March 2020 arXiv papers — page 96

A. Sanna, L. Burderi, K. C. Gendreau, T. Di Salvo

We report on the phase-coherent timing analysis of the accreting millisecond X-ray pulsar IGR J17591-2342, using Neutron Star Interior Composition Explorer (NICER) data taken during the outburst of the source between 2018 August 15 and 2018 October 17. We obtain an updated orbital solution of the binary system. We investigate the evolution of the neutron sta

Slawomir Kolodziej, Ngoc Cuong Nguyen

We prove the existence of a continuous quasi-plurisubharmonic solution to the Monge-Ampère equation on a compact Hermitian manifold for a very general measre on the right hand side. We admit measures dominated by capacity in a certain manner, in particular, moderate measures studied by Dinh-Nguyen-Sibony. As a consequence, we give a characterization of measu

Tyler R. Harvey, Jan-Wilke Henke, Ofer Kfir, Hugo Lorenço-Martins

Circular dichroism spectroscopy is an essential technique for understanding molecular structure and magnetic materials, but spatial resolution is limited by the wavelength of light, and sensitivity sufficient for single-molecule spectroscopy is challenging. We demonstrate that electrons can efficiently measure the interaction between circularly polarized lig

Yuri I. Fujii, Masahiro Ogihara

Several mechanisms have been proposed to explain the formation process of satellite systems, and relatively large moons are thought to be born in circumplanetary disks. Making a single-moon system is known to be more difficult than multiple-moon or moonless systems. We aim to find a way to form a system with a single large moon, such as Titan around Saturn.

Songkai Xue, Mikhail Yurochkin, Yuekai Sun

We consider the task of auditing ML models for individual bias/unfairness. We formalize the task in an optimization problem and develop a suite of inferential tools for the optimal value. Our tools permit us to obtain asymptotic confidence intervals and hypothesis tests that cover the target/control the Type I error rate exactly. To demonstrate the utility o

Leanne Friedrich, Matthew Begley

3D printing methods which enable control over the position and orientation of embedded particles have promising applications in cell patterning and composite scaffolds. Extrusion-based additive manufacturing techniques such as fused deposition modeling and direct ink writing can experience particle patterning defects at corners which could hinder cell surviv

Kazuki Maeda, Adam D Maxwell

Cloud cavitation causes nontrivial energy concentration and acoustic shielding in liquid, and its control is a long-standing challenge due to complex dynamics of bubble clouds. We present a new framework to study closed-loop control of cavitation through acoustic feedback. While previous approaches used empirical thresholding, we employ model-based state est

Vuong M. Ngo, M-Tahar Kechadi

Nowadays, the agricultural data can be generated through various sources, such as: Internet of Thing (IoT), sensors, satellites, weather stations, robots, farm equipment, agricultural laboratories, farmers, government agencies and agribusinesses. The analysis of this big data enables farmers, companies and agronomists to extract high business and scientific

V. M. Prokip

Polynomial $n\times n$ matrices $A(λ)$ and $B(λ)$ over a field $\mathbb F $ are called semi-scalar equivalent if there exist a nonsingular $n\times n$ matrix $P$ over the field $\mathbb F $ and an invertible $n\times n$ matrix $Q(λ)$ over the ring ${\mathbb F}[λ]$ such that $A(λ)=P B(λ)Q(λ).$ The semi-scalar equivalence of matrices over a field $ {\mathbb F}

Irshad A. Meer, Mustafa Ozger, Cicek Cavdar

Localization plays a key role for safe operation of UAVs enabling beyond visual line of sight applications. Compared to GPS based localization, cellular networks can reduce the positioning error and cost since cellular connectivity is becoming a prominent solution as a communication system for UAVs. As a first step towards localization, UAV needs to receive

Xin Liu, Yongbin Sun, Ziwei Liu, Dahua Lin

Fashion recommendation systems are highly desired by customers to find visually-collocated fashion items, such as clothes, shoes, bags, etc. While existing methods demonstrate promising results, they remain lacking in flexibility and diversity, e.g. assuming a fixed number of items or favoring safe but boring recommendations. In this paper, we propose a nove

Rukayat Ayomide Erinfolami, Aravind Prakash

Complexities that arise from implementation of object-oriented concepts in C++ such as virtual dispatch and dynamic type casting have attracted the attention of attackers and defenders alike. Binary-level defenses are dependent on full and precise recovery of class inheritance tree of a given program. While current solutions focus on recovering single and mu

