July 2023 arXiv papers — page 42

Hanjia Lyu, Song Jiang, Hanqing Zeng, Yinglong Xia

Text-based recommendation holds a wide range of practical applications due to its versatility, as textual descriptions can represent nearly any type of item. However, directly employing the original item descriptions may not yield optimal recommendation performance due to the lack of comprehensive information to align with user preferences. Recent advances i

Romain Azaïs, Florian Ingels

Frequent pattern mining is a relevant method to analyse structured data, like sequences, trees or graphs. It consists in identifying characteristic substructures of a dataset. This paper deals with a new type of patterns for tree data: common subtrees with identical label distribution. Their detection is far from obvious since the underlying isomorphism prob

Jianning Guo, Dmitrii Semenok, Grigoriy Shutov, Di Zhou

High pressure plays a crucial role in the field of superconductivity. Compressed hydride superconductors are leaders in the race for a material that can conduct electricity without resistance at high or even room temperature. In the present work, we have discovered new lanthanum superhydride, cubic A15-type La$_4$H$_{23}$, with lower stabilization pressure c

Amit Pande, Kunal Ghosh, Rankyung Park

Buy It Again (BIA) recommendations are crucial to retailers to help improve user experience and site engagement by suggesting items that customers are likely to buy again based on their own repeat purchasing patterns. Most existing BIA studies analyze guests personalized behavior at item granularity. A category-based model may be more appropriate in such sce

Chutao Zheng, Yuchu Ge, Anfu Guo

Ultra-wideband (UWB) technology is a wireless communication technology designed for short-range applications. It is characterized by its ability to generate and transmit radio-frequency energy over an extensive frequency range. This paper provides an overview of UWB technology including its definition, two representative schemes and some key characteristics

Gabriel Jaumà, Juan José García-Ripoll, Manuel Pino

We study the spin-glass transition in several Ising models of relevance for quantum annealers. We extract the spin-glass critical temperature by extrapolating the pseudo-critical properties obtained with Replica-Exchange Monte-Carlo for finite-size systems. We find a spin-glass phase for some random lattices (random-regular and small-world graphs) in good ag

Zhenxin Liu, Di Lu

This paper is concerned with ergodic properties of inhomogeneous Markov processes. Since the transition probabilities depend on initial times, the existing methods to obtain invariant measures for homogeneous Markov processes are not applicable straightforwardly. We impose some appropriate conditions under which invariant measure families for inhomogeneous M

Praveen Manoharan, Kostas D. Kokkotas

We present applications of statistical data analysis methods from both bi- and multivariate statistics to find suitable sets of neutron star features that can be leveraged for accurate and EoS independent -- or universal -- relations. To this end, we investigate the ability of various correlation measures such as Distance Correlation and Mutual Information i

Debmalya Das, George Thomas, Andrew N. Jordan

In a quantum Stirling heat engine, the heat exchanged with two thermal baths is partly utilized for performing work by redistributing the energy levels of the working substance. We analyze the thermodynamics of a quantum Stirling engine operating in finite time. We develop a model in which a time-dependent potential barrier changes the energy-level structure

Yinzhu Jin, Jonathan C. Garneau, P. Thomas Fletcher

This paper introduces feature gradient flow, a new technique for interpreting deep learning models in terms of features that are understandable to humans. The gradient flow of a model locally defines nonlinear coordinates in the input data space representing the information the model is using to make its decisions. Our idea is to measure the agreement of int

J. Waghorne, F. P. Bonomo, A. Rabbani, D. Bell

The meniscal tissue is a layered material with varying properties influenced by collagen content and arrangement. Understanding the relationship between structure and properties is crucial for disease management, treatment development, and biomaterial design. The internal layer of the meniscus is softer and more deformable than the outer layers, thanks to in

Krissia Zawadzki, Guilherme A. Canella, Vivian V. França, Irene D'Amico

Entanglement in many-body systems may display interesting signatures of quantum phase transitions and similar properties are starting to be encountered in the analysis of work fluctuations. Here, we consider the fermionic superfluid-to-insulator transition (SIT) and relate its entanglement properties with its work distribution statistics. The SIT is modeled

Rodrigo Bazaes, Chiranjib Mukherjee, Mark Sellke, S. R. S. Varadhan

We prove that there is a constant $\overline C\in (0,\infty)$ such that the effective mass $m(\alpha)$ of the Fr\"ohlich Polaron satisfies $m(\alpha) \geq \overline C \alpha^4$, which is sharp according to a long-standing prediction of Landau-Pekar [19] from 1948 and of Spohn [36] from 1987. The method of proof, which demonstrates how the sharp quartic diver

