October 2023 arXiv papers — page 14

T. Lancaster

A glance at recent research on magnetism turns up a curious set of articles discussing, or claiming evidence for, a state of matter called a quantum spin liquid (QSL). These articles are notable in their invocation of exotic notions of topological physics, quantum entanglement, fractional quantum numbers, anyon statistics and gauge field theories. So what is

Hong-Yan Zhang, Zhi-Qiang Feng, Haoting Liu, Rui-Jia Lin

Kuiper's $V_n$ statistic, a measure for comparing the difference of ideal distribution and empirical distribution, is of great significance in the goodness-of-fit test. However, Kuiper's formulae for computing the cumulative distribution function, false positive probability and the upper tail quantile of $V_n$ can not be applied to the case of small sample c

Martino Garonzi, Claude Marion

We investigate finite groups with the Magnus Property, where a group is said to have the Magnus Property (MP) if whenever two elements have the same normal closure then they are conjugate or inverse conjugate. In particular we observe that a finite MP group is solvable, determine the finite primitive MP groups and determine all the possible orders of the chi

Debvrat Varshney, Masoud Yari, Oluwanisola Ibikunle, Jilu Li

Airborne radar sensors capture the profile of snow layers present on top of an ice sheet. Accurate tracking of these layers is essential to calculate their thicknesses, which are required to investigate the contribution of polar ice cap melt to sea-level rise. However, automatically processing the radar echograms to detect the underlying snow layers is a cha

Sharath M Shankaranarayana

Supervised machine learning relies on the availability of good labelled data for model training. Labelled data is acquired by human annotation, which is a cumbersome and costly process, often requiring subject matter experts. Active learning is a sub-field of machine learning which helps in obtaining the labelled data efficiently by selecting the most valuab

Zhuocheng Gong, Jiahao Liu, Qifan Wang, Jingang Wang

In-context learning (ICL) is an emerging capability of large autoregressive language models where a few input-label demonstrations are appended to the input to enhance the model's understanding of downstream NLP tasks, without directly adjusting the model parameters. The effectiveness of ICL can be attributed to the strong language modeling capabilities of l

Adrien Chaigneau, Denis S. Grebenkov

We numerically investigate the generalized Steklov problem for the modified Helmholtz equation and focus on the relation between its spectrum and the geometric structure of the domain. We address three distinct aspects: (i) the asymptotic behavior of eigenvalues for polygonal domains; (ii) the dependence of the integrals of eigenfunctions on the domain symme

Tanay Paul, Nalina Vadakkayil, Subir K. Das

To study the kinetics of phase separation in active matter systems, we consider models that impose a Vicsek-type self-propulsion rule on otherwise passive particles interacting via the Lennard-Jones potential. Two types of kinetics are of interest: one conserves the total momentum of all the constituents and the other that does not. We carry out numerical si

Takuya Inoue, Yusuke Nakamura

We investigate the "stratified Ehrhart ring theory" for periodic graphs, which gives an algorithm for determining the growth sequences of periodic graphs. The growth sequence $(s_{\Gamma, x_0, i})_{i \ge 0}$ is defined for a graph $\Gamma$ and its fixed vertex $x_0$, where $s_{\Gamma, x_0, i}$ is defined as the number of vertices of $\Gamma$ at distance $i$

Jan Luxemburk, Karel Hynek

The machine learning communities, such as those around computer vision or natural language processing, have developed numerous supportive tools and benchmark datasets to accelerate the development. In contrast, the network traffic classification field lacks standard benchmark datasets for most tasks, and the available supportive software is rather limited in

Heather Lent, Kushal Tatariya, Raj Dabre, Yiyi Chen

Creoles represent an under-explored and marginalized group of languages, with few available resources for NLP research.While the genealogical ties between Creoles and a number of highly-resourced languages imply a significant potential for transfer learning, this potential is hampered due to this lack of annotated data. In this work we present CreoleVal, a c

Lorenzo Caprini, Anton Ldov, Rahul Kumar Gupta, Hendrik Ellenberg

In an equilibrium thermal environment, random elastic collisions between background particles and a tracer establish the picture of Brownian motion fulfilling the celebrated Einstein relation between diffusivity and mobility. In nature, environments often comprise collections of autonomously moving objects that exhibit fascinating non-equilibrium phenomena a