Ophir Gozes, Maayan Frid-Adar, Hayit Greenspan, Patrick D. Browning

Purpose: Develop AI-based automated CT image analysis tools for detection, quantification, and tracking of Coronavirus; demonstrate they can differentiate coronavirus patients from non-patients. Materials and Methods: Multiple international datasets, including from Chinese disease-infected areas were included. We present a system that utilizes robust 2D and

Ali Dabouei, Sobhan Soleymani, Fariborz Taherkhani, Nasser M. Nasrabadi

This paper presents a supervised mixing augmentation method termed SuperMix, which exploits the salient regions within input images to construct mixed training samples. SuperMix is designed to obtain mixed images rich in visual features and complying with realistic image priors. To enhance the efficiency of the algorithm, we develop a variant of the Newton i

Michael Arbel, Liang Zhou, Arthur Gretton

We introduce the Generalized Energy Based Model (GEBM) for generative modelling. These models combine two trained components: a base distribution (generally an implicit model), which can learn the support of data with low intrinsic dimension in a high dimensional space; and an energy function, to refine the probability mass on the learned support. Both the e

E. Tardiff, X. Fan, G. Gabrielse, D. Grzonka

High-accuracy spectroscopic comparisons of trapped antihydrogen atoms ($\overline{\text{H}}$) and hydrogen atoms ($\text{H}$) promise to stringently test the fundamental CPT symmetry invariance of the standard model of particle physics. ATRAP's nested Penning-Ioffe trap was developed for such studies. The first of its unique features is that its magnetic Iof

J. William Hoffman, Fang-Ting Tu

We consider algebraic transformations of hypergeometric functions from a geometric point of view. Hypergeometric functions are shown to arise from the deRham realization of a hypergeometric motive. The $\ell$-adic realization of the motive gives rise to hypergeometric characters sums over finite fields. This helps to unify and explain some recent results abo

Luana Ruiz, Luiz F. O. Chamon, Alejandro Ribeiro

Graphons are infinite-dimensional objects that represent the limit of convergent sequences of graphs as their number of nodes goes to infinity. This paper derives a theory of graphon signal processing centered on the notions of graphon Fourier transform and linear shift invariant graphon filters, the graphon counterparts of the graph Fourier transform and gr

Chenglong Li, Emmeric Tanghe, David Plets, Pieter Suanet

Radio frequency identification (RFID) technology brings tremendous advancement in Internet-of-Things, especially in supply chain and smart inventory management. Phase-based passive ultra high frequency RFID tag localization has attracted great interest, due to its insensitivity to the propagation environment and tagged object properties compared with the sig

Frank Freimuth, Stefan Blügel, Yuriy Mokrousov

We investigate the influence of magnons on the temperature-dependence and the anisotropy of the spin-orbit torque (SOT). For this purpose we use 3rd order perturbation theory in the framework of the Keldysh formalism in order to derive suitable equations to compute the magnonic SOT. We find several contributions to the magnonic SOT, which depend differently

P. Stemmermann, K. Garbev, B. Gasharova, G. Beuchle

Celitement is a new type of cement that is based on hydraulic calcium-hydrosilicate (hCHS) that possesses a potential for minimizing the ratio C/S from above 3 in OPC down to 1, which significantly reduces the amount of CO$_2$ released during processing. The reaction kinetics of hCHS differs from that of classical clinker phases due to the presence of highly

Dave Dice, Alex Kogan

Classic test-and-test (TS) mutual exclusion locks are simple, and enjoy high performance and low latency of ownership transfer under light or no contention. However, they do not scale gracefully under high contention and do not provide any admission order guarantees. Such concerns led to the development of scalable queue-based locks, such as a recent Compact

Amitabh Basu, Michele Conforti, Marco Di Summa, Hongyi Jiang

We investigate the theoretical complexity of branch-and-bound (BB) and cutting plane (CP) algorithms for mixed-integer optimization. In particular, we study the relative efficiency of BB and CP, when both are based on the same family of disjunctions. We extend a result of Dash to the nonlinear setting which shows that for convex 0/1 problems, CP does at leas

Amitabh Basu, Michele Conforti, Marco Di Summa, Hongyi Jiang

We provide a polynomial time cutting plane algorithm based on split cuts to solve integer programs in the plane. We also prove that the split closure of a polyhedron in the plane has polynomial size.

