July 2022 arXiv papers — page 4

Ruoshui Wang, Timothy H. Hsieh, Guifre Vidal

We use matrix product techniques to investigate the performance of two algorithms for obtaining the ground state of a quantum many-body Hamiltonian $H = H_A + H_B$ in infinite systems. The first algorithm is a generalization of the quantum approximate optimization algorithm (QAOA) and uses a quantum computer to evolve an initial product state into an approxi

Cristian F. Coletti, Nevena Marić, Pablo M. Rodriguez

Habitat loss is one of the biggest threats facing plant species nowadays. We formulate a simple mathematical model of seed dispersal on reduced habitats to discuss survival of the species in relation to the habitat size and seeds production rate. Seeds get dispersed around the mother plant via several agents in a random way. In our model seeds landing sites

Francisco Zanartu, Christoph Treude, Bruno Cartaxo, Hudson Silva Borges

GitHub is the largest host of open source software on the Internet. This large, freely accessible database has attracted the attention of practitioners and researchers alike. But as GitHub's growth continues, it is becoming increasingly hard to navigate the plethora of repositories which span a wide range of domains. Past work has shown that taking the appli

Zhongxia Yan, Abdul Rahman Kreidieh, Eugene Vinitsky, Alexandre M. Bayen

Emerging vehicular systems with increasing proportions of automated components present opportunities for optimal control to mitigate congestion and increase efficiency. There has been a recent interest in applying deep reinforcement learning (DRL) to these nonlinear dynamical systems for the automatic design of effective control strategies. Despite conceptua

Peng Yin, Weijie Du, Wei Zuo, Xingbo Zhao

We employ the non-perturbative time-dependent basis function (tBF) approach to solve for the sub-Coulomb barrier scattering of the deuteron projectile on the $^{208}$Pb target. Specifically, we treat the target as a source of a strong external Coulomb field that induces higher-order effects in electric-dipole excitations of the deuteron projectile including

Xavier Bekaert, Niels Kowalzig, Paolo Saracco

We extend a theorem, originally formulated by Blattner-Cohen-Montgomery for crossed products arising from Hopf algebras weakly acting on noncommutative algebras, to the realm of left Hopf algebroids. Our main motivation is an application to universal enveloping algebras of projective Lie-Rinehart algebras: for any given curved (resp. flat) connection, that i

CMS Collaboration

A search is presented for the Higgs boson decay to a pair of electrons (e$^+$e$^-$) in proton-proton collisions at $\sqrt{s}$ = 13 TeV. The data set was collected with the CMS experiment at the LHC between 2016 and 2018, corresponding to an integrated luminosity of 138 fb$^{-1}$. The analysis uses event categories targeting Higgs boson production via gluon f

Mohammad Ghafari, Konstantin Rubinov, Mohammad Mehdi Pourhashem K

Software developers study and reuse existing source code to understand how to properly use application programming interfaces (APIs). However, manually finding sufficient and adequate code examples for a given API is a difficult and a time-consuming activity. Existing approaches to find or generate examples assume availability of a reasonable set of client c

Lijie Cui, Chuandong Lin

The lattice gas automaton (LGA) is proposed for a closed economic market of agents with heterogeneous saving interests. There are two procedures in the standard LGA, i.e., "propagation" + "transaction". If the propagation step is removed and the transaction is conducted among all agents, the LGA reduces to a more simplified kinetic model. In addition, two de

Xiaoyi Cai, Brent Schlotfeldt, Kasra Khosoussi, Nikolay Atanasov

This paper considers the problem of safely coordinating a team of sensor-equipped robots to reduce uncertainty about a dynamical process, where the objective trades off information gain and energy cost. Optimizing this trade-off is desirable, but leads to a non-monotone objective function in the set of robot trajectories. Therefore, common multi-robot planne

Philip Relton, Andrea Virtuoso, Sophie Bini, Vivien Raymond

Standard detection and analysis techniques for transient gravitational waves make the assumption that detector data contains, at most, one signal at any time. As detectors improve in sensitivity, this assumption will no longer be valid. In this paper we examine how current search techniques for transient gravitational waves will behave under the presence of

Vincenzo Di Gennaro

Fix integers $r\geq 4$ and $i\geq 2$ (for $r=4$ assume $i\geq 3$). Assuming that the rational number $s$ defined by the equation $\binom{i+1}{2}s+(i+1)=\binom{r+i}{i}$ is an integer, we prove an upper bound for the genus of a reduced and irreducible complex projective curve in $\mathbb P^r$, of degree $d\gg s$, not contained in hypersurfaces of degree $\leq

