June 2020 arXiv papers — page 25

Jiarong Li, Jin Lin, Philipp-Matthias Heuser, Heidi Ursula Heinrichs

Converting wind energy into ammonia (WtA) has been recognized as a promising pathway to enhance the usage of wind generation. This paper proposes a generic optimal configuration model of WtA at the network level to minimize the ammonia production cost by optimizing capacities and locations of WtA facilities including wind turbines, electrolyzers, hydrogen ta

Tonghua Liu, Shuo Cao, Marek Biesiada, Yuting Liu

In this paper, we present a cosmological model-independent test for the cosmic opacity at high redshifts ($z\sim5$). We achieve this with the opacity-dependent luminosity distances derived from nonlinear relation between X-ray and UV emissions of quasars, combined with two types of opacity-independent luminosity distances derived from the Hubble parameter me

Felipe Lepe, Gonzalo Rivera

In this paper we analyze a virtual element method (VEM) for a pseudostress formulation of the Stokes eigenvalue problem. This formulation allows to eliminate the velocity and the pressure, leading to an elliptic formulation where the only unknown is the pseudostress tensor. The velocity and pressure can be recovered by a post-process. Adapting the non-compac

Shujaat Khan, Jaeyoung Huh, Jong Chul Ye

Ultrasound (US) imaging is a fast and non-invasive imaging modality which is widely used for real-time clinical imaging applications without concerning about radiation hazard. Unfortunately, it often suffers from poor visual quality from various origins, such as speckle noises, blurring, multi-line acquisition (MLA), limited RF channels, small number of view

Donald M. Davis, Michael Harrison, David Recio-Mitter

We study the geodesic complexity of the ordered and unordered configuration spaces of graphs in both the $\ell_1$ and $\ell_2$ metrics. We determine the geodesic complexity of the ordered two-point $\varepsilon$-configuration space of any star graph in both the $\ell_1$ and $\ell_2$ metrics and of the unordered two-point configuration space of any tree in th

Xueli Bai, Zheng-Hai Huang, Mengmeng Zheng

An interesting observation is that most pairs of weakly homogeneous mappings have no strongly monotonic property, which is one of the key conditions to ensure the unique solvability of the generalized variational inequality. This paper focuses on studying the unique solvability of the generalized variational inequality with a pair of weakly homogeneous mappi

Pierre Derbez, Yi Liu, Shicheng Wang

For any closed orientable 3-manifold, there is a volume function defined on the space of all Seifert representations of the fundamental group. The maximum absolute value of this function agrees with the Seifert volume of the manifold due to Brooks and Goldman. For any Seifert representation of a graph manifold, the authors establish an effective formula for

Aishwarya Padmakumar, Raymond J. Mooney

Dialog systems research has primarily been focused around two main types of applications - task-oriented dialog systems that learn to use clarification to aid in understanding a goal, and open-ended dialog systems that are expected to carry out unconstrained "chit chat" conversations. However, dialog interactions can also be used to obtain various ty

Jake S. Bobowski, Saimoom Ferdous, Thomas Johnson

A single-contact voltage sensor designed for accurate measurements of ac voltages across a pair of conductors is described. The sensor design is motivated by remote monitoring applications where accurate voltage measurement of high-voltage transmission lines is required. The body of the sensor is electrically and mechanically attached to a single conductor:

Tingmin Wu, Wanlun Ma, Sheng Wen, Xin Xia

Computer users are generally faced with difficulties in making correct security decisions. While an increasingly fewer number of people are trying or willing to take formal security training, online sources including news, security blogs, and websites are continuously making security knowledge more accessible. Analysis of cybersecurity texts can provide insi

Zakaria Mhammedi, Benjamin Guedj, Robert C. Williamson

Conditional Value at Risk (CVaR) is a family of "coherent risk measures" which generalize the traditional mathematical expectation. Widely used in mathematical finance, it is garnering increasing interest in machine learning, e.g., as an alternate approach to regularization, and as a means for ensuring fairness. This paper presents a generalization b

Julius Susanto, Farhad Shahnia

Battery energy storage systems can be integrated with photovoltaic (PV)-diesel microgrids, as an enabling technology to increase the penetration of PV systems and aid microgrid stability by smoothing out the power fluctuations of the PV systems. The aim of this paper is to derive correlations between the optimal capacity of the smoothing batteries and variab

