October 2023 arXiv papers — page 4

Edoardo D'Angelo, Nicola Pinamonti

We prove local existence of solutions of a functional Renormalisation Group equation for the effective action of an interacting quantum field theory, when a suitable Local Potential Approximation is considered. To obtain this equation in a Lorentzian setting, a quantum state for the theory is selected, and a regulator consisting in a mass is added to the act

D. A. Maltsev, Yu. V. Lomachuk, V. M. Shakhova, N. S. Mosyagin

The compound-tunable embedding potential (CTEP) method is applied to study actinide substitutions in the niobate crystals YNbTiO$_6$ and CaNb$_2$O$_6$. Two one-center clusters centered on Ca and Y are built and 20 substitutions of Ca and Y with U, Np, Pu, Am, and Cm in four different oxidation states were made for each cluster. Geometry relaxation is perform

Andrea Ciamarra, Federico Becattini, Lorenzo Seidenari, Alberto Del Bimbo

Forecasting motion and spatial positions of objects is of fundamental importance, especially in safety-critical settings such as autonomous driving. In this work, we address the issue by forecasting two different modalities that carry complementary information, namely optical flow and depth. To this end we propose FLODCAST a flow and depth forecasting model

Brandon Curd, Richard Anantua, Hayley West, Joaquin Duran

Magnetically arrested accretion disks (MADs) around a rapidly rotating black hole (BH) have been proposed as a model for jetted tidal disruption events (TDEs). However, the stream and disk interact strongly at times, and this will lead to different dynamics than expected in the standard MAD model. Here we employ global GRMHD simulations of a MAD disk interac

Yohei Ito

In this paper, we shall consider some finiteness of ind-sheaves with ring actions. As the main result of this paper, there exists an equivalence of categories between the abelian category of coherent ind-$\beta\mathcal{A}$-modules and the one of coherent $\mathcal{A}$-modules, where $\mathcal{A}$ is a sheaf of k-algebras and $\Bbbk$ is a field.

Ronit Chitre, Arpita Sinha

Mobile robots often have limited battery life and need to recharge periodically. This paper presents an RRT- based path-planning algorithm that addresses battery power management. A path is generated continuously from the robot's current position to its recharging station. The robot decides if a recharge is needed based on the energy required to travel on th

Omar Momen, David Arps, Laura Kallmeyer

In this paper, we describe our submission to the BabyLM Challenge 2023 shared task on data-efficient language model (LM) pretraining (Warstadt et al., 2023). We train transformer-based masked language models that incorporate unsupervised predictions about hierarchical sentence structure into the model architecture. Concretely, we use the Structformer archite

Yuqi Wang, Zeqiang Wang, Wei Wang, Qi Chen

In the era of the Internet of Things (IoT), the retrieval of relevant medical information has become essential for efficient clinical decision-making. This paper introduces MedFusionRank, a novel approach to zero-shot medical information retrieval (MIR) that combines the strengths of pre-trained language models and statistical methods while addressing their

Ruizhe Shi, Yuyao Liu, Yanjie Ze, Simon S. Du

Offline reinforcement learning (RL) aims to find a near-optimal policy using pre-collected datasets. In real-world scenarios, data collection could be costly and risky; therefore, offline RL becomes particularly challenging when the in-domain data is limited. Given recent advances in Large Language Models (LLMs) and their few-shot learning prowess, this pape

Jinwei Zhang, Lianrui Zuo, Blake E. Dewey, Samuel W. Remedios

Deep learning algorithms utilizing magnetic resonance (MR) images have demonstrated cutting-edge proficiency in autonomously segmenting multiple sclerosis (MS) lesions. Despite their achievements, these algorithms may struggle to extend their performance across various sites or scanners, leading to domain generalization errors. While few-shot or one-shot dom

Dan Stetson, Paul Labrousse, Hugh Russell, David Shera

Circulating tumour DNA (ctDNA) detection of molecular residual disease (MRD) in solid tumours correlates strongly with patient outcomes and is being adopted as a new clinical standard. ctDNA levels are known to correlate with tumor volume, and although the absolute levels vary across indication and histology, its analysis is driving the adoption of MRD. MRD

M. Juvela

Dust emission is an important tool in studies of star-forming clouds, as a tracer of column density and indirectly via the dust evolution that is connected to the history and physical conditions of the clouds. We examine radiative transfer (RT) modelling of dust emission over an extended cloud region, using a filament in the Taurus molecular cloud as an exam

