arXiv papers from June 2024

Andrea Fedrigucci, Nicola Marzari, Paolo Ricci

Plasma-facing materials (PFMs) represent one of the most significant challenges for the design of future nuclear fusion reactors. Inside the reactor, the divertor will experience the harshest material environment: intense bombardment of neutrons and plasma particles coupled with large and intermittent heat fluxes. The material designated to cover this role i

Najib Khachiaa

Let $H_1$ and $H_2$ be two Hilbert spaces, $K$ and $L$ be bounded operatrors on $H_1$ and $H_2$ respectively. In this paper we study the relationship between $K$-frames for $H_1$ and $L$-frames for $H_2$ and $K\oplus L$-frames for $H_1\oplus H_2$. The $K\oplus L$-minimal frames and $K\oplus L$-orthonormal bases for $H_1\oplus H_2$ are also studied.

Edward Belbruno, James Green

In this note, an interesting region about the Sun in phase space is described where the permanent capture of an object, $P$, of small mass from interstellar space can occur, under the gravitational perturbation of the resultant mass of the Galaxy. $P$ is never ejected back into interstellar space and won't collide with the Sun. It cycles about the Sun for al

MJ Johns, Rita Tesfay, Mário Escarce Junior, Emmanuel Ezenwa

Info Overload is a minigame within a larger collection aimed at increasing awareness and preparation for an evacuation in the event of a wildfire. The game relies on experiential two-player cooperative gameplay and is played on a mobile device (a phone or tablet).

I. M. Suslov

We consider the mutual distribution of two linearly independent solutions y_1(x) and y_2(x) of the 1D Schroedinger equation with a random potential. Since individual distributions of $y_1$ and $y_2$ are log-normal, it is naturally to suggest that their mutual distribution is also log-normal. Such hypothesis is confirmed in the deep of the allowed and forbidd

Lawrence Herman, Christopher Barbarie, Mohan Agrawal, Vlad Calinescu

The development of low-frequency radio astronomy experiments for detecting 21-cm line emission from hydrogen presents new opportunities for creative solutions to the challenge of characterizing an antenna beam pattern. The Array of Long Baseline Antennas for Taking Radio Observations from the Seventy-ninth parallel (ALBATROS) is a new radio interferometer si

Ashim Sen Gupta, Bartolomeo Fiorini, Tessa Baker

The $\texttt{Hi-COLA}$ code is an efficient dark matter simulation suite that flexibly handles the Horndeski family of modified gravity models. In this work we extend the scope of $\texttt{Hi-COLA}$ to accommodate Horndeski theories with K-mouflage screening, allowing for the computation of matter power spectra in the non-linear regime in these models. We ex

Rahul Das, Anil K. Bajaj, Sayan Gupta

This study investigates the nonlinear normal modes (NNMs) of a system comprising of two coupled Duffing oscillators, with one oscillator being grounded and with the coupling being both linear and nonlinear. The study utilizes the eigenfunctions of the Koopman operator and validates their connection with the Shaw-Piere invariant manifold framework for NNMs. F

Edward Belbruno

The geometry of the weak stability boundary region for the planar restricted three-body problem about the secondary mass point has been an open problem. Previous studies have conjectured that it may have a fractal structure. In this paper, this region is studied for infinitely many cycles about the secondary mass point, instead of a finite number studied pre

Andrew Zhu, David P. Tew

We extend the Intrinsic Atomic Orbital (IAO) method for localisation of molecular orbitals to calculate well-localised generalised Wannier functions in crystals using the Pipek--Mezey locality metric. We furthermore present a one-shot diabatic Wannierisation procedure that aligns the phases of the Bloch functions, providing immediate Wannier localisation, wh

Max Muzeau, Joana Frontera-Pons, Chengfang Ren, Jean-Philippe Ovarlez

Due to its all-weather and day-and-night capabilities, Synthetic Aperture Radar imagery is essential for various applications such as disaster management, earth monitoring, change detection and target recognition. However, the scarcity of labeled SAR data limits the performance of most deep learning algorithms. To address this issue, we propose a novel self-

Harold Blum, Yuchen Liu

We construct projective asymptotically good moduli spaces parametrizing boundary polarized CY surface pairs, which are projective slc Calabi-Yau pairs $(X,D)$ such that $D$ is ample and $X$ has dimension two. The moduli space provides a wall crossing between certain KSBA and K-moduli spaces and is the ample model of the Hodge line bundle. In the case of K3 s

