December 2023 arXiv papers — page 108

Shuyang Sun, Runjia Li, Philip Torr, Xiuye Gu

Existing open-vocabulary image segmentation methods require a fine-tuning step on mask labels and/or image-text datasets. Mask labels are labor-intensive, which limits the number of categories in segmentation datasets. Consequently, the vocabulary capacity of pre-trained VLMs is severely reduced after fine-tuning. However, without fine-tuning, VLMs trained u

Jeong Han Kim, Kyoungchul Kong, Se Hwan Lim, Jong-Chul Park

We explore extensive N-body simulations with two-component cold dark matter candidates. We delve into the temperature evolution, power spectrum, density perturbation, and maximum circular velocity functions. We find that the substantial mass difference between the two candidates and the annihilation of the heavier components to the lighter ones effectively e

Iain Davies, Harvey S. Reall

We describe a method for defining dynamical black hole entropy in gravitational effective field theories (EFTs). The entropy is constructed order by order in derivatives. For any fixed number of derivatives, the entropy satisfies a non-perturbative second law of black hole mechanics if the black hole remains within the regime of validity of EFT. In equilibri

Chae-Yeun Park, Pablo A. M. Casares, Juan Miguel Arrazola, Joonsuk Huh

Recent experiments demonstrated quantum computational advantage in random circuit sampling and Gaussian boson sampling. However, it is unclear whether these experiments can lead to practical applications even after considerable research effort. On the other hand, simulating the quantum coherent dynamics of interacting spins has been considered as a potential

Luca Sala, Milena Valentini, Veronica Biffi, Klaus Dolag

Mass and spin of massive black holes (BHs) at the centre of galaxies evolve due to gas accretion and mergers with other BHs. Besides affecting e.g. the evolution of relativistic jets, the BH spin determines the efficiency with which the BH radiates energy. Using cosmological, hydrodynamical simulations, we investigate the evolution of the BH spin across cosm

Maryam Rahmani, Emily M. Barrentine, Eric R. Switzer, Alyssa Barlis

We describe a testbed to characterize the optical response of compact superconducting on-chip spectrometers in development for the Experiment for Cryogenic Large-Aperture Intensity Mapping (EXCLAIM) mission. EXCLAIM is a balloonborne far-infrared experiment to probe the CO and CII emission lines in galaxies from redshift 3.5 to the present. The spectrometer,

Haotian Cao, Hai Tao Li, Zihao Mi

We present the complete spectrum for the Bjorken $x$ weighted Energy-Energy Correlation in the deep inelastic scattering (DIS) process, from the target fragmentation region to the current fragmentation region, in the Breit frame. The corresponding collinear and transverse momentum-dependent logarithms are resummed to all orders with the accuracy of NLL and N

Dominic W. Berry, Nicholas C. Rubin, Ahmed O. Elnabawy, Gabriele Ahlers

This paper improves and demonstrates the usefulness of the first quantized plane-wave algorithms for the quantum simulation of electronic structure, developed by Babbush et al. and Su et al. We describe the first quantum algorithm for first quantized simulation that accurately includes pseudopotentials. We focus on the Goedecker-Tetter-Hutter (GTH) pseudopot

Hendrik Hohmann, Matteo Dürrnagel, Matthew Bunney, Stefan Enzner

Van-Hove (vH) singularities in the vicinity of the Fermi level facilitate the emergence of electronically mediated Fermi surface instabilities. This is because they provide a momentum-localized enhancement of density of states promoting selective electronic scattering channels. High-temperature topological superconductivity has been argued for in graphene at

IceCube Collaboration, R. Abbasi, M. Ackermann, J. Adams

We present the results of a search for 10--1,000 GeV neutrinos from 2,268 gamma-ray bursts over 8 years of IceCube-DeepCore data. This work probes burst physics below the photosphere where electromagnetic radiation cannot escape. Neutrinos of tens of GeVs are predicted in sub-photospheric collision of free streaming neutrons with bulk-jet protons. In a first

Nima Arkani-Hamed, Clifford Cheung, Carolina Figueiredo, Grant N. Remmen

Is string theory uniquely determined by self-consistency? Causality and unitarity seemingly permit a multitude of putative deformations, at least at the level of two-to-two scattering. Motivated by this question, we initiate a systematic exploration of the constraints on scattering from higher-point factorization, which imposes extraordinarily restrictive su

Mariana Carrillo González

We find bounds on the Wilson coefficients of effective field theories (EFTs) living in a Universe undergoing expansion by requiring that its modes do not propagate further than a minimally coupled photon by a resolvable amount. To do so, we compute the spatial shift suffered by the EFT modes at a fixed time slice within the WKB approximation and the regime o