Morris Ang, Nina Holden, Xin Sun, Pu Yu

Two-pointed quantum disks with a weight parameter $W>0$ is a canonical family of finite-volume random surfaces in Liouville quantum gravity. We extend the conformal welding of quantum disks in [AHS23] to the non-simple regime, and give a construction of the multiple SLE associated with any given link pattern for $\kappa\in(4,8)$. Our proof is based on connec

Thomas F. Varley, Daniel Havert, Leandro Fosque, Abolfazl Alipour

Most of the recent work in psychedelic neuroscience has been done using non-invasive neuroimaging, with data recorded from the brains of adult volunteers under the influence of a variety of drugs. While this data provides holistic insights into the effects of psychedelics on whole-brain dynamics, the effects of psychedelics on the meso-scale dynamics of cort

Jihao Andreas Lin, Shreyas Padhy, Javier Antorán, Austin Tripp

As is well known, both sampling from the posterior and computing the mean of the posterior in Gaussian process regression reduces to solving a large linear system of equations. We study the use of stochastic gradient descent for solving this linear system, and show that when \emph{done right} -- by which we mean using specific insights from the optimisation

A. L. Avakyan, G. V. Lipunova, K. L. Malanchev

Theoretical models of accretion discs and observational data indicate that the X-ray emission from the inner parts of an accretion disc can irradiate its outer regions and induce a thermal wind, which carries away the mass and angular momentum from the disc. Our aim is to investigate the influence of the thermal wind on the outburst light curves of black hol

Jiayuan Ye, Zhenyu Zhu, Fanghui Liu, Reza Shokri

We analytically investigate how over-parameterization of models in randomized machine learning algorithms impacts the information leakage about their training data. Specifically, we prove a privacy bound for the KL divergence between model distributions on worst-case neighboring datasets, and explore its dependence on the initialization, width, and depth of

Qian Xu, Pei Zeng, Daohong Xu, Liang Jiang

Fault-tolerant quantum computation with bosonic qubits often necessitates the use of noisy discrete-variable ancillae. In this work, we establish a comprehensive and practical fault-tolerance framework for such a hybrid system and synthesize it with fault-tolerant protocols by combining bosonic quantum error correction (QEC) and advanced quantum control tech

Ilja Behnke, Philipp Wiesner, Paul Voelker, Odej Kao

Offloading is a popular way to overcome the resource and power constraints of networked embedded devices, which are increasingly found in industrial environments. It involves moving resource-intensive computational tasks to a more powerful device on the network, often in close proximity to enable wireless communication. However, many Industrial Internet of T

Peng Dong, Xiang Zhou, Xiaofei Hou, Jiadian He

Nontrivial topological superconductivity has received enormous research attentions due to its potential for diverse applications in topological quantum computing. The intrinsic issue concerning the correlation between a topological insulator and a superconductor is, however, still widely open. Here, we systemically report an emergent superconductivity in a c

Solmaz Golmohammadi, Mina Zarei, Jacopo Grilli

The ecological dynamics of interacting predator and prey populations can display sustained oscillations, as for instance predicted by the Rosenzweig-MacArthur predator-prey model. The presence of demographic stochasticity, due to the finiteness of population sizes, alters the amplitude and frequency of these oscillations. Here we present a method for charact

Philipp Dahlinger, Philipp Becker, Maximilian Hüttenrauch, Gerhard Neumann

Stochastic gradient-based optimization is crucial to optimize neural networks. While popular approaches heuristically adapt the step size and direction by rescaling gradients, a more principled approach to improve optimizers requires second-order information. Such methods precondition the gradient using the objective's Hessian. Yet, computing the Hessian is

Odile Sauzet, Julia Dyck, Victoria Cornelius

Objectives: Statistical methods for signal detection of adverse drug reactions in electronics health records (EHRs) are not usually provided with information about optimal p-values and indicative sample sizes to achieve sufficient power. Sauzet \& Cornelius (2022) have proposed test for signal detection based on the hazard functions of Weibull type distribut

A. Moullet, T. Kataria, D. Lis, S. Unwin

PRIMA (The PRobe for-Infrared Mission for Astrophysics) is a concept for a far-infrared (IR) observatory. PRIMA features a cryogenically cooled 1.8 m diameter telescope and is designed to carry two science instruments enabling ultra-high sensitivity imaging and spectroscopic studies in the 24 to 235 microns wavelength range. The resulting observatory is a po

Young-Hun Kim, So-Yeon Lee, Young-Tak Oh

Assuming Stanley's $P$-partition conjecture holds, the regular Schur labeled skew shape posets with underlying set $\{1,2,\ldots, n\}$ are precisely the posets $P$ such that the $P$-partition generating function is symmetric and the set of linear extensions of $P$, denoted $\Sigma_L(P)$, is a left weak Bruhat interval in the symmetric group $\mathfrak{S}_n$.

