December 2023 arXiv papers — page 62

Yinhong Liu, Yixuan Su, Ehsan Shareghi, Nigel Collier

Instruction-tuned large language models have shown remarkable performance in aligning generated text with user intentions across various tasks. However, maintaining human-like discourse structure in the generated text remains a challenging research question. In this paper, we propose Instruct-SCTG, a flexible and effective sequential framework that harnesses

Silvia Mura, Dario Tagliaferri, Marouan Mizmizi, Umberto Spagnolini

Integrated Sensing and Communication (ISAC) is one of the key pillars envisioned for 6G wireless systems. ISAC systems combine communication and sensing functionalities over a single waveform, with full resource sharing. In particular, waveform design for legacy Orthogonal Frequency Division Multiplexing (OFDM) systems consists of a suitable time-frequency r

Ziyu Lin, Enzo Tartaglione, Van-Tam Nguyen

On-device training is an emerging approach in machine learning where models are trained on edge devices, aiming to enhance privacy protection and real-time performance. However, edge devices typically possess restricted computational power and resources, making it challenging to perform computationally intensive model training tasks. Consequently, reducing r

D. M. Jezek, P. Capuzzi

We study the nucleation and dynamics of vortices in rotating lattice potentials where weakly linked condensates are formed with each condensate exhibiting an almost axial symmetry. Due to such a symmetry, the on-site phases acquire a linear dependence on the coordinates as a result of the rotation, which allows us to predict the position of vortices along th

Marina Zajnulina, Alessandro Lupo, Serge Massar

We provide a theoretical, numerical, and experimental investigation of the Kerr nonlinearity impact on the performance of a frequency-multiplexed Extreme Learning Machine (ELM). In such ELM, the neuron signals are encoded in the lines of a frequency comb. The Kerr nonlinearity facilitates the randomized neuron connections allowing for efficient information m

Nuofan Qiu, Fang Wan, Chaoyang Song

The robot development process is divided into several stages, which create barriers to the exchange of information between these different stages. We advocate for an interactive lifecycle representation, extending from robot morphology design to learning, and introduce the role of robot description formats in facilitating information transfer throughout this

Andreas Bernig, Jan Kotrbatý, Thomas Wannerer

The algebra of smooth translation-invariant valuations on convex bodies, introduced by S.Alesker in the early 2000s, was in part proved and in part conjectured to satisfy properties formally analogous to those of the cohomology ring of a compact K\"ahler manifold: Poincar\'e duality, the hard Lefschetz theorem, and the Hodge-Riemann relations. Our main resul

Andrei Jaikin-Zapirain, Ismael Morales

Surface groups are known to be the Poincar\'e Duality groups of dimension two since the work of Eckmann, Linnell and M\"uller. We prove a prosolvable analogue of this result that allows us to show that surface groups are profinitely (and prosolvably) rigid among finitely generated groups that satisfy $\mathrm{cd}(G)=2$ and $b_2^{(2)}(G)=0$. We explore two ot

Thong T. Q. Nguyen

In the vicinity of the Milky Way Galactic Center, celestial bodies, including neutron stars, reside within a dense dark matter environment. This study explores the accumulation of dark matter by neutron stars through dark matter-nucleon interactions, leading to increased internal dark matter density. Consequently, dark matter annihilation produces long-lived

Eva Paprotzki, Alexander Osterkorn, Vibhu Mishra, Stefan Kehrein

Charge-density wave phases in quantum materials stem from the complex interplay of electronic and lattice degrees of freedom. Nowadays, various time-resolved spectroscopy techniques allow to actively manipulate such phases and monitor their dynamics in real time. Modeling such nonequilibrium dynamics theoretically is a great challenge and exact methods can u

Muhammad Suffian, Ulrike Kuhl, Jose M. Alonso-Moral, Alessandro Bogliolo

As computational systems supported by artificial intelligence (AI) techniques continue to play an increasingly pivotal role in making high-stakes recommendations and decisions across various domains, the demand for explainable AI (XAI) has grown significantly, extending its impact into cognitive learning research. Providing explanations for novel concepts is

Hao-Fu Zhu, Xufen Wu, Guo-Zhu Liu

Although neutron stars have been studied for decades, their internal structure remains enigmatic, mainly due to large uncertainties in the equation of state. In neutron stars, the nucleons are strongly interacting by exchanging mesons, which can lead to significant quantum many-body correlation effects. Mean-field calculations failed to capture these effects