Qianshu Lu, Matthew Reece, Zhiquan Sun

It is difficult to construct a post-inflation QCD axion model that solves the axion quality problem (and hence the Strong CP problem) without introducing a cosmological disaster. In a post-inflation axion model, the axion field value is randomized during the Peccei-Quinn phase transition, and axion domain walls form at the QCD phase transition. We emphasize

Qinrui Liu, Damiano F. G. Fiorillo, Carlos A. Argüelles, Mauricio Bustamante

The flavor composition of TeV--PeV astrophysical neutrinos, i.e., the proportion of neutrinos of different flavors in their flux, is a versatile probe of high-energy astrophysics and fundamental physics. Because flavor identification is challenging and the number of detected high-energy astrophysical neutrinos is limited, so far measurements of the flavor co

Tuhin Ghosh, Sourav Chatterjee, James C. Lombardi

Observed high multiplicity planetary systems are often tightly packed. Numerical studies indicate that such systems are susceptible to dynamical instabilities. Dynamical instabilities in close-in tightly packed systems, similar to those found in abundance by Kepler, often lead to planet-planet collisions. For sub-Neptunes, the dominant type of observed exopl

Matthew E. Caplan, Earl P. Bellinger, Andrew D. Santarelli

There is probably not a black hole in the center of the sun. Despite this detail, our goal in this work to convince the reader that this question is interesting and that work studying stars with central black holes is well motivated. If primordial black holes exist then they may exist in sufficiently large numbers to explain the dark matter in the universe.

Daniel Duckworth, Peter Hedman, Christian Reiser, Peter Zhizhin

Recent techniques for real-time view synthesis have rapidly advanced in fidelity and speed, and modern methods are capable of rendering near-photorealistic scenes at interactive frame rates. At the same time, a tension has arisen between explicit scene representations amenable to rasterization and neural fields built on ray marching, with state-of-the-art in

Ulyana Piterbarg, Lerrel Pinto, Rob Fergus

Neural Language Models (LMs) offer an exciting solution for general-purpose embodied control. However, a key technical issue arises when using an LM-based controller: environment observations must be converted to text, which coupled with history, results in long and verbose textual prompts. As a result, prior work in LM agents is limited to restricted domain

Hongyu Liu, Xuan Wang, Ziyu Wan, Yujun Shen

This work presents HeadArtist for 3D head generation from text descriptions. With a landmark-guided ControlNet serving as the generative prior, we come up with an efficient pipeline that optimizes a parameterized 3D head model under the supervision of the prior distillation itself. We call such a process self score distillation (SSD). In detail, given a samp

Prashanth Chandran, Gaspard Zoss

Coordinate based implicit neural representations have gained rapid popularity in recent years as they have been successfully used in image, geometry and scene modeling tasks. In this work, we present a novel use case for such implicit representations in the context of learning anatomically constrained face models. Actor specific anatomically constrained face

Tianxing Wu, Chenyang Si, Yuming Jiang, Ziqi Huang

Though diffusion-based video generation has witnessed rapid progress, the inference results of existing models still exhibit unsatisfactory temporal consistency and unnatural dynamics. In this paper, we delve deep into the noise initialization of video diffusion models, and discover an implicit training-inference gap that attributes to the unsatisfactory inf

Sicheng Mo, Fangzhou Mu, Kuan Heng Lin, Yanli Liu

Recent approaches such as ControlNet offer users fine-grained spatial control over text-to-image (T2I) diffusion models. However, auxiliary modules have to be trained for each type of spatial condition, model architecture, and checkpoint, putting them at odds with the diverse intents and preferences a human designer would like to convey to the AI models duri

Anders Aamand, Justin Y. Chen, Huy Lê Nguyen, Sandeep Silwal

Estimating frequencies of elements appearing in a data stream is a key task in large-scale data analysis. Popular sketching approaches to this problem (e.g., CountMin and CountSketch) come with worst-case guarantees that probabilistically bound the error of the estimated frequencies for any possible input. The work of Hsu et al. (2019) introduced the idea of

Nayantara Mudur, Carolina Cuesta-Lazaro, Douglas P. Finkbeiner

Cosmological simulations play a crucial role in elucidating the effect of physical parameters on the statistics of fields and on constraining parameters given information on density fields. We leverage diffusion generative models to address two tasks of importance to cosmology -- as an emulator for cold dark matter density fields conditional on input cosmolo

