang, Yanjie Ze, Yifei Sun, Zhecheng Yuan

Learning policies that can generalize to unseen environments is a fundamental challenge in visual reinforcement learning (RL). While most current methods focus on acquiring robust visual representations through auxiliary supervision, pre-training, or data augmentation, the potential of modern vision foundation models remains underleveraged. In this work, we

Aldo Conca

Let $R$ be a finitely generated $\mathbb N$-graded algebra domain over a Noetherian ring and let $I$ be a homogeneous ideal of $R$. Given $P\in Ass(R/I)$ one defines the $v$-invariant $v_P(I)$ of $I$ at $P$ as the least $c\in \mathbb N$ such that $P=I:f$ for some $f\in R_c$. A classical result of Brodmann asserts that $Ass(R/I^n)$ is constant for large $n$.

Yang Xiao, Yi Cheng, Jinlan Fu, Jiashuo Wang

In recent years, AI has demonstrated remarkable capabilities in simulating human behaviors, particularly those implemented with large language models (LLMs). However, due to the lack of systematic evaluation of LLMs' simulated behaviors, the believability of LLMs among humans remains ambiguous, i.e., it is unclear which behaviors of LLMs are convincingly hum

Sonali Patnaik, Lopamudra Nayak, Priyanka Sadangi, Sanjay Swain

In this work, we investigate angular observables such as the longitudinal polarization of charged leptons, $\tau$-polarization, and forward-backward asymmetry in semileptonic $B_c$ decays. Additionally, we provide predictions for lepton flavor violating observables, the $\mathcal{R}$ ratios in the decay channels $B_c \rightarrow \eta_c (J/\psi) l \nu_l$ and

Christiana Chamon, Kamalesh Mohanasundar, Sarah A. Flanery, Francis K. Quek

This paper presents a statistical physical generation of random keys for a decentralized identity ecosystem that uses Web 3.0 protocols. Web 3.0 is driven by secure keys, typically represented in hexadecimal, that are pseudo-randomly generated by an initialization vector and complex computational algorithms. We demonstrate that the statistical physical Kirch

Renan Assimos, Yaoting Gui, Jürgen Jost

We prove the local Lipschitz continuity of sub-elliptic harmonic maps between certain singular spaces, more specifically from the $n$-dimensional Heisenberg group into $CAT(0)$ spaces. Our main theorem establishes that these maps have the desired Lipschitz regularity, extending the H\"older regularity in this setting proven by Y. Gui et. al and obtaining sam

Xinshuai Dong, Haoyue Dai, Yewen Fan, Songyao Jin

Financial data is generally time series in essence and thus suffers from three fundamental issues: the mismatch in time resolution, the time-varying property of the distribution - nonstationarity, and causal factors that are important but unknown/unobserved. In this paper, we follow a causal perspective to systematically look into these three demons in finan

Xin Wen, Will Wei Sun, Yichen Zhang

Contemporary applications, such as recommendation systems and mobile health monitoring, require real-time processing and analysis of sequentially arriving high-dimensional tensor data. Traditional offline learning, involving the storage and utilization of all data in each computational iteration, becomes impractical for these tasks. Furthermore, existing low

Mohamad Qadri, Harry Freeman, Eric Schneider, George Kantor

Agricultural robotics is an active research area due to global population growth and expectations of food and labor shortages. Robots can potentially help with tasks such as pruning, harvesting, phenotyping, and plant modeling. However, agricultural automation is hampered by the difficulty in creating high resolution 3D semantic maps in the field that would

Alice Allen, Alberto Accomazzi, Joe P. Renaud

The Astrophysics Source Code Library (ASCL) is a free online registry for source codes of interest to astronomers, astrophysicists, and planetary scientists. It lists, and in some cases houses, software that has been used in research appearing in or submitted to peer-reviewed publications. As of December 2023, it has over 3300 software entries and is indexed

Wenyi Wu, Qi Li, Wenliang Zhong, Junzhou Huang

Vision-language models have been widely explored across a wide range of tasks and achieve satisfactory performance. However, it's under-explored how to consolidate entity understanding through a varying number of images and to align it with the pre-trained language models for generative tasks. In this paper, we propose MIVC, a general multiple instance visua