Pardeep Kaur, Kuldeep Suthar, Dilip Angom, Sandeep Gautam

We examine the quench dynamics across quantum phase transitions from a Mott insulator (MI) to a superfluid (SF) phase in a two-component bosonic mixture in an optical lattice. We show that two-component Bose mixtures exhibit qualitatively different quantum dynamics than one-component Bose gas. Besides second-order MI-SF transitions, we also investigate quenc

Ivan Kolář, Tomáš Málek

We present a new covariant method of construction of the (position space) propagators in the $N$-dimensional (Euclidean) anti-de Sitter background for any gravitational theory with the Lagrangian that is an analytic expression in the metric, curvature, and covariant derivative. We show that the propagators (in Landau gauge) for all such theories can be expre

Yun Zhu, Haizhou Shi, Zhenshuo Zhang, Siliang Tang

In this work, we investigate the problem of out-of-distribution (OOD) generalization for unsupervised learning methods on graph data. This scenario is particularly challenging because graph neural networks (GNNs) have been shown to be sensitive to distributional shifts, even when labels are available. To address this challenge, we propose a \underline{M}odel

Alexey Vladimirov

This work is dedicated to the study of power expansion in the transverse momentum dependent (TMD) factorization theorem. Each genuine term in this expansion gives rise to a series of kinematic power corrections (KPCs). All terms of this series exhibit the same properties as the leading term and share the same nonperturbative content. Among various power corr

Claudio Guarcello, Roberta Citro, Francesco Giazotto, Alessandro Braggio

We theoretically study the quasiparticle current behaviour of a thermally-biased bipolar thermoelectrical superconducting quantum interference proximity transistor, formed by a normal metal wire embedded in a superconducting ring and tunnel-coupled to a superconducting probe. In this configuration, the superconducting gap of the wire can be modified through

Grigalius Taujanskas

We study spacetime estimates for the wave map null form $Q_0$ on $\mathbb{R} \times \mathbb{S}^3$. By using the Lie group structure of $\mathbb{S}^3$ and Peter-Weyl theory, combined with the time-periodicity of the conformal wave equation on $\mathbb{R} \times \mathbb{S}^3$, we extend the classical ideas of Klainerman and Machedon to estimates on $\mathbb{R}

Jan Boruch, Luca V. Iliesiu, Cynthia Yan

Understanding how to prepare and count black hole micro-states by using the gravitational path integral is one of the most important problems in quantum gravity. Nevertheless, a state-by-state count of black hole microstates is difficult because the apparent number of degrees of freedom available in the gravitational effective theory can vastly exceed the en

Noah Franz, Mitchell Dennis, Jeremy Sakstein

We use a novel method to constrain the neutrino magnetic dipole moment ($\mu_{\nu}$) using the empirically-calibrated tip of the red giant branch I-band magnitude that fully accounts for uncertainties in stellar physics. Our method uses machine learning to emulate the results of stellar evolution codes. This reduces the I-Band magnitude computation time to m

Michele Bonaldi, Antonio Borrielli, Giovanni Di Giuseppe, Nicola Malossi

In this work, we present an Opto-Electro-Mechanical Modulator (OEMM) for RF-to-optical transduction realized via an ultra-coherent nanomembrane resonator capacitively coupled to an rf injection circuit made of a microfabricated read-out able to improve the electro-optomechanical interaction. This device configuration can be embedded in a Fabry-Perot cavity f

IceCube-Gen2, :, R. Abbasi, M. Ackermann

IceCube-Gen2 is a planned next-generation neutrino observatory at the South Pole that builds upon the successful design of IceCube. Integrating two complementary detection technologies for neutrinos, optical and radio Cherenkov emission, in combination with a surface array for cosmic ray air shower detection, IceCube-Gen2 will cover a broad neutrino energy r

IceCube, :, R. Abbasi, M. Ackermann

The IceCube Observatory at the South Pole has been operating in its full configuration since May 2011 with a duty cycle of about 99%. Its main component consists of a cubic-kilometer array of optical sensors deployed deep in the Glacial ice designed for the detection of high-energy astrophysical neutrinos. A surface array for cosmic ray air shower detection,

Aike Liu, David Simmons-Duffin, Ning Su, Balt C. van Rees

We study families of semidefinite programs (SDPs) that depend nonlinearly on a small number of "external" parameters. Such families appear universally in numerical bootstrap computations. The traditional method for finding an optimal point in parameter space works by first solving an SDP with fixed external parameters, then moving to a new point in parameter

