June 2020 arXiv papers — page 5

František Dinnbier, Pavel Kroupa

We study the formation and evolution of the tidal tail released from a young Pleiades-like star cluster, due to expulsion of primordial gas in a realistic gravitational field of the Galaxy. The tidal tails (as well as clusters) are integrated from their embedded phase for 300 Myr. We vary star formation efficiencies (SFEs) from 33% to 100% and the timescales

Benjamin Call

We set out some general criteria to prove the K-property, refining the assumptions used in arXiv:1906.09315 for the flow case, and introducing the analogous discrete-time result. We also introduce one-sided $λ$-decompositions, as well as multiple techniques for checking the pressure gap required to show the K-property. We apply our results to the family of M

Eftychia Sagkrioti

We compute the anomalous dimension of the single current operator in the case of single and doubly deformed asymmetric $λ$-models with a general deformation matrix. Our method uses the underlying geometry of the coupling space, as well as an auxiliary group interaction, which completely decouples from the asymmetric model in a specific limit, consistent with

Yanhong Xu, Reihaneh Safavi-Naini, Khoa Nguyen, Huaxiong Wang

Policy-based signatures (PBS) were proposed by Bellare and Fuchsbauer (PKC 2014) to allow an {\em authorized} member of an organization to sign a message on behalf of the organization. The user's authorization is determined by a policy managed by the organization's trusted authority, while the signature preserves the privacy of the organization's

Jinzhao Wang

Entropy and energy are found to be closely tied on our quest for quantum gravity. We point out an interesting connection between the recently proposed outer entropy, a coarse-grained entropy defined for a compact spacetime domain motivated by the holographic duality, and the Bartnik-Bray quasilocal mass long known in the mathematics community. In both scenar

Marija Cuic, Kresimir Kumericki, Andreas Schafer

Using the available data on deeply virtual Compton scattering (DVCS) off protons and utilizing neural networks enhanced by the dispersion relation constraint, we determine six out of eight leading Compton form factors in the valence quark kinematic region. Furthermore, adding recent data on DVCS off neutrons, we separate contributions of up and down quarks t

Ufuk Aydemir

We discuss the astrophysical and cosmological implications of having primordial thermal 2-2-hole remnants as dark matter. Thermal 2-2-holes emanate in quadratic gravity as horizonless classical solutions for ultracompact distributions of relativistic thermal gas. In contrast to a large 2-2-hole that imitates the thermodynamic behaviour of a black hole, a sma

You Xie, Nils Thuerey

We propose a novel training approach for improving the generalization in neural networks. We show that in contrast to regular constraints for orthogonality, our approach represents a {\em data-dependent} orthogonality constraint, and is closely related to singular value decompositions of the weight matrices. We also show how our formulation is easy to realiz

M. Kramer, F. R. N. Schneider, S. T. Ohlmann, S. Geier

Common envelope (CE) phases in binary systems where the primary star reaches the tip of the red giant branch are discussed as a formation scenario for hot subluminous B-type (sdB) stars. For some of these objects, observations point to very low-mass companions. In hydrodynamical CE simulations with the moving-mesh code AREPO, we test whether low-mass objects

Aklant K. Bhowmick, Laura Blecha, July Thomas

We study the association between active galactic nuclei (AGN) and environment at scales of $0.01-1\ h^{-1}$Mpc in the IllustrisTNG (TNG100) simulated universe. We identify supermassive black hole (BH) pairs and multiples within scales of 0.01, 0.1, & 1 $h^{-1}$Mpc and examine their AGN activity in relation to randomly-selected pairs and multiples. The number

E. Gatuzz, T. W. Gorczyca, M. F. Hasoglu, N. S. Schulz

We present a detailed analysis of the gaseous component of the Si K edge using high-resolution Chandra spectra of low-mass X-ray binaries. We fit the spectra with amodified version of the ISMabs model, including new photoabsorption cross sectionscomputed for all Si ionic species. We estimate column densities for Si i, Si ii, Si iii, Si xii and Si xiii, which

Andrew Repp, István Szapudi

Counts-in-cells (CIC) measurements contain a wealth of cosmological information yet are seldom used to constrain theories. Although we can predict the shape of the distribution for a given cosmology, to fit a model to the observed CIC probabilities requires the covariance matrix -- both the variance of counts in one probability bin and the covariance between

Martin Bies, Mirjam Cvetic, Ron Donagi, Ling Lin

Motivated by engineering vector-like (Higgs) pairs in the spectrum of 4d F-theory compactifications, we combine machine learning and algebraic geometry techniques to analyze line bundle cohomologies on families of holomorphic curves. To quantify jumps of these cohomologies, we first generate 1.8 million pairs of line bundles and curves embedded in $dP_3$, fo