Padmapani Seneviratne, Hannah Cuff, Alexandra Koletsos, Kerry Seekamp

We use multidimensional circulant approach to construct new qutrit stabilizer $\dsb{\ell, 0, d}$ codes with parameters $(\ell, d) \in \{(51, 16), (52, 16), (54, 17), (55, 17), (57, 17)\}$ through symplectic self-dual additive codes over $\F_9$. In addition to these five new codes, we use bordered construction to derive two more qutrit codes with parameters $

Erik Tjong Kim Sang

We describe the project REE-HDSC and outline our efforts to improve the quality of named entities extracted automatically from texts generated by hand-written text recognition (HTR) software. We describe a six-step processing pipeline and test it by processing 19th and 20th century death certificates from the civil registry of Curacao. We find that the pipel

Ranadeep Daw, Jonathan R. Bradley, Christopher K. Wikle, Scott H. Holan

The criterion for aggregation error (CAGE) is an important metric that aims to measure errors that arise in multiscale (or multi-resolution) spatial data, referred to as the modifiable areal unit problem and the ecological fallacy. Specifically, CAGE is a measure of between scale variance of eigenvectors in a Karhunen-Lo\'{e}ve expansion (KLE), motivated by

F. B. M. dos Santos, G. Rodrigues, J. G. Rodrigues, R. de Souza

Natural inflation is a well-motivated model for the early universe in which an inflaton potential of the pseudo-Nambu-Goldstone form, $V(\phi) = \Lambda^4[1 + \cos{(\phi/f)}]$, can naturally drive a cosmic accelerated epoch. This paper investigates the observational viability of the minimally and non-minimally coupled natural inflation scenarios in light of

Antón Baleato Lizancos, Martin White

It is commonplace in cosmology to analyze fields projected onto the celestial sphere, and in particular density fields that are defined by a set of points e.g. galaxies. When performing an harmonic-space analysis of such data (e.g. an angular power spectrum) using a pixelized map one has to deal with aliasing of small-scale power and pixel window functions.

Sarira Sahu, B. Medina-Carrillo, D. I. Páez-Sánchez, G. Sánchez-Colón

The High Energy Stereoscopic System (H.E.S.S.) started observing the extremely powerful long-duration gamma-ray burst, GRB 221009A, after 53 hours of the triggering event. The H.E.S.S. collaboration carried out observations on the 11, 12, and 17, of October 2022 under poor atmospheric conditions, without detecting significant very high-energy photons from th

Qing Tong, Shubo Wang

Artificial structures have been widely used to manipulate sound fields. Most properties of these structures derive from the material and geometry. Few are explicitly related to the structural topology in the real space. Here, we discover a fundamental connection between the real-space topology of acoustic structures and the topological properties of sound fi

Ulrich Langer, Richard Löscher, Olaf Steinbach, Huidong Yang

We propose, analyze, and test new iterative solvers for large-scale systems of linear algebraic equations arising from the finite element discretization of reduced optimality systems defining the finite element approximations to the solution of elliptic tracking-type distributed optimal control problems with both the standard $L_2$ and the more general energ

Simão da Graça Marto, Massimiliano Vasile, Andrew Campbell, Paul Murray

Spectral lightcurves consisting of time series single-pixel spectral measurements of spacecraft are used to infer the spacecraft's attitude and rotation. Two methods are used. One based on numerical optimisation of a regularised least squares cost function, and another based on machine learning with a neural network model. The aim is to work with minimal inf

Guy Doron, Sam Genway, Mark Roberts, Sai Jasti

The rapid advance of generative AI is reshaping the strategic vision for R&D across industries. The unique challenges of pharmaceutical R&D will see applications of generative AI deliver value along the entire value chain from early discovery to regulatory approval. This perspective reviews these challenges and takes a three-horizon approach to explore the g

Krzysztof J. Ciosmak

We investigate an analogue of the irreducible convex paving in the context of generalised convexity. Consider two Radon probability measures $\mu,\nu$ ordered with respect to a cone $\mathcal{F}$ of functions on $\Omega$ stable under maxima. Under the assumption that any $\mathcal{F}$-transport between $\mu$ and $\nu$ is local, we establish the existence of

Demircan Tas, Rohit Priyadarshi Sanatani

There has been a growing adoption of computer vision tools and technologies in architectural design workflows over the past decade. Notable use cases include point cloud generation, visual content analysis, and spatial awareness for robotic fabrication. Multiple image classification, object detection, and semantic pixel segmentation models have become popula

Harshit Pandey, Soeren Schlichting, Sayantan Sharma

We perform classical-statistical real-time lattice simulations to compute real-time spectral functions and momentum broadening of quarks in the presence of strongly populated non-Abelian gauge fields. Based on a novel methodology to extract the momentum broadening for relativistic quarks, we find that the momentum distribution of quarks exhibit interesting n

Akash Hossain

We give a characterization of forking in regular ordered Abelian groups. In particular, we prove that the type of C over AB does not fork over A if and only if the type over AB of each C-definable singleton does not fork over A in these structures.