Xiao Qian, Utkarsh Gangwal, Shangjia Dong, Rachel Davidson

Household and individual-level sociodemographic data are essential for understanding human-infrastructure interaction and policymaking. However, the Public Use Microdata Sample (PUMS) offers only a sample at the state level, while census tract data only provides the marginal distributions of variables without correlations. Therefore, we need an accurate synt

Jiajun Zhu, Siqi Miao, Rex Ying, Pan Li

The interpretability of machine learning models has gained increasing attention, particularly in scientific domains where high precision and accountability are crucial. This research focuses on distinguishing between two critical data patterns -- sensitive patterns (model-related) and decisive patterns (task-related) -- which are commonly used as model inter

Quynh-Anh Nguyen, Leonid L Rubchinsky

Synchronization of neural activity in the gamma frequency band is associated with various cognitive phenomena. Abnormalities of gamma synchronization may underlie symptoms of several neurological and psychiatric disorders such as schizophrenia and autism spectrum disorder. Properties of neural oscillations in the gamma band depend critically on the synaptic

Qingyan Xiang, Paola Sebastiani, Thomas Perls, Stacy L. Andersen

The issue of "truncation by death" commonly arises in clinical research: subjects may die before their follow-up assessment, resulting in undefined clinical outcomes. To address this issue, we focus on survival-incorporated quantiles -- quantiles of a composite outcome combining death and clinical outcomes -- to summarize the effect of treatment. Using inver

Rahul Kumar Padhy, Aaditya Chandrasekhar

Topology Optimization (TO) holds the promise of designing next-generation compact and efficient photonic components. However, ensuring the optimized designs comply with fabrication constraints imposed by semiconductor foundries remains a challenge. This work presents a TO framework that guarantees designs satisfy fabrication criteria, particularly minimum fe

Yannik Brune, Elena Rozas, Ken West, Kirk Baldwin

In recent years, quantum information science has made significant progress, leading to a multitude of quantum protocols for the most diverse applications. States carrying resources such as quantum coherence are a key component for these protocols. In this study, we optimize the quantum coherence of a nonresonantly excited exciton-polariton condensate of long

Tobias Dott

In this work we investigate Gromov-Hausdorff limits of compact surfaces carrying length metrics. More precisely, we consider the case where all surfaces have the same Euler characteristic. We give a complete description of the limit spaces and study their topological properties. Our investigation builds on the results of a previous work which treats the case

Lorenzo Bonasera, Emilio Carrizosa

Tree ensembles are very popular machine learning models, known for their effectiveness in supervised classification and regression tasks. Their performance derives from aggregating predictions of multiple decision trees, which are renowned for their interpretability properties. However, tree ensemble models do not reliably exhibit interpretable output. Our w

Fan Yang, Shichen Liu, Hao Wang, Heun Jin Lee

Cytoskeletal networks can repair defects to maintain structural integrity. However, the mechanisms and dynamics of defect merging remain poorly understood. Here we report a geometry-tunable merging mechanism in microtubule-motor networks initiated by active crosslinking. We directly generate defects using a light-controlled microtubule-motor system in O-shap

Timothy Nguyen

Transformer based large-language models (LLMs) display extreme proficiency with language yet a precise understanding of how they work remains elusive. One way of demystifying transformer predictions would be to describe how they depend on their context in terms of simple template functions. This paper takes a first step in this direction by considering famil

Martin Callejo, Andrei Mursa, Rémy Vicarini, Emmanuel Klinger

We report on the development and short-term stability characterization of an optical frequency reference based on the spectroscopy of the rubidium two-photon transition at 778 nm in a microfabricated vapor cell. When compared against a 778 nm reference signal extracted from a frequency-doubled cavity-stabilized telecom laser, the short-term stability of the

Zekai Wang, Tieming Liu, Bing Yao

The era of big data has made vast amounts of clinical data readily available, particularly in the form of electronic health records (EHRs), which provides unprecedented opportunities for developing data-driven diagnostic tools to enhance clinical decision making. However, the application of EHRs in data-driven modeling faces challenges such as irregularly sp

Mouadh Yagoubi, David Danan, Milad Leyli-abadi, Jean-Patrick Brunet

The integration of machine learning (ML) techniques for addressing intricate physics problems is increasingly recognized as a promising avenue for expediting simulations. However, assessing ML-derived physical models poses a significant challenge for their adoption within industrial contexts. This competition is designed to promote the development of innovat

Michael Wawrzoniak, Rodrigo Bruno, Ana Klimovic, Gustavo Alonso

Serverless Function-as-a-Service (FaaS) platforms provide applications with resources that are highly elastic, quick to instantiate, accounted at fine granularity, and without the need for explicit runtime resource orchestration. This combination of the core properties underpins the success and popularity of the serverless FaaS paradigm. However, these benef