Ji Lin, Hongxu Yin, Wei Ping, Yao Lu

Visual language models (VLMs) rapidly progressed with the recent success of large language models. There have been growing efforts on visual instruction tuning to extend the LLM with visual inputs, but lacks an in-depth study of the visual language pre-training process, where the model learns to perform joint modeling on both modalities. In this work, we exa

Xueyan Zou, Linjie Li, Jianfeng Wang, Jianwei Yang

Foundation models possess strong capabilities in reasoning and memorizing across modalities. To further unleash the power of foundation models, we present FIND, a generalized interface for aligning foundation models' embeddings with unified image and dataset-level understanding spanning modality and granularity. As shown in the teaser figure, a lightweight t

Soyong Shin, Juyong Kim, Eni Halilaj, Michael J. Black

The estimation of 3D human motion from video has progressed rapidly but current methods still have several key limitations. First, most methods estimate the human in camera coordinates. Second, prior work on estimating humans in global coordinates often assumes a flat ground plane and produces foot sliding. Third, the most accurate methods rely on computatio

Kuan-Chih Huang, Yi-Hsuan Tsai, Ming-Hsuan Yang

Weakly supervised 3D object detection aims to learn a 3D detector with lower annotation cost, e.g., 2D labels. Unlike prior work which still relies on few accurate 3D annotations, we propose a framework to study how to leverage constraints between 2D and 3D domains without requiring any 3D labels. Specifically, we employ visual data from three perspectives t

Keivan Alizadeh, Iman Mirzadeh, Dmitry Belenko, Karen Khatamifard

Large language models (LLMs) are central to modern natural language processing, delivering exceptional performance in various tasks. However, their substantial computational and memory requirements present challenges, especially for devices with limited DRAM capacity. This paper tackles the challenge of efficiently running LLMs that exceed the available DRAM

Babak Esmaeili, Robin Walters, Heiko Zimmermann, Jan-Willem van de Meent

Incorporating geometric inductive biases into models can aid interpretability and generalization, but encoding to a specific geometric structure can be challenging due to the imposed topological constraints. In this paper, we theoretically and empirically characterize obstructions to training encoders with geometric latent spaces. We show that local optima c

Szabolcs Borsányi, Zoltán Fodor, Jana N. Guenther, Sándor D. Katz

Fluctuations play a key role in the study of QCD phases. Lattice QCD is a valuable tool to calculate them, but going to high orders is challenging. Up to the fourth order, continuum results are available since 2015. We present the first continuum results for sixth order baryon fluctuations for temperatures between $T=130 - 200$ MeV, and eighth order at $T=14

Peter Clark, Bhavana Dalvi Mishra, Oyvind Tafjord

While there are numerous benchmarks comparing the performance of modern language models (LMs), end-task evaluations often conflate notions of *factual accuracy* ("truth") and *reasoning ability* ("rationality", or "honesty" in the sense of correctly reporting implications of beliefs). Our goal is a dataset that clearly distinguishes these two notions. Our ap

Peng Lu, Tao Jiang, Yining Li, Xiangtai Li

Real-time multi-person pose estimation presents significant challenges in balancing speed and precision. While two-stage top-down methods slow down as the number of people in the image increases, existing one-stage methods often fail to simultaneously deliver high accuracy and real-time performance. This paper introduces RTMO, a one-stage pose estimation fra

M. A. Kudenko, S. V. Troitsky

Cosmic rays with energies above $10^{19}$ eV, observed in 1999-2004 by the High Resolution Fly's Eye (HiRes) experiment in the stereoscopic mode, were found to correlate with directions to distant BL Lac type objects (BL Lacs), suggesting non-standard neutral particles travelling for cosmological distances without attenuation. This effect could not be tested

Edward Shuryak, Gregory Falkovvich

It was proposed that acoustic perturbations generated by the QCD phase transition could create an inverse turbulent cascade \cite{Kalaydzhyan:2014wca}. An assumption was that propagation toward smaller momenta could reach the wavelength of a few km, the Universe's size at the time. Such acoustic waves were proposed to be the source of gravity waves. The kilo

C. Lin Liu, Israel L. Donato Ridgley, Matthew L. Elwin, Michael Rubenstein

Human-swarm interaction is facilitated by a low-dimensional encoding of the swarm formation, independent of the (possibly large) number of robots. We propose using image moments to encode two-dimensional formations of robots. Each robot knows its pose and the desired formation moments, and simultaneously estimates the current moments of the entire swarm whil

Emeric Gioan

For an oriented matroid M, and given a generic single element extension and a generic single element lifting of M, the main result of [1] provides a bijection between bases of M and certain reorientations of M induced by the extension-lifting. This note is intended to somehow clarify and precise the geometric setting for this paper in terms of oriented matro

