August 2022 arXiv papers — page 110

Yu-Ki Lee, Yue Hao, Zhonghua Xi, Woongbae Kim

We propose an algorithmic framework of a pluripotent structure evolving from a simple compact structure into diverse complex 3-D structures for designing the shape transformable, reconfigurable, and deployable structures and robots. Our algorithmic approach suggests a way of transforming a compact structure consisting of uniform building blocks into a large,

Avery Meiksin, Teresita Suarez

We investigate the possible influence of fluctuations in the metagalactic photoionizing ultra-violet background (UVBG) on the clustering of Ly$\alpha$-emitting galaxies through the modulation of the ionization level of the gas surrounding the systems. At redshifts $z > 5$, even when assuming the reionization of the intergalactic medium has completed, the flu

Ting Chen, Ruixiang Zhang, Geoffrey Hinton

We present Bit Diffusion: a simple and generic approach for generating discrete data with continuous state and continuous time diffusion models. The main idea behind our approach is to first represent the discrete data as binary bits, and then train a continuous diffusion model to model these bits as real numbers which we call analog bits. To generate sample

Victor Ukleev, Max Burian, Sebastian Gliga, C. A. F. Vaz

Magnetic patterns can be controlled globally using fields or spin polarized currents. In contrast, the local control of the magnetization on the nanometer length scale remains challenging. Here, we demonstrate how magnetic domain patterns in a Tm-doped yttrium iron garnet (Tm:YIG) thin film with perpendicular magnetic anisotropy can be permanently and locall

Bernd Schmidt, Jiří Zeman

The purpose of this note is to establish two continuum theories for the bending and torsion of inextensible rods as $\Gamma$-limits of 3D atomistic models. In our derivation we study simultaneous limits of vanishing rod thickness $h$ and interatomic distance $\varepsilon$. First, we set up a novel theory for ultrathin rods composed of finitely many atomic fi

Xiaolong Li, Federica B. Bianco, Gregory Dobler, Roee Partoush

Light Echoes (LEs) are the reflections of astrophysical transients off of interstellar dust. They are fascinating astronomical phenomena that enable studies of the scattering dust as well as of the original transients. LEs, however, are rare and extremely difficult to detect as they appear as faint, diffuse, time-evolving features. The detection of LEs still

Seyed Sajad Tabas, Mahsa Berahman, Javad T. Firouzjaee

In this paper, we have investigated the processes of evaporation and accretion of primordial black holes during the radiation-dominated era and the matter-dominated era. This subject is very important since usually these two processes are considered independent of each other. In other words, previous works consider them in such a way that they do not have a

Xiaoxian Tang, Kaizhang Wang

For the reaction networks with zero-one stoichiometric coefficients (or simply zero-one networks), we prove that if a network admits a Hopf bifurcation, then the rank of the stoichiometric matrix is at least four. As a corollary, we show that if a zero-one network admits a Hopf bifurcation, then it contains at least four species and five reactions. As applic

Bernd Schmidt, Jiří Zeman

Starting from a particle system with short-range interactions, we derive a continuum model for the bending, torsion, and brittle fracture of inextensible rods moving in three-dimensional space. As the number of particles tends to infinity, it is assumed that the rod's thickness is of the same order as the interatomic distance. Fracture energy in the $\Gamma$

Lluís Hurtado-Gil, Michael A. Kuhn, Pablo Arnalte-Mur, Eric D. Feigelson

Dark matter simulations require statistical techniques to properly identify and classify their halos and structures. Nonparametric solutions provide catalogs of these structures but lack the additional learning of a model-based algorithm and might misclassify particles in merging situations. With mixture models, we can simultaneously fit multiple density pro

Mario Bravo, Roberto Cominetti

We study a stochastically perturbed version of the well-known Krasnoselski--Mann iteration for computing fixed points of nonexpansive maps in finite dimensional normed spaces. We discuss sufficient conditions on the stochastic noise and stepsizes that guarantee almost sure convergence of the iterates towards a fixed point, and derive non-asymptotic error bou

Hiran H Lathabai, Abhirup Nandy, Vivek Kumar Singh

The shift from 'trust-based funding' to 'performance-based funding' is one of the factors that has forced institutions to strive for continuous improvement of performance. Several studies have established the importance of collaboration in enhancing the performance of paired institutions. However, identification of suitable institutions for collaboration is

Yiqin Wang, Yuanbo Li, Chong Han, Yi Chen

The Terahertz (THz) band (0.1-10 THz) has been envisioned as one of the promising spectrum bands for sixth-generation (6G) and beyond communications. In this paper, a dual-band angular-resolvable wideband channel measurement in an indoor L-shaped hallway is presented and THz channel characteristics at 306-321 GHz and 356-371 GHz are analyzed. It is found tha

