May 2022 arXiv papers — page 138

Julia Liebert

Density functional theory constitutes the workhorse of modern electronic structure calculations due to its favourable computational cost despite the fact that it usually fails to describe strongly correlated systems. A particularly promising approach to overcome those difficulties is reduced density matrix functional theory (RDMFT): It abandons the complexit

Nima Ghanbari

Let $G=(V,E)$ be a simple graph. A dominating set of $G$ is a subset $S\subseteq V$ such that every vertex not in $S$ is adjacent to at least one vertex in $S$. The cardinality of a smallest dominating set of $G$, denoted by $γ(G)$, is the domination number of $G$. A dominating set $S$ is called a super dominating set of $G$, if for every vertex $u\in \overl

Jozefien D'haeseleer, Klaus Metsch, Daniel Werner

We determine the chromatic number of the Kneser graph qΓ_{7,{3,4}} of flags of vectorial type {3, 4} of a rank 7 vector space over the finite field GF(q) for large q and describe the colorings that attain the bound. This result relies heavily, not only on the independence number, but also on the structure of all large independent sets. Furthermore, our proof

Gabriel Amaral, Odinaldo Rodrigues, Elena Simperl

Data verbalisation is a task of great importance in the current field of natural language processing, as there is great benefit in the transformation of our abundant structured and semi-structured data into human-readable formats. Verbalising Knowledge Graph (KG) data focuses on converting interconnected triple-based claims, formed of subject, predicate, and

Peizhuo Li, Kfir Aberman, Zihan Zhang, Rana Hanocka

We present GANimator, a generative model that learns to synthesize novel motions from a single, short motion sequence. GANimator generates motions that resemble the core elements of the original motion, while simultaneously synthesizing novel and diverse movements. Existing data-driven techniques for motion synthesis require a large motion dataset which cont

Zhiguang Zhao

In the present paper, we give a systematic study of the correspondence theory of generalized modal algebras and generalized modal spaces. The special feature of the present paper is that in the proof of the (right-handed) topological Ackermann lemma, the admissible valuations are not the clopen valuations anymore, but values in the set DK(X) which are only c

Fabian Oboril, Cornelius Buerkle, Alon Sussmann, Simcha Bitton

The development of Automated Vehicles (AVs) is progressing quickly and the first robotaxi services are being deployed worldwide. However, to receive authority certification for mass deployment, manufactures need to justify that their AVs operate safer than human drivers. This in turn creates the need to estimate and model the collision rate (failure rate) of

Fangfei Lin, Bing Bai, Kun Bai, Yazhou Ren

Hierarchical clustering recursively partitions data at an increasingly finer granularity. In real-world applications, multi-view data have become increasingly important. This raises a less investigated problem, i.e., multi-view hierarchical clustering, to better understand the hierarchical structure of multi-view data. To this end, we propose a novel neural

Lawrence Ong, Badri N. Vellambi

In the pliable variant of index coding, receivers are allowed to decode any new message not known a priori. Optimal code design for this variant involves identifying each receiver's choice of a new message that minimises the overall transmission rate. This paper proposes a formulation that further relaxes the decoding requirements of pliable index coding

Peter Albers, Serge Tabachnikov

In this article we consider area preserving diffeomorphisms of planar domains, and we are interested in their conformal points, i.e., points at which the derivative is a similarity. We present some conditions that guarantee existence of conformal points for the infinitesimal problem of Hamiltonian vector fields as well as for what we call moderate symplectom

Andreas Padalkin, Christian Scheideler, Daniel Warner

The amoebot model [Derakhshandeh et al., 2014] has been proposed as a model for programmable matter consisting of tiny, robotic elements called amoebots. We consider the reconfigurable circuit extension [Feldmann et al., JCB 2022] of the geometric (variant of the) amoebot model that allows the amoebot structure to interconnect amoebots by so-called circuits.

Borna Radatović, Valentino Jadriško, Sherif Kamal, Marko Kralj

A major challenge in the investigation of all 2D materials is the development of synthesis protocols and tools which would enable their large-scale production and effective manipulation. The same holds for borophene, where experiments are still largely limited to in situ characterizations of small-area samples. In contrast, our work is based on millimeter-si

D. Borka, V. Borka Jovanović, V. N. Nikolić, N. Dj. Lazarov

We estimate the parameters of Hybrid Palatini gravity model with the Schwarzschild precession of S-stars, specifically of S2, S38 and S55 stars. We also take into account case of bulk mass distribution near Galactic Center. We assume that the Schwarzschild orbital precession of mentioned S-stars is the same like in General Relativity (GR) in all studied case