Sarah M. R. Jeffreson, J. M. Diederik Kruijssen, Benjamin W. Keller, Mélanie Chevance

We examine the role of the large-scale galactic-dynamical environment in setting the properties of giant molecular clouds in Milky Way-like galaxies. We perform three high-resolution simulations of Milky Way-like discs with the moving-mesh hydrodynamics code Arepo, yielding a statistical sample of $\sim 80,000$ giant molecular clouds and $\sim 55,000$ HI clo

ChunJun Cao, Xiao-Liang Qi, Brian Swingle, Eugene Tang

Using the tensor Radon transform and related numerical methods, we study how bulk geometries can be explicitly reconstructed from boundary entanglement entropies in the specific case of $\mathrm{AdS}_3/\mathrm{CFT}_2$. We find that, given the boundary entanglement entropies of a $2$d CFT, this framework provides a quantitative measure that detects whether th

Juyang Weng

Universal Turing Machines [29, 10, 18] are well known in computer science but they are about manual programming for general purposes. Although human children perform conscious learning (i.e., learning while being conscious) from infancy [24, 23, 14, 4], it is unknown that Universal Turing Machiness can facilitate not only our understanding of Autonomous Prog

Iwan Duursma, Hsin-Po Wang

An $(n, k, d, α)$-MSR (minimum storage regeneration) code is a set of $n$ nodes used to store a file. For a file of total size $kα$, each node stores $α$ symbols, any $k$ nodes recover the file, and any $d$ nodes can repair any other node via each sending out $α/(d-k+1)$ symbols. In this work, we explore various ways to re-express the infamous product-matrix

Antoine Bourget, Julius F. Grimminger, Amihay Hanany, Marcus Sperling

Magnetic quivers and Hasse diagrams for Higgs branches of rank 1 $4d$ $\mathcal{N}=2$ SCFTs are provided. These rank 1 theories fit naturally into families of higher rank theories, originating from higher dimensions, which are addressed.

Flavia Bonomo-Braberman, Fabiano S. Oliveira, Moysés S. Sampaio, Jayme L. Szwarcfiter

Interval and proper interval graphs are very well-known graph classes, for which there is a wide literature. As a consequence, some generalizations of interval graphs have been proposed, in which graphs in general are expressed in terms of $k$ interval graphs, by splitting the graph in some special way. As a recent example of such an approach, the classes of

Shuyang Gu, Jianmin Bao, Dong Chen, Fang Wen

Generative adversarial networks (GANs) have achieved rapid progress in learning rich data distributions. However, we argue about two main issues in existing techniques. First, the low quality problem where the learned distribution has massive low quality samples. Second, the missing modes problem where the learned distribution misses some certain regions of

Tarik Aougab, Max Lahn, Marissa Loving, Yang Xiao

Given two finite covers $p: X \to S$ and $q: Y \to S$ of a connected, oriented, closed surface $S$ of genus at least $2$, we attempt to characterize the equivalence of $p$ and $q$ in terms of which curves lift to simple curves. Using Teichmüller theory and the complex of curves, we show that two regular covers $p$ and $q$ are equivalent if for any closed cur

S. Sanyal, K. Damle, J. T. Chalker, R. Moessner

We exhibit an exactly solvable example of a SU(2) symmetric Majorana spin liquid phase, in which quenched disorder leads to random-singlet phenomenology. More precisely, we argue that a strong-disorder fixed point controls the low temperature susceptibility $χ(T)$ of an exactly solvable $S=1/2$ model on the decorated honeycomb lattice with quenched bond diso

A. I. Lvovsky, Philippe Grangier, Alexei Ourjoumtsev, Valentina Parigi

This review covers recent theoretical and experimental efforts to extend the application of the continuous-variable quantum technology of light beyond "Gaussian" quantum states, such as coherent and squeezed states, into the domain of "non-Gaussian" states with negative Wigner functions. Starting with basic Gaussian nonclassicality associated

Trevor J. Hefley, Robin E. Russell, Anne E. Ballmann, Haoyu Zhang

A fundamental question during the outbreak of a novel disease or invasion of an exotic pest is: At what location and date was it first introduced? With this information, future introductions can be anticipated and perhaps avoided. Point process models are commonly used for mapping species distribution and disease occurrence. If the time and location of intro