Oskar Riedler

The eigenfamilies of Gudmundsson and Sakovich can be used to generate harmonic morphisms, proper $r$-harmonic maps, and minimal co-dimension $2$ submanifolds. This article begins by characterising the globally defined eigenfamilies of the sphere $S^m$; they correspond to orthogonal families of homogeneous polynomial harmonic morphisms from $\Bbb{R}^{m+1}$ to

Arthur C. R. Dutra, Roberto D. Baldijão, Marcelo Terra Cunha

KS-contextuality is a crucial feature of quantum theory. Previous research demonstrated the vanishing of $N$-cycle KS-contextuality in setups where multiple independent observers measure sequentially on the same system, which we call Public Systems. This phenomenon can be explained as the additional observers' measurements degrading the state and depleting t

Lucia Falconi, Andrea Martinelli, John Lygeros

The linear programming (LP) approach is, together with value iteration and policy iteration, one of the three fundamental methods to solve optimal control problems in a dynamic programming setting. Despite its simple formulation, versatility, and predisposition to be employed in model-free settings, the LP approach has not enjoyed the same popularity as the

Rolf Schneider

A nonempty closed convex set in ${\mathbb R}^n$, not containing the origin, is called a pseudo-cone if with every $x$ it also contains $\lambda x$ for $x\ge 1$. We consider pseudo-cones with a given recession cone $C$, called $C$-pseudo-cones. The family of $C$-pseudo-cones can, with reasonable justification, be considered as a counterpart to the family of c

P. C. Lopez-Custodio, K. Bharath, A. Kucukyilmaz, S. P. Preston

Many of the tools available for robot learning were designed for Euclidean data. However, many applications in robotics involve manifold-valued data. A common example is orientation; this can be represented as a 3-by-3 rotation matrix or a quaternion, the spaces of which are non-Euclidean manifolds. In robot learning, manifold-valued data are often handled b

Cédric Bonnafé

French abstract. Il est connu que le quotient du groupe d\'eriv\'e du groupe de r\'eflexions complexe $G_{32}$ de Shephard-Todd (qui est de rang $4$) par son centre est isomorphe au groupe d\'eriv\'e du groupe de Weyl de type $E_6$. Nous montrons que cet isomorphisme peut se r\'ealiser via la puissance ext\'erieure deuxi\`eme et en profitons pour proposer un

Changsheng Lv, Shuai Zhang, Yapeng Tian, Mengshi Qi

In this paper, we propose a Disentangled Counterfactual Learning~(DCL) approach for physical audiovisual commonsense reasoning. The task aims to infer objects' physics commonsense based on both video and audio input, with the main challenge is how to imitate the reasoning ability of humans. Most of the current methods fail to take full advantage of different

Yiwei Li, Chien-Wei Huang, Shuai Wang, Chong-Yung Chi

Federated learning (FL) has been recognized as a rapidly growing research area, where the model is trained over massively distributed clients under the orchestration of a parameter server (PS) without sharing clients' data. This paper delves into a class of federated problems characterized by non-convex and non-smooth loss functions, that are prevalent in FL

Christian Glocker, Matteo Iacopini, Tamás Krisztin, Philipp Piribauer

The spatial autoregressive (SAR) model is extended by introducing a Markov switching dynamics for the weight matrix and spatial autoregressive parameter. The framework enables the identification of regime-specific connectivity patterns and strengths and the study of the spatiotemporal propagation of shocks in a system with a time-varying spatial multiplier m

Mohamed Saidi

We investigate sections of the arithmetic fundamental group pi_1(X) where X is either a smooth affinoid p-adic curve, or a formal germ of a p-adic curve, and prove that they can be lifted (unconditionally) to sections of cuspidally abelian Galois groups. As a consequence, if X admits a compactification Y, and the exact sequence of pi_1(X) splits, then index

Ginga Kato, Yoshihiro Kuroda, Kiyoshi Kiyokawa, Haruo Takemura

Most existing locomotion devices that represent the sensation of walking target a user who is actually performing a walking motion. Here, we attempted to represent the walking sensation, especially a kinesthetic sensation and advancing feeling (the sense of moving forward) while the user remains seated. To represent the walking sensation using a relatively s

Yizhuo Li, Kunchang Li, Yinan He, Yi Wang

Building video-language foundation models is costly and difficult due to the redundant nature of video data and the lack of high-quality video-language datasets. In this paper, we propose an efficient framework to harvest video foundation models from image ones. Our method is intuitively simple by randomly dropping input video patches and masking out input t

