August 2022 arXiv papers — page 130

Rehana Begum Popy, Julia Frank, Robert L. Stamps

Geometrical designs of interacting nanomagnets have been studied extensively in the form of two dimensional arrays called artificial spin ice. These systems are usually designed to create geometrical frustration and are of interest for the unusual and often surprising phenomena that can emerge. Advanced lithographic and element growth techniques have enabled

Melvyn B. Nathanson

Let $\Omega$ be a set of positive integers and let $f:\Omega \rightarrow \Omega$ be an arithmetic function. Let $V = (v_i)_{i=1}^n$ be a finite sequence of positive integers. An integer $m \in \Omega$ has \textit{increasing-decreasing pattern} $V$ with respect to $f$ if, for all odd integers $i \in \{1,\ldots, n\}$, \[ f^{v_1+ \cdots + v_{i-1}}(m) < f^{v_1+

Richard Archibald, Feng Bao, Jiongmin Yong

In this work, we introduce a stochastic maximum principle (SMP) approach for solving the reinforcement learning problem with the assumption that the unknowns in the environment can be parameterized based on physics knowledge. For the development of numerical algorithms, we shall apply an effective online parameter estimation method as our exploration techniq

Yehonatan Fridman, Re'em Harel, Gal Oren

HPC as a service (HPCaaS) is a new way to expose HPC resources via cloud services. However, continued effort to port large-scale tightly coupled applications with high interprocessor communication to multiple (and many) nodes synchronously, as in on-premise supercomputers, is still far from satisfactory due to network latencies. As a consequence, in said cas

Ashutosh Kumar Alok, Neetu Raj Singh Chundawat, Arindam Mandal, Trisha Sarkar

Any observable repercussion of electromagnetic properties of neutrinos will provide a perspicuous signature of new physics. This includes the phenomenon of neutrino spin flip in the propinquity of an external magnetic field. In this work, we study the inklings of spin flip in a neutron star with a radially varying magnetic field and matter density, known as

Raj Patel, Chia-Wei Hsing, Serkan Sahin, Saeed S. Jahromi

Partial Differential Equations (PDEs) are used to model a variety of dynamical systems in science and engineering. Recent advances in deep learning have enabled us to solve them in a higher dimension by addressing the curse of dimensionality in new ways. However, deep learning methods are constrained by training time and memory. To tackle these shortcomings,

Lamiya A. Mowla, Kartheik G. Iyer, Guillaume Desprez, Vicente Estrada-Carpenter

Using data from JWST, we analyze the compact sources ("sparkles") located around a remarkable $z_{\rm spec}=1.378$ galaxy (the "Sparkler") that is strongly gravitationally lensed by the $z=0.39$ galaxy cluster SMACS J0723.3-7327. Several of these compact sources can be cross-identified in multiple images, making it clear that they are associated with the hos

Keyur Joshi, Chiao Hsieh, Sayan Mitra, Sasa Misailovic

Modern autonomous vehicle systems use complex perception and control components. These components can rapidly change during development of such systems, requiring constant re-testing. Unfortunately, high-fidelity simulations of these complex systems for evaluating vehicle safety are costly. The complexity also hinders the creation of less computationally int

Rachel Chaiser, Maeve Coates-Welsh, Robin J. Deeley, Annika Farhner

We study invariants associated to Smale spaces obtained from an expanding endomorphism on a (closed connected Riemannian) flat manifold. Specifically, the relevant invariants are the $K$-theory of the associated $C^*$-algebras and Putnam's homology theory for Smale spaces. The latter is isomorphic to the groupoid homology of the groupoids used to construct t

D. D. Cherkashin, A. J. Kanel-Belov, G. A. Strukov, V. A. Voronov

We prove that for an arbitrary $\varepsilon > 0$ holds \[ \chi (\mathbb{R}^3 \times [0,\varepsilon]^6) \geq 10, \] where $\chi(M)$ stands for the chromatic number of an (infinite) graph with the vertex set $M$ and the edge set consists of pairs of monochromatic points at the distance 1 apart.

Daniel W. Cranston, Reem Mahmoud

The coloring reconfiguration graph $\mathcal{C}_k(G)$ has as its vertex set all the proper $k$-colorings of $G$, and two vertices in $\mathcal{C}_k(G)$ are adjacent if their corresponding $k$-colorings differ on a single vertex. Cereceda conjectured that if an $n$-vertex graph $G$ is $d$-degenerate and $k\geq d+2$, then the diameter of $\mathcal{C}_k(G)$ is

Omprokash Das, Christopher Hacon

In this short article we show that if $(X, B)$ is a compact K\"ahler klt pair of maximal Albanese dimension, then it has a good minimal model, i.e. there is a bimeromorphic contraction $\phi:X\dashrightarrow X'$ such that $K_{X'}+B'$ is semi-ample.