Chang Il Rim, Jong Gyong Kim, Chol-Hui Yun

In this paper, we generalize the existence result in [14] and prove convergence theorems of the iterative scheme in [12, 16] for monotone generalized alpa-nonexpansive mappings in uniformly convex partially ordered hyperbolic metric spaces. And we also give a numerical example to show that this scheme converges faster than the scheme in [14] and apply the re

Daohan Lu, Yi Fang

We present a new technique named "Meta Deformation Network" for 3D shape matching via deformation, in which a deep neural network maps a reference shape onto the parameters of a second neural network whose task is to give the correspondence between a learned template and query shape via deformation. We categorize the second neural network as a meta-f

Chao Min, Yang Chen

We study the Hankel determinant generated by a singularly perturbed Jacobi weight $$ w(x,t):=(1-x^2)^α\mathrm{e}^{-\frac{t}{x^{2}}},\;\;\;\;\;\;x\in[-1,1],\;\;α>0,\;\;t\geq 0. $$ If $t=0$, it is reduced to the classical symmetric Jacobi weight. For $t>0$, the factor $\mathrm{e}^{-\frac{t}{x^{2}}}$ induces an infinitely strong zero at the origin. This Hankel

Michael W. Coughlin, Tim Dietrich, Sarah Antier, Mouza Almualla

Joint multi-messenger observations with gravitational waves and electromagnetic data offer new insights into the astrophysical studies of compact objects. The third Advanced LIGO and Advanced Virgo observing run began on April 1, 2019; during the eleven months of observation, there have been 14 compact binary systems candidates for which at least one compone

Luc Gossart

We consider a $\mathbb R/\mathbb Z$ extension of an Anosov diffemorphism of a compact Riemannian manifold by a random function $τ$ and show that the flat traces of the transfer operator, reduced with respect to frequency in the fibers, converge in law towards Gaussians, up to an Ehrenfest time that decreases with the regularity of $τ$.

Shashank Reddy Vadyala, Sai Nethra Betgeri, Eric A. Sherer, Amod Amritphale

COVID-19 is a pandemic disease that began to rapidly spread in the US with the first case detected on January 19, 2020, in Washington State. March 9, 2020, and then increased rapidly with total cases of 25,739 as of April 20, 2020. The Covid-19 pandemic is so unnerving that it is difficult to understand how any person is affected by the virus. Although most

Ruda Zhang

Efficient approximation of geodesics is crucial for practical algorithms on manifolds. Here we introduce a class of retractions on submanifolds, induced by a foliation of the ambient manifold. They match the projective retraction to the third order and thus match the exponential map to the second order. In particular, we show that Newton retraction (NR) is a

Labhaoise Ni Fhaolain, Andrew Hines

Is a new regulated profession, such as Artificial Intelligence (AI) Architect who is responsible and accountable for AI outputs necessary to ensure trustworthy AI? AI is becoming all pervasive and is often deployed in everyday technologies, devices and services without our knowledge. There is heightened awareness of AI in recent years which has brought with

Oscar de Lima, Sean Franklin, Shreshtha Basu, Blake Karwoski

Better generative models and larger datasets have led to more realistic fake videos that can fool the human eye but produce temporal and spatial artifacts that deep learning approaches can detect. Most current Deepfake detection methods only use individual video frames and therefore fail to learn from temporal information. We created a benchmark of the perfo

Jasel Berra-Montiel, Elías Castellanos, Alberto Molgado, Jonathan Trinidad-García

In this work, we analyze the corrections obtained on a homogeneous one-dimensional Bose gas within the high densities limit by means of the polymer quantization scheme. Thus, starting from the Bogoliubov formalism, we analyze the ground expectation value of the polymer momentum operator in terms of semiclassical states, in order to obtain an analytic express

Sergio R. Coria, Leonardo Marcos-Santiago, Christian A. Cruz-Melendez, Juan M. Jimenez-Canseco

This article addresses a problem in the electronic government discipline with special interest in Mexico: the need for a concentrated and updated information source about municipal e-government websites. One reason for this is the lack of a complete and updated database containing the electronic addresses (web domain names) of the municipal governments havin

Chiang-Mei Chen, James M. Nester, Walter Vogel

We present an English translation of a third 1918 paper by Felix Klein which follows up on his earlier work.

