December 2023 arXiv papers — page 44

Luca Ratti

Learning-based and data-driven techniques have recently become a subject of primary interest in the field of reconstruction and regularization of inverse problems. Besides the development of novel methods, yielding excellent results in several applications, their theoretical investigation has attracted growing interest, e.g., on the topics of reliability, st

Angel Gómez Nicola, Jacobo Ruiz de Elvira, Andrea Vioque-Rodríguez

We review recent work regarding the role of light scalar resonances at finite temperature for chiral symmetry and $U(1)_A$ restoration. The results obtained are based on unitarized Chiral Perturbation Theory and Ward Identities and are directly connected with presently open problems within the QCD phase diagram

Elizabeth A. Tolman, Matthew W. Kunz, James M. Stone, Lev Arzamasskiy

In high-Lundquist-number plasmas, reconnection proceeds via onset of tearing, followed by a nonlinear phase during which plasmoids continuously form, merge, and are ejected from the current sheet (CS). This process is understood in fully ionized, magnetohydrodynamic plasmas. However, many plasma environments, such as star-forming molecular clouds and the sol

Senqiao Yang, Jiaming Liu, Ray Zhang, Mingjie Pan

Recently, Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) have shown promise in instruction following and 2D image understanding. While these models are powerful, they have not yet been developed to comprehend the more challenging 3D physical scenes, especially when it comes to the sparse outdoor LiDAR data. In this paper, we introd

Matteo Giordano, Alisa Kirichenko, Judith Rousseau

This work studies nonparametric Bayesian estimation of the intensity function of an inhomogeneous Poisson point process in the important case where the intensity depends on covariates, based on the observation of a single realisation of the point pattern over a large area. It is shown how the presence of covariates allows to borrow information from far away

Thorin Bristow, Luke Thorburn, Diana Acosta-Navas

Recent developments in AI have brought broader attention to tensions between two overlapping communities, "AI Ethics" and "AI Safety." In this article we (i) characterize this false binary, (ii) argue that a simple binary is not an accurate model of AI discourse, and (iii) provide concrete suggestions for how individuals can help avoid the emergence of us-vs

Jorge Martín-Pérez, Oscar Amador, Markus Rydeberg, Linnéa Olsson

Road safety is the main motivation for Cooperative Intelligent Transport Systems (C-ITS) in general, and vehicular communications (V2X) technology in particular. The V2X-based Vulnerable Road User (VRU) protection is an approach that relies on the persistent broadcasting of "beacon" awareness messages by a VRU mobile device. To this end the European Telecomm

Robert Bluhm, Yu Zhi

Explicit and spontaneous breaking of spacetime symmetry under diffeomorphisms, local translations, and local Lorentz transformations due to the presence of fixed background fields is examined in Einstein-Cartan theory. In particular, the roles of torsion and violation of local translation invariance are highlighted. The nature of the types of background fiel

I. Plakias, O. Sumensari

In this paper, we perform a comprehensive study of Lepton Flavor Violation (LFV) in semileptonic transitions in the framework of an Effective Field Theory with general flavor structure. We account for the Renormalization Group Equations (RGEs), which induce non-trivial correlations between the different types of LFV processes. In particular, we show that the

Maureen de Seyssel, Antony D'Avirro, Adina Williams, Emmanuel Dupoux

We introduce EmphAssess, a prosodic benchmark designed to evaluate the capability of speech-to-speech models to encode and reproduce prosodic emphasis. We apply this to two tasks: speech resynthesis and speech-to-speech translation. In both cases, the benchmark evaluates the ability of the model to encode emphasis in the speech input and accurately reproduce

Kyle Rockwell, Joel Hirst, Thomas A. Ostler, Ezio Iacocca

Magnetic materials host a wealth of nonlinear dynamics, textures, and topological defects. This is possible due to the competition between strong nonlinearity and dispersion that act at the atomic scale as well as long-range interactions. However, these features are difficult to analytically and numerically study because of the vastly different temporal and

Laura Shou, Amit Vikram, Victor Galitski

Spectral statistics such as the level spacing statistics and spectral form factor (SFF) are widely expected to accurately identify ``ergodicity'', including the presence of underlying macroscopic symmetries, in generic quantum systems ranging from quantized chaotic maps to interacting many-body systems. By studying various quantizations of maximally chaotic

Xiaowei Qian, Bingheng Li, Zhao Kang

Multi-relational clustering is a challenging task due to the fact that diverse semantic information conveyed in multi-layer graphs is difficult to extract and fuse. Recent methods integrate topology structure and node attribute information through graph filtering. However, they often use a low-pass filter without fully considering the correlation among multi