I. Marini, A. Saro, S. Borgani, M. Boi

Disentangling the stellar population in the central galaxy from the intrahalo light can help us shed light on the formation history of the host halo, as the properties of the stellar components are expected to retain traces of its formation history. Many approaches are adopted, depending on different physical assumptions (e.g. the light profile, chemical com

William Chen, Wangyou Zhang, Yifan Peng, Xinjian Li

Self-supervised learning (SSL) has helped extend speech technologies to more languages by reducing the need for labeled data. However, models are still far from supporting the world's 7000+ languages. We propose XEUS, a Cross-lingual Encoder for Universal Speech, trained on over 1 million hours of data across 4057 languages, extending the language coverage o

Margarita P. Castro, Merve Bodur, Amer Shalaby

The multi-depot vehicle scheduling problem (MDVSP) is a critical planning challenge for transit agencies. We introduce a novel approach to MDVSP by incorporating service reliability through chance-constrained programming (CCP), targeting the pivotal issue of travel time uncertainty and its impact on transit service quality. Our model guarantees service relia

D. Main, P. Drmota, D. P. Nadlinger, E. M. Ainley

Distributed quantum computing (DQC) combines the computing power of multiple networked quantum processing modules, enabling the execution of large quantum circuits without compromising on performance and connectivity. Photonic networks are well-suited as a versatile and reconfigurable interconnect layer for DQC; remote entanglement shared between matter qubi

Weiying Zhao, Natalia Efremova

Continuous monitoring of crops and forecasting crop conditions through time series analysis is crucial for effective agricultural management. This study proposes a framework based on an attention Bidirectional Long Short-Term Memory (BiLSTM) network for predicting multiband images. Our model can forecast target images on user-defined dates, including future

Richard Bass

A draft of a paper by Mandelbaum, "The dynamic complementarity problem", was circulated in 1987, but has never been published. We give an exposition of two important results from that paper which are not readily accessible in the literature. The first is an example of a Skorokhod problem in two dimensions in the quadrant for which there is not uniqueness. Th

Michael Wawrzoniak, Rodrigo Bruno, Ana Klimovic, Gustavo Alonso

Elasticity is a key property of cloud computing. However, elasticity is offered today at the granularity of virtual machines, which take tens of seconds to start. This is insufficient to react to load spikes and sudden failures in latency sensitive applications, leading users to resort to expensive overprovisioning. Function-as-a-Service (FaaS) provides sign

Daniel Álvarez, Marco Gualtieri, Yucong Jiang

A description of the fundamental degrees of freedom underlying generalized K\"ahler geometry, which separates its holomorphic moduli from its compatible Riemannian metric in a similar way to the K\"ahler case, has been sought since its discovery in 1984. In this paper, we describe a full solution to this problem for arbitrary generalized K\"ahler manifolds.

Ogulcan Eryuksel, Kamil Anil Ozfuttu, Fatih Cagatay Akyon, Kadir Sahin

Drone detection is a challenging object detection task where visibility conditions and quality of the images may be unfavorable, and detections might become difficult due to complex backgrounds, small visible objects, and hard to distinguish objects. Both provide high confidence for drone detections, and eliminating false detections requires efficient algori

Ouya Wang, Shenglong Zhou, Geoffrey Ye Li

Stochastic gradient descent-based algorithms are widely used for training deep neural networks but often suffer from slow convergence. To address the challenge, we leverage the framework of the alternating direction method of multipliers (ADMM) to develop a novel data-driven algorithm, called batch ADMM (BADM). The fundamental idea of the proposed algorithm

Nandor Simanyi

In this paper we present an unconditional proof of Wojtkowski's Ergodicity Conjecture for almost every system of 1D perfectly elastic balls falling down in a half line under constant gravitational acceleration. Namely, by introducing a new algebraic approach, we prove that almost every such system is (completely hyperbolic and) ergodic.