Harsh Tataria

We analyze the uplink radio frequency (RF) interference from a multiplicity of single-antenna user equipments transmitting to a cellular base station (BS) within the same time-frequency resource. The BS is assumed to operate with a lens antenna array, which induces additional focusing gain for the incoming signals. Considering line-of-sight propagation condi

Robert Karsthof, Ymir Kalmann Frodason, Augustinas Galeckas, Philip Michael Weiser

Nickel oxide is a versatile p-type semiconducting oxide with many applications in opto-electronic devices, but high doping concentrations are often required to achieve necessary electrical conductivity. In contrast to many other transparent oxide semiconductors, even moderate levels of doping of NiO can lead to significant optical absorption in the visible s

Gaurav Kumar Nayak, Ruchit Rawal, Rohit Lal, Himanshu Patil

Adversarial attack perturbs an image with an imperceptible noise, leading to incorrect model prediction. Recently, a few works showed inherent bias associated with such attack (robustness bias), where certain subgroups in a dataset (e.g. based on class, gender, etc.) are less robust than others. This bias not only persists even after adversarial training, bu

Jack Kuipers, Giusi Moffa

Describing the causal relations governing a system is a fundamental task in many scientific fields, ideally addressed by experimental studies. However, obtaining data under intervention scenarios may not always be feasible, while discovering causal relations from purely observational data is notoriously challenging. In certain settings, such as genomics, we

Mauro Castelli, Luca Manzoni, Luca Mariot, Giuliamaria Menara

Among the evolutionary methods, one that is quite prominent is Genetic Programming, and, in recent years, a variant called Geometric Semantic Genetic Programming (GSGP) has shown to be successfully applicable to many real-world problems. Due to a peculiarity in its implementation, GSGP needs to store all the evolutionary history, i.e., all populations from t

M. Arana-Catania, Elena Kochkina, Arkaitz Zubiaga, Maria Liakata

We present a comprehensive work on automated veracity assessment from dataset creation to developing novel methods based on Natural Language Inference (NLI), focusing on misinformation related to the COVID-19 pandemic. We first describe the construction of the novel PANACEA dataset consisting of heterogeneous claims on COVID-19 and their respective informati

Ruixin Hong, Hongming Zhang, Xintong Yu, Changshui Zhang

Knowing the reasoning chains from knowledge to the predicted answers can help construct an explainable question answering (QA) system. Advances on QA explanation propose to explain the answers with entailment trees composed of multiple entailment steps. While current work proposes to generate entailment trees with end-to-end generative models, the steps in t

Lukáš Holík, Petr Peringer, Adam Rogalewicz, Veronika Šoková

The paper proposes a new static analysis designed to handle open programs, i.e., fragments of programs, with dynamic pointer-linked data structures - in particular, various kinds of lists - that employ advanced low-level pointer operations. The goal is to allow such programs be analysed without a need of writing analysis harnesses that would first initialise

Yinbo Yu, Jiajia Liu, Shouqing Li, Kepu Huang

Deep reinforcement learning (DRL) has made significant achievements in many real-world applications. But these real-world applications typically can only provide partial observations for making decisions due to occlusions and noisy sensors. However, partial state observability can be used to hide malicious behaviors for backdoors. In this paper, we explore t

Bence Hetényi, Stefano Bosco, Daniel Loss

An anomalous energy splitting of spin triplet states at zero magnetic field has recently been measured in germanium quantum dots. This zero-field splitting could crucially alter the coupling between tunnel-coupled quantum dots, the basic building blocks of state-of-the-art spin-based quantum processors, with profound implications for semiconducting quantum c

Jean-Baptiste Gaudemet, Jules Deschamps, Olivier Vinciguerra

The initial Climate-Extended Risk Model (CERM) addresses the estimate of climate-related financial risk embedded within a bank loan portfolio, through a climatic extension of the Basel II IRB model. It uses a Gaussian copula model calibrated with non stationary macro-correlations in order to reflect the future evolution of climate-related financial risks. In

Victor Cohen, Axel Parmentier

Optimal policies for partially observed Markov decision processes (POMDPs) are history-dependent: Decisions are made based on the entire history of observation. Memoryless policies, which take decisions based on the last observation only, are generally considered useless in the literature because we can construct POMDP instances for which optimal memoryless

Vadim Shlyonsky, Bertrand de Prelle, Florian Bodranghien, Don Patrick Bischop

We present a collection of biophysics examination problems that focus on electrodiffusion, the superposition principle, and currents in RC circuits, leading towards an understanding of the Hodgkin-Huxley model of action potentials. These problems link basic concepts in electricity to the physiology of living cells. The models described in these problems are