Baptiste Louf, Colin McDiarmid, Fiona Skerman

We relate two important notions in graph theory: expanders which are highly connected graphs, and modularity a parameter of a graph that is primarily used in community detection. More precisely, we show that a graph having modularity bounded below 1 is equivalent to it having a large subgraph which is an expander. We further show that a connected component $

Lihua Lei, Brad Ross

We develop a spectral approach for identifying and estimating average counterfactual outcomes under a low-rank factor model with short panel data and general outcome missingness patterns. Applications include event studies and studies of outcomes of "matches" between agents of two types, e.g. people and places, typically conducted using less-flexible Two-Way

Wenkui Du, Connor Mooney, Yang Yang, Jingze Zhu

We prove that an anisotropic minimal graph over a half-space with flat boundary must itself be flat. This generalizes a result of Edelen-Wang to the anisotropic case. The proof uses only the maximum principle and ideas from fully nonlinear PDE theory in lieu of a monotonicity formula.

Anton V. Solov'yov

We define natural volume forms on $n$-dimensional oriented pseudo-Finslerian manifolds with non-degenerate $m$-th root metrics. Our definitions of the natural volume forms depend on the parity of the positive integer $m>1$. The advantage of the stated definitions is their algebraic structure. The natural volume forms are expressed in terms of Cayley hyperdet

Jianwei Zhang, Helian Feng, Xin He, Grant P. Strimel

We present a novel search optimization solution for approximate nearest neighbor (ANN) search on resource-constrained edge devices. Traditional ANN approaches fall short in meeting the specific demands of real-world scenarios, e.g., skewed query likelihood distribution and search on large-scale indices with a low latency and small footprint. To address these

Marco Fanizza, Niklas Galke, Josep Lumbreras, Cambyse Rouzé

Matrix product operators allow efficient descriptions (or realizations) of states on a 1D lattice. We consider the task of learning a realization of minimal dimension from copies of an unknown state, such that the resulting operator is close to the density matrix in trace norm. For finitely correlated translation-invariant states on an infinite chain, a real

Talieh S. Ghiasi, Davit Petrosyan, Josep Ingla-Aynés, Tristan Bras

A promising approach to attain long-distance coherent spin propagation is accessing topological spin-polarized edge states in graphene. Achieving this without external magnetic fields necessitates engineering graphene band structure, obtainable through proximity effects in van der Waals heterostructures. In particular, proximity-induced staggered potentials

Yi Wei, Xingjian Wang, Xinyu Tian, Shaoping Wang

For lower limb amputees, an active ankle joint prosthesis can provide basic mobility functions. This study focuses on an ankle joint prosthesis system based on the principle of electric-hydraulic actuation. By analyzing the characteristics of human gait cycles and the mechanics of ankle joint movement, a lightweight and integrated ankle joint prosthesis is d

Zexu Pan, Gordon Wichern, Francois G. Germain, Sameer Khurana

Neuro-steered speaker extraction aims to extract the listener's brain-attended speech signal from a multi-talker speech signal, in which the attention is derived from the cortical activity. This activity is usually recorded using electroencephalography (EEG) devices. Though promising, current methods often have a high speaker confusion error, where the inter

Pavel D. Kurilovich, Vladislav D. Kurilovich, Aleksandr E. Svetogorov, Wolfgang Belzig

A mechanism to deterministically prepare a nanowire Josephson junction in an odd parity state is proposed. The mechanism involves population of two Andreev levels by a resonant microwave drive breaking a Cooper pair, and a subsequent ionization of one of the levels by the same drive. Robust preparation of the odd state is allowed by a residual Coulomb repuls

Alexandre Duval, Simon V. Mathis, Chaitanya K. Joshi, Victor Schmidt

Recent advances in computational modelling of atomic systems, spanning molecules, proteins, and materials, represent them as geometric graphs with atoms embedded as nodes in 3D Euclidean space. In these graphs, the geometric attributes transform according to the inherent physical symmetries of 3D atomic systems, including rotations and translations in Euclid

Paulo Areyuna C., Jilberto Zamora-Saa, Alfonso R. Zerwekh

In this work, we propose a novel approach to particle physics phenomenology, which we dubbed as model benchmark analysis. We consider models that provide vertices with similar topology but different Lorentz and gauge structure, which we call isomorphic models. Under this setup, the coupling constants for each theory have the same meaning, in the sense that d

Yash Jain, Anshul Nasery, Vibhav Vineet, Harkirat Behl

Modern video generation models like Sora have achieved remarkable success in producing high-quality videos. However, a significant limitation is their inability to offer interactive control to users, a feature that promises to open up unprecedented applications and creativity. In this work, we introduce the first solution to equip diffusion-based video gener