Keisuke Harigaya, Evan Petrosky, Aaron Pierce

We examine how different assumptions about the hadronic vacuum polarization, the $W$ boson mass, and the forward-backward asymmetry in $b$-quarks at the $Z$ pole can impact the precision electroweak fit. We study the implications for a kinetically mixed dark photon, addressing the complementarity of precision bounds and direct searches, particularly in the c

Pavlos Kazakopoulos, Georgios Regkas

We propose an interpretation for the meets and joins in the lattice of experimental propositions of a physical theory, answering a question of Birkhoff and von Neumann in [1]. When the lattice is atomistic, it is isomorphic to the lattice of definably closed sets of a finitary relational structure in First Order Logic. In terms of mapping experimental propos

Pau Amaro Seoane

We have evidence of X-ray flares in several galaxies consistent with a a star being tidally disrupted by a supermassive black hole (MBH). If the star starts on a nearly parabolic orbit relative to the MBH, one can derive that the fallback rate follows a $t^{-5/3}$ decay. Depending on the penetration factor, $\beta$, a star will be torn apart differently, and

Ana Hudomal, Ryan Smith, Andrew Hallam, Zlatko Papić

Recent quantum simulation by Google [Nature 612, 240 (2022)] has demonstrated the formation of bound states of interacting photons in a quantum-circuit version of the XXZ spin chain. While such bound states are protected by integrability in a one-dimensional chain, the experiment found the bound states to be unexpectedly robust when integrability was broken

Marcelo E. Rubio, Áron D. Kovács, M. Herrero-Valea, Miguel Bezares

Partial differential equations exhibiting an anisotropic scaling between space and time -- such as those of Horava-Lifshitz gravity -- have a dispersive nature. They contain higher-order spatial derivatives, but remain second order in time. This is inconvenient for performing long-time numerical evolutions, as standard explicit schemes fail to maintain conve

Martin Bojowald, David Brizuela, Paula Calizaya Cabrera, Sara F. Uria

According to general relativity, the generic early-universe dynamics is chaotic. Various quantum-gravity effects have been suggested that may change this behavior in different ways. Here, it is shown how key mathematical properties of the classical dynamics can be extended to evolving quantum states using quasiclassical methods, making it possible to apply t

M. Herrero-Valea

Horava gravity is a proposal for a UV completion of gravitation obtained by endowing the space-time manifold with a preferred foliation in space-like hypersurfaces. This allows for a power-counting renormalizable theory free of ghosts, at the cost of breaking local Lorentz invariance and diffeomorphism invariance down to foliation preserving transformations.

Ahana Chakraborty, Kun Chen, Aidan Zabalo, Justin H. Wilson

We study critical properties of the entanglement and charge-sharpening measurement-induced phase transitions in a non-unitary quantum circuit evolving with a U(1) conserved charge. Our numerical estimation of the critical properties of the entanglement transition at finite system sizes appears distinct from the generic non-conserving case and percolation. We

Andrés N. Ruiz, Héctor J. Martínez, Valeria Coenda, Hernán Muriel

We study the population of backsplash galaxies at $z=0$ in the outskirts of massive, isolated clusters of galaxies taken from the MDPL2-SAG semi-analytic catalogue. We consider four types of backsplash galaxies according to whether they are forming stars or passive at three stagesin their lifetimes: before entering the cluster, during their first incursion t

Lumen Boco, Andrea Lapi, Francesco Shankar, Hao Fu

In recent years, increasing attention has been devoted to semi empirical, data-driven models to tackle some aspects of the complex and still largely debated topic of galaxy formation and evolution. We here present a new semi empirical model whose marking feature is simplicity: it relies on solely two assumptions, one initial condition and two free parameters

Mariana P. Júlio, Jarle Brinchmann, Sebastiaan L. Zoutendijk, Justin I. Read

Aims. We use the stellar line-of-sight velocities of Antlia B (Ant B), a faint dwarf galaxy in the NGC 3109 association, to derive constraints on the fundamental properties of scalar field dark matter (SFDM), which was originally proposed to solve the small-scale problems faced by cold dark matter models. Methods. We used the first spectroscopic observations

Romy Rodríguez Martínez, David V. Martin, B. Scott Gaudi, Joseph G. Schulze

We investigate and compare the composition of M-dwarf planets in systems with only one known planet (``singles") to those residing in multi-planet systems (``multis") and the fundamental properties of their host stars. We restrict our analysis to planets with directly measured masses and radii, which comprise a total of 70 planets: 30 singles and 40 multis i

Sophia Simon, Raffaele Santagati, Matthias Degroote, Nikolaj Moll

We present a super-polynomial improvement in the precision scaling of quantum simulations for coupled classical-quantum systems in this paper. Such systems are found, for example, in molecular dynamics simulations within the Born-Oppenheimer approximation. By employing a framework based on the Koopman-von Neumann formulation of classical mechanics, we expres