A. Klenke, A. Steinkopff, C. Aleshire, C. Jauregui

We present a coherently-combined femtosecond fiber CPA system based on a rod-type, Ytterbium-doped, multicore fiber with 4x4 cores. A high average power of up to 500 W (after combination and compression) could be achieved at 10 MHz repetition rate with an excellent beam quality. Additionally, <500 fs pulses with up to 600 uJ of pulse energy were also realize

Yujie Xing, Jinglun Cai, Nils Barlaug, Peng Liu

Open-domain conversational systems are assumed to generate equally good responses on multiple domains. Previous work achieved good performance on the single corpus, but training and evaluating on multiple corpora from different domains are less studied. This paper explores methods of generating relevant responses for each of multiple multi-domain corpora. We

Mihir Durve, Adriano Tiribocchi, Fabio Bonaccorso, Andrea Montessori

Deep neural networks are rapidly emerging as data analysis tools, often outperforming the conventional techniques used in complex microfluidic systems. One fundamental analysis frequently desired in microfluidic experiments is counting and tracking the droplets. Specifically, droplet tracking in dense emulsions is challenging as droplets move in tightly pack

Qingxia Li, Xinyao Yang

We prove that the steady state of a class of multidimensional reaction-diffusion systems is asymptotically stable at the intersection of unweighted space and exponentially weighted Sobolev spaces, and pay particular attention to a special case, namely, systems of equations that arise in combustion theory. The steady-state solutions considered here are the en

Giorgio Arcadi, Simone Marciano, Davide Meloni

We present a simple extension of the Standard Model with three right-handed neutrinos in a SUSY framework, with an additional U(1$)_\text{F}$ abelian flavor symmetry with a non standard leptonic charge $L_e-L_μ-L_τ$ for lepton doublets and arbitrary right-handed charges. We show that the model is able to reproduce the experimental values of the mixing angles

Sian Gooding, Manuel Tragut

Complex Word Identification (CWI) aims to detect words within a text that a reader may find difficult to understand. It has been shown that CWI systems can improve text simplification, readability prediction and vocabulary acquisition modelling. However, the difficulty of a word is a highly idiosyncratic notion that depends on a reader&#39;s first language,

Yuechen Lei, Zhi-Gang Hu, Min Wang, Yi-Meng Gao

Fully reconfigurable add-drop filters (ADFs) have important applications in optical communication and information processing. Here we demonstrate a broadly tunable add-drop filter based on a double-disk cavity optomechanical system, side-coupled with a pair of tapered fiber waveguides. By varying the coupling rates between the cavity and the two waveguides,

Annet Onnes

Knowledge-based systems have been used to monitor machines and processes in the real world. In this paper we propose the use of knowledge-based systems to monitor other AI systems in operation. We motivate and provide a problem analysis of this novel setting and subsequently propose a framework that allows for structuring future research related to this sett

R. L. Singh, C. Stehle, F. Suzuki-Vidal, M. Kozlova

Radiative shocks (RS) are complex phenomena which are ubiquitous in astrophysical environments. The study of such hypersonic shocks in the laboratory, under controlled conditions, is of primary interest to understand the physics at play and also to check the ability of numerical simulations to reproduce the experimental results. In this context, we conducted

Giovanni Montani, Nakia Carlevaro, Brunello Tirozzi

We construct a model for the turbulence near the X-point of a Tokamak device and, under suitable assumptions, we arrive to a closed equation for the electric field potential fluctuations. The analytical and numerical analysis is focused on a reduced two-dimensional formulation of the dynamics, which allows a direct mapping to the incompressible Navier-Stokes

Hedieh Ajam, Marzieh Najafi, Vahid Jamali, Robert Schober

The line-of-sight (LOS) requirement of free-space optical (FSO) systems can be relaxed by employing optical relays and optical intelligent reflecting surfaces (IRSs). Unlike radio frequency (RF) IRSs, which typically exhibit a quadratic power scaling law, the power reflected from FSO IRSs and collected at the receiver lens may scale quadratically or linearly

Santanu Saha, Simone Di Cataldo, Federico Giannessi, Alessio Cucciari

The discovery of high-$T_c$ conventional superconductivity in high-pressure hydrides has helped establish computational methods as a formidable tool to guide material discoveries in a field traditionally dominated by serendipitous experimental search. This paves the way to an ever-increasing use of data-driven approaches to the study and design of supercondu

