July 2022 arXiv papers — page 7

Maayan Gelboim, Amir Adler, Yen Sun, Mauricio Araya-Polo

Inverting seismic data to build 3D geological structures is a challenging task due to the overwhelming amount of acquired seismic data, and the very-high computational load due to iterative numerical solutions of the wave equation, as required by industry-standard tools such as Full Waveform Inversion (FWI). For example, in an area with surface dimensions of

Olaf Hohm, Allison F. Pinto

We explore perturbative double field theory about time-dependent (cosmological) backgrounds to cubic order. To this order the theory is consistent in a weakly constrained sense, so that for a toroidal geometry it encodes both momentum and genuine winding modes. We give a self-contained discussion of the consistency problems and their resolution, including th

Bryan O'Gorman

Shadow tomography via classical shadows is a state-of-the-art approach for estimating properties of a quantum state. We present a simplified, combinatorial analysis of a recently proposed instantiation of this approach based on the ensemble of unitaries that are both fermionic Gaussian and Clifford. Using this analysis, we derive a corrected expression for t

Carlos Cartes

During the second half of October 2019, Chile, and especially its capital city, Santiago, suffered from widespread violence with public and private infrastructure destruction. This work aims to expand an epidemiological non-local model that successfully described the French riots of 2005 to incorporate the topology of Santiago's subway network and explain th

A. O. Scheie, Y. Kamiya, Hao Zhang, Sangyun Lee

Quantum spin liquids (QSL) are theoretical states of matter with long-range entanglement and exotic quasiparticles. However, they generally elude quantitative theory, rendering their underlying phases mysterious and hampering efforts to identify experimental QSL states. Here we study triangular lattice resonating valence bond QSL candidate materials KYbSe$_2

Pedro Carrilho, Chiara Moretti, Alkistis Pourtsidou

We analyse the BOSS DR12 galaxy power spectrum data jointly with BAO data for three models of dark energy. We use recent measurements using a windowless estimator, and an independent and fast pipeline based on EFTofLSS implemented via the FAST-PT algorithm to compute the redshift-space loop corrections. We accelerate our analysis by using the BACCO linear em

Jaime del Moral, Laura Montes, Victor J. Rico, Carmen Lopez-Santos

Icing has become a hot topic both in academia and in the industry given its implications in strategic sectors such as transport, robotics, wind turbines, photovoltaics, and electricity supply. Recently proposed de-icing solutions involving the propagation of acoustic waves (AWs) at suitable substrates may open the path for a sustainable alternative to standa

Weng Fei Low, Gim Hee Lee

Explicit neural surface representations allow for exact and efficient extraction of the encoded surface at arbitrary precision, as well as analytic derivation of differential geometric properties such as surface normal and curvature. Such desirable properties, which are absent in its implicit counterpart, makes it ideal for various applications in computer v

Pranav Agnihotri, Sara Ketabi, Khashayar, Namdar

Traditional datasets for the radiological diagnosis tend to only provide the radiology image alongside the radiology report. However, radiology reading as performed by radiologists is a complex process, and information such as the radiologist's eye-fixations over the course of the reading has the potential to be an invaluable data source to learn from. Nonet

Dean S. Hazineh, Soon Wei Daniel Lim, Zhujun Shi, Federico Capasso

Optical metasurfaces are planar substrates with custom-designed, nanoscale features that selectively modulate incident light with respect to direction, wavelength, and polarization. When coupled with photodetectors and appropriate post-capture processing, they provide a means to create computational imagers and sensors that are exceptionally small and have d

Margarita P. Castro, Merve Bodur, Yongjia Song

We introduce an aggregation framework to address multi-stage stochastic programs with mixed-integer state variables and continuous local variables (MSILPs). Our aggregation framework imposes additional structure to the integer state variables by leveraging the information of the underlying stochastic process, which is modeled as a Markov chain (MC). We demon

Lorenzo Gavassino, Marco Antonelli, Brynmor Haskell

We set up a general framework for systematically building and classifying, in the linear regime, causal and stable dissipative hydrodynamic theories that, alongside with the usual hydrodynamic modes, also allow for an arbitrary number of non-hydrodynamic modes with complex dispersion relation (such theories are often referred to as "quasi-hydrodynamic"). To

Youssra Boujakhrout, El Hassan Saidi

Using 4D Chern-Simons (CS) theory with gauge symmetry $G$ having minuscule coweights, we develop a suitable operator basis to deal with the explicit calculation of the Lax operator of integrable spin chain satisfying the RLL equation. Using this basis, we derive the oscillator realisations of the full list of the minuscule L-operators which are classified by