Ognjen Stanisavljević, Jean-Côme Philippe, Julien Gabelli, Marco Aprili

We demonstrate an efficient and continuous microwave photon to electron converter with large quantum efficiency ($83\%$) and low dark current. These unique properties are enabled by the use of a high kinetic inductance disordered superconductor, granular aluminium, to enhance light-matter interaction and the coupling of microwave photons to electron tunnelin

Mahindra Rautela, S. Gopalakrishnan, J. Senthilnath

In this paper, we propose a novel inverse parameter estimation approach called Bayesian optimized physics-informed neural network (BOPINN). In this study, a PINN solves the partial differential equation (PDE), whereas Bayesian optimization (BO) estimates its parameter. The proposed BOPINN estimates wave velocity associated with wave propagation PDE using a s

Sungjin Im, Benjamin Moseley, Hung Q. Ngo, Kirk Pruhs

Datalogo is an extension of Datalog that allows for aggregation and recursion over an arbitrary commutative semiring. Like Datalog, Datalogo programs can be evaluated via the natural iterative algorithm until a fixed point is reached. However unlike Datalog, the natural iterative evaluation of some Datalogo programs over some semirings may not converge. It i

Bin Wang, Zhen Miao, Yaolin Jiang

In this paper, we formulate and analyse a geometric low-regularity integrator for solving the nonlinear Klein-Gordon equation in the $d$-dimensional space with $d=1,2,3$. The integrator is constructed based on the two-step trigonometric method and thus it has a simple form. Error estimates are rigorously presented to show that the integrator can achieve seco

Andrew Kresch, Yuri Tschinkel

We investigate the birational geometry of Deligne-Mumford stacks and define new birational invariants in this context.

Shouzhen Gu, Alex Retzker, Aleksander Kubica

The overhead of quantum error correction (QEC) poses a major bottleneck for realizing fault-tolerant computation. To reduce this overhead, we exploit the idea of erasure qubits, relying on an efficient conversion of the dominant noise into erasures at known locations. We start by introducing a formalism for QEC schemes with erasure qubits and express the cor

Oscar Amador, Erik Ronelöv, Katarina Boustedt, Jesper Blidkvist

The use of reactive detection technologies such as passive and active sensors for avoiding car accidents involving pedestrians and other Vulnerable Road Users (VRU) is one of the cornerstones of Cooperative, Connected, and Automated Mobility (CCAM). However, CCAM systems are not yet present in all roads at all times. The use of currently available technologi

Asmae Benhemou, Georgia Nixon, Aydin Deger, Ulrich Schneider

In the curved spacetime of a black hole, quantum physics gives rise to distinctive effects such as Hawking radiation and maximally fast scrambling. Here, we present a scheme for an analogue quantum simulation of (1 + 1) and (2 + 1)-dimensional black holes using ultracold atoms in a locally Floquet-driven optical lattice. We show how the effective dynamics of

Anthony Nouy, Bertrand Michel

We consider the problem of approximating a function from $L^2$ by an element of a given $m$-dimensional space $V_m$, associated with some feature map $\boldsymbol{\varphi}$, using evaluations of the function at random points $x_1, \dots,x_n$. After recalling some results on optimal weighted least-squares using independent and identically distributed points,

Marion Zannese, Benoît Tabone, Emilie Habart, Javier R. Goicoechea

Water is a key ingredient for the emergence of life as we know it. Yet, its destruction and reformation in space remains unprobed in warm gas. Here, we detect the hydroxyl radical (OH) emission from a planet-forming disk exposed to external far-ultraviolet (FUV) radiation with the James Webb Space Telescope. The observations are confronted with the results o

Zeqian Li, Qirui Chen, Tengda Han, Ya Zhang

In this paper, we aim to establish an automatic, scalable pipeline for denoising the large-scale instructional dataset and construct a high-quality video-text dataset with multiple descriptive steps supervision, named HowToStep. We make the following contributions: (i) improving the quality of sentences in dataset by upgrading ASR systems to reduce errors fr

Marten Richter

Monolayers of transition metal dichalcogenides (TMDC) became one of the most studied nanostructures in the last decade. Combining two different TMDC monolayers results in a heterostructure whose properties can be individually tuned by the twist angle between the lattices of the two van-der-Waals layers and the relative placement of the layers, leading to Moi

Rasha Alshawi, Md Tamjidul Hoque, Md Meftahul Ferdaus, Mahdi Abdelguerfi

The proposed architecture, Dual Attentive U-Net with Feature Infusion (DAU-FI Net), addresses challenges in semantic segmentation, particularly on multiclass imbalanced datasets with limited samples. DAU-FI Net integrates multiscale spatial-channel attention mechanisms and feature injection to enhance precision in object localization. The core employs a mult