Chris Akers, Adam Levine, Geoff Penington, Elizabeth Wildenhain

Following the work of [2008.03319], we define a generally covariant max-entanglement wedge of a boundary region $B$, which we conjecture to be the bulk region reconstructible from $B$. We similarly define a covariant min-entanglement wedge, which we conjecture to be the bulk region that can influence the state on $B$. We prove that the min- and max-entanglem

Patrick H. Wilhelm, Yves H. Kwan, Andreas M. Läuchli, S. A. Parameswaran

We study a model of spinless fermions on the honeycomb lattice with nearest-neighbor exclusion and extended repulsive interactions that exhibits `lattice supersymmetry' [P. Fendley, K. Schoutens, and J. de Boer, Phys. Rev. Lett. 90, 120402 (2003)]. Using a combination of exact diagonalization of large ($N\leq56$ site) systems, mean-field numerics, and symmet

Emile Pangburn, Miguel Alvarado, Oladunjoye A. Awoga, Catherine Pépin

We consider the most energetically favorable symmetry-allowed spin-singlet and spin-triplet superconducting pairing symmetries in twisted bilayer graphene at the magic angle, whose normal state physics is described by a six-band effective tight-binding model. We compute the Chern number as a function of the superconducting order parameter strength and the ch

Janus Kozdon, Sean Brittain, Jeffrey Fung, Josh Kern

CI Tau is currently the only T Tauri star with an inner protoplanetary disk that hosts a planet, CI Tau b, that has been detected by a radial velocity survey. This provides the unique opportunity to study disk features that were imprinted by that planet. We present multi-epoch spectroscopic data, taken with NASA IRTF in 2022, of the ${}^{12}$CO and hydrogen

W. Gong, Yaroslav Kharkov, Minh C. Tran, Przemyslaw Bienias

Simulating quantum systems is one of the most promising avenues to harness the computational power of quantum computers. However, hardware errors in noisy near-term devices remain a major obstacle for applications. Ideas based on the randomization of Suzuki-Trotter product formulas have been shown to be a powerful approach to reducing the errors of quantum s

Mirjam Cvetič, Jonathan J. Heckman, Max Hübner, Ethan Torres

Generalized global symmetries are a common feature of many quantum field theories decoupled from gravity. By contrast, in quantum gravity / the Swampland program, it is widely expected that all global symmetries are either gauged or broken, and this breaking is in turn related to the expected completeness of the spectrum of charged states in quantum gravity.

Geraint Pratten, Patricia Schmidt, Hannah Middleton, Alberto Vecchio

The Laser Interferometer Space Antenna (LISA) will play a vital role in constraining the origin and evolution of massive black holes throughout the Universe. In this study we use a waveform model (IMRPhenomXPHM) that includes both precession and higher multipoles, and full Bayesian inference to explore the accuracy to which LISA can constrain the binary para

Rafael F. del Castillo, Max Jaarsma, Ignazio Scimemi, Wouter Waalewijn

In view of the increasing precision of theoretical calculations and experimental measurements, power corrections to transverse-momentum-dependent observables are highly important. We study the next-to-leading power corrections for transverse momentum measurements in $e^+ e^- \rightarrow 2$ jets. We obtain a factorized expression for the cross section, which

Xavier Rodrigues, Vaidehi S. Paliya, Simone Garrappa, Anastasiia Omeliukh

The origin of the diffuse astrophysical neutrino flux observed by the IceCube experiment is still under debate. In recent years there have been associations of neutrino events with individual blazars, which are active galaxies with relativistic jets pointing toward Earth, such as the source TXS 0506+056. From a theoretical perspective, the properties of thes

M. Sten Delos, Michael Korsmeier, Axel Widmark, Carlos Blanco

Recent studies indicate that thermally produced dark matter will form highly concentrated, low-mass cusps in the early universe that often survive until the present. While these cusps contain a small fraction of the dark matter, their high density significantly increases the expected gamma-ray flux from dark matter annihilation, particularly in searches of l

A. Pandhi, R. K. Friesen, L. Fissel, J. E. Pineda

Studies of dense core morphologies and their orientations with respect to gas flows and the local magnetic field have been limited to only a small sample of cores with spectroscopic data. Leveraging the Green Bank Ammonia Survey alongside existing sub-millimeter continuum observations and Planck dust polarization, we produce a cross-matched catalogue of 399

Bogdan Ganchev, Stefano Giusto, Anthony Houppe, Rodolfo Russo

Microstrata are the non-extremal analogues of superstrata: they are smooth, non-extremal (non-BPS) solitonic solutions to IIB supergravity whose deep-throat limits approximate black holes. Using perturbation theory and numerical methods, we construct families of solutions using a consistent truncation to three-dimensional supergravity. The most general famil