Xiaoting Gao, Mathieu Isoard, Fengxiao Sun, Carlos E. Lopetegui

Entanglement in continuous-variable non-Gaussian states provides irreplaceable advantages in many quantum information tasks. However, the sheer amount of information in such states grows exponentially and makes a full characterization impossible. Here, we develop a neural network that allows us to use correlation patterns to effectively detect continuous-var

Juan Luis Vázquez

We construct the Very Singular Solution (VSS) for the Anisotropic Fast Diffusion Equation (AFDE) in the suitable good exponent range of fast diffusion. VSS is a solution that, starting from an infinite mass located at one point as initial datum, evolves according to the corresponding equation as an admissible solution away from the singularity. It is expecte

Farhad Ghanipoor, Carlos Murguia, Peyman Mohajerin Esfahani, Nathan van de Wouw

We present a framework for learning of modeling uncertainties in Linear Time Invariant (LTI) systems. We propose a methodology to extend the dynamics of an LTI (without uncertainty) with an uncertainty model, based on measured data, to improve the predictive capacity of the model in the input-output sense. The proposed framework guarantees stability of the e

Cesare Donati, Martina Mammarella, Fabrizio Dabbene, Carlo Novara

The aim of this paper is to present a novel physics-based framework for the identification of dynamical systems, in which the physical and structural insights are reflected directly into a backpropagation-based learning algorithm. The main result is a method to compute in closed form the gradient of a multi-step loss function, while enforcing physical proper

Wonjune Choi, Michael Knap, Frank Pollmann

We study the logarithmic entanglement negativity of symmetry-protected topological (SPT) phases and quantum critical points (QCPs) of one-dimensional noninteracting fermions at finite temperatures. In particular, we consider a free fermion model that realizes not only quantum phase transitions between gapped phases but also an exotic topological phase transi

Maria Quadeer

We study Haar-random bases and pretty good measurement for Bayesian state estimation. Given $N$ Haar-random bases we derive a bound on fidelity averaged over IID sequences of such random measurements for a uniform ensemble of pure states. For ensembles of mixed qubit states, we find that measurements defined through unitary 2-designs closely approximate thos

Bo Mu, Jing Liu, Gong Cheng, Zong-Kuan Guo

Ultra-slow-roll~(USR) inflation predicts an exponential amplification of scalar perturbations at small scales, which leads to a stochastic gravitational wave background~(SGWB) through the coupling of the scalar and tensor modes at the second-order expansion of the Einstein equation. In this work, we search for such a scalar-induced SGWB from the NANOGrav 15-

Andrea Miotti

This paper provides policy recommendations to reduce extinction risks from advanced artificial intelligence (AI). First, we briefly provide background information about extinction risks from AI. Second, we argue that voluntary commitments from AI companies would be an inappropriate and insufficient response. Third, we describe three policy proposals that wou

Aloysius Helminck, Gerardus Helminck

Inside the algebra $LT_{\mathbb{Z}}(R)$ of $\mathbb{Z} \times \mathbb{Z}$-matrices with coefficients from a commutative $\mathbb{C}$-algebra $R$ that have only a finite number of nonzero diagonals above the central diagonal, we consider a deformation of a commutative Lie algebra $\mathcal{C}_{sh}(\mathbb{C})$ of finite band skew hermitian matrices that is di

Siddharth H. Nair, Hotae Lee, Eunhyek Joa, Yan Wang

We propose a Stochastic MPC (SMPC) formulation for path planning with autonomous vehicles in scenarios involving multiple agents with multi-modal predictions. The multi-modal predictions capture the uncertainty of urban driving in distinct modes/maneuvers (e.g., yield, keep speed) and driving trajectories (e.g., speed, turning radius), which are incorporated

Andrzej Herdegen

The extended algebra of the free electromagnetic fields, including infrared singular fields, and the almost radial gauge, both introduced earlier, are postulated for the construction of the quantum electrodynamics in a Hilbert space (no indefinite metric). Both the Dirac and electromagnetic fields are constructed up to the first order (based on the incoming

Baike She, Rebecca Lee Smith, Ian Pytlarz, Shreyas Sundaram

During the COVID-19 pandemic, different countries, regions, and communities constructed various epidemic models to evaluate spreading behaviors and assist in making mitigation policies. Model uncertainties, introduced by complex transmission behaviors, contact-tracing networks, time-varying spreading parameters, and human factors, as well as insufficient dat

Liam McAllister, Fernando Quevedo

We give an overview of moduli stabilization in compactifications of string theory. We summarize current methods for construction and analysis of vacua with stabilized moduli, and we describe applications to cosmology and particle physics. This is a contribution to the Handbook of Quantum Gravity.

