July 2022 arXiv papers — page 71

Yuqi Tian, Bryan E. Shepherd, Chun Li, Donglin Zeng

Continuous response variables often need to be transformed to meet regression modeling assumptions; however, finding the optimal transformation is challenging and results may vary with the choice of transformation. When a continuous response variable is measured repeatedly for a subject or the continuous responses arise from clusters, it is more challenging

Xianbo Yang, Dexue Zhang

The construction of the formal ball model for metric spaces due to Edalat and Heckmann was generalized to ${\sf Q}$-categories by Kostanek and Waszkiewicz. This paper concerns the influence of the structure of the quantale ${\sf Q}$ on the connection between Yoneda completeness of ${\sf Q}$-categories and directed completeness of their sets of formal balls.

Jiahui Fu, Chengyuan Lin, Yuichi Taguchi, Andrea Cohen

The ability to process environment maps across multiple sessions is critical for robots operating over extended periods of time. Specifically, it is desirable for autonomous agents to detect changes amongst maps of different sessions so as to gain a conflict-free understanding of the current environment. In this paper, we look into the problem of change dete

Alina Carmen Cojocaru, McKinley Meyer

Let $E$ be an elliptic curve defined over $\mathbb{Q}$ and without complex multiplication. For a prime $p$ of good reduction for $E$, we write $\#E_p(\mathbb{F}_p) = p + 1 - a_p(E)$ for the number of $\mathbb{F}_p$-rational points of the reduction $E_p$ of $E$ modulo $p$. Under the Generalized Riemann Hypothesis (GRH), we study the primes $p$ for which the i

Zhou Lan, Arkaprava Roy

Spatially varying directional data are routinely observed in several modern applications such as meteorology, biology, geophysics, engineering, etc. However, only a few approaches are available for covariate-dependent statistical analysis for such data. To address this gap, we propose a novel generalized linear model to analyze such that using a von Mises Fi

Noyan Evirgen, Xiang 'Anthony' Chen

Generative Adversarial Network (GAN) is widely adopted in numerous application areas, such as data preprocessing, image editing, and creativity support. However, GAN's 'black box' nature prevents non-expert users from controlling what data a model generates, spawning a plethora of prior work that focused on algorithm-driven approaches to extract editing dire

Junpu Wang, Guili Xu, Fuju Yan, Jinjin Wang

Surface defect detection is an extremely crucial step to ensure the quality of industrial products. Nowadays, convolutional neural networks (CNNs) based on encoder-decoder architecture have achieved tremendous success in various defect detection tasks. However, due to the intrinsic locality of convolution, they commonly exhibit a limitation in explicitly mod

Bugao Zou, Steve K. Choi, Nicholas F. Cothard, Rodrigo Freundt

The Epoch of Reionization Spectrometer (EoR-Spec) is one of the instrument modules to be installed in the Prime-Cam receiver of the Fred Young Submillimeter Telescope (FYST). This six-meter aperture telescope will be built on Cerro Chajnantor in the Atacama Desert in Chile. EoR-Spec is designed to probe early star-forming regions by measuring the [CII] fine-

John Rushby, Daniel Sanchez

We report on a series of eight workshops held in the summer of 2017 on the topic "technology and consciousness." The workshops covered many subjects but the overall goal was to assess the possibility of machine consciousness, and its potential implications. In the body of the report, we summarize most of the basic themes that were discussed: the structure an

Lixue Cheng, Jiace Sun, J. Emiliano Deustua, Vignesh C. Bhethanabotla

We introduce a novel machine learning strategy, kernel addition Gaussian process regression (KA-GPR), in molecular-orbital-based machine learning (MOB-ML) to learn the total correlation energies of general electronic structure theories for closed- and open-shell systems by introducing a machine learning strategy. The learning efficiency of MOB-ML (KA-GPR) is

I. Sh. Kalimullin

We are studying the degrees in which a computable structure is relatively computably categoricity, i.e., computably categorcial among all non-computable copies of the structure. Unlike the degrees of computable categoricity we can bound the possible degrees of relative computable categoricity by the oracle 0". In the case of rigid structures the bound is in

Ioakeim Ampatzoglou

In this paper, we prove global in time existence, uniqueness and stability of mild solutions near vacuum for the 4-wave inhomogeneous kinetic wave equation, for Laplacian dispersion relation in dimension $d=2,3$. We also show that for non-negative initial data, the solution remains non-negative. This is achieved by connecting the inhomogeneous kinetic wave e