Ionut Chifan, Daniel Drimbe, Adrian Ioana

In the first part of the paper we survey several results from Popa's deformation/rigidity theory on the classification of tensor product decompositions of large natural classes of II$_1$ factors. Using a m\'elange of techniques from deformation/rigidity theory, model theory, and the recent works \cite{CIOS21,CDI22} we highlight an uncountable family of exist

Pascal Marc André, Quentin Stiévenart, Mohammad Ghafari

WebAssembly is a growing technology to build cross-platform applications. We aim to understand the security issues that developers encounter when adopting WebAssembly. We mined WebAssembly questions on Stack Overflow and identified 359 security-related posts. We classified these posts into 8 themes, reflecting developer intentions, and 19 topics, representin

Yaofang Hu, Wanjie Wang

Community detection is an important problem when processing network data. Traditionally, this is done by exploiting the connections between nodes, but connections can be too sparse to detect communities in many real datasets. Node covariates can be used to assist community detection; see Binkiewicz et al. (2017); Weng and Feng (2022); Yan and Sarkar (2021);

Dylan G. Stone, Carlo Bradac

In recent years, machine and quantum learning have gained considerable momentum sustained by growth in computational power and data availability and have shown exceptional aptness for solving recognition- and classification-type problems, as well as problems that require complex, strategic planning. In this work, we discuss and analyze the role machine and q

Alan Frieze, Gregory B. Sorkin

We show that with high probability we can build a Hamilton cycle after at most $1.85 n$ rounds in a particular semi-random model. In this model, in one round, we are given a {uniform random} $v\in[n]$ and then we can add an {arbitrary} edge $\{v,w\}$. Our result improves on $2.016 n$ in a recent paper of Gao, MacRury, and Pralat.

Hiromu Tanaka

Given a base point free linear system on an algebraic variety, many classes of singularities are stable under taking suitable members after enlarging the base field. We establish analogous results when the base ring is an excellent ring.

Sergei Nedelko, Vladimir Voronin

Dipole polarizabilities of light pseudoscalar mesons are calculated in the framework of the mean field approach to QCD vacuum and bosonization based on the statistical ensemble of almost everywhere homogeneous Abelian (anti-)self-dual gluon fields -- the domain model of QCD vacuum. In this approach, one derives a nonlocal effective action of meson fields whi

Kamaledin Ghiasi-Shirazi

In this paper, we highlight a profound difference between conditional statements in mathematical logic and natural languages. This difference exists even when the conditional statements are used in mathematical theorems.

Samuel Davenport, Thomas E. Nichols, Armin Schwarzman

Local maxima of random processes are useful for finding important regions and are routinely used, for summarising features of interest (e.g. in neuroimaging). In this work we provide confidence regions for the location of local maxima of the mean and standardized effect size (i.e. Cohen's d) given multiple realisations of a random process. We prove central l

Kelly W. Zhang, Omer Gottesman, Finale Doshi-Velez

In the reinforcement learning literature, there are many algorithms developed for either Contextual Bandit (CB) or Markov Decision Processes (MDP) environments. However, when deploying reinforcement learning algorithms in the real world, even with domain expertise, it is often difficult to know whether it is appropriate to treat a sequential decision making

Jackie Ayoub, Zifei Wang, Meitang Li, Huizhong Guo

Advanced driver assistance systems (ADAS) are designed to improve vehicle safety. However, it is difficult to achieve such benefits without understanding the causes and limitations of the current ADAS and their possible solutions. This study 1) investigated the limitations and solutions of ADAS through a literature review, 2) identified the causes and effect

Hamed M. Jafari, Xilin Liu, Roman Genov

Accurate temperature regulation is critical for amperometric DNA analysis to achieve high fidelity, reliability, and throughput. In this work, a 9x6 cell array of mixed-signal CMOS distributed temperature regulators for on-CMOS multi-modal amperometric DNA analysis is presented. Three DNA analysis methods are supported, including constant potential amperomet

Marta De Simone, Cecilia Ceccarelli, Claudio Codella, Brian E. Svoboda

To understand the origin of the diversity observed in exoplanetary systems, it is crucial to characterize the early stages of their formation, represented by Solar-type protostars. Likely, the gaseous chemical content of these objects directly depends on the composition of the dust grain mantles formed before the collapse. Directly retrieving the ice mantle

Nikolaos N. Vlassis, WaiChing Sun

The history-dependent behaviors of classical plasticity models are often driven by internal variables evolved according to phenomenological laws. The difficulty to interpret how these internal variables represent a history of deformation, the lack of direct measurement of these internal variables for calibration and validation, and the weak physical underpin