Alec Payne

We study existence problems for closed $G_2$-structures with negative Ricci curvature, and we prove the $G_2$-Goldberg conjecture for noncompact manifolds. We first show that no closed manifold admits a closed $G_2$-structure with negative Ricci curvature. In the noncompact setting, we show that no complete manifold admits a closed $G_2$-structure with Ricci

Roger J. A. Laeven, Emanuela Rosazza Gianin, Marco Zullino

This paper presents novel characterization results for classes of law-invariant star-shaped functionals. We begin by establishing characterizations for positively homogeneous and star-shaped functionals that exhibit second- or convex-order stochastic dominance consistency. Building on these characterizations, we proceed to derive Kusuoka-type representations

Soheil Solhjoo

This note provides a MATLAB code to determine the critical strain associated with the onset of dynamic recrystallization. The code takes a closed-form constitutive model and derives the critical strain by solving $\partial^2 \theta / \partial \sigma^2 = 0$. Moreover, several models that could be used for this purpose are studied.

Deepak Aswani

With a broad market of Distributed Energy Resource (DER) aggregated control solutions, technology investment and implementation decisions for electric utilities and grid operators need to consider complexity, cost, and performance. This paper compares the performance tradeoffs of two Virtual Power Plant (VPP) architectures for DER aggregated control.

Javier Argüello-Luengo, Utso Bhattacharya, Alessio Celi, Ravindra W. Chhajlany

In this Perspective article we report on recent progress on studies of synthetic dimensions, mostly, but not only, based on the research realized around the Barcelona groups (ICFO, UAB), Donostia (DIPC), Pozna\'n (UAM), Krak\'ow (UJ), and Allahabad (HRI). The concept of synthetic dimensions works particularly well in atomic physics, quantum optics, and photo

Massimo Fornasier, Pascal Heid, Giacomo Enrico Sodini

The challenge of approximating functions in infinite-dimensional spaces from finite samples is widely regarded as formidable. We delve into the challenging problem of the numerical approximation of Sobolev-smooth functions defined on probability spaces. Our particular focus centers on the Wasserstein distance function, which serves as a relevant example. In

Alberto Scalesi, Carlo Barbieri, Enrico Vigezzi

Ab initio studies of atomic nuclei are based on Hamiltonians including one-, two- and three-body operators with very complicated structures. Traditionally, matrix elements of such operators are expanded on a Harmonic Oscillator single-particle basis, which allows for a simple separation of the center-of-mass motion from the intrinsic one. A few recent invest

Linhao Ma, Cole Johnston, Earl P. Bellinger, Selma E. de Mink

The blue supergiant (BSG) problem, namely, the overabundance of BSGs inconsistent with classical stellar evolution theory, remains an open question in stellar astrophysics. Several theoretical explanations have been proposed, which may be tested by their predictions for the characteristic time variability. In this work, we analyze the light curves of a sampl

Colton R. Crum, Adam Czajka

Leveraging human perception into training of convolutional neural networks (CNN) has boosted generalization capabilities of such models in open-set recognition tasks. One of the active research questions is where (in the model architecture or training pipeline) and how to efficiently incorporate always limited human perceptual data into training strategies o

Heejoung Hong, Ui Min, Minho Son, Tevong You

Axions and dark photons are common in many extensions of the Standard Model. The dark axion portal -- an axion coupling to the dark photon and photon -- can significantly modify their phenomenology. We study the cosmological constraints on the dark axion portal from Cosmic Microwave Background (CMB) bounds on the energy density of dark radiation, $\Delta N_\

Alain Hecq, Daniel Velasquez-Gaviria

This paper introduces new techniques for estimating, identifying and simulating mixed causal-noncausal invertible-noninvertible models. We propose a framework that integrates high-order cumulants, merging both the spectrum and bispectrum into a single estimation function. The model that most adequately represents the data under the assumption that the error

Chuanming Tang, Kai Wang, Joost van de Weijer, Jianlin Zhang

Visual object tracking is a fundamental component of transportation systems, especially for intelligent driving. Despite achieving state-of-the-art performance in visual tracking, recent single-branch trackers tend to overlook the weak prior assumptions associated with the Vision Transformer (ViT) encoder and inference pipeline in visual tracking. Moreover,

Botond Szabó, Aad van der Vaart, Lasse Vuursteen, Harry van Zanten

Combining test statistics from independent trials or experiments is a popular method of meta-analysis. However, there is very limited theoretical understanding of the power of the combined test, especially in high-dimensional models considering composite hypotheses tests. We derive a mathematical framework to study standard {meta-analysis} testing approaches