Reza Ghanavi, Craig Jin

We investigate a speech enhancement method based on the binaural coherence-to-diffuse power ratio (CDR), which preserves auditory spatial cues for maskers and a broadside target. Conventional CDR estimators typically rely on a mathematical coherence model of the desired signal and/or diffuse noise field in their formulation, which may influence their accurac

Jiaxin Jin, Chanwoo Kim

In this paper, we study exponentially fast mixing induced/enhanced by gravity and stochastic boundary in the kinetic theory of Vlasov equations. We consider the Vlasov equations with and without a vertical magnetic field inside a horizontally-periodic 3D half-space equipped with a non-isothermal diffusive reflection boundary condition of bounded continuous b

Duncan Calvert, Bhavyansh Mishra, Stephen McCrory, Sylvain Bertrand

In trying to build humanoid robots that perform useful tasks in a world built for humans, we address the problem of autonomous locomotion. Humanoid robot planning and control algorithms for walking over rough terrain are becoming increasingly capable. At the same time, commercially available depth cameras have been getting more accurate and GPU computing has

Cole Franks, Tasuku Soma, Michel X. Goemans

A recent breakthrough in Edmonds' problem showed that the noncommutative rank can be computed in deterministic polynomial time, and various algorithms for it were devised. However, only quite complicated algorithms are known for finding a so-called shrunk subspace, which acts as a dual certificate for the value of the noncommutative rank. In particular, the

S. Haessler, B. Fabre, J. Higuet, J. Caillat

We photoionize nitrogen molecules with a train of extreme ultraviolet attosecond pulses together with a weak infrared field. We measure the phase of the two-color two-photon ionization transition (molecular phase) for different states of the ion. We observe a 0.76 $\pi$ shift for the electrons produced in the ionization channels leading to the X$^2 \Sigma_g^

Oliver Daniels-Koch

We introduce CULT (Continual Unsupervised Representation Learning with Typicality-Based Environment Detection), a new algorithm for continual unsupervised learning with variational auto-encoders. CULT uses a simple typicality metric in the latent space of a VAE to detect distributional shifts in the environment, which is used in conjunction with generative r

L. G. González Ricardo, G. López Lagomasino

We obtain the strong asymptotics of multiple orthogonal polynomials which arise in a mixed type Hermite-Pad\'e approximation problem defined on a Nikishin system of functions. The results obtained allow to give exact estimates of the rate of convergence of the approximating rational functions and the strong asymptotics of Cauchy biorthogonal polynomials.

Salman Ahmadi-Asl

The existing randomized algorithms need an initial estimation of the tubal rank to compute a tensor singular value decomposition. This paper proposes a new randomized fixedprecision algorithm which for a given third-order tensor and a prescribed approximation error bound, automatically finds an optimal tubal rank and the corresponding low tubal rank approxim

Aleksandr Beknazaryan, Hailin Sang

We consider regression estimation with modified ReLU neural networks in which network weight matrices are first modified by a function $\alpha$ before being multiplied by input vectors. We give an example of continuous, piecewise linear function $\alpha$ for which the empirical risk minimizers over the classes of modified ReLU networks with $l_1$ and squared

Yongxin Zhou, François Portet, Fabien Ringeval

Pre-trained language models have established the state-of-the-art on various natural language processing tasks, including dialogue summarization, which allows the reader to quickly access key information from long conversations in meetings, interviews or phone calls. However, such dialogues are still difficult to handle with current models because the sponta

Ruchika Chavhan, Henry Gouk, Jan Stühmer, Timothy Hospedales

Providing invariances in a given learning task conveys a key inductive bias that can lead to sample-efficient learning and good generalisation, if correctly specified. However, the ideal invariances for many problems of interest are often not known, which has led both to a body of engineering lore as well as attempts to provide frameworks for invariance lear

Lamis Amer, Murat Erkoc, Esber Andiroglu, Nurcin Celik

Resilience is a key driver for planning adaptation strategies to mitigate risks due to both natural and anthropogenic hazards. The effectiveness of a resilience-driven decision-making strategy for adapting systems against stressors depends on how resilience is mapped to decision variables. This requires a functional resilience metric, without which it would

T. Thiemann

The U(1)$^3$ model for 3+1 Euclidian signature general relativity is an interacting, generally covariant field theory with two physical polarisations that shares many features of Lorentzian general relativity. In particular, it displays a non-trivial realisation of the hypersurface deformation algebroid with non-trivial, i.e. phase space dependent structure