Arash Hamzehloo, David J. Lusher, Sylvain Laizet, Neil D. Sandham

Counter-flow or counter-current configurations can maintain high turbulence intensities and exhibit a significant level of mixing. We have previously introduced a wall-bounded counter-flow turbulent channel configuration (Physical Review Fluids, 6(9), p.094603.) as an efficient framework to study compressibility effects on turbulence. Here, we extend our pre

Yifan Wang, Jing Zhao, Junwei Bao, Chaoqun Duan

Dialogue state tracking (DST) aims to predict the current dialogue state given the dialogue history. Existing methods generally exploit the utterances of all dialogue turns to assign value for each slot. This could lead to suboptimal results due to the information introduced from irrelevant utterances in the dialogue history, which may be useless and can eve

Paul J. Meza-Morales, Alessandro Fumarola, Volha Taliaronak, Afrid Shirsekar

The Heusler compounds have provided a playground of material candidates for various technological applications based on their highly diverse and tunable properties, controlled by chemical composition and crystal structure. However, physical exploration of the Heusler chemical space en masse is impossible in practice, hindering the exploration of the chemical

Ignatius Ezeani, Mahmoud El-Haj, Jonathan Morris, Dawn Knight

Welsh is an official language in Wales and is spoken by an estimated 884,300 people (29.2% of the population of Wales). Despite this status and estimated increase in speaker numbers since the last (2011) census, Welsh remains a minority language undergoing revitalization and promotion by Welsh Government and relevant stakeholders. As part of the effort to in

Naresh Saini, Promodh Pinto, Aravinth Bheemaraj, Deepak Kumar

We present the largest publicly available synthetic OCR benchmark dataset for Indic languages. The collection contains a total of 90k images and their ground truth for 23 Indic languages. OCR model validation in Indic languages require a good amount of diverse data to be processed in order to create a robust and reliable model. Generating such a huge amount

Huxiao Luo, Bernhard Ruf, Cristina Tarsi

We consider the semilinear elliptic equations $$ \left\{ \begin{array}{ll} &-Δu+V(x)u=\left(I_α\ast |u|^p\right)|u|^{p-2}u+λu\quad \hbox{for } x\in\mathbb R^N, \\ &u(x) \to 0 \hbox{ as } |x| \to\infty, \end{array} \right. $$ where $I_α$ is a Riesz potential, $p\in(\frac{N+α}N,\frac{N+α}{N-2})$, $N\geq3$, and $V $ is continuous periodic. We assume that $0$ li

Xiangjun Tang, He Wang, Bo Hu, Xu Gong

Real-time in-between motion generation is universally required in games and highly desirable in existing animation pipelines. Its core challenge lies in the need to satisfy three critical conditions simultaneously: quality, controllability and speed, which renders any methods that need offline computation (or post-processing) or cannot incorporate (often unp

Xiangjun Tang, Wenxin Sun, Yong-Liang Yang, Xiaogang Jin

Sharing short personalized videos to various social media networks has become quite popular in recent years. This raises the need for digital retouching of portraits in videos. However, applying portrait image editing directly on portrait video frames cannot generate smooth and stable video sequences. To this end, we present a robust and easy-to-use parametr

Arash Amini, Arul Selvam Periyasamy, Sven Behnke

6D object pose estimation is a crucial prerequisite for autonomous robot manipulation applications. The state-of-the-art models for pose estimation are convolutional neural network (CNN)-based. Lately, Transformers, an architecture originally proposed for natural language processing, is achieving state-of-the-art results in many computer vision tasks as well

Xu Wang

Previously we proposed a new approach of exciting the $^{229}$Th nucleus using laser-driven electron recollision [W. Wang et al., Phys. Rev. Lett. 127, 052501 (2021)]. The current article is aimed to elaborate the method by explaining further theoretical details and presenting extended new results. The method has also been improved by adopting the electronic

Simone Virili

We combine a combinatorial idea of Benjamin Weiss and some localization theory of Grothendieck categories to give a short and completely self-contained proof of the following recent result of Hanfeng Li and Bingbing Liang: Given a left Noetherian ring $R$ and a sofic group $G$, the group-ring $R[G]$ is stably finite.

Nicolas Babinet, Taro Kimura

We study matrix models involving Pfaffian interactions as generalizations of the standard $β= 1$ and $β= 4$ matrix models. We present the Pfaffian formulas for the partition function and the characteristic polynomial averages. We also explore the matrix chain with the Pfaffian interaction, which realizes the BCD-type quiver matrix models.