Hongyi Xiao, Zhekai Deng, Julio M. Ottino, Paul B. Umbanhowar

We present a continuum approach to model segregation of size-bidisperse granular materials in unsteady bounded heap flow as a prototype for modeling segregation in other time varying flows. In experiments, a periodically modulated feed rate produces stratified segregation like that which occurs due to intermittent avalanching, except with greater layer-unifo

Niklas Christoph Affolter, Béatrice de Tilière, Paul Melotti

We consider nine geometric systems: Miquel dynamics, P-nets, integrable cross-ratio maps, discrete holomorphic functions, orthogonal circle patterns, polygon recutting, circle intersection dynamics, (corrugated) pentagram maps and the short diagonal hyperplane map. Using a unified framework, for each system we prove an explicit expression for the solution as

Jiapei Zhuang, Ching-Yu Huang, Po-Yao Chang, Daw-Wei Wang

We systematically investigate the ground state phase diagram and the finite temperature phase transitions for a Rydberg-dressed Fermi gas loaded in a bilayer optical lattice. When an effective finite-ranged attraction is induced, our self-consistent mean-field calculation shows that the gapped topological ( $p$-wave) superfluids in each layer are coupled tog

Minu J. Bae

Entropic uncertainty relations are underpinning to compute the quantitative security bound in quantum cryptographic applications, such as quantum random number generation (QRNG) and quantum key distribution (QKD). All security proofs derive a relation between the information accessible to the legitimate group and the maximum knowledge that an adversary may h

Inna Entova-Aizenbud, Thorsten Heidersdorf

We study the Deligne interpolation categories $\underline{\mathrm{Rep}}(GL_{t}(\mathbb{F}_q))$ for $t\in \mathbb{C}$, first introduced by F. Knop. These categories interpolate the categories of finite dimensional complex representations of the finite general linear group $GL_n(\mathbb{F}_q)$. We describe the morphism spaces in this category via generators an

Andrés Jaramillo Puentes, Sabrina Pauli

Using tropical geometry one can translate problems in enumerative geometry to combinatorial problems. Thus tropical geometry is a powerful tool in enumerative geometry over the complex and real numbers. Results from $\mathbb{A}^1$-homotopy theory allow to enrich classical enumerative geometry questions and get answers over an arbitrary field. In the resultin

Niklas Christoph Affolter, Béatrice de Tilière, Paul Melotti

We prove an explicit expression for the solutions of the discrete Schwarzian octahedron recurrence, also known as the discrete Schwarzian KP equation (dSKP), as the ratio of two partition functions. Each one counts weighted oriented dimer configurations of an associated bipartite graph, and is equal to the determinant of a Kasteleyn matrix. This is in the sp

Haolin Pan, Yong Guo, Qinyi Deng, Haomin Yang

Self-supervised learning (SSL) has achieved remarkable performance in pretraining the models that can be further used in downstream tasks via fine-tuning. However, these self-supervised models may not capture meaningful semantic information since the images belonging to the same class are always regarded as negative pairs in the contrastive loss. Consequentl

Ruida Zhang, Yan Di, Zhiqiang Lou, Fabian Manhardt

Category-level object pose estimation aims to predict the 6D pose as well as the 3D metric size of arbitrary objects from a known set of categories. Recent methods harness shape prior adaptation to map the observed point cloud into the canonical space and apply Umeyama algorithm to recover the pose and size. However, their shape prior integration strategy bo

Ruowei Li, Lidan Wang

In this paper, we study the nonlinear Choquard equation \begin{eqnarray*} \Delta^{2}u-\Delta u+(1+\lambda a(x))u=(R_{\alpha}\ast|u|^{p})|u|^{p-2}u \end{eqnarray*} on a Cayley graph of a discrete group of polynomial growth with the homogeneous dimension $N\geq 2$, where $\alpha\in(0,N),\,p>\frac{N+\alpha}{N},\,\lambda$ is a positive parameter and $R_\alpha$ s

Roberto Dillon, Arushi

This paper describes the design process for the cybersecurity serious game 'PeriHack'. Publicly released under a CC (BY-NC-SA) license, PeriHack is a board and card game for two players or teams that simulates the struggle between a red team (attackers) and a blue team (defenders). The game requires players to explore a sample network looking for vulnerabili

Franco Aquistapace, Nicolás Vazquez, Matías Chiarpotti, Orlando Deluigi

Ductile failure is studied in a bcc HfNbTaZr High Entropy Alloy (HEA) with a pre-existing void. Using molecular dynamics simulations of uniaxial tensile tests, we explore the effect of void radius on the elastic modulus and yield stress. The elastic modulus scales with porosity as in closed-cell foams. The critical stress for dislocation nucleation as a func