Gokul Swamy, Sanjiban Choudhury, J. Andrew Bagnell, Zhiwei Steven Wu

We consider imitation learning problems where the learner's ability to mimic the expert increases throughout the course of an episode as more information is revealed. One example of this is when the expert has access to privileged information: while the learner might not be able to accurately reproduce expert behavior early on in an episode, by considering t

K. A. Gutiérrez-Dávila, A. López-Ortega

We calculate numerically the quasinormal frequencies of the Klein-Gordon and Dirac fields moving in the two-dimensional dimensionally reduced BTZ black hole. Our work extends results previously published on the damped oscillations of this black hole. First, we compute the quasinormal frequencies of the minimally coupled Klein-Gordon field for a range of the

Elan J. Weiss, Logan Ward, Christian Oberdorfer, Travis Withrow

A critical limitation to the wide-scale use of classical molecular dynamics for alloy design is the limited availability of suitable interatomic potentials. Here, we introduce the Rapid Alloy Method for Producing Accurate General Empirical Potentials or RAMPAGE, a computationally economical procedure to generate binary embedded-atom model potentials from alr

Jaouad El-hassouny, Ahmed Jellal, El Houssine Atmani

We investigate spin-dependent transmission in a curved graphene superlattice of $N$ cells where each one is made up of four regions. The first is concave, and the third is convex, two arcs of circles separated by a distance $d$ from flat graphene sheets. The tunneling analysis allows us to determine all transmission and reflection channels associated with ou

Yining Liu, Yanfeng Ouyang

This study presents a multi-zone queuing network model for steady-state ride-pooling operations that serve heterogeneous demand, and then builds upon this model to optimize the design of ride-pooling services. Spatial heterogeneity is addressed by partitioning the study region into a set of relatively homogeneous zones, and a set of criteria are imposed to a

Luis Sanchez Tapia

Convolutional Neural Networks (CNN) have provided new and accurate methods for processing digital images and videos. Yet, training CNNs is extremely demanding in terms of computational resources. Also, for specific applications, the standard use of transfer learning also tends to require far more resources than what may be needed. Furthermore, the final syst

Horia D. Cornean, Massimo Moscolari, Kasper S. Sørensen

We consider two-dimensional unbounded magnetic Dirac operators, either defined on the whole plane, or with infinite mass boundary conditions on a half-plane. Our main results use techniques from elliptic PDEs and integral operators, while their topological consequences are presented as corollaries of some more general identities involving magnetic derivative

Enrico Catalano

Understanding the biophysical and magnetic interactions of nanoparticles (NPs) with cell mem-branes is critical for developing effective nanocarrier systems for drug delivery applications and targeted nanophysics applications. Recent discoveries in nanomedicine can be used to test an in vitro system that reproduce a similar tumor model. Iron-oxide nanopartic

Anasuya Lyons, Soonwon Choi, Ehud Altman

We formulate a semi-classical circuit model to clarify the role of quantum entanglement in the recently discovered encoding phase transitions in quantum circuits with measurements. As a starting point we define a random circuit model with nearest neighbor classical gates interrupted by erasure errors. In analogy with the quantum setting, this system undergoe

Jun-Ru Li, Kyle Matsuda, Calder Miller, Annette N. Carroll

Strongly interacting spins underlie many intriguing phenomena and applications ranging from magnetism to quantum information processing. Interacting spins combined with motion display exotic spin transport phenomena, such as superfluidity arising from pairing of spins induced by spin attraction. To understand these complex phenomena, an interacting spin syst

G. Audagnotto, C. H. Keitel, A. Di Piazza

Accelerated charges emit both electromagnetic and gravitational radiation. Classically, it was found that the electromagnetic energy spectrum radiated by an electron in a monochromatic plane wave is proportional to the corresponding gravitational one. Quantum mechanically, it was shown that the amplitudes of graviton photoproduction and Compton scattering ar

Maibam Ricky Devi, Kalpana Bora

One of the possible ways to explain the observed flavour structure of fundamental particles is to include flavor symmetries in the theories. In this work, we investigate the rare charged lepton flavour violating (cLFV) decay process ($\mu \rightarrow e\gamma$) in two of the low scale ($\sim$TeV) seesaw models: (i) the Inverse seesaw (ISS) and (ii) Linear see