Rundong Ge, Moonyoung Lee, Vivek Radhakrishnan, Yang Zhou

In this paper, we address the vision-based detection and tracking problems of multiple aerial vehicles using a single camera and Inertial Measurement Unit (IMU) as well as the corresponding perception consensus problem (i.e., uniqueness and identical IDs across all observing agents). We design several vision-based decentralized Bayesian multi-tracking filter

G. S. Venkatesh

The goal of the paper is two-fold. The first of which is to derive an explicit formula to compute the generating series of a closed-loop system when a plant, given in a Chen-Fliess series description is in multiplicative output feedback connection with another system given in Chen-Fliess series description. Further, the objective extends in showing that the

T. Thiemann

A basic assumption in classical GR is that the metric field is nowhere degenerate in spacetime. In particular the induced metric on Cauchy surfaces must be nowhere degenerate. It is only under this assumption that one can derive the hypersurace deformation algebra between the initial value constraints which is absolutely transparent from the fact that the {\

Sasindu Wijeratne, Ta-Yang Wang, Rajgopal Kannan, Viktor Prasanna

Tensor decomposition has become an essential tool in many data science applications. Sparse Matricized Tensor Times Khatri-Rao Product (MTTKRP) is the pivotal kernel in tensor decomposition algorithms that decompose higher-order real-world large tensors into multiple matrices. Accelerating MTTKRP can speed up the tensor decomposition process immensely. Spars

Liam J Berrisford, Eraldo Ribeiro, Ronaldo Menezes

In recent years, the world has become increasingly concerned with air pollution. Particularly in the global north, countries are implementing systems to monitor air pollution on a large scale to aid decision-making. Such efforts are essential but they have at least three shortcomings: (1) they are costly and are difficult to implement expediently; (2) they f

Yuri A. Godin, Boris Vainberg

We consider acoustic wave propagation through a periodic array of the inclusions of arbitrary shape. The inclusion size is much smaller than the array period while the wavelength is fixed. We derive and rigorously justify the dispersion relation for general frequencies and show that there are exceptional frequencies for which the solution is a cluster of wav

Zhendong Zhang, Shu Nagata, Kaixuan Yao, Cheng Chin

Chemical reactions in the quantum degenerate regime are described by mixing of matterwave fields. Quantum coherence and bosonic enhancement are two unique features of many-body reactions involving bosonic reactants and products. Such collective reactions of chemicals, dubbed "super-chemistry", is an elusive goal in quantum chemistry research. Here we report

T. Thiemann

In constructive quantum field theory (CQFT) it is customary to first regularise the theory at finite UV and IR cut-off. Then one first removes the UV cutoff using renormalisation techniques applied to families of CQFT's labelled by finite UV resolutions and then takes the thermodynamic limit. Alternatively, one may try to work directly without IR cut-off. Mo

Antonio Agresti

This paper is concerned with the problem of regularization by noise of systems of reaction-diffusion equations with mass control. It is known that $\textit{strong}$ solutions to such systems of PDEs may blow-up in finite time. Moreover, for many systems of practical interest, establishing whether the blow-up occurs or not is an open question. Here we prove t

Ali Can Kocabiyikoglu, François Portet, Prudence Gibert, Hervé Blanchon

Spoken medical dialogue systems are increasingly attracting interest to enhance access to healthcare services and improve quality and traceability of patient care. In this paper, we focus on medical drug prescriptions acquired on smartphones through spoken dialogue. Such systems would facilitate the traceability of care and would free clinicians' time. Howev

T. Thiemann

The Hamiltonian renormalisation programme motivated by constructive QFT and Osterwalder-Schrader reconstruction which was recently launched for bosonic field theories is extended to fermions. As fermion quantisation is not in terms of measures, the scheme has to be mildly modified accordingly. We exemplify the scheme for free fermions both for compact and no

T. Thiemann, E. -A. Zwicknagel

Hamiltonian Renormalisation, as defined within this series of works, was derived from covariant Wilson renormalisation via Osterwalder-Schrader reconstruction. As such it directly applies to QFT with a true (physical) Hamiltonian bounded from below. The validity of the scheme was positively tested for free QFT in any dimension with or without Abelian gauge s