Gilles Crommen, Jad Beyhum, Ingrid Van Keilegom

This paper considers the problem of inferring the causal effect of a variable $Z$ on a dependently censored survival time $T$. We allow for unobserved confounding variables, such that the error term of the regression model for $T$ is correlated with the confounded variable $Z$. Moreover, $T$ is subject to dependent censoring. This means that $T$ is right cen

Johannes Jakubik, Jakob Schöffer, Vincent Hoge, Michael Vössing

In this work, we empirically examine human-AI decision-making in the presence of explanations based on predicted outcomes. This type of explanation provides a human decision-maker with expected consequences for each decision alternative at inference time - where the predicted outcomes are typically measured in a problem-specific unit (e.g., profit in U.S. do

Sarah Kleest-Meißner, Jonas Marasus, Matthias Niewerth

We describe a framework for maintaining forest algebra representations that are of logarithmic height for unranked trees. Such representations can be computed in O(n) time and updated in O(log(n)) time. The framework is of potential interest for data structures and algorithms for trees whose complexity depend on the depth of the tree (representation). We pro

Yan Cao, Guantao Chen, Guangming Jing, Songling Shan

Let $G$ be a simple graph. Denote by $n$, $\Delta(G)$ and $\chi' (G)$ be the order, the maximum degree and the chromatic index of $G$, respectively. We call $G$ \emph{overfull} if $|E(G)|/\lfloor n/2\rfloor > \Delta(G)$, and {\it critical} if $\chi'(H) < \chi'(G)$ for every proper subgraph $H$ of $G$. Clearly, if $G$ is overfull then $\chi'(G) = \Delta(G)+1$

Johannes Müller-Seidlitz, Robert Andritschke, Michael Bonholzer, Valentin Emberger

The Wide Field Imager for the Athena X-ray telescope is composed of two back side illuminated detectors using DEPFET sensors operated in rolling shutter readout mode: A large detector array featuring four sensors with 512x512 pixels each and a small detector that facilitates the high count rate capability of the WFI for the investigation of bright, point-lik

Silouanos Brazitikos, Apostolos Giannopoulos, Minas Pafis

Let $\mu$ be a log-concave probability measure on ${\mathbb R}^n$ and for any $N>n$ consider the random polytope $K_N={\rm conv}\{X_1,\ldots ,X_N\}$, where $X_1,X_2,\ldots $ are independent random points in ${\mathbb R}^n$ distributed according to $\mu $. We study the question if there exists a threshold for the expected measure of $K_N$. Our approach is bas

Lloyd N. Trefethen

M\"untz's theorem asserts, for example, that the even powers $1, x^2, x^4,\dots$ are dense in $C([0,1])$. We show that the associated expansions are so inefficient as to have no conceivable relevance to any actual computation. For example, approximating $f(x)=x$ to accuracy $\varepsilon = 10^{-6}$ in this basis requires powers larger than $x^{280{,}000}$ and

Philippe Nadeau, Vasu Tewari

We establish Guay-Paquet's unpublished linear relation between certain chromatic symmetric functions by relating his algebra on paths to the $q$-Klyachko algebra. The coefficients in this relations are $q$-hit polynomials, and they come up naturally in our setup as connected remixed Eulerian numbers, in contrast to the computational approach of Colmenarejo-M

Fong En Oon, Rainer Dumke

A single-seed, module-based compact laser system is demonstrated on a transportable $^{87}\text{Rb}$-based high-precision atomic gravimeter. All the required laser frequencies for the atom interferometry are provided by free-space acousto-optic modulators (AOMs) and resonant electro-optic phase modulators (EOMs). The optical phase-locked loop between the two

Jiawei Li, Chenxi Lan, Xinyi Zhang, Bolin Jiang

Recent trends in AIGC effectively boosted the application of visual inspection. However, most of the available systems work in a human-in-the-loop manner and can not provide long-term support to the online application. To make a step forward, this paper outlines an automatic annotation system called SsaA, working in a self-supervised learning manner, for con

Sachit Mishra, Rajat Srivastava, Atta Muhammad, Amit Amit

Hybrid electric vehicles and portable electronic systems use supercapacitors for energy storage owing to their fast charging discharging rates, long life cycle, and low maintenance. Specific capacitance is regarded as one of the most important performance-related characteristics of a supercapacitor's electrode. In the current study, Machine Learning (ML) alg