Perfect Y. Gidisu, Michiel E. Hochstenbach

We present block variants of the discrete empirical interpolation method (DEIM); as a particular application, we will consider a CUR factorization. The block DEIM algorithms are based on the concept of the maximum volume of submatrices and a rank-revealing QR factorization. We also present a version of the block DEIM procedures, which allows for adaptive cho

Shreyasi Datta, Yewei Xu

We prove inheritance of measure zero property of the set of singular vectors for affine subspaces and submanifolds inside those affine subspaces. We define a notion of $n$-singularity for matrices, which is closely related to the uniform exponent of irrationality. For certain affine subspaces, we show that the set of singular vectors has measure zero if and

W. Simeth, Z. Wang, E. A. Ghioldi, D. M. Fobes

Electrons at the border of localization generate exotic states of matter across all classes of strongly correlated electron materials and many other quantum materials with emergent functionality. Heavy electron metals are a model example, in which magnetic interactions arise from the opposing limits of localized and itinerant electrons. This remarkable duali

Michail Christos Doukas, Evangelos Ververas, Viktoriia Sharmanska, Stefanos Zafeiriou

We present Free-HeadGAN, a person-generic neural talking head synthesis system. We show that modeling faces with sparse 3D facial landmarks are sufficient for achieving state-of-the-art generative performance, without relying on strong statistical priors of the face, such as 3D Morphable Models. Apart from 3D pose and facial expressions, our method is capabl

Rabsan G. Ahmed, Tejinder P. Singh

The term Bell's theorem refers to a set of closely related results which imply that quantum mechanics is incompatible with local hidden variable theories. Bell's inequality is the statement that if measurements are performed independently on two space-like separated particles of an entangled pair, the assumption that outcomes depend on hidden variables impli

Hailiang Liu, Xuping Tian

In this paper, we propose SGEM, Stochastic Gradient with Energy and Momentum, to solve a large class of general non-convex stochastic optimization problems, based on the AEGD method that originated in the work [AEGD: Adaptive Gradient Descent with Energy. arXiv: 2010.05109]. SGEM incorporates both energy and momentum at the same time so as to inherit their d

Brendan Hertel, Matthew Pelland, S. Reza Ahmadzadeh

Learning from Demonstration (LfD) is a popular method of reproducing and generalizing robot skills from human-provided demonstrations. In this paper, we propose a novel optimization-based LfD method that encodes demonstrations as elastic maps. An elastic map is a graph of nodes connected through a mesh of springs. We build a skill model by fitting an elastic

Ludovic Berthier, David R. Reichman

The physics of the glass transition and amorphous materials continues to attract the attention of a wide research community after decades of effort. Supercooled liquids and glasses have been studied numerically since the advent of molecular dynamics and Monte Carlo simulations in the last century. Computer studies have greatly enhanced both experimental disc

Navjot Kaur, Cheng-Chun Lee, Ali Mostafavi, Ali Mahdavi-Amiri

This paper presents \dahitra, a novel deep-learning model with hierarchical transformers to classify building damages based on satellite images in the aftermath of natural disasters. Satellite imagery provides real-time and high-coverage information and offers opportunities to inform large-scale post-disaster building damage assessment, which is critical for

Fivos Kalogiannis, Ioannis Anagnostides, Ioannis Panageas, Emmanouil-Vasileios Vlatakis-Gkaragkounis

Computing Nash equilibrium policies is a central problem in multi-agent reinforcement learning that has received extensive attention both in theory and in practice. However, provable guarantees have been thus far either limited to fully competitive or cooperative scenarios or impose strong assumptions that are difficult to meet in most practical applications

Marco Olivieri

We study a system composed of a hydrogen atom interacting with an infinite conductor wall. The interaction energy decays like $L^{-3}$, where $L$ is the distance between the atom and the wall, due to the emergence of the van der Waals forces. In this paper we show how, considering the contributions from the quantum fluctuations of the electromagnetic field,

D. A. St-Onge, M. Barnes, F. I. Parra

We formulate a generalized periodic boundary condition as a limit of the standard twist-and-shift parallel boundary condition that is suitable for simulations of plasmas with low magnetic shear. This is done by applying a phase shift in the binormal direction when crossing the parallel boundary. While this phase shift can be set to zero without loss of gener

Kevin Carrier, Thomas Debris-Alazard, Charles Meyer-Hilfiger, Jean-Pierre Tillich