Giorgio Arcadi, Juan Carlos Criado, Abdelhak Djouadi

We reanalyze the effective field theory (EFT) approach for the scenario in which the particles that account for the dark matter (DM) in the universe are vector states that interact only through the Standard Model-like Higgs boson. These DM particles are searched for in direct and indirect detection in astrophysical experiments and in invisible Higgs decays a

Axel Klawonn, Martin Lanser, Janine Weber

Hybrid algorithms, which combine black-box machine learning methods with experience from traditional numerical methods and domain expertise from diverse application areas, are progressively gaining importance in scientific machine learning and various industrial domains, especially in computational science and engineering. In the present survey, several prom

Simon Muntwiler, Johannes Köhler, Melanie N. Zeilinger

In this paper, we study joint state and parameter estimation for general nonlinear systems with uncertain parameters and persistent process and measurement noise. In particular, we are interested in stability properties of the resulting state estimate in the absence of persistency of excitation (PE). With a simple academic example, we show that existing movi

Kai Huang, Wei Gao

With the wide adoption of AI applications, there is a pressing need of enabling real-time neural network (NN) inference on small embedded devices, but deploying NNs and achieving high performance of NN inference on these small devices is challenging due to their extremely weak capabilities. Although NN partitioning and offloading can contribute to such deplo

Jean-Luc Lehners, K. S. Stelle

General relativity allows for inhomogeneous and anisotropic universes with finite action. By contrast, in quadratic gravity such solutions obtain infinite action and are thus eliminated. What remains are homogeneous and isotropic solutions undergoing accelerated expansion, thereby automatically inducing an early inflationary phase. In this manner, semi-class

Eric Cereceda-Lóopez, Mattia Ostinato, Antonio Ortiz-Ambriz, Arthur V. Straube

In our combined experimental, theoretical and numerical work, we study the out of equilibrium deformations in a shrinking ring of optically trapped, interacting colloidal particles. Steerable optical tweezers are used to confine dielectric microparticles along a circle of discrete harmonic potential wells, and to reduce the ring radius at a controlled quench

Carolyn A. Raithel, Vasileios Paschalidis

Observations of the high-frequency gravitational waves (GWs) emitted by the hot and massive remnant of a binary neutron star merger will provide new probes of the dense-matter equation of state (EoS). We show that current uncertainties in the thermal physics can cause the emergent GW spectum to differ by a degree comparable to changing the cold EoS by $\pm\s

Alex C. Hollenbeck, Ramana Grandhi, John H. Hansen, Alexander M. Pankonien

Arrays of bioinspired artificial hair-cell airflow velocity sensors can enable flight-by-feel of small, unmanned aircraft. Natural fliers - bats, insects, and birds - have hundred or thousands of velocity sensors distributed across their wings. Aircraft designers do not have this luxury due to size, weight, and power constraints. The challenge is to identify

J. Ma, H. M. Schmid, T. Stolker

Ground-based high-contrast instruments have yielded reflected light images of protoplanetary disks. Quantitative measurements of the reflected radiation provide strong constraints on the scattering dust which can clarify the dust particle evolution in these disks and the composition of the forming planets. This study aimed to derive the wavelength dependence

Roberto Daluiso, Marco Pinciroli, Michele Trapletti, Edoardo Vittori

This work studies the dynamic risk management of the risk-neutral value of the potential credit losses on a portfolio of derivatives. Sensitivities-based hedging of such liability is sub-optimal because of bid-ask costs, pricing models which cannot be completely realistic, and a discontinuity at default time. We leverage recent advances on risk-averse Reinfo

Tristan da Câmara Santa Clara Gomes, Nicolas Marchal, Anatole Moureaux, Simon de Wergifosse

Three-dimensional interconnected nanowire networks have recently attracted notable attention for the fabrication of new devices for energy harvesting/storage, sensing, catalysis, magnetic and spintronic applications and for the design of new hardware neuromorphic computing architectures. However, the complex branching of these nanowire networks makes it chal

Amr Tamimi, Martin Caldarola, Sebastian Hambura, Juan C. Boffi

Two-photon microscopy (2PM) has become an important tool in biology to study the structure and function of intact tissues in-vivo. However, adult mammalian tissues such as the mouse brain are highly scattering, thereby putting fundamental limits on the achievable imaging depth, which typically resides around 600-800um. In principle, shifting both the excitat