Dániel Horváth, Gábor Erdős, Zoltán Istenes, Tomáš Horváth

Robots working in unstructured environments must be capable of sensing and interpreting their surroundings. One of the main obstacles of deep-learning-based models in the field of robotics is the lack of domain-specific labeled data for different industrial applications. In this article, we propose a sim2real transfer learning method based on domain randomiz

Plawan Das, Subham Sarkar

We prove a certain uniform version of the Shafarevich Conjecture. As a corollary, we prove the Rasmussen-Tamagawa Conjecture for a particular class of abelian varieties $A$ defined over a number $K$ of dimension $g$ having everywhere potential good reduction, in particular, for any finite place $v$ of $K$ the localization $A_v:=A\times_{\mathrm{Spec}(K)}\mat

James H. Adler, Casey Cavanaugh, Xiaozhe Hu, Andy Huang

Convection-diffusion equations arise in a variety of applications such as particle transport, electromagnetics, and magnetohydrodynamics. Simulation of the convection-dominated regime for these problems, even with high-fidelity techniques, is particularly challenging due to the presence of sharp boundary layers and shocks causing jumps and discontinuities in

Siphiwo R. Dlamini, Alex Matos-Abiague

We theoretically investigate the effects of tunable magnetic fringe fields generated by arrays of switchable magnetic junctions (MJs) on the quantum states of an underlying two-dimensional (2D) system formed in a semiconductor quantum well. The magnetic landscape generated by the MJ-array can be reconfigured on the nanometer scale by electrically switching t

G. Dagvadorj, P. Comaron, M. H. Szymanska

We study a four-component polariton system in the optical parametric oscillator regime consisting of exciton/photon and signal/idler modes across the Berezinskii-Kosterlitz-Thouless (BKT) transition. We show that all four components share the same BKT critical point, and algebraic decay of spatial coherence with the same critical exponent. However, while the

Ahmed El-Gazzar, Rajat Mani Thomas, Guido Van Wingen

Single-subject mapping of resting-state brain functional activity to non-imaging phenotypes is a major goal of neuroimaging. The large majority of learning approaches applied today rely either on static representations or on short-term temporal correlations. This is at odds with the nature of brain activity which is dynamic and exhibit both short- and long-r

Yue Hu, Siheng Chen, Xu Chen, Ya Zhang

Visual relationship detection aims to detect the interactions between objects in an image; however, this task suffers from combinatorial explosion due to the variety of objects and interactions. Since the interactions associated with the same object are dependent, we explore the dependency of interactions to reduce the search space. We explicitly model objec

Xiangwen Kong, Xiangyu Zhang

Recently, Masked Image Modeling (MIM) achieves great success in self-supervised visual recognition. However, as a reconstruction-based framework, it is still an open question to understand how MIM works, since MIM appears very different from previous well-studied siamese approaches such as contrastive learning. In this paper, we propose a new viewpoint: MIM

Virgile Rennard, Guokan Shang, Julie Hunter, Michalis Vazirgiannis

A system that could reliably identify and sum up the most important points of a conversation would be valuable in a wide variety of real-world contexts, from business meetings to medical consultations to customer service calls. Recent advances in deep learning, and especially the invention of encoder-decoder architectures, has significantly improved language

Anne-Lena Moor, Christoph Zechner

We develop numerical and analytical approaches to calculate mutual information between complete paths of two molecular components embedded into a larger reaction network. In particular, we focus on a continuous-time Markov chain formalism, frequently used to describe intracellular processes involving lowly abundant molecular species. Previously, we have show

Nikolaos E. Palaiodimopoulos, Maximilian Kiefer-Emmanouilidis, Gershon Kurizki, David Petrosyan

We examine spin excitation or polarization transfer via long-range interacting spin chains with diagonal and off-diagonal disorder. To this end, we determine the mean localization length of the single-excitation eigenstates of the chain for various strengths of the disorder. We then identify the energy eigenstates of the system with large localization length

Wanyue Xu, Liwang Zhu, Jiale Guan, Zuobai Zhang

As an important factor governing opinion dynamics, stubbornness strongly affects various aspects of opinion formation. However, a systematically theoretical study about the influences of heterogeneous stubbornness on opinion dynamics is still lacking. In this paper, we study a popular opinion model in the presence of inhomogeneous stubbornness. We show analy

Ningning Wang, Guodong Li, Sihuang Hu, Min Ye

Wang et al. (IEEE Transactions on Information Theory, vol. 62, no. 8, 2016) proposed an explicit construction of an $(n=k+2,k)$ Minimum Storage Regenerating (MSR) code with $2$ parity nodes and subpacketization $2^{k/3}$. The number of helper nodes for this code is $d=k+1=n-1$, and this code has the smallest subpacketization among all the existing explicit c

Rohit Lal, Bharath Kumar Bolla, Sabeesh Ethiraj

One of the most pressing challenges prevalent in the steel manufacturing industry is the identification of surface defects. Early identification of casting defects can help boost performance, including streamlining production processes. Though, deep learning models have helped bridge this gap and automate most of these processes, there is a dire need to come

Armando Bellante, Stefano Zanero

Representing signals with sparse vectors has a wide range of applications that range from image and video coding to shape representation and health monitoring. In many applications with real-time requirements, or that deal with high-dimensional signals, the computational complexity of the encoder that finds the sparse representation plays an important role.