The security of code-based cryptography relies primarily on the hardness of generic decoding with linear codes. The best generic decoding algorithms are all improvements of an old algorithm due to Prange: they are known under the name of information set decoders (ISD). A while ago, a generic decoding algorithm which does not belong to this family was propose

D. V. Babukhin

Harrow-Hassidim-Lloyd algorithm (HHL) allows for the exponentially faster solution of a system of linear equations. However, this algorithm requires the postselection of an ancilla qubit to obtain the solution. This postselection makes the algorithm result probabilistic. Here we show conditions when the HHL algorithm can work without postselection of ancilla

Seunghoon Lee, Joonho Lee, Huanchen Zhai, Yu Tong

The idea to use quantum mechanical devices to simulate other quantum systems is commonly ascribed to Feynman. Since the original suggestion, concrete proposals have appeared for simulating molecular and materials chemistry through quantum computation, as a potential ``killer application''. Indications of potential exponential quantum advantage in artificial

Cyndia Yu, Zeeshan Ahmed, J. Mitch D'Ewart, Josef C. Frisch

We present the details of a simulation suite for modeling the effects of readout with SLAC Microresonator RF (SMuRF) electronics. The SMuRF electronics are a warm readout and control system for use with superconducting microwave resonator-based detector systems. The system has been used with the BICEP/Keck program and will be used on the upcoming Simons Obse

Rouven Frassek, István M. Szécsényi

In this note we construct Q-operators for the spin s open Heisenberg XXX chain with diagonal boundaries in the framework of the quantum inverse scattering method. Following the algebraic Bethe ansatz we diagonalise the introduced Q-operators using the fundamental commutation relations. By acting on Bethe off-shell states and explicitly evaluating the trace i

Yu Fu, Jacopo Ghiglieri, Shahin Iqbal, Aleksi Kurkela

We employ the QCD kinetic theory, including next-to-leading(NLO) order corrections in coupling constant, to study the evolution of weakly coupled non-Abelian plasmas towards thermal equilibrium. For two characteristic far-from-equilibrium systems with either under- or over-occupied initial conditions, the NLO corrections remain well under control for a wide

Ravi Yadav, Lei Xu, Michele Pizzochero, Jeroen van den Brink

Although chromium trihalides are widely regarded as a promising class of two-dimensional magnets for next-generation devices, an accurate description of their electronic structure and magnetic interactions has proven challenging to achieve. Here, we quantify electronic excitations and spin interactions in Cr$X_3$ ($X=$~Cl, Br, I) using embedded many-body wav

Peizhen Bai, Filip Miljković, Bino John, Haiping Lu

Predicting drug-target interaction is key for drug discovery. Recent deep learning-based methods show promising performance but two challenges remain: (i) how to explicitly model and learn local interactions between drugs and targets for better prediction and interpretation; (ii) how to generalize prediction performance on novel drug-target pairs from differ

Haoyang Ma, Qingchao Shen, Yongqiang Tian, Junjie Chen

Deep Learning (DL) compilers are widely adopted to optimize advanced DL models for efficient deployment on diverse hardware. Their quality has profound effect on the quality of compiled DL models. A recent bug study shows that the optimization of high-level intermediate representation (IR) is the most error-prone compilation stage. Bugs in this stage are acc

Sara Romiti, Christopher Inskip, Viktoriia Sharmanska, Novi Quadrianto

Machine learning classifiers are typically trained to minimise the average error across a dataset. Unfortunately, in practice, this process often exploits spurious correlations caused by subgroup imbalance within the training data, resulting in high average performance but highly variable performance across subgroups. Recent work to address this problem prop

Konstantin Tiurev, Peter-Jan H. S. Derks, Joschka Roffe, Jens Eisert

A common approach to studying the performance of quantum error correcting codes is to assume independent and identically distributed single-qubit errors. However, the available experimental data shows that realistic errors in modern multi-qubit devices are typically neither independent nor identical across qubits. In this work, we develop and investigate the

Sathish R. Kuppuswamy, Hugo Kerstens, Chun-Xiao Liu, Lin Wang

A scalable spin-based quantum processor requires a suitable semiconductor heterostructure and a gate design, with multiple alternatives being investigated. Characterizing such devices experimentally is a demanding task, with the full development cycle taking at least months. While numerical simulations are more time-efficient, their predictive power is limit

Qibing Bai, Tom Ko, Yu Zhang

In human speech, the attitude of a speaker cannot be fully expressed only by the textual content. It has to come along with the intonation. Declarative questions are commonly used in daily Cantonese conversations, and they are usually uttered with rising intonation. Vanilla neural text-to-speech (TTS) systems are not capable of synthesizing rising intonation