Yusheng Wang, Yonghoon Ji, Hiroshi Tsuchiya, Hajime Asama

Retrieving the missing dimension information in acoustic images from 2D forward-looking sonar is a well-known problem in the field of underwater robotics. There are works attempting to retrieve 3D information from a single image which allows the robot to generate 3D maps with fly-through motion. However, owing to the unique image formulation principle, estim

Romulo Meloca, Ingrid Nunes

Performance and scalability requirements have a fundamental role in most large-scale software applications. To satisfy such requirements, caching is often used at various levels and infrastructure layers. Application-level caching -- or memoization -- is an increasingly used form of caching within the application boundaries, which consists of storing the res

Alexander Liu, Samuel Yang

Despite the progresses on pre-trained language models, there is a lack of unified frameworks for pre-trained sentence representation. As such, it calls for different pre-training methods for specific scenarios, and the pre-trained models are likely to be limited by their universality and representation quality. In this work, we extend the recently proposed M

Fu-Quan Dou, Min-Peng Han, Chuan-Cun Shu

According to the Heisenberg uncertainty principle between time and energy fluctuation, a concept of the quantum speed limit (QSL) has been established to determine the minimum evolutionary time between quantum states. Considerable theoretical and experimental efforts are invested in obtaining the QSL time bounds in various scenarios. However, it remains a lo

Sahand Tokasi

The equivalence class of absolute configurations of a system under the group of similarity transformations $Sim(3)$ is called the shape of the system. The $Sim(3)$ invariant Lagrangian of the modified Newtonian theory ensures the existence of the its law of motion on shape space. To deduce the equations of motion for a system's shape degrees of freedom from

Yao Nie, Weikui Ye

In this paper, we prove a sharp and strong non-uniqueness for a class of weak solutions to the three-dimensional magneto-hydrodynamic (MHD) system. More precisely, we show that any weak solution $(v,b)\in L^p_tL^{\infty}_x$ is non-unique in $L^p_tL^{\infty}_x$ with $1\le p<2$, which reveals the strong non-uniqueness, and the sharpness in terms of the classic

Fatemeh Akbari, Somayeh Taghizadeh, Diana Shvydka, Nicholas Niven Sperling

Purpose: Accurate electronic stopping power data is crucial for calculating radiation-induced effects in various applications, from dosimetry and radiotherapy to particle physics. In this study, Stacking Ensemble Machine Learning (EML) algorithm was developed to predict electronic stopping power for any incident ion and target combination over a wide range o

Mohit Arora, Deepankar Basu

Analyzing 5 historical and 670 contemporary input-output (IO) tables, we show that all of these IO matrices are singular. We map this phenomenon onto underlying production network topologies. While singularity trivially emerges from sectors lacking intermediate forward or backward linkages, it could frequently persist due to deeper economic properties: propo

Côme Fontaine, Malo Tarpin, Freddy Bouchet, Léonie Canet

Shell models are simplified models of hydrodynamic turbulence, retaining only some essential features of the original equations, such as the non-linearity, symmetries and quadratic invariants. Yet, they were shown to reproduce the most salient properties of developed turbulence, in particular universal statistics and multi-scaling. We set up the functional r

Sandro Franceschi, Kilian Raschel

We introduce a transient reflected Brownian motion in a multidimensional orthant, which is either absorbed at the apex of the cone or escapes to infinity. We address the question of computing the absorption probability, as a function of the starting point of the process. We provide a necessary and sufficient condition for the absorption probability to admit

Aoran Xiao, Jiaxing Huang, Dayan Guan, Kaiwen Cui

LiDAR point clouds, which are usually scanned by rotating LiDAR sensors continuously, capture precise geometry of the surrounding environment and are crucial to many autonomous detection and navigation tasks. Though many 3D deep architectures have been developed, efficient collection and annotation of large amounts of point clouds remain one major challenge

Fanrong Shi, Huailiang Li, Simon X. Yang, Xianguo Tuo

Clock skew compensation is essential for accurate time synchronization in wireless networks. However, contemporary clock skew estimation is based on inaccurate transmission time measurement, which makes credible estimation challenging. Based on one-way broadcast synchronization, this study presents a novel maximum likelihood estimation (MLE) with an innovati

Amirhosein Vedadi, Kasra Sinaei, Pezhman Abdolahnezhad, Shahriar Sheikh Aboumasoudi