Halvor R. Fergestad, Wolfgang Haensel, Arne Kordts, Alessandro Prencipe

Photonic integrated circuits are a paramount platform for optoelectronics and nonlinear optics, enabling high confinement nonlinear interactions, where advanced waveguide dispersion engineering can be leveraged to tailor broadband nonlinear processes, supercontinuum generation, soliton formation and joint spectral amplitudes of photon pairs. Accurately measu

Uwe M. Borghoff, Lars Berger, François Fischer

In fulfilling the European security commitment, the actors of the so-called "Intelligence Community" play a central role. They provide political and military decision-makers with important analyses and information. The Intelligence College in Europe (ICE) is the first entity to offer professional intelligence training as well as postgraduate level academic e

Olivier Moliner, Sangxia Huang, Kalle Åström

We address the challenges in estimating 3D human poses from multiple views under occlusion and with limited overlapping views. We approach multi-view, single-person 3D human pose reconstruction as a regression problem and propose a novel encoder-decoder Transformer architecture to estimate 3D poses from multi-view 2D pose sequences. The encoder refines 2D sk

Si-Pei Wang, Rui Wang, Jun-Ting Ye, Lie-Wen Chen

It is important to develop a unified theoretical framework to describe the nuclear experiments and astrophysical observations based on the same effective nuclear interactions. Based on the so-called Skyrme pseudopotential up to next-to-next-to-next-to-leading order, we construct a series of extended Skyrme interactions by modifying the density-dependent term

Yu Liu, Julian Schmidt, Zhimin Liu, David R. Leibrandt

Understanding molecular state evolution is central to many disciplines, including molecular dynamics, precision measurement, and molecule-based quantum technology. Details of the evolution are obscured when observing a statistical ensemble of molecules. Here, we reported real-time observations of thermal radiation-driven transitions between individual states

CMS Collaboration

A search for partonic collective effects inside jets produced in proton-proton collisions is performed via correlation measurements of charged constituents using the CMS detector at the CERN LHC. The analysis uses data collected at a center-of-mass energy of $\sqrt{s}$ = 13 TeV, corresponding to an integrated luminosity of 138 fb$^{-1}$. Jets are reconstruct

Konrad Staniszewski, Szymon Tworkowski, Sebastian Jaszczur, Yu Zhao

Recent advancements in long-context large language models have attracted significant attention, yet their practical applications often suffer from suboptimal context utilization. This study investigates structuring training data to enhance semantic interdependence, demonstrating that this approach effectively improves context utilization. To this end, we int

Wen-Li Yuan, Ang Li

Large uncertainties in the determinations of the equation of state of dense stellar matter allow the intriguing possibility that the bulk quark matter in beta equilibrium might be the true ground state of the matter at zero pressure. And quarks will form Cooper pairs very readily since the dominant interaction between quarks is attractive in some channels. A

Manuel D. Contreras, Francisco J. Cruz-Zamorano, Maria Kourou, Luis Rodríguez-Piazza

This work studies the Hardy number for the class of hyperbolic planar domains satisfying Abel's inclusion property, which are usually known as Koenigs domains. More explicitly, we prove that for all regular domains in the above class, the Hardy number is greater or equal than $1/2$, and this lower bound is sharp. In contrast to this result, we provide exampl

Jan Bączek, Dmytro Zhylko, Gilberto Titericz, Sajad Darabi

While machine learning has witnessed significant advancements, the emphasis has largely been on data acquisition and model creation. However, achieving a comprehensive assessment of machine learning solutions in real-world settings necessitates standardization throughout the entire pipeline. This need is particularly acute in time series forecasting, where d

Giorgio Arcadi, Sarif Khan

We illustrate and discuss the phenomenology of a model featuring a two-Higgs doublet sector augmented by two $SU(2)$ singlet scalars. The gauge symmetry group is extended as well with a $U(1)_{B_{i}-L_{i}}$ component whose spontaneous breaking leads to the gauge boson which has an important effect in the muon (g-2). A global PQ symmetry is introduced upon it

Shi-Qiang Chen, Csaba Sándor, Quan-Hui Yang

Let $\mathbb{N}$ be the set of all nonnegative integers. For $S\subseteq \mathbb{N}$ and $n\in \mathbb{N}$, let $R_S(n)$ denote the number of solutions of the equation $n=s+s'$, $s, s'\in S$, $s<s'$. In this paper, we determine the structure of all sets $A$ and $B$ such that $A\cup B=\mathbb{N}\setminus\{r+mk:k\in\mathbb{N}\}$, $A\cap B=\emptyset$ and $R_{A}