Anna Neufeld, Joshua Popp, Lucy L. Gao, Alexis Battle

The analysis of single-cell RNA sequencing (scRNA-seq) data often involves fitting a latent variable model to learn a low-dimensional representation for the cells. Validating such a model poses a major challenge. If we could sequence the same set of cells twice, we could use one dataset to fit a latent variable model and the other to validate it. In reality,

Francesco Aprile, Enrico Olivucci

We study fishnet Feynman diagrams defined by a certain triangulation of a planar n-gon, with massless scalars propagating along and across the cuts. Our solution theory uses the technique of Separation of Variables, in combination with the theory of symmetric polynomials and Mellin space. The n-point split-ladders are solved by a recursion where all building

Zechu Li, Tao Chen, Zhang-Wei Hong, Anurag Ajay

Reinforcement learning is time-consuming for complex tasks due to the need for large amounts of training data. Recent advances in GPU-based simulation, such as Isaac Gym, have sped up data collection thousands of times on a commodity GPU. Most prior works used on-policy methods like PPO due to their simplicity and ease of scaling. Off-policy methods are more

Soumendu Sundar Mukherjee

Consider the spiked Wigner model \[ X = \sum_{i = 1}^k \lambda_i u_i u_i^\top + \sigma G, \] where $G$ is an $N \times N$ GOE random matrix, and the eigenvalues $\lambda_i$ are all spiked, i.e. above the Baik-Ben Arous-P\'ech\'e (BBP) threshold $\sigma$. We consider AIC-type model selection criteria of the form \[ -2 \, (\text{maximised log-likelihood}) + \g

Yining Hong, Haoyu Zhen, Peihao Chen, Shuhong Zheng

Large language models (LLMs) and Vision-Language Models (VLMs) have been proven to excel at multiple tasks, such as commonsense reasoning. Powerful as these models can be, they are not grounded in the 3D physical world, which involves richer concepts such as spatial relationships, affordances, physics, layout, and so on. In this work, we propose to inject th

Jindong Gu, Zhen Han, Shuo Chen, Ahmad Beirami

Prompt engineering is a technique that involves augmenting a large pre-trained model with task-specific hints, known as prompts, to adapt the model to new tasks. Prompts can be created manually as natural language instructions or generated automatically as either natural language instructions or vector representations. Prompt engineering enables the ability

Jacob Jackson

The Adam optimizer is the standard choice in deep learning applications. I propose a simple explanation of Adam's success: it makes each parameter's step size independent of the norms of the other parameters. Based on this principle I derive Iso, a new optimizer which makes the norm of a parameter's update invariant to the application of any linear transform

Abdulsalam H. Alsulami, Irene D'Amico, Marta P. Estarellas, Timothy P. Spiller

Spin network systems can be used to achieve quantum state transfer with high fidelity and to generate entanglement. A new approach to design spin-chain-based spin network systems, for shortrange quantum information processing and phase-sensing, has been proposed recently in [1]. In this paper, we investigate the scalability of such systems, by designing larg

Omar León Sánchez, Marcus Tressl

We provide a characterisation of differentially large fields in arbitrary characteristic and a single derivation in the spirit of Blum axioms for differentially closed fields. In the case of characteristic zero, we use these axioms to characterise differential largeness in terms of being existentially closed in the differential algebraic Laurent series ring,

Roi Cohen, Eden Biran, Ori Yoran, Amir Globerson

Modern language models capture a large body of factual knowledge. However, some facts can be incorrectly induced or become obsolete over time, resulting in factually incorrect generations. This has led to the development of various editing methods that allow updating facts encoded by the model. Evaluation of these methods has primarily focused on testing whe

Xiang Ji, Huazheng Wang, Minshuo Chen, Tuo Zhao

For a real-world decision-making problem, the reward function often needs to be engineered or learned. A popular approach is to utilize human feedback to learn a reward function for training. The most straightforward way to do so is to ask humans to provide ratings for state-action pairs on an absolute scale and take these ratings as reward samples directly.

Hung-I Lin, Jeffrey Geldmeier, Erwan Baleine, Fan Yang

Long-wave infrared (LWIR, 8-12 $\mu m$ wavelengths) is a spectral band of vital importance to thermal imaging. Conventional LWIR optics made from single-crystalline Ge and chalcogenide glasses are bulky and fragile. The challenge is exacerbated for wide field-of-view (FOV) optics, which traditionally mandates multiple cascaded elements that severely add to c

Flor Miriam Plaza-del-Arco, Debora Nozza, Dirk Hovy

Large Language Models (LLMs) exhibit remarkable text classification capabilities, excelling in zero- and few-shot learning (ZSL and FSL) scenarios. However, since they are trained on different datasets, performance varies widely across tasks between those models. Recent studies emphasize the importance of considering human label variation in data annotation.