Li Hu, Rong-Gen Cai, Shao-Jiang Wang

Recent detections of a low-frequency gravitational wave background (GWB) from various pulsar-timing-array (PTA) observations have renewed the interest in the inspiraling supermassive black hole binaries (SMBHBs), whose population is believed to be the most promising candidate with possible generalizations from including either orbital eccentricity or dark ma

Kai Huang, Boyuan Yang, Wei Gao

On-device training is essential for neural networks (NNs) to continuously adapt to new online data, but can be time-consuming due to the device's limited computing power. To speed up on-device training, existing schemes select trainable NN portion offline or conduct unrecoverable selection at runtime, but the evolution of trainable NN portion is constrained

Lucas Gautheron

How do scientists navigate between the need to capitalize on their prior knowledge through specialization, and the urge to adapt to evolving research opportunities? Drawing from diverse perspectives on adaptation, including cultural evolution, this paper proposes an unsupervised Bayesian approach motivated by Optimal Transport of the evolution of scientists'

M. Strumik, M. Bzowski, M. A. Kubiak

We present a study of the influence of solar UV anisotropy on the heliospheric backscatter helioglow generated by resonant scattering of solar Lyman-alpha photons on interstellar hydrogen atoms around the Sun. Simulations based on the WawHelioGlow model suggest that the response of the helioglow pole-to-ecliptic ratio to the anisotropy is linear, but 15% of

Hou-Wan Long, Xiongfei Zhao, Yain-Whar Si

Decentralized Finance (DeFi), propelled by Blockchain technology, has revolutionized traditional financial systems, improving transparency, reducing costs, and fostering financial inclusion. However, transaction activities in these systems fluctuate significantly and the throughput can be effected. To address this issue, we propose a Dynamic Mining Interval

Yikun Ban, Yunzhe Qi, Jingrui He

In the dynamic landscape of online businesses, recommender systems are pivotal in enhancing user experiences. While traditional approaches have relied on static supervised learning, the quest for adaptive, user-centric recommendations has led to the emergence of the formulation of contextual bandits. This tutorial investigates the contextual bandits as a pow

Kelvin L Walls, Iran R Roman, Bea Steers, Elena Georgieva

Pitch variability in rap vocals is overlooked in favor of the genre's uniquely dynamic rhythmic properties. We present an analysis of fundamental frequency (F0) variation in rap vocals over the past 14 years, focusing on song examples that represent the state of modern rap music. Our analysis aims at identifying meaningful trends over time, and is in turn a

TaeYoung Kim, Gyuhyeon Pak, Euntai Kim

Targetless IMU-LiDAR extrinsic calibration methods are gaining significant attention as the importance of the IMU-LiDAR fusion system increases. Notably, existing calibration methods derive calibration parameters under the assumption that the methods require full motion in all axes. When IMU and LiDAR are mounted on a ground robot the motion of which is rest

P. Belardinelli, W. Yang, A. Bachtold, M. I. Dykman

We demonstrate that a quiet state and large-amplitude self-sustained oscillations can co-exist in a carbon nanotube subject to time-independent drive. A feature of the bistability is that it would be hysteresis-free in the absence of noise and the oscillatory state would not be seen. It is revealed by random switching between the stable states, which we obse

Zehui Chen, Weihua Du, Wenwei Zhang, Kuikun Liu

Large language models (LLM) have achieved remarkable performance on various NLP tasks and are augmented by tools for broader applications. Yet, how to evaluate and analyze the tool-utilization capability of LLMs is still under-explored. In contrast to previous works that evaluate models holistically, we comprehensively decompose the tool utilization into mul

Julian Brüggemann

In this work, we introduce a combinatorial-geometric model for the space of discrete Morse functions on any CW complex $X$. We relate this version of a space of discrete Morse functions to the space of cellular filtrations of $X$ and discuss its relationship to various concepts such as smooth Morse theory, Cerf theory, complexes of discrete Morse matchings,

Ben Hoare, Ana L. Retore, Fiona K. Seibold

With the aim of investigating the existence of an integrable elliptic deformation of strings on $\mathsf{AdS}_3 \times \mathsf{S}^3 \times \mathsf{T}^4$, we compute the tree-level worldsheet S-matrix of the elliptically-deformed bosonic sigma model on $\mathsf{AdS}_3 \times \mathsf{S}^3$ in uniform light-cone gauge. The resulting tree-level S-matrix is compa

Fatemeh Hashemniya, Benoït Caillaud, Erik Frisk, Mattias Krysander

Multi-mode systems can operate in different modes, leading to large numbers of different dynamics. Consequently, applying traditional structural diagnostics to such systems is often untractable. To address this challenge, we present a multi-mode diagnostics algorithm that relies on a multi-mode extension of the Dulmage-Mendelsohn decomposition. We introduce