Khashayar Namdar, Matthias W. Wagner, Birgit B. Ertl-Wagner, Farzad Khalvati

Background: As an important branch of machine learning pipelines in medical imaging, radiomics faces two major challenges namely reproducibility and accessibility. In this work, we introduce open-radiomics, a set of radiomics datasets along with a comprehensive radiomics pipeline based on our proposed technical protocol to improve the reproducibility of the

Ricardo A. Pasquini

We examine the allocation of a limited pool of matching funds to public good projects using Quadratic Funding. In particular, we consider a variation of the Capital Constrained Quadratic Funding (CQF) mechanism proposed by Buterin, Hitzig and Weyl (2019) where only funds in the matching pool are distributed among projects. We show that this mechanism achieve

P. Franco, A. Izidoro, O. C. Winter, K. S. Torres

The classical scenario of terrestrial planet formation is characterized by a phase of giant impacts among Moon-to-Mars mass planetary embryos. While the classic model and its adaptations have produced adequate analogs of the outer three terrestrial planets, Mercury's origin remains elusive. Mercury's high-core mass fraction compared to the Earth's is particu

Sanu Mishra, Yu Liu, Eric D. Bauer, Filip Ronning

We report anisotropic resistivity measurements of the heavy-fermion superconductor CeRh$_2$As$_2$ in magnetic fields up to 16 T and temperatures down to 0.35 K. The measured CeRh$_2$As$_2$ resistivity shows a signature corresponding to the suggested quadrupole density wave order state at $T_0 \sim$ 0.5 K for both measured directions. For a magnetic field app

Nicholas Muir, Steven James

In this work, we consider the problem of procedural content generation for video game levels. Prior approaches have relied on evolutionary search (ES) methods capable of generating diverse levels, but this generation procedure is slow, which is problematic in real-time settings. Reinforcement learning (RL) has also been proposed to tackle the same problem, a

Rodrigo Chaves, Jaime Santos, Bruno Chagas

We obtained analytical expressions considering a directed continuous-time quantum walk on a directed infinite line using Bessel functions, expanding previous results in the literature, for a general initial condition. We derive the equation for the probability distribution, and show how to recover normal and enhanced decay rates for the survival probability

Jaap Eising, Jorge Cortes

Recent work in data-driven control has led to methods that find stabilizing controllers directly from measurements of an unknown system. However, for multi-agent systems we are often interested in finding controllers that take their distributed nature into account. For instance, the full state might not be available for feedback at every agent. In order to d

Peibei Cao, Dingquan Li, Kede Ma

Learning-based image quality assessment (IQA) has made remarkable progress in the past decade, but nearly all consider the two key components -- model and data -- in isolation. Specifically, model-centric IQA focuses on developing ``better'' objective quality methods on fixed and extensively reused datasets, with a great danger of overfitting. Data-centric I

Catherine Cossaboom, Sharon Zhou

A well-known observation of Serre and Tate is that the Hecke algebra acts locally nilpotently on modular forms mod 2 on $\mathrm{SL}_2(\mathbb{Z})$. We give an algorithm for calculating the degree of Hecke nilpotency for cusp forms, and we obtain a formula for the total number of cusp forms mod 2 of any given degree of nilpotency. Using these results, we fin

Jaap Eising, Shenyu Liu, Sonia Martinez, Jorge Cortes

This work studies data-driven switched controller design for discrete-time switched linear systems. Instead of having access to the full system dynamics, an initialization phase is performed, during which noiseless measurements of the state and the input are collected for each mode. Under certain conditions on these measurements, we develop a stabilizing swi

Qiang Liu, Nakjung Choi, Tao Han

5G and beyond is expected to enable various emerging use cases with diverse performance requirements from vertical industries. To serve these use cases cost-effectively, network slicing plays a key role in dynamically creating virtual end-to-end networks according to specific resource demands. A network slice may have hundreds of configurable parameters over

Enrique Moreno Méndez

Astrophysical black holes (BHs) can be fully described by their mass and spin. However, producing rapidly spinning ones is extremely difficult as the stars that produce them lose most of their angular momentum before the BH is formed. Binaries where the progenitor is paired with a low-mass star in a tight orbit can produce rapidly spinning BHs (through tides

Jan Peszek, David Poyato

We introduce a multi-dimensional variant of the kinetic Cucker-Smale model with singular and matrix-valued communication weight, which reduces to the singular kinetic Cucker-Smale equation in the one-dimensional case. We propose an appropriate notion of weak measure-valued solution to this second-order system and a suitable first-order reduction, which persi