Michael J. Mossinghoff, Timothy S. Trudgian

Let $R(n) = \sum_{a+b=n} Λ(a)Λ(b)$, where $Λ(\cdot)$ is the von Mangoldt function. The function $R(n)$ is often studied in connection with Goldbach's conjecture. On the Riemann hypothesis (RH) it is known that $\sum_{n\leq x} R(n) = x^2/2 - 4x^{3/2} G(x) + O(x^{1+ε})$, where $G(x)=\Re \sum_{γ>0} \frac{x^{iγ}}{(\frac{1}{2} + iγ)(\frac{3}{2} + iγ)}$ and th

Seung Gyo Jeong, Gyeongtak Han, Sehwan Song, Taewon Min

Bonding geometry engineering of metal-oxygen octahedra is a facile way of tailoring various functional properties of transition metal oxides. Several approaches, including epitaxial strain, thickness, and stoichiometry control, have been proposed to efficiently tune the rotation and tilting of the octahedra, but these approaches are inevitably accompanied by

Sepehr Ataei, Javad Alirezaie, Paul Babyn

Low Dose CT Denoising research aims to reduce the risks of radiation exposure to patients. Recently researchers have used deep learning to denoise low dose CT images with promising results. However, approaches that use mean-squared-error (MSE) tend to over smooth the image resulting in loss of fine structural details in low contrast regions of the image. The

Doaa Ayad, Nokuthaba Sibanda

Most statistical process control programmes in healthcare focus on surveillance of outcomes at the final stage of a procedure, such as mortality or failure rates. Such an approach ignores the multi-stage nature of these procedures, in which a patient progresses through several stages prior to the final stage. In this paper, we develop a multi-stage control c

Sarah Hoback, Sarthak Parikh

We conjecture a simple set of "Feynman rules" for constructing $n$-point global conformal blocks in any channel in $d$ spacetime dimensions, for external and exchanged scalar operators for arbitrary $n$ and $d$. The vertex factors are given in terms of Lauricella hypergeometric functions of one, two or three variables, and the Feynman rules furnish a

V. A. Dzuba, Saleh O. Allehabi, V. V. Flambaum, Jiguang Li

We study the prospects of using the electric quadrupole transitions from the ground states of Cu, Ag and Au to the metastable state $^2{\rm D}_{5/2}$ as clock transitions in optical lattice clocks. We calculate lifetimes, transition rates, systematic shifts, and demonstrate that the fractional uncertainty of the clocks can be similar to what is achieved in t

Debajyoti Mondal, N. Parthiban, V. Kavitha, Indra Rajasingh

Consider an information diffusion process on a graph $G$ that starts with $k>0$ burnt vertices, and at each subsequent step, burns the neighbors of the currently burnt vertices, as well as $k$ other unburnt vertices. The \emph{$k$-burning number} of $G$ is the minimum number of steps $b_k(G)$ such that all the vertices can be burned within $b_k(G)$ steps. No

V. Y. Chernyak, N. A. Sinitsyn

Exactly solvable multistate Landau-Zener (MLZ) models are associated with families of operators that commute with the MLZ Hamiltonians and depend on time linearly. There can also be operators that satisfy the integrability conditions with the MLZ Hamiltonians but depend on time quadratically. We show that, among the MLZ systems, such time-quadratic operators

Tatiana Komarova, Denis Nekipelov

The paper redefines econometric identification under formal privacy constraints, particularly differential privacy (DP). Traditionally, econometrics focuses on point or partial identification, aiming to recover parameters precisely or within a deterministic set. However, DP introduces a fundamental challenge: information asymmetry between researchers and dat

Jennifer F. Lilieholm, Vasilis Niaouris, Alexander Kato, Kai-Mei C. Fu

We propose an optical scheme to generate an entangled state between a trapped ion and a solid state donor qubit through which-path erasure of identical photons emitted from the two systems. The proposed scheme leverages the similar transition frequencies between In donor bound excitons in ZnO and the $^2P_{1/2}$ to $^2S_{1/2}$ transition in Yb$^+$. The lifet

Satyam Mohla, Anshul Nasery, Biplab Banerjee

Recent experiments in computer vision demonstrate texture bias as the primary reason for supreme results in models employing Convolutional Neural Networks (CNNs), conflicting with early works claiming that these networks identify objects using shape. It is believed that the cost function forces the CNN to take a greedy approach and develop a proclivity for l