António Pedro Branco, Cátia Vaz, Alexandre P. Francisco

There are several tools available to infer phylogenetic trees, which depict the evolutionary relationships among biological entities such as viral and bacterial strains in infectious outbreaks, or cancerous cells in tumor progression trees. These tools rely on several inference methods available to produce phylogenetic trees, with resulting trees not being u

Muhammad Imran, Gábor Ivanyos

The semidirect discrete logarithm problem (SDLP) is the following analogue of the standard discrete logarithm problem in the semidirect product semigroup $G\rtimes \mathrm{End}(G)$ for a finite semigroup $G$. Given $g\in G, \sigma\in \mathrm{End}(G)$, and $h=\prod_{i=0}^{t-1}\sigma^i(g)$ for some integer $t$, the SDLP$(G,\sigma)$, for $g$ and $h$, asks to de

Sebastian Bieringer, Gregor Kasieczka, Maximilian F. Steffen, Mathias Trabs

Uncertainty estimation is a key issue when considering the application of deep neural network methods in science and engineering. In this work, we introduce a novel algorithm that quantifies epistemic uncertainty via Monte Carlo sampling from a tempered posterior distribution. It combines the well established Metropolis Adjusted Langevin Algorithm (MALA) wit

Niklas Cichutek, Andreas Rückriegel, Peter Kopietz

Using a functional renormalization group approach we derive the renormalization group (RG) flow of a dissipative variant of the Yukawa-Sachdev-Ye-Kitaev model describing $N$ fermions on a quantum dot which interact via a disorder-induced Yukawa coupling with $M$ bosons. The inverse Euclidean propagator of the bosons is assumed to exhibit a non-analytic term

Marc Bourdon, Bertrand Rémy

We initiate the investigation of critical exponents (in degree equal to the rank) for the vanishing of L^p-cohomology of higher rank Lie groups and related manifolds. We deal with the rank 2 case and exhibit such phenomena for SL$_3$(R) and for a family of 5-dimensional solvable Lie groups. This leads us to exhibit a continuum of quasi-isometry classes of ra

Riccardo Marin, Enric Corona, Gerard Pons-Moll

Aligning a template to 3D human point clouds is a long-standing problem crucial for tasks like animation, reconstruction, and enabling supervised learning pipelines. Recent data-driven methods leverage predicted surface correspondences. However, they are not robust to varied poses, identities, or noise. In contrast, industrial solutions often rely on expensi

Yakov Shalunov

Efficient derandomization has long been a goal in complexity theory, and a major recent result by Yanyi Liu and Rafael Pass identifies a new class of hardness assumption under which it is possible to perform time-bounded derandomization efficiently: that of ''leakage-resilient hardness.'' They identify a specific form of this assumption which is $\textit{equ

Chun Y. Leung, Dganit Meidan, Alessandro Romito

Monitored quantum systems undergo Measurement-induced Phase Transitions (MiPTs) stemming from the interplay between measurements and unitary dynamics. When the detector readout is post-selected to match a given value, the dynamics is generated by a Non-Hermitian Hamiltonian with MiPTs characterized by different universal features. Here, we derive a partial p

Davide Berghi, Philip J. B. Jackson

Conventional audio-visual approaches for active speaker detection (ASD) typically rely on visually pre-extracted face tracks and the corresponding single-channel audio to find the speaker in a video. Therefore, they tend to fail every time the face of the speaker is not visible. We demonstrate that a simple audio convolutional recurrent neural network (CRNN)

Md Gulzar Hussain, Mahmuda Rahman, Babe Sultana, Ye Shiren

In the field of audio and speech analysis, the ability to identify emotions from acoustic signals is essential. Human-computer interaction (HCI) and behavioural analysis are only a few of the many areas where the capacity to distinguish emotions from speech signals has an extensive range of applications. Here, we are introducing BanSpEmo, a corpus of emotion

Paolo Zanardi

We introduce an elementary measure of non-commutativity between two algebras of quantum operators acting on the same Hilbert space. This quantity, which we call Mutual Averaged Non-commutativity (MAN), is a simple generalization of a type of averaged Out-of-Time-Order-Correlators used in the study of quantum scrambling and chaos. MAN is defined by a Haar ave