Mariana Moreira, Patric Muggli, Jorge Vieira

The hosing instability poses a feasibility risk for plasma-based accelerator concepts. We show that the growth rate for beam hosing in the linear regime (which is relevant for concepts that use a long driver) is a function of the centroid perturbation wavelength. We demonstrate how this property can be used to damp centroid oscillations by detuning the plasm

D. A. H. Buckley, R. J. Britto, S. Chandra, V. Krushinsky

We present multiwavelength observations and a model for flat spectrum radio quasar NVSS J141922-083830, originally classified as a blazar candidate of unknown type (BCU II object) in the Third Fermi-LAT AGN Catalog (3LAC). Relatively bright flares (>3 magnitudes) were observed on 21 February 2015 (MJD 57074) and 8 September 2018 (MJD 58369) in the optical ba

Jin-Zhu Yu, Mincheng Wu, Gisela Bichler, Felipe Aros-Vera

Network structure provides critical information for understanding the dynamic behavior of networks. However, the complete structure of real-world networks is often unavailable, thus it is crucially important to develop approaches to infer a more complete structure of networks. In this paper, we integrate the configuration model for generating random networks

Giles Blaney, Cristianne Fernandez, Angelo Sassaroli, Sergio Fantini

Significance: This work targets the contamination of optical signals by superficial hemodynamics, which is one of the chief hurdles in non-invasive optical measurements of the human brain. Aim: To identify optimal source-detector distances for Dual-Slope (DS) measurements in Frequency-Domain (FD) Near-InfraRed Spectroscopy (NIRS) and demonstrate preferential

Hang Chu, Amir Hosein Khasahmadi, Karl D. D. Willis, Fraser Anderson

User modeling is crucial to understanding user behavior and essential for improving user experience and personalized recommendations. When users interact with software, vast amounts of command sequences are generated through logging and analytics systems. These command sequences contain clues to the users' goals and intents. However, these data modalities ar

Robert Davis, Florian Kohl

A subset $S$ of vertices of a graph $G$ is called a perfectly matchable set of $G$ if the subgraph induced by $S$ contains a perfect matching. The perfectly matchable set polynomial of $G$, first made explicit by Ohsugi and Tsuchiya, is the (ordinary) generating function $p(G; z)$ for the number of perfectly matchable sets of $G$. In this work, we provide ex

Alicia Villanueva

This volume constitutes the informal proceedings of the 32nd International Symposium on Logic-Based Program Synthesis and Transformation (LOPSTR 2022), held on 21-23rd September 2022 as a hybrid (blended) meeting, both in-person (at the Ivane Javakhishvili Tbilisi State University -TSU- in Tbilisi, Georgia) and virtual, and co-located with the 24th Internati

Taylor Yow, Christopher W. Hays, Aryslan Malik, Troy Henderson

The Product of Exponentials (PoE) formulation is most commonly used in the field of robotics, but has recently been adapted for use in describing orbital motion. The PoE formula for orbital mechanics is an alternate method for defining and drawing an orbit based on its orbital elements set. Currently the PoE formula for orbital mechanics has only been derive

Nicola Messina, Matteo Stefanini, Marcella Cornia, Lorenzo Baraldi

Image-text matching is gaining a leading role among tasks involving the joint understanding of vision and language. In literature, this task is often used as a pre-training objective to forge architectures able to jointly deal with images and texts. Nonetheless, it has a direct downstream application: cross-modal retrieval, which consists in finding images r

Johannes Milz, Thomas M. Surowiec

Optimal values and solutions of empirical approximations of stochastic optimization problems can be viewed as statistical estimators of their true values. From this perspective, it is important to understand the asymptotic behavior of these estimators as the sample size goes to infinity. This area of study has a long tradition in stochastic programming. Howe

Johannes Milz, Michael Ulbrich

The sample average approximation (SAA) approach is applied to risk-neutral optimization problems governed by semilinear elliptic partial differential equations with random inputs. After constructing a compact set that contains the SAA critical points, we derive nonasymptotic sample size estimates for SAA critical points using the covering number approach. Th

Christian Lehn, Giovanni Mongardi, Gianluca Pacienza

We prove the Morrison--Kawamata cone conjecture for projective primitive symplectic varieties with $\Q$-factorial and terminal singularities with $b_2\geq 5$, from which we derive for instance the finiteness of minimal models of such varieties, up to isomorphisms. To prove the conjecture we establish along the way some results on the monodromy group which ma

James P. Long, Hongxu Zhu, Kim-Anh Do, Min Jin Ha

Recent works have proposed regression models which are invariant across data collection environments. These estimators often have a causal interpretation under conditions on the environments and type of invariance imposed. One recent example, the Causal Dantzig (CD), is consistent under hidden confounding and represents an alternative to classical instrument

Ernst Albrecht, Raúl E. Curto, Michael Hartz, Mihai Putinar

An outline of J\"org Eschmeier's main mathematical contributions is organized both on a historical perspective, as well as on a few distinct topics. The reader can grasp from our essay the dynamics of spectral theory of commutative tuples of linear operators during the last half century. Some clear directions of future research are also underlined.