Toru Masuda, Hiroaki Matsunaga

The perturbative path-integral gives a morphism of the (quantum) $A_{\infty }$ structure intrinsic to each quantum field theory, which we show explicitly on the basis of the homological perturbation. As is known, in the BV formalism, any effective action also solves the BV master equation, which implies that the path-integral can be understood as a morphism

Colin D. Froggatt, Holger B. Nielsen

Our earlier put forward model of dark matter, consisting of cm-size pearls with ordinary matter inside under high pressure and with a mass of order $1.4 *10^8$ kg, is used to explain the mysterious 3.5 keV X-ray line from the galactic center and various galaxies and galaxy clusters. The pearls are bubbles of a new type of vacuum and thus surrounded by a surf

Stephanie Milani, Nicholay Topin, Brandon Houghton, William H. Guss

To facilitate research in the direction of sample efficient reinforcement learning, we held the MineRL Competition on Sample Efficient Reinforcement Learning Using Human Priors at the Thirty-third Conference on Neural Information Processing Systems (NeurIPS 2019). The primary goal of this competition was to promote the development of algorithms that use huma

Benjamin Harrop-Griffiths, Rowan Killip, Monica Visan

We prove that the cubic nonlinear Schr\"odinger equation (both focusing and defocusing) is globally well-posed in $H^s(\mathbb R)$ for any regularity $s>-\frac12$. Well-posedness has long been known for $s\geq 0$, see [55], but not previously for any $s<0$. The scaling-critical value $s=-\frac12$ is necessarily excluded here, since instantaneous norm inflati

Tabassum S Tanvir, James E Dale

In a series of papers we investigate the effect of collisions between turbulent molecular clouds on their structure, evolution and star formation activity. In this paper we look into the role of the clouds&#39; initial virial ratios. Three different scenarios were examined: both clouds initially bound, one cloud bound and one unbound, and both clouds initial

G. S. Ramos, M. V. T. Machado

In this work we analyse the entanglement entropy in deep inelastic scattering off protons and nuclei. It is computed based on the formalism where the partonic state at small-x is maximally entangled with proton being constituted by large number of microstates occuring with equal probabilities. We consider analytical expressions for the number of gluons, N_{g

Trevor Knuth, Lindsay Glesener

Solar flares are known to release a large amount of energy into accelerating electrons. Studying small timescale ($\leq$ 2s) fluctuations in nonthermal X-ray flux offers the opportunity to probe the nature of those acceleration mechanisms. By comparing the durations, differences in timing between energy bands, and the periodicity of these spikes against the

S. Goldstein, J. L. Lebowitz, E. R. Speer

We describe the translation invariant stationary states of the one dimensional discrete-time facilitated totally asymmetric simple exclusion process (F-TASEP). In this system a particle at site $j$ in $Z$ jumps, at integer times, to site $j+1$, provided site $j-1$ is occupied and site $j+1$ is empty. This defines a deterministic noninvertible dynamical evolu

Daniel Otero Baguer, Johannes Leuschner, Maximilian Schmidt

In this work, we investigate the application of deep learning methods for computed tomography in the context of having a low-data regime. As motivation, we review some of the existing approaches and obtain quantitative results after training them with different amounts of data. We find that the learned primal-dual has an outstanding performance in terms of r

Yong-Geun Oh, Hiro Lee Tanaka

We construct an unwrapped Floer theory for bundles of Liouville sectors. In particular, we construct a compatible collection of unwrapped Fukaya categories of fibers of a Liouville bundle, and prove that the two natural constructions of continuation maps in this setting behave compatibly. These constructions are exploited in [OT19] to construct homotopically

Giuseppe Floridia

Let us consider a nonlinear degenerate reaction-diffusion equation with application to climate science. After proving that the solution remains nonnegative at any time, when the initial state is nonnegative, we prove the approximate controllability between nonnegative states at any time via multiplicative controls, that is, using as control the reaction coef

Sanmit Narvekar, Bei Peng, Matteo Leonetti, Jivko Sinapov

Reinforcement learning (RL) is a popular paradigm for addressing sequential decision tasks in which the agent has only limited environmental feedback. Despite many advances over the past three decades, learning in many domains still requires a large amount of interaction with the environment, which can be prohibitively expensive in realistic scenarios. To ad

Gheorghe Craciun, Maya Mincheva, Casian Pantea, Polly Y. Yu

Delay differential equations are used as a model when the effect of past states has to be taken into account. In this work we consider delay models of chemical reaction networks with mass action kinetics. We obtain a sufficient condition for absolute delay stability of equilibrium concentrations, i.e., local asymptotic stability independent of the delay para

Eoghan McDowell

This paper proves an identity between flagged Schur polynomials, giving a duality between row flags and column flags. This identity generalises both the binomial determinant duality theorem due to Gessel and Viennot and the symmetric function duality theorem due to Aitken. As corollaries we obtain the lifts of the binomial determinant duality theorem to $q$-