Hongyang Li, Hao Zhang, Zhaoyang Zeng, Shilong Liu

In this paper, we propose a new operator, called 3D DeFormable Attention (DFA3D), for 2D-to-3D feature lifting, which transforms multi-view 2D image features into a unified 3D space for 3D object detection. Existing feature lifting approaches, such as Lift-Splat-based and 2D attention-based, either use estimated depth to get pseudo LiDAR features and then sp

Md Abrar Jahin, Md Sakib Hossain Shovon, Jungpil Shin, Istiyaque Ahmed Ridoy

This article intends to systematically identify and comparatively analyze state-of-the-art supply chain (SC) forecasting strategies and technologies. A novel framework has been proposed incorporating Big Data Analytics in SC Management (problem identification, data sources, exploratory data analysis, machine-learning model training, hyperparameter tuning, pe

Christian Carrillo, Gissela Torres, Christian Mejia-Escobar

Volcanic eruptions emit ash that can be harmful to human health and cause damage to infrastructure, economic activities and the environment. The delimitation of ash clouds allows to know their behavior and dispersion, which helps in the prevention and mitigation of this phenomenon. Traditional methods take advantage of specialized software programs to proces

Vitor M. de Oliveira

In this work, we numerically investigate and visually illustrate the dynamical properties of the dissipative spin-orbit problem such as the co-existence of multiple periodic and quasi-periodic attractors, and the complexity of the corresponding basins of attraction. Our model is composed by a triaxial satellite (planet) orbiting a planet (star) in a fixed Ke

Lorenzo Lucchese, Mikko S. Pakkanen, Almut E. D. Veraart

The aim of this paper is to develop estimation and inference methods for the drift parameters of multivariate L\'evy-driven continuous-time autoregressive processes of order $p\in\mathbb{N}$. Starting from a continuous-time observation of the process, we develop consistent and asymptotically normal maximum likelihood estimators. We then relax the unrealistic

Benjamin Eysenbach, Matthieu Geist, Sergey Levine, Ruslan Salakhutdinov

As with any machine learning problem with limited data, effective offline RL algorithms require careful regularization to avoid overfitting. One-step methods perform regularization by doing just a single step of policy improvement, while critic regularization methods do many steps of policy improvement with a regularized objective. These methods appear disti

Xuanchen Lu, Xiaolong Wang, Judith E Fan

Humans effortlessly grasp the connection between sketches and real-world objects, even when these sketches are far from realistic. Moreover, human sketch understanding goes beyond categorization -- critically, it also entails understanding how individual elements within a sketch correspond to parts of the physical world it represents. What are the computatio

Yufei Wang, Wanjun Zhong, Liangyou Li, Fei Mi

Large Language Models (LLMs) trained on extensive textual corpora have emerged as leading solutions for a broad array of Natural Language Processing (NLP) tasks. Despite their notable performance, these models are prone to certain limitations such as misunderstanding human instructions, generating potentially biased content, or factually incorrect (hallucina

Jose M. Garcia-Calcines, Lucile Vandembroucq

In this paper, we provide sufficient conditions for a space $X$ to satisfy the Ganea conjecture for topological complexity. To achieve this, we employ two auxiliary invariants: weak topological complexity in the sense of Berstein-Hilton, along with a certain stable version of it. Several examples are discussed

Sarah Ibrahimi, Xiaohang Sun, Pichao Wang, Amanmeet Garg

Text-to-video retrieval systems have recently made significant progress by utilizing pre-trained models trained on large-scale image-text pairs. However, most of the latest methods primarily focus on the video modality while disregarding the audio signal for this task. Nevertheless, a recent advancement by ECLIPSE has improved long-range text-to-video retrie

Qingtao Chen, Shengmao Zhu

This is the first article in a series devoted to the study of the asymptotic expansions of various quantum invariants related to the twist knots. In this paper, by using the saddle point method developed by Ohtsuki, we obtain an asymptotic expansion formula for the colored Jones polynomial of twist knots $\mathcal{K}_p$ with $p\geq 6$ at the root of unity $e

Nikita Rawat, J. C. Pandey, Arti Joshi, Srinivas M Rao

We present the preliminary timing analysis of confirmed intermediate polar UU Col and possible intermediate polar Swift J0939.7-3224 in the optical band with the help of long-term, high-cadence continuous photometry from Transiting Exoplanet Survey Satellite (TESS). For UU Col, we revise previously reported orbital and spin periods as 3.464 $\pm$ 0.005 h and

Talat Nazir, Sergei Silvestrov

The fixed point results for generalized Pre\v{s}i\'c type mappings in the setup of $b$-metric spaces are obtained. The stability of fixed point set of Pre\v{s}i\'c type mappings is also established. Several examples are also presented to illustrate the validity of the main results.