J. Galvis, H. M. Versieux

A novel regularized fracture model for crack propagation in porous media is proposed. Our model is obtained through homogenization theory and formal asymptotic expansions. We start with a regularized quasi-static fracture model posed in a periodically perforated domain obtained by periodic extension of a re-scaled unit cell with a hole. This setup allows us

Michael R. Walker, Joseph A. O'Sullivan

The single-scatter approximation is fundamental in many tomographic imaging problems including x-ray scatter imaging and optical scatter imaging for certain media. In all cases, noisy measurements are affected by both local scatter events and nonlocal attenuation. Prior works focus on reconstructing one of two images: scatter density or total attenuation. Ho

Giulio Caviglia, Alessandro De Stefani

We prove a Cayley-Bacharach-type theorem for points in projective space $\mathbb{P}^n$ that lie on a complete intersection of $n$ hypersurfaces. This is made possible by new bounds on the growth of the Hilbert function of almost complete intersections.

Amy L. Glazier, Ward S. Howard, Hank Corbett, Nicholas M. Law

The nearby ultracool dwarf TRAPPIST-1 possesses several Earth-sized terrestrial planets, three of which have equilibrium temperatures that may support liquid surface water, making it a compelling target for exoplanet characterization. TRAPPIST-1 is an active star with frequent flaring, with implications for the habitability of its planets. Superflares (stell

Gabriel Leitão, Juan Colonna, Edwin Monteiro, Elaine Oliveira

Technology applied in education can provide great benefits and overcome challenges by facilitating access to learning objects anywhere and anytime. However, technology alone is not enough, since it requires suitable planning and learning methodologies. Using technology can be problematic, especially in determining whether learning has occurred or not. Futher

D. Babusci, M. Berlowski, C. Bloise, F. Bossi

Based on an integrated luminosity of 1.61 fb$^{-1}$ $e^+e^-$ collision data collected with the KLOE detector at DA$Φ$NE, the Frascati $ϕ$-factory, a search for the $P$- and $CP$-violating decay $η\toπ^{+}π^{-}$ has been performed. Radiative $ϕ\toηγ$ decay is exploited to access the $η$ mesons. No signal is observed in the $π^{+}π^{-}$ invariant mass spectrum

Sebastian Goldt, Bruno Loureiro, Galen Reeves, Florent Krzakala

Understanding the impact of data structure on the computational tractability of learning is a key challenge for the theory of neural networks. Many theoretical works do not explicitly model training data, or assume that inputs are drawn component-wise independently from some simple probability distribution. Here, we go beyond this simple paradigm by studying

Peter Bartholomew

Spreadsheets offer a supremely successful and intuitive means of processing and exchanging numerical content. Its intuitive ad-hoc nature makes it hugely popular for use in diverse areas including business and engineering, yet these very same characteristics make it extraordinarily error-prone; many would question whether it is suitable for serious analysis

Nafis I Karim, Alexandru Maries, Chandralekha Singh

We describe the impact of physics education research-based pedagogical techniques in flipped and active-engagement non-flipped courses on student performance on validated conceptual surveys. We compare student performance in courses which make significant use of evidence-based active engagement (EBAE) strategies with courses that primarily use lecture-based

Saypraseuth Mounsaveng, Issam Laradji, Ismail Ben Ayed, David Vazquez

Data augmentation is a key practice in machine learning for improving generalization performance. However, finding the best data augmentation hyperparameters requires domain knowledge or a computationally demanding search. We address this issue by proposing an efficient approach to automatically train a network that learns an effective distribution of transf

MacCallum Robertson, Christopher J. Agostino, Gong Chen, Sang Pyo Kang

The interfacial Dzyaloshinskii-Moriya interaction (DMI) is of great interest as it can stabilize chiral spin structures in thin films. Experiments verifying the orientation of the interfacial DMI vector remain rare, in part due to the difficulty of separating vector components of DMI. In this study, Fe/Ni bilayers and Co/Ni multilayers were deposited epitaxi

Henry Liu

We prove an equivalence between the Bryan--Steinberg theory of $π$-stable pairs on $Y = \mathcal{A}_{m-1} \times \mathbb{C}$ and the theory of quasimaps to $X = \mathrm{Hilb}(\mathcal{A}_{m-1})$, in the form of an equality of K-theoretic equivariant vertices. In particular, the combinatorics of both vertices are described explicitly via box counting. Then we