Eugene Stolyarov

Time-frequency entangled photons constitute an important resource for a plethora of applications across the diverse quantum technology landscape. Thus, efficient and tunable setups for the generation of entangled photons are requisite for modern quantum technologies. In this work, we propose a generic cavity QED setup designed for on-demand generation of tim

Christos K. Verginis, Zhe Xu, Ufuk Topcu

We develop a learning-based algorithm for the distributed formation control of networked multi-agent systems governed by unknown, nonlinear dynamics. Most existing algorithms either assume certain parametric forms for the unknown dynamic terms or resort to unnecessarily large control inputs in order to provide theoretical guarantees. The proposed algorithm a

Serena Y. Kim, Koushik Ganesan, Crystal Soderman, Raven O'Rourke

This paper presents a comprehensive analysis of the social and environmental determinants of solar photovoltaic (PV) deployment rates in Colorado, USA. Using 652,795 satellite imagery and computer vision frameworks based on a convolutional neural network, we estimated the proportion of households with solar PV systems and the roof areas covered by solar pane

William Hogan

Relation Extraction (RE) is a foundational task of natural language processing. RE seeks to transform raw, unstructured text into structured knowledge by identifying relational information between entity pairs found in text. RE has numerous uses, such as knowledge graph completion, text summarization, question-answering, and search querying. The history of R

Alexandru Mustăţea

This article presents a construction of the concept of stochastic integration in Riemannian manifolds from a purely functional-analytic point of view. We show that there are infinitely many such integrals, and that any two of them are related by a simple formula. We also find that the Stratonovich and It\^o integrals known to probability theorists are two in

H. M. Araújo, S. N. Balashov, J. E. Borg, F. M. Brunbauer

We present the Migdal In Galactic Dark mAtter expLoration (MIGDAL) experiment aiming at the unambiguous observation and study of the so-called Migdal effect induced by fast-neutron scattering. It is hoped that this elusive atomic process can be exploited to enhance the reach of direct dark matter search experiments to lower masses, but it is still lacking ex

Chenxi Feng, Haochen Wu

RRT* is an efficient sampling-based motion planning algorithm. However, without taking advantages of accessible environment information, sampling-based algorithms usually result in sampling failures, generate useless nodes, and/or fail in exploring narrow passages. For this paper, in order to better utilize environment information and further improve searchi

Huaxin Wang-Lu, Octasiano Miguel Valerio Mendoza

China's structural changes have brought new challenges to its regional employment structures, entailing labour redistribution. By now Chinese research on migration decisions with a forward-looking stand and on bilateral longitudinal determinants at the prefecture city level is almost non-existent. This paper investigates the effects of sector-based job prosp

Chunqiu Steven Xia, Lingming Zhang

Due to the promising future of Automated Program Repair (APR), researchers have proposed various APR techniques, including heuristic-based, template-based, and constraint-based techniques. Among such classic APR techniques, template-based techniques have been widely recognized as state of the art. However, such template-based techniques require predefined te

Luca Mariot, Luca Manzoni

Correlation immune Boolean functions play an important role in the implementation of efficient masking countermeasures for side-channel attacks in cryptography. In this paper, we investigate a method to construct correlation immune functions through families of mutually orthogonal cellular automata (MOCA). First, we show that the orthogonal array (OA) associ

Haochen Wu, Amin Ghadami, Alparslan Emrah Bayrak, Jonathon M. Smereka

In operations of multi-agent teams ranging from homogeneous robot swarms to heterogeneous human-autonomy teams, unexpected events might occur. While efficiency of operation for multi-agent task allocation problems is the primary objective, it is essential that the decision-making framework is intelligent enough to manage unexpected task load with limited res

Gavin Brown, Jarosław Buczyński, Alexander Kasprzyk

We explain a web of Sarkisov links that overlies the classification of Fano weighted projective spaces in dimensions 3 and 4, extending results of Prokhorov.