Walking motion planning based on Divergent Component of Motion (DCM) and Linear Inverted Pendulum Model (LIPM) is one of the alternatives that could be implemented to generate online humanoid robot gait trajectories. This algorithm requires different parameters to be adjusted. Herein, we developed a framework to attain optimal parameters to achieve a stable

Lennart Schneider, Lennart Schäpermeier, Raphael Patrick Prager, Bernd Bischl

Hyperparameter optimization (HPO) is a key component of machine learning models for achieving peak predictive performance. While numerous methods and algorithms for HPO have been proposed over the last years, little progress has been made in illuminating and examining the actual structure of these black-box optimization problems. Exploratory landscape analys

Gongjie Zhang, Zhipeng Luo, Kaiwen Cui, Shijian Lu

Few-shot object detection has been extensively investigated by incorporating meta-learning into region-based detection frameworks. Despite its success, the said paradigm is still constrained by several factors, such as (i) low-quality region proposals for novel classes and (ii) negligence of the inter-class correlation among different classes. Such limitatio

Tianyu Lu, Liquan Chen, Junqing Zhang, Chen Chen

Key generation is a promising technique to establish symmetric keys between resource-constrained legitimate users. However, key generation suffers from low secret key rate (SKR) in harsh environments where channel randomness is limited. To address the problem, reconfigurable intelligent surfaces (RISs) are introduced to reshape the channels by controlling ma

Ivan Cheltsov, Frédéric Mangolte, Egor Yasinsky, Susanna Zimmermann

We classify birational involutions of the real projective plane up to conjugation. In contrast with an analogous classification over the complex numbers (due to E. Bertini, G. Castelnuovo, F. Enriques, L. Bayle and A. Beauville), which includes 4 different classes of involutions, we discover 12 different classes over the reals, and provide many examples when

Khyati Sharma, A. Satyanarayana Reddy

A finite group is called a CLT-group if it contains a subgroup corresponding to every divisor of the order of the group. It is said to be a Cyclic (Abelian) CLT group if it contains a cyclic (abelian) subgroup corresponding to every proper divisor of the order of the group. A natural number is said to be a CCLT (ACLT) number if every group of that order is a

Fanrong Shi, Xianguo Tuo, Lili Ran, Zhenwen Ren

Average consensus theory is intensely popular for building time synchronization in wireless sensor network (WSN). However, the average consensus-based time synchronization algorithm is based on iteration that pose challenges for efficiency, as they entail high communication cost and long convergence time in large-scale WSN. Based on the suggestion that the g

Grigori A. Karagulyan, Michael T. Lacey, Vahan A. Martirosyan

Given sequence of measure preserving transformations $\{U_k:\,k=1,2,\ldots, n\}$ on a measurable space $(X,\mu)$. We prove a.e. convergence of the ergodic means \begin{equation} \frac{1}{s_1\cdots s_{n}}\sum_{j_1=0}^{s_1-1}\cdots\sum_{j_n=0}^{s_n-1}f\left(U_1^{j_1}\cdots U_n^{j_n} x \right) \end{equation} as $\min_j s_j\to\infty $, for any function $f\in L\l

Qiang Meng, Feng Zhou

Most visual retrieval applications store feature vectors for downstream matching tasks. These vectors, from where user information can be spied out, will cause privacy leakage if not carefully protected. To mitigate privacy risks, current works primarily utilize non-invertible transformations or fully cryptographic algorithms. However, transformation-based m

Fanrong Shi, Xianguo Tuo, Simon X. Yang, Jing Lu

Accurate and fast-convergent time synchronization is very important for wireless sensor networks. The flooding time synchronization converges fast, but its transmission delay and by-hop error accumulation seriously reduce the synchronization accuracy. In this article, a rapidflooding multiple one-way broadcast time-synchronization (RMTS) protocol for large-s

Jia-Feng Pan, Jia-Jia Luo, Xi-Wen Guan

Using exact Bethe ansatz solution, we rigorously study excitation spectra of the spin-1/2 Fermi gas (called Yang-Gaudin model) with an attractive interaction. Elementary excitations of this model involve particle-hole excitations, hole excitations and adding particles in the Fermi seas of pairs and unpaired fermions. The gapped magnon excitations in spin sec

Gaia Collaboration, A. Vallenari, A. G. A. Brown, T. Prusti

We present the third data release of the European Space Agency's Gaia mission, GDR3. The GDR3 catalogue is the outcome of the processing of raw data collected with the Gaia instruments during the first 34 months of the mission by the Gaia Data Processing and Analysis Consortium. The GDR3 catalogue contains the same source list, celestial positions, proper mo