Diego Maldonado, Pedro Montealegre, Martín Ríos-Wilson

Finite-State Dynamics (FSD) is one of the simplest and constrained distributed systems. An FSD is defined by an $n$-node network, with each node maintaining an internal state selected from a finite set. At each time-step, these nodes synchronously update their internal states based solely on the states of their neighboring nodes. Rather than focusing on spec

Paul Carter, Arjen Doelman, Annalisa Iuorio, Frits Veerman

Reaction-diffusion models describing interactions between vegetation and water reveal the emergence of several types of patterns and travelling wave solutions corresponding to structures observed in real-life. Increasing their accuracy by also considering the ecological factor known as autotoxicity has lead to more involved models supporting the existence of

Junxiang Wang, Guangji Bai, Wei Cheng, Zhengzhang Chen

Time series domain adaptation stands as a pivotal and intricate challenge with diverse applications, including but not limited to human activity recognition, sleep stage classification, and machine fault diagnosis. Despite the numerous domain adaptation techniques proposed to tackle this complex problem, they primarily focus on domain adaptation from a singl

Ilya Zisman, Vladislav Kurenkov, Alexander Nikulin, Viacheslav Sinii

Recently, extensive studies in Reinforcement Learning have been carried out on the ability of transformers to adapt in-context to various environments and tasks. Current in-context RL methods are limited by their strict requirements for data, which needs to be generated by RL agents or labeled with actions from an optimal policy. In order to address this pre

Peter Kocsis, Vincent Sitzmann, Matthias Nießner

We present Intrinsic Image Diffusion, a generative model for appearance decomposition of indoor scenes. Given a single input view, we sample multiple possible material explanations represented as albedo, roughness, and metallic maps. Appearance decomposition poses a considerable challenge in computer vision due to the inherent ambiguity between lighting and

Chun-Mei Feng, Yang Bai, Tao Luo, Zhen Li

Albeit progress has been made in Composed Image Retrieval (CIR), we empirically find that a certain percentage of failure retrieval results are not consistent with their relative captions. To address this issue, this work provides a Visual Question Answering (VQA) perspective to boost the performance of CIR. The resulting VQA4CIR is a post-processing approac

Samuel Van Stroud, Nikita Pond, Max Hart, Jackson Barr

In high-energy particle collisions, the reconstruction of secondary vertices from heavy-flavour hadron decays is crucial for identifying and studying jets initiated by $b$- or $c$-quarks. Traditional methods, while effective, require extensive manual optimisation and struggle to perform consistently across wide regions of phase space. Meanwhile, recent advan

Lukas Wagner, Stefan Braun, Bernhard Scheichl

The axially symmetric, swirl-free gas dynamics and interlinked motion of a cork stopper provoked by the opening of a champagne bottle are modelled rigorously and studied numerically. The experimental study by Liger-Belair, Cordier \& Georges (Science Advances, 5(9), 2019) animated the present investigation. Inspection analysis justifies the inviscid treatmen

Demircan Tas

Visual design relies on seeing things in different ways, acting on them, and seeing results to act again. Parametric design tools are often not robust to design changes that result from sketching over the visualization of their output. We propose a sketch to 3d workflow as an experiment medium for evaluating neural networks and their latent spaces as a repre

Gloria Araiza-Illan, Luke Meyer, Khiet P. Truong, Deniz Baskent

A practical speech audiometry tool is the digits-in-noise (DIN) test for hearing screening of populations of varying ages and hearing status. The test is usually conducted by a human supervisor (e.g., clinician), who scores the responses spoken by the listener, or online, where a software scores the responses entered by the listener. The test has 24 digit-tr

Sarah A. Flanery, Kamalesh Mohanasundar, Christiana Chamon, Srujan D. Kotikela

With the natural evolution of the web, the need for decentralization has rendered the current centralized education system out of date. The student does not "own" their credentials, as the only way their accomplishments are directly linked to their person and considered valuable is by verification through a stamp of an expensive, prestigious institution. How

Antonin Colot, Yiting Chen, Bertrand Cornelusse, Jorge Cortes

This paper considers the problem of controlling inverter-interfaced distributed energy resources (DERs) in a distribution grid to solve an AC optimal power flow (OPF) problem in real time. The AC OPF includes voltage constraints, and seeks to minimize costs associated with the economic operation, power losses, or the power curtailment from renewables. We dev