Zexiang Liu, Liren Yang, Necmiye Ozay

In this paper, we first propose a method that can efficiently compute the maximal robust controlled invariant set for discrete-time linear systems with pure delay in input. The key to this method is to construct an auxiliary linear system (without delay) with the same state-space dimension of the original system in consideration and to relate the maximal inv

Andrea Brunello, Guido Sciavicco, Ionel Eduard Stan

Decision trees are simple, yet powerful, classification models used to classify categorical and numerical data, and, despite their simplicity, they are commonly used in operations research and management, as well as in knowledge mining. From a logical point of view, a decision tree can be seen as a structured set of logical rules written in propositional log

Gonzalo Fernandez-Torija Daza, Martin Lopez-Corredoira

Feng & Gallo (2011) developed a numerical method of deriving rotation curves from the density distribution and, in particular, the inverse problem while considering just a self-gravitating disc and the thin disc approximation. Our first aim here is to reproduce the same analysis and expand it with various ideas and examples. The main obstacles to building th

Shan Lin, Fangbo Qin, Yangming Li, Randall A. Bly

Intelligent vision is appealing in computer-assisted and robotic surgeries. Vision-based analysis with deep learning usually requires large labeled datasets, but manual data labeling is expensive and time-consuming in medical problems. We investigate a novel cross-domain strategy to reduce the need for manual data labeling by proposing an image-to-image tran

Kristen Morse, Neha Das, Yixin Lin, Austin S. Wang

Being able to quickly adapt to changes in dynamics is paramount in model-based control for object manipulation tasks. In order to influence fast adaptation of the inverse dynamics model's parameters, data efficiency is crucial. Given observed data, a key element to how an optimizer updates model parameters is the loss function. In this work, we propose to ap

Mohammadhadi Shateri, Francisco Messina, Pablo Piantanida, Fabrice Labeau

Smart meters (SMs) play a pivotal rule in the smart grid by being able to report the electricity usage of consumers to the utility provider (UP) almost in real-time. However, this could leak sensitive information about the consumers to the UP or a third-party. Recent works have leveraged the availability of energy storage devices, e.g., a rechargeable batter

William Craig, Peter A. Linnell

We prove that a uniform pro-p group with no nonabelian free subgroups has a normal series with torsion-free abelian factors. We discuss this in relation to unique product groups. We also consider generalizations of Hantzsche-Wendt groups.

Keith Hawkins, Madeline Lucey, Jason Curtis

Recently, a new cylindrical-shaped stream of stars up to 700 pc long was discovered hiding in the Galactic disk using kinematic data enabled by the Gaia mission. This stream of stars, dubbed Pisces-Eridanus (Psc-Eri), was initially thought to be as old as 1 Gyr, yet its stars shared a rotation period distribution consistent with a population that was 120-Myr

Arvind Shrivats, Dena Firoozi, Sebastian Jaimungal

Solar Renewable Energy Certificate (SREC) markets are a market-based system that incentivizes solar energy generation. A regulatory body imposes a lower bound on the amount of energy each regulated firm must generate via solar means, providing them with a tradeable certificate for each MWh generated. Firms seek to navigate the market optimally by modulating

Thomas Hambye, Matteo Lucca, Laurent Vanderheyden

If, during the early Universe epoch, the dark matter particle thermalizes in a hidden sector which does not thermalize with the Standard Model thermal bath, its relativistic thermal decoupling can easily lead to the observed relic density, even if the dark matter particle mass is many orders of magnitude heavier than the usual $\sim$ eV hot relic mass scale.

Eleonora Di Valentino, Alessandro Melchiorri, Joseph Silk

We show that a combined analysis of CMB anisotropy power spectra obtained by the Planck satellite and luminosity distance data simultaneously excludes a flat universe and a cosmological constant at $99 \%$ CL. These results hold separately when combining Planck with three different datasets: the two determinations of the Hubble constant from Riess et al. 201

Justin S. Smith, Benjamin Nebgen, Nithin Mathew, Jie Chen

Accuracy of molecular dynamics simulations depends crucially on the interatomic potential used to generate forces. The gold standard would be first-principles quantum mechanics (QM) calculations, but these become prohibitively expensive at large simulation scales. Machine learning (ML) based potentials aim for faithful emulation of QM at drastically reduced

Tamer Tolba, Dieter Grzonka, Thomas Sefzick, James Ritman

In this work we study the performance of silicon photomultiplier (SiPM) light sensors after exposure to the JULIC cyclotron proton beam, of energy $\sim$ 39 MeV, relative to their performance before exposure. The SiPM devices used in this study show a significant change in their behavior and downward shift of their breakdown voltage by as much as $\sim$ 0.4$