Chuanming Tang, Kai Wang, Joost van de Weijer

Large-scale text-to-image diffusion models have been a ground-breaking development in generating convincing images following an input text prompt. The goal of image editing research is to give users control over the generated images by modifying the text prompt. Current image editing techniques predominantly hinge on DDIM inversion as a prevalent practice ro

Alex Doboli

This paper proposes a novel representation to support computing metrics that help understanding and improving in real-time a team's behavior during problem solving in real-life. Even though teams are important in modern activities, there is little computing aid to improve their activity. The representation captures the different mental images developed, enha

F. Terhag, P. Knechtges, A. Basermann, R. Tempone

Recent studies have confirmed cardiovascular diseases remain responsible for highest death toll amongst non-communicable diseases. Accurate left ventricular (LV) volume estimation is critical for valid diagnosis and management of various cardiovascular conditions, but poses significant challenge due to inherent uncertainties associated with segmentation algo

Ruohan Shen, Yixu Wang, ChunJun Cao

We apply the recent graphical framework of "Quantum Lego" to XP stabilizer codes where the stabilizer group is generally non-Abelian. We show that the idea of operator matching continues to hold for such codes and is sufficient for generating all their XP symmetries provided the resulting code is XP. We provide an efficient classical algorithm for tracking t

Wojciech Masarczyk, Tomasz Trzciński, Mateusz Ostaszewski

In the era of transfer learning, training neural networks from scratch is becoming obsolete. Transfer learning leverages prior knowledge for new tasks, conserving computational resources. While its advantages are well-documented, we uncover a notable drawback: networks tend to prioritize basic data patterns, forsaking valuable pre-learned features. We term t

Jialin Liu, Xinyan Su, Zeyu He, Xiangyu Zhao

Rewards serve as a measure of user satisfaction and act as a limiting factor in interactive recommender systems. In this research, we focus on the problem of learning to reward (LTR), which is fundamental to reinforcement learning. Previous approaches either introduce additional procedures for learning to reward, thereby increasing the complexity of optimiza

Zhaowei Gao, Mingyang Song, Christopher Schroers, Yang Zhang

Due to old CRT display technology and limited transmission bandwidth, early film and TV broadcasts commonly used interlaced scanning. This meant each field contained only half of the information. Since modern displays require full frames, this has spurred research into deinterlacing, i.e. restoring the missing information in legacy video content. In this pap

Robert Ranecki, Benedikt Baumann, Stefan Lach, Christiane Ziegler

Donor-acceptor (D-A) structured molecules are essential components in organic electronics. The respective molecular structure of these molecules and their synthesis are primarily determined by the intended area of application. Typically, D-A molecules promote charge separation and transport in organic photovoltaics (OPV) or organic field-effect transistors (

S. S. Vergeles, I. A. Vointsev

We consider a classical problem about dynamic instability that leads to the Langmuir circulation. The problem statement assumes that there is initially a wind-driven shear flow and a plane surface wave propagating in the direction of the flow. The unstable mode is a superposition of i) shear flow and ii) surface waves both modulated in the horizontal spanwis

Guy Chanfray

The work that Peter Schuck and I carried out during the nineties in collaboration with the Lyon and Darmstadt theory groups is summarized. I retrace how our theoretical developments combined with experimental results concerning the in-medium modification of the pion-pion interaction allowed a clarification of the chiral status of the sigma meson introduced i

Zhenpeng Su, Xing Wu, Xue Bai, Zijia Lin

Generative language models are usually pretrained on large text corpus via predicting the next token (i.e., sub-word/word/phrase) given the previous ones. Recent works have demonstrated the impressive performance of large generative language models on downstream tasks. However, existing generative language models generally neglect an inherent challenge in te

D. Fabri Gonçalves, R. da Rocha

The generalized Fierz identities are addressed in the K\"ahler-Atiyah bundle framework from the perspective of the equations governing constrained generalized Killing spinor fields. We explore the spin geometry in a Riemannian 8-manifold composing a warped flux compactification AdS$_3\times M_8$, whose metric and fluxes preserve one supersymmetry in AdS$_3$.

Ioannis Papavasileiou, Dionysios Syrigos

We study finite subgroups of outer automorphisms of free products. We give upper bounds for the orders of these finite subgroups as well as bounds for the orders of individual torsion outer automorphisms under some (necessary) conditions for the free factors.

Hans-E. Porst

Not only motivated by the fact that the publication of the GAFT first appeared 60 years ago in print we reconstruct its history and so show that it is no exaggeration to claim that it has appeared already 75 years ago!