Aman Jaiswal, Evangelos Milios

Transformer-based models, specifically BERT, have propelled research in various NLP tasks. However, these models are limited to a maximum token limit of 512 tokens. Consequently, this makes it non-trivial to apply it in a practical setting with long input. Various complex methods have claimed to overcome this limit, but recent research questions the efficacy

Petar Marević, David Regnier, Denis Lacroix

The nuclear time-dependent density functional theory (TDDFT) is a tool of choice for describing various dynamical phenomena in atomic nuclei. In a recent study, we reported an extension of the framework - the multiconfigurational TDDFT (MC-TDDFT) model - that takes into account quantum fluctuations in the collective space by mixing several TDDFT trajectories

En-Hung Chao, Harvey B. Meyer, Julian Parrino

As several lattice collaborations agree on the result for the window quantity of the hadronic vacuum polarization (HVP) contribution to $(g-2)_\mu$, whilst being in tension with the calculation using the dispersive approach, further effort is needed in order to pin down the cause for this difference. Here we want to focus on the isospin breaking corrections

Jean C. Cortissoz, Juan J. Villamarín

We study the subsequential convergence of singular solutions to the Ricci flow with prescribed constant in space geodesic curvature on compact surfaces with boundary. Furthermore, we show that in the particular case of rotational symmetry, this convergence does not depend on the sign of the geodesic curvature of the boundary.

Dominik Bez, Jonas Sauer

We study journey planning in multimodal networks consisting of public transit plus an unrestricted transfer mode (e.g., walking or cycling). In order to provide good results in practice, algorithms must account for vehicle delays. Delay-responsive algorithms receive a continuous stream of delay updates and must return optimal journeys in the currently known

Mounika Gosika, Angel J. Moreno

We perform equilibrium Langevin dynamics simulations to understand the structure-viscoelasticity relationship of a dually crosslinked reversible polymer network. The cross-linking is achieved by introducing orthogonal crosslinkers (A and B) in to the polymer backbone, where only intra-species bonds (A-A or B-B) are allowed to be formed. We study the systems

Ruofan Wu, Mingyang Zhang, Lingjuan Lyu, Xiaolong Xu

The paradigm of vertical federated learning (VFL), where institutions collaboratively train machine learning models via combining each other's local feature or label information, has achieved great success in applications to financial risk management (FRM). The surging developments of graph representation learning (GRL) have opened up new opportunities for F

Oscar A. Garrido-Jiménez, Hugo A. Rincón-Mejía

In this paper we introduce some lattices of classes of left R-module relative to a preradical sigma. These lattices are generalizations of the lattices R-TORS, R-tors, R-nat, R-conat, of torsion theories, hereditary torsion theories, natural classes and conatural classes, respectively. We define the lattices $\sigma$-(R-TORS), $\sigma$-(R-tors), $\sigma$-(R-

Qiying Yu, Quan Sun, Xiaosong Zhang, Yufeng Cui

Large multimodal models demonstrate remarkable generalist ability to perform diverse multimodal tasks in a zero-shot manner. Large-scale web-based image-text pairs contribute fundamentally to this success, but suffer from excessive noise. Recent studies use alternative captions synthesized by captioning models and have achieved notable benchmark performance.

Kevin Ingles, Dananjaya Liyanage, Alexandra C. Semposki, John C. Yannotty

Uncertainty quantification using Bayesian methods is a growing area of research. Bayesian model mixing (BMM) is a recent development which combines the predictions from multiple models such that each model's best qualities are preserved in the final result. Practical tools and analysis suites that facilitate such methods are therefore needed. Taweret introdu

Lucía Soledad Ramirez, Federico Vazquez, Maxi San Miguel, Tobias Galla

We study the ordering dynamics of nonlinear voter models with multiple states, also providing a discussion of the two-state model. The rate with which an individual adopts an opinion scales as the $q$-th power of the number of the individual's neighbours in that state. For $q>1$ the dynamics favor the opinion held by the most agents. The ordering to consensu

Johan Bijnens, Nils Hermansson-Truedsson, Joan Ruiz-Vidal

We derive the order $p^8$ Lagrangian of odd intrinsic parity for mesonic chiral perturbation theory, and provide the resulting operator basis in the supplementary material. Neglecting the non-zero singlet trace, we find $999$ operators for a general number of quark flavours $N_f$, $705$ for $N_f=3$ and $92$ for $N_f=2$. Our numbers agree with those obtained