Ofer Aharony, Suman Kundu, Tal Sheaffer

Two dimensional gauge theories with charged matter fields are useful toy models for studying gauge theory dynamics, and in particular for studying the duality of large $N$ gauge theories to perturbative string theories. A useful starting point for such studies is the pure Yang-Mills theory, which is exactly solvable. Its $1/N$ expansion was interpreted as a

Peter Constantin, Mihaela Ignatova, Quoc-Hung Nguyen

We prove the existence and uniqueness of global smooth solutions of the critical dissipative SQG equation in bounded domains in $\mathbb R^2$. This solves an open problem. We introduce a new methodology of transforming the single nonlocal nonlinear evolution equation in a bounded domain into an interacting system of extended nonlocal nonlinear evolution equa

Jichang Li, Guanbin Li, Hui Cheng, Zicheng Liao

Federated learning with noisy labels (F-LNL) aims at seeking an optimal server model via collaborative distributed learning by aggregating multiple client models trained with local noisy or clean samples. On the basis of a federated learning framework, recent advances primarily adopt label noise filtering to separate clean samples from noisy ones on each cli

Luke Meyer, Gloria Araiza-Illan, Laura Rachman, Etienne Gaudrain

Underlying mechanisms of speech perception masked by background speakers, a common daily listening condition, are often investigated using various and lengthy psychophysical tests. The presence of a social agent, such as an interactive humanoid NAO robot, may help maintain engagement and attention. However, such robots potentially have limited sound quality

Kai Yang, Junzhi Wang, Keping Qiu, Tianwei Zhang

Deuterated molecules are valuable probes for investigating the evolution and the kinematics in the earliest stages of star formation. In this study, we conduct a comprehensive investigation by performing a single point survey of 101 starless clump candidates, and carrying out on-the-fly (OTF) observations of 11 selected sources, focusing on deuterated molecu

Josef Hanke, Ana Rita Pires

Austin's moving knife procedure was originally introduced to find a consensus division of an interval/circular cake between two agents, each of whom believes that they receive exactly half of the cake. We generalise this in two ways: we consider cakes modelled by graphs, and let the two agents have unequal, arbitrary entitlements. In this setting, we seek a

Beth Bjorkman, Zachary Brennan, Mary Flagg, Johnathan Koch

The power domination problem seeks to determine the minimum number of phasor measurement units (PMUs) needed to monitor an electric power network. We introduce random sensor failure before the power domination process occurs and call this the fragile power domination process. For a given graph, PMU placement, and probability of PMU failure $q$, we study the

Steven Mortier, Amir Hamedpour, Bart Bussmann, Ruth Phoebe Tchana Wandji

Changes in climate can greatly affect the phenology of plants, which can have important feedback effects, such as altering the carbon cycle. These phenological feedback effects are often induced by a shift in the start or end dates of the growing season of plants. The normalized difference vegetation index (NDVI) serves as a straightforward indicator for ass

István Juhász, Jan van Mill

If $X$ is a topological space and $Y$ is any set then we call a family $\mathcal{F}$ of maps from $X$ to $Y$ nowhere constant if for every non-empty open set $U$ in $X$ there is $f \in \mathcal{F}$ with $|f[U]| > 1$, i.e. $f$ is not constant on $U$. We prove the following result that improves several earlier results in the literature. If $X$ is a topological

María Hernández Ruiz, Yintao Ma, Hana Medhat, Chiara Mazzinghi

We demonstrate continuous Pound-Drever-Hall (PDH) nondestructive monitoring of the electron spin polarization of an atomic vapor in a microfabricated vapor cell within an optical resonator. The two-chamber silicon and glass cell contains $^{87}$Rb and 1.3 amagat of N$_{2}$ buffer gas, and is placed within a planar optical resonator formed by two mirrors with

Jiayu Chen, Guosheng Li, Chao Yu, Xinyi Yang

This paper addresses multi-UAV pursuit-evasion, where a group of drones cooperates to capture a fast evader in a confined environment with obstacles. Existing heuristic algorithms, which simplify the pursuit-evasion problem, often lack expressive coordination strategies and struggle to capture the evader in extreme scenarios, such as when the evader moves at

Stefan Boettcher, Paula A. Gago

The process of aging following a hard quench into a glassy state is characterized universally, for a wide class of materials, by logarithmic evolution of state variables and a power-law decay of two-time correlation functions that collapse only for the ratio of those times. This stands in stark contrast with relaxation in equilibrium materials, where time-tr