Shannon Ray, Paul M. Alsing, Carlo Cafaro, Shelton Jacinto

In this paper, we construct the metric tensor and volume for the manifold of purifications associated with an arbitrary reduced density operator $\rho_S$. We also define a quantum coarse-graining (CG) to study the volume where macrostates are the manifolds of purifications, which we call surfaces of ignorance (SOI), and microstates are the purifications of $

O. Adriani, M. Antonelli, A. Basti, E. Berti

The measurement of cosmic-ray individual spectra provides unique information regarding the origin and propagation of astro-particles. Due to the limited acceptance of current space experiments, protons and nuclei around the "knee" region ($\sim1\ PeV$) can only be observed by ground based experiments. Thanks to an innovative design, the High Energy cosmic-Ra

Ugo Marzolino

Conversion of chemical energy into mechanical work is the fundamental mechanism of several natural phenomena at the nanoscale, like molecular machines and Brownian motors. Quantum mechanical effects are relevant for optimising these processes and to implement them at the atomic scale. This paper focuses on engines that transform chemical work into mechanical

Philippe Nadeau, Vasu Tewari

Remixed Eulerian numbers are a polynomial $q$-deformation of Postnikov's mixed Eulerian numbers. They arose naturally in previous work by the authors concerning the permutahedral variety and subsume well-known families of polynomials such as $q$-binomial coefficients and Garsia--Remmel's $q$-hit numbers. We study their combinatorics in more depth. As polynom

Sebastian Zainali, Dazhi Yang, Tomas Landelius, Pietro E. Campana

Gridded global horizontal irradiance (GHI) databases are fundamental for analysing solar energy applications' technical and economic aspects, particularly photovoltaic applications. Today, there exist numerous gridded GHI databases whose quality has been thoroughly validated against ground-based irradiance measurements. Nonetheless, databases that generate d

Lai Jiang, Huo-Jun Ruan

Let $f$ be a generalized affine fractal interpolation function with vertical scaling function $S$. In this paper, we study $\dim_B \Gamma f$, the box dimension of the graph of $f$, under the assumption that $S$ is a Lipschtz function. By introducing vertical scaling matrices, we estimate the upper bound and the lower bound of oscillations of $f$. As a result

Haoye Tian, Xunzhu Tang, Andrew Habib, Shangwen Wang

In this work, we propose a novel perspective to the problem of patch correctness assessment: a correct patch implements changes that "answer" to a problem posed by buggy behaviour. Concretely, we turn the patch correctness assessment into a Question Answering problem. To tackle this problem, our intuition is that natural language processing can provide the n

Samson Clymton, Hyun-Chul Kim

We investigate $\pi\rho$ scattering based on the coupled-channel formalism with the $\pi\rho$ and $K\bar{K}^*$ ($\bar{K}K^*$) channels included. We construct the kernel amplitudes by using the meson-exchange model and compute the coupled integral equation for $\pi\rho$ scattering. By performing the partial-wave expansion, we show explicitly that the $a_1(126

Syed Zuhair Abbas Shah, Shanawer Niaz, Tabassum Nasir, James Sifuna

Owing to the energy shortages and various severe adverse effects of traditional fossil fuel power generation mechanisms, photovoltaic and thermoelectric materials are considered as the potential candidates for building non-traditional, efficient, and eco-friendly power generation portfolios. Lead-based perovskites have emerged as highly efficient, abundantly

Zhilong Chen, Jinghua Piao, Xiaochong Lan, Hancheng Cao

Recommender systems are playing an increasingly important role in alleviating information overload and supporting users' various needs, e.g., consumption, socialization, and entertainment. However, limited research focuses on how values should be extensively considered in industrial deployments of recommender systems, the ignorance of which can be problemati

Jean-Louis Colliot-Thélène

Lichtenbaum proved that index and period coincide for a curve of genus one over a $p$-adic field. Salberger proved that the Hasse principle holds for a smooth complete intersection of two quadrics $X \subset P^n$ over a number field, if it contains a conic and if $n\geq 5$. Building upon these two results, we extend recent results of Creutz and Viray (2021)