Matthew Seitz, Jacob Boisvere, Bryan Melanson, John Wyatt Morrell

III-Nitride micropillar structures show great promise for applications in micro light-emitting diodes and vertical power transistors due to their excellent scalability and outstanding electrical properties. Typically, III-Nitride micropillars are fabricated through a top-down approach using reactive ion etch which leads to roughened, non-vertical sidewalls t

Adrián Lozano-Durán, Gonzalo Arranz, Yuenong Ling

We introduce an information-theoretic method for quantifying causality in chaotic systems. The approach, referred to as IT-causality, quantifies causality by measuring the information gained about future events conditioned on the knowledge of past events. The causal interactions are classified into redundant, unique, and synergistic contributions depending o

Arka Bandyopadhyay, Nesta Benno Joseph, Awadhesh Narayan

The emergence of the fascinating non-linear Hall effect intrinsically depends on the non-zero value of the Berry curvature dipole. In this work, we predict that suitable strain engineering in layered van der Waals material phosphorene can give rise to a significantly large Berry curvature dipole. Using symmetry design principles, and a combination of feasibl

Katrin Herweg, Volkmar Schulz, David Schug

In PET a high percentage of gamma photons being detected undergo Compton scattering in the scintillator. Scintillator blocks are often built from optically isolated crystals. Depending on the angle of incidence and the scintillator geometry this might lead to inter crystal scatter (ICS) events, where energy is deposited in two or more crystals in the detecto

Hui Xu, Longben Wei, Zhiwen Duan

This paper is inspired by Wang, Wang and Zhang's work [ Observability and unique continuation inequalities for the Schr\"odinger equation. J. Eur. Math. Soc. 21, 3513--3572 (2019)], where they present several observability and unique continuation inequalities for the free Schr\"{o}dinger equation in $\mathbb{R}^{n}$. We extend all such observability and uniq

E. Nieto Hernández, H. B. Yağcı, V. Pugliese, P. Aprà

Single-photon emitters (SPEs) within wide-bandgap materials represent an appealing platform for the development of single-photon sources operating at room temperatures. Group III- nitrides have previously been shown to host efficient SPEs which are attributed to deep energy levels within the large bandgap of the material, in a way that is similar to extensiv

Chi-Ning Chou

Two transformative waves of computing have redefined the way we approach science. The first wave came with the birth of the digital computer, which enabled scientists to numerically simulate their models and analyze massive datasets. This technological breakthrough led to the emergence of many sub-disciplines bearing the prefix "computational" in their names

Giovanni Calvaruso, Lorenzo Pellegrino, Joeri Van der Veken

We classify and describe totally geodesic and parallel hypersurfaces for the entire class of Siklos spacetimes. A large class of minimal hypersurfaces is also described.

Saptarshi Roy, Raymond K. W. Wong, Yang Ni

Discovering causal relationship using multivariate functional data has received a significant amount of attention very recently. In this article, we introduce a functional linear structural equation model for causal structure learning when the underlying graph involving the multivariate functions may have cycles. To enhance interpretability, our model involv

Tianxiao Li, Jingxun Liang, Huacheng Yu, Renfei Zhou

Dictionaries have been one of the central questions in data structures. A dictionary data structure maintains a set of key-value pairs under insertions and deletions such that given a query key, the data structure efficiently returns its value. The state-of-the-art dictionaries [Bender, Farach-Colton, Kuszmaul, Kuszmaul, Liu 2022] store $n$ key-value pairs w

Martino Romaniello, Magda Arnaboldi, Mauro Barbieri, Nausicaa Delmotte

Scientific data collected at ESO's observatories are freely and openly accessible online through the ESO Science Archive Facility. In addition to the raw data straight out of the instruments, the ESO Science Archive also contains four million processed science files available for use by scientists and astronomy enthusiasts worldwide. ESO subscribes to the FA

Jan Klamka

Future e$^+$e$^-$ colliders, thanks to their clean environment and triggerless operation, offer a unique opportunity to search for long-lived particles (LLPs). Considered in this contribution are promising prospects for LLP searches offered by the International Large Detector (ILD), with a Time Projection Chamber (TPC) as the core of its tracking systems, pr

Kathryn Haymaker, Beth Malmskog, Gretchen L. Matthews

Codes with locality, also known as locally recoverable codes, allow for recovery of erasures using proper subsets of other coordinates. These subsets are typically of small cardinality to promote recovery using limited network traffic and other resources. Hierarchical locally recoverable codes allow for recovery of erasures using sets of other symbols whose