Nikhil Parthasarathy, Eero P. Simoncelli

We develop a model for representing visual texture in a low-dimensional feature space, along with a novel self-supervised learning objective that is used to train it on an unlabeled database of texture images. Inspired by the architecture of primate visual cortex, the model uses a first stage of oriented linear filters (corresponding to cortical area V1), co

Yoann Génolini, Pasquale Serpico, Peter Tinyakov

Primordial black holes (PBH), produced through a variety of processes in the early universe, could fill galactic halos accounting for a fraction or the totality of the dark matter. In particular, PBH with sub-stellar masses could be captured by stars, start to swallow their material, and eventually turn them into BH, hence originating a peculiar new type of

Jiachen Sun, Yulong Cao, Qi Alfred Chen, Z. Morley Mao

Perception plays a pivotal role in autonomous driving systems, which utilizes onboard sensors like cameras and LiDARs (Light Detection and Ranging) to assess surroundings. Recent studies have demonstrated that LiDAR-based perception is vulnerable to spoofing attacks, in which adversaries spoof a fake vehicle in front of a victim self-driving car by strategic

Ronald Orozco López

In this paper, autonomous differential equations type delta of order one on integral domains are defined. For this we will use the autonomous ring defined on the Hurwitz expansion ring of exponential generating functions with coefficients in an integral domain. We will also use delta operators, which behave like derivatives when acting on polynomials, along

M. L. Lister, D. C. Homan, Y. Y. Kovalev, S. Mandal

We have carried out a Chandra X-ray and multi-frequency radio VLBA study of the AGN TXS 0128+554, which is associated with the Fermi gamma-ray source 4FGL J0131.2+5547. The AGN is unresolved in a target 19.3 ks Chandra image, and its spectrum is well fit by a simple absorbed power law model, with no distinguishable spectral features. Its relatively soft X-ra

Yang Li

We study polarised algebraic degenerations of Calabi-Yau manifolds. We prove a uniform Skoda type estimate, and a uniform $L^\infty$-estimate for the Calabi-Yau Kähler potentials.

Niufa Fang, Sudan Xing, Deping Ye

The aim of this paper is to develop a basic framework of the $L_p$ theory for the geometry of log-concave functions, which can be viewed as a functional "lifting" of the $L_p$ Brunn-Minkowski theory for convex bodies. To fulfill this goal, by combining the $L_p$ Asplund sum of log-concave functions for all $p>1$ and the total mass, we obtain a Prékop

Manar Mazkatli, David Monschein, Johannes Grohmann, Anne Koziolek

Architecture-based Performance Prediction (AbPP) allows evaluation of the performance of systems and to answer what-if questions without measurements for all alternatives. A difficulty when creating models is that Performance Model Parameters (PMPs, such as resource demands, loop iteration numbers and branch probabilities) depend on various influencing facto

Ansh, Jeevesh Kumar, Gaurav Sheoran, Mayank Shrivastava

We report, for CVD-grown monolayer MoS2, the very first results on temporal degradation of material and device performance under electrical stress. Both low and high field regimes of operation are explored at different temperatures, gate bias and stress cycles. During low field operation, current is found to saturate after hundreds of seconds of operation wi

Xinming Liu, Joseph Y. Halpern

While traditional economics assumes that humans are fully rational agents who always maximize their expected utility, in practice, we constantly observe apparently irrational behavior. One explanation is that people have limited computational power, so that they are, quite rationally, making the best decisions they can, given their computational limitations.

Nathanael Arkor, Marcelo Fiore

We develop algebraic models of simple type theories, laying out a framework that extends universal algebra to incorporate both algebraic sorting and variable binding. Examples of simple type theories include the unityped and simply-typed $λ$-calculi, the computational $λ$-calculus, and predicate logic. Simple type theories are given models in presheaf catego

Daniele Calandriello, Michał Dereziński, Michal Valko

Determinantal point processes (DPPs) are a useful probabilistic model for selecting a small diverse subset out of a large collection of items, with applications in summarization, stochastic optimization, active learning and more. Given a kernel function and a subset size $k$, our goal is to sample $k$ out of $n$ items with probability proportional to the det

Carlos Denner dos Santos, Isadora Castro, George Kuk, Silvia Onoyama

Blog management is central to the digitalization of work. However, existing theories tend to focus on environmental influence rather than managerial control of a blogs attractiveness at a microlevel. This study provides an agentive account of the adaptive behaviours exerted by the bloggers through the ways they use contents of their blogs to locate and harne