Matthew Heffernan, Charles Gale, Sangyong Jeon, Jean-Francois Paquet

We present a demonstration of the design sampling and closure for the first comprehensive Bayesian model-to-data comparison of heavy-ion measurements with IP-Glasma initial conditions, in which we combine with state-of-the-art hydrodynamics (MUSIC), particlization (iS3D), and transport (SMASH). We further introduce a systematically-improvable method of sampl

L. Gries, M. Jonak, A. Elghandour, K. Dey

We report the thermodynamic properties studied by thermal expansion, magnetostriction, magnetisation, and specific heat measurements as well as the low-energy magnetic excitations of \mto\ and investigate how magneto-elastic coupling and magnetic anisotropy affect the evolution of long-range order and the magnetic phase diagram. Specifically, we utilise high

Wei-Yuan Liu, Xing-Long Zhu, Min Chen, Su-Ming Weng

Relativistic laser wakefield acceleration is characterized by an unsurpassed accelerating gradient, which is very suitable for electron acceleration over short distances and could be a promising candidate for next-generation compact accelerators. However, using this technique for positron acceleration is still challenging because positively charged particles

Riccardo Borsato, Sibylle Driezen, Juan Miguel Nieto García, Leander Wyss

We study a Jordanian deformation of the $AdS_5 \times S^5$ superstring that preserves 12 superisometries. It is an example of homogeneous Yang-Baxter deformations, a class that generalises TsT deformations to the non-abelian case. Many of the attractive features of TsT carry over to this more general class, from the possibility of generating new supergravity

M. Van der Swaelmen, C. Viscasillas Vázquez, G. Cescutti, L. Magrini

A renewed interest about the origin of \emph{r}-process elements has been stimulated by the multi-messenger observation of the gravitational event GW170817, with the detection of both gravitational waves and electromagnetic waves corresponding to the merger of two neutron stars. Such phenomenon has been proposed as one of the main sources of the \emph{r}-pro

Deng-hui Yu, Chang-shui Yu

In quantum metrology, the parameter estimation accuracy is bounded by quantum Fisher information. In this paper, we present coherence measures in terms of (quantum) Fisher information by directly considering the post-selective non-unitary parametrization process. This coherence measure demonstrates the apparent operational meaning by the exact connection bet

Jessie van Dam, Andreea Tulbure, Maria Vittoria Minniti, Firas Abi-Farraj

To safely deploy legged robots in the real world it is necessary to provide them with the ability to reliably detect unexpected contacts and accurately estimate the corresponding contact force. In this paper, we propose a collision detection and identification pipeline for a quadrupedal manipulator. We first introduce an approach to estimate the collision ti

Saman Ahmadi, Guido Tack, Daniel Harabor, Philip Kilby

The classic problem of constrained pathfinding is a well-studied, yet challenging, topic in AI with a broad range of applications in various areas such as communication and transportation. The Weight Constrained Shortest Path Problem (WCSPP), the base form of constrained pathfinding with only one side constraint, aims to plan a cost-optimum path with limited

A. Evans, B. Pimpanuwat, A. M. S. Richards, D. P. K. Banerjee

There are indications that the third known eruption of the recurrent nova T CrB is imminent, and multi-wavelength observations prior to the eruption are important to characterise the system before it erupts. T CrB is known to display the SiO fundamental vibrational feature at 8$\,\mu$m. When the anticipated eruption occurs, it is possible that the shock prod

Sebastian Cammerer, Jakob Hoydis, Fayçal Aït Aoudia, Alexander Keller

In this work, we propose a fully differentiable graph neural network (GNN)-based architecture for channel decoding and showcase a competitive decoding performance for various coding schemes, such as low-density parity-check (LDPC) and BCH codes. The idea is to let a neural network (NN) learn a generalized message passing algorithm over a given graph that rep