Antoine C. Petit, Erik A. Petigura, Melvyn B. Davies, Anders Johansen

K2-19 hosts a planetary system composed of two outer planets, b and c, with size of $7.0\pm 0.2~R_\oplus$ and $4.1\pm0.2~R_\oplus$ , and an inner planet, d, with a radius of $1.11\pm 0.05 R_\oplus$. A recent analysis of Transit-Timing Variations (TTVs) suggested b and c are close to but not in 3:2 mean motion resonance (MMR) because the classical resonant an

Sarah Peluse

We show that the number of positive integers $n\leq N$ such that $\mathbb{Z}/(n^2+n+1)\mathbb{Z}$ contains a perfect difference set is asymptotically $N/\log{N}$.

P. C. M. Delgado, N. Pinto-Neto

In quantum cosmology, one has to select a specific wave function solution of the quantum state equations under consideration in order to obtain concrete results. The simplest choices have been already explored, in different frameworks, yielding, in many cases, quantum bounces. As there is no consensually established boundary condition proposal in quantum cos

Ruth Gregory, Ian G. Moss, Naritaka Oshita

Static oscillating bounces in Schwarzschild de Sitter spacetime are investigated. The oscillating bounce with many oscillations gives a super-thick bubble wall, for which the total vacuum energy increases while the mass of the black hole decreases due to the conservation of Arnowitt-Deser-Misner (ADM) mass. We show that the transition rate of such an &#34;up

Noga Alon, Kai Zheng

Let $G$ be a Cayley graph of the elementary abelian $2$-group $\mathbb{Z}_2^{n}$ with respect to a set $S$ of size $d$. We prove that for any such $G, S$ and $d$, the maximum degree of any induced subgraph of $G$ on any set of more than half the vertices is at least $\sqrt d$. This is deduced from the recent breakthrough result of Huang who proved the above

Florent Leclercq, Baptiste Faure, Guilhem Lavaux, Benjamin D. Wandelt

Existing cosmological simulation methods lack a high degree of parallelism due to the long-range nature of the gravitational force, which limits the size of simulations that can be run at high resolution. To solve this problem, we propose a new, perfectly parallel approach to simulate cosmic structure formation, which is based on the spatial COmoving Lagrang

Saad Qadeer, Boyce E. Griffith

High-order numerical methods for solving elliptic equations over arbitrary domains typically require specialized machinery, such as high-quality conforming grids for finite elements method, and quadrature rules for boundary integral methods. These tools make it difficult to apply these techniques to higher dimensions. In contrast, fixed Cartesian grid method

S. Fretwell, K. G. Leach, C. Bray, G. B. Kim

We report a high-statistics measurement of the $L/K$ orbital electron capture (EC) ratio in $^7$Be embedded in cryogenic Ta. The thin Ta film formed part of a high-resolution superconducting tunnel junction (STJ) radiation detector that was used to identify the signals from different decay channels. The measured $L/K$ capture ratio of 0.070(7) is significant

R. Connor Lawson, Linda Wills, Panagiotis Tsiotras

Sampling-based planning has become a de facto standard for complex robots given its superior ability to rapidly explore high-dimensional configuration spaces. Most existing optimal sampling-based planning algorithms are sequential in nature and cannot take advantage of wide parallelism available on modern computer hardware. Further, tight synchronization of

Jared Willard, Xiaowei Jia, Shaoming Xu, Michael Steinbach

There is a growing consensus that solutions to complex science and engineering problems require novel methodologies that are able to integrate traditional physics-based modeling approaches with state-of-the-art machine learning (ML) techniques. This paper provides a structured overview of such techniques. Application-centric objective areas for which these a

Juho Salmensuu

In this paper, we study a density version of Waring's problem. We prove that a positive density subset of $k$th-powers forms an asymptotic additive basis of order $O(k^2)$ provided that the relative lower density of the set is greater than $(1 - \mathcal{Z}_k^{-1}/2)^{1/k}$, where $\mathcal{Z}_k$ is certain constant depending on $k$ for which it holds that $

Shengzheng Kang, Hongtao Wu, Yao Li, Xiaolong Yang

This paper presents a new fractional-order normalized Bouc-Wen (BW) (FONBW) model to describe the asymmetric and rate-dependent hysteresis nonlinearity of piezoelectric actuators (PEAs). In view of the fact that the classical BW (CBW) model is only efficient for the symmetric and rate-independent hysteresis description, the FONBW model is devoted to characte