Y. Gong, X. Ma

Smoke detection has become a significant task in associated industries due to the close relationship between the petrochemical industry's smoke emission and its safety production and environmental damage. There are several production situations in the real industrial production environment, including complete combustion of exhaust gas, inadequate combustion

Anton Freund, Patrick Uftring

The uniform Kruskal theorem extends the original result for trees to general recursive data types. As shown by A. Freund, M. Rathjen and A. Weiermann, it is equivalent to $\Pi^1_1$-comprehension, over $\mathsf{RCA_0}$ with the chain antichain principle ($\mathsf{CAC}$). This result provides a connection between finite combinatorics and abstract set existence

Chuwen Zhang, Dongdong Ge, Chang He, Bo Jiang

In this paper, we propose a Dimension-Reduced Second-Order Method (DRSOM) for convex and nonconvex (unconstrained) optimization. Under a trust-region-like framework, our method preserves the convergence of the second-order method while using only curvature information in a few directions. Consequently, the computational overhead of our method remains compara

Qifeng Gao, Rui Ding, Linyuan Wang, Bin Xue

In the practical applications of computed tomography imaging, the projection data may be acquired within a limited-angle range and corrupted by noises due to the limitation of scanning conditions. The noisy incomplete projection data results in the ill-posedness of the inverse problems. In this work, we theoretically verify that the low-resolution reconstruc

A. Kit, A. Jaervinen, S. Wiesen, Y. Poels

Predictive and real-time inference capability for the upstream separatrix electron density, $n_\text{e, sep}$, is essential for design and control of core-edge integrated plasma scenarios. In this study, both supervised and semi-supervised machine learning algorithms are explored to establish direct mapping as well as indirect compressed representation of th

Xiao Yi, Yuzhou Fang, Daoyuan Wu, Lingxiao Jiang

Due to the open-source nature of the blockchain ecosystem, it is common for new blockchains to fork or partially reuse the code of classic blockchains. For example, the popular Dogecoin, Litecoin, Binance BSC, and Polygon are all variants of Bitcoin/Ethereum. These "forked" blockchains thus could encounter similar vulnerabilities that are propagated from Bit

Lennart Schneider, Florian Pfisterer, Paul Kent, Juergen Branke

Neural architecture search (NAS) has been studied extensively and has grown to become a research field with substantial impact. While classical single-objective NAS searches for the architecture with the best performance, multi-objective NAS considers multiple objectives that should be optimized simultaneously, e.g., minimizing resource usage along the valid

Fuwei Tian, Christoph Treude

Deep learning models have been successfully applied to a variety of software engineering tasks, such as code classification, summarisation, and bug and vulnerability detection. In order to apply deep learning to these tasks, source code needs to be represented in a format that is suitable for input into the deep learning model. Most approaches to representin

Simone Foa, Corrado Coppola, Giorgio Grani, Laura Palagi

Recently, the applications of the methodologies of Reinforcement Learning (RL) to NP-Hard Combinatorial optimization problems have become a popular topic. This is essentially due to the nature of the traditional combinatorial algorithms, often based on a trial-and-error process. RL aims at automating this process. At this regard, this paper focuses on the ap

A. V. Nesterenok

The collisional pumping of H$_2$O and CH$_3$OH masers in magnetohydrodynamic nondissociative C-type shocks is considered. A grid of C-type shock models with speeds in the range $5-70$ km s$^{-1}$ and preshock gas densities $n_{\rm H_2,0} = 10^4-10^7$ cm$^{-3}$ is constructed. The large velocity gradient approximation is used to solve the radiative transfer e

M. L. Pereira Júnior, L. A. Ribeiro Júnior, D. S. Galvão, J. M. De Sousa

Carbon nanoscrolls (CNSs) are nanomaterials with geometry resembling graphene layers rolled up into a spiral (papyrus-like) form. Effects of hydrogenation and temperature on the self-scrolling process of two nanoribbons interacting with a carbon nanotube (CNT) have been studied by molecular dynamics simulations for three configurations: (1) graphene/graphene

Lea Boßmann, Sören Petrat

We consider the ground state and the low-energy excited states of a system of $N$ identical bosons with interactions in the mean-field scaling regime. For the ground state, we derive an Edgeworth expansion for the fluctuations of bounded one-body operators, which yields corrections to a central limit theorem to any order in $1/\sqrt{N}$ . For suitable excite

Lei Xie, Xianghao Yu, S. H. Song

Maneuvering target sensing will be an important service of future vehicular networks, where precise velocity estimation is one of the core tasks. To this end, the recently proposed integrated sensing and communications (ISAC) provides a promising platform for achieving accurate velocity estimation. However, with one mono-static ISAC base station (BS), only t