Khaled Alrfou, Amir Kordijazi, Tian Zhao

Finding quantitative descriptors representing the microstructural features of a given material is an ongoing research area in the paradigm of Materials-by-Design. Historically, microstructural analysis mostly relies on qualitative descriptions. However, to build a robust and accurate process-structure-properties relationship, which is required for designing

Zelin Zhao, Jiaya Jia

In this paper, we present a simple seq2seq formulation for view synthesis where we take a set of ray points as input and output colors corresponding to the rays. Directly applying a standard transformer on this seq2seq formulation has two limitations. First, the standard attention cannot successfully fit the volumetric rendering procedure, and therefore high

Fanqi Meng, Xixi Xiao, Jingdong Wang

Online public opinion usually spreads rapidly and widely, thus a small incident probably evolves into a large social crisis in a very short time, and results in a heavy loss in credit or economic aspects. We propose a method to rate the crisis of online public opinion based on a multi-level index system to evaluate the impact of events objectively. Firstly,

Alex Sierra Cárdenas

In this article we calculate two aspects of the representation theory of a Brauer configuration algebra: its Cartan matrix, and the module length of its associated indecomposable projective modules. Then we introduce the concept of subgroup-occurrence of an element in a group and use the previous aspects to demonstrate combinatorial equalities satisfied for

Félix Locas, Jean-François Renaud

We consider De Finetti's control problem for absolutely continuous strategies with control rates bounded by a concave function and prove that a generalized mean-reverting strategy is optimal. In order to solve this problem, we need to deal with a nonlinear Ornstein-Uhlenbeck process. Despite the level of generality of the bound imposed on the rate, an explic

Feng Zhu, Andrew Zimmer

This is the second in a series of two papers that develops a theory of relatively Anosov representations using the original "contracting flow on a bundle" definition of Anosov representations introduced by Labourie and Guichard-Wienhard. In this paper we focus on building families of examples.

Feng Zhu, Andrew Zimmer

This is the first in a series of two papers that develops a theory of relatively Anosov representations using the original "contracting flow on a bundle" definition of Anosov representations introduced by Labourie and Guichard-Wienhard. In this paper we will mostly focus on general theory while in the second paper we will focus on examples. In the case of re

Cong-Thanh Do, Mohan Li, Rama Doddipatla

This paper proposes a new approach to perform unsupervised fine-tuning and self-training using unlabeled speech data for recurrent neural network (RNN)-Transducer (RNN-T) end-to-end (E2E) automatic speech recognition (ASR) systems. Conventional systems perform fine-tuning/self-training using ASR hypothesis as the targets when using unlabeled audio data and a

Derek Inman, Kazunori Kohri

We consider the consequences of a matter power spectrum which rises on small scales until eventually being cutoff by microphysical processes associated with the particle nature of dark matter. Evolving the perturbations of a weakly interacting massive particle from before decoupling until deep in the nonlinear regime, we show that nonlinear structure can for

Angus Lowe, Matija Medvidović, Anthony Hayes, Lee J. O'Riordan

We propose a new method to extend the size of a quantum computation beyond the number of physical qubits available on a single device. This is accomplished by randomly inserting measure-and-prepare channels to express the output state of a large circuit as a separable state across distinct devices. Our method employs randomized measurements, resulting in a s

L. Barrufet, P. A. Oesch, A. Weibel, G. Brammer

Over the last few years, both ALMA and Spitzer/IRAC observations have revealed a population of likely massive galaxies at $z>3$ that was too faint to be detected in HST rest-frame ultraviolet imaging. However, due to the very limited photometry for individual galaxies, the true nature of these so-called HST-dark galaxies has remained elusive. Here, we presen

Silvia Pietroni, Valerio Bozza

After the amazing discoveries by the GRAVITY collaboration in the last few years on the star S2 orbiting the black hole Sgr A* in the center of the Milky Way, we present a detailed investigation of the impact of gravitational lensing on the reconstruction of stellar orbits around this massive black hole. We evaluate the lensing astrometric effects on the sta

Daphna Shimon, Kelly A. Cantwell, Linta Joseph, Chandrasekhar Ramanathan

Dynamic nuclear polarization (DNP) is a method of enhancing NMR signals via the transfer of polarization from electron spins to nuclear spins using on-resonance microwave (MW) irradiation. In most cases, monochromatic continuous-wave (MCW) MW irradiation is used. Recently, several groups have shown that the use of frequency modulation of the MW irradiation c

Yigermal Bassie, Mohammed Mahmud, and Mulugeta Bekele

A large number of water molecules are each placed on a lattice far apart so that they are very weakly interacting with each other and in contact with a heat bath at temperature $T$. A strong static electric field, $E_{0}$, is applied to these molecules along a $z$-axis causing three level split energy values. A weak AC electric field that acts for a finite t