Itzhak Tamo

Folded Reed-Solomon (FRS) and univariate multiplicity codes are prominent polynomial codes over finite fields, renowned for achieving list decoding capacity. These codes have found a wide range of applications beyond the traditional scope of coding theory. In this paper, we introduce improved bounds on the list size for list decoding of these codes, achieved

Boris A. Malomed

This concise review aims to provide a summary of the most relevant recent experimental and theoretical results for solitons, i.e., self-trapped bound states of nonlinear waves, in two- and three-dimensional (2D and 3D) media. In comparison with commonly known one-dimensional solitons, which are, normally, stable modes, a challenging problem is the propensity

Iosif Petrakis

We introduce cs-topologies, or topologies of open complemented subsets, as a new approach to constructive topology that preserves the duality between open and closed subsets of classical topology. Complemented subsets were used successfully by Bishop in his constructive formulation of the Daniell approach to measure and integration. Here we use complemented

Ali Khosravi, Jin Wang, Andrea Silva, Andrea Vanossi

The way metal interfaces evolve during frictional sliding, and how that evolution can be externally influenced under external drivers are important questions, hard to investigate experimentally because the contacts themselves are generally difficult to access. Here we focus on an elementary constituent of a general metal-metal interface, namely an ultra-thin

Michael Etienne Van Huffel, Olympio Hacquard, Vadim Lebovici, Matteo Palo

Topological data analysis leverages topological features to analyze datasets, with applications in diverse fields like medical sciences and biology. A key tool of this theory is the persistence diagram, which encodes topological information but poses challenges for integration into standard machine learning pipelines. We introduce Qupid (QUantized Persistenc

CMS Collaboration

Despite the f$_0$(980) hadron having been discovered half a century ago, the question about its quark content has not been settled: it might be an ordinary quark-antiquark ($\mathrm{q\bar{q}}$) meson, a tetraquark ($\mathrm{q\bar{q}q\bar{q}}$) exotic state, a kaon-antikaon ($\mathrm{K\bar{K}}$) molecule, or a quark-antiquark-gluon ($\mathrm{q\bar{q}g}$) hybr

Bram Wouters

With the rise of large language models (LLMs) and concerns about potential misuse, watermarks for generative LLMs have recently attracted much attention. An important aspect of such watermarks is the trade-off between their identifiability and their impact on the quality of the generated text. This paper introduces a systematic approach to this trade-off in

Nadav Drukker, Omar Shahpo

We study M2-branes in $AdS_4\times S^7/{\mathbb Z}_k$ dual to 1/2 and 1/3 BPS vortex loop operators in ABJM theory and compute their one-loop correction beyond the classical M2-brane action. The correction depends only on the parity of $k$ and is independent of all continues parameters in the definition of the vortex loops. The result for odd $k$ agrees with

Haoning Wu, Zicheng Zhang, Weixia Zhang, Chaofeng Chen

The explosion of visual content available online underscores the requirement for an accurate machine assessor to robustly evaluate scores across diverse types of visual contents. While recent studies have demonstrated the exceptional potentials of large multi-modality models (LMMs) on a wide range of related fields, in this work, we explore how to teach them

Fatemeh Mohammadi, Mojtaba Tabatabaei, Mehdi Kargarian, Abolhassan Vaezi

Recent experiments show that the ground state of some layered materials with localized moments is in close proximity to the Kitaev spin liquid, calling for a proper model to describe the measurements. The Kitaev-Hubbard (KHu) model is the minimal model that captures the essential ingredients of these systems; it yields the Kitaev-Heisenberg spin model at the

Thomas Theurer, Kun Fang, Gilad Gour

We study entanglement distillation and dilution of states and channels in the single-shot regime. With the help of a recently introduced conversion distance, we provide compact closed-form expressions for the dilution and distillation of pure states and show how this can be used to efficiently calculate these quantities on multiple copies of pure states. The

David Bechara Senior, Patrice Le Calvez, Abror Pirnapasov

We establish that the asymptotic mean action and the asymptotic linking number of irrational pseudo-rotations remain well-defined everywhere and constant for every $C^{1}$ irrational pseudo-rotation that behaves as a rotation on the boundary. As a consequence, we demonstrate that the isotopy of irrational pseudo-rotations with a positive rotation number is a