C. Vamsi Krishna, Mengying Wang, Maziar S. Hemati, Mitul Luhar

Particle Image Velocimetry (PIV) systems are often limited in their ability to fully resolve the spatiotemporal fluctuations inherent in turbulent flows due to hardware constraints. In this study, we develop models based on Rapid Distortion Theory (RDT) and Taylor&#39;s Hypothesis (TH) to reconstruct the time evolution of a turbulent flow field in the interm

Andrei Asinowski, Cyril Banderier, Benjamin Hackl

Flip-sort is a natural sorting procedure which raises fascinating combinatorial questions. It finds its roots in the seminal work of Knuth on stack-based sorting algorithms and leads to many links with permutation patterns. We present several structural, enumerative, and algorithmic results on permutations that need few (resp. many) iterations of this proced

Shulin Lyu, Yang Chen

In the hard edge scaling limit of the Jacobi unitary ensemble generated by the weight $x^{\alpha}(1-x)^{\beta},~x\in[0,1],~\alpha,\beta>0$, the probability that all eigenvalues of Hermitian matrices from this ensemble lie in the interval $[t,1]$ is given by the Fredholm determinant of the Bessel kernel. We derive the constant in the asymptotics of this Besse

Nicolò Defenu, Andrea Trombettoni, Dario Zappalà

We show that four-dimensional systems may exhibit a topological phase transition analogous to the well-known Berezinskii-Kosterlitz-Thouless vortex unbinding transition in two-dimensional systems. The realisation of an engineered quantum system, where the predicted phase transition shall occur, is also presented. We study a suitable generalization of the sin

Hooman Davoudiasl

We describe a scenario where the smallness of neutrino masses is related to a global symmetry that is only violated by quantum gravitational effects. The coupling of neutrinos to gauge singlet right-handed fermions is attributed to symmetry preserving gravitational operators suppressed by the Planck mass, in this framework. The proposed scenario leads to axi

Fatih Dinc, Lauren E. Hayward, Agata M. Brańczyk

We study the collective decay rates of multi-dimensional quantum networks in which one-dimensional waveguides form an intersecting hyper-rectangular lattice, with qubits located at the lattice points. We introduce and motivate the \emph{dimensional reduction of poles} (DRoP) conjecture, which identifies all collective decay rates of such networks via a conne

Tumelo Mangena, Sultan Hassan, Mario G. Santos

Upcoming 21cm surveys with the SKA1-LOW telescope will enable imaging of the neutral hydrogen distribution on cosmological scales in the early Universe. These surveys are expected to generate huge imaging datasets that will encode more information than the power spectrum. This provides an alternative unique way to constrain the reionization history, which mi

Reuven Balkin, Javi Serra, Konstantin Springmann, Andreas Weiler

We show how the properties of the QCD axion change in systems at finite baryonic density, such as neutron stars. At nuclear saturation densities, where corrections can be reliably computed, we find a mild reduction of the axion mass and up to an order of magnitude enhancement in the model-independent axion coupling to neutrons. At moderately higher densities

Federico Carta, Jakob Moritz, Alexander Westphal

We present a vast landscape of O3/O7 orientifolds that descends from the famous set of complete intersection Calabi-Yau threefolds (CICY). We give distributions of topological data relevant for phenomenology such as the orientifold-odd Hodge numbers, the D3-tadpole, and multiplicities of O3 and O7-planes. Somewhat surprisingly, almost all of these orientifol

Dominic M. Rouse, Brendon W. Lovett, Erik M. Gauger, Niclas Westerberg

Systems of interacting charges and fields are ubiquitous in physics. Recently, it has been shown that Hamiltonians derived using different gauges can yield different physical results when matter degrees of freedom are truncated to a few low-lying energy eigenstates. This effect is particularly prominent in the ultra-strong coupling regime. Such ambiguities a

Thomas Bachlechner, Bodhisattwa Prasad Majumder, Huanru Henry Mao, Garrison W. Cottrell

Deep networks often suffer from vanishing or exploding gradients due to inefficient signal propagation, leading to long training times or convergence difficulties. Various architecture designs, sophisticated residual-style networks, and initialization schemes have been shown to improve deep signal propagation. Recently, Pennington et al. used free probabilit

Andreas Crivellin, Martin Hoferichter, Claudio Andrea Manzari, Marc Montull

Hadronic vacuum polarization (HVP) is not only a critical part of the Standard Model (SM) prediction for the anomalous magnetic moment of the muon $(g-2)_μ$, but also a crucial ingredient for global fits to electroweak (EW) precision observables due to its contribution to the running of the fine-structure constant encoded in $Δα^{(5)}_\text{had}$. We find th