Hannah Devinney, Jenny Björklund, Henrik Björklund

The rise of concern around Natural Language Processing (NLP) technologies containing and perpetuating social biases has led to a rich and rapidly growing area of research. Gender bias is one of the central biases being analyzed, but to date there is no comprehensive analysis of how &#34;gender&#34; is theorized in the field. We survey nearly 200 articles con

Marco Lewis, Sadegh Soudjani, Paolo Zuliani

Controlled operations allow for the entanglement of quantum registers. In particular, a controlled-$U$ gate allows an operation, $U$, to be applied to the target register and entangle the results to certain values in the control register. This can be generalised by making use of the classical notion of conditional statements, where if a value (or state) sati

Ning Wang

This paper deals with the utterance-level modalities missing problem with uncertain patterns on emotion recognition in conversation (ERC) task. Present models generally predict the speaker&#39;s emotions by its current utterance and context, which is degraded by modality missing considerably. Our work proposes a framework Missing-Modality Robust emotion Reco

Jiri Vlasak, Michal Sojka, Zdeněk Hanzálek

The problem of path planning for automated parking is usually presented as finding a collision-free path from initial to goal positions, where three out of four parking slot edges represent obstacles. We rethink the path planning problem for parallel parking by decomposing it into two independent parts. The topic of this paper is finding optimal parking slot

Joan Mateu, Laura Prat

In this paper we study removable singularities for solutions of the fractional heat equation in time varying domains. We introduce associated capacities and we study some of its metric and geometric properties.

Xiaodong Yang, Xinfang Nie, Tao Xin, Dawei Lu

Quantum systems are exceedingly difficult to engineer because they are sensitive to various types of noises. In particular, time-dependent noises are frequently encountered in experiments but how to overcome them remains a challenging problem. In this work, we extend and apply the recently proposed robust control technique of inverse geometric optimization t

Sergey Gaifullin, Georgiy Shirinkin

Trinomial hypersurfaces form a natural class of affine algebraic varieties closely connected with varieties admitting a torus action of complexity one. We investigate orbits of the automorphism group on these hypersurfaces. We prove that each nonrigid trinomial variety has finite number of orbits. We investigate singular orbits and this gives us description

Shaokang Hu, Derrick Wing Kwan Ng, Jinhong Yuan

In this paper, the secure performance of multiuser multiple-input single-output wireless communications systems assisted by a multifunctional active intelligent reflection surface (IRS) is investigated. The active IRS can simultaneously reflect and amplify the incident signals and emit artificial noise to combat potential wiretapping. We minimize the total s

Hervé Chabannne, Vincent Despiegel, Linda Guiga

We introduce a new wallet recovery process. Our solution associates 1) visual passwords: a photograph of a secretly picked object (Chabanne et al., 2013) with 2) ImageNet classifiers transforming images into binary vectors and, 3) obfuscated fuzzy matching (Galbraith and Zobernig, 2019) for the storage of visual passwords/retrieval of wallet seeds. Our exper

Bihui Zou, Chao Song, Zipeng He, Jaehyung Ju

The ability to morph flat sheets into complex 3D shapes is extremely useful for fast manufacturing and saving materials while also allowing volumetrically efficient storage and shipment and a functional use. Direct 4D printing is a compelling method to morph complex 3D shapes out of as-printed 2D plates. However, most direct 4D printing methods require multi

Miguel A. Martin-Delgado

General Relativity (GR) is shown to be a complete theory with respect to the isochrony of the pendulum. This guarantees that time can be measured with a mechanical clock within the theory itself as a matter of principle. The proper and coordinate oscillation frequencies of a simple pendulum are computed as a function of 3 coordinate parameters: the distance

Alessandro Brighente, Mauro Conti, Hanan Idriss, Stefano Tomasin

The high configurability and low cost of Reflective Intelligent Surfaces (RISs) made them a promising solution for enhancing the capabilities of Beyond Fifth-Generation (B5G) networks. Recent works proposed to mount RISs on Unmanned Aerial Vehicles (UAVs), combining the high network configurability provided by RIS with the mobility brought by UAVs. However,

Mikhail Dyachenko, Erlan Nursultanov, Sergey Tikhonov, Ferenc Weisz

We obtain Fourier inequalities in the weighted $L_p$ spaces for any $1<p<\infty$ involving the Hardy-Cesàro and Hardy-Bellman operators. We extend these results to product Hardy spaces for $p\le 1$. Moreover, boundedness of the Hardy-Cesàro and Hardy-Bellman operators in various spaces (Lebesgue, Hardy, BMO) is discussed. One of our main tools is an appropri