Ji-Chong Yang, Yu-Chen Guo, Bing Liu, Tong Li

The search for magnetic monopoles has been a longstanding concern of the physics community for nearly a century. However, up to now, the existence of elementary magnetic monopoles remains an open question. The electroweak 't Hooft-Polyakov monopoles have been predicted with mass at the order of 10 TeV. This mass scale is unreachable at current colliders. Rec

Eduardo C. Garrido Merchán, Sara Lumbreras

Consciousness and intelligence are properties commonly understood as dependent by folk psychology and society in general. The term artificial intelligence and the kind of problems that it managed to solve in the recent years has been shown as an argument to establish that machines experience some sort of consciousness. Following the analogy of Russell, if a

Gopalan Sajith, Sanjeev Saxena

In this note we give two proofs of Brooks' Theorem. The first is obtained by modifying an earlier proof and the second by combining two earlier proofs. We believe these proofs are easier to teach in Computer Science courses.

Jia Huang

We generalize recent work of Andrews, Just, and Simay on modular palindromic compositions and anti-palindromic compositions by viewing all compositions partially (modular) palindromic or anti-palindromic. More precisely, we enumerate compositions by the extent to which they are (modular) palindromic or anti-palindromic. We obtain various closed formulas from

Amir Dembo, Izumi Okada

We establish both the $\limsup$ and the $\liminf$ law of the iterated logarithm (LIL), for the capacity of the range of a simple random walk in any dimension $d\ge 3$. While for $d \ge 4$, the order of growth in $n$ of such LIL at dimension $d$ matches that for the volume of the random walk range in dimension $d-2$, somewhat surprisingly this correspondence

Robert J. Piechocki, Xiaoyang Wang, Mohammud J. Bocus

A new method for multimodal sensor fusion is introduced. The technique relies on a two-stage process. In the first stage, a multimodal generative model is constructed from unlabelled training data. In the second stage, the generative model serves as a reconstruction prior and the search manifold for the sensor fusion tasks. The method also handles cases wher

Matthias Thamm, Bernd Rosenow

As the complexity of quantum systems such as quantum bit arrays increases, efforts to automate expensive tuning are increasingly worthwhile. We investigate machine learning based tuning of gate arrays using the CMA-ES algorithm for the case study of Majorana wires with strong disorder. We find that the algorithm is able to efficiently improve the topological

Marilena Crupi, Antonino Ficarra

We consider vector-spread Borel ideals. We show that these ideals have linear quotients and thereby we determine the graded Betti numbers and the bigraded Poincar\'e series. A characterization of the extremal Betti numbers of such a class of ideals is given. Finally, we classify all Cohen-Macaulay vector-spread Borel ideals.

Luca Gamberale

I consider coherent vibrational states of the quantum plasmas formed by the conduction electrons and protons inside a metal hydride. Such states can interact coherently through weak interaction to produce neutrons at very low energy. The existence of the vibrational coherent states is supported by a recent theoretical analysis showing that these configuratio

Colin M. Huber, Nathaniel S. Barlow, Steven J. Weinstein

Industrial coating processes create thin liquid films with tight thickness tolerances, and thus models that predict the response to inevitable disturbances are essential. The mathematical modeling complexities are reduced through linearization as even small thickness variations in films can render a product unsalable. The signaling problem, considered in thi

T. J. Bogaarts, M. Hoelzl, G. T. A. Huijsmans, X. Wang

Energetic particle (EP) driven instabilities will be of strongly increased relevance in future burning plasmas as the EP pressure will be very large compared to the thermal plasma. Understanding the interaction of EPs and bulk plasma is crucial for developing next-generation fusion devices. In this work, the JOREK MHD code is extended to allow for the simula

Jin Zhang, Qiuwei Liang, Yanjiao Shi

Most existing salient object detection (SOD) models are difficult to apply due to the complex and huge model structures. Although some lightweight models are proposed, the accuracy is barely satisfactory. In this paper, we design a novel semantics-guided contextual fusion network (SCFNet) that focuses on the interactive fusion of multi-level features for acc

Anichur Rahman, Antonio Montieri, Dipanjali Kundu, Md. Razaul Karim

Blockchain (BC) and Software-Defined Networking (SDN) are leading technologies which have recently found applications in several network-related scenarios and have consequently experienced a growing interest in the research community. Indeed, current networks connect a massive number of objects over the Internet and in this complex scenario, to ensure securi

D. Gazda, T. Yadanar Htun, C. Forssén

The energy levels of light hypernuclei are experimentally accessible observables that contain valuable information about the interaction between hyperons and nucleons. In this work we study strangeness $S = -1$ systems $^{3,4}_\Lambda$H and $^{4,5}_\Lambda$He using the ab initio no-core shell model (NCSM) with realistic interactions obtained from chiral effe

Marilena Crupi, Antonino Ficarra

We study the minimal primary decomposition of completely $t$-spread lexsegment ideals via simplicial complexes. We determine some algebraic invariants of such a class of $t$-spread ideals. Hence, we classify all $t$-spread lexsegment ideals which are Cohen-Macaulay.