Feng Zhou, Tao Chen, Baiying Lei

Amid the ongoing COVID-19 pandemic, whether COVID-19 patients with high risks can be recovered or not depends, to a large extent, on how early they will be treated appropriately before irreversible consequences are caused to the patients by the virus. In this research, we reported an explainable, intuitive, and accurate machine learning model based on logist

Saeed Khaki, Dan Nettleton

Neural networks are among the most powerful nonlinear models used to address supervised learning problems. Similar to most machine learning algorithms, neural networks produce point predictions and do not provide any prediction interval which includes an unobserved response value with a specified probability. In this paper, we proposed the $k$-fold predictio

Yalin Liu, Jinfeng Lin, Jane Cleland-Huang

Software traceability establishes associations between diverse software artifacts such as requirements, design, code, and test cases. Due to the non-trivial costs of manually creating and maintaining links, many researchers have proposed automated approaches based on information retrieval techniques. However, many globally distributed software projects produ

Elizabeth Baldwin, Omer Edhan, Ravi Jagadeesan, Paul Klemperer

We show that, with indivisible goods, the existence of competitive equilibrium fundamentally depends on agents' substitution effects, not their income effects. Our Equilibrium Existence Duality allows us to transport results on the existence of competitive equilibrium from settings with transferable utility to settings with income effects. One consequenc

Francesco Tonolini, Pablo G. Moreno, Andreas Damianou, Roderick Murray-Smith

We propose a new probabilistic method for unsupervised recovery of corrupted data. Given a large ensemble of degraded samples, our method recovers accurate posteriors of clean values, allowing the exploration of the manifold of possible reconstructed data and hence characterising the underlying uncertainty. In this setting, direct application of classical va

Volker J. Sorger, Rishi Maiti

Photodetectors are key optoelectronic building blocks performing the essential optical-to-electrical signal conversion, and unlike solar cells, operate at a specific wavelength and at high signal or sensory speeds. Towards achieving high detector performance, device physics, however, places a fundamental limit of the achievable detector sensitivity, such as

Pascal Maillard, Elliot Paquette

We consider a Markovian evolution on point processes, the $Ψ$--process, on the unit interval in which points are added according to a rule that depends only on the spacings of the existing point configuration. Having chosen a spacing, a new point is added uniformly within it. Building on previous work of the authors and of Junge, we show that the empirical d

Hans W. Wilschut

The approximate frequency shift of a radar echo from a meteoroid is derived. The origin of head echos observed during trail formation are discussed by considering schematic models. The echo is either a reflection of the radar signal from thermalized electrons in the meteoroid trail or from the plasma electrons co-moving with the meteoroid itself. It is shown

Jörn Tillmanns, Jiska Classen, Felix Rohrbach, Matthias Hollick

Bluetooth chips must include a Random Number Generator (RNG). This RNG is used internally within cryptographic primitives but also exposed to the operating system for chip-external applications. In general, it is a black box with security-critical authentication and encryption mechanisms depending on it. In this paper, we evaluate the quality of RNGs in vari

A. Khukhro

We give a new characterisation of virtually free groups using graph minors. Namely, we prove that a finitely generated, infinite group is virtually free if and only if for any finite generating set, the corresponding Cayley graph is minor excluded. This answers a question of Ostrovskii and Rosenthal. The proof relies on showing that a finitely generated grou

Jiaoyan Chen, Freddy Lecue, Yuxia Geng, Jeff Z. Pan

Zero-shot learning (ZSL) is a popular research problem that aims at predicting for those classes that have never appeared in the training stage by utilizing the inter-class relationship with some side information. In this study, we propose to model the compositional and expressive semantics of class labels by an OWL (Web Ontology Language) ontology, and furt

Annalisa Fierro, Antonio Coniglio, Marco Zannetti

The standard phase-ordering process is obtained by quenching a system, like the Ising model, to below the critical point. This is usually done with periodic boundary conditions to insure ergodicity breaking in the low temperature phase. With this arrangement the infinite system is known to remain permanently out of equilibrium, i.e. there exists a well defin

Chris H. Lee, Edmund Hodges-Kluck, Elena Gallo

Many ultra-diffuse galaxies (UDGs) have been discovered in the Coma cluster, and there is evidence that some, notably Dragonfly 44, have Milky Way-like dynamical masses despite dwarf-like stellar masses. We used X-ray, UV, and optical data to investigate the star formation and nuclear activity in the Coma UDGs, and we obtained deep UV and X-ray data (Swift a