Robert Eisenberg, Xavier Oriols, David K. Ferry

Kirchhoff's Current Law is an essential tool in the design of circuits that operate very quickly, faster than nanoseconds. But Kirchhoff's current is often identified as the flow of particles. The continuity equation or the Maxwell-Ampere law shows that the sum of displacement current $\textbf{plus}$ particle current is conserved by Maxwell's equations and K

Paul Égré, Lorenzo Rossi, Jan Sprenger

This paper develops a trivalent semantics for the truth conditions and the probability of the natural language indicative conditional. Our framework rests on trivalent truth conditions first proposed by W. Cooper and yields two logics of conditional reasoning: (i) a logic C of inference from certain premises; and (ii) a logic U of inference from uncertain pr

Yue Yu, Jonathan Salfity, David Fridovich-Keil, Ufuk Topcu

In an inverse game problem, one needs to infer the cost function of the players in a game such that a desired joint strategy is a Nash equilibrium. We study the inverse game problem for a class of multiplayer matrix games, where the cost perceived by each player is corrupted by random noise. We provide sufficient conditions for the players' quantal response

Ilia Tutunnikov, Long Xu, Yehiam Prior, Ilya Sh. Averbukh

Ultrashort laser pulses are widely used for transient field-free molecular orientation -- a phenomenon important in chemical reaction dynamics, ultrafast molecular imaging, high harmonics generation, and attosecond science. However, significant molecular orientation usually requires rotationally cold molecules, like in rarified molecular beams, because chaot

Roman Rausch, Matthias Peschke, Cassian Plorin, Jürgen Schnack

The ferrimagnetic phase of the sawtooth chain with mixed ferromagnetic nearest-neighbour interactions $J$ and antiferromagnetic next-nearest-neighbour interactions $J'$ (within the isotropic Heisenberg model) was previously characterized as a phase with commensurate order. In this paper, we demonstrate that the system in fact exhibits an incommensurate quant

Jose M Munoz, Ilyes Batatia, Christoph Ortner

Deep Learning approaches are becoming the go-to methods for data analysis in High Energy Physics (HEP). Nonetheless, most physics-inspired modern architectures are computationally inefficient and lack interpretability. This is especially the case with jet tagging algorithms, where computational efficiency is crucial considering the large amounts of data prod

Charly Andral, Randal Douc, Hugo Marival, Christian P. Robert

The Importance Markov chain is a novel algorithm bridging the gap between rejection sampling and importance sampling, moving from one to the other through a tuning parameter. Based on a modified sample of an instrumental Markov chain targeting an instrumental distribution (typically via a MCMC kernel), the Importance Markov chain produces an extended Markov

Mariana Penna-Lima, Nelson Pinto-Neto, Sandro D. P. Vitenti

The problem of finding a vacuum definition for a single quantum field in curved space-times is discussed under a new geometrical perspective. The phase space dynamics of the quantum field modes are mapped to curves in a 2-dimensional hyperbolic metric space, in which distances between neighbor points are shown to be proportional to the Bogoliubov coefficient

Alfred Z. Msezane, Zineb Felfli

We briefly review recent applications of the Regge pole analysis to low-energy E less than/equal to 10.0 eV electron elastic collisions with large multi-electron atoms and fullerene molecules. We then conclude with a demonstration of the sensitivity of the Regge pole-calculated Ramsauer-Townsend minima and shape resonances to the electronic structure and dyn

David P. Woodruff, Taisuke Yasuda

The seminal work of Cohen and Peng introduced Lewis weight sampling to the theoretical computer science community, yielding fast row sampling algorithms for approximating $d$-dimensional subspaces of $\ell_p$ up to $(1+\epsilon)$ error. Several works have extended this important primitive to other settings, including the online coreset and sliding window mod

Jingwei Zhang, Xin Zhang, Ke Ma, Rajarsi Gupta

Histopathology whole slide images (WSIs) play a very important role in clinical studies and serve as the gold standard for many cancer diagnoses. However, generating automatic tools for processing WSIs is challenging due to their enormous sizes. Currently, to deal with this issue, conventional methods rely on a multiple instance learning (MIL) strategy to pr

Mikhail Ganzhinov

A generalization of highly symmetric frames is presented by considering also projective stabilizers of frame vectors. This allows construction of highly symmetric line systems and study of highly symmetric frames in a more unified manner. Construction of highly symmetric line systems involves computation of twisted spherical functions associated with finite

Ammar Haydari, Yasin Yilmaz

Secure vehicular communication is a critical factor for secure traffic management. Effective security in intelligent transportation systems (ITS) requires effective and timely intrusion detection systems (IDS). In this paper, we consider false data injection attacks and distributed denial-of-service (DDoS) attacks, especially the stealthy DDoS attacks, targe

Bin Xie, Hao Tang, Bin Duan, Dawen Cai

Brain vessel image segmentation can be used as a promising biomarker for better prevention and treatment of different diseases. One successful approach is to consider the segmentation as an image-to-image translation task and perform a conditional Generative Adversarial Network (cGAN) to learn a transformation between two distributions. In this paper, we pre