Demircan Tas, Rohit Priyadarshi Sanatani

Sentiment analysis methods are rapidly being adopted by the field of Urban Design and Planning, for the crowdsourced evaluation of urban environments. However, most models used within this domain are able to identify positive or negative sentiment associated with a textual appraisal as a whole, without inferring information about specific urban aspects conta

Jerome Garnier-Brun, Michael Benzaquen, Jean-Philippe Bouchaud

As a schematic model of the complexity economic agents are confronted with, we introduce the ``SK-game'', a discrete time binary choice model inspired from mean-field spin-glasses. We show that even in a completely static environment, agents are unable to learn collectively-optimal strategies. This is either because the learning process gets trapped in a sub

Jesús Aranda, Sebastián Betancourt, Juan Fco. Díaz, Frank Valencia

We introduce a DeGroot-based model for opinion dynamics in social networks. A community of agents is represented as a weighted directed graph whose edges indicate how much agents influence one another. The model is formalized using labeled transition systems, henceforth called opinion transition systems (OTS), whose states represent the agents' opinions and

Jiaming Liu, Ran Xu, Senqiao Yang, Renrui Zhang

Continual Test-Time Adaptation (CTTA) is proposed to migrate a source pre-trained model to continually changing target distributions, addressing real-world dynamism. Existing CTTA methods mainly rely on entropy minimization or teacher-student pseudo-labeling schemes for knowledge extraction in unlabeled target domains. However, dynamic data distributions cau

Idris Hamoud, Muhammad Abdullah Jamal, Vinkle Srivastav, Didier Mutter

Surgical robotics holds much promise for improving patient safety and clinician experience in the Operating Room (OR). However, it also comes with new challenges, requiring strong team coordination and effective OR management. Automatic detection of surgical activities is a key requirement for developing AI-based intelligent tools to tackle these challenges.

I. Andrade, M. A. Marques, R. Menezes

In this work, we investigate the presence of thick branes modeled by a single scalar field with Born-Infeld-like dynamics. We consider the 4-dimensional metric being Minkowski, de Sitter or anti-de Sitter. We obtain the field equations and the conditions to get a first order formalism compatible with them. To illustrate our procedure, some specific models ar

F. J. Escoto, J. L. Velasco, I. Calvo, M. Landreman

MONKES is a new neoclassical code for the evaluation of monoenergetic transport coefficients in stellarators. By means of a convergence study and benchmarks with other codes, it is shown that MONKES is accurate and efficient. The combination of spectral discretization in spatial and velocity coordinates with block sparsity allows MONKES to compute monoenerge

Fulvio Gesmundo, Hang, Huang, Hal Schenck

We describe the minimal free resolution of the ideal of $2 \times 2$ subpermanents of a $2 \times n$ generic matrix $M$. In contrast to the case of $2 \times 2$ determinants, the $2 \times 2$ permanents define an ideal which is neither prime nor Cohen-Macaulay. We combine work of Laubenbacher-Swanson on the Gr\"obner basis of an ideal of $2 \times 2$ permane

Asbjørn Munk, Ao Ma, Mads Nielsen

The current state-of-the art techniques for image segmentation are often based on U-Net architectures, a U-shaped encoder-decoder networks with skip connections. Despite the powerful performance, the architecture often does not perform well when used on data which has different characteristics than the data it was trained on. Many techniques for improving pe

Chiara Castello

Sidon spaces have been introduced by Bachoc, Serra and Z\'emor as the $q$-analogue of Sidon sets, classical combinatorial objects introduced by Simon Szidon. In 2018 Roth, Raviv and Tamo introduced the notion of $r$-Sidon spaces, as an extension of Sidon spaces, which may be seen as the $q$-analogue of $B_r$-sets, a generalization of classical Sidon sets. Th

Mohamed Elfiatoure, Mohammadali Mohammadi, Hien Quoc Ngo, Peter J. Smith

This paper studies the coexistence between a downlink multiuser massive multi-input-multi-output (MIMO) communication system and MIMO radar. The performance of the massive MIMO system with maximum ratio ($\MR$), zero-forcing ($\ZF$), and protective $\ZF$ ($\PZF$) precoding designs is characterized in terms of spectral efficiency (SE) and by taking the channe

Henrik Lievonen, Timothé Picavet, Jukka Suomela

Balliu et al. (DISC 2020) classified the hardness of solving binary labeling problems with distributed graph algorithms; in these problems the task is to select a subset of edges in a $2$-colored tree in which white nodes of degree $d$ and black nodes of degree $\delta$ have constraints on the number of selected incident edges. They showed that the determini