Lakshwin Shreesha, Michael Levin

Biological genotypes do not code directly for phenotypes; developmental physiology is the control layer that separates genomes from capacities ascertained by selection. A key aspect is competency, as cells are not a passive material but descendants of unicellular organisms with complex context-sensitive capabilities. We used an evolutionary simulation in the

Jakub Kwaśny, Marcin Stawiski

An edge colouring of a graph is called distinguishing if there is no non-trivial automorphism which preserves it. We prove that every at most countable, finite or infinite, connected regular graph of order at least $7$ admits a distinguishing edge colouring from any set of lists of length $2$. Furthermore, we show that the same holds for connected regular gr

Florian Gunsilius, Meng Hsuan Hsieh, Myung Jin Lee

We develop a notion of projections between sets of probability measures using the geometric properties of the 2-Wasserstein space. It is designed for general multivariate probability measures, is computationally efficient to implement, and provides a unique solution in regular settings. The idea is to work on regular tangent cones of the Wasserstein space us

Haida Li, Shengzhi Li, Yongge Ma

The connection dynamics of the 5-dimensional Kaluza-Klein theory reduced on 4-dimensional spacetime is obtained by performing the Hamiltonian analysis and canonical transformations. Deparametrization is achieved in the spherically symmetric model of the theory without introducing additional matter fields beyond the 5-dimensional gravity. Thus the physical ti

Ursula Carow-Watamura, Kohei Miura, Satoshi Watamura

In this article we investigate the gauge invariance and duality properties of DFT based on a metric algebroid formulation given previously in [1]. The derivation of the general action given in this paper does not employ the section condition. Instead, the action is determined by requiring a pre-Bianchi identity on the structure functions of the metric algebr

Richard S. J. Tol

The IPCC started at a time when climate policy was an aspiration for the future. The research assessed in the early IPCC reports was necessarily about potential climate policies, always stylized and often optimized. The IPCC has continued on this path, even though there is now a considerable literature studying actual climate policy, in all its infuriating d

Shuang Hu, Zuoxiang Peng, Johan Segers

Multivariate extreme value distributions are a common choice for modelling multivariate extremes. In high dimensions, however, the construction of flexible and parsimonious models is challenging. We propose to combine bivariate max-stable distributions into a Markov random field with respect to a tree. Although in general not max-stable itself, this Markov t

Xu Han, Feng Wu

Most reinforcement learning (RL) methods only focus on learning a single task from scratch and are not able to use prior knowledge to learn other tasks more effectively. Context-based meta RL techniques are recently proposed as a possible solution to tackle this. However, they are usually less efficient than conventional RL and may require many trial-and-err

Yixiang Wang, Yujing Hu, Feng Wu, Yingfeng Chen

Reward design is a critical part of the application of reinforcement learning, the performance of which strongly depends on how well the reward signal frames the goal of the designer and how well the signal assesses progress in reaching that goal. In many cases, the extrinsic rewards provided by the environment (e.g., win or loss of a game) are very sparse a

B. Kaminsky, A. Evans, Ya. V. Pavlenko, C. E. Woodward

We present an analysis of the red giant component of the recurrent nova V3890 Sgr, using data obtained before and after its 2019 eruption. Its effective temperature is $T_{\rm eff}=3050\pm$200 K for $\log{g}=0.7$, although there are modest changes in $T_{\rm eff}$. There is an overabundance of both carbon ($0.20\pm0.05$~dex) and sodium ($1.0\pm0.3$~dex) rela

Daniela Dobrynin, Iryna Polishchuk, Boaz Pokroy

Since the first case of COVID-19 disease in Wuhan in December 2019, there is a worldwide struggle to reduce the transmission of acute respiratory syndrome coronavirus SARS-CoV-2. Many countries worldwide decided to impose local lockdowns in order to reduce person-to-person interactions, masks became obligatory especially in closed spaces, and there was a gen

Samuel Pawel, Frederik Aust, Leonhard Held, Eric-Jan Wagenmakers

The ongoing replication crisis in science has increased interest in the methodology of replication studies. We propose a novel Bayesian analysis approach using power priors: The likelihood of the original study's data is raised to the power of $\alpha$, and then used as the prior distribution in the analysis of the replication data. Posterior distribution an

Hieu Van Ha, Vu Anh Le, Tu Thi Cam Nguyen, Hoa Duong Quang

We give a classification of real solvable Lie algebras whose non-trivial coadjoint orbits of corresponding simply connected Lie groups are all of codimension 2. These Lie algebras belong to a well-known class, called the class of MD-algebras.