Dominik Szczȩśniak, Sabre Kais

In the present study we investigate the selected local aspects of the metal-induced gap states (MIGSs) at the disordered metal-insulator interface, that were previously proposed to produce magnetic moments responsible for the magnetic flux noise in some of the superconducting qubit modalities. Our analysis attempts to supplement the available studies and pro

Nicholas Carlini, Matthew Jagielski, Ilya Mironov

We argue that the machine learning problem of model extraction is actually a cryptanalytic problem in disguise, and should be studied as such. Given oracle access to a neural network, we introduce a differential attack that can efficiently steal the parameters of the remote model up to floating point precision. Our attack relies on the fact that ReLU neural

Veronica Mattioli, Davide Alinovi, Riccardo Raheli

Video processing solutions for motion analysis are key tasks in many computer vision applications, ranging from human activity recognition to object detection. In particular, speed estimation algorithms may be relevant in contexts such as street monitoring and environment surveillance. In most realistic scenarios, the projection of a framed object of interes

José L. Vázquez, Marius Brühlmeier, Alexander Liniger, Alisa Rupenyan

In this paper we propose a hierarchical controller for autonomous racing where the same vehicle model is used in a two level optimization framework for motion planning. The high-level controller computes a trajectory that minimizes the lap time, and the low-level nonlinear model predictive path following controller tracks the computed trajectory online. Foll

Daniel Filan, Shlomi Hod, Cody Wild, Andrew Critch

The learned weights of a neural network are often considered devoid of scrutable internal structure. To discern structure in these weights, we introduce a measurable notion of modularity for multi-layer perceptrons (MLPs), and investigate the modular structure of MLPs trained on datasets of small images. Our notion of modularity comes from the graph clusteri

Philippe Landry, Reed Essick, Katerina Chatziioannou

Observations of neutron stars, whether in binaries or in isolation, provide information about the internal structure of the most extreme material objects in the Universe. In this work, we combine information from recent observations to place joint constraints on the properties of neutron star matter. We use (i) lower limits on the maximum mass of neutron sta

M. A. Yurtalan, J. Shi, M. Kononenko, A. Lupascu

We have implemented a Walsh-Hadamard gate, which performs a quantum Fourier transform, in a superconducting qutrit. The qutrit is encoded in the lowest three energy levels of a capacitively shunted flux device, operated at the optimal flux-symmetry point. We use an efficient decomposition of the Walsh-Hadamard gate into two unitaries, generated by off-diagon

Thaddeus D. Komacek, Daniel P. Thorngren, Eric D. Lopez, Sivan Ginzburg

Understanding the anomalous radii of many transiting hot gas giant planets is a fundamental problem of planetary science. Recent detections of re-inflated warm Jupiters orbiting post-main-sequence stars and the re-inflation of hot Jupiters while their host stars evolve on the main-sequence may help constrain models for the anomalous radii of hot Jupiters. In

Manuel Schilling, Étienne Wodey, Ludger Timmen, Dorothee Tell

Absolute gravimeters (AG) are used in geodesy, geophysics, and physics for a wide spectrum of applications. Stable gravimetric measurements over timescales from several days to decades are required to provide relevant insight into geophysical processes. Users of AGs participate in comparisons with a metrological reference in order to monitor the temporal sta

Bala Kameshwar Poolla, Ashish R. Hota, Saverio Bolognani, Duncan S. Callaway

We consider the problem of look-ahead economic dispatch (LAED) with uncertain renewable energy generation. The goal of this problem is to minimize the cost of conventional energy generation subject to uncertain operational constraints. The risk of violating these constraints must be below a given threshold for a family of probability distributions with chara

M. Lampón, M. López-Puertas, L. M. Lara, A. Sánchez-López

HD 209458b is an exoplanet with an upper atmosphere undergoing blow-off escape that has mainly been studied using measurements of the Ly-alpha absorption. Recently, high-resolution measurements of absorption in the He I triplet line at 10830 angstroms of several exoplanets (including HD 209458b) have been reported, creating a new opportunity to probe escapin

Philipp Markert, Daniel V. Bailey, Maximilian Golla, Markus Dürmuth

In this paper, we provide the first comprehensive study of user-chosen 4- and 6-digit PINs (n=1220) collected on smartphones with participants being explicitly primed for device unlocking. We find that against a throttled attacker (with 10, 30, or 100 guesses, matching the smartphone unlock setting), using 6-digit PINs instead of 4-digit PINs provides little