Michal Nauman, Marek Cygan

Risk-aware Reinforcement Learning (RL) algorithms like SAC and TD3 were shown empirically to outperform their risk-neutral counterparts in a variety of continuous-action tasks. However, the theoretical basis for the pessimistic objectives these algorithms employ remains unestablished, raising questions about the specific class of policies they are implementi

E. Nieto Hernandez, G. Andrini, A. Crnjac, M. Brajkovic

Nitrogen-Vacancy (NV) centers in diamond are promising systems for quantum technologies, including quantum metrology and sensing. A promising strategy for the achievement of high sensitivity to external fields relies on the exploitation of large ensembles of NV centers, whose fabrication by ion implantation is upper limited by the amount of radiation damage

Gbenga Onifade Ebenezer

In this study, a thorough investigation was conducted into the Homotopy Perturbation Method (HPM) and its application to solve the Burger and Blasius equations. The HPM is a mathematical technique that combines aspects of homotopy and perturbation methods. By introducing an auxiliary parameter, the complex problems were transformed into a series of simpler e

Paul Geoerg, Ann Katrin Boomers, Maxine Berthiaume, Maik Boltes

Individual differences in mobility (e.g., due to wheelchair use) during crowd movement are not well understood. Perceived vulnerability of neighbors in a crowd could affect, for example, how much space is given to them by others. To explore how pedestrians perceive people moving in front of them, in particular, how vulnerable they believe them to be, we aske

Dragos-Patru Covei, Traian A. Pirvu, Catalin Sterbeti

This paper considers a nonlinear model for population dynamics with age structure. The fertility rate with respect to age is non constant and has the form proposed by [17]. Moreover, its multiplicative structure and the multiplicative structure of mortality makes the model separable. In this setting it is shown that the number of births in unit time is given

Bin-Lei Wang, Long-Jun Wang

The first-forbidden transition of nuclear $\beta$ decay is expected to play crucial roles in many aspects in nuclear physics, nuclear astrophysics and particle physics such as the stellar $\beta$-decay rates and the reactor anti-neutrino spectra. In this work we develop the projected shell model (PSM) for description of first-forbidden transition of nuclear

Joana Palés Huix, Adithya Raju Ganeshan, Johan Fredin Haslum, Magnus Söderberg

The deep learning field is converging towards the use of general foundation models that can be easily adapted for diverse tasks. While this paradigm shift has become common practice within the field of natural language processing, progress has been slower in computer vision. In this paper we attempt to address this issue by investigating the transferability

Riccardo Milani, Florent Renac, Jean Ruel

We investigate the properties of the high-order discontinuous Galerkin spectral element method (DGSEM) with implicit backward-Euler time stepping for the approximation of hyperbolic linear scalar conservation equation in multiple space dimensions. We first prove that the DGSEM scheme in one space dimension preserves a maximum principle for the cell-averaged

Yuri Makeenko

I discuss the recent progress in bypassing the KPZ barrier for the existence of nonperturbative bosonic strings in $1<d<25$. I consider string anomalies which emerge from higher terms of the DeWitt-Seeley expansion as $\varepsilon \times \varepsilon^{-1}$ with $\varepsilon$ being a UV cutoff. I show they give a nonvanishing contribution to the central charge

Jialin Liu, Xinyan Su, Peng Zhou, Xiangyu Zhao

Survivor bias in observational data leads the optimization of recommender systems towards local optima. Currently most solutions re-mines existing human-system collaboration patterns to maximize longer-term satisfaction by reinforcement learning. However, from the causal perspective, mitigating survivor effects requires answering a counterfactual problem, wh

Vladimir Rovenski

Weak almost contact manifolds, i.e., the linear complex structure on the contact distribution is approximated by a nonsingular skew-symmetric tensor, defined by the author and R. Wolak (2022), allowed a new look at the theory of contact manifolds. This article studies the curvature and topology of new structures of this type, called the weak nearly cosymplec

Ladislav Šamaj

The model under study is an infinite 2D jellium of pointlike particles with elementary charge $e$, interacting via the logarithmic potential and in thermal equilibrium at the inverse temperature $\beta$. Two cases of the coupling constant $\Gamma\equiv \beta e^2$ are considered: the Debye-H\"uckel limit $\Gamma\to 0$ and the free-fermion point $\Gamma=2$. In