Dimitrios Michael Manias, Ali Chouman, Abdallah Shami

The advent of Fifth Generation (5G) and beyond 5G networks (5G+) has revolutionized the way network operators consider the management and orchestration of their networks. With an increased focus on intelligence and automation through core network functions such as the NWDAF, service providers are tasked with integrating machine learning models and artificial

The DarkLight Collaboration, E. Cline, R. Corliss, J. C. Bernauer

The search for a dark photon holds considerable interest in the physics community. Such a force carrier would begin to illuminate the dark sector. Many experiments have searched for such a particle, but so far it has proven elusive. In recent years the concept of a low mass dark photon has gained popularity in the physics community. Of particular recent inte

Xiao-Han Wang, Pei Shi, Bin Xi, Jie Hu

Applying artificial intelligence to scientific problems (namely AI for science) is currently under hot debate. However, the scientific problems differ much from the conventional ones with images, texts, and etc., where new challenges emerges with the unbalanced scientific data and complicated effects from the physical setups. In this work, we demonstrate the

De-Fu Bu, Erlin Qiao, Xiao-Hong Yang, Jifeng Liu

One of the most prominent problems of optical/ultraviolet (UV) tidal disruption events (TDEs) is the origin of their optical/UV emission. It has been proposed that the soft X-rays produced by the stellar debris accretion disk can be reprocessed into optical/UV photons by a surrounding optically thick envelope or outflow. However, there is still no detailed m

Darija Barak, Edoardo Gallo, Ke Rong, Ke Tang

On 11th Jan 2020, the first COVID-19 related death was confirmed in Wuhan, Hubei. The Chinese government responded to the outbreak with a lockdown that impacted most residents of Hubei province and lasted for almost three months. At the time, the lockdown was the strictest both within China and worldwide. Using an interactive web-based experiment conducted h

Xiaoyang Liu, Chong Liu, Pinzheng Wang, Rongqin Zheng

Sequential recommendation models are primarily optimized to distinguish positive samples from negative ones during training in which negative sampling serves as an essential component in learning the evolving user preferences through historical records. Except for randomly sampling negative samples from a uniformly distributed subset, many delicate methods h

Rosario Paradiso, Angelos Georghiou, Said Dabia, Denise Tönissen

Uncertain optimization problems with decision dependent information discovery allow the decision maker to control the timing of information discovery, in contrast to the classic multistage setting where uncertain parameters are revealed sequentially based on a prescribed filtration. This problem class is useful in a wide range of applications, however, its a

Margherita Rosnati, Eyal Soreq, Miguel Monteiro, Lucia Li

The accurate prognosis for traumatic brain injury (TBI) patients is difficult yet essential to inform therapy, patient management, and long-term after-care. Patient characteristics such as age, motor and pupil responsiveness, hypoxia and hypotension, and radiological findings on computed tomography (CT), have been identified as important variables for TBI ou

Jianchang Hu, Silke Szymczak

Precision medicine provides customized treatments to patients based on their characteristics and is a promising approach to improving treatment efficiency. Large scale omics data are useful for patient characterization, but often their measurements change over time, leading to longitudinal data. Random forest is one of the state-of-the-art machine learning m

Lyuben Lichev

In this short note, we consider a graph process recently introduced by Frieze, Krivelevich and Michaeli. In their model, the edges of the complete graph $K_n$ are ordered uniformly at random and are then revealed consecutively to a player called Builder. At every round, Builder must decide if they accept the edge proposed at this round or not. We prove that,

Volkan Bakış, Zeki Eker

Standard luminosity ($L$) of 406 main-sequence stars with the most accurate astrophysical parameters are predicted from their absolute magnitudes and bolometric corrections at Johnson $B,V$, and Gaia EDR3 $G$, $G_{BP}$, $G_{RP}$ filters. Required multiband $BC$ and $BC-T_{eff}$ relations are obtained first from the parameters of 209 DDEB (Double-lined Detach

Nirmali Roy, Anuradha Jha

In this article, we have considered a time-dependent two-parameter singularly perturbed parabolic problem with discontinuous convection coefficient and source term. The problem contains the parameters $\epsilon$ and $\mu$ multiplying the diffusion and convection coefficients, respectively. A boundary layer develops on both sides of the boundaries as a result

Yuji Arakawa, Kazuharu Uchiyama, Kingo Uchida, Makoto Naruse

We demonstrate history-dependent or dynamic nano-photoisomerization by sequential formation of multiple memory pathways in photochromic crystals via optical near-field interactions. We observed the incident photons passing through the photoisomerization memory pathways by a double-probe optical near-field microscope, with one probe located on the front surfa

Alex Kaltenbach, Michael Růžička

In the present paper, we prove convergence rates for the Local Discontinuous Galerkin (LDG) approximation, proposed in Part I of the paper, for systems of $p$-Navier-Stokes type and $p$-Stokes type with $p\in (2,\infty)$. The convergence rates are optimal for linear ansatz functions. The results are supported by numerical experiments.