Maria Kudenko, Sergey Troitsky

$\it{Context.}$ Various high-energy phenomena in the Universe are associated with blazars, powerful active galaxies with jets pointing to the observer. Novel results relating blazars to high-energy neutrinos, cosmic rays, and even possible manifestations of new particle physics, are often based on statistical analyses of blazar samples, and uniform sky cover

Alexander Mehta, William Yang

In the task of emotion recognition from videos, a key improvement has been to focus on emotions over time rather than a single frame. There are many architectures to address this task such as GRUs, LSTMs, Self-Attention, Transformers, and Temporal Convolutional Networks (TCNs). However, these methods suffer from high memory usage, large amounts of operations

N. Barry, J. L. B. Line, C. R. Lynch, M. Kriele

Measurements with widefield radio interferometers often include the near-infinite gradient between the sky and the horizon. This causes aliasing inherent to the measurement itself, and is purely a consequence of the Fourier basis. For this reason, the horizon is often attenuated by the instrumental beam down to levels deemed inconsequential. However, this ef

Alberto Garilli, Pedro E. Harunari, Matteo Polettini

Coarse-grained models are widely used to explain the effective behavior of partially observable physical systems with hidden degrees of freedom. Reduction procedures in state space typically disrupt Markovianity and a fluctuation relation cannot be formulated. A recently developed framework of transition-based coarse-graining gave rise to a fluctuation relat

Yang Fu, Sifei Liu, Amey Kulkarni, Jan Kautz

While neural rendering has led to impressive advances in scene reconstruction and novel view synthesis, it relies heavily on accurately pre-computed camera poses. To relax this constraint, multiple efforts have been made to train Neural Radiance Fields (NeRFs) without pre-processed camera poses. However, the implicit representations of NeRFs provide extra ch

P. Amedo, R. Hafeji, A. Roberts, A. Lowe

Argon gas doped with 1% wavelength-shifter (CF$_4$) has been employed in an optical time projection chamber (OTPC) to image cosmic radiation. We present results obtained during the system commissioning, performed with two stacked glass-THGEMs and an EMCCD camera at 1 bar. Preliminary estimates indicate that the combined optical gain was of the order of 10$^6

Xiao Fang, Anindya Bhadra

In nonparameteric Bayesian approaches, Gaussian stochastic processes can serve as priors on real-valued function spaces. Existing literature on the posterior convergence rates under Gaussian process priors shows that it is possible to achieve optimal or near-optimal posterior contraction rates if the smoothness of the Gaussian process matches that of the tar

Svjetlana Fajfer, Eleftheria Solomonidi, Luiz Vale Silva

Physics of the up-type flavour offers unique possibilities of testing the Standard Model (SM) compared to the down-type flavour sector. Here, we discuss SM and New Physics (NP) contributions to the rare charm-meson decay $ D^0 \to \pi^+ \pi^- \ell^+ \ell^- $. In particular, we discuss the effect of including the lightest scalar isoscalar resonance in the SM

Quoc-Bao Ninh, Hai-Chan Nguyen, Triet Huynh, Trung-Nghia Le

For a long time, images have proved perfect at both storing and conveying rich semantics, especially human emotions. A lot of research has been conducted to provide machines with the ability to recognize emotions in photos of people. Previous methods mostly focus on facial expressions but fail to consider the scene context, meanwhile scene context plays an i

Albert Wong, Lien Pham, Young Lee, Shek Chan

This paper presents the development process of a natural language to SQL model using the T5 model as the basis. The models, developed in August 2022 for an online transaction processing system and a data warehouse, have a 73\% and 84\% exact match accuracy respectively. These models, in conjunction with other work completed in the research project, were impl

Timofei Rusalev, Daniil Stepanenko, Igor Volovich

The usual derivation of the violation of Bell-type inequalities can be applied actually only for small distances between detectors. It does not take into account the dependence of the quantum mechanical wave function on space-time variables. We study the behavior of entangled photons obtained in spontaneous parametric down-conversion (SPDC) experiments and s

Kirill Kobialko, Igor Bogush, Dmitri Gal'tsov

Explicitly covariant analytical expressions are derived that describe the boundaries of shadows cast by massive particles scattered by a gravitating object. This covers scenarios with particles having effectively variable mass, such as photons in plasma, geodesics in higher dimensions, and particles interacting with a scalar field. The derived formula takes