C. T. Kelley

We make the interprecision transfers explicit in an algorithmic description of iterative refinement and obtain new insights into the algorithm. One example is the classic variant of iterative refinement where the matrix and the factorization are stored in a working precision and the residual is evaluated in a higher precision. In that case we make the observ

Yuka Ko, Ryo Fukuda, Yuta Nishikawa, Yasumasa Kano

This paper describes NAIST's submission to the simultaneous track of the IWSLT 2024 Evaluation Campaign: English-to-{German, Japanese, Chinese} speech-to-text translation and English-to-Japanese speech-to-speech translation. We develop a multilingual end-to-end speech-to-text translation model combining two pre-trained language models, HuBERT and mBART. We t

Olivér Kürtössy, Mihály Bodócs, Cătălin Paşcu Moca, Zoltán Scherübl

Topological superconductors (SCs) hold great promise for fault-tolerant quantum hardware, however, their experimental realization is very challenging. Recently, superconducting artificial molecules (Andreev molecules) have opened new avenues to engineer topological superconducting materials. In this work, we demonstrate a heteroatomic Andreev molecule, where

Saray Busto, Laura Río-Martín

We present a new hybrid semi-implicit finite volume / finite element numerical scheme for the solution of incompressible and weakly compressible media. From the continuum mechanics model proposed by Godunov, Peshkov and Romenski (GPR), we derive the incompressible GPR formulation as well as a weakly compressible GPR system. As for the original GPR model, the

V. Druskin, S. Moskow, M. Zaslavsky

The Lippmann--Schwinger--Lanczos (LSL) algorithm has recently been shown to provide an efficient tool for imaging and direct inversion of synthetic aperture radar data in multi-scattering environments [17], where the data set is limited to the monostatic, a.k.a. single input/single output (SISO) measurements. The approach is based on constructing data-driven

Florian Effenberg, Klaus Schmid, Federico Nespoli, Alessandro Bortolon

An integrated modeling framework for investigating the application of solid boron powder injection for real-time surface conditioning of plasma-facing components in tokamak environments is presented. Utilizing the DIII-D impurity powder dropper setup, this study simulates B powder injection scenarios ranging from mg/s to tens of mg/s, corresponding to B flux

Hamid Ben Yakkou, Brahim Boudine, Pagdame Tiebekabe

Let $m$ be a rational integer with $m \neq 0, \pm 1$, and consider the pure number field $K = \mathbb{Q}(\sqrt[n]{m})$ with $n \ge 3$. Most papers discussing the monogenity of pure number fields focus exclusively on the case where $m$ is square-free. For every integer $n \ge 4$, the monogenity of number fields of degree $n$ is not completely characterized. F

Ricardo de Deijn, Rajeev Bukralia

This study presents a computer vision approach aimed at detecting snow on sidewalks and pavements to reduce winter-related fall injuries, especially among elderly and visually impaired individuals. Leveraging fine-tuned VGG-19 and ResNet50 convolutional neural networks (CNNs), the research focuses on identifying snow presence in pavement images. The dataset

Tianhao Wei, Hanjiang Hu, Luca Marzari, Kai S. Yun

Deep Neural Networks (DNN) are crucial in approximating nonlinear functions across diverse applications, ranging from image classification to control. Verifying specific input-output properties can be a highly challenging task due to the lack of a single, self-contained framework that allows a complete range of verification types. To this end, we present \te

Supriyo Maji, Hyungjoo Park, Gi moon Hong, Souradip Poddar

In analog circuits, process variation can cause unpredictability in circuit performance. Common-centroid (CC) type layouts have been shown to mitigate process-induced variations and are widely used to match circuit elements. Nevertheless, selecting the most suitable CC topology necessitates careful consideration of important layout constraints. Manual handli

David R. Berman, Lee O. Leonard

Two players play a game by alternately splitting a surface of a compact $2$-manifold along a simple closed curve that is not null-homotopic and attaching disks to the resulting boundary; the last player who can move wins. Starting from an orientable surface, the $G$-series is $01\dot{2}\dot{0}$ according to increasing genus. Starting from a nonorientable sur

G. C. Bento, B. S. Mordukhovich, T. S. Mota, Yu. Nesterov

This paper develops a comprehensive convergence analysis for generic classes of descent algorithms in nonsmooth and nonconvex optimization under several conditions of the Polyak-\L ojasiewicz-Kurdyka (PLK) type. Along other results, we prove the finite termination of generic algorithms under the PLK conditions with lower exponents. Specifications are given t

Tianxiang Du, David E Laughlin, Jian-Gang, Zhu

A near field transducer (NFT) is a key photonics component in heat assisted magnetic recording (HAMR) for the localized heating of the magnetic medium. In this work, we present a novel NFT design through capacitive coupling. In our design, tapered metal bars separated by thin dielectric materials with gap distance G are used to create the plasmonic resonance