Euclid Collaboration, T. Castro, A. Fumagalli, R. E. Angulo

Euclid's photometric galaxy cluster survey has the potential to be a very competitive cosmological probe. The main cosmological probe with observations of clusters is their number count, within which the halo mass function (HMF) is a key theoretical quantity. We present a new calibration of the analytic HMF, at the level of accuracy and precision required fo

Simo Alami C., Jérémie Decock, Rim Kaddah, Jesse Read

Non-Intrusive Load Monitoring (NILM) seeks to save energy by estimating individual appliance power usage from a single aggregate measurement. Deep neural networks have become increasingly popular in attempting to solve NILM problems. However most used models are used for Load Identification rather than online Source Separation. Among source separation models

Taixia Shi, Yang Chen

A photonics-assisted analog wideband RF self-interference (SI) cancellation and frequency downconversion approach for in-band full-duplex (IBFD) multiple-input multiple-output (MIMO) systems with adaptive digital amplitude and delay pre-matching is proposed based on a dual-parallel Mach-Zehnder modulator (DP-MZM). In each MIMO receiving antenna, the received

Pierre A. Burger, Oliver Friedrich, Joachim Harnois-Déraps, Peter Schneider

Context. Weak lensing and clustering statistics beyond two-point functions can capture non-Gaussian information about the matter density field, thereby improving the constraints on cosmological parameters relative to the mainstream methods based on correlation functions and power spectra. Aims. This paper presents a cosmological analysis of the fourth data r

Maximilian Bailey, Alexander Sprenger, Fabio Grillo, Hartmut Löwen

The active Brownian particle (ABP) model is widely used to describe the dynamics of active matter systems, such as Janus microswimmers. In particular, the analytical expression for an ABP's mean-squared-displacement (MSD) is useful as it provides a means to describe the essential physics of a self-propelled, spherical Brownian particle. However, the truncate

Peng Qi, Guangtao Wang, Jing Huang

Distilling supervision signal from a long sequence to make predictions is a challenging task in machine learning, especially when not all elements in the input sequence contribute equally to the desired output. In this paper, we propose SpanDrop, a simple and effective data augmentation technique that helps models identify the true supervision signal in a lo

Martin Buhmann, Janin Jäger, Yuan Xu

We study the $\ell^1$-summability of functions in the $d$-dimensional torus $\mathbb{T}^d$ and so-called $\ell^1$-invariant functions. Those are functions on the torus whose Fourier coefficients depend only on the $\ell^1$-norm of their indices. Such functions are characterized as divided differences that have $\cos \theta_1,\ldots,\cos\theta_d$ as knots for

Goksu Yamac, Carol O'Sullivan

Our aim is to develop a better understanding of how the Point of Release (PoR) of a ball affects the perception of animated throwing motions. We present the results of a perceptual study where participants viewed animations of a virtual human throwing a ball, in which the point of release was modified to be early or late. We found that errors in overarm thro

Sandra Nguemto, Vicente Leyton-Ortega

Adversarial learning represents a powerful technique for generating data statistics. Its successful implementation in quantum computational platforms is not straightforward due to limitations in connectivity, quantum operation fidelity, and limited access to the quantum processor for statistically relevant results. Constraining the number of quantum operatio

Ruiwen Dong

Let $G$ be a unitriangular matrix group of nilpotency class at most ten. We show that the Identity Problem (does a semigroup contain the identity matrix?) and the Group Problem (is a semigroup a group?) are decidable in polynomial time for finitely generated subsemigroups of $G$. Our decidability results also hold when $G$ is an arbitrary finitely generated

C. Domingo-Pardo, V. Babiano-Suarez, J. Balibrea-Correa, L. Caballero

This article presents a few selected developments and future ideas related to the measurement of $(n,\gamma)$ data of astrophysical interest at CERN n_TOF. The MC-aided analysis methodology for the use of low-efficiency radiation detectors in time-of-flight neutron-capture measurements is discussed, with particular emphasis on the systematic accuracy. Severa