Paul C Bressloff

In this chapter, we review our recent work on first passage time (FPT) problems for absorption by a target whose interface is semipermeable. For pedagogical reasons, we focus on a single Brownian particle searching for a single target in a bounded domain. We begin by writing down the forward diffusion equation for the target problem, and define various quant

Pinsong Zhao, Fengshan Liu, Qifan Cui, Hassen M. Yesuf

We have measured structural parameters and radial color profiles of 108 ultra-diffuse galaxies (UDGs), carefully selected from six distant massive galaxy clusters in the Hubble Frontier Fields (HFF) in redshift range from 0.308 to 0.545. Our best-fitting GALFIT models show that the HFF UDGs have a median S\'ersic index of 1.09, which is close to 0.86 for loc

Giovanni Calvaruso, Lorenzo Pellegrino, Joeri Van der Veken

We classify parallel and totally geodesic hypersurfaces of the relevant class of G\"odel-type spacetimes, with particular regard to the homogeneous examples.

E. V. Ferapontov, V. Novikov, I. Roustemoglou

We consider the 3D Mikhalev system, $$ u_t=w_x, \quad u_y= w_t-u w_x+w u_x, $$ which has first appeared in the context of KdV-type hierarchies. Under the reduction $w=f(u)$, one obtains a pair of commuting first-order equations, $$ u_t=f'u_x, \quad u_y=(f'^2-uf'+f)u_x, $$ which govern simple wave solutions of the Mikhalev system. In this paper we study {\it

Yunze Yang, Kimberly R. Gergelis, Jiajian Shen, Arslan Afzal

Purpose: To study the effect of proton linear energy transfer (LET) on rib fracture in breast cancer patients treated with pencil-beam scanning proton therapy (PBS) using a novel tool of dose-LET volume histogram (DLVH). Methods: From a prospective registry of patients treated with post-mastectomy proton therapy to the chest wall and regional lymph nodes for

Hairong Liu, Long Tian, Xiaoping Yang

In this paper, we focus on estimating measure upper bounds of nodal sets of solutions to the following boundary value problem \begin{equation*} \left\{ \begin{array}{lll} \Delta u+Vu=0\quad \mbox{in}\ \Omega,\\[2mm] u=0\quad \mbox{on}\ \partial\Omega, \end{array}\right. \end{equation*} where $V\in W^{1,\infty}(\Omega)$ is a potential function, and $\Omega \s

Andrea Bevilacqua

In the following work we will introduce and discuss in detail a particular model of complex $\kappa$-deformed scalar field, whose behaviour under C, P , T transformation is particularly transparent from both a formal and phenomenological point of view. We will begin by introducing the key mathematical structure at the basis of our investigation, namely the $

Vladimir M. Stojanovic

The Holstein model, which describes purely local coupling of an itinerant excitation (electron, hole, exciton) with zero-dimensional (dispersionless) phonons, represents the paradigm for short-range excitation-phonon interactions. It is demonstrated here how spectral properties of small Holstein polarons -- heavily phonon-dressed quasiparticles, formed in th

Aytijhya Saha, Nikhil R. Pal

In this paper, we present a novel embedded feature selection method based on a Multi-layer Perceptron (MLP) network and generalize it for group-feature or sensor selection problems, which can control the level of redundancy among the selected features or groups. Additionally, we have generalized the group lasso penalty for feature selection to encompass a me

Sen Guo, Yu-Xiang Huang, Yu-Hao Cui, Yan Han

The optical characteristics of three types of black holes (BHs) surrounded by a thin accretion disk are discussed, namely the Schwarzschild BH, Bardeen BH, and Hayward BH. We calculate the deflection angle of light as it traverses the vicinity of each BH using numerical integration and semi-analytical methods, revealing that both approaches can effectively e

Édouard Bonnet, Julien Duron, John Sylvester, Viktor Zamaraev

A class of graphs admits an adjacency labeling scheme of size $b(n)$, if the vertices in each of its $n$-vertex graphs can be assigned binary strings (called labels) of length $b(n)$ so that the adjacency of two vertices can be determined solely from their labels. We give tight bounds on the size of adjacency labels for every family of monotone (i.e., subgra

Beatrice Polacchi, Francesco Hoch, Giovanni Rodari, Stefano Savo

Quantum state teleportation represents a pillar of quantum information and a milestone on the roadmap towards quantum networks with a large number of nodes. Successful photonic demonstrations of this protocol have been carried out employing different qubit encodings. However, demonstrations in the Fock basis encoding are challenging, due to the impossibility