Peter Lowdon, Owe Philipsen

Spectral functions encode a wealth of information about the dynamics of any given system, and the determination of their non-perturbative characteristics is a long-standing problem in quantum field theory. Whilst numerical simulations of lattice QCD provide ample data for various Euclidean correlation functions, the inversion required to extract spectral fun

Yannis Chaumeny, Johan van der Molen Moris, Anthony C. Davison, Paul D. W. Kirk

We consider the Bayesian mixture of finite mixtures (MFMs) and Dirichlet process mixture (DPM) models for clustering. Recent asymptotic theory has established that DPMs overestimate the number of clusters for large samples and that estimators from both classes of models are inconsistent for the number of clusters under misspecification, but the implications

Maximilian Böhme, Zhandos A. Moldabekov, Jan Vorberger, Tobias Dornheim

We combine ab initio path integral Monte Carlo (PIMC) simulations with fixed ion configurations from density functional theory molecular dynamics (DFT-MD) simulations to solve the electronic problem for hydrogen under warm dense matter conditions [M.B\"ohme et. al. Phys.Rev.Lett.(in print)]. The problem of path collapse due to the Coulomb attraction is avoid

Bertrand Cloez, Bénédicte Fontez, Eliel González García, Isabelle Sanchez

Impulsed noise outliers are data points that differs significantly from other observations.They are generally removed from the data set through local regression or Kalman filter algorithm.However, these methods, or their generalizations, are not well suited when the number of outliers is ofthe same order as the number of low-noise data. In this article, we p

Slavko Radenković, Dominik Domin, Julien Toulouse, Benoît Braïda

The VB-QMC method is presented in this chapter. It consists of using in quantum Monte Carlo (QMC) approaches with a wave function expressed as a usually short expansion of classical Valence-Bond (VB) structures supplemented by a Jastrow factor to account for dynamical correlation. Two variants exist: the VB-VMC (using variational Monte Carlo) and VB-DMC (usi

Alfredo Iorio, Boris Ivetić, Salvatore Mignemi, Pablo Pais

We show that graphene, in its simplest form and settings, is a practical table-top realization of the analog of exotic quantum gravity scenarios, which are speculated to lead to certain generalized Heisenberg algebras. In particular, we identify three different energy regimes (the ``layers'') where the physics is still of a pseudorelativistic (Dirac) type bu

Christian Mateo Frausto-Avila, Victor Arellano-Arreola, Jose Martin Yañez Limon, Andres de Luna-Bugallo

We characterize heat dissipation of supported molybdenum disulfide (MoS$_2$) monolayers grown by chemical vapor deposition by means of ambient-condition scanning thermal microscopy (SThM). We find that the thermal boundary conductance of the MoS$_2$ monolayers in contact with 300 nm of SiO$_2$ is around 4.6 $\pm$ 2 MW m$^{-2}$ K$^{-1}$. This value is in the

Daniel B. Thomas, Timothy Clifton, Theodore Anton

Parameterised Post-Newtonian Cosmology (PPNC) is a theory-agnostic framework for testing gravity in cosmology, which connects gravitational physics on small and large scales in the Universe. It is a direct extension of the Parameterised Post-Newtonian (PPN) approach to testing gravity in isolated astrophysical systems, and therefore allows constraints on gra

Andreas Gleis, Jheng-Wei Li, Jan von Delft

DMRG ground state search algorithms employing symmetries must be able to expand virtual bond spaces by adding or changing symmetry sectors if these lower the energy. Traditional single-site DMRG does not allow bond expansion; two-site DMRG does, but at much higher computational costs. We present a controlled bond expansion (CBE) algorithm that yields two-sit

Jasmine Latendresse, Suhaib Mujahid, Diego Elias Costa, Emad Shihab

Modern software systems are often built by leveraging code written by others in the form of libraries and packages to accelerate their development. While there are many benefits to using third-party packages, software projects often become dependent on a large number of software packages. Consequently, developers are faced with the difficult challenge of mai

Mariachiara Manoccio, Vittorianna Tasco, Francesco Todisco, Adriana Passaseo

Chiral lattice modes are hybrid states arising from chiral plasmonic particles assembled in ordered arrays with opportune periodicity. These resonances exhibit dependence on excitation handedness, and their observation in plasmonic lattices is strictly related to the chiroptical features of the fundamental plasmonic unit. Here, we show the emergence of chira