Saray Shai, Isaac Jacobs, Peter J. Mucha

Network classification aims to group networks (or graphs) into distinct categories based on their structure. We study the connection between classification of a network and of its constituent nodes, and whether nodes from networks in different groups are distinguishable based on structural node characteristics such as centrality and clustering coefficient. W

Umut Demirhan, Ahmed Alkhateeb

Integrating sensing and communication is a defining theme for future wireless systems. This is motivated by the promising performance gains, especially as they assist each other, and by the better utilization of the wireless and hardware resources. Realizing these gains in practice, however, is subject to several challenges where leveraging machine learning

Ariel Caticha

The entropic dynamics (ED) approach to quantum mechanics is ideally suited to address the problem of measurement because it is based on entropic and Bayesian methods of inference that have been designed to process information and data. The approach succeeds because ED achieves a clear-cut separation between ontic and epistemic elements: positions are ontic w

A. Khansili, R. Sharma, R. Hissariya, I. Baev

Employing the elemental sensitivity of x-ray absorption spectroscopy (XAS) and x-ray magnetic circular dichroism (XMCD), we study the valence and magnetic order in the heavy fermion superconductor CeCoIn$_5$. We probe spin population of the f-electrons in Ce and d-electrons in Co as a function of temperature (down to 0.1 K) and magnetic field (up to 6 T). Fr

Phillip Sherlock, Herman T. Knopf, Robert Chapman, Maya Schreiber

The aggregate ability of child care providers to meet local demand for child care is linked to employment rates in many sectors of the economy. Amid growing concern regarding child care provider sustainability due to the COVID-19 pandemic, state and local governments have received large amounts of new funding to better support provider stability. In response

Albert R. Jiang

Methods to determine the existence of Hamiltonian Cycles in graphs have been extensively studied. However, little research has been done following cases when no Hamiltonian Cycle exists. Let a vertex be "unbounded" if it is visited more than once in a path. Furthermore, let a k-Unbounded Hamiltonian Cycle be a path with finite length that visits every vertex

Wai-Kit Lam, Arnab Sen

We consider the disordered monomer-dimer model on general finite graphs with bounded degrees. Under the finite fourth moment assumption on the weight distributions, we prove a Gaussian central limit theorem for the free energy of the associated Gibbs measure with a rate of convergence. The central limit theorem continues to hold under a nearly optimal finite

Chuhan Xu, Pablo Coen-Pirani, Xia Jiang

Overfitting is defined as the fact that the current model fits a specific data set perfectly, resulting in weakened generalization, and ultimately may affect the accuracy in predicting future data. In this research we used an EHR dataset concerning breast cancer metastasis to study overfitting of deep feedforward Neural Networks (FNNs) prediction models. We

Moxuan Han, Yang Chen

A digitally-assisted photonic analog domain self-interference cancellation (SIC) and frequency downconversion method is proposed for in-band full-duplex multiple-input multiple-output (MIMO) systems using the least square (LS) algorithm with adaptive order. The SIC and frequency downconversion are achieved in the optical domain via a dual-parallel Mach-Zehnd

Benyuan Sun, Jin Dai, Zihao Liang, Congying Liu

Pre-training over mixtured multi-task, multi-domain, and multi-modal data remains an open challenge in vision perception pre-training. In this paper, we propose GPPF, a General Perception Pre-training Framework, that pre-trains a task-level dynamic network, which is composed by knowledge "legos" in each layers, on labeled multi-task and multi-domain datasets

Ratan Joarder, Siba P. Choudhury, Syam S., Nagendra Singh

A new optical technique based on light-matter interaction is devised in-house to detect thermo-acoustic disturbances generated after ignition and during propagation of a premixed flame front in a half open channel. The technique involves passing a polarized laser light through a medium whose density or refractive index varies due to the passage of acoustic w

Panting Ge, Xiaotao Huang, Miroslav Saur, Liang Sun

The neutrino closure method is often used to obtain kinematics of semileptonic decays with one unreconstructed particle. The kinematics of decays can be deducted by a two-fold ambiguity with a quadratic equation. To resolve the two-fold ambiguity, a new method based on Machine Learning (ML) is proposed. We study the effect of different sets of features and r

Amir N. Khan

We derive new limits on the neutrino electromagnetic interactions and weakly coupled light vector and scalar mediators using the recent XENONnT data of the solar neutrino-electron elastic scattering. XENONnT has already reported the world's best constraint on the flavor-independent effective neutrino magnetic moment with almost twice the exposure and improve

