December 2023 arXiv papers — page 14

Jules Pitcho

We prove that for bounded, divergence-free vector fields in $L^1_{loc}((0,+\infty);BV_{loc}(R^d;R^d))$, regularisation by convolution of the vector field selects a single solution of the transport equation for any integrable initial datum. We recall the vector field constructed by Depauw in [10], which lies in the above class of vector fields. We show that t

V. Yu. Denisov

A model for hot-fusion reactions leading to the synthesis of super-heavy nuclei is discussed. The values of the hot-fusion cross-sections obtained in the model agree with the available experimental data. The hot-fusion cross-sections are found for two different models of the fission barrier heights of super-heavy nuclei. The calculations of the cross-section

Sahal Kaushik, Filipp N. Rybakov, Egor Babaev

We consider a new class of topological defects in chiral magnetic crystals such as FeGe and MnSi. These are composite topological defects that arise when skyrmions in the magnetic order intersect with twin boundaries in the underlying crystalline lattice. We show that the resulting stable configurations are a new type of defect that can be viewed as half-hop

Mar Canet Sola, Varvara Guljajeva

This paper discusses the artwork "Visions of Destruction", with a primary conceptual focus on the Anthropocene, which is communicated through audience interaction and generative AI as artistic research methods. Gaze-based interaction transitions the audience from mere observers to agents of landscape transformation, fostering a profound, on-the-edge engageme

Marwan Najjar, Jiahua Tian, Yi-Nan Wang

We study 3D $N=2$ supersymmetric field theories geometrically engineered from M-theory on non-compact Calabi-Yau fourfolds (CY4). We establish a detailed dictionary between the geometry and topology of non-compact CY4 and the physics of 3D $N=2$ theories in three different regimes. The first one is the Coulomb branch description when the CY4 is smooth. The s

Jiawen Kang, Junhong Zhang, Helin Yang, Dongdong Ye

Vehicular Metaverses represent emerging paradigms arising from the convergence of vehicle road cooperation, Metaverse, and augmented intelligence of things. Users engaging with Vehicular Metaverses (VMUs) gain entry by consistently updating their Vehicular Twins (VTs), which are deployed on RoadSide Units (RSUs) in proximity. The constrained RSU coverage and

Zhongshen Zeng, Pengguang Chen, Shu Liu, Haiyun Jiang

In this work, we introduce a novel evaluation paradigm for Large Language Models (LLMs) that compels them to transition from a traditional question-answering role, akin to a student, to a solution-scoring role, akin to a teacher. This paradigm, focusing on "reasoning about reasoning," hence termed meta-reasoning, shifts the emphasis from result-oriented asse

Alexander Munoz Garcia

This work is devoted to study the relation between regularity and decay of solutions of some dissipative perturbations of the Korteweg-de Vries equation in weighted and asymmetrically weighted Sobolev spaces.

Bohan Lyu, Xin Cong, Heyang Yu, Pan Yang

Large Language Models (LLMs) excel in traditional natural language processing tasks but struggle with problems that require complex domain-specific calculations or simulations. While equipping LLMs with external tools to build LLM-based agents can enhance their capabilities, existing approaches lack the flexibility to address diverse and ever-evolving user q

Suresh C. Jaryal, Ayan Chatterjee, Akshay Kumar

In this paper we study the shear free spherical symmetric gravitational collapse of charged radiating star. All the physical quantities including pressure, density are regular. Energy conditions are satisfied throughout the interior of the matter configuration. The luminosity is time independent and mass is radiated linearly. The causal and non causal temper

Chenxu Pang, Xiaojie Wang, Yue Wu

It is of significant interest in many applications to sample from a high-dimensional target distribution $\pi$ with the density $\pi(\text{d} x) \propto e^{-U(x)} (\text{d} x) $, based on the temporal discretization of the Langevin stochastic differential equations (SDEs). In this paper, we propose an explicit projected Langevin Monte Carlo (PLMC) algorithm

Tong Zhou, Senmao Qi, Guangdu Cen, Ziqi Zha

In mobile robot navigation, despite advancements, the generation of optimal paths often disrupts pedestrian areas. To tackle this, we propose three key contributions to improve human-robot coexistence in shared spaces. Firstly, we have established a comprehensive framework to understand disturbances at individual and flow levels. Our framework provides speci

Zhaobin Chen, Yizhou Gu, Hu Zou, Qirong Yuan

To investigate the environment effects on size growth of galaxies, we study the size-mass relation across a broad range of environment with a vast sample of approximately 32 million galaxies at z < 0.5 from the DESI Legacy Imaging Surveys. This sample is divided into 3 subsamples representing galaxies within three different environments: brightest cluster ga