Shuai Huang, James J. Lah, Jason W. Allen, Deqiang Qiu

Purpose: For quantitative susceptibility mapping (QSM), the lack of ground-truth in clinical settings makes it challenging to determine suitable parameters for the dipole inversion. We propose a probabilistic Bayesian approach for QSM with built-in parameter estimation, and incorporate the nonlinear formulation of the dipole inversion to achieve a robust rec

V. V. Zharkova, I. Vasilieva, S. J. Shepherd, E. Popova

We attempt to establish links between a summary curve, or modulus summary curve, MSC, of the solar background magnetic field (SBMF) derived from Principal Component Analysis, with the averaged sunspot numbers (SSN). The comparison of MSC with the whole set of SSN reveals rather close correspondence of cycle timings, duration and maxima times for the cycles 1

Yoann Pelet, Grégory Sauder, Mathis Cohen, Laurent Labonté

We present a real field quantum key distribution link based on energy-time entanglement. Three nodes are connected over the city of Nice by means of optical fibers with a total distance of 50\,km. We have implemented a high-quality source of energy-time entangled photon pairs and actively stabilized analysers to project the quantum states, associated with an

K. A. G. Bonsma-Fisher, P. J. Bustard, C. Parry, T. A. Wright

Quantum frequency conversion of single photons between wavelength bands is a key enabler to realizing widespread quantum networks. We demonstrate the quantum frequency conversion of a heralded 1551 nm photon to any wavelength within an ultrabroad (1226 - 1408 nm) range in a group-velocity-symmetric photonic crystal fiber (PCF), covering over 150 independent

Haotian Tong, Dag Westerståhl

We show that intuitionistic propositional logic is \emph{Carnap categorical}: the only interpretation of the connectives consistent with the intuitionistic consequence relation is the standard interpretation. This holds relative to the most well-known semantics with respect to which intuitionistic logic is sound and complete; among them Kripke semantics, Bet

Lucas Möller, Sebastian Padó

A number of models for neural content-based news recommendation have been proposed. However, there is limited understanding of the relative importances of the three main components of such systems (news encoder, user encoder, and scoring function) and the trade-offs involved. In this paper, we assess the hypothesis that the most widely used means of matching

Max Forester

This paper concerns locally finite 2-complexes $X_{m,n}$ which are combinatorial models for the Baumslag-Solitar groups $BS(m,n)$. We show that, in many cases, the locally compact group Aut($X_{m,n}$) contains incommensurable uniform lattices. The lattices we construct also admit isomorphic Cayley graphs and are finitely presented, torsion-free, and coherent

Dipak Kumar Bhunia, Cristina Fernández-Córdoba, Mercè Villanueva

The $\mathbb{Z}_p\mathbb{Z}_{p^2}\dots\mathbb{Z}_{p^s}$-additive codes are subgroups of $\mathbb{Z}_p^{\alpha_1} \times \mathbb{Z}_{p^2}^{\alpha_2} \times \cdots \times \mathbb{Z}_{p^s}^{\alpha_s}$, and can be seen as linear codes over $\mathbb{Z}_p$ when $\alpha_i=0$ for all $i \in \{2,\dots, s\}$, a $\mathbb{Z}_{p^s}$-additive code when $\alpha_i=0$ for al

Amir Babak Aazami

We approach the problem of finding obstructions to curvature distinguished Riemannian metrics by considering Lorentzian metrics to which they are dual in a suitable sense. Obstructions to the latter then yield obstructions to the former. This framework applies both locally and globally, including to compact manifolds, and is sensitive to various aspects of c

Seung Yeon Shin, Thomas C. Shen, Stephen A. Wank, Ronald M. Summers

Finding small lesions is very challenging due to lack of noticeable features, severe class imbalance, as well as the size itself. One approach to improve small lesion segmentation is to reduce the region of interest and inspect it at a higher sensitivity rather than performing it for the entire region. It is usually implemented as sequential or joint segment

Debbie Zhuang, Martin Z. Bazant

Disorder-driven degradation phenomena, such as structural phase transformations and surface reconstructions, can significantly reduce the lifetime of Li-ion batteries, especially those with nickel-rich layered-oxide cathodes. We develop a general free energy model for layered-oxide ion-intercalation materials as a function of the degree of disorder, which re

Jiachang Hao, Haifeng Sun, Pengfei Ren, Jingyu Wang

Temporal grounding aims to locate a target video moment that semantically corresponds to the given sentence query in an untrimmed video. However, recent works find that existing methods suffer a severe temporal bias problem. These methods do not reason the target moment locations based on the visual-textual semantic alignment but over-rely on the temporal bi