Arkopal Dutt, William Kirby, Rudy Raymond, Charles Hadfield

Many hybrid quantum-classical algorithms for the application of ground state energy estimation in quantum chemistry involve estimating the expectation value of a molecular Hamiltonian with respect to a quantum state through measurements on a quantum device. To guide the selection of measurement methods designed for this observable estimation problem, we prop

Pavel D. Grigoriev, Taras I. Mogilyuk

We develop the theory of magnetoresistance oscillations in layered quasi-two-dimensional (quasi-2D) metals. Using the Kubo-Streda formula, we calculate the Hall intralayer conductivity in a magnetic field perpendicular to conducting layers. The analytical expressions for the amplitudes and phases of magnetic quantum oscillations (MQO) and of the difference o

Jiangning Zhang, Xuhai Chen, Yabiao Wang, Chengjie Wang

This work studies a challenging and practical issue known as multi-class unsupervised anomaly detection (MUAD). This problem requires only normal images for training while simultaneously testing both normal and anomaly images across multiple classes. Existing reconstruction-based methods typically adopt pyramidal networks as encoders and decoders to obtain m

Alexis Michelat

Furthering the development of Da Lio-Gianocca-Rivi\`ere's Morse stability theory (arXiv:2212.03124) that was first applied to harmonic maps between manifolds and later extended to the case of Willmore immersions (arXiv:2306.04608-04609), we generalise the method to the case of (intrinsic or extrinsic) biharmonic maps. In the course of the proof, we develop a

Sahal Kaushik

In this work, it is shown that in certain nonsymmorphic space groups, electric polarization due to an external electric field or ferroelectric order produces Weyl phonons.

Manish Nagireddy, Lamogha Chiazor, Moninder Singh, Ioana Baldini

Current datasets for unwanted social bias auditing are limited to studying protected demographic features such as race and gender. In this work, we introduce a comprehensive benchmark that is meant to capture the amplification of social bias, via stigmas, in generative language models. Taking inspiration from social science research, we start with a document

Kerstin S. Haring

This position paper briefly considers the current benefits and shortcomings surrounding robot trust and acceptance, focusing on robots with interactive capabilities. The paper concludes with currently unanswered questions and may serve as a jumping-off point for discussion.

Gia-Bao Le, Van-Tien Nguyen, Trung-Nghia Le, Minh-Triet Tran

Whole-slide image (WSI) analysis plays a crucial role in cancer diagnosis and treatment. In addressing the demands of this critical task, self-supervised learning (SSL) methods have emerged as a valuable resource, leveraging their efficiency in circumventing the need for a large number of annotations, which can be both costly and time-consuming to deploy sup

Hao Shao, Yuxuan Hu, Letian Wang, Steven L. Waslander

Despite significant recent progress in the field of autonomous driving, modern methods still struggle and can incur serious accidents when encountering long-tail unforeseen events and challenging urban scenarios. On the one hand, large language models (LLM) have shown impressive reasoning capabilities that approach "Artificial General Intelligence". On the o

Oleksiy Kolezhuk, Roman Teslia, Ihor Buryak, Olena Gomonay

Chirality as internal degree of freedom of a mesoscopic domain wall inside a quasi-one-dimensional fixture can be controlled by spin-polarized current for ferro- as well as anti-ferro-magnetic domain walls. We show that the current density required for the chirality manipulation can be significantly reduced in the low-temperature regime where the chirality d

Stylianos A. Tsilioukas, Emmanuel N. Saridakis, Charalampos Tzerefos

It is known that the appearance of microscopic objects with distinct topologies and different Euler characteristics, such as instatons and wormholes, at the spacetime-foam level in Euclidean quantum gravity approaches, leads to spacetime topology changes. Such changes, in principle, may affect the field equations that arise through the semiclassical variatio

Jianxiong Gao, Yuqian Fu, Yun Wang, Xuelin Qian

In this paper, we introduce Recon3DMind, an innovative task aimed at reconstructing 3D visuals from Functional Magnetic Resonance Imaging (fMRI) signals, marking a significant advancement in the fields of cognitive neuroscience and computer vision. To support this pioneering task, we present the fMRI-Shape dataset, which includes data from 14 participants an

CMS Collaboration

A search for long-lived heavy neutral leptons (HNLs) is presented, which considers the hadronic final state and coupling scenarios involving all three lepton generations in the 2-20 GeV HNL mass range for the first time. Events comprising two leptons (electrons or muons) and jets are analyzed in a data sample of proton-proton collisions, recorded with the CM

Arthur D. Adams, Greg Laughlin

Venus may have had both an Earth-like climate as well as extensive water oceans and active (or incipient) plate tectonics for an extended interval of its history. The topographical power spectrum of Venus provides important clues to the planet's past evolution. By drawing detailed contrast with the strong low-order odd-$l$ dominated global topography of Eart