Kuanren Qian, Genesis Omana Suarez, Toshihiko Nambara, Takahisa Kanekiyo

Neurodevelopmental disorders (NDDs) have arisen as one of the most prevailing chronic diseases within the US. Often associated with severe adverse impacts on the formation of vital central and peripheral nervous systems during the neurodevelopmental process, NDDs are comprised of a broad spectrum of disorders, such as autism spectrum disorder, attention defi

Matthew T. Dearing, Yiheng Tao, Xingfu Wu, Zhiling Lan

This paper addresses the problem of providing a novel approach to sourcing significant training data for LLMs focused on science and engineering. In particular, a crucial challenge is sourcing parallel scientific codes in the ranges of millions to billions of codes. To tackle this problem, we propose an automated pipeline framework called LASSI, designed to

Fred Matanel Grabovski, Lior Yasur

Recursive Best-First Search (RBFS) is a heuristic search algorithm known for its efficient memory usage compared to traditional best-first search methods like A*. Despite its theoretical advantages, RBFS is complex and difficult to teach and to implement, limiting its widespread adoption. To address these challenges, Iterative Linear Best-First Search (ILBFS

Hong Zhao, Jin Wei-Kocsis, Adel Heidari Akhijahani, Karen L Butler-Purry

Driven by advancements in sensing and computing, deep reinforcement learning (DRL)-based methods have demonstrated significant potential in effectively tackling distribution system restoration (DSR) challenges under uncertain operational scenarios. However, the data-intensive nature of DRL poses obstacles in achieving satisfactory DSR solutions for large-sca

Ori Linial, Guy Tennenholtz, Uri Shalit

In many reinforcement learning (RL) applications one cannot easily let the agent act in the world; this is true for autonomous vehicles, healthcare applications, and even some recommender systems, to name a few examples. Offline RL provides a way to train agents without real-world exploration, but is often faced with biases due to data distribution shifts, l

H. Fleurbaey, S. Kassi, A. Campargue

The hydrogen dimer, (H2)2, is among the most weakly bound van der Waals complexes and a prototype species for first principles ab initio studies. The detection of the (H2)2 infrared absorption spectrum was reported more than thirty years ago at a temperature of 20 K. Due to the sharp decrease of the (H2)2 abundance with temperature, a detection at room tempe

Elliott Thornley, Alexander Roman, Christos Ziakas, Leyton Ho

The POST-Agents Proposal (PAP) is an idea for ensuring that advanced artificial agents never resist shutdown. A key part of the PAP is using a novel `Discounted Reward for Same-Length Trajectories (DReST)' reward function to train agents to (1) pursue goals effectively conditional on each trajectory-length (be `USEFUL'), and (2) choose stochastically between

Muyan Jiang, Ilya M. Spitkovsky

Reciprocal matrices are tridiagonal matrices $(a_{ij})_{i,j=1}^n$ with constant main diagonal and such that $a_{i,i+1}a_{i+1,i}=1$ for $i=1,\ldots,n-1$. For these matrices, criteria are established under which their Kippenhahn curves contain elliptical components or even consist completely of such. These criteria are in terms of system of homogeneous polynom

Agustín Roca, Nicolás Ignacio Britos

Innocence Project is a non-profitable organization that works in reducing wrongful convictions. In collaboration with Laboratorio de Sue\~no y Memoria from Instituto Tecnol\'ogico de Buenos Aires (ITBA), they are studying human memory in the context of face identification. They have a strong hypothesis stating that human memory heavily relies in face's frame

Laura dos Santos Martins, Nicolas Laurent-Puig, Pascal Lefebvre, Simon Neves

Multipartite entangled states are an essential building block for advanced quantum networking applications. Realizing such tasks in practice puts stringent requirements on the characteristics of the states in terms of fidelity and generation rate, along with a desired compatibility with telecommunication network deployment. Here, we demonstrate a photonic pl

Alessio Russo, Alexandre Proutiere

We study the problem of exploration in Reinforcement Learning and present a novel model-free solution. We adopt an information-theoretical viewpoint and start from the instance-specific lower bound of the number of samples that have to be collected to identify a nearly-optimal policy. Deriving this lower bound along with the optimal exploration strategy enta

Mingyi Hou

We establish the boundedness of weak subsolutions for a class of degenerate Kolmogorov equations of hypoelliptic type, compatible with a homogeneous Lie group structure, within bounded product domains using the De Giorgi iteration. We employ the renormalization formula to handle boundary values and provide energy estimates. An $L^1$-$L^p$ type embedding esti

Henrik Finsberg, Verena Charwat, Kevin Healy, Samuel Wall

Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) are an effective tool for studying cardiac function and disease, and hold promise for screening drug effects on human tissue. Changes to motion patterns in these cells are one of the important features to be characterized to understand how an introduced drug or disease may alter the human