Yu-Chen Ding, Nan Li, Chun-Cheng Wei, Yu-Feng Zhou

Cosmic-ray (CR) anti-nuclei are often considered as important observables for dark matter (DM) indirect detections at low kinetic energies below GeV per nucleon. Since the primary CR fluxes drop quickly towards high energies, the secondary anti-nuclei in CR are expected to be significantly suppressed in high energy regions ($\gtrsim 100$ GeV per nucleon). If

Andrew J. Larkoski

Jet grooming has emerged as a necessary and powerful tool in a precision jet physics program. In this paper, we present three results on jet grooming in perturbation theory, focusing on heavy jet mass in $e^+e^-\to$ hadrons collisions, groomed with the modified mass drop tagger. First, we calculate the analytic cross section at leading-order. Second, using t

Akash Kumar, Adish Singla, Yisong Yue, Yuxin Chen

We examine the task of locating a target region among those induced by intersections of $n$ halfspaces in $\mathbb{R}^d$. This generic task connects to fundamental machine learning problems, such as training a perceptron and learning a $ϕ$-separable dichotomy. We investigate the average teaching complexity of the task, i.e., the minimal number of samples (ha

W. Castiglioni, W. Foreman, I. Lepetic, B. R. Littlejohn

Using truth-level Monte Carlo simulations of particle interactions in a large volume of liquid argon, we demonstrate physics capabilities enabled by reconstruction of topologically compact and isolated low-energy features, or `blips,' in large liquid argon time projection chamber (LArTPC) events. These features are mostly produced by electron products of

Christian Klingenberg, Ru-Yu Lai, Qin Li

In this paper, we investigate an inverse problem for the radiative transfer equation that is coupled with a heat equation in a nonscattering medium in $\mathbb{R}^n$, $n\geq 2$. The two equations are coupled through a nonlinear blackbody emission term that is proportional to the fourth power of the temperature. By measuring the radiation intensity on the sur

Florian Knoop, Thomas A. R. Purcell, Matthias Scheffler, Christian Carbogno

Theoretical frameworks used to qualitatively and quantitatively describe nuclear dynamics in solids are often based on the harmonic approximation. However, this approximation is known to become inaccurate or to break down completely in many modern functional materials. Interestingly, there is no reliable measure to quantify anharmonicity so far. Thus, a syst

Constantin Shramov

We classify finite groups that can act by automorphisms and birational automorphisms on non-trivial Severi-Brauer surfaces over fields of characteristic zero.

Yang Sun, Yong-Xin Yao, Manh Cuong Nguyen, Cai-Zhuang Wang

We propose a scheme of decomposition of the total relativistic energy in solids to intra- and interatomic contributions. The method is based on a variation of the speed of light from its value in relativistic theory to infinity (a non-relativistic limit). As an illustration of the method, we tested such decomposition in the case of a spin-orbit interaction v

Angela Dai, Yawar Siddiqui, Justus Thies, Julien Valentin

We present SPSG, a novel approach to generate high-quality, colored 3D models of scenes from RGB-D scan observations by learning to infer unobserved scene geometry and color in a self-supervised fashion. Our self-supervised approach learns to jointly inpaint geometry and color by correlating an incomplete RGB-D scan with a more complete version of that scan.

Giacomo Serafini, Stefano Zippilli, Irene Marzoli

We propose and analyze a microscopic Stirling heat engine based on an optomechanical system. The working fluid is a single vibrational mode of a mechanical resonator, which interacts by radiation pressure with a feedback-controlled optical cavity. The cavity light is used to engineer the thermal reservoirs and to steer the resonator through a thermodynamic c

Riddhi Mehta, Maxim Barkov, Lorenzo Sironi, Maxim Lyutikov

We consider the tilting instability of a magnetically confined spheromak using 3D MHD and relativistic PIC calculations with an application to astrophysical plasmas, specifically those occurring in magnetar magnetospheres. The instability is driven by the counter alignment of the spheromak's intrinsic magnetic dipole with the external magnetic field. Ini

Yi Wang, Jingyang Zhou, Tianlong Chen, Sijia Liu

With the trend of adversarial attacks, researchers attempt to fool trained object detectors in 2D scenes. Among many of them, an intriguing new form of attack with potential real-world usage is to append adversarial patches (e.g. logos) to images. Nevertheless, much less have we known about adversarial attacks from 3D rendering views, which is essential for