Manar Mohamed Hafez, Rebeca P. Díaz Redondo, Ana Fernández-Vilas, Héctor Olivera Pazó

Food retailing is now on an accelerated path to a success penetration into the digital market by new ways of value creation at all stages of the consumer decision process. One of the most important imperatives in this path is the availability of quality data to feed all the process in digital transformation. But the quality of data is not so obvious if we co

Wolfgang König, Quirin Vogel, Alexander Zass

We consider the path-integral representation of the ideal Bose gas under various boundary conditions. We show that Bose--Einstein condensation occurs at the famous critical density threshold, by proving that its $1$-particle-reduced density matrix exhibits off-diagonal long-range order above that threshold, but not below. Our proofs are based on the well-kno

Himanshu Vashishtha, Parastoo Jamshidi, Anastasia Vrettou, Anna Kareer

This study explores cardiovascular stents fabricated using laser powder bed fusion (LPBF); an emerging method to offer patient-specific customisable parts. Here, the shape memory alloy NiTi, in a near equiatomic composition, was investigated to deconvolve the material response from macroscopic component effects. Specifically, stress-geometry interactions wer

Nora Ouzir, Frédéric Pascal, Jean-Christophe Pesquet

The multivariate generalized Gaussian distribution (MGGD), also known as the multivariate exponential power (MEP) distribution, is widely used in signal and image processing. However, estimating MGGD parameters, which is required in practical applications, still faces specific theoretical challenges. In particular, establishing convergence properties for the

Zihao Wang, Jing Zhao, Xuetong Ding, Hui Zhang

Face plays an important role in humans visual perception, and reconstructing perceived faces from brain activities is challenging because of its difficulty in extracting high-level features and maintaining consistency of multiple face attributes, such as expression, identity, gender, etc. In this study, we proposed a novel reconstruction framework, which we

H. R. Christiansen, R. M. Lima

We present a comprehensive spectral analysis of cylindrical quantum heterostructures by considering effective electronic carriers with position-dependent mass for five different kinetic-operator orderings. We obtain the bound energy eigenstates of particles in a three-dimensional cylindrical nanowire under a confining hyperbolic potential with both open and

Jonah Kudler-Flam, Samuel Leutheusser, Adel A. Rahman, Gautam Satishchandran

While von Neumann entropies for subregions in quantum field theory universally contain ultraviolet divergences, differences between von Neumann entropies are finite and well-defined in many physically relevant scenarios. We demonstrate that such a notion of entropy differences can be rigorously defined in quantum field theory in a general curved spacetime by

Caoyun Fan, Jidong Tian, Yitian Li, Hao He

In-Context Learning (ICL) is an important paradigm for adapting Large Language Models (LLMs) to downstream tasks through a few demonstrations. Despite the great success of ICL, the limitation of the demonstration number may lead to demonstration bias, i.e. the input-label mapping induced by LLMs misunderstands the task's essence. Inspired by human experience

Srihari M. Kastuar, Zhong-Li Liu, Sina Najmaei, Chinedu E. Ekuma

We report the mechanical properties of cubic boron nitride (c-BN) and diamond under the combined impact of dynamical pressure and temperature, calculated using ab initio molecular dynamics. Our study revealed a pronounced sensitivity of the mechanical properties of c-BN to applied pressure. Notably, c-BN undergoes a brittle-to-ductile transition at ~220 GPa,

Wei Min, Xin Gao

Stimulated Raman scattering (SRS) has played an increasingly pivotal role in chemistry and photonics. Recently, understanding of light-molecule interaction during SRS was brought to a new quantitative level through the introduction of stimulated Raman cross section, $\sigma_{SRS}$. Measurements of Raman-active molecules have revealed interesting insights, an

Patricio Gaete, José Abdalla Helayël-Neto

We investigate physical consequences of non-linear electrodynamic coupled to parameters that signal violation Lorentz-symmetry breaking (LSV). Our undertaking is done by considering a general non-linear photonic Lagrangian which coupled to the Carroll-Field-Jackiw's model (CFJ). Our endeavor reveals how the (meta) material constitutive properties of the vacu

Yiran Qin, Enshen Zhou, Qichang Liu, Zhenfei Yin

It is a long-lasting goal to design an embodied system that can solve long-horizon open-world tasks in human-like ways. However, existing approaches usually struggle with compound difficulties caused by the logic-aware decomposition and context-aware execution of these tasks. To this end, we introduce MP5, an open-ended multimodal embodied system built upon