Ivica Zivkovic, Mohamed A. Kassem, Yoshikazu Tabata, Takeshi Waki

In Co$_3$Sn$_2$S$_2$ two transitions are observed, the main one to a ferromagnetic state at $T_C = 174$ K and the second one, involving in-plane components at $T_P = 127$ K. We follow their doping dependence as Sn is replaced with In, which causes a reduction of $T_C$ and $T_P$. Importantly, both transitions follow the same doping dependence, indicating a si

Maria Rose, Sreekanth K Manikandan

For arbitrary non-equilibrium transformations in complex systems, we show that the distance between the current state and a target state can be decomposed into two terms: one corresponding to an independent estimate of the distance, and another corresponding to interactions, quantified using the relative mutual information between the variables. This decompo

Biswajit Pandey

We study the time evolution of the mutual information between the mass distributions in spatially separated but casually connected regions in an expanding universe. The evolution of the mutual information is primarily determined by the configuration entropy rate which depends on the dynamics of the expansion and the growth of the density perturbations. The j

C. S. Barroso, V. Ferreira

In this paper we consider the class of Lipschitz maps on the unit ball $B_X$ of a Banach space $X$, and the question we deal with is whether for any $\lambda>1$ there exists a $\lambda$-Lipschitz fixed-point free mapping $T\colon B_X\to B_X$ with $\mathrm{d}(T,B_X)=0$. We also consider its H\"older version. New related results are obtained. We show that if $

Logan W. Cooke, Arina Tashchilina, Mason Protter, Joseph Lindon

Holonomic quantum computing (HQC) functions by transporting an adiabatically degenerate manifold of computational states around a closed loop in a control-parameter space; this cyclic evolution results in a non-Abelian geometric phase which may couple states within the manifold. Realizing the required degeneracy is challenging, and typically requires auxilia

Ludwig A. Hoffmann, Luca Giomi

Chirality is a feature of many biological systems and much research has been focused on understanding the origin and implications of this property. Famously, sugars and amino acids found in nature are homochiral, i.e., chiral symmetry is broken and only one of the two possible chiral states is ever observed. Certain types of cells show chiral behavior, too.

Aya Mahmoud Ahmed, Mohamed Yousef, Khaled F. Hussain, Yousef Bassyouni Mahdy

Captioning images is a challenging scene-understanding task that connects computer vision and natural language processing. While image captioning models have been successful in producing excellent descriptions, the field has primarily focused on generating a single sentence for 2D images. This paper investigates whether integrating depth information with RGB

Dimitrios Krommydas, Livio Nicola Carenza, Luca Giomi

Collective cell migration in epithelia relies on cell intercalation: a local remodelling of the cellular network that allows neighbouring cells to swap their positions. Unlike foams and passive cellular fluid, in epithelial intercalation these rearrangements crucially depend on activity. During these processes, the local geometry of the network and the contr

Joshua Males

In this short note, we prove equidistribution results regarding three families of three-colour partitions recently introduced by Schlosser and Zhou. To do so, we prove an asymptotic formula for the infinite product $F_{a,c}(\zeta ; {\rm e}^{-z}) := \prod_{n \geq 0} \big(1- \zeta {\rm e}^{-(a+cn)z}\big)$ ($a,c \in \mathbb{N}$ with $0<a\leq c$ and $\zeta$ a ro

V. V. Kashikhin, S. Cohan, V. Lombardo, D. Turrioni

This paper reports progress in the development of COMB magnet technology with STAR wires. A two-layer dipole magnet with 60 mm clear bore has been recently fabricated and tested in liquid nitrogen. The purpose of the test was to determine what kind of critical current degradation occurs in the process of winding the STAR wire into the COMB structure.