Jeffrey Larson, Matt Menickelly

We present new methods for solving a broad class of bound-constrained nonsmooth composite minimization problems. These methods are specially designed for objectives that are some known mapping of outputs from a computationally expensive function. We provide accompanying implementations of these methods: in particular, a novel manifold sampling algorithm (\ms

Livio Flaminio, Davide Ravotti

We consider Abelian covers of compact hyperbolic surfaces. We establish an asymptotic expansion of the correlations for the horocycle flow on $\mathbb{Z}^d$-covers, thus proving a strong form of Krickeberg mixing. We also prove that the spectral measures around $0$ of the Casimir operators on any increasing sequence of finite Abelian covers converge weakly t

Mark Agranovsky, Leonid Kunyansky

The spherical means Radon transform $\mathcal{M}f(x,r)$ is defined by the integral of a function $f$ in $\mathbb{R}^{n}$ over the sphere $S(x,r)$ of radius $r$ centered at a $x$, normalized by the area of the sphere. The problem of reconstructing $f$ from the data $\mathcal{M}f(x,r)$ where $x$ belongs to a hypersurface $\Gamma\subset\mathbb{R}^{n}$ and $r \i

Toni Helm, Motoi Kimata, Kenta Sudo, Atsuhiko Miyata

The potential spin-triplet heavy-fermion superconductor UTe$_2$ exhibits signatures of multiple distinct superconducting phases. For field aligned along the $b$ axis, a metamagnetic transition occurs at $\mu_0 H_\mathrm{m}\approx35\,$T. It is associated with magnetic fluctuations that may be beneficial for the field-reinforced superconductivity surviving up

Nguyen S. Hoang

A class of explicit pseudo two-step Runge-Kutta-Nystr\"{o}m (GEPTRKN) methods for solving second-order initial value problems $y'' = f(t,y,y')$, $y(t_0) = y_0$, $y'(t_0)=y'_0$ has been studied. This new class of methods can be considered a generalized version of the class of classical explicit pseudo two-step Runge-Kutta-Nystr\"{o}m methods. %The new methods

Jakob Assländer, Cem Gultekin, Andrew Mao, Xiaoxia Zhang

Purpose: To explore efficient encoding schemes for quantitative magnetization transfer (qMT) imaging with few constraints on model Theory and Methods: We combine two recently proposed models in a Bloch-McConnell equation: the dynamics of the free spin pool are confined to the hybrid state, and the dynamics of the semi-solid spin pool are described by the gen

Ted Moskovitz, Ta-Chu Kao, Maneesh Sahani, Matthew M. Botvinick

We propose a novel framework for multitask reinforcement learning based on the minimum description length (MDL) principle. In this approach, which we term MDL-control (MDL-C), the agent learns the common structure among the tasks with which it is faced and then distills it into a simpler representation which facilitates faster convergence and generalization

Amit Attia, Tomer Koren

We consider the problem of designing uniformly stable first-order optimization algorithms for empirical risk minimization. Uniform stability is often used to obtain generalization error bounds for optimization algorithms, and we are interested in a general approach to achieve it. For Euclidean geometry, we suggest a black-box conversion which given a smooth

Fajrian Yunus, Chloé Clavel, Catherine Pelachaud

Image schema is a recurrent pattern of reasoning where one entity is mapped into another. Image schema is similar to conceptual metaphor and is also related to metaphoric gesture. Our main goal is to generate metaphoric gestures for an Embodied Conversational Agent. We propose a technique to learn the vector representation of image schemas. As far as we are

V. A. Zaytsev, M. E. Groshev, I. A. Maltsev, A. V. Durova

We investigate the possibility to calculate the ground-state energy of the atomic systems on a quantum computer. For this purpose we evaluate the lowest binding energy of the moscovium atom with the use of the iterative phase estimation and variational quantum eigensolver. The calculations by the variational quantum eigensolver are performed with a disentang

Adarsh Prabhakaran, Valerio Restocchi, Benjamin D. Goddard

Over the years, population-level tobacco control policies have considerably reduced smoking prevalence worldwide. However, the rate of decline of smoking prevalence is slowing down. Therefore, there is a need for models that capture the full complexity of the smoking epidemic. These models can then be used as test-beds to develop new policies to limit the sp

Yiding Feng, Chien-Ju Ho, Wei Tang

Classic mechanism/information design imposes the assumption that agents are fully rational, meaning each of them always selects the action that maximizes her expected utility. Yet many empirical evidence suggests that human decisions may deviate from this full rationality assumption. In this work, we attempt to relax the full rationality assumption with boun

Elena A. Lebedeva

In the paper we design a Parseval wavelet frame with a compact support and many vanishing moments. The corresponding refinement mask approximates an arbitrary continuous periodic function $f$, $f(0)=1$. The refinable function has stable integer shifts.