Alex Kaltenbach, Michael Růžička

In the present paper, we propose a Local Discontinuous Galerkin (LDG) approximation for fully non-homogeneous systems of $p$-Navier-Stokes type. On the basis of the primal formulation, we prove well-posedness, stability (a priori estimates), and weak convergence of the method. To this end, we propose a new DG discretization of the convective term and develop

Patrick Gérard, Enno Lenzmann

We study the Calogero--Moser derivative NLS equation $$ i \partial_t u +\partial_{xx} u + (D+|D|)(|u|^2) u =0 $$ posed on the Hardy-Sobolev space $H^s_+(\mathbb{R})$ with suitable $s>0$. By using a Lax pair structure for this $L^2$-critical equation, we prove global well-posedness for $s \geq 1$ and initial data with sub-critical or critical $L^2$-mass $\| u

Ahtsham Manzoor, Dietmar Jannach

Conversational recommender systems (CRS) that are able to interact with users in natural language often utilize recommendation dialogs which were previously collected with the help of paired humans, where one plays the role of a seeker and the other as a recommender. These recommendation dialogs include items and entities that indicate the users' preferences

R. B. Batista, M. J. Dias Carneiro, S. Oliffson Kamphorst

We study the billiard dynamics in annular tables between two excentric circles. As the center and the radius of the inner circle change, a two parameters map is defined by the first return of trajectories to the obstacle. We obtain an increasing family of hyperbolic sets, in the sense of the Hausdorff distance, as the radius goes to zero and the center of th

Ariadna Soro, Carlos Sánchez Muñoz, Anton Frisk Kockum

Giant atoms -- quantum emitters that couple to light at multiple discrete points -- are emerging as a new paradigm in quantum optics thanks to their many promising properties, such as decoherence-free interaction. While most previous work has considered giant atoms coupled to open continuous waveguides or a single giant atom coupled to a structured bath, her

Yi Luo, Jianwei Yu

The training of modern speech processing systems often requires a large amount of simulated room impulse response (RIR) data in order to allow the systems to generalize well in real-world, reverberant environments. However, simulating realistic RIR data typically requires accurate physical modeling, and the acceleration of such simulation process typically r

Yanwu Gu, Yunheng Ma, Nicolo Forcellini, Dong E. Liu

We develop an error mitigation method for the control-free phase estimation. We prove a theorem that under the first-order correction, the noise channels with only Hermitian Kraus operators do not change the phases of a unitary operator, and therefore, the benign types of noise for phase estimation are identified. By using the randomized compiling protocol,

Yen-Chieh Huang, Robert L. Byer

A dielectric laser accelerator, operating at optical frequencies and GHz pulse rate, is expected to produce attosec electron bunches with a moderate beam current at high energy. For relativistic electrons, the attosec bunch has a spatial length of a few nanometers, which is well suited for generating high-brightness superradiance in the VUV, EUV, and x-ray s

Paulina Majchrzak, Yuntian Liu, Klara Volckaert, Deepnarayan Biswas

Heterostructures composed of the intrinsic magnetic topological insulator MnBi$_2$Te$_4$ and its non-magnetic counterpart Bi$_2$Te$_3$ host distinct surface electronic band structures depending on the stacking order and exposed termination. Here, we probe the ultrafast dynamical response of MnBi$_2$Te$_4$ and MnBi$_4$Te$_7$ following near-infrared optical ex

Rohit Ram, Emma Thomas, David Kernot, Marian-Andrei Rizoiu

Online ideology detection is crucial for downstream tasks, like countering ideologically motivated violent extremism and modeling opinion dynamics. However, two significant issues arise in practitioners' deployment. Firstly, gold-standard training data is prohibitively labor-intensive to collect and has limited reusability beyond its collection context (i.e.