Andrzej Szczepkowicz, Dmytro Konakhovych, Damian Sniezek, Dylan S. Black

We propose a setup for measuring visible and near-visible internal Smith-Purcell radiation and Cherenkov Diffraction Radiation, based on silica and silicon, and perform quantitative numerical analysis of its radiation efficiency. We calculate the total radiated energy per electron and the spectral distribution of different radiation orders, taking into accou

Slimane Thabet, Romain Fouilland, Mehdi Djellabi, Igor Sokolov

Transformers are increasingly employed for graph data, demonstrating competitive performance in diverse tasks. To incorporate graph information into these models, it is essential to enhance node and edge features with positional encodings. In this work, we propose novel families of positional encodings tailored for graph transformers. These encodings leverag

Jiri Vlasak, Michal Sojka, Zdeněk Hanzálek

Automated parking is a self-driving feature that has been in cars for several years. Parking assistants in currently sold cars fail to park in more complex real-world scenarios and require the driver to move the car to an expected starting position before the assistant is activated. We overcome these limitations by proposing a planning algorithm consisting o

Song He, Yuan Sun, Jiashi Yin

We investigate higher-order corrections to correlators in a general CFT (conformal field theory) with the double-trace $T\bar{T}$ deformation. Standard perturbation theory proves inadequate for this problem due to the intricate stress-tensor flow induced by the deformation. To tackle this challenge, we introduce a novel technique termed the conservation equa

Luca Scalambrin, Andrea Zanella, Xavier Vilajosana

Internet of Things applications have gained widespread recognition for their efficacy in typical scenarios, such as smart cities and smart healthcare. Nonetheless, there exist numerous unconventional situations where IoT technologies have not yet been massively applied, though they can be extremely useful. One of such domains is the underground mining sector

Jian Wang, Yefan Wang, Da-Jiang Zhang

The Higgs boson decay to a massive bottom quark pair provides the dominant contribution to the Higgs boson width. We present an exact result for such a decay induced by the bottom quark Yukawa coupling with next-to-next-to-leading order (NNLO) QCD corrections. We have adopted the canonical differential equations in the calculation and obtained the result in

Benjamin V. Lehmann, Logan Morrison, Stefano Profumo, Nolan Smyth

We study the possibility that dark matter re-enters kinetic equilibrium with a radiation bath after kinetic decoupling, a scenario we dub kinetic recoupling. This naturally occurs, for instance, with certain types of resonantly-enhanced interactions, or as the result of a phase transition. While late kinetic decoupling damps structure on small scales below a

Anchit Srivastava, Andreas Herbst, Mahdi M. Bidhendi, Max Kieker

Measuring transient optical field is pivotal not only for understanding ultrafast phenomena but also for quantitative detection of various molecular species in a sample. In this work, we demonstrate near-petahertz electric field detection of a few femtosecond pulses with 2oo attosecond temporal resolution, 10$^8$ detection dynamic range in electric field and

Fornasiero Antongiulio, Terzo Giuseppina

Let K be an algebraically bounded structure and T be its theory. If T is model complete, then the theory of K endowed with a derivation, denoted by $T^{\delta}$, has a model completion. Additionally, we prove that if the theory T is stable/NIP then the model completion of $T^{\delta}$ is also stable/NIP. Similar results hold for the theory with several deriv

Jialin Gong, Yang Wang, Yilin Han, Zhenxiang Cheng

Recently, the real topology has been attracting widespread interest in two dimensions (2D). Here, based on first-principles calculations and theoretical analysis, we reveal the monolayer Cr$_2$Se$_2$O (ML-CrSeO) as the first material example of a 2D antiferromagnetic (AFM) real Chern insulator (RCI) with topologically protected corner states. Unlike previous

Manuel Esser, Anna Kraut

We consider a stochastic individual-based model of adaptive dynamics for an asexually reproducing population with mutation, with linear birth and death rates, as well as a density-dependent competition. To depict repeating changes of the environment, all of these parameters vary over time as piecewise constant and periodic functions, on an intermediate time-

François HU, Philipp Ratz, Arthur Charpentier

Algorithmic fairness has gained prominence due to societal and regulatory concerns about biases in Machine Learning models. Common group fairness metrics like Equalized Odds for classification or Demographic Parity for both classification and regression are widely used and a host of computationally advantageous post-processing methods have been developed aro