Alan Demlow, Sebastian Franz, Natalia Kopteva

We prove residual-type a posteriori error estimates in the maximum norm for a linear scalar elliptic convection-diffusion problem that may be singularly perturbed. Similar error analysis in the energy norm by Verf\"{u}rth indicates that a dual norm of the {convective derivative of the} error must be added to the natural energy norm in order for the natural r

Robert Bluhm

A brief recap is given of issues that can occur when fixed nondynamical backgrounds that explicitly break diffeomorphism invariance are included in gravity theories. Implications for the Standard-Model Extension (SME) are summarized, including recent results showing how the SME can be modified to accommodate such fixed nondynamical backgrounds.

Anton Skrobotov

This review discusses methods of testing for explosive bubbles in time series. A large number of recently developed testing methods under various assumptions about innovation of errors are covered. The review also considers the methods for dating explosive (bubble) regimes. Special attention is devoted to time-varying volatility in the errors. Moreover, the

J. M. Almira

Aichinger's equation is used to give simple proofs of several well-known characterizations of polynomial functions as solutions of certain functional equations. Concretely, we use that Aichinger's equation characterizes polynomial functions to solve, for arbitrary commutative groups, Ghurye-Olkin's functional equation, Wilson's functional equation, the Kakut

V. A. Vassiliev

We develop a technique for calculating the cohomology groups of spaces of complex parametric knots in ${\mathbb C}^k$, $k \geq 3$, and carry out these calculations to obtain these groups of low dimensions.

Takeshi Kobayashi, Daniele Perri

We present new bounds on the cosmic abundance of magnetic monopoles based on the survival of primordial magnetic fields during the reheating and radiation-dominated epochs. The new bounds can be stronger than the conventional Parker bound from galactic magnetic fields, as well as bounds from direct searches. We also apply our bounds to monopoles produced by

Jeffrey Galkowski, Leonid Parnovski, Roman Shterenberg

In this article, we consider the asymptotic behaviour of the spectral function of Schr\"odinger operators on the real line. Let $H: L^2(\mathbb{R})\to L^2(\mathbb{R})$ have the form $$ H:=-\frac{d^2}{dx^2}+V, $$ where $V$ is a formally self-adjoint first order differential operator with smooth coefficients, bounded with all derivatives. We show that the kern

Apostolos I. Rikos, Christoforos N. Hadjicostis, Karl H. Johansson

Due to their flexibility, battery powered or energy-harvesting wireless networks are employed in diverse applications. Securing data transmissions between wireless devises is of critical importance in order to avoid privacy-sensitive user data leakage. In this paper, we focus on the scenario where some nodes are curious (but not malicious) and try to identif

Mattia Moroder, Martin Grundner, François Damanet, Ulrich Schollwöck

Recent advances in numerical methods significantly pushed forward the understanding of electrons coupled to quantized lattice vibrations. At this stage, it becomes increasingly important to also account for the effects of physically inevitable environments. In particular, we study the transport properties of the Hubbard-Holstein Hamiltonian that models a lar

A. Mironov, A. Morozov

Once famous and a little mysterious, AGT relations between Nekrasov functions and conformal blocks are now understood as the Hubbard-Stratanovich duality in the Dijkgraaf-Vafa (DV) phase of a peculiar Dotsenko-Fateev multi-logarithmic matrix model. However, it largely remains a collection of somewhat technical tricks, lacking a clear and generalizable concep

Mathias Casiulis, Stefano Martiniani

In statistical mechanics, measuring the number of available states and their probabilities, and thus the system's entropy, enables the prediction of the macroscopic properties of a physical system at equilibrium. This predictive capacity hinges on the knowledge of the a priori probabilities of observing the states of the system, given by the Boltzmann distri

Yutong Li, Nan Li, H. Eric Tseng, Anouck Girard

The action governor is an add-on scheme to a nominal control loop that monitors and adjusts the control actions to enforce safety specifications expressed as pointwise-in-time state and control constraints. In this paper, we introduce the Robust Action Governor (RAG) for systems the dynamics of which can be represented using discrete-time Piecewise Affine (P