Guoxing Wang, Tianya Xia, Li Lin Yang, Xiaoping Ye

In this note, we propose a factorization formula for gauge-theory scattering amplitudes up to two loops in the high-energy boosted limit. Our formula extends existing results in the literature by incorporating the contributions from massive loops. We derive the new ingredients in our formula using the method of regions with analytic regulators for the rapidi

Mehran Kazemi, Hamidreza Alvari, Ankit Anand, Jialin Wu

Large language models have shown impressive results for multi-hop mathematical reasoning when the input question is only textual. Many mathematical reasoning problems, however, contain both text and image. With the ever-increasing adoption of vision language models (VLMs), understanding their reasoning abilities for such problems is crucial. In this paper, w

Alex Louat, Matthew D. Watson, Timur K. Kim, Danrui Ni

In continuation of research into RuCl$_3$ and RuBr$_3$ as potential quantum spin liquids, a phase with unique magnetic order characterised by long-range quantum entanglement and fractionalised excitations, the compound RuI$_3$ has been recently synthesised. Here, we show RuI$_3$ is a moderately correlated metal with two bands crossing the Fermi level, implyi

Chuan Liu, Wen Wei Ho

We study the non-equilibrium dynamics of kicked Ising models in $1+1$ dimensions which have interactions alternating between odd and even bonds in time. These models can be understood as quantum circuits tiling space-time with the generalized space-time dual properties of tri-unitarity (three "arrows of time") at the global level, and also second-level dual-

Nicolas Dupré

Let $G$ be the group of rational points of a split connected reductive group over a non-archimedean local field of residue characteristic $p$, and let $\mathcal{H}$ denote the pro-$p$ Iwahori-Hecke algebra of $G$ over a field of characteristic $p$. We study the parabolic induction functor for $\mathcal{H}$-modules in terms of the Gorenstein projective model

Yue Duan, Zhen Zhao, Lei Qi, Luping Zhou

While semi-supervised learning (SSL) has yielded promising results, the more realistic SSL scenario remains to be explored, in which the unlabeled data exhibits extremely high recognition difficulty, e.g., fine-grained visual classification in the context of SSL (SS-FGVC). The increased recognition difficulty on fine-grained unlabeled data spells disaster fo

Xinying Zou, Samir M. Perlaza, Iñaki Esnaola, Eitan Altman

In this paper, the worst-case probability measure over the data is introduced as a tool for characterizing the generalization capabilities of machine learning algorithms. More specifically, the worst-case probability measure is a Gibbs probability measure and the unique solution to the maximization of the expected loss under a relative entropy constraint wit

Aparna Saksena, Ayman El-Zoka, Alaukik Saxena, Ezgi Hatipoglu

For its potential as a catalyst, nanoporous gold (NPG) prepared through dealloying of bulk Ag-Au alloys has been extensively investigated. NPG thin films can offer ease of handling, better tunability of the chemistry and microstructure of the nanoporous structure, and represent a more sustainable usage of scarce resources. These films are however prone to in

Guangzhou Chen, Xiaodong Niu, Jiufeng Shi

Orthogonal array and a large set of orthogonal arrays are important research objects in combinatorial design theory, and they are widely applied to statistics, computer science, coding theory and cryptography. In this paper, some new series of large sets of orthogonal arrays are given by direct construction, juxtaposition construction, Hadamard construction,

Victor Pacheco-Peña, Nader Engheta

Photonic time interfaces, as the temporal analogue of spatial interfaces between two media, consist of a rapid change of the electromagnetic properties of a material (such as permittivity {\epsilon}, and permeability {\mu}) while the wave is present in the material. Here we exploit cascading of such time interfaces in spatially cascaded guided-wave structure

Lingjun Zhang, Xinyuan Chen, Yaohui Wang, Yue Lu

Recently, diffusion-based image generation methods are credited for their remarkable text-to-image generation capabilities, while still facing challenges in accurately generating multilingual scene text images. To tackle this problem, we propose Diff-Text, which is a training-free scene text generation framework for any language. Our model outputs a photo-re

Maxence Cassier, Patrick Joly, Luis Alejandro Rosas Martínez

This work concerns the analysis of electromagnetic dispersive media modelled by generalized Lorentz models. More precisely, this paper is the second of two articles dedicated to the long time behaviour of solutions of Maxwell's equations in dissipative Lorentz media, via the long time decay rate of the electromagnetic energy for the corresponding Cauchy prob

Reza Belbasi, Aras Selvi, Wolfram Wiesemann

Problem definition: A key challenge in supervised learning is data scarcity, which can cause prediction models to overfit to the training data and perform poorly out of sample. A contemporary approach to combat overfitting is offered by distributionally robust problem formulations that consider all data-generating distributions close to the empirical distrib