Zhenqiao Cheng, Nanxi Li, Jianchi Zhu, Xiaoming She

A pioneering secure transmission scheme is proposed, which harnesses movable antennas (MAs) to optimize antenna positions for augmenting the physical layer security. Particularly, an MA-enabled secure wireless system is considered, where a multi-antenna transmitter communicates with a single-antenna receiver in the presence of an eavesdropper. The beamformer

V. Cuomo, L. Morelli, J. A. L. Aguerri, E. M. Corsini

Dwarf barred galaxies are the perfect candidates for hosting slowly-rotating bars. They are common in dense environments and they have a relatively shallow potential well, making them prone to heating by interactions. When an interaction induces bar formation, the bar should rotate slowly. They reside in massive and centrally-concentrated dark matter halos,

Liyi Zhang, R. Thomas McCoy, Theodore R. Sumers, Jian-Qiao Zhu

Large language models (LLMs) can produce long, coherent passages of text, suggesting that LLMs, although trained on next-word prediction, must represent the latent structure that characterizes a document. Prior work has found that internal representations of LLMs encode one aspect of latent structure, namely syntax; here we investigate a complementary aspect

Volodymyr Gorkavenko, Brij Jashal, Valerii Kholoimov, Yehor Kyselov

For years, it has been believed that the main LHC detectors can only restrictively play the role of a lifetime frontier experiment exploring the parameter space of long-lived particles (LLPs) - hypothetical particles with tiny couplings to the Standard Model. This paper demonstrates that the LHCb experiment may become a powerful lifetime frontier experiment

Joey Huston, Klaus Rabbertz, Giulia Zanderighi

This article is part of the "Review of Particle Physics" by the Particle Data Group and reviews the current status of quantum chromodynamics and the strong coupling constant $\alpha_s$. The latest updates as of August 2023 are included.

Ankit Sharma, Animesh Datta, Uttam Singisetti

In this work, the Effective Phonon Dispersion of $\beta$- (Al$_x$Ga$_{1-x}$)$_2$O$_3$ alloy is investigated using the Phonon unfolding formalism. To capture the true randomness of the system, supercells are designed using the technique of special quasirandom structues. The phonon unfolding technique is then used to obtain the effective phonon dispersion (EPD

Sakie J. Arachchige, Xinyuan Chen, Qian M. Zhou

We propose a two-stage estimation procedure for a copula-based model with semi-competing risks data, where the non-terminal event is subject to dependent censoring by the terminal event, and both events are subject to independent censoring. With a copula-based model, the marginal survival functions of individual event times are specified by semiparametric tr

Chen Yang, Tianyu Shi

In this paper, we introduce a novel approach to trajectory generation for autonomous driving, combining the strengths of Diffusion models and Transformers. First, we use the historical trajectory data for efficient preprocessing and generate action latent using a diffusion model with DiT(Diffusion with Transformers) Blocks to increase scene diversity and sto

Yao Ma

The method of regions, which provides a systematic approach for computing Feynman integrals involving multiple kinematic scales, proposes that a Feynman integral can be approximated and even reproduced by summing over integrals expanded in certain regions. A modern perspective of the method of regions considers any given Feynman integral as a specific Newton

M. A. Wolfe, Brighton X. Coe, Justin S. Edwards, Tyler J. Kovach

Optical illumination of quantum-dot qubit devices at cryogenic temperatures, while not well studied, is often used to recover operating conditions after undesired shocking events or charge injection. Here, we demonstrate systematic threshold voltage shifts in a dopant-free, Si/SiGe field effect transistor using a near infrared (780 nm) laser diode. We find t

Lukas Müller, Christoph Schweigert, Lukas Woike, Yang Yang

The Levin-Wen string-nets of a spherical fusion category $\mathcal{C}$ describe, by results of Kirillov and Bartlett, the representations of mapping class groups of closed surfaces obtained from the Turaev-Viro construction applied to $\mathcal{C}$. We provide a far-reaching generalization of this statement to arbitrary pivotal finite tensor categories, incl

A. Tkachenko, K. Pavlovski, N. Serebriakova, D. M. Bowman

Abridged. Eclipsing spectroscopic double-lined binaries are the prime source of precise and accurate measurements of masses and radii of stars. These measurements provide a stringent test of models of stellar evolution that are persistently reported to contain major shortcomings. The mass discrepancy observed for the eclipsing spectroscopic double-lined bina

Tommaso Maria Botta, Ben Davison

Let $Q$ be an arbitrary finite quiver. We use nonabelian stable envelopes to relate representations of the Maulik-Okounkov Lie algebra $\mathfrak{g}^{MO}_Q$ to representations of the BPS Lie algebra associated to the tripled quiver $\tilde Q$ with its canonical potential. We use this comparison to provide an isomorphism between the Maulik-Okounkov Lie algebr