Zhichao Zhou, Yuming Zhou, Chunrong Fang, Zhenyu Chen

Unit testing is a critical part of software development process, ensuring the correctness of basic programming units in a program (e.g., a method). Search-based software testing (SBST) is an automated approach to generating test cases. SBST generates test cases with genetic algorithms by specifying the coverage criterion (e.g., branch coverage). However, a g

J. -M. Wang, P. Du, Y. -Y. Songsheng, Y. -R. Li

As a major feature in spectra of active galactic nuclei, broad emission lines deliver information of kinematics and spatial distributions of ionized gas surrounding the central supermassive black holes (SMBHs), that is the so-called broad-line regions (BLRs). There is growing evidence for appearance of spiral arms in the BLRs. It has been shown by reverberat

Danlan Huang, Feifei Gao, Xiaoming Tao, Qiyuan Du

Semantic communications has received growing interest since it can remarkably reduce the amount of data to be transmitted without missing critical information. Most existing works explore the semantic encoding and transmission for text and apply techniques in Natural Language Processing (NLP) to interpret the meaning of the text. In this paper, we conceive t

B. V. Rajarama Bhat, Chaitanya Gopalakrishna

In this paper we develop a tool to identify functions which have no iterative roots of any order. Using this, we prove that when $X$ is $[0,1]^m$, $\mathbb{R}^m$ or $S^1$, every non-empty open set of the space $\mathcal{C}(X)$ of continuous self-maps on $X$ endowed with the compact-open topology contains a map that does not have even discontinuous iterative

Arturo Fernández-Pérez, Vângellis Sagnori Maia

In this paper, we study holomorphic foliations of degree four on complex projective space $\mathbb{P}^n$, where $n\geq 3$, with a special focus on obtaining a structural theorem for these foliations. Furthermore, for a foliation $\mathcal{F}$ of degree $d\geq 4$ with a sufficiently high $k^{th}$-jet, we prove that either $\mathcal{F}$ is transversely affine

Andrius Grigutis

In this work we set up the generating function of the ultimate time survival probability $\varphi(u+1)$, where $$\varphi(u)=\mathbb{P}\left(\sup_{n\geqslant 1}\sum_{i=1}^{n}\left(X_i-\kappa\right)<u\right)$$ and $u\in\mathbb{N}_0,\,\kappa\in\mathbb{N}$, and the random walk $\left\{\sum_{i=1}^{n}X_i,\,n\in\mathbb{N}\right\}$ consists of independent and identi

Alberto Rosso, James P. Sethna, Matthieu Wyart

In this chapter, we discuss avalanches in glasses and disordered systems, and the macroscopic dynamical behavior that they mediate. We briefly review three classes of systems where avalanches are observed: depinning transition of disordered interfaces, yielding of amorphous materials, and the jamming transition. Without extensive formalism, we discuss result

Zeheng Wang, MengKe Feng, Santiago Serrano, William Gilbert

The small size and excellent integrability of silicon metal-oxide-semiconductor (SiMOS) quantum dot spin qubits make them an attractive system for mass-manufacturable, scaled-up quantum processors. Furthermore, classical control electronics can be integrated on-chip, in-between the qubits, if an architecture with sparse arrays of qubits is chosen. In such an

Genming Lai, Junyu Jiao, Chi Fang, Liyuan Sheng

Due to the rapid growth in the demand for high-energy-density Li batteries and insufficient global Li reserves, the anode-free Li metal batteries are receiving increasing attention. Various strategies, such as surface modification and structural design of Cu current collectors, have been proposed to stabilize the anode-free Li metal batteries. Unfortunately,

Erik Faust, Alexander Schlüter, Henning Müller, Ralf Müller

Recently, Murthy et al. [2017] and Escande et al. [2020] adopted the Lattice Boltzmann Method (LBM) to model the linear elastodynamic behaviour of isotropic solids. The LBM is attractive as an elastodynamic solver because it can be parallelised readily and lends itself to finely discretised dynamic continuum simulations, allowing transient phenomena such as

Sebastian Heri, Julia Lieb, Joachim Rosenthal

This paper investigates the concept of self-dual convolutional code. We derive the basic properties of this interesting class of codes and we show how some of the techniques to construct self-dual linear block codes generalize to self-dual convolutional codes. As for self-dual linear block codes we are able to give a complete classification for some small pa

Clément Aubert, Cinzia Di Giusto, Larisa Safina, Alceste Scalas

This volume contains the proceedings of ICE'22, the 15th Interaction and Concurrency Experience, which was held as an hybrid event in Lucca, Italy, and as a satellite event of DisCoTec'22. The ICE workshop series features a distinguishing review and selection procedure: PC members are encouraged to interact, anonymously, with authors. The 2022 edition of ICE

Freya Blekman, Fréderic Déliot, Valentina Dutta, Emanuele Usai

The production of four top quarks is a rare process in the Standard Model that provides unique opportunities and sensitivity to Standard Model observables including potential enhancement from many popular new physics extensions. This article summarises the latest experimental measurements of the four-top quark production cross section at the LHC. An overview