Mohammed Munzer Dwedari, Matthias Niessner, Dave Zhenyu Chen

3D question answering is a young field in 3D vision-language that is yet to be explored. Previous methods are limited to a pre-defined answer space and cannot generate answers naturally. In this work, we pivot the question answering task to a sequence generation task to generate free-form natural answers for questions in 3D scenes (Gen3DQA). To this end, we

Çağlar Küçük, Apostolos Giannakos, Stefan Schneider, Alexander Jann

Weather radar data are critical for nowcasting and an integral component of numerical weather prediction models. While weather radar data provide valuable information at high resolution, their ground-based nature limits their availability, which impedes large-scale applications. In contrast, meteorological satellites cover larger domains but with coarser res

Lorenzo Beretta, Aviad Rubinstein

We design an additive approximation scheme for estimating the cost of the min-weight bipartite matching problem: given a bipartite graph with non-negative edge costs and $\varepsilon > 0$, our algorithm estimates the cost of matching all but $O(\varepsilon)$-fraction of the vertices in truly subquadratic time $O(n^{2-\delta(\varepsilon)})$. Our algorithm has

Frédéric A. Dreyer, Daniel Cutting, Constantin Schneider, Henry Kenlay

We consider the problem of antibody sequence design given 3D structural information. Building on previous work, we propose a fine-tuned inverse folding model that is specifically optimised for antibody structures and outperforms generic protein models on sequence recovery and structure robustness when applied on antibodies, with notable improvement on the hy

Haoxin Chen, Menghan Xia, Yingqing He, Yong Zhang

Video generation has increasingly gained interest in both academia and industry. Although commercial tools can generate plausible videos, there is a limited number of open-source models available for researchers and engineers. In this work, we introduce two diffusion models for high-quality video generation, namely text-to-video (T2V) and image-to-video (I2V

Manuel Boldrer, Alvaro Serra-Gomez, Lorenzo Lyons, Vit Kratky

This paper presents a distributed rule-based Lloyd algorithm (RBL) for multi-robot motion planning and control. The main limitations of the basic Loyd-based algorithm (LB) concern deadlock issues and the failure to address dynamic constraints effectively. Our contribution is twofold. First, we show how RBL is able to provide safety and convergence to the goa

Murat Can Sarihan, Jiahui Huang, Jin Ho Kang, Cody Fan

Color centers in the O-band (1260-1360 nm) are critical for realizing long-coherence quantum network nodes in memory-assisted quantum communications. However, only a limited number of O-band color centers have been explored in silicon hosts as spin-photon interfaces. This study explores and compares two promising O-band defects in silicon: T centers and $^*$

Haitao Xu, Songwei Liu, Yuyang Xu, Shuai Wang

To address the challenge of increasing network size, researchers have developed sparse models through network pruning. However, maintaining model accuracy while achieving significant speedups on general computing devices remains an open problem. In this paper, we present a novel mobile inference acceleration framework SparseByteNN, which leverages fine-grain

José Tarciso S. S. Junior, Francisco S. N. Lobo, Manuel E. Rodrigues

In this work, we explore black hole and regular black hole solutions in the recently proposed Conformal Killing Gravity (CKG). This theory is of third order in the derivatives of the metric tensor and essentially satisfies three theoretical criteria for gravitational theories beyond General Relativity (GR). The criteria essentially stipulate the following, t

Federica Adobbati, Łukasz Mikulski

In the modelling and analysis of large, real systems, the main problem in their efficient processing is the size of the global model. One of the popular approaches that address this issue is the decomposition of such global model into much smaller submodels and interaction between them. In this paper we discuss the translation of multi-agent systems with the

Jing Li, Wenchang Chu

By means of the contour integration method, we evaluate, in closed form, a class of definite integrals involving hyperbolic tangent function.

Domenico Fiorenza, Hông Vân Lê

We encode the real homotopy type of an $n$-dimensional $(r-1)$-connected compact manifold $M$, $ r\ge 2$ into a minimal unital $C_\infty$-structure on $H^* (M,\mathbb R)$, obtained via homotopy transfer of the unital DGCA structure of the small quotient algebra associated with a Hodge decomposition of the de Rham algebra $\mathcal A^*(M)$, which has been pro

Chen Li, Yuhan Du, Haonan Chen, Xinxin Han

Understanding the optical transmission property of human hair, especially in the infrared regime, is vital in physical, clinical, and biomedical research. However, the majority of infrared spectroscopy on human hair is performed in the reflection mode, which only probes the absorptance of the surface layer. The direct transmission spectrum of individual hair