Lenin S. Shagolsem

The behavior of energy polydisperse $2d$ Lennard-Jones fluid (in thin-film geometry) is studied subjected to linear flow field using molecular dynamics simulations. By considering neutral and selective substrates we systematically explore the effect of flow field on particle ordering as well as response of the system. It is shown that particle density profil

Connor Jackman

Consider the dynamics of two point masses on a surface of constant curvature subject to an attractive force analogue of Newton's inverse square law. When the distance between the bodies is sufficiently small, the reduced equations of motion may be seen as a perturbation of an integrable system. We define suitable action-angle coordinates to average these

Hsin-Hao Su, Nicole Wein

We study the problem of distributed task allocation in multi-agent systems. Suppose there is a collection of agents, a collection of tasks, and a demand vector, which specifies the number of agents required to perform each task. The goal of the agents is to cooperatively allocate themselves to the tasks to satisfy the demand vector. We study the dynamic vers

Daniel Berjón, Pablo Carballeira, Julián Cabrera, Carlos Carmona

FVV Live is a novel real-time, low-latency, end-to-end free viewpoint system including capture, transmission, synthesis on an edge server and visualization and control on a mobile terminal. The system has been specially designed for low-cost and real-time operation, only using off-the-shelf components.

Andrew K. Harter, Naomichi Hatano

Non-Hermitian Hamiltonians provide a simple picture for analyzing systems with natural or induced gain and loss; however, in general, such Hamiltonians feature complex energies and a corresponding non-orthonormal eigenbasis. Provided that the Hamiltonian has $\mathcal{PT}$ symmetry, it is possible to find a regime in which the eigenspectrum is completely rea

Alexander V. Oleynichenko, Leonid V. Skripnikov, Andrei Zaitsevskii, Ephraim Eliav

The four-component relativistic Fock space coupled cluster method is used to describe the magnetic hyperfine interaction in low-lying electronic states of the KCs molecule. Both diagonal and off-diagonal matrix elements as functions of the internuclear separation $R$ are calculated within the finite-field scheme. The resulting matrix elements exhibit very we

Melvyn Tyloo, Philippe Jacquod

Many recent works in control of electric power systems have investigated their synchronization through global performance metrics under external disturbances. The approach is motivated by fundamental changes in the operation of power grids, in particular by the substitution of conventional power plants with new renewable sources of electrical energy. This su

Patrick Meisner

We consider the expected value of $\mbox{Tr}(Θ_C^n)$ where $C$ runs over a thin family of $r$-cyclic covers of $\mathbb{P}^1_{\mathbb{F}_q}$ for any $r$. We obtain many lower order terms dependent on the divisors of $r$. We use these results to calculate the one-level density of the family and hypothesize a refined one-level density result.

Athanasios Sourmelidis, Teerapat Srichan, Jörn Steuding

We prove explicit formulae for $α$-points of $L$-functions from the Selberg class. Next we extend a theorem of Littlewood on the vertical distribution of zeros of the Riemann zeta-function $ζ(s)$ to the case of $α$-points of the aforementioned $L$-functions. This result implies the uniform distribution of subsequences of $α$-points and from this a discrete u

I. V. Pylyuk, O. A. Dobush

The paper is devoted to the development of a microscopic description of the critical behavior of a cell fluid model with allowance for the contributions from collective variables with nonzero values of the wave vector. The mathematical description is performed in the supercritical temperature range ($T>T_c$) in the case of a modified Morse potential with add

Zengjing Chen, Larry G. Epstein

We prove a central limit theorem for a sequence of random variables whose means are ambiguous and vary in an unstructured way. Their joint distribution is described by a set of measures. The limit is (not the normal distribution and is) defined by a backward stochastic differential equation that can be interpreted as modeling an ambiguous continuous-time ran

Ryo Matsumoto, Zhufeng Hou, Shintaro Adachi, Sayaka Yamamoto

Layered transition-metal chalcogenides (Zr,Hf)GeTe$_{4}$ were screened out from database of Atomwork as a candidate for pressure-induced superconductivity due to their narrow band gap and high density of state near the Fermi level. The (Zr,Hf)GeTe$_{4}$ samples were synthesized in single crystal and then the compositional ratio, crystal structures, and valen

Shivangi Shree, Ioannis Paradisanos, Xavier Marie, Cedric Robert

In this technical review we give an introduction to optical spectroscopy for layered materials as a powerful, non-invasive tool to access details of the electronic band structure and crystal quality. Potential applications in photonics and optoelectronics are based on our understanding of the light-matter interaction on an atomic monolayer scale. Here atomic