L. P. Chaintron, Álvaro Mateos González, Laurent Mertz, Philippe Moireau

We address the problem of deterministic sequential estimation for a nonsmooth dynamics in R governed by a variational inequality, as illustrated by the Skorokhod problem with a reflective boundary condition at 0. For smooth dynamics, Mortensen introduced an energy for the likelihood that the state variable produces-up to perturbations disturbances-a given ob

Hyowon Kim, Karl Granström, Lennart Svensson, Sunwoo Kim

Radio-based vehicular simultaneous localization and mapping (SLAM) aims to localize vehicles while mapping the landmarks in the environment. We propose a sequence of three Poisson multi-Bernoulli mixture (PMBM) based SLAM filters, which handle the entire SLAM problem in a theoretically optimal manner. The complexity of the three proposed SLAM filters is prog

Flera G. Kopylova, Alexander I. Kopylov

The paper presents the results of studying the dynamics of galaxies, properties of early-type galaxies, properties of galaxies with the quenched star formation (QGs) in the A 2142 based on the archival data from the Sloan Digital Sky Survey. We found the observed halo boundary, the splashback radius $R_{sp}$, which is equal to 4.12 Mpc ($M_r < -20\,.\!\!^{\r

Eklavya Sarkar, Pavel Korshunov, Laurent Colbois, Sébastien Marcel

Morphing attacks are a threat to biometric systems where the biometric reference in an identity document can be altered. This form of attack presents an important issue in applications relying on identity documents such as border security or access control. Research in generation of face morphs and their detection is developing rapidly, however very few data

Helmut Abels, Felicitas Bürger, Harald Garcke

We consider a system consisting of a geometric evolution equation for a hypersurface and a parabolic equation on this evolving hypersurface. More precisely, we discuss mean curvature flow scaled with a term that depends on a quantity defined on the surface coupled to a diffusion equation for that quantity. Several properties of solutions are analyzed. Emphas

Xinzhe Wu, Davor Davidovic, Sebastian Achilles, Edoardo Di Napoli

As modern massively parallel clusters are getting larger with beefier compute nodes, traditional parallel eigensolvers, such as direct solvers, struggle keeping the pace with the hardware evolution and being able to scale efficiently due to additional layers of communication and synchronization. This difficulty is especially important when porting traditiona

Martin Tømterud, Sabrina D. Eder, Christin Büchner, Markus Heyde

The boson peak is an excess in the phonon density of states relative to the Debye Model, which occurs at frequencies below the Debye limit. It is present in most amorphous materials and, as was recently shown, can sometimes be found also in crystals. Here we present first experimental evidence of the boson peak in a 2D material, namely 2D silica (SiO$_2$). T

Christoph Schweimer, Christine Gfrerer, Florian Lugstein, David Pape

Online social networks are a dominant medium in everyday life to stay in contact with friends and to share information. In Twitter, users can connect with other users by following them, who in turn can follow back. In recent years, researchers studied several properties of social networks and designed random graph models to describe them. Many of these appro

Damien Bégué, Asaf Pe&#39;er, Guoqiang Zhang, BinBin Zhang

We introduce a new GPU-accelerated general-relativistic magneto-hydrodynamic (GR-MHD) code based on HARM which we call cuHARM. The code is written in CUDA-C and uses OpenMP to parallelize multi-GPU setups. Our code allows us to run high resolution simulations of accretion disks and the formation and structure of jets without the need of multi-node supercompu

Adrien Suau, Marc Vuffray, Andrey Y. Lokhov, Lukasz Cincio

As the variety of commercially available quantum computers continues to increase so does the need for tools that can characterize, verify and validate these computers. This work explores using quantum state tomography for characterizing the performance of individual qubits and develops a vector field visualization for presentation of the results. The propose

Anshu Kumari

In this article, the association of solar radio type IV bursts with active region location on the Sun is studied for the solar cycle 24. The active regions associated with moving and stationary type IV bursts are categorised as close to disk center and far from disk center regions based on their location on the solar surface (i.e, $\leq 45^{\circ}$ or $\geq

Kai Cheng, Hao Chen, Wei Yin, Guangkai Xu

Multi-view depth estimation plays a critical role in reconstructing and understanding the 3D world. Recent learning-based methods have made significant progress in it. However, multi-view depth estimation is fundamentally a correspondence-based optimization problem, but previous learning-based methods mainly rely on predefined depth hypotheses to build corre