Jesús Rubio, Paul A Knott, Timothy J Proctor, Jacob A Dunningham

The theoretical framework for networked quantum sensing has been developed to a great extent in the past few years, but there are still a number of open questions. Among these, a problem of great significance, both fundamentally and for constructing efficient sensing networks, is that of the role of inter-sensor correlations in the simultaneous estimation of

Alexis Coleiro, Marta Colomer Molla, Damien Dornic, Massimiliano Lincetto

The multi-messenger observation of the next galactic core-collapse supernova will shed light on the different physical processes involved in these energetic explosions. Good timing and pointing capabilities of neutrino detectors would help in the search for an electromagnetic or gravitational-wave counterparts. An approach for the determination of the arriva

Kyriakos Axiotis, Aleksander Mądry, Adrian Vladu

We present an $m^{4/3+o(1)}\log W$-time algorithm for solving the minimum cost flow problem in graphs with unit capacity, where $W$ is the maximum absolute value of any edge weight. For sparse graphs, this improves over the best known running time for this problem and, by well-known reductions, also implies improved running times for the shortest path proble

Kanata Suzuki, Hiroki Mori, Tetsuya Ogata

Robotic applications require both correct task performance and compensation for undefined behaviors. Although deep learning is a promising approach to perform complex tasks, the response to undefined behaviors that are not reflected in the training dataset remains challenging. In a human-robot collaborative task, the robot may adopt an unexpected posture due

Vignesh Sivaramakrishnan, Meeko M. K. Oishi

We consider the problem of stochastic optimal control in the presence of an unknown disturbance. We characterize the disturbance via empirical characteristic functions, and employ a chance constrained approach. By exploiting properties of characteristic functions and underapproximating cumulative distribution functions, we can reformulate a nonconvex problem

Yihao Zhao, Ruihai Wu, Hao Dong

Unpaired image-to-image translation is a class of vision problems whose goal is to find the mapping between different image domains using unpaired training data. Cycle-consistency loss is a widely used constraint for such problems. However, due to the strict pixel-level constraint, it cannot perform geometric changes, remove large objects, or ignore irreleva

Yuqian Zhou, David Ren, Neil Emerton, Sehoon Lim

The new trend of full-screen devices encourages us to position a camera behind a screen. Removing the bezel and centralizing the camera under the screen brings larger display-to-body ratio and enhances eye contact in video chat, but also causes image degradation. In this paper, we focus on a newly-defined Under-Display Camera (UDC), as a novel real-world sin

Stevanus K. Nugroho, Neale P. Gibson, Ernst J. W. de Mooij, Chris A. Watson

We analyse the transmission spectra of KELT-20b/MASCARA-2b to search for possible thermal inversion agents. The data consist of three transits obtained using HARPSN and one using CARMENES. We removed stellar and telluric lines before cross-correlating the residuals with spectroscopic templates produced using a 1D plane-parallel model assuming an isothermal a

Hongmin Gao, Frank Schlawin, Michele Buzzi, Andrea Cavalleri

We demonstrate how virtual scattering of laser photons inside a cavity via two-photon processes can induce controllable long-range electron interactions in two-dimensional materials. We show that laser light that is red(blue)-detuned from the cavity yields attractive(repulsive) interactions, whose strength is proportional to the laser intensity. Furthermore,

Ian Shrier, Etsuji Suzuki

When developing new interventions to minimize the harmful effects of an exposure, investigators usually target the mechanisms that mediate the causal effect of the exposure on the outcome. Predicting the causal effect of these new interventions is generally done through identifying either (1) the controlled direct effect, or (2) the pure (natural) direct eff

Fabao Gao, Xia Liu

This paper statistically describes the orbital distribution laws of Jupiter&#39;s irregular moons, most of which are members of the Ananke, Carme and Pasiphae groups. By comparing 19 known continuous distributions, it is verified that suitable distribution functions exist to describe the orbital distributions of these natural satellites. For each distributio

Maximilian Kiefer-Emmanouilidis, Razmik Unanyan, Michael Fleischhauer, Jesko Sirker

We investigate the number entropy $S_N$---which characterizes particle-number fluctuations between subsystems---following a quench in one-dimensional interacting many-body systems with potential disorder. We find evidence that in the regime which is expected to show many-body localization (MBL) and where the entanglement entropy grows as $S\sim \ln t$ as fun

Rui Luo, Yunpeng Men, Kejia Lee, Weiyang Wang

The luminosity function of Fast Radio Bursts (FRBs), defined as the event rate per unit cosmic co-moving volume per unit luminosity, may help to reveal the possible origins of FRBs and design the optimal searching strategy. With the Bayesian modelling, we measure the FRB luminosity function using 46 known FRBs. Our Bayesian framework self-consistently models