Javad Mashreghi, Pierre-Olivier Parisé, Thomas Ransford

We construct a Hilbert holomorphic function space $H$ on the unit disk such that the polynomials are dense in $H$, but the odd polynomials are not dense in the odd functions in $H$. As a consequence, there exists a function $f$ in $H$ that lies outside the closed linear span of its Taylor partial sums $s_n(f)$, so it cannot be approximated by any triangular

Tomasz Gogacz, Víctor Gutiérrez-Basulto, Albert Gutowski, Yazmín Ibáñez-García

We study the problem of finite entailment of ontology-mediated queries. Going beyond local queries, we allow transitive closure over roles. We focus on ontologies formulated in the description logics ALCOI and ALCOQ, extended with transitive closure. For both logics, we show 2EXPTIME upper bounds for finite entailment of unions of conjunctive queries with tr

Tuan Tran, Jory Denny, Chinwe Ekenna

Many state-of-art robotics applications require fast and efficient motion planning algorithms. Existing motion planning methods become less effective as the dimensionality of the robot and its workspace increases, especially the computational cost of collision detection routines. In this work, we present a framework to address the cost of expensive primitive

Mark Christopher Ballandies, Evangelos Pournaras

Building trustworthy knowledge graphs for cyber-physical social systems (CPSS) is a challenge. In particular, current approaches relying on human experts have limited scalability, while automated approaches are often not accountable to users resulting in knowledge graphs of questionable quality. This paper introduces a novel pervasive knowledge graph builder

Zhi-Hui Guo

We review the recent developments on the light-flavor resonances in the $U(3)$ chiral effective filed theory. The spectral function sum rules and the semilocal duality in the scattering, which will be focus of this note, can provide us interesting and useful theoretical objects to bridge the hadron resonances in the intermediate energy region and the QCD beh

Salman Khalid, Waqas bin Abbas, Farhan Khalid, Michele Zorzi

A hybrid architecture for millimeter wave (mmW) massive MIMO systems is considered practically implementable due to low power consumption and high energy efficiency. However, due to the limited number of RF chains, user selection becomes necessary for such architecture. Traditional user selection algorithms suffer from high computational complexity and, ther

Siegfried Van Hille

We prove that the function $P_α(x) = \exp(1-x^{-α})$ with $α> 0$, is $1/α$-mild. We apply this result to obtain a uniform $1/α$-mild parametrization of the family of curves $\{xy = ε^2 \mid (x,y) \in (0,1)^2\}$ for $ε\in (0,1)$, which does not have a uniform $0$-mild parametrization by work of Yomdin. More generally we can parametrize families of power-suban

Beatrice Perez, Sara R. Machado, Jerone T. A. Andrews, Nicolas Kourtellis

Donations to charity-based crowdfunding environments have been on the rise in the last few years. Unsurprisingly, deception and fraud in such platforms have also increased, but have not been thoroughly studied to understand what characteristics can expose such behavior and allow its automatic detection and blocking. Indeed, crowdfunding platforms are the onl

Rie Johnson, Tong Zhang

This paper presents a framework of successive functional gradient optimization for training nonconvex models such as neural networks, where training is driven by mirror descent in a function space. We provide a theoretical analysis and empirical study of the training method derived from this framework. It is shown that the method leads to better performance

Antonino Del Popolo, Maksym Deliyergiyev, Morgan Le Delliou, Laura Tolos

We discuss the formation of dark compact objects in a dark matter environment in view of the possible mass dependence of pulsars on the distribution of dark matter in the Galaxy. Our results indicate that the pulsar masses should decrease going towards the center of the Milky Way due to dark matter capture, thus becoming a probe for the existence and nature

Mika Sarvilahti, Audun Skaugen, Lasse Laurson

We study a one-dimensional model of a dislocation pileup driven by an external stress and interacting with random quenched disorder, focusing on predictability of the plastic deformation process. Upon quasistatically ramping up the externally applied stress from zero the system responds by exhibiting an irregular stress--strain curve consisting of a sequence

Eliane M. De Bortoli Fávero, Dalcimar Casanova, Andrey Ricardo Pimentel

Estimating effort based on requirement texts presents many challenges, especially in obtaining viable features to infer effort. Aiming to explore a more effective technique for representing textual requirements to infer effort estimates by analogy, this paper proposes to evaluate the effectiveness of pre-trained embeddings models. For this, two embeddings ap

Boyun Li, Yuanbiao Gou, Shuhang Gu, Jerry Zitao Liu

In this paper, we study two challenging and less-touched problems in single image dehazing, namely, how to make deep learning achieve image dehazing without training on the ground-truth clean image (unsupervised) and a image collection (untrained). An unsupervised neural network will avoid the intensive labor collection of hazy-clean image pairs, and an untr