Alberto Chiarini, Maximilian Nitzschner

This article investigates the behavior of the continuous-time simple random walk on $\mathbb{Z}^d$, $d \geq 3$. We derive an asymptotic lower bound on the principal exponential rate of decay for the probability that the average value over a large box of some non-decreasing local function of the field of occupation times of the walk exceeds a given positive v

Ufuk Aydemir

We investigate the effects of an early cosmological period dominated by primordial 2-2-holes on axion dark matter. The 2-2-holes emerge as a new family of horizonless classical solutions for ultracompact matter distributions in quadratic gravity, a candidate theory of quantum gravity. Thermal 2-2-holes, sourced by relativistic thermal gas, exhibit Hawking-li

Luo Ji, Jiayu Mao, Hailong Shi, Qian Li

Online to offline recommendation strongly correlates with the user and service's spatiotemporal information, therefore calling for a higher degree of model personalization. The traditional methodology is based on a uniform model structure trained by collected centralized data, which is unlikely to capture all user patterns over different geographical areas o

Zhengze Xu, Dongyue Wu, Changqian Yu, Xiangxiang Chu

Recent real-time semantic segmentation methods usually adopt an additional semantic branch to pursue rich long-range context. However, the additional branch incurs undesirable computational overhead and slows inference speed. To eliminate this dilemma, we propose SCTNet, a single branch CNN with transformer semantic information for real-time segmentation. SC

Roberto Gargiulo, Gianluca Passarelli, Procolo Lucignano, Angelo Russomanno

We propose a Floquet period-doubling time-crystal model based on a disordered interacting long-range spin chain where the periodic swapping of nearby spin couples is applied. This protocol can be applied to systems with any local spin magnitude $s$ {and in principle also to systems with nonspin (fermionic or bosonic) local Hilbert space}. We explicitly consi

M. A. Kassem, T. Shiotani, H. Ohta, Y. Tabata

ScFe$_6$Ge$_4$ with the LiFe$_6$Ge$_4$-type structure (space group $R{\bar{3}}m$), which has a double-layered kagome lattice (18$h$ site) of Fe crystallographically equivalent to that of a well-known topological ferromagnet Fe$_3$Sn$_2$, is newly found to be antiferromagnetic (AFM) with a high N\'eel temperature of $T_{\rm{N}} \approx 650$ K, in contrast to

Juan Martín Pérez, Florent Schaffhauser

We provide an account of the construction of the moduli stack of elliptic curves as an analytic orbifold. While intimately linked to Thurston's point of view on the subject (discrete groups acting properly and effectively on differentiable manifolds), the construction of the modular orbi-curve and its universal family of elliptic curves ends up requiring a b

Siddharth G. Prabhu

We show that position space correlators of a Poincare invariant quantum field theory can be recast in terms of conformally invariant correlators, in other words, as functions of conformal cross ratios. In particular, we show that correlators of massless fields in flat spacetimes with $n-$point interactions can be expressed as position space soft limits of co

J. M. Gonzalez, H. Command, G. Valdez

The Multipurpose Interferometer Array Pathfinder (MIA), developed from the Argentine Institute of Radio Astronomy (IAR), is a radio astronomical instrument based on interferometry techniques, designed for the detection of radio emission from astronomical sources. Phase one consists of 16 antennas of 5 meters in diameter, with the possibility of increasing th

Ke Xu, Yingqiu Zhu, Yijing Liu, Hansheng Wang

This article introduces CluBear, a Python-based open-source package for interactive massive data analysis. The key feature of CluBear is that it enables users to conduct convenient and interactive statistical analysis of massive data with only a traditional single-computer system. Thus, CluBear provides a cost-effective solution when mining large-scale datas

Zhen Fan, Jian-Feng Zhang, Bo Zhan, Dingshun Lv

The discovery of superconductivity at 80 K under high pressure in La$_3$Ni$_2$O$_7$ presents the groundbreaking confirmation that high-$T_c$ superconductivity is a property of strongly correlated materials beyond cuprates. We use density functional theory (DFT) calculations of the band structure of La$_3$Ni$_2$O$_7$ under pressure to verify that the low-ener

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

A massless particle beyond the Standard Model is searched for in the two-body decay $\Sigma^+\rightarrow p+{\rm invisible}$ using $(1.0087\pm0.0044)\times10^{10}$ $J/\psi$ events collected at a center-of-mass energy of $\sqrt{s}=3.097$ GeV with the BESIII detector at the BEPCII collider. No significant signal is observed, and the upper limit on the branching