Kotaro Sato

In this paper, the global-in-time $ L^2 $-solvability of the initial-boundary value problem for differential inclusions of doubly-nonlinear type, which arises from fracture mechanics, is proved. This problem is not covered by general existence theories due to the degeneracy and singularity of a dissipation potential along with the nonlinearity of elliptic te

Milad Haghani, Enrico Ronchi

The paper "Simulating dynamical features of escape panic" by Helbing, Farkas, and Vicsek, published over two decades ago in Nature, has left an indelible mark on the field of crowd dynamics. With nearly 3,000 citations to date, according to the Web of Science records, and significant influence, it has shaped the crowd dynamics field. This analysis investigat

Alessandro Ercoli, Vittorio Lubicz

We present an educational proposal which aims to illustrate the elegant, refined and coherent physics contained in Thermodynamics, through a path which assigns to the microscopic description of the physical systems a constantly privileged role. This approach allows to reach a simple and, at the same time, deep understanding of the laws of Thermodynamics, whi

V. Ripepi, G. Catanzaro, E. Trentin, O. Straniero

Anomalous Cepheids (ACEPs) are intermediate mass metal-poor pulsators mostly discovered in dwarf galaxies of the Local Group. However, recent Galactic surveys, including the Gaia DR3, found a few hundreds of ACEPs in the Milky Way. Their origin is not well understood. We aim to investigate the origin and evolution of Galactic ACEPs by studying for the first

Paul C Bressloff

There are a large variety of hybrid stochastic systems that couple a continuous process with some form of stochastic switching mechanism. In many cases the system switches between different discrete internal states according to a finite-state Markov chain, and the continuous dynamics depends on the current internal state. The resulting hybrid stochastic diff

Sunhao Dai, Yuqi Zhou, Liang Pang, Weihao Liu

Recently, the emergence of large language models (LLMs) has revolutionized the paradigm of information retrieval (IR) applications, especially in web search, by generating vast amounts of human-like texts on the Internet. As a result, IR systems in the LLM era are facing a new challenge: the indexed documents are now not only written by human beings but also

Romain Tessera, Matthew Tointon

We show that if $K\ge1$ is a parameter and $S$ is a finite symmetric subset of a group containing the identity such $|S^{2n}|\le K|S^n|$ for some integer $n\ge2K^2$, then $|S^{3n}|\le\exp(\exp(O(K^2)))|S^n|$. Such a result was previously known only under the stronger assumption that $|S^{2n+1}|\le K|S^n|$. We prove similar results for locally compact groups

Tian Liang, Zhiwei He, Jen-tse Huang, Wenxuan Wang

The automatic evaluation of LLM-based agent intelligence is critical in developing advanced LLM-based agents. Although considerable effort has been devoted to developing human-annotated evaluation datasets, such as AlpacaEval, existing techniques are costly, time-consuming, and lack adaptability. In this paper, inspired by the popular language game ``Who is

Alex Meiburg, Jing Chen, Jacob Miller, Raphaëlle Tihon

Beyond their origin in modeling many-body quantum systems, tensor networks have emerged as a promising class of models for solving machine learning problems, notably in unsupervised generative learning. While possessing many desirable features arising from their quantum-inspired nature, tensor network generative models have previously been largely restricted

Rocco Mora

In this article, we continue the analysis started in \cite{CMT23} for the matrix code of quadratic relationships associated with a Goppa code. We provide new sparse and low-rank elements in the matrix code and categorize them according to their shape. Thanks to this description, we prove that the set of rank 2 matrices in the matrix codes associated with squ

Zelin Ni, Hang Yu, Shizhan Liu, Jianguo Li

Bases have become an integral part of modern deep learning-based models for time series forecasting due to their ability to act as feature extractors or future references. To be effective, a basis must be tailored to the specific set of time series data and exhibit distinct correlation with each time series within the set. However, current state-of-the-art m

Stephen Majeski, Matthew W. Kunz

We describe the interaction of parallel-propagating Alfv\'en waves with ion-acoustic waves and other Alfv\'en waves, in magnetized, high-$\beta$ collisionless plasmas. This is accomplished through a combination of analytical theory and numerical fluid simulations of the Chew-Goldberger-Low (CGL) magnetohydrodynamic (MHD) equations closed by Landau-fluid heat

Hui Ma, Jian Wang, Hongfei Lin, Bo Zhang

Emotion recognition in conversations (ERC), the task of recognizing the emotion of each utterance in a conversation, is crucial for building empathetic machines. Existing studies focus mainly on capturing context- and speaker-sensitive dependencies on the textual modality but ignore the significance of multimodal information. Different from emotion recogniti