X. R. Wang, X. C. Hu, Z. Z. Sun

Stripy states, consisting of a collection of stripy spin textures, are the precursors of skyrmion crystals (SkXs). Common belief is that stripy states and SkXs are topologically unconnected, and transitions between SkXs and stripy states are phase transitions. Here, we show that both stripy states and SkXs are skyrmion condensates and they are topologically

Hongkai Liu

In this paper, we present the differential decay distributions for $\bar B \to D^{(*)} \ell \bar{X}$ decays with a massive right-handed neutrino in the low-energy effective field theory framework and show how the massive effects of the RH neutrinos can explain the positive value of the difference in forward-backward asymmetries, $\Delta A_{\text{FB}}\equiv A

Lauro Silini

We prove that geodesic balls centered at some base point are isoperimetric in the real hyperbolic space $H_{\mathbb R}^n$ endowed with a smooth, radial, strictly log-convex density on the volume and perimeter. This is an analogue of the result by G. R. Chambers for log-convex densities on $\mathbb R^n$. As an application we prove that in any rank one symmetr

Yanhao Wang, Francesco Fabbri, Michael Mathioudakis

Diversity maximization is a fundamental problem with wide applications in data summarization, web search, and recommender systems. Given a set $X$ of $n$ elements, it asks to select a subset $S$ of $k \ll n$ elements with maximum \emph{diversity}, as quantified by the dissimilarities among the elements in $S$. In this paper, we focus on the diversity maximiz

Cristian E. Gutierrez, Annamaria Montanari

The cost functions considered are $c(x,y)=h(x-y)$, where $h\in C^2(\mathbb{R}^n)$, homogeneous of degree $p\geq 2$, with a positive definite Hessian in the unit sphere. We study multivalued monotone maps with respect to that cost and establish that they are single-valued almost everywhere. Further consequences are then deduced.

João Barbosa, Mário Florido, Vítor Santos Costa

The semantic foundations for logic programming are usually separated into two different approaches. The operational semantics, which uses SLD-resolution, the proof method that computes answers in logic programming, and the declarative semantics, which sees logic programs as formulas and its semantics as models. Here, we define a new operational semantics cal

Giorgio Grani, Corrado Coppola, Valerio Agasucci

This work describes PUSH, a primal heuristic combining Feasibility Pump and Shifting. The main idea is to replace the rounding phase of the Feasibility Pump with a suitable adaptation of the Shifting and other rounding heuristics. The algorithm presents different strategies, depending on the nature of the partial rounding obtained. In particular, we distingu

Harald Reiss

A superconductor is stable if it does not quench. Quench is a short-time physics problem. For its deeper understanding of, and how to avoid quench, the physics behind stability has to be analysed. A previously suggested dynamic relaxation model is re-considered and applied to YBaCuO 123 and BSCCO 2223 high-temperature, thin film superconductors. Parallel to

Svetlana Pastukhova

In the whole space $R^d$ ($d\ge 2$), we study homogenization of a divergence-form matrix elliptic operator $L_\varepsilon$ of an arbitrary even order larger than 2 with measurable $\varepsilon$-periodic coefficients, where $\varepsilon$ is a small parameter. We constuct an approximation for the resolvent of $L_\varepsilon$ with the remainder term of order $\

Giacomo Galloni, Nicola Bartolo, Sabino Matarrese, Marina Migliaccio

We have taken a comprehensive approach to update the limits on the tensor-to-scalar ratio ($r$) and the tensor spectral index ($n_t$), using 10 datasets from the BICEP/Keck Array 2015 and 2018, Planck releases 3 and 4, and LIGO-Virgo-KAGRA Collaboration. By fitting the complete $\Lambda$CDM+$r$+$n_t$ model with two different approaches for the tensor sector,

Patrick Barthel, Patrick H. Huber, Jorge Casanova, Iñigo Arrazola

We present the experimental implementation of a two-qubit phase gate, using a radio frequency (RF) controlled trapped-ion quantum processor. The RF-driven gate is generated by a pulsed dynamical decoupling sequence applied to the ions' carrier transitions only. It allows for a tunable phase shift with high-fidelity results, in particular a fringe contrast up

Shengxin Li, Feng Xie

In this paper we consider the long time well-posedness of solutions to two dimensional compressible magnetohydrodynamics (MHD) boundary layer equations. When the initial data is a small perturbation of a steady solution with size of $\varepsilon$ and the far-field state is also a small perturbation around such a steady solution in Sobolev space, then the lif