Adam Rycerz, Piotr Witkowski

Ballistic graphene samples in a multimode regime show the sub-Sharvin charge transport, characterized by the conductance reduced by a factor of $\pi/4$ comparing to standard Sharvin contacts in two-dimensional electron gas, and the shot-noise power enhanced up to $F\approx{}1/8$ (with $F$ the Fano factor) [Phys. Rev. B 104, 165413 (2021)]. Here we consider t

Kyle Gannon, Jinhe Ye

Motivated by the theory of domination for types, we introduce a notion of domination for Keisler measures called extension domination. We argue that this variant of domination behaves similarly to its type setting counterpart. We prove that extension domination extends domination for types and that it forms a preorder on the space of global Keisler measures.

Eni Musta, Valentin Patilea, Ingrid Van Keilegom

Cure models have been developed as an alternative modelling approach to conventional survival analysis in order to account for the presence of cured subjects that will never experience the event of interest. Mixture cure models, which model separately the cure probability and the survival of uncured subjects depending on a set of covariates, are particularly

Apostolos I. Rikos, Christoforos N. Hadjicostis, Karl H. Johansson

In this paper, we focus on the problem of data sharing over a wireless computer network (i.e., a wireless grid). Given a set of available data, we present a distributed algorithm which operates over a dynamically changing network, and allows each node to calculate the optimal allocation of data in a finite number of time steps. We show that our proposed algo

David Benisty

Many alternative theories of gravity screens a Yukawa-type potential. This article shows Keplerian-type parametrization as a solution of Yukawa type potential accurate equations of motion for two non-spinning compact objects moving in an eccentric orbit. A bound from the solar system is presented.

Cheng Cheng, Haojing Yan, Jia-Sheng Huang, Christopher N. A. Willmer

Using the 0.9--4.4~$\mu$m imaging data from the James Webb Space Telescope (JWST) Early Release Observation in the SMACS J0723.3-7327 galaxy cluster field, we discuss the properties of three submillimeter galaxies (SMGs) detected by the Atacama Large Millimeter Array. These sources are magnified by 1.4--2.1$\times$due to gravitational lensing. This is the fi

Anna Szumowicz

Let $D$ be a Dedekind domain. Roughly speaking, a simultaneous $\mathfrak{p}$-ordering is a sequence of elements from $D$ which is equidistributed modulo every power of every prime ideal in $D$ as well as possible. Bhargava asked which subsets of the Dedekind domains admit simultaneous $\mathfrak{p}$-orderings. We give an overview on the progress in this pro

Apostolos I. Rikos, Gabriele Oliva, Christoforos N. Hadjicostis, Karl H. Johansson

In this paper, we present a distributed algorithm which implements the $k$-means algorithm in a distributed fashion for multi-agent systems with directed communication links. The goal of $k$-means is to partition the network's agents in mutually exclusive sets (groups) such that agents in the same set have (and possibly share) similar information and are abl

William Chang

Inspired by the Stochastic processes described by the Feller Coupling and Chinese Restaurant Processes, we create four different bijections from words in the set $[1]\times [2] \times\cdot \times[n]$ to $S_n$. We then compose these maps with their inverse to obtain a toal of six bijections $S_n \to S_n$. Following that, we investigate the fixed points ($1$-c

Seyhmus Yilmaz, Sultan Zavrak

In this study, we aimed to address the growing concern of trolling behavior on social media by developing and evaluating a set of model architectures for the automatic detection of troll tweets. Utilizing deep learning techniques and pre-trained word embedding methods such as BERT, ELMo, and GloVe, we evaluated the performance of each architecture using metr

Alex Lamb, Riashat Islam, Yonathan Efroni, Aniket Didolkar

In many sequential decision-making tasks, the agent is not able to model the full complexity of the world, which consists of multitudes of relevant and irrelevant information. For example, a person walking along a city street who tries to model all aspects of the world would quickly be overwhelmed by a multitude of shops, cars, and people moving in and out o

Ying-Hai Wu

Motivated by the experiments on double monolayer graphene that observe a variety of fractional quantum Hall states [Liu et al., Nat. Phys. 15, 893 (2019); Li et al., Nat. Phys. 15, 898 (2019)], we study the special setting in which two monolayers have different areas. It has not been considered before and allows us to construct a class of exotic topological