Gaëtan Borot, Thomas Buc-d'Alché

We establish identities of Pfaffian type for the theta function associated with twice or half the period matrix of a hyperelliptic curve. They are implied by the large size asymptotic analysis of exact Pfaffian identities for expectation values of ratios of characteristic polynomials in ensembles of orthogonal or quaternionic self-dual random matrices. We sh

LHCb collaboration, R. Aaij, A. S. W. Abdelmotteleb, C. Abellan Beteta

The first search for nonresonant $B_c^+\to\pi^+\mu^+\mu^-$ decays is reported. The analysis uses proton-proton collision data collected with the LHCb detector between 2011 and 2018, corresponding to an integrated luminosity of 9 fb$^{-1}$. No evidence for an excess of signal events over background is observed and an upper limit is set on the branching fracti

Gaoge Han, Shaoli Huang, Mingming Gong, Jinglei Tang

We introduce HuTuMotion, an innovative approach for generating natural human motions that navigates latent motion diffusion models by leveraging few-shot human feedback. Unlike existing approaches that sample latent variables from a standard normal prior distribution, our method adapts the prior distribution to better suit the characteristics of the data, as

Satoki Ishikawa, Ryo Karakida

Second-order optimization has been developed to accelerate the training of deep neural networks and it is being applied to increasingly larger-scale models. In this study, towards training on further larger scales, we identify a specific parameterization for second-order optimization that promotes feature learning in a stable manner even if the network width

Hyungjin Kim, Andrea Mitridate

Metric perturbations induced by ultralight dark matter (ULDM) fields have long been identified as a potential target for pulsar timing array (PTA) observations. Previous works have focused on the coherent oscillation of metric perturbations at the characteristic frequency set by the ULDM mass. In this work, we show that ULDM fields source low-frequency stoch

Ricardo A. Pastrán, Oscar Riaño

We study spatial decay properties for solutions of the Pelinovski-Stepanyants equation posed on the cylinder. We establish the maximum polynomial decay admissible for solutions of such a model. It is verified that the equation on the cylinder propagates polynomial weights with different restrictions than the model set in $\mathbb{R}^2$. For example, a local

Alonso Urbano, David W. Romero

Group equivariance can overly constrain models if the symmetries in the group differ from those observed in data. While common methods address this by determining the appropriate level of symmetry at the dataset level, they are limited to supervised settings and ignore scenarios in which multiple levels of symmetry co-exist in the same dataset. In this paper

Junjue Wang, Zhuo Zheng, Zihang Chen, Ailong Ma

Earth vision research typically focuses on extracting geospatial object locations and categories but neglects the exploration of relations between objects and comprehensive reasoning. Based on city planning needs, we develop a multi-modal multi-task VQA dataset (EarthVQA) to advance relational reasoning-based judging, counting, and comprehensive analysis. Th

Xiang-Ke Chang, Jacek Szmigielski

We are exploring variations of the Novikov equation that have weak solutions called peakons. Our focus is on a two-component Novikov equation with a non-self-adjoint $4\times 4$ Lax operator for which we examine the related forward and inverse spectral maps for the peakon sector. To tackle the forward spectral problem, we convert it into a matrix eigenvalue

Are Austad, Jens Kaad, David Kyed

We show how to equip the crossed product between a group of polynomial growth and a compact quantum metric space with a compact quantum metric space structure. When the quantum metric on the base space arises from a spectral triple, which is compatible with the action of the group, we furthermore show that the crossed product becomes a spectral metric space.

Adam Walton, Benjamin T. H. Varcoe

High-precision frequency alignment with classical communication channels is difficult due to noise, propagation delays, and signal degradation. Current optical methods, commonly involving frequency combs, are capable of synchronising clocks with exceptional precision up to the region of a part in 10e20. Alternatively, wireless methods see use where this is n

Lechang Qin, Huiyuan Li, Zhiguo Yang

In this paper, we present exact divergence-free spectral method for solving the incompressible and resistive magneto-hydrodynamic (MHD) equations in two and three dimensions, as well as the efficient solution algorithm and unconditionally energy-stable fully-discretized numerical schemes. We introduce new ideas of constructing two families of exact divergenc

Giovanni Antinozzi, Matteo Martinelli, Roberto Maoli

We present a forecast for the upcoming Einstein Telescope (ET) interferometer with two new methods to infer cosmological parameters. We consider the emission of Gravitational Waves (GWs) from compact binary coalescences, whose electromagnetic counterpart is missing, namely Dark Sirens events. Most of the methods used to infer cosmological information from GW