Claudio Bonanno, Massimo D'Elia, Francesca Margari

The topological susceptibility of $2d$ $\mathrm{CP}^{N-1}$ models is expected, based on perturbative computations, to develop a divergence in the limit $N \to 2$, where these models reduce to the well-known non-linear $\mathrm{O}(3)$ $\sigma$-model. The divergence is due to the dominance of instantons of arbitrarily small size and its detection by numerical

Hengwei Xu, Yong Liao, Haiyong Xie, Pengyuan Zhou

The rapidly enlarging neural network models are becoming increasingly challenging to run on a single device. Hence model parallelism over multiple devices is critical to guarantee the efficiency of training large models. Recent proposals fall short either in long processing time or poor performance. Therefore, we propose Celeritas, a fast framework for optim

Zhen Xing, Yijiang Chen, Zhixin Ling, Xiangdong Zhou

3D reconstruction of novel categories based on few-shot learning is appealing in real-world applications and attracts increasing research interests. Previous approaches mainly focus on how to design shape prior models for different categories. Their performance on unseen categories is not very competitive. In this paper, we present a Memory Prior Contrastive

Athira Subhash, Abla Kammoun, Ahmed Elzanaty, Sheetal Kalyani

Smart radio environments aided by reconfigurable intelligent reflecting surfaces (RIS) have attracted much research attention recently. We propose a joint optimization strategy for beamforming, RIS phases, and power allocation to maximize the minimum SINR of an uplink RIS-aided communication system. The users are subject to constraints on their transmit powe

Paola Deriu, Fabrizio Lillo, Piero Mazzarisi, Francesca Medda

This paper investigates how Covid mobility restrictions impacted the population of investors of the Italian stock market. The analysis tracks the trading activity of individual investors in Italian stocks in the period January 2019-September 2021, investigating how their composition and the trading activity changed around the Covid-19 lockdown period (March

Adel Kara Slimane, Geneviève Fleury

We study the non-interacting time-dependent resonant level model mimicking a driven quantum dot connected through leads to two electronic reservoirs held at different temperatures and electrochemical potentials. Using a scattering approach, we provide analytical formulas of the time-dependent particle currents, heat currents, and input driving power under th

K. Y. Jing, X. Gong, X. R. Wang

The fascinating high-speed field-driven domain wall (DW) motion along ferrimagnetic nanowires near the angular momentum compensation point (AMCP) is solved based on the generic ferrimagnetic dynamics. The physics of the absences of precessional torque and infinite high Walker breakdown field at the AMCP is proved under general conditions. Based on the energy

X. Gong, K. Y. Jing, J. Lu, X. R. Wang

High precision skyrmion pinning by an intentionally created magnetic structure is important in skyrmion manipulation. Here, we consider skyrmion pinning by various types of disks. Among other findings, we clarify that, in terms of pinning position and pinning potential landscape, one needs to distinguish thin-wall skyrmions from thick-wall skyrmions because

Francesc Cunillera

The subject of this thesis is cosmological implications of string compactifications understood in a broad sense. In the first half of the thesis, we will begin by reviewing the four-dimensional description of the tree-level perturbative type IIB action. We will then review a number of open questions in cosmology and their relevance with regards to the remain

Huije Lee, Young Ju NA, Hoyun Song, Jisu Shin

Online trolls increase social costs and cause psychological damage to individuals. With the proliferation of automated accounts making use of bots for trolling, it is difficult for targeted individual users to handle the situation both quantitatively and qualitatively. To address this issue, we focus on automating the method to counter trolls, as counter res

Harry Asada

The dynamic complexity of robots and mechatronic systems often pertains to the hybrid nature of dynamics, where governing equations consist of heterogenous equations that are switched depending on the state of the system. Legged robots and manipulator robots experience contact-noncontact discrete transitions, causing switching of governing equations. Analysi

José E. Chacón, Javier Fernández Serrano

Bump hunting deals with finding in sample spaces meaningful data subsets known as bumps. These have traditionally been conceived as modal or concave regions in the graph of the underlying density function. We define an abstract bump construct based on curvature functionals of the probability density. Then, we explore several alternative characterizations inv

Chaoning Zhang, Chenshuang Zhang, Junha Song, John Seon Keun Yi

Masked autoencoders are scalable vision learners, as the title of MAE \cite{he2022masked}, which suggests that self-supervised learning (SSL) in vision might undertake a similar trajectory as in NLP. Specifically, generative pretext tasks with the masked prediction (e.g., BERT) have become a de facto standard SSL practice in NLP. By contrast, early attempts