Roy Shalev

Assuming an instance of the Brodsky-Rinot proxy principle holding at a regular uncountable cardinal $\kappa$, we construct $2^\kappa$-many pairwise non-embeddable minimal non-$\sigma$-scattered linear orders of size $\kappa$. In particular, in G\"odel's constructible universe $L$, these linear orders exist for any regular uncountable cardinal $\kappa$ that i

Parley R Yang, Alexander Y Shestopaloff

Vector Error Correction Model (VECM) is a classic method to analyse cointegration relationships amongst multivariate non-stationary time series. In this paper, we focus on high dimensional setting and seek for sample-size-efficient methodology to determine the level of cointegration. Our investigation centres at a Bayesian approach to analyse the cointegrati

Lasse Mueller, Pedro Bicudo, Marina Krstic Marinkovic, Marc Wagner

We present results for tetraquark potentials of two static anti-quarks $\bar b \bar b$ in the presence of two light quarks $u$ and/or $d$. We improve on existing results by computing the static potential also for off-axis separations, which increases the number of data points significantly. Moreover, we compute for the first time $\bar b \bar b u s$ potentia

Tomohiro Yamada

We shall prove that if $N=p^\alpha q_1^{2\beta_1} q_2^{2\beta_2} \cdots q_{r-1}^{2\beta_{r-1}}$ is an odd perfect number such that $p, q_1, \ldots, q_{r-1}$ are distinct primes, $p\equiv\alpha\equiv 1\mod{4}$ and $t$ divides $2\beta_i+1$ for all $i=1, 2, \ldots, r-1$, then $t^5$ divides $N$, improving an eighty-year old result of Kanold.

Bruno Mazorra

In the realm of cost-sharing mechanisms, the vulnerability to Sybil strategies -- also known as false-name strategies, where agents create fake identities to manipulate outcomes -- has not yet been studied. In this paper, we delve into the details of different cost-sharing mechanisms proposed in the literature, highlighting their non-Sybil-resistant nature.

Diego Forlivesi, Lorenzo Valentini, Marco Chiani

Surface codes are versatile quantum error-correcting codes known for their planar geometry, making them ideal for practical implementations. While the original proposal used Pauli $X$ or Pauli $Z$ operators in a square structure, these codes can be improved by rotating the lattice or incorporating a mix of generators in the XZZX variant. However, a comprehen

Riccardo Borsato, Sibylle Driezen, Ben Hoare, Ana L. Retore

Light-cone gauge-fixed sigma-models on $AdS_n\times S^n$ backgrounds play an important role in the integrability formulation of the AdS/CFT correspondence. The string spectrum of the sigma-model is gauge-independent, however the Hamiltonian and scattering matrix of the transverse worldsheet fields are not. We study how these change for a large family of ineq

Ruizhe Zhong, Xingbo Du, Shixiong Kai, Zhentao Tang

Driven by Moore's Law, the complexity and scale of modern chip design are increasing rapidly. Electronic Design Automation (EDA) has been widely applied to address the challenges encountered in the full chip design process. However, the evolution of very large-scale integrated circuits has made chip design time-consuming and resource-intensive, requiring sub

Chengwei Qin, Wenhan Xia, Fangkai Jiao, Chen Chen

Large language models (LLMs) have shown impressive few-shot generalization on many tasks via in-context learning (ICL). Despite their success in showing such emergent abilities, the scale and complexity of larger models also lead to unprecedentedly high computational demands and deployment challenges. In reaction, researchers explore transferring the powerfu

Alimzhan Amanov, Damir Yeliussizov

We conjecture unimodality for some sequences of generalized Kronecker coefficients and prove it for partitions with at most two columns. The proof is based on a hard Lefschetz property for corresponding highest weight spaces. We also study more general Lefschetz properties, show implications to a higher-dimensional analogue of the Alon--Tarsi conjecture on L

Qingqing Wang, Xin Ren, Bo Wang, Yi-Fu Cai

We use galaxy-galaxy lensing data to test General Relativity and $f(T)$ gravity at galaxies scales. We consider an exact spherically symmetric solution of $f(T)$ theory which is obtained from an approximate quadratic correction, and thus it is expected to hold for every realistic deviation from General Relativity. Quantifying the deviation by a single parame

Shulei QU, Zhenguo Gao, Xiaoxiao Wu, Yuanyuan Qiu

Drowsy driving represents a major contributor to traffic accidents, and the implementation of driver drowsy driving detection systems has been proven to significantly reduce the occurrence of such accidents. Despite the development of numerous drowsy driving detection algorithms, many of them impose specific prerequisites such as the availability of complete

Wan Xu, Tianyu Huang, Tianyu Qu, Guanglei Yang

Few-shot class-incremental learning (FSCIL) aims to mitigate the catastrophic forgetting issue when a model is incrementally trained on limited data. However, many of these works lack effective exploration of prior knowledge, rendering them unable to effectively address the domain gap issue in the context of 3D FSCIL, thereby leading to catastrophic forgetti

Huanjing Yue, Zifan Cui, Kun Li, Jingyu Yang

Dual-lens super-resolution (SR) is a practical scenario for reference (Ref) based SR by utilizing the telephoto image (Ref) to assist the super-resolution of the low-resolution wide-angle image (LR input). Different from general RefSR, the Ref in dual-lens SR only covers the overlapped field of view (FoV) area. However, current dual-lens SR methods rarely ut

Valeri V. Makarov, Alexey Goldin

(Abridged) Planets are surrounded by fractal surfaces (traditionally called Hill spheres), separating the inner zones of long-term stable orbital motion of their satellites from the outer space where the gravitational pull from the Sun takes over. Through this surface, external minor bodies in trajectories loosely co-orbital to a planet can be stochastically

Jialiang Hu, Jing Ye, Yuhao Chen, Zhixing Mei

We propose a mechanism for the excitation of large-scale quasi-periodic fast-propagating magnetoacoustic (QFP) waves observed on both sides of the coronal mass ejection (CME). Through a series of numerical experiments, we successfully simulated the quasi-static evolution of the equilibrium locations of the magnetic flux rope in response to the change of the

Zhao Lyu, Wai Ming Tai, Mladen Kolar, Bryon Aragam

Despite numerous years of research into the merits and trade-offs of various model selection criteria, obtaining robust results that elucidate the behavior of cross-validation remains a challenging endeavor. In this paper, we highlight the inherent limitations of cross-validation when employed to discern the structure of a Gaussian graphical model. We provid

Ergun Akleman, Youyou Wang, Ozgur Gonen

In this paper, we present a framework to represent mock 3D objects and scenes, which are not 3D but appear 3D. In our framework, each mock-3D object is represented using 2D non-conservative vector fields and thickness information that are mapped on 2-complexes. Mock-3D scenes are simply scenes consisting of more than one mock-3D object. We demonstrated that

Zexiang Liu, Necmiye Ozay, Eduardo D. Sontag

Linear immersions (such as Koopman eigenfunctions) of a nonlinear system have wide applications in prediction and control. In this work, we study the properties of linear immersions for nonlinear systems with multiple omega-limit sets. While previous research has indicated the possibility of discontinuous one-to-one linear immersions for such systems, it has

Liang Zhao, Xiachong Feng, Xiaocheng Feng, Weihong Zhong

Built upon the Transformer, large language models (LLMs) have captured worldwide attention due to their remarkable abilities. Nevertheless, all Transformer-based models including LLMs suffer from a preset length limit and can hardly generalize from short training sequences to longer inference ones, namely, they cannot perform length extrapolation to handle l

Tomasz R. Działa

We introduce the Collatz-Weyl Generators, a family of uniform pseudorandom number generators (PRNGs) which are based on generalized Collatz mappings, derived from the Collatz conjecture and Weyl sequences. The high-quality statistical properties of our generators is demonstrated by the fact that they pass stringent randomness tests used by the research and s

Qihang Ma, Kai Leong Chong, Feng Feng, Jianhua Zhang

The high-order Target ENO (TENO) scheme, known for its innovative weighting strategy, has demonstrated strong potential for complex flow predictions. This study extends the TENO weighting approach to develop non-oscillatory central TENO (CTENO and CTENOZ) family schemes for unstructured meshes. The CTENO schemes employ compact directional stencils, which inc

Kathrin Kromer, Chunhai Lyu, Jacek Bieroń, Menno Door

The atomic mass of uranium-238 has been determined to be $238.050\,787\,618(15)\,\text{u}$, improving the literature uncertainty by two orders of magnitude. It is obtained from a measurement of the mass ratio of $^{238}$U$^{47+}$ and $^{132}$Xe$^{26+}$ ions with an uncertainty of $3.5\times 10^{-12}$. The measurement was carried out with the Penning-trap mas

Necip Enes Gengec, Ergin Tari, Ulas Bagci

This study presents an innovative approach for automatic road detection with deep learning, by employing fusion strategies for utilizing both lower-resolution satellite imagery and GPS trajectory data, a concept never explored before. We rigorously investigate both early and late fusion strategies, and assess deep learning based road detection performance us

Sri Satwika Adusumalli, Kathaa Senapati, Shivam Singh, Ayan Khan

We analyze the surface tension in ultra-cold atomic gases in a quasi one-dimensional and one-dimensional geometry. In recent years, experimental observations have confirmed the ``clustering of atoms" to form droplets in ultra-cold atomic gases and the emergence of this new phase is attributed to the beyond mean-field interaction. However, two decades earlier

Dharam Vir Ahluwalia, G. B. de Gracia, Julio M. Hoff da Silva, Cheng-Yang Lee

Not all complete set of spinors can be used as expansion coefficients of a quantum field. In fact, Steven Weinberg established the uniqueness of Dirac spinors for this purpose provided: (a) one paid due attention to the multiplicative phases for each of the spinors, and (b) one paired these to creation and annihilation operators in a specific manner. This is

Bouchra Bensiali, Salma Lahbabi, Abdallah Maichine, Othmane Mirinioui

This paper studies DFT models for homogeneous 1D materials in the 3D space. It follows our previous work about DFT models for homogeneous 2D materials in 3D. We show how to reduce the problem from a 3D energy functional to a 2D energy functional. The kinetic energy is treated as in the 2D case by diagonilizing admissible states, and writing the kinetic energ

Yao Yuan

Let $M(d,\chi)$ be the moduli space of semistable 1-dimensional sheaves supported at curves of degree $d$ on $\mathbb{P}^2$, with Euler characteristic $\chi$. We have the Hilbert-Chow morphism $\pi: M(d,\chi)\rightarrow |dH|$ sending each sheaf to its support. We study the perverse filtration on $H^*(M(d,\chi),\mathbb{Q})$ via map $\pi$, especially the P=C c

A. Kerbizi, L. Lönnblad, A. Martin

The quark spin effects are introduced for the first time in the string fragmentation routine of the Pythia 8 Monte Carlo event generator for the simulation of $e^+e^-$ annihilation to hadrons. To describe the spin effects the string+${}^3P_0$ model of polarized hadronization with emissions of pseudoscalar and vector mesons is used. The spin effects are activ

Anastasia V. Vikulova

In this paper we find the largest automorphism group of a smooth cubic surface over any finite field of characteristic $2.$ We prove that if the order of the field is a power of $4,$ then the automorphism group of maximal order of~a~smooth cubic surface over this field is $\mathrm{PSU}_4(\mathbb{F}_2).$ If the order of the field of characteristic $2$ is not

Barış Can Çam, Kemal Öksüz, Fehmi Kahraman, Zeynep Sonat Baltacı

This paper introduces Generalized Mask-aware Intersection-over-Union (GmaIoU) as a new measure for positive-negative assignment of anchor boxes during training of instance segmentation methods. Unlike conventional IoU measure or its variants, which only consider the proximity of anchor and ground-truth boxes; GmaIoU additionally takes into account the segmen

Chandan Agrawal, Ashish Papanai, Jerome White

This paper describes and evaluates a multistage approach to AI deployment. Each stage involves a more accurate method of inference, yet engaging each comes with an increasing cost. In outlining the architecture, we present a method for quantifying model uncertainty that facilitates confident deferral decisions. The architecture is currently under active depl

Jiacheng Ruan, Jingsheng Gao, Mingye Xie, Suncheng Xiang

Recently, Visual Transformer (ViT) has been extensively used in medical image segmentation (MIS) due to applying self-attention mechanism in the spatial domain to modeling global knowledge. However, many studies have focused on improving models in the spatial domain while neglecting the importance of frequency domain information. Therefore, we propose Multi-

Matvei Anoshin, Asel Sagingalieva, Christopher Mansell, Dmitry Zhiganov

The drug design process currently requires considerable time and resources to develop each new compound that enters the market. This work develops an application of hybrid quantum generative models based on the integration of parametrized quantum circuits into known molecular generative adversarial networks, and proposes quantum cycle architectures that impr

Ho Man Kwan, Shenghui Song

Recently, innovative model aggregation methods based on knowledge distillation (KD) have been proposed for federated learning (FL). These methods not only improved the robustness of model aggregation over heterogeneous learning environment, but also allowed training heterogeneous models on client devices. However, the scalability of existing methods is not s

Peter Rosenberg, Efstratios Manousakis

Beginning from the conventional square-lattice nearest-neighbor antiferromagnetic Heisenberg model, we allow the $J_x$ and $J_y$ couplings to be anisotropic, with their values depending on the bond orientation. The emergence of anisotropic, bond-dependent, couplings should be expected to occur naturally in most antiferromagnetic compounds which undergo struc

Anas Emad

Measurements of atmosphere-surface exchange are largely limited by the availability of fast-response gas analyzers; this limitation hampers our understanding of the role of terrestrial ecosystems in atmospheric chemistry and global change. Current micrometeorological methods, compatible with slow-response gas analyzers, are difficult to implement, or rely on

Francesco Sisini

Physical theories must stem from observation. The possibility that perceived events are simulated, not real, raises a crucial dilemma about the credibility of known physics, known as the simulation hypothesis. To analyze this hypothesis in deterministic and mechanistic terms, an observer is conceptually developed, whose internal state depends on external eve

Maëliss Jallais, Marco Palombo

This work proposes $\mu$GUIDE: a general Bayesian framework to estimate posterior distributions of tissue microstructure parameters from any given biophysical model or MRI signal representation, with exemplar demonstration in diffusion-weighted MRI. Harnessing a new deep learning architecture for automatic signal feature selection combined with simulation-ba

Ilia Krasikov, Yehuda Roditty, Bhalchandra D. Thatte

Harary and Lauri conjectured that the class reconstruction number of trees is 2, that is, each tree has two unlabelled vertex-deleted subtrees that are not both in the deck of any other tree. We show that each tree $T$ can be reconstructed up to isomorphism given two of its unlabelled subgraphs $T-u$ and $T-v$ under the assumption that $u$ and $v$ are chosen

Chen Qian, Yufan Dang, Jiahao Li, Wei Liu

Recent advancements in large language models (LLMs) have brought significant changes to various domains, especially through LLM-driven autonomous agents. A representative scenario is in software development, where LLM agents demonstrate efficient collaboration, task division, and assurance of software quality, markedly reducing the need for manual involvemen

Xutan Peng, Yi Zhang, Dejia Peng, Jiafa Zhu

Run-Length Encoding (RLE) is one of the most fundamental tools in data compression. However, its compression power drops significantly if there lacks consecutive elements in the sequence. In extreme cases, the output of the encoder may require more space than the input (aka size inflation). To alleviate this issue, using combinatorics, we quantify RLE's spac

Jonathan Sterling

We present a survey of the two-dimensional and tensorial structure of the lifting doctrine in constructive domain theory, i.e. in the theory of directed-complete partial orders (dcpos) over an arbitrary elementary topos. We establish the universal property of lifting of dcpos as the Sierpi\'nski cone, from which we deduce (1) that lifting forms a Kock-Z\"obe

Deisiane Lopes Gonçalves, Bhalchandra D. Thatte

Kelly's lemma is a basic result on graph reconstruction. It states that given the deck of a graph $G$ on $n$ vertices, and a graph $F$ on fewer than $n$ vertices, we can count the number of subgraphs of $G$ that are isomorphic to $F$. Moreover, for a given card $G-v$ in the deck, we can count the number of subgraphs of $G$ that are isomorphic to $F$ and that

Qiumeng Li, Haibo Lin, Sibei Yang

Let $n\in\mathbb{N}$ and ${\alpha}\in(0,\min\{2,n\})$. For any $a\in[a^\ast,\infty)$, the fractional Schr\"odinger operator $L_\alpha$ is defined by \begin{equation*} L_\alpha:=(-\Delta)^{{\alpha}/2}+a{|x|}^{-{\alpha}}, \end{equation*} where $a^*:=-{\frac{2^{\alpha}{\Gamma}((d+{\alpha})/4)^2}{{\Gamma}((d-{\alpha})/4)^2}}$. Let $\gamma\in[0,\frac{\alpha}{n})$

Alexei V. Filippenko

I review the use of Type Ia supernovae (SNe Ia) in the 1998 discovery of the accelerating expansion of the Universe, as well as the subsequent use of SNe Ia to study the expansion history in more detail, determine the equation-of-state parameter w, and measure the current value of the Hubble constant. This is the lightly edited transcript of a lecture given

Štěpán Šmíd, Roberto Bondesan

In this work, we consider a fundamental task in quantum many-body physics - finding and learning ground states of quantum Hamiltonians and their properties. Recent works have studied the task of predicting the ground state expectation value of sums of geometrically local observables by learning from data. For short-range gapped Hamiltonians, a sample complex

Jason Chun Lok Li, Chang Liu, Binxiao Huang, Ngai Wong

Existing approaches to Implicit Neural Representation (INR) can be interpreted as a global scene representation via a linear combination of Fourier bases of different frequencies. However, such universal basis functions can limit the representation capability in local regions where a specific component is unnecessary, resulting in unpleasant artifacts. To th

Daiki Suenaga, Kotaro Murakami, Etsuko Itou, Kei Iida

We construct an extended version of the linear sigma model in such a way as to describe spin-$1$ hadrons as well as spin-$0$ hadrons in two-color QCD (QC$_2$D) by respecting the Pauli-G\"{u}rsey $SU(4)$ symmetry. Within a mean-field approximation, we therefrom examine a mass spectrum of the spin-$1$ hadrons at finite quark chemical potential ($\mu_q$) and ze

Eunseop Kim, Steven N. MacEachern, Mario Peruggia

Bayesian inference with empirical likelihood faces a challenge as the posterior domain is a proper subset of the original parameter space due to the convex hull constraint. We propose a regularized exponentially tilted empirical likelihood to address this issue. Our method removes the convex hull constraint using a novel regularization technique, incorporati

Junbeom Ko, Bogeun Gwak

We herein investigate the universal relation proposed by Goon and Penco in de Sitter black holes with electric charge or angular momentum. Our analysis focuses on the cosmological horizon, which only exists in de Sitter and Nariai spacetimes. Because the relation is given in a general case, the overall relationship may be valid. However, we elucidate the det

Le Cong Khoo, Anwitaman Datta

This study delves into the media analysis of China's ambitious Belt and Road Initiative (BRI), which, in a polarized world, and furthermore, owing to the very polarizing nature of the initiative itself, has received both strong criticisms and conversely positive coverage in media from across the world. In that context, Hong Kong's dynamic media environment,

Javier Fumanal-Idocin, Zdenko Takac, Lubomira Horanska, Thiago da Cruz Asmus

Intervals are a popular way to represent the uncertainty related to data, in which we express the vagueness of each observation as the width of the interval. However, when using intervals for this purpose, we need to use the appropriate set of mathematical tools to work with. This can be problematic due to the scarcity and complexity of interval-valued funct

Yongqiang Du, Xin Hua, Zhengeng Zhao, Xiaoran Sun

Random numbers play a crucial role in numerous scientific applications. Source-independent quantum random number generators (SI-QRNGs) can offer true randomness by leveraging the fundamental principles of quantum mechanics, eliminating the need for a trusted source. Silicon photonics shows great promise for QRNG due to its benefits in miniaturization, cost-e

Aritra Dutta, G Suseela, Asmita Sood

Multi-modal image stitching can be a difficult feat. That's why, in this paper, we've devised a unique and comprehensive image-stitching pipeline that taps into OpenCV's stitching module. Our approach integrates feature-based matching, transformation estimation, and blending techniques to bring about panoramic views that are of top-tier quality - irrespectiv

Valentin Ovsienko, Emmanuel Pedon

$q$-deformed real numbers are power series with integer coefficients. We study Stieltjes and Jacobi type continued fraction expansions of $q$-deformed real numbers and find many new examples of such continued fractions. We also investigate the corresponding sequences of Hankel determinants and find an infinite family of power series for which several of the

Dragan Marković, Mihailo Čubrović

We analyze the time-dependent free energy functionals of the semiclassical one-dimensional Bose-Hubbard chain. We first review the weakly chaotic dynamics and the consequent early-time anomalous diffusion in the system. The anomalous diffusion is robust, appears with strictly quantized coefficients, and persists even for very long chains (more than hundred s

Michael Kohler, Adam Krzyzak

One of the most recent and fascinating breakthroughs in artificial intelligence is ChatGPT, a chatbot which can simulate human conversation. ChatGPT is an instance of GPT4, which is a language model based on generative gredictive gransformers. So if one wants to study from a theoretical point of view, how powerful such artificial intelligence can be, one app

Sadek Belamfedel Alaoui, Adnane Saoud, Pushpak Jagtap, Abdalla Swikir

In this paper, we present a compositional methodology for constructing symbolic models of nonlinear interconnected impulsive systems. Our approach relies on the concept of "alternating simulation function" to establish a relationship between concrete subsystems and their symbolic models. Assuming some small-gain type conditions, we develop an alternating sim

I. Klincare, A. Lapins, M. Tamanis, R. Ferber

Rotationally-resolved Fourier-transform spectra of laser-induced fluorescence (LIF) $A^1\Sigma^+_u\sim b^3\Pi_u \rightarrow X^1\Sigma^+_g$ of K$_2$ molecules were recorded and analyzed yielding 4053 term values of spin-orbit (SO) coupled $A \sim b$ complex of $^{39}$K$_2$ isotopologue with ca 0.01 cm$^{-1}$ accuracy. Their compilation with 1739 term values f

Pratibha Kumari, Joohi Chauhan, Afshin Bozorgpour, Boqiang Huang

Medical imaging analysis has witnessed remarkable advancements even surpassing human-level performance in recent years, driven by the rapid development of advanced deep-learning algorithms. However, when the inference dataset slightly differs from what the model has seen during one-time training, the model performance is greatly compromised. The situation re

Giorgio Riva, Stefano Radrizzani, Giulio Panzani

The sustainable mobility trend touches the racing world as well, from the hybridization of Formula 1 (F1) and Le Mans Hypercars to the fully electric Formula E racing class. In this scenario, the research community is studying how to push electric racing vehicles to their limit, combining vehicle dynamics and energy management, to successfully solve the mini

Aiguo Xu, Dejia Zhang, Yanbiao Gan

The study of macro continuous flow has a long history. Simultaneously, the exploration of heat and mass transfer in small systems with a particle number of several hundred or less has gained significant interest in the fields of statistical physics and nonlinear science. However, due to absence of suitable methods, the understanding of mesoscale behavior sit

S. N. Denisov, I. I. Mokhov

The natural fluxes of CO2 and CH4 into the atmosphere from the territory of Russia in the 21st century have been analyzed using the results of calculations with the ensemble of global climate models of the international project CMIP6. Estimates of natural CO2 fluxes for Russian regions differ greatly for different models. Their values for the beginning of th

N. Aizawa, V. K. Dobrev

In the present paper we continue the project of systematic construction of invariant differential operators on the example of the non-compact algebras $sp(n,1)$. Our choice of these algebras is motivated by the fact that they belong to a narrow class of algebras, which are of split rank one, of which class the other cases were studied, some long time ago. We

Kunlun Wang, Yongyi Tang, Trung Q. Duong, Saeed R. Khosravirad

Digital twin (DT) is the recurrent and common feature in discussions about future technologies, bringing together advanced communication, computation, and artificial intelligence, to name a few. In the context of Industry 4.0, industries such as manufacturing, automotive, and healthcare are rapidly adopting DT-based development. The main challenges to date h

Hao Zhang, Qi Wang, Jun Shi, Shihui Ying

Multi-modal Magnetic Resonance Imaging (MRI) offers complementary diagnostic information, but some modalities are limited by the long scanning time. To accelerate the whole acquisition process, MRI reconstruction of one modality from highly undersampled k-space data with another fully-sampled reference modality is an efficient solution. However, the misalign

Rohit Raj Rai, Amit Awekar

Word embedding methods (WEMs) are extensively used for representing text data. The dimensionality of these embeddings varies across various tasks and implementations. The effect of dimensionality change on the accuracy of the downstream task is a well-explored question. However, how the dimensionality change affects the bias of word embeddings needs to be in

Jon Lachmann, Aliaksandr Hubin

Bayesian Generalized Nonlinear Models (BGNLM) offer a flexible nonlinear alternative to GLM while still providing better interpretability than machine learning techniques such as neural networks. In BGNLM, the methods of Bayesian Variable Selection and Model Averaging are applied in an extended GLM setting. Models are fitted to data using MCMC within a genet

Supriyo Ghosh, Chantira Boonsri, William Martin, Hugh R. A. Jones

Modal noise appears due to the non-uniform and unstable distribution of light intensity among the finite number of modes in multimode fibres. It is an important limiting factor in measuring radial velocity precisely by fibre-fed high-resolution spectrographs. The problem can become particularly severe as the fibre's core become smaller and the number of mode

Miaojie Feng, Longliang Liu, Hao Jia, Gangwei Xu

Collecting real-world optical flow datasets is a formidable challenge due to the high cost of labeling. A shortage of datasets significantly constrains the real-world performance of optical flow models. Building virtual datasets that resemble real scenarios offers a potential solution for performance enhancement, yet a domain gap separates virtual and real d

Zifan Wang, Shuvrangsu Das, Akshay Joshi, Angkur Jyoti Dipanka Shaikeea

The mechanical response of rubbers has been ubiquitously assumed to be only a function of the imposed strain. Using innovative X-ray measurements capturing the three-dimensional spatial volumetric strain fields, we demonstrate that rubbers and indeed many common engineering polymers, undergo significant local volume changes. But remarkably the overall specim

Monojit Ghosh

In this proceeding we discuss the status of the currently running experiments and the capability of the future proposed experiments to study neutrino oscillation. In particular, we discuss the current results of the accelerator-based long-baseline experiments in the standard three-flavour scenario and for a scenario where one assumes the existence of a light

Chenxi Wang, Pierre Pinson, Yi Wang

Energy forecasting is pivotal in energy systems, by providing fundamentals for operation, with different horizons and resolutions. Though energy forecasting has been widely studied for capturing temporal information, very few works concentrate on the frequency information provided by forecasts. They are consequently often limited to single-resolution applica

Marco Amelio, Simon André, Katrin Tent

It is well-known that every sharply 2-transitive group of characteristic 3 splits. Here we construct the first examples of non-split sharply 2-transitive groups in odd positive characteristic $p$, for sufficiently large primes $p$. Furthermore, we show that any group without 2-torsion can be embedded into a non-split sharply 2-transitive group of characteris