Bing Yao, Mingjun Zhang, Sihua Yang, Guoxing Wang

For building up twin-graphic lattices towards topological cryptograph, we define four kinds of new odd-magic-type colorings: odd-edge graceful-difference total coloring, odd-edge edge-difference total coloring, odd-edge edge-magic total coloring, and odd-edge felicitous-difference total coloring in this article. Our RANDOMLY-LEAF-ADDING algorithms are based

Neeraj Chhimwal, Anirudh Gupta, Rishabh Gaur, Harveen Singh Chadha

In this paper, we propose a pipeline to find the number of speakers, as well as audios belonging to each of these now identified speakers in a source of audio data where number of speakers or speaker labels are not known a priori. We used this approach as a part of our Data Preparation pipeline for Speech Recognition in Indic Languages (https://github.com/Op

Huan Zhao, Linghan Zhu, Xiangzhi Li, Vigneshwaran Chandrasekaran

Interlayer excitons (IXs) formed at the interface of atomically-thin semiconductors possess various novel properties. In a parallel development, nanoscale strain engineering has emerged as an effective means for creating 2D quantum light sources. Exploring the intersection of these two exciting areas, where strain and defects are exploited for the manipulati

Haipeng Sun, Junwei Bao, Youzheng Wu, Xiaodong He

A typical end-to-end task-oriented dialog system transfers context into dialog state, and upon which generates a response, which usually faces the problem of error propagation from both previously generated inaccurate dialog states and responses, especially in low-resource scenarios. To alleviate these issues, we propose BORT, a back and denoising reconstruc

Cheol-Hyun Cho, Wonbo Jeong, Kyoungmo Kim, Kyungmin Rho

Burban-Drozd showed that the degenerate cusp singularities have tame Cohen-Macaulay representation type, and classified all indecomposable Cohen-Macaulay modules over them. One of their main example is the non-isolated singularity $W=xyz$. On the other hand, Abouzaid-Auroux-Efimov-Katzarkov-Orlov showed that $W=xyz$ is mirror to a pair of pants. In this pape

Jiongyu Guo, Defang Chen, Can Wang

Existing knowledge distillation methods on graph neural networks (GNNs) are almost offline, where the student model extracts knowledge from a powerful teacher model to improve its performance. However, a pre-trained teacher model is not always accessible due to training cost, privacy, etc. In this paper, we propose a novel online knowledge distillation frame

Massimo Gobbino, Nicola Picenni

We consider the Perona-Malik functional in dimension one, namely an integral functional whose Lagrangian is convex-concave with respect to the derivative, with a convexification that is identically zero. We approximate and regularize the functional by adding a term that depends on second order derivatives multiplied by a small coefficient. We investigate the

Hilal Asi, Vitaly Feldman, Kunal Talwar

We study the problem of mean estimation of $\ell_2$-bounded vectors under the constraint of local differential privacy. While the literature has a variety of algorithms that achieve the asymptotically optimal rates for this problem, the performance of these algorithms in practice can vary significantly due to varying (and often large) hidden constants. In th

Alexey I. Gubin, Irina A. Protsenko, Alexander A. Barannik, Svetlana Vitusevich

Studies of biological solutions require high measurement accuracy, the ability to detect low changes in substance concentration, and small amounts of the liquid under test. A microwave complex permittivity measurement technique based on a high-quality-factor whispering-gallery-mode resonator with a microfluidic chip allows small amounts of dielectric liquids

Longfei Yin, Yijie Mao, Onur Dizdar, Bruno Clerckx

This letter is the second part of a three-part tutorial focusing on rate-splitting multiple access (RSMA) for 6G. As Part II of the tutorial, this letter addresses the interplay between RSMA and integrated radar sensing and communications (ISAC). In particular, we introduce a general RSMAassisted ISAC architecture, where the ISAC platform has a dual capabili

Zhen Zhang, Simona Ispas, Walter Kob

We use large-scale simulations to investigate the dynamic fracture of silica and sodium-silicate glasses under uniaxial tension. The stress-strain curves demonstrate that silica glass is brittle whereas the glasses rich in Na show pronounced ductility. A strong composition dependence is also seen in the crack velocity which is on the order of 1800 m/s for gl

Yongqi Zhang, Zhanke Zhou, Quanming Yao, Yong Li

While hyper-parameters (HPs) are important for knowledge graph (KG) learning, existing methods fail to search them efficiently. To solve this problem, we first analyze the properties of different HPs and measure the transfer ability from small subgraph to the full graph. Based on the analysis, we propose an efficient two-stage search algorithm KGTuner, which