Alexander Kochin

The buoyancy force is the cause of ordered vertical movements in the atmosphere, therefore, the analysis of the causes and conditions of its formation is important not only for the formation of convective clouds, but also for understanding all atmospheric transport processes. Due to the absence of rigid boundaries inside the gas, a horizontal pressure gradie

Soutik Ghosal, Zhen Chen

The receiver operating characteristic (ROC) curve is an important graphic tool for evaluating a test in a wide range of disciplines. While useful, an ROC curve can cross the chance line, either by having an S-shape or a hook at the extreme specificity. These non-concave ROC curves are sub-optimal according to decision theory, as there are points that are sup

Barbara Roos

Since Bardeen-Cooper-Schrieffer theory of superconductivity is non-linear, it is difficult to study superconducting properties analytically. There is a more tractable linear criterion which determines a temperature $T_l$ below which the system is superconducting. Here, we observe that there is a similar linear criterion which gives a temperature $T_u$ above

Qing Wang, Ning Hao

The Su-Schrieffer-Heeger (SSH) model is a fundamental lattice model used to study topological physics. Here, we propose a new versatile one-dimensional (1D) lattice model that extends beyond the SSH model. Our 1D model breaks chiral symmetry and has generalized topology characterized by a projected winding number $W_{1D,P}=1$. When this model is extended to

Angela Pistoia, Delia Schiera

We consider the Hamiltonian system with Neumann boundary conditions: \[ -\Delta u + \mu u=v^{q }, \quad -\Delta v+ \mu v=u^{p} \quad \text{ in $\Omega$}, \qquad u, v >0 \quad \text{ in $\Omega$,} \qquad \partial_\nu u= \partial_\nu v=0 \quad \text{ on $\partial \Omega$, } \] where $\mu >0$ is a parameter and $\Omega$ is a smooth bounded domain in $\mathbb R^

Felix Hermann, Adrián Gonzalez Casanova, Renato Soares dos Santos, András Tóbiás

We consider a population whose size $N$ is fixed over the generations, and in which random beneficial mutations arrive at a rate of order $1/\log N$ per generation. In this so-called Gerrish--Lenski regime, typically a finite number of contending mutations are present together with one resident type. These mutations compete for fixation, a phenomenon address

Nikos Barakitis, Valerio Loi, Stefano Serra-Capizzano

Here, we consider a more general class of matrix-sequences and we prove that they belong to the maximal $*$-algebra of generalized locally Toeplitz (GLT) matrix-sequences. Then, we identify the associated GLT symbols and GLT momentary symbols in the general setting and in the specific case, by providing in both cases a spectral and singular value analysis. M

Finn Lindgren, Fabian Bachl, Janine Illian, Man Ho Suen

The integrated nested Laplace approximation (INLA) method has become a popular approach for computationally efficient approximate Bayesian computation. In particular, by leveraging sparsity in random effect precision matrices, INLA is commonly used in spatial and spatio-temporal applications. However, the speed of INLA comes at the cost of restricting the us

Gijs Heuts, Markus Land

We study the loop and suspension functors on the category of augmented $\mathbb{E}_n$-algebras. One application is to the formality of the cochain algebra of the $n$-sphere. We show that it is formal as an $\mathbb{E}_n$-algebra, also with coefficients in general commutative ring spectra, but rarely $\mathbb{E}_{n+1}$-formal unless the coefficients are ratio

Shrinit Singh

In this work, we explore the following question: If two words in a finitely generated free group have identical images as word maps on every finite group, must they be endomorphic to each other? In this regard, we introduce weak profinite rigidity for words, a parallel to profinite rigidity, as defined in \cite{hanany2020some}. We establish that the powers o

Haofan Wang, Peng Xing, Renyuan Huang, Hao Ai

Style transfer is an inventive process designed to create an image that maintains the essence of the original while embracing the visual style of another. Although diffusion models have demonstrated impressive generative power in personalized subject-driven or style-driven applications, existing state-of-the-art methods still encounter difficulties in achiev

Reda Igebaria, Eran Fainman, Sarai Mizrachi, Moran Beladev

User-generated reviews significantly influence consumer decisions, particularly in the travel domain when selecting accommodations. This paper contribution comprising two main elements. Firstly, we present a novel dataset of authentic guest reviews sourced from a prominent online travel platform, totaling over two million reviews from 50,000 distinct accommo