Frederik Møller, Federica Cataldini, Jörg Schmiedmayer

In the hydrodynamics of integrable models, diffusion is a subleading correction to ballistic propagation. Here we quantify the diffusive contribution for one-dimensional Bose gases and find it most influential in the crossover between the main thermodynamic regimes of the gas. Analysing the experimentally measured dynamics of a single density mode, we find d

Francesco Lancellotti, Stephan Welte, Matteo Simoni, Carmelo Mordini

We demonstrate low-excitation transport and separation of two-ion crystals consisting of one beryllium and one calcium ion, with a high mass ratio of $4.4$. The full separation involves transport of the mixed-species chain, splitting each ion into separate potential wells, and then transport of each ion prior to detection. We find the high mass ratio makes t

Aurian Quelennec, Michel Olvera, Geoffroy Peeters, Slim Essid

Current state-of-the-art audio analysis systems rely on pre-trained embedding models, often used off-the-shelf as (frozen) feature extractors. Choosing the best one for a set of tasks is the subject of many recent publications. However, one aspect often overlooked in these works is the influence of the duration of audio input considered to extract an embeddi

S P Fitzgerald, T J W Honour

Transition probabilities for stochastic systems can be expressed in terms of a functional integral over paths taken by the system. Evaluating the integral by the saddle point method in the weak-noise limit leads to a remarkable mapping between dominant stochastic paths and conservative, Hamiltonian mechanics in an effective potential. The conserved ``energy'

Riccardo Barbieri, Gino Isidori

We construct two concrete examples of flavour non-universal gauge theories which, after the inclusion of all $d\leq 4$ gauge invariant operators, allow to describe the observed pattern of flavour in the charged fermion sector without any small Yukawa coupling ($y \gtrsim 0.1$). Guided by the criterium of minimality, we assume that flavour non universality is

Jayita Lahiri, Subhaditya Bhattacharya, Purusottam Ghosh, Biswarup Mukhopadhyaya

We investigate ways of identifying two kinds of dark matter (DM) component particles at high-energy colliders. The strategy is to notice and distinguish double-peaks(humps) in the missing energy/transverse energy distribution. The relative advantage of looking for {\em missing energy} is pointed out, in view of the fact that the longitudinal component of the

Debasmita Maiti, Sing-Hong Chan, Pochung Chen

We benchmark recently proposed tensor network based finite-size scaling analysis in Phys. Rev. B {\bf 107}, 205123 (2023) against two-dimensional classical 3-state clock model. Due to the higher complexity of the model, more complicated crossover behavior is observed. We advocate that the crossover behavior can be understood from the perspective of finite bo

Enoch Solomon, Abraham Woubie, Eyael Solomon Emiru

Achieving state-of-the-art results in face verification systems typically hinges on the availability of labeled face training data, a resource that often proves challenging to acquire in substantial quantities. In this research endeavor, we proposed employing Siamese networks for face recognition, eliminating the need for labeled face images. We achieve this

Hany Abdulsamad, Sahel Iqbal, Adrien Corenflos, Simo Särkkä

Stochastic optimal control of dynamical systems is a crucial challenge in sequential decision-making. Recently, control-as-inference approaches have had considerable success, providing a viable risk-sensitive framework to address the exploration-exploitation dilemma. Nonetheless, a majority of these techniques only invoke the inference-control duality to der

Andrey Losev, Vyacheslav Lysov

We generalize the BV formalism for the physical theories on supermanifolds with graded symmetry algebras realized off-shell and on-shell. An application of such generalization to supersymmetric theories allows us to formulate the new classification which refines the usual off-shell/on-shell classification. Our new classification is based on the type of highe

L. Bastianelli, R. Diamanti, E. Colella, V. Mariani Primiani

In this paper we evaluated the performance of a reconfigurable intelligent surface tested with a fifth generation signal provided by a commercial fifth generation base station. We adopted a reverberation chamber as a real life propagating environment. Tests were conducted at the millimeter wave frequency range. This measurement campaign was carried out under

Raffaele Giuseppe Cestari, Filippo Barchi, Riccardo Busetto, Daniele Marazzina

Accurately forecasting the direction of financial returns poses a formidable challenge, given the inherent unpredictability of financial time series. The task becomes even more arduous when applied to cryptocurrency returns, given the chaotic and intricately complex nature of crypto markets. In this study, we present a novel prediction algorithm using limit