Nissim Fraija, Antonio Galvan-Gamez, Boris Betancourt Kamenetskaia, Maria G. Dainotti

Gamma-ray bursts (GRBs) are fascinating extragalactic objects. They represent a fantastic opportunity to investigate unique properties not exhibited in other sources. Multi-wavelength afterglow observations from some short- and long-duration GRBs reveal an atypical long-lasting emission that evolves differently from the canonical afterglow light curves favor

Feng Sun, Cong Bai

Precipitation nowcasting based on radar echo maps is essential in meteorological research. Recently, Convolutional RNNs based methods dominate this field, but they cannot be solved by parallel computation resulting in longer inference time. FCN based methods adopt a multi-frame-to-single-frame inference (MSI) strategy to avoid this problem. They feedback int

Yuhang Liu, Wei Wei, Daowan Peng, Feida Zhu

In recent years, the pre-training-then-fine-tuning paradigm has yielded immense success on a wide spectrum of cross-modal tasks, such as visual question answering (VQA), in which a visual-language (VL) model is first optimized via self-supervised task objectives, e.g., masked language modeling (MLM) and image-text matching (ITM), and then fine-tuned to adapt

Abhinav Joshi, Ashwani Bhat, Ayush Jain, Atin Vikram Singh

Emotions are an inherent part of human interactions, and consequently, it is imperative to develop AI systems that understand and recognize human emotions. During a conversation involving various people, a person&#39;s emotions are influenced by the other speaker&#39;s utterances and their own emotional state over the utterances. In this paper, we propose CO

Aigerim Bogyrbayeva, Meraryslan Meraliyev, Taukekhan Mustakhov, Bissenbay Dauletbayev

This paper provides a systematic overview of machine learning methods applied to solve NP-hard Vehicle Routing Problems (VRPs). Recently, there has been a great interest from both machine learning and operations research communities to solve VRPs either by pure learning methods or by combining them with the traditional hand-crafted heuristics. We present the

Denis S. Grebenkov

Depletion of natural and artificial resources is a fundamental problem and a potential cause of economic crises, ecological catastrophes, and death of living organisms. Understanding the depletion process is crucial for its further control and optimized replenishment of resources. In this paper, we investigate a stock depletion by a population of species tha

Yasser Abduallah, Jason T. L. Wang, Prianka Bose, Genwei Zhang

The disturbance storm time (Dst) index is an important and useful measurement in space weather research. It has been used to characterize the size and intensity of a geomagnetic storm. A negative Dst value means that the Earth&#39;s magnetic field is weakened, which happens during storms. In this paper, we present a novel deep learning method, called the Dst

Fan Zhang, Qiuying Peng, Yulin Wu, Zheng Pan

Recently, industrial recommendation services have been boosted by the continual upgrade of deep learning methods. However, they still face de-biasing challenges such as exposure bias and cold-start problem, where circulations of machine learning training on human interaction history leads algorithms to repeatedly suggest exposed items while ignoring less-act

Muhan Wang, Zhe Zhang, Yue Wang, Silin Gao

Synthetic aperture radar (SAR) tomography (TomoSAR) has attracted remarkable interest for its ability in achieving three-dimensional reconstruction along the elevation direction from multiple observations. In recent years, compressed sensing (CS) technique has been introduced into TomoSAR considering for its super-resolution ability with limited samples. Whe

Rong Ye, Mingxuan Wang, Lei Li

How can we learn unified representations for spoken utterances and their written text? Learning similar representations for semantically similar speech and text is important for speech translation. To this end, we propose ConST, a cross-modal contrastive learning method for end-to-end speech-to-text translation. We evaluate ConST and a variety of previous ba

Asadullah Hill Galib, Andrew McDonald, Tyler Wilson, Lifeng Luo

Accurate forecasting of extreme values in time series is critical due to the significant impact of extreme events on human and natural systems. This paper presents DeepExtrema, a novel framework that combines a deep neural network (DNN) with generalized extreme value (GEV) distribution to forecast the block maximum value of a time series. Implementing such a

Mikhail S. Podoshvedov, Sergey A. Podoshvedov

We introduce a family of new continuous variable states of definite parity originating from even single mode squeezed vacuum state by subtracting an arbitrary number of photons from it.

Qinghe Tian, Jean-Claude Franchitti

Painting is one of the ways for people to express their ideas, but what if people with disabilities in hands want to paint? To tackle this challenge, we create an end-to-end solution that can generate artistic images from text descriptions. However, due to the lack of datasets with paired text description and artistic images, it is hard to directly train an