Najwa Alshehri, Daniele Boffi, Lucia Gastaldi

A posteriori error estimator is derived for an elliptic interface problem in the fictitious domain formulation with distributed Lagrange multiplier considering a discontinuous Lagrange multiplier finite element space. A posteriori error estimation plays a pivotal role in assessing the accuracy and reliability of computational solutions across various domains

Saad Eddine Baddis, Adil Belhaj

In this paper, we investigate hypergeometric stringy corrections in the swampland program for rescaled gravity. Precisely, we study inflationary models from Gauss-Bonnet hypergeometric scalar couplings via the falsification scenario. We first derive generalized exponential potentials from such hypergeometric behaviors. Then, we examine certain selected scala

Ankit Gangwal, Aashish Paliwal

The recent rise of CubeSat has revolutionized global space explorations, as it offers cost-effective solutions for low-orbit space applications (including climate monitoring, weather measurements, communications, and earth observation). A salient feature of CubeSat is that applications currently on-boarded can either be updated or entirely replaced by new ap

Michael Fuest, Pingchuan Ma, Ming Gui, Johannes Schusterbauer

Diffusion Models are popular generative modeling methods in various vision tasks, attracting significant attention. They can be considered a unique instance of self-supervised learning methods due to their independence from label annotation. This survey explores the interplay between diffusion models and representation learning. It provides an overview of di

Zimu Lu, Aojun Zhou, Ke Wang, Houxing Ren

Direct Preference Optimization (DPO) has proven effective at improving the performance of large language models (LLMs) on downstream tasks such as reasoning and alignment. In this work, we propose Step-Controlled DPO (SCDPO), a method for automatically providing stepwise error supervision by creating negative samples of mathematical reasoning rationales that

Anas Abu-Odeh, Bin Xing, Penghui Cao, Blas Pedro Uberuaga

Short-range ordering (SRO) in multi-principal element alloys influences material properties such as strength and corrosion. While some degree of SRO is expected at equilibrium, predicting the kinetics of its formation is challenging. We present a simplified isothermal concentration-wave (CW) model to estimate an effective relaxation time of SRO formation. Es

Revati Gunjal, Syed Shadab Nayyer, Sushama Wagh, Navdeep Singh

A common theme in all the above areas is designing a dynamical system to accomplish desired objectives, possibly in some predefined optimal way. Since control theory advances the idea of suitably modifying the behavior of a dynamical system, this paper explores the role of control theory in designing efficient algorithms (or dynamical systems) related to pro

Geigh Zollicoffer, Kshitij Bhatta, Manish Bhattarai, Phil Romero

In this paper, we introduce innovative approaches for accelerating the Jacobi method for matrix diagonalization, specifically through the formulation of large matrix diagonalization as a Semi-Markov Decision Process and small matrix diagonalization as a Markov Decision Process. Furthermore, we examine the potential of utilizing scalable architecture between

Emily Y. Chen, Sujit S. Datta

Diverse chemical, energy, environmental, and industrial processes involve the flow of polymer solutions in porous media. The accumulation and dissipation of elastic stresses as the polymers are transported through the tortuous, confined pore space can lead to the development of an elastic flow instability above a threshold flow rate. This flow instability ca

Itsaso Fernández-Irisarri, Manuel Mañas

In this paper, we extend our investigation into semiclassical multiple discrete orthogonal polynomials by considering an arbitrary number of weights. We derive multiple versions of the Toda equations and the Laguerre-Freud equations for the multiple generalized Charlier and multiple generalized Meixner II families.

Debabrata Mondal, Andrey Kolovsky, S. Sinha

We consider a coupled atom-photon system described by the Tavis-Cummings dimer (two coupled cavities) in the presence of photon loss and atomic pumping, to investigate the quantum signature of dissipative chaos. The appropriate classical limit of the model allows us to obtain a phase diagram identifying different dynamical phases, especially the onset of cha

Thibault Lacombe, Xavier Lamy

We show that Lipschitz solutions $u$ of $\mathrm{div}\, G(\nabla u)=0$ in $B_1\subset\mathbb R^2$ are $C^1$, for strictly monotone vector fields $G\in C^0(\mathbb R^2;\mathbb R^2)$ satisfying a mild ellipticity condition. If $G=\nabla F$ for a strictly convex function $F$, and $0\leq \lambda(\xi)\leq \Lambda(\xi)$ are the two eigenvalues of $\nabla^2 F(\xi)$

Diksha Sharma, Vivek Balasaheb Sabale, Parvinder Singh, Atul Kumar

In the present study, we use cross-domain classification using quantum machine learning for quantum advantages to readdress the entanglement versus separability paradigm. The inherent structure of quantum states and its relation to a particular class of quantum states are used to intuitively classify testing states from domains different from training states

Oren Bergman, Eduardo Garcia-Valdecasas, Francesco Mignosa, Diego Rodriguez-Gomez

We propose a holographic description of the operators implementing $U(1)$ global symmetries that are dual to superstring gauge fields in terms of non-BPS D-branes. We check the consistency of our proposal in a number of examples.