Cristina Momblona, Hiroyuki Kanda, Albertus Adrian Sutanto, Mounir Mensi

The most studied perovskite-based solar cells reported up to date contain the toxic lead in its composition. Photovoltaic research and development towards non-toxic, lead-free perovskite solar cells are critical to finding alternatives to reduce human health concerns associated with them. Bismuth-based perovskite variants, especially in the form of methylamm

Bjorn K. Berntson, Rob Klabbers, Edwin Langmann

We consider the half-wave maps (HWM) equation which provides a continuum description of the classical Haldane-Shastry spin chain on the real line. We present exact multi-soliton solutions of this equation. Our solutions describe solitary spin excitations that can move with different velocities and interact in a non-trivial way. We make an ansatz for the solu

Yoel Zeldes, Dan Padnos, Or Sharir, Barak Peleg

We introduce a simple and efficient method, called Auxiliary Tuning, for adapting a pre-trained Language Model to a novel task; we demonstrate this approach on the task of conditional text generation. Our approach supplements the original pre-trained model with an auxiliary model that shifts the output distribution according to the target task. The auxiliary

Julian Kappler, Ronojoy Adhikari

The trajectories of diffusion processes are continuous but non-differentiable, and each occurs with vanishing probability. This introduces a gap between theory, where path probabilities are used in many contexts, and experiment, where only events with non-zero probability are measurable. Here we bridge this gap by considering the probability of diffusive tra

Márton Borbényi, Péter Csikvári

For a graph $G$ on $v(G)$ vertices let $m_k(G)$ denote the number of matchings of size $k$, and consider the partition function $M_{G}(λ)=\sum_{k=0}^nm_k(G)λ^k$. In this paper we show that if $G$ is a $d$--regular graph and $0<λ<(4d)^{-2}$, then $$\frac{1}{v(G)}\ln M_G(λ)>\frac{1}{v(K_{d+1})}\ln M_{K_{d+1}}(λ).$$ The same inequality holds true if $d=3$ and $

Duc-Viet Vu

We compare the notion of relative non-pluripolar products and that of density currents on compact Kahler manifolds.

Isha Agarwal, Paul Braverman, Patrick Chen, William Du

There are $n$ bags with coins that look the same. Each bag has an infinite number of coins and all coins in the same bag weigh the same amount. Coins in different bags weigh 1, 2, 3, and so on to $n$ grams exactly. There is a unique label from the set 1 through $n$ attached to each bag that is supposed to correspond to the weight of the coins in that bag. Th

Cunjun Yu, Zhongang Cai, Daxuan Ren, Haiyu Zhao

Ever since the prevalent use of the LiDARs in autonomous driving, tremendous improvements have been made to the learning on the point clouds. However, recent progress largely focuses on detecting objects in a single 360-degree sweep, without extensively exploring the temporal information. In this report, we describe a simple way to pass such information in t

Anton V. Hlushchenko, Vitalii I. Shcherbinin, Denis V. Novitsky, Vladimir R. Tuz

A rigorous analytical approach is applied to solve the eigenvalue problem for a pair of circular dielectric cylinders with complex permittivity. This approach relies on field expansion in terms of two sets of orthogonal azimuthal modes, which are coupled due to finite distance between the cylinders. We investigate the ability of a gain-dielectric cylinder op

Matej Daniel, Kristina Eleršič Filipič, Eva Filová, Jaroslav Fojt

Titanium surface treated with titanium oxide nanotubes was used in many studies to quantify the effect of surface topography on cell fate. However, the predicted optimal diameter of nanotubes considerably differs among studies. We propose a model that explain cell adhesion to nanostructured surface by considering deformation energy of cell protrusions into t

Xi Zhang, Qiangqiang Gu, Haigen Sun, Tianchuang Luo

Unconventional quasiparticle excitations in condensed matter systems have become one of the most important research frontiers. Beyond two- and fourfold degenerate Weyl and Dirac fermions, three-, six- and eightfold symmetry protected degeneracies have been predicted however remain challenging to realize in solid state materials. Here, charge density wave com

Sébastien Loranger, Philip St. J. Russell, David Novoa

The possibility of performing time-resolved spectroscopic studies in the molecular fingerprinting region or extending the cut-off wavelength of high-harmonic generation has recently boosted the development of efficient mid-infrared ultrafast lasers. In particular, fibre lasers based on active media such as thulium or holmium are a very active area of researc