Jezer Jojo, Ankit Khandelwal, M Girish Chandra

In this work, we discuss two modifications that can be made to a known variational quantum singular value decomposition algorithm popular in the literature. The first is a change to the objective function which hints at improved performance of the algorithm. The second modification introduces a new way of computing expectation values of general matrices, whi

Luis-Daniel Ibáñez, John Domingue, Sabrina Kirrane, Oshani Seneviratne

Knowledge Graphs (KGs) have emerged as fundamental platforms for powering intelligent decision-making and a wide range of Artificial Intelligence (AI) services across major corporations such as Google, Walmart, and AirBnb. KGs complement Machine Learning (ML) algorithms by providing data context and semantics, thereby enabling further inference and question-

Christopher L. Rom, Andrew Novick, Matthew J. McDermott, Andrey A. Yakovenko

Recent computational studies have predicted many new ternary nitrides, revealing synthetic opportunities in this underexplored phase space. However, synthesizing new ternary nitrides is difficult, in part because intermediate and product phases often have high cohesive energies that inhibit diffusion. Here, we report the synthesis of two new phases, calcium

Yohei Ito

In [arXiv:2109.13991], the author explained a relation between enhanced ind-sheaves and enhanced subanalytic sheaves. In this paper, we shall define C-constructability for enhanced subanalytic sheaves which was announced in [arXiv:2109.13991], and show that there exists an equivalence of categories between the triangulated category of C-constructible enhance

Vadim Korolev, Artem Mitrofanov

Reticular materials, including metal-organic frameworks and covalent organic frameworks, combine relative ease of synthesis and an impressive range of applications in various fields, from gas storage to biomedicine. Diverse properties arise from the variation of building units$\unicode{x2013}$metal centers and organic linkers$\unicode{x2013}$in almost infini

Martina Fruttidoro

Let $G_{\mathbb{Q}_p}$ be the absolute Galois group of $\mathbb{Q}_p$ and let $L$ be a finite extension of $\mathbb{Q}_p$. Moreover let $\bar\rho:G_{\mathbb{Q}_p}\rightarrow GL_n(k_L)$ be a continous representation of $G_{\mathbb{Q}_p}$, where $k_L$ is the residue field of $L$ and $n$ is a natural number greater than $1$. We find sufficient conditions for wh

Hanxin Zhao

Green ammonia is poised to be a key part in the hydrogen economy. This paper discusses green ammonia supply chains from a higher-level industry perspective with a focus on market structures. The architecture of upstream and downstream supply chains are explored. Potential ways to accelerate market emergence are discussed. Market structure is explored based o

K. -J. Chuang, C. Jaeger, N. -E. Sie, C. -H. Huang

The chemical inventory of protoplanetary midplanes is the basis for forming planetesimals. Among them, solid-state reactions based on CO/CO$_2$ toward molecular complexity on interstellar dust grains have been studied in theoretical and laboratory work. In this work, the erosion of C dust grains induced by X-ray irradiation of H$_2$O ice was systematically i

Masataka Chida, Satoshi Wakatsuki

In this paper, we give some non-vanishing results on the central values of prime twists of modular $L$-functions by imaginary quadratic fields for specific elliptic modular forms. In particular, we show that the central values of prime twists of $L$-functions of some elliptic modular forms are always non-vanishing whenever the root number is positive.

M. Sunbeam

This paper aims to briefly survey deep learning methods for visual navigation of underwater robotics. The scope of this paper includes the visual perception of underwater robotics with deep learning methods, the available visual underwater datasets, imitation learning, and reinforcement learning methods for navigation. Additionally, relevant works will be ca

A. C. Maggs

We link the large-scale dynamics of non-reversible Monte Carlo algorithms as well as a lifted TASEP to an exactly soluble model of self-repelling motion. We present arguments for the connection between the problems and perform simulations, where we show that the empirical distribution functions generated from Monte Carlo are well described by the analytic so

Urei Miura, Kenji Shimomura, Keisuke Totsuka

Lattice models with supersymmetry are known to exhibit a variety of remarkable properties that do not exist in the relativistic models. In this paper, we introduce an interacting generalization of the Kitaev chain of Majorana fermions with $\mathcal{N} = 1$ supersymmetry and investigate its low-energy properties, paying particular attention to the ground-sta