Tobias Hyrup, Anton Danholt Lautrup, Arthur Zimek, Peter Schneider-Kamp

Data sharing is a necessity for innovative progress in many domains, especially in healthcare. However, the ability to share data is hindered by regulations protecting the privacy of natural persons. Synthetic tabular data provide a promising solution to address data sharing difficulties but does not inherently guarantee privacy. Still, there is a lack of ag

Praveen Manju, Rajendra Kumar Sharma

In this article, we study the derivations of group algebras of some important groups, namely, dihedral ($D_{2n}$), Dicyclic ($T_{4n}$) and Semi-dihedral ($SD_{8n}$). First, we explicitly classify all inner derivations of a group algebra $\mathbb{F}G$ of a finite group $G$ over an arbitrary field $\mathbb{F}$. Then we classify all $\mathbb{F}$-derivations of

Léo Bigorgne

We construct an isometric modified scattering operator, mapping any sufficiently regular past scattering state, with a small distribution function, to the future one corresponding to forward evolution by the Vlasov-Maxwell system. The main part of this work is devoted to the construction of a modified wave operator, which relates the future asymptotic dynami

Sadashige Ishida, Hugo Lavenant

We present a discretization of the dynamic optimal transport problem for which we can obtain the convergence rate for the value of the transport cost to its continuous value when the temporal and spatial stepsize vanish. This convergence result does not require any regularity assumption on the measures, though experiments suggest that the rate is not sharp.

I. V. Vovchenko, A. A. Zyablovsky, A. A. Pukhov, E. S. Andrianov

The dynamics of open quantum systems connected with several reservoirs attract great attention due to its importance in quantum optics, biology, quantum thermodynamics, transport phenomena, etc. In many problems, the Born approximation is applicable which implies that the influence of the open quantum system on the reservoirs can be neglected. However, in th

Huiping Huang, Tianjian Zhang, Feng Yin, Bin Liao

The problem of joint direction-of-arrival estimation and distorted sensor detection has received a lot of attention in recent decades. Most state-of-the-art work formulated such a problem via low-rank and row-sparse decomposition, where the low-rank and row-sparse components were treated in an isolated manner. Such a formulation results in a performance loss

M. Fernandez-Lopez, P. Benaglia, S. Cichowolski, F. S. Correra

The Large Latin American Millimeter Array (LLAMA for short) is a joint scientific and technological undertaking of Argentina and Brazil whose goal is to install and to operate an observing facility capable of performing observations of the Universe at millimeter and sub-millimeter wavelengths. It will consist of a 12m ALMA-like antenna with the addition of t

Theis P. Rasmussen, Álvaro Rodríguez Echarri, Joel D. Cox, F. Javier García de Abajo

Entangled photon pairs are a key resource in future quantum-optical communication and information technologies. While high-power laser light propagating in bulk nonlinear optical crystals is conventionally used to generate entangled photons that are routed into optical configurations, such schemes suffer from low efficiency due to the weak intrinsic nonlinea

Caixia Bu, Liam S. Morrissey, Benjamin C. Bostick, Matthew H. Burger

We have measured the absolute doubly differential angular sputtering yield for 20 keV Kr+ impacting a polycrystalline Cu slab at an incidence angle of {\theta}i = 45{\deg} relative to the surface normal. Sputtered Cu atoms were captured using collectors mounted on a half dome above the sample, and the sputtering distribution was measured as a function of the

Stacey Alberts, Christina C. Williams, Jakob M. Helton, Katherine A. Suess

We present the robust selection of quiescent (QG) and post-starburst (PSB) galaxies using ultra-deep NIRCam and MIRI imaging from the JWST Advanced Deep Extragalactic Survey (JADES). Key to this is MIRI 7.7$\mu$m imaging which breaks the degeneracy between old stellar populations and dust attenuation at $3<z<6$ by providing rest-frame $J$-band. Using this, w

Jie Qiao, Zhengming Chen, Jianhua Yu, Ruichu Cai

Missing data are an unavoidable complication frequently encountered in many causal discovery tasks. When a missing process depends on the missing values themselves (known as self-masking missingness), the recovery of the joint distribution becomes unattainable, and detecting the presence of such self-masking missingness remains a perplexing challenge. Conseq

Fei Pan, Sangryul Jeon, Brian Wang, Frank Mckenna

Existing building recognition methods, exemplified by BRAILS, utilize supervised learning to extract information from satellite and street-view images for classification and segmentation. However, each task module requires human-annotated data, hindering the scalability and robustness to regional variations and annotation imbalances. In response, we propose