Luke Keyte, Mihkel Kama, Ko-Ju Chuang, L. Ilsedore Cleeves

Volatile elements play a crucial role in the formation of planetary systems. Their abundance and distribution in protoplanetary disks provide vital insights into the connection between formation processes and the atmospheric composition of individual planets. Sulfur, being one of the most abundant elements in planet-forming environments, is of great signific

Josep Batle, Tomasz Białecki, Tomasz Rybotycki, Jakub Tworzydło

We investigate the dimensionality of bipartite quantum systems by construction of a device-independent null witness test. This test assesses whether a given bipartite state conforms with the expected quantum dimension, Schmidt number, and distinguishes between real and complex spaces. By employing local measurements on each party, the proposed method aims to

Davi Máximo, Hunter Stufflebeam

We prove that strictly convex 2-spheres, all of whose simple closed geodesics are close in length to 2{\pi}, are C^0 Cheeger-Gromov close to the round sphere.

Ren-Hua Wua, Chen-Yu Wang, Ce Meng, Yan-Qing Ma

We study the mass spectra of hidden-charm tetraquark systems with quantum numbers $(I^G)J^P=(1^+)1^+$ using QCD sum rules. The analysis incorporates the complete next-to-leading order (NLO) contribution to the perturbative QCD part of the operator product expansions, with particular attention to operator mixing effects due to renormalization group evolution.

Victor V. Braguta, Maxim N. Chernodub, Artem A. Roenko

Using first-principle numerical simulations, we find a new spatially inhomogeneous phase in rigidly rotating $N_c = 3$ gluon plasma. This mixed phase simultaneously possesses both confining and deconfining phases in thermal equilibrium. Unexpectedly, the local critical temperature of the phase transition at the rotation axis does not depend on the angular fr

Reuben Markham, Juan M. Espin, Mario Nieto-Hidalgo, Juan E. Tapia

The accurate detection of ID card Presentation Attacks (PA) is becoming increasingly important due to the rising number of online/remote services that require the presentation of digital photographs of ID cards for digital onboarding or authentication. Furthermore, cybercriminals are continuously searching for innovative ways to fool authentication systems t

H. P. Freund, T. Bui, R. L. Ives, T. Habermann

In this paper, we discuss the design and whole-cavity simulation of a Multi-Beam Inductive Output Tube (MBIOT) that uses a 3rd harmonic component to the drive voltage on the grid. High-efficiency inductive output tubes (IOTs) are typically characterized by efficiencies up to 70 - 75%. However, the achievement of efficiencies greater than 80% would substantia

Cristian Axenie, Oliver López-Corona, Michail A. Makridis, Meisam Akbarzadeh

Antifragility characterizes the benefit of a dynamical system derived from the variability in environmental perturbations. Antifragility carries a precise definition that quantifies a system's output response to input variability. Systems may respond poorly to perturbations (fragile) or benefit from perturbations (antifragile). In this manuscript, we review

Tim Gräfnitz, Patrick Luo

We use deformations and mutations of scattering diagrams to show that the coefficients of a scattering diagram with initial functions $f1 = (1+tx)^{\mu}$ and $f2 = (1+ty)^{\nu}$ are polynomial in ${\mu}$, ${\nu}$ and non-trivial in a certain dense region. We discuss consequences for Gromov-Witten invariants and quiver representations.

Guille Carrión Santiago, Antonio Díaz Ramos

We characterize cofibrant objects in the category of functors indexed in a filtered poset and we show that these objects are acyclic. As a consequence, we show that Mackey functors over posets are also acyclic, where we define this type of Mackey functors mimicking the classical notion. As application, we study homotopy colimits over posets and we give a hom

Karma Dajani, Cor Kraaikamp, Slade Sanderson

We revisit Ito's (\cite{I1989}) natural extension of the Farey tent map, which generates all regular continued fraction convergents and mediants of a given irrational. With a slight shift in perspective on the order in which these convergents and mediants arise, this natural extension is shown to provide an elegant and powerful tool in the metric theory of c

Wenbin Hu, Fernando Acero, Eleftherios Triantafyllidis, Zhaocheng Liu

We present a modular framework designed to enable a robot hand-arm system to learn how to catch flying objects, a task that requires fast, reactive, and accurately-timed robot motions. Our framework consists of five core modules: (i) an object state estimator that learns object trajectory prediction, (ii) a catching pose quality network that learns to score

Shan Yin, Haotian Zhong, Wei Huang, Wentao Zhang

Metamaterials open up a new way to manipulate electromagnetic waves and realize various functional devices. Metamaterials with high-quality (Q) resonance responses are widely employed in sensing, detection, and other applications. Traditional design of metamaterials involves laborious simulation-optimization and limits the efficiency. The high-Q metamaterial