Hai-Ling Liu, Chao-Hua Yu, Lin-Chun Wan, Su-Juan Qin

Mean Centering (MC) is an important data preprocessing technique, which has a wide range of applications in data mining, machine learning, and multivariate statistical analysis. When the data set is large, this process will be time-consuming. In this paper, we propose an efficient quantum MC algorithm based on the block-encoding technique, which enables the

G. Grätzer

A new result of G. Cz\'edli states that for an ordered set $P$ with at least two elements and a group $G$, there exists a bounded lattice $L$ such that the ordered set of principal congruences of $L$ is isomorphic to $P$ and the automorphism group of $L$ is isomorphic to $G$. I provide an alternative proof utilizing a result of mine with J. Sichler from the

Jie Qi, Diego Ibarra Hoyos, S. Joseph Poon

The design of high-entropy alloys (HEA) with desired properties is challenging due to their large compositional space. While various machine learning (ML) models can predict specific HEA solid-solution phases (SS), predicting high-entropy intermetallic phases (IM) is underdeveloped due to limited datasets and inadequate ML features. This paper introduces fea

Lars Hillebrand, Tobias Deußer, Tim Dilmaghani, Bernd Kliem

We present KPI-BERT, a system which employs novel methods of named entity recognition (NER) and relation extraction (RE) to extract and link key performance indicators (KPIs), e.g. "revenue" or "interest expenses", of companies from real-world German financial documents. Specifically, we introduce an end-to-end trainable architecture that is based on Bidirec

Andrew J. Archer, Tomonari Dotera, Alastair M. Rucklidge

Aperiodic (quasicrystalline) tilings, such as Penrose's tiling, can be built up from e.g. kites and darts, squares and equilateral triangles, rhombi or shield shaped tiles and can have a variety of different symmetries. However, almost all quasicrystals occurring in soft-matter are of the dodecagonal type. Here, we investigate a class of aperiodic tilings wi

Nicholas A. Blumenschein, Gregory M. Stephen, Cory D. Cress, Samuel W. LaGasse

Due to its proximity to room temperature and demonstrated high degree of temperature tunability, the metamagnetic ordering transition in FeRh is attractive for novel high-performance computing devices seeking to use magnetism as the state variable. We demonstrate electrical control of the transition via Joule heating in FeRh wires. Finite element simulations

Erhard Scholz

If one wants to translate the heliocentric picture of planets moving uniformly on circular orbits about the sun to the perspective of a terrestrial observer, using classical (ancient) geometric means only, one is naturally led to the investigation of epicyclic constructions. The announcement of the heliocentric hypothesis by Aristarchos of Samos and the inve

Emanuela Gussetti

We establish existence of an ergodic invariant measure on $H^1(D,\mathbb{R}^3)\cap L^2(D,\mathbb{S}^2)$ for the stochastic Landau-Lifschitz-Gilbert equation on a bounded one dimensional interval $D$. The conclusion is achieved by employing the classical Krylov-Bogoliubov theorem. In contrast to other equations, verifying the hypothesis of the Krylov-Bogoliub

Berke Doga Basaran, Mengyun Qiao, Paul M. Matthews, Wenjia Bai

Understanding the intensity characteristics of brain lesions is key for defining image-based biomarkers in neurological studies and for predicting disease burden and outcome. In this work, we present a novel foreground-based generative method for modelling the local lesion characteristics that can both generate synthetic lesions on healthy images and synthes

Gábor Czédli, George Grätzer, Harry Lakser

The Swing Lemma of the second author describes how a congruence spreads from a prime interval to another in a slim (having no $M_3$ sublattice), planar, semimodular lattice. We generalize the Swing Lemma to planar semimodular lattices.

Hetsron L. Nyandjo-Bamen, Jean Marie Ntaganda, Aurelien Tellier, Olivier Menoukeu-Pamen

Vaccination is essential for the management of infectious diseases, many of which continue to pose devastating public health and economic challenges across the world. However, many vaccines are imperfect having only a partial protective effect in decreasing disease transmission and/or favouring recovery of infected individuals, and possibly exhibiting trade-

Hao-Chung Cheng

Achievability in information theory refers to demonstrating a coding strategy that accomplishes a prescribed performance benchmark for the underlying task. In quantum information theory, the crafted Hayashi-Nagaoka operator inequality is an essential technique in proving a wealth of one-shot achievability bounds since it effectively resembles a union bound i