A. E. McEwen, J. K. Swiggum, D. L. Kaplan, C. M. Tan

The Green Bank North Celestial Cap survey is one of the largest and most sensitive searches for pulsars and transient radio objects. Observations for the survey have finished; priorities have shifted toward long-term monitoring of its discoveries. In this study, we have developed a pipeline to handle large datasets of archival observations and connect them t

Lexy A. L. Andati, O. M. Smirnov, S. Makhathini, L. M. Sebokolodi

Astronomers performing polarimetric analysis on astronomical images often have to manually identify locations on their objects of interest, such as galaxies, which exhibit the influence of magnetic forces due to interaction with their environments or inherent processes. These locations are known as Lines of Sight (LoS). Analysing the various lines of sight c

Ben-Hur Francisco Cardoso, Eva Yamila da Silva Catela, Guilherme Viegas, Flávio L. Pinheiro

Research on productive structures has shown that economic complexity conditions economic growth. However, little is known about which type of complexity, e.g., export or industrial complexity, matters more for regional economic growth in a large emerging country like Brazil. Brazil exports natural resources and agricultural goods, but a large share of the em

Akhil Aravind, Gautham Vadlamudi, Saptarshi Basu

Understanding the dynamics of flames at small scales opens up opportunities to enhance the performance of small-scale power generation devices, micro-reactors, fire safety devices, and numerous other systems that confine combustion to micro/meso scales. The current study delves into the dynamics of laminar premixed methane-air flames in mesoscale channels, s

Md Abrar Jahin, Saleh Akram Naife, Anik Kumar Saha, M. F. Mridha

Supply chain risk assessment (SCRA) is pivotal for ensuring resilience in increasingly complex global supply networks. While existing reviews have explored traditional methodologies, they often neglect emerging artificial intelligence (AI) and machine learning (ML) applications and mostly lack combined systematic and bibliometric analyses. This study address

Heikki Mäntysaari, Farid Salazar, Björn Schenke, Chun Shen

Within the Color Glass Condensate framework, we demonstrate that exclusive vector meson production at high energy is sensitive to the geometric deformation of the target nucleus and subnucleon scale fluctuations. Deformation of the nucleus enhances the incoherent cross section in the small $|t|$ region. Subnucleon scale fluctuations increase the incoherent c

Aitor Martinez Seras, Javier Del Ser, Pablo Garcia-Bringas

Besides performance, efficiency is a key design driver of technologies supporting vehicular perception. Indeed, a well-balanced trade-off between performance and energy consumption is crucial for the sustainability of autonomous vehicles. In this context, the diversity of real-world contexts in which autonomous vehicles can operate motivates the need for emp

S. M. Puchinin, E. R. Korolkov, F. S. Stonyakin, M. S. Alkousa

In this paper, we consider two variants of the concept of sharp minimum for mathematical programming problems with quasiconvex objective function and inequality constraints. It investigated the problem of describing a variant of a simple subgradient method with switching along productive and non-productive steps, for which, on a class of problems with Lipsch

STAR Collaboration, M. I. Abdulhamid, B. E. Aboona, J. Adam

Flow coefficients ($v_2$ and $v_3$) are measured in high-multiplicity $p$+Au, $d$+Au, and $^{3}$He$+$Au collisions at a center-of-mass energy of $\sqrt{s_{_{\mathrm{NN}}}}$ = 200 GeV using the STAR detector. The measurements utilize two-particle correlations with a pseudorapidity requirement of $|\eta| <$ 0.9 and a pair gap of $|\Delta\eta|>1.0$. The primary

Manar Mohamed Hafez, Rebeca P. Díaz Redondo, Ana Fernández-Vilas, Héctor Olivera Pazó

With the exponential increase in information, it has become imperative to design mechanisms that allow users to access what matters to them as quickly as possible. The recommendation system ($RS$) with information technology development is the solution, it is an intelligent system. Various types of data can be collected on items of interest to users and pres

Zhi-Xing Lin, Shu Zhang

The stacking of intrinsically magnetic van der Waals materials provides a fertile platform to explore tunable transport effects of magnons, presenting significant prospects for spintronic applications. The possibility of having topologically nontrivial magnons in these systems can further expand the scope of exploration. In this work, we consider a bilayer s

Giuliano Giacalone, Bjoern Schenke, Soeren Schlichting, Pragya Singh

Results on collisions of $^{16}$O nuclei performed at the Relativistic Heavy Ion Collider (RHIC) have been presented for the first time at Quark Matter 2023 by the STAR collaboration. $^{16}$O+$^{16}$O collisions are also expected to take place in the near future at the Large Hadron Collider (LHC) at much higher beam energies. We explore the potential of bea