Diego G. Arbó, Sebastián D. López, Joachim Burgdörfer

Phase and time delays of atomic above-threshold ionization were recently experimentally explored in an $\omega -2\omega$ setting [Zipp et al, Optica 1, 361 (2014)]. The phases of wavepackets ejected from argon by a strong $2\omega$ pulse were probed as a function of the relative phase of a weaker $\omega$ probe pulse. Numerical simulations solving the time-d

Iman Munire Bilal, Bo Wang, Adam Tsakalidis, Dong Nguyen

We introduce the task of microblog opinion summarisation (MOS) and share a dataset of 3100 gold-standard opinion summaries to facilitate research in this domain. The dataset contains summaries of tweets spanning a 2-year period and covers more topics than any other public Twitter summarisation dataset. Summaries are abstractive in nature and have been create

Alexey Golovnev

Conformal and disformal transformations are now being very intensively studied in the context of various modified gravity theories. In particular, some special classes of them can be used for constructing Mimetic Dark Matter models. Recently, it has been shown that many more transformations of this type, if not virtually all of them when the coefficients dep

Heng Cong, Lingzhi Fu, Rongyu Zhang, Yusheng Zhang

In this work, we introduce Gradient Siamese Network (GSN) for image quality assessment. The proposed method is skilled in capturing the gradient features between distorted images and reference images in full-reference image quality assessment(IQA) task. We utilize Central Differential Convolution to obtain both semantic features and detail difference hidden

Jiarui Fang, Geng Zhang, Jiatong Han, Shenggui Li

Deep learning recommendation models (DLRMs) have been widely applied in Internet companies. The embedding tables of DLRMs are too large to fit on GPU memory entirely. We propose a GPU-based software cache approaches to dynamically manage the embedding table in the CPU and GPU memory space by leveraging the id's frequency statistics of the target dataset. Our

Callum Vyner, Christopher Nemeth, Chris Sherlock

Divide-and-conquer strategies for Monte Carlo algorithms are an increasingly popular approach to making Bayesian inference scalable to large data sets. In its simplest form, the data are partitioned across multiple computing cores and a separate Markov chain Monte Carlo algorithm on each core targets the associated partial posterior distribution, which we re

Yili Jin, Junhua Liu, Fangxin Wang, Shuguang Cui

360{\deg} videos in recent years have experienced booming development. Compared to traditional videos, 360{\deg} videos are featured with uncertain user behaviors, bringing opportunities as well as challenges. Datasets are necessary for researchers and developers to explore new ideas and conduct reproducible analyses for fair comparisons among different solu

Elsie Lee-Robbins, Eytan Adar

When designing communicative visualizations, we often focus on goals that seek to convey patterns, relations, or comparisons (cognitive learning objectives). We pay less attention to affective intents--those that seek to influence or leverage the audience's opinions, attitudes, or values in some way. Affective objectives may range in outcomes from making the

John McDonald

It is likely that the Higgs potential of the Standard Model is unstable, turning negative at $\phi < \Lambda \sim 10^{10}$ GeV. Here we consider whether it is possible to have Higgs Inflation on the positive stable region of the potential at $\phi < \Lambda$. To do this we add a non-minimally coupled induced gravity sector with scalar $\chi$ to the Standard

Heng Cong, Rongyu Zhang, Jiarong He, Jin Gao

Face anti-spoofing researches are widely used in face recognition and has received more attention from industry and academics. In this paper, we propose the EulerNet, a new temporal feature fusion network in which the differential filter and residual pyramid are used to extract and amplify abnormal clues from continuous frames, respectively. A lightweight sa

Otmane Sakhi, David Rohde, Alexandre Gilotte

Personalised interactive systems such as recommender systems require selecting relevant items from massive catalogs dependent on context. Reward-driven offline optimisation of these systems can be achieved by a relaxation of the discrete problem resulting in policy learning or REINFORCE style learning algorithms. Unfortunately, this relaxation step requires

Hilal AlQuabeh, Aliakbar Abdurahimov

The pairwise objective paradigms are an important and essential aspect of machine learning. Examples of machine learning approaches that use pairwise objective functions include differential network in face recognition, metric learning, bipartite learning, multiple kernel learning, and maximizing of area under the curve (AUC). Compared to pointwise learning,

Yu. L. Sachkov, E. F. Sachkova

The left-invariant sub-Lorentzian problem on the Heisenberg group is considered. An optimal synthesis is constructed, the sub-Lorentzian distance and spheres are described.