Albert M. Park, Zhen Chen, Xiyue S. Zhang, Lijun Zhu

Magnetic skyrmions hold promise for spintronic devices. To explore the dynamical properties of skyrmions in devices, a nanoscale method to image spin textures in response to a stimulus is essential. Here, we apply a technique for operando electrical current pulsing of chiral magnetic devices in a Lorentz transmission electron microscope. In ferromagnetic mul

Pierre Suret, Alexey Tikan, Félicien Bonnefoy, François Copie

Soliton gases represent large random soliton ensembles in physical systems that display integrable dynamics at the leading order. Despite significant theoretical developments and observational evidence of ubiquity of soliton gases in fluids and optical media their controlled experimental realization has been missing. We report the first controlled synthesis

Taro Langner, Robin Strand, Håkan Ahlström, Joel Kullberg

The UK Biobank Imaging Study has acquired medical scans of more than 40,000 volunteer participants. The resulting wealth of anatomical information has been made available for research, together with extensive metadata including measurements of liver fat. These values play an important role in metabolic disease, but are only available for a minority of imaged

Satoshi Tanioka, Kunihiko Hasegawa, Yoichi Aso

The detection of gravitational-waves provides us with a deep insight into the universe. In order to increase the number of detectable gravitational-wave sources, several future gravitational-wave detectors will operate with cryogenic mirrors. Recent studies, however, showed residual gas molecules inside the vacuum chamber adhere to the cryogenic mirror surfa

Phoebus Rosakis, Timothy J. Healey, Ugur Alyanak

We propose a one-dimensional, nonconvex elastic constitutive model with higher gradients that can predict spontaneous fracture at a critical load via a bifurcation analysis. It overcomes the problem of discontinuous deformations without additional field variables, such as damage or phase-field variables, and without a priori specified surface energy. Our mai

Christine Markarian, Abdul-Nasser Kassar, Manal Yunis

Facility Location problems ask to place facilities in a way that optimizes a given objective function so as to provide a service to all clients. These are one of the most well-studied optimization problems spanning many research areas such as operations research, computer science, and management science. Traditionally, these problems are solved with the assu

Silvan Käser, Debasish Koner, Anders S. Christensen, O. Anatole von Lilienfeld

Machine Learning (ML) has become a promising tool for improving the quality of atomistic simulations. Using formaldehyde as a benchmark system for intramolecular interactions, a comparative assessment of ML models based on state-of-the-art variants of deep neural networks (NN), reproducing kernel Hilbert space (RKHS+F), and kernel ridge regression (KRR) is p

Rahul Bandyopadhyay, Ramkrishna Das, Soumen Mondal, Samrat Ghosh

We present results of our study of two planetary nebulae (PNe), PB1 and PC 19. We use the optical spectra of these two PNe observed at 2 m Himalayan Chandra Telescope and also archival and literature data for the study. We use the morphokinematic code SHAPE to construct 3D morphologies of the PNe and the photoionization code CLOUDY to model the observed spec

Hongwei Sun, Qiang Wu

Distributed machine learning systems have been receiving increasing attentions for their efficiency to process large scale data. Many distributed frameworks have been proposed for different machine learning tasks. In this paper, we study the distributed kernel regression via the divide and conquer approach. This approach has been proved asymptotically minima

R. Robinson, Q. Dou, D. C. Castro, K. Kamnitsas

We investigate the use of image-and-spatial transformer networks (ISTNs) to tackle domain shift in multi-site medical imaging data. Commonly, domain adaptation (DA) is performed with little regard for explainability of the inter-domain transformation and is often conducted at the feature-level in the latent space. We employ ISTNs for DA at the image-level wh

Aswathi K. Sivan, Alejandro Galan-Gonzalez, Lorenzo Di Mario, Nicolas Tappy

The controlled modification of the electronic properties of ZnO nanorods via transition metal doping is reported. A series of ZnO nanorods were synthesized by chemical bath growth with varying Co content from 0 to 20 atomic % in the growth solution. Optoelectronic behavior was probed using cathodoluminescence, time-resolved luminescence, transient absorbance

Chih-Teng Ling, Tetsuya Hashimoto, Tomotsugu Goto, Ting-Yi Lu

Observationally, it has been reported that the densest stellar system in the Universe does not exceed a maximum stellar surface density, $Σ^{\max}_{*}$ = $3\times10^5$M$_{\odot}$pc$^{-2}$, throughout a wide physical scale ranging from star cluster to galaxy. This suggests there exists a fundamental physics which regulates the star formation and stellar densi