Liam Mazurowski, Tongrui Wang

We develop a min-max theory for the area functional in the class of locally wedge-shaped manifolds. Roughly speaking, a locally wedge-shaped manifold is a Riemannian manifold that is allowed to have both boundary and certain types of edges. Fix a dimension $3 \le n+1 \le 6$. As our main theorem, we prove that every compact locally wedge-shaped manifold $M^{n

Jingke Xu, Duncan Adams, Brian Lenardo, Teal Pershing

The Migdal effect predicts that a nuclear recoil interaction can be accompanied by atomic ionization, allowing many dark matter direct detection experiments to gain sensitivity to sub-GeV masses. We report the first direct search for the Migdal effect for M- and L-shell electrons in liquid xenon using 7.0$\pm$1.6 keV nuclear recoils produced by tagged neutro

Peng Guo, Vladimir Gasparian

In present work, a relation that connects the integrated correlation function of a trapped two-particle system to infinite volume particles scattering phase shift is derived. It has the potential to provide an alternative approach for extracting two-particle scattering phase shift from integrated correlation function in lattice simulation at small Euclidean

Kevin Yang, Dan Klein, Asli Celikyilmaz, Nanyun Peng

We propose Reinforcement Learning from Contrastive Distillation (RLCD), a method for aligning language models to follow principles expressed in natural language (e.g., to be more harmless) without using human feedback. RLCD creates preference pairs from two contrasting model outputs, one using a positive prompt designed to encourage following the given princ

Viet Dac Lai, Abel Salinas, Hao Tan, Trung Bui

Punctuation restoration is an important task in automatic speech recognition (ASR) which aim to restore the syntactic structure of generated ASR texts to improve readability. While punctuated texts are abundant from written documents, the discrepancy between written punctuated texts and ASR texts limits the usability of written texts in training punctuation

Liam Mazurowski, Tongrui Wang

In this paper, we consider locally wedge-shaped manifolds, which are Riemannian manifolds that are allowed to have both boundary and certain types of edges. We define and study the properties of free boundary minimal hypersurfaces inside locally wedge-shaped manifolds. In particular, we show a compactness theorem for free boundary minimal hypersurfaces with

Peng Liang, Guanzhou Zhu, Cheng-Liang Huang, Yuan-Yao Li

Low temperature rechargeable batteries are important to life in cold climates, polar/deep-sea expeditions and space explorations. Here, we report ~ 3.5 - 4 V rechargeable lithium/chlorine (Li/Cl2) batteries operating down to -80 {\deg}C, employing Li metal negative electrode, a novel CO2 activated porous carbon (KJCO2) as the positive electrode, and a high i

Ekaterina Borodich, Georgiy Kormakov, Dmitry Kovalev, Aleksandr Beznosikov

In this work, we focuses on the following saddle point problem $\min_x \max_y p(x) + R(x,y) - q(y)$ where $R(x,y)$ is $L_R$-smooth, $\mu_x$-strongly convex, $\mu_y$-strongly concave and $p(x), q(y)$ are convex and $L_p, L_q$-smooth respectively. We present a new algorithm with optimal overall complexity $\mathcal{O}\left(\left(\sqrt{\frac{L_p}{\mu_x}} + \fra

Vincenzo Fazio, Nicola Maria Pugno, Orazio Giustolisi, Giuseppe Puglisi

Multiscale phenomena exhibit complex structure-function relationships, and predicting their macroscopic behavior requires deducing differential equations at different scales. The complexity of these equations and the number of essential parameters make developing effective, predictive models challenging. To overcome this, researchers explore leveraging advan

Artur Tarassow

This paper presents a study on the feasibility of using large language models (LLM) for coding with low-resource and domain-specific programming languages that typically lack the amount of data required for effective LLM processing techniques. This study focuses on the econometric scripting language named hansl of the open-source software gretl and employs a

John L. A. Gardner, Kathryn T. Baker, Volker L. Deringer

Machine learning (ML) based interatomic potentials have transformed the field of atomistic materials modelling. However, ML potentials depend critically on the quality and quantity of quantum-mechanical reference data with which they are trained, and therefore developing datasets and training pipelines is becoming an increasingly central challenge. Leveragin

Duncan Calvert, Dexton Anderson, Tomasz Bialek, Stephen McCrory

Humanoid robots have the potential to perform useful tasks in a world built for humans. However, communicating intention and teaming with a humanoid robot is a multi-faceted and complex problem. In this paper, we tackle the problems associated with quickly and interactively authoring new robot behavior that works on real hardware. We bring the powerful conce

Yunbum Kook, Santosh S. Vempala

The connections between (convex) optimization and (logconcave) sampling have been considerably enriched in the past decade with many conceptual and mathematical analogies. For instance, the Langevin algorithm can be viewed as a sampling analogue of gradient descent and has condition-number-dependent guarantees on its performance. In the early 1990s, Nesterov

Davis Brown, Nikhil Vyas, Yamini Bansal

In this study, we investigate whether the representations learned by neural networks possess a privileged and convergent basis. Specifically, we examine the significance of feature directions represented by individual neurons. First, we establish that arbitrary rotations of neural representations cannot be inverted (unlike linear networks), indicating that t