Yash Kanoria, Seungki Min, Pengyu Qian

We study the competition for partners in two-sided matching markets with heterogeneous agent preferences, with a focus on how the equilibrium outcomes depend on the connectivity in the market. We model random partially connected markets, with each agent having an average degree $d$ in a random (undirected) graph, and a uniformly random preference ranking ove

Samyadeep Basu, Philip Pope, Soheil Feizi

Influence functions approximate the effect of training samples in test-time predictions and have a wide variety of applications in machine learning interpretability and uncertainty estimation. A commonly-used (first-order) influence function can be implemented efficiently as a post-hoc method requiring access only to the gradients and Hessian of the model. F

Yi-Kuan Chiang, Ryu Makiya, Brice Ménard, Eiichiro Komatsu

The cosmic thermal history, quantified by the evolution of the mean thermal energy density in the universe, is driven by the growth of structures as baryons get shock heated in collapsing dark matter halos. This process can be probed by redshift-dependent amplitudes of the thermal Sunyaev-Zeldovich (SZ) effect background. To do so, we cross-correlate eight s

Raghwinder Singh Grewal, Mauricio Pulido, Gour Pati, Renu Tripathi

We report a new technique for generating magnetic resonance with synchronous modulation of two-photon resonant light fields. Magnetic resonances in fluorescence from a sodium cell are measured to demonstrate suitability of this technique for remote magnetometry. A strong magnetic resonance with its dip corresponding to the Larmor frequency is produced in the

Kyrylo Snizhko, Nihal Rao, Parveen Kumar, Yuval Gefen

Coherent steering of a quantum state, induced by a sequence of weak measurements, has become an active area of theoretical and experimental study. For a closed steered trajectory, the underlying phase factors involve both geometrical and dynamical terms. Furthermore, considering the reversal of the order of the measurement sequence, such a phase comprises a

Avijit Das, Abhishek Dhar, Ion Santra, Urbashi Satpathi

The motion of a free quantum particle in a thermal environment is usually described by the quantum Langevin equation, where the effect of the bath is encoded through a dissipative and a noise term, related to each other via the fluctuation dissipation theorem. The quantum Langevin equation can be derived starting from a microscopic model of the thermal bath

M. Huertas-Company, Y. Guo, O. Ginzburg, C. T. Lee

A significant fraction of high redshift star-forming disc galaxies are known to host giant clumps, whose nature and role in galaxy evolution are yet to be understood. In this work we first present a new method based on neural networks to detect clumps in galaxy images. We use this method to detect clumps in the rest-frame optical and UV images of a complete

Jacob Sonnenschein, Dorin Weissman

Classical rotating closed string are folded strings. At the folding points the scalar curvature associated with the induced metric diverges. As a consequence one cannot properly quantize the fluctuations around the classical solution since there is no complete set of normalizable eigenmodes. Furthermore in the non-critical effective string action of Polchins

Giacomo Fragione, Rosalba Perna, Abraham Loeb

As the sensitivity of gravitational wave (GW) instruments improves and new networks start operating, hundreds of merging stellar-mass black holes (SBHs) and intermediate-mass black holes (IMBHs) are expected to be observed in the next few years. The origin and distribution of SBH and IMBH binaries in various dynamical environments is a fundamental scientific

Teymoor Saifollahi, Ignacio Trujillo, Michael A. Beasley, Reynier F. Peletier

There is a growing consensus that the vast majority of ultra-diffuse galaxies (UDGs) are dwarf galaxies. However, there remain a few UDGs that seem to be special in terms of their globular cluster (GC) systems. In particular, according to some authors, certain UDGs exhibit large GC populations when compared to expectations from their stellar (or total) mass.

Elisa Maggio, Luca Buoninfante, Anupam Mazumdar, Paolo Pani

A generic feature of nearly out-of-equilibrium dissipative systems is that they resonate through a set of quasinormal modes. Black holes - the absorbing objects par excellence - are no exception. When formed in a merger, black holes vibrate in a process called "ringdown", which leaves the gravitational-wave footprint of the event horizon. In some mod

Monica Gallegos-Garcia, Blakesley Burkhart, Anna Rosen, Jill P. Naiman

Intermediