April 2023 arXiv papers — page 138

Daniel Basilewitsch, Clemens Dlaska, Wolfgang Lechner

An important aspect that strongly impacts the experimental feasibility of quantum circuits is the ratio of gate times and typical error time scales. Algorithms with circuit depths that significantly exceed the error time scales will result in faulty quantum states and error correction is inevitable. We present a comparison of the theoretical minimal gate tim

Guo Chen, Caoping Niu, Wenming Xia, Jie Zhang

Cubic gauche polynitrogen (cg-N) is an attractive high-energy density material. However, high-pressure synthesized cg-N will decompose at low-pressure and cannot exist at ambient conditions. Here, the stabilities of cg-N surfaces with and without saturations at different pressures and temperatures are investigated systematically. Pristine surfaces at 0 GPa a

Michael Gnewuch, Aicke Hinrichs, Klaus Ritter, Robin Rüßmann

We study integration and $L^2$-approximation of functions of infinitely many variables in the following setting: The underlying function space is the countably infinite tensor product of univariate Hermite spaces and the probability measure is the corresponding product of the standard normal distribution. The maximal domain of the functions from this tensor

Stephen M. Watt

The usual formulation of efficient division uses Newton iteration to compute an inverse in a related domain where multiplicative inverses exist. On one hand, Newton iteration allows quotients to be calculated using an efficient multiplication method. On the other hand, working in another domain is not always desirable and can lead to a library structure wher

Yassine Ouali, Adrian Bulat, Brais Martinez, Georgios Tzimiropoulos

Vision-Language (V-L) models trained with contrastive learning to align the visual and language modalities have been shown to be strong few-shot learners. Soft prompt learning is the method of choice for few-shot downstream adaptation aiming to bridge the modality gap caused by the distribution shift induced by the new domain. While parameter-efficient, prom

Marcel Niedermeier, Jose L. Lado, Christian Flindt

Quantum algorithms reformulate computational problems as quantum evolutions in a large Hilbert space. Most quantum algorithms assume that the time-evolution is perfectly unitary and that the full Hilbert space is available. However, in practice, the available entanglement may be limited, leading to a reduced fidelity of the quantum algorithms. To simulate th

M. H. Hooshmand

Recently, we have introduced and studied the topic of sub-indices and sub-factors of groups. During those studies, an algorithm for obtaining the sub-factors of a finite group was stated and proved, which has a particular case for calculating the transversals of subgroups. In this work, we first show that it is a complete algorithm for obtaining all transver

Ysla F. Adans, Guilherme França, José F. Gomes, Gabriel V. Lobo

The KdV hierarchy is a paradigmatic example of the rich mathematical structure underlying integrable systems and has far-reaching connections in several areas of theoretical physics. While the positive part of the KdV hierarchy is well known, in this paper we consider an affine Lie algebraic construction for its negative part. We show that the original Miura

G. Théret, D. Sugny

We study the concepts of complete positivity, positivity and non-Markovianity in a two-level open quantum system whose dynamics are governed by a time-local quantum master equation. We establish necessary and sufficient conditions on the time-dependent relaxation rates to ensure complete positivity and positivity of the dynamical map. We discuss their relati

Bowen Peng, Jianyue Xie, Bo Peng, Li Liu

The deep neural networks (DNNs) have freed the synthetic aperture radar automatic target recognition (SAR ATR) from expertise-based feature designing and demonstrated superiority over conventional solutions. There has been shown the unique deficiency of ground vehicle benchmarks in shapes of strong background correlation results in DNNs overfitting the clutt

Tao Fang, Shu Yang, Kaixin Lan, Derek F. Wong

ChatGPT, a large-scale language model based on the advanced GPT-3.5 architecture, has shown remarkable potential in various Natural Language Processing (NLP) tasks. However, there is currently a dearth of comprehensive study exploring its potential in the area of Grammatical Error Correction (GEC). To showcase its capabilities in GEC, we design zero-shot cha

Yu. M. Poluektov

Classical and quantum complex nonlinear scalar fields are considered. A new approach to the quantization of nonlinear fields and the construction of a perturbation theory with allowance for spontaneous symmetry breaking is proposed, based on the use of the relativistic model of a self-consistent field as the main approximation. The concept of a particle is a

Artem Lensky, Mingyu Hao

Introduction: The paper addresses the challenging problem of predicting the short-term realized volatility of the Bitcoin price using order flow information. The inherent stochastic nature and anti-persistence of price pose difficulties in accurate prediction. Methods: To address this, we propose a method that transforms order flow data over a fixed time int

Baiqiang Zhu, Keye Zhang, Weiping Zhang

Photon number-squeezed states are of significant value in fundamental quantum research and have a wide range of applications in quantum metrology. Most of their preparation mechanisms require precise control of quantum dynamics and are less tolerant to dissipation. We propose a mechanism that is not subject to these restraints. In contrast to common approach

Tuukka Korhonen, Konrad Majewski, Wojciech Nadara, Michał Pilipczuk

We present a data structure that for a dynamic graph $G$ that is updated by edge insertions and deletions, maintains a tree decomposition of $G$ of width at most $6k+5$ under the promise that the treewidth of $G$ never grows above $k$. The amortized update time is ${\cal O}_k(2^{\sqrt{\log n}\log\log n})$, where $n$ is the vertex count of $G$ and the ${\cal

Guo-Shuai Mao

In this paper, we mainly prove two congruence conjecture of Z.-W. Sun. Let $p\equiv3\pmod 4$ be a prime. Then $$\sum_{k=0}^{p-1}\frac{\binom{2k}k^2}{8^k}\equiv-\sum_{k=0}^{p-1}\frac{\binom{2k}k^2}{(-16)^k}\pmod{p^3}.$$ And for any odd prime $p$, if $p=x^2+y^2$ with $4|x-1, 2|y$, then $$ \sum_{k=0}^{p-1}\frac{(k+1)\binom{2k}k^2}{8^k}+\sum_{k=0}^{(p-1)/2}\frac

Pietro Antonio Grassi

We make some considerations and remarks on D=11 supergravity and its integral form. We start from the geometrical formulation of supergravity and by means of the integral form technique we provide a superspace action that reproduces (at the quadratic level) the recent formulation of supergravity in pure spinor framework. We also make some remarks on Chevalle

Jiakai Li

We prove an unoriented skein extract triangle for the real monopole Floer homology and introduce a Fr{\o}yshov-type invariant.

Max Z. Festenstein

Visual methods are of great utility in understanding and interpreting quantum mechanics at all levels of understanding. The Bloch sphere, for example, is an invaluable and widely used tool for visualising quantum dynamics of a two level qubit system. In this work we present an `octant' visualisation method for qutrits bearing similarity to the Bloch sphere,

Qian Xiao, Qizhi Li, Jinjin Liu, Yongkai Li

The Kagome material $A{\mathrm{V}}_3{\mathrm{Sb}}_5$ ($A$ = K, Rb, Cs) with geometry frustration hosts non-trivial topological electronic structures, electronic nematicity, charge density wave (CDW) and superconductivity, providing an ideal platform to study the interplay between these phases. Specifically, in pressurized- or substituted-${\mathrm{CsV}}_3{\m

Numair Sani, Atalanti A. Mastakouri, Dominik Janzing

Probabilities of Causation play a fundamental role in decision making in law, health care and public policy. Nevertheless, their point identification is challenging, requiring strong assumptions such as monotonicity. In the absence of such assumptions, existing work requires multiple observations of datasets that contain the same treatment and outcome variab

Dragan Mašulović, Maja Pech

The main problem of clone theory is to describe the clone lattice for a given basic set. For a two-element basic set this was resolved by E.L. Post, but for at least three-element basic set the full structure of the lattice is still unknown, and the complete description in general is considered to be hopeless. Therefore, it is studied by its substructures an

Ayaz Ahmed, P. Ramadevi, Shoaib Akhtar

We propose an algebraic expression for $U_q(\mathfrak{sl}_3)$ quantum $3j$ symbols (quantum Clebsch-Gordan coefficients) appearing in the decomposition of tensor product of symmetric representations. Our compact form will be useful to write the spectral parameter dependent $R$-matrix elements for any bi-partite vertex model whose edges carry states of the sy

Alberto Arcagni, Roy Cerqueti, Rosanna Grassi

This paper proposes a new class of assortativity measures for weighted and directed networks. We extend the classical Newman's degree-degree assortativity by considering nodes' attributes different from the degree. Moreover, we propose connections among the nodes through directed paths of length greater than one, thus obtaining higher-order assortativity. We

Matteo Gallone, Vieri Mastropietro

We prove that in the 2d Ising Model with a weak bidimensional quasi-periodic disorder in the interaction, the critical behavior is the same as in the non-disordered case, that is the critical exponents for the specific heat and energy-energy correlations are identical and no logarithmic corrections are present. The disorder produces a quasi-periodic modulati

Chao Xia, Xuwen Zhang

In this paper, we consider the classification problem for critical points of relative isoperimetric-type problem in the half-space. Under certain regularity assumption, we prove an Alexandrov-type theorem for the singular capillary CMC hypersurfaces in the half-space. The key ingredient is a new shifted distance function that is suitable for the study of cap

Nikolay Bobev, Junho Hong, Valentin Reys

We study the $S^1\times\Sigma_{\mathfrak g}$ topologically twisted index and the squashed sphere partition function of various 3d $\mathcal N\geq2$ holographic superconformal field theories arising from M2-branes. Employing numerical techniques in combination with well-motivated conjectures we provide compact closed-form expressions valid to all orders in th

Marko Hudomalj, Andrej Trost, Andrej Čampa

Traveling wave theory is deployed today to improve the monitoring of transmission lines in electrical power grids. Most traveling wave methods require prior knowledge of the wave propagation of the transmission line, which is a major source of error as the value changes during the operation of the line. To improve the localization of events on transmission l

Ivica Kičić, Pantelis R. Vlachas, Georgios Arampatzis, Michail Chatzimanolakis

Predictive simulations are essential for applications ranging from weather forecasting to material design. The veracity of these simulations hinges on their capacity to capture the effective system dynamics. Massively parallel simulations predict the systems dynamics by resolving all spatiotemporal scales, often at a cost that prevents experimentation. On th

Jiawei Shao, Fangzhao Wu, Jun Zhang

While federated learning is promising for privacy-preserving collaborative learning without revealing local data, it remains vulnerable to white-box attacks and struggles to adapt to heterogeneous clients. Federated distillation (FD), built upon knowledge distillation--an effective technique for transferring knowledge from a teacher model to student models--

Mark CW van Rossum

The brain is not only constrained by energy needed to fuel computation, but it is also constrained by energy needed to form memories. Experiments have shown that learning simple conditioning tasks already carries a significant metabolic cost. Yet, learning a task like MNIST to 95% accuracy appears to require at least 10^{8} synaptic updates. Therefore the br

Reynold Fregoli

We compute the Hausdorff dimension of the set of $\psi$-exactly approximable vectors, in the simultaneous case, in dimension strictly larger than $2$ and for approximating functions $\psi$ with order at infinity less than or equal to $-2$. Our method relies on the analogous result in dimension $1$, proved by Yann Bugeaud and Carlos Moreira, and a version of

Ali Erdem Banak, Tınaz Ekim, Z. Caner Taşkın

The maximum number of edges in a graph with matching number m and maximum degree d has been determined in [1] and [2], where some extremal graphs have also been provided. Then, a new question has emerged: how the maximum edge count is affected by forbidding some subgraphs occurring in these extremal graphs? In [3], the problem is solved in triangle-free grap

Jacob Badger, Stefan Henneking, Socratis Petrides, Leszek Demkowicz

This paper presents a scalable multigrid preconditioner targeting large-scale systems arising from discontinuous Petrov-Galerkin (DPG) discretizations of high-frequency wave operators. This work is built on previously developed multigrid preconditioning techniques of Petrides and Demkowicz (Comput. Math. Appl. 87 (2021) pp. 12-26) and extends the convergence

Ranjeet Kumar Tiwari, Shovan Bhaumik

Conventional Bayesian estimation requires an accurate stochastic model of a system. However, this requirement is not always met in many practical cases where the system is not completely known or may differ from the assumed model. For such a system, we consider a scenario where the measurements are transmitted to a remote location using a common communicatio

Zheng Lu, Chao Xia, Xuwen Zhang

In this paper, we introduce a notion of capillary Schwarz symmetrization in the half-space. It can be viewed as the counterpart of the classical Schwarz symmetrization in the framework of capillary problem in the half-space. A key ingredient is a special anisotropic gauge, which enables us to transform the capillary symmetrization to the convex symmetrizatio

Tim Sonnekalb, Christopher-Tobias Knaust, Bernd Gruner, Clemens-Alexander Brust

Static analysis tools come in many forms andconfigurations, allowing them to handle various tasks in a (secure) development process: code style linting, bug/vulnerability detection, verification, etc., and adapt to the specific requirements of a software project, thus reducing the number of false positives.The wide range of configuration options poses a hurd

Alexandru-Ionuţ Băbeanu, Tatiana Filatova, Jan H. Kwakkel, Neil Yorke-Smith

Agent-based modelling constitutes a versatile approach to representing and simulating complex systems. Studying large-scale systems is challenging because of the computational time required for the simulation runs: scaling is at least linear in system size (number of agents). Given the inherently modular nature of MABSs, parallel computing is a natural appro

Nicholas Pischke

We further develop the theoretical framework of proof mining, a program in mathematical logic that seeks to quantify and extract computational information from prima facie `non-computational' proofs from the mainstream mathematical literature. To that end, we establish logical metatheorems that allow for the treatment of proofs involving nonlinear semigroups

Ignacio Brevis, Ignacio Muga, David Pardo, Oscar Rodriguez

The efficient approximation of parametric PDEs is of tremendous importance in science and engineering. In this paper, we show how one can train Galerkin discretizations to efficiently learn quantities of interest of solutions to a parametric PDE. The central component in our approach is an efficient neural-network-weighted Minimal-Residual formulation, which

Anna Panagopoulou, Michele Paolino, Daniel Raho

Recently, FPGA accelerators have risen in popularity as they present a suitable way of satisfying the high-computation and low-power demands of real time applications. The modern electric transportation systems (such as aircraft, road vehicles) can greatly profit from embedded FPGAs, which incorporate both high-performance and flexibility features into a sin

Mohit Kumar Jat, Priya Tiwari, Robin Bajaj, Ishita Shitut

This letter presents our findings on the recursive band gap engineering of chiral fermions in bilayer graphene doubly aligned with hBN. By utilizing two interfering moir\'{e} potentials, we generate a supermoir\'{e} pattern which renormalizes the electronic bands of the pristine bilayer graphene, resulting in higher-order fractal gaps even at very low energi

J. Terasaki

A qualitative difference in the running sum for the nuclear matrix element of the two-neutrino double-$\beta$ decay of $^{136}$Xe was found four years ago between quasiparticle random-phase approximation (QRPA) and shell model calculations. The former result has large increase and decrease with respect to the excitation energy of the intermediate state, and

Shanghuo Li, Patricio Sanhueza, Qizhou Zhang, Garay Guido

We present the dynamical properties of 294 cores embedded in twelve IRDCs observed as part of the ASHES Survey. Protostellar cores have higher gas masses, surface densities, column densities, and volume densities than prestellar cores, indicating core mass growth from the prestellar to the protostellar phase. We find that ~80% of cores with virial parameter

Ahmed Salih, Ilaria Boscolo Galazzo, Zahra Raisi-Estabragh, Steffen E. Petersen

Explainable Artificial Intelligence (XAI) provides tools to help understanding how the machine learning models work and reach a specific outcome. It helps to increase the interpretability of models and makes the models more trustworthy and transparent. In this context, many XAI methods were proposed being SHAP and LIME the most popular. However, the proposed

Meng You, Junhui Hou

The challenge of dynamic view synthesis from dynamic monocular videos, i.e., synthesizing novel views for free viewpoints given a monocular video of a dynamic scene captured by a moving camera, mainly lies in accurately modeling the \textbf{dynamic objects} of a scene using limited 2D frames, each with a varying timestamp and viewpoint. Existing methods usua

Haochen Wang, Cilin Yan, Shuai Wang, Xiaolong Jiang

Video Instance Segmentation (VIS) aims at segmenting and categorizing objects in videos from a closed set of training categories, lacking the generalization ability to handle novel categories in real-world videos. To address this limitation, we make the following three contributions. First, we introduce the novel task of Open-Vocabulary Video Instance Segmen

Artemy Kolchinsky, Naruo Ohga, Sosuke Ito

In discrete-state Markovian systems, many important properties of correlations functions and relaxation dynamics depend on the spectrum of the rate matrix. Here we demonstrate the existence of a universal trade-off between thermodynamic and spectral properties. We show that the entropy production rate, the fundamental thermodynamic cost of a nonequilibrium s

Xianyong Ding, Xin Jin, Zhuo Chen, Xuewei Lv

Three-dimensional obstructed atomic insulators (OAIs) are characterized by the appearance of floating surface states (FSSs) at specific surfaces. Benefiting from this feature, our study here shows the presence of abundant surface-semimetal phases in 3D OAIs. The symmetries of obstructed Wannier charge centers ensure the degeneracy of such FSSs at high-symmet

Yaohou Fan

In recent years people have become increasingly reliant on social media to read news and get information, and some social media users post unsubstantiated information to gain attention. Such information is known as rumours. Nowadays, rumour detection is receiving a growing amount of attention because of the pandemic of the New Coronavirus, which has led to a

Shoeb Joarder, Mohamed Amine Chatti, Seyedemarzie Mirhashemi, Qurat Ul Ain

Research on Human-Centered Learning Analytics (HCLA) has provided demonstrations of a successful co-design process for LA tools with different stakeholders. However, there is a need for 'quick and dirty' methods to allow the low-cost design of LA indicators. Recently, Indicator Specification Cards (ISC) have been proposed to help different learning analytics

Frithjof Karsch, Marius Neumann, Mugdha Sarkar

We analyze scaling functions in the $3$-$d$, $Z(2)$, $O(2)$ and $O(4)$ universality classes and their finite size dependence using Monte Carlo simulations of improved $\phi^4$ models. Results for the scaling functions are fitted to the Widom-Griffiths form, using a parametrization also used in analytic calculations. We find good agreement on the level of sca

Johannes Mauritzen

A fundemantal and unanswered question for the widely shared goal of electrifying passenger vehicles is how the price of electricity, which can vary greatly across countries and regions, affects buying behavior. I make use of a natural experiment in Norway in the period 2021-2022 when large price differences between north and south emerged to estimate the eff

Tingyan Ma, Ligong Wang, Yang Hu

Let $G=(V(G), E(G))$ be a graph with vertex set $V(G)$ and edge set $E(G)$. For $k\geq2$ and given any subset $S\subseteq|V(G)|$ with $|S|=k$, if a graph $G$ of order $|V(G)|\geq k+1$ always has a spanning tree $T$ such that $S$ is precisely the set of leaves of $T$, then the graph $G$ is a $k$-leaf-connected graph. A graph $G$ is called Hamilton-connected i

Muhammad Abdullah Naeem

In this work, we study non-asymptotic bounds on correlation between two time realizations of stable linear systems with isotropic Gaussian noise. Consequently, via sampling from a sub-trajectory and using \emph{Talagrands'} inequality, we show that empirical averages of reward concentrate around steady state (dynamical system mixes to when closed loop system

Ranjeet Kumar Tiwari, Shovan Bhaumik

A networked system often uses a shared communication network to transmit the measurements to a remotely located estimation center. Due to the limited bandwidth of the channel, a delay may appear while receiving the measurements. This delay can be arbitrary step random, and packets are sometimes dropped during transmission as it exceeds a certain permissible

Mostafa Bendahmane, Herbert Nzeti, Jacques Tagoudjeu, Mohamed Zagour

This paper is devoted to the mathematical analysis of a nonlinear stochastic reaction-diffusion system modeling predator-prey interactions with prey-taxis and noises. Precisely, we detail the proof of the existence of weak martingale solutions by Faedo-Galerkin approximations and the stochastic compactness method. We prove the nonnegativity of solutions by a

Guillaume Sallé, Pierre-Henri Conze, Julien Bert, Nicolas Boussion

\textit{Objectives}: Data scarcity and domain shifts lead to biased training sets that do not accurately represent deployment conditions. A related practical problem is cross-modal image segmentation, where the objective is to segment unlabelled images using previously labelled datasets from other imaging modalities. \textit{Methods}: We propose a cross-moda

Ljubomir Budinski, Ossi Niemimäki, Roberto Zamora-Zamora, Valtteri Lahtinen

Basis state shift is central to many quantum algorithms, most notably the quantum walk. Efficient implementations are of major importance for achieving a quantum speedup for computational applications. We optimize the state shift algorithm by incorporating the shift in different directions in parallel. This provides a significant reduction in the depth of th

Anish Chakraborty, Rahul Maitra

The dual exponential coupled cluster (CC) theory proposed by Tribedi et al.[J. Chem. Theory Comput. 2020, 16, 10, 6317-6328] performs significantly better than the coupled cluster theory with singles and doubles excitations (CCSD) due to the implicit inclusion of high-rank excitations. The high-rank excitations are included through the action of a set of vac

Chi Zhang, Yiliang Liu, Hsiao-Hwa Chen

In this article, physical layer security (PLS) in an intelligent reflecting surface (IRS) assisted multiple-input multiple-output multiple antenna eavesdropper (MIMOME) system is studied. In particular, we consider a practical scenario without instantaneous channel state information (CSI) of the eavesdropper and assume that the eavesdropping channel is a Ray

Rebecka Winqvist, Inês Lourenco, Francesco Quinzan, Cristian R. Rojas

The contribution of this paper is a generalized formulation of correctional learning using optimal transport, which is about how to optimally transport one mass distribution to another. Correctional learning is a framework developed to enhance the accuracy of parameter estimation processes by means of a teacher-student approach. In this framework, an expert

Spencer Gessner, Erik Adli, James M. Allen, Weiming An

Plasmas are a compelling medium for particle acceleration owing to their natural ability to sustain electric fields that are orders of magnitude larger than those available in conventional radio-frequency accelerators. Plasmas are also unique amongst accelerator technologies in that they respond differently to beams of opposite charge. The asymmetric respons

Lucas Fresse, Salah Mehdi

We obtain inductive and enumerative formulas for the multiplicities of the weights of the spin module for the Clifford algebra of a Levi subalgebra in a complex semisimple Lie algebra. Our formulas involve only matrices and tableaux, and our techniques combine linear algebra, Lie theory, and combinatorics. Moreover, this suggests a relationship with complex

Himali Singh, Kumar Vijay Mishra, Arpan Chattopadhyay

Rapid advances in designing cognitive and counter-adversarial systems have motivated the development of inverse Bayesian filters. In this setting, a cognitive 'adversary' tracks its target of interest via a stochastic framework such as a Kalman filter (KF). The target or 'defender' then employs another inverse stochastic filter to infer the forward filter es

Hisashi Kasuya, Dan Popovici

We propose and investigate two types, the latter with two variants, of notions of partial hyperbolicity accounting for several classes of compact complex manifolds behaving hyperbolically in certain directions, defined by a vector subbundle of the holomorphic tangent bundle, but not necessarily in the other directions. A key role is played by certain entire

Chandu Jayawardhana, Thushan Sivalingam, Nurul Huda Mahmood, Nandana Rajatheva

Effective resource allocation is a crucial requirement to achieve the stringent performance targets of ultra-reliable low-latency communication (URLLC) services. Predicting future interference and utilizing it to design efficient interference management algorithms is one way to allocate resources for URLLC services effectively. This paper proposes an empiric

Peng Zhao, David Hilditch, Juan A. Valiente Kroon

We consider the formation of trapped surfaces in the evolution of the Einstein-scalar field system without symmetries. To this end, we follow An's strategy to analyse the formation of trapped surfaces in vacuum and for the Einstein-Maxwell system. Accordingly, we set up a characteristic initial value problem (CIVP) for the Einstein-Scalar system with initial

Andreas Crivellin

I provide a (personal) review of the current hints for physics beyond the Standard Model, called ``anomalies'', obtained both at the intensity frontier (flavour and electroweak precision observables) and in direct LHC searches. This includes the deviations from the Standard Model predictions in semi-leptonic $B$ decays, the anomalous magnetic moment of the m

Molham Alsakati, Charlie Pettersson, Sebastian Max, Vishnu Narayanan Moothedath

Since its first release in the late 1990s, Wi-Fi has been updated to keep up with evolving user needs. Recently, Wi-Fi and other radio access technologies have been pushed to their edge when serving Augmented Reality (AR) applications. AR applications require high throughput, low latency, and high reliability to ensure a high-quality user experience. The 802

D. Marcuzzi, V. Toigo, M. Boldrin, G. Chitarin

ITER envisages the use of two heating neutral beam injectors plus an optional one as part of the auxiliary heating and current drive system. The 16.5 MW expected neutral beam power per injector is several notches higher than worldwide existing facilities. A Neutral Beam Test Facility (NBTF) was established at Consorzio RFX, exploiting the synergy of two test

Jawher Jerray, Laurent Fribourg

Methods based on "(Jacobian) matrix measure" to show the convergence of a dynamical system to a limit cycle (LC), generally assume that the measure is negative everywhere on the LC. We relax this assumption by assuming that the matrix measure is negative "on average" over one period of LC. Using an approximate Euler trajectory, we thus present a method that

Arianna Crippa, Lena Funcke, Tobias Hartung, Beate Heinemann

The LUXE experiment is a new experiment in planning in Hamburg, which will study Quantum Electrodynamics at the strong-field frontier. LUXE intends to measure the positron production rate in this unprecedented regime by using, among others, a silicon tracking detector. The large number of expected positrons traversing the sensitive detector layers results in

Yao Chen, Wensheng Gan, Gengsen Huang, Yongdong Wu

DNA motif discovery is an important issue in gene research, which aims to identify transcription factor binding sites (i.e., motifs) in DNA sequences to reveal the mechanisms that regulate gene expression. However, the phenomenon of data silos and the problem of privacy leakage have seriously hindered the development of DNA motif discovery. On the one hand,

Dennis Adelhütte, Frauke Liers

Gamma uncertainty sets have been introduced for adjusting the degree of conservatism of robust counterparts of (discrete) linear programs. The contribution of this paper is a generalization of this approach to (mixed integer) nonlinear optimization programs. We focus on the cases in which the uncertainty is linear or concave but also derive formulations for

James Dannatt, Ian R. Petersen

In this paper, we present a strictly negative imaginary state feedback control methodology for relative degree two negative imaginary systems such as flexible structures with collocated sensors and actuators. We show that by augmenting a nominal model with a destabilising PID controller, we can apply state feedback control to the system, resulting in a stric

Bang-Dang Pham, Phong Tran, Anh Tran, Cuong Pham

We consider the challenging task of training models for image-to-video deblurring, which aims to recover a sequence of sharp images corresponding to a given blurry image input. A critical issue disturbing the training of an image-to-video model is the ambiguity of the frame ordering since both the forward and backward sequences are plausible solutions. This

Frances Y. Kuo, Weiwen Mo, Dirk Nuyens, Ian H. Sloan

The kernel interpolant in a reproducing kernel Hilbert space is optimal in the worst-case sense among all approximations of a function using the same set of function values. In this paper, we compare two search criteria to construct lattice point sets for use in lattice-based kernel approximation. The first candidate, $\calP_n^*$, is based on the power funct

Ting-Qi Yan, Wen-Xuan Zhang, Duojie Jia

Inspired by the observation of the $X(6900)$ by LHCb and the $X(6600)$ (with mass $6552\pm 10$ $\pm 12$ MeV) recently by CMS and ATLAS experiments of the LHC in the di-$J/\Psi $ invariant mass spectrum, we systemically study masses of all ground-state configurations of the hidden heavy-flavor tetraquarks $q_{1}Q_{2}\bar{q}_{3}\bar{Q}_{4}$ and $Q_{1}Q_{2}\bar

Ge-Hui Zhu, Ying-Li Wu, Jia-Liang Wan, Xiao-Qin Yu

A new nonlinear magnetothermal effect, namely unidirectional Seebeck effect(USE), has been recently reported in magnetic/nonmagnetic topological insulator (TI) heterostructure and is ascribed to the asymmetry magnon scattering. Here, we show a new mechanism to generate USE in the Rashba two dimensional electron gas (2DEG), in which the magnetism or magnetic

Wuwei Ren, Siyuan Shen, Linlin Li, Shengyu Gao

Light scattering imposes a major obstacle for imaging objects seated deeply in turbid media, such as biological tissues and foggy air. Diffuse optical tomography (DOT) tackles scattering by volumetrically recovering the optical absorbance and has shown significance in medical imaging, remote sensing and autonomous driving. A conventional DOT reconstruction p

Ahmed Jafar, Omar Ajebbar, Elhoucien Elqorachi

Let $S$ be a semigroup and $z_{0}$ a fixed element in $S.$ We determine the complex-valued solutions of the following Kannappan-sine addition law $f(xyz_{0})=f(x)g(y)+f(y)g(x),x,y\in S.$

Omid Abbassi Aghda, Mohammad Javad Omidi, Hamid Saeedi-Sourck

Orthogonal Time Frequency Space (OTFS) systems face significant challenges in channel estimation due to high pilot overhead and peak-to-average power ratio (PAPR). To address these issues, we propose a two-step channel estimation method for Zero-Pad OTFS (ZP-OTFS), a modified OTFS system characterized by multiple zero rows along the delay axis. This method s

Irina Proskurina, Irina Piontkovskaya, Ekaterina Artemova

This paper investigates how Transformer language models (LMs) fine-tuned for acceptability classification capture linguistic features. Our approach uses the best practices of topological data analysis (TDA) in NLP: we construct directed attention graphs from attention matrices, derive topological features from them, and feed them to linear classifiers. We in

Hiroaki Ito, Naofumi Shimokawa, Yuji Higuchi

Dynamic lateral transport of lipids, proteins, and self-assembled structures in biomembranes plays crucial roles in diverse cellular processes. In this study, we perform a coarse-grained molecular dynamics simulation on a vesicle composed of a binary mixture of neutral and anionic lipids to investigate the lateral transport of individual lipid molecules and

ATLAS Collaboration

A search for the associated production of a heavy resonance with a top-quark or a top-antitop-quark pair, and decaying into a $t\bar{t}$ pair is presented. The search uses the data recorded by the ATLAS detector in $pp$ collisions at $\sqrt{s}= 13$ TeV at the Large Hadron Collider during the years 2015-2018, corresponding to an integrated luminosity of 139 f

Junhua Liu, Kwan Hui Lim, Kristin L. Wood, Menglin Li

Itinerary recommendation is a complex sequence prediction problem with numerous real-world applications. This task becomes even more challenging when considering the optimization of multiple user queuing times and crowd levels, as well as numerous involved parameters, such as attraction popularity, queuing time, walking time, and operating hours. Existing so

Marcin Nowakowski

In both quantum mechanics and relativity theory, the concept of the observer plays a critical role. However, there is no consensus on the definition of observer in these theories. Following Einstein's thought experiments, one could ask: What would it look like to sit inside a photon or to be a photon? And what type of observer could represent this more globa

Amir Nassereldine, Safaa Diab, Mohammed Baydoun, Kenneth Leach

In modern computing environments, users may have multiple systems accessible to them such as local clusters, private clouds, or public clouds. This abundance of choices makes it difficult for users to select the system and configuration for running an application that best meet their performance and cost objectives. To assist such users, we propose a predict

Mahmoud Raeisi, Asil Koc, Ibrahim Yildirim, Ertugrul Basar

This paper investigates the effect of various antenna array structures, i.e., uniform linear array (ULA), uniform rectangular array (URA), uniform circular array (UCA), and concentric circular array (CCA), on cluster index modulation (CIM) enabled massive multiple-input multiple-output (mMIMO) millimeter-wave (mmWave) communications systems. As the CIM techn

Michael Hammer, Min-Kai Lin

Past computational studies of planet-induced vortices have shown that the dust asymmetries associated with these vortices can be long-lived enough that they should be much more common in mm/sub-mm observations of protoplanetary discs, even though they are quite rare. Observed asymmetries also have a range of azimuthal extents from compact to elongated even t

Josu C. Aurrekoetxea, Katy Clough, Francesco Muia

We study the non-perturbative evolution of inflationary fluctuations during preheating using fully non-linear general-relativistic field-theory simulations. We choose a single-field inflationary model that is consistent with observational constraints and start the simulations at the end of inflation with fluctuations both in the field and its conjugate momen

Jubo Yu, Tianxiang Ren, Shihui Guo, Fengyi Fang

In this paper, we follow a data-centric philosophy and propose a novel motion annotation method based on the inherent representativeness of motion data in a given dataset. Specifically, we propose a Representation-based Representativeness Ranking R3 method that ranks all motion data in a given dataset according to their representativeness in a learned motion

Jason L. Sanders

Gaia DR3 parallaxes are used to calibrate preliminary period--luminosity relations of O-rich Mira variables in the 2MASS $J$, $H$ and $K_s$ bands using a probabilistic model accounting for variations in the parallax zeropoint and underestimation of the parallax uncertainties. The derived relations are compared to those measured for the Large and Small Magell

Duo Xu, Jonathan C. Tan, Chia-Jung Hsu, Ye Zhu

We introduce the state-of-the-art deep learning Denoising Diffusion Probabilistic Model (DDPM) as a method to infer the volume or number density of giant molecular clouds (GMCs) from projected mass surface density maps. We adopt magnetohydrodynamic simulations with different global magnetic field strengths and large-scale dynamics, i.e., noncolliding and col

Ngoc-Bao Nguyen, Keshigeyan Chandrasegaran, Milad Abdollahzadeh, Ngai-Man Cheung

Model inversion (MI) attacks aim to infer and reconstruct private training data by abusing access to a model. MI attacks have raised concerns about the leaking of sensitive information (e.g. private face images used in training a face recognition system). Recently, several algorithms for MI have been proposed to improve the attack performance. In this work,

D. Filippas, C. Peltekis, G. Dimitrakopoulos, C. Nicopoulos

The acceleration of deep-learning kernels in hardware relies on matrix multiplications that are executed efficiently on Systolic Arrays (SA). To effectively trade off deep-learning training/inference quality with hardware cost, SA accelerators employ reduced-precision Floating-Point (FP) arithmetic. In this work, we demonstrate the need for new pipeline orga

Gilles Pisier

This note is motivated by Kirchberg's conjecture that the local lifting property (LLP) implies the lifting property (LP) for $C^*$-algebras. The author recently constructed by a "local" method an example of $C^*$-algebra with the LLP and the weak expectation property (WEP) which might be a counterexample. We give here several equivalent conditions all equiva

Stefano Montanelli, Francesco Periti

Semantic Shift Detection (SSD) is the task of identifying, interpreting, and assessing the possible change over time in the meanings of a target word. Traditionally, SSD has been addressed by linguists and social scientists through manual and time-consuming activities. In the recent years, computational approaches based on Natural Language Processing and wor

Yixuan Weng, Minjun Zhu, Fei Xia, Bin Li

Language models' (LMs) proficiency in handling deterministic symbolic reasoning and rule-based tasks remains limited due to their dependency implicit learning on textual data. To endow LMs with genuine rule comprehension abilities, we propose "Neural Comprehension" - a framework that synergistically integrates compiled neural networks (CoNNs) into the standa