Alfred Zong, Sheng-Chih Lin, Shunsuke A. Sato, Emma Berger

Advances in attosecond core-level spectroscopies have successfully unlocked the fastest dynamics involving high-energy electrons. Yet, these techniques are not conventionally regarded as an appropriate probe for low-energy quasiparticle interactions that govern the ground state of quantum materials, nor for studying long-range order because of their limited

Andre Erpenbeck, Thomas Blommel, Lei Zhang, Wei-Ting Lin

A precise dynamical characterization of quantum impurity models with multiple interacting orbitals is challenging. In quantum Monte Carlo methods, this is embodied by sign problems. A dynamical sign problem makes it exponentially difficult to simulate long times. A multi-orbital sign problem generally results in a prohibitive computational cost for systems w

Andrei A. Agrachev, Stefano Baranzini, Eugenio Bellini, Luca Rizzi

Through the use of sub-Riemannian metrics we provide quantitative estimates for the maximal tight neighbourhood of a Reeb orbit on a three-dimensional contact manifold. Under appropriate geometric conditions we show how to construct closed curves which are boundaries of overtwisted disks. We introduce the concept of \emph{contact} Jacobi curve, and prove low

Rong Fu, Zhongling Su, Han-Sen Zhong, Xiti Zhao

Quantum Computational Superiority boasts rapid computation and high energy efficiency. Despite recent advances in classical algorithms aimed at refuting the milestone claim of Google's sycamore, challenges remain in generating uncorrelated samples of random quantum circuits. In this paper, we present a groundbreaking large-scale system technology that levera

Deepika Tiwari, Yogya Gamage, Martin Monperrus, Benoit Baudry

Typically, a conventional unit test (CUT) verifies the expected behavior of the unit under test through one specific input / output pair. In contrast, a parameterized unit test (PUT) receives a set of inputs as arguments, and contains assertions that are expected to hold true for all these inputs. PUTs increase test quality, as they assess correctness on a b

Yin-Da Guo, Nayun Jia, Shou-Shan Bao, Hong Zhang

Ultralight vectors can extract energy and angular momentum from a Kerr black hole (BH) due to superradiant instability, resulting in the formation of a BH-condensate system. In this work, we carefully investigate the evolution of this system numerically with multiple superradiant modes. Simple formulas are obtained to estimate important timescales, maximum m

Masato Murata, Koichi Miyazaki, Tomoki Koriyama

With the development of speech synthesis, recent research has focused on challenging tasks, such as speaker generation and emotion intensity control. Attribute interpolation is a common approach to these tasks. However, most previous methods for attribute interpolation require specific modules or training methods. We propose an attribute interpolation method

Stefan Arnold, Rene Gröbner, Annika Schreiner

Differential Privacy (DP) can be applied to raw text by exploiting the spatial arrangement of words in an embedding space. We investigate the implications of such text privatization on Language Models (LMs) and their tendency towards stereotypical associations. Since previous studies documented that linguistic proficiency correlates with stereotypical bias,

M. Ertug Pihtili, Mehmet C. Ilter, Ertugrul Basar

The rising demand for energy and spectrum resources in next-generation Internet-of-things (IoT) systems accounts for innovative modes of information and power transfer. One potential solution is to harness the active transmission capability of devices to facilitate data transmission and wireless energy harvesting (WEH) for backscatter communication so as to

Yoonjae Lee, Goutam Das, Daigo Shishika, Efstathios Bakolas

In this paper, we investigate a multi-agent target guarding problem in which a single defender seeks to capture multiple attackers aiming to reach a high-value target area. In contrast to previous studies, the attackers herein are assumed to be heterogeneous in the sense that they have not only different speeds but also different weights representing their r

Govinda Anantha Padmanabha, Jan Niklas Fuhg, Cosmin Safta, Reese E. Jones

Most scientific machine learning (SciML) applications of neural networks involve hundreds to thousands of parameters, and hence, uncertainty quantification for such models is plagued by the curse of dimensionality. Using physical applications, we show that $L_0$ sparsification prior to Stein variational gradient descent ($L_0$+SVGD) is a more robust and effi