Pasquale Avella, Paolo Nobili, Antonio Sassano

The climate change emergency calls for a reduction in energy consumption in all human activities and production processes. The radio broadcasting industry is no exception. However, reducing energy requirements by uniformly cutting the radiated power at every transmitter can potentially impair the quality of service. A careful evaluation and optimization stud

Yuanyuan Wang, Xi Geng, Wei Huang, Biwei Huang

In this paper, we present conditions for identifying the generator of a linear stochastic differential equation (SDE) from the distribution of its solution process with a given fixed initial state. These identifiability conditions are crucial in causal inference using linear SDEs as they enable the identification of the post-intervention distributions from i

Cheng Ziying, Kang Chuangchuang, Lü Jiafeng

In this paper, we explicitly determine all $\mathcal{O}$-operators with respect to the adjoint representation of 3-dimensional complex 3-Lie algebras. Furthermore, we provide the induced 3-Pre-Lie algebra structures and the corresponding solutions of the 3-Lie classical Yang-Baxter equation in the 6-dimensional 3-Lie algebras $A\ltimes_{\mathrm{ad}^*} A^*$.

Lukas Trommer, Halil Yigit Oksuz

The theory of Kazantzis-Kravaris/Luenberger (KKL) observer design introduces a methodology that uses a nonlinear transformation map and its left inverse to estimate the state of a nonlinear system through the introduction of a linear observer state space. Data-driven approaches using artificial neural networks have demonstrated the ability to accurately appr

Yang Zhang, Fuli Feng, Jizhi Zhang, Keqin Bao

Leveraging Large Language Models as Recommenders (LLMRec) has gained significant attention and introduced fresh perspectives in user preference modeling. Existing LLMRec approaches prioritize text semantics, usually neglecting the valuable collaborative information from user-item interactions in recommendations. While these text-emphasizing approaches excel

Vincenzo J. Pratley, Enej Caf, Miha Ravnik, Gareth P. Alexander

We study the three-dimensional spontaneous flow transition of an active nematic in an infinite slab geometry using a combination of numerics and analytics. We show that it is determined by the interplay of two eigenmodes -- called S- and D-mode -- that are unstable at the same activity threshold and spontaneously breaks both rotational symmetry and chiral sy

Eon-Kyung Lee, Sang-Jin Lee

A petal diagram of a knot is a projection with a single multi-crossing such that there are no nested loops. The petal number $p(K)$ of a knot $K$ is the minimum number of loops among all petal diagrams of $K$. Let $T_{n,s}$ denote the $(n,s)$-torus knot for relatively prime integers $2\le n<s$. Recently, Kim, No and Yoo proved that $p(T_{n,s})\le 2s-2\left\l

Bohayra Mortazavi, Fazel Shojaei, Fei Ding, Xiaoying Zhuang

Most recently the formation of boron monoxide (BO) in the two-dimensional (2D) form has been confirmed experimentally (J. Am. Chem. Soc. 2023, 145, 14660). Motivated by the aforementioned finding, herein we theoretically explore the key physical properties of the single-layer and suspended BO. Density functional theory (DFT) results reveal that BO monolayer

Hung-Hsiang Yang, Louise Desplat, Volodymyr P. Kravchuk, Marie Hervé

The nanoscopic magnetic texture forming in a monolayer of iron on the (111) surface of iridium, Fe/Ir(111), is spatially modulated and uniaxially incommensurate with respect to the crystallographic periodicities. As a consequence, a low-energy magnetic excitation is expected that corresponds to the sliding of the texture along the incommensurate direction, i

Joel Chaskalovic, Franck Assous

In this paper, we present an approach to enhance interpolation and approximation error estimates. Based on a previously derived first-order Taylor-like formula, we demonstrate its applicability in improving the $P_1$-interpolation error estimate. Following the same principles, we also develop a novel numerical scheme for the heat equation that yields a bette

Daniel Kral, Ander Lamaison, Magdalena Prorok, Xichao Shu

Erd\H os, Lov\'asz and Spencer showed in the late 1970s that the dimension of the region of $k$-vertex graph profiles, i.e., the region of feasible densities of $k$-vertex graphs in large graphs, is equal to the number of non-trivial connected graphs with at most $k$ vertices. We determine the dimension of the region of $k$-vertex tournament profiles. Our re

Thomas Williams, James M. McCaw, James Osborne

The role of direct cell-to-cell spread in viral infections - where virions spread between host and susceptible cells without needing to be secreted into the extracellular environment - has come to be understood as essential to the dynamics of medically significant viruses like hepatitis C and influenza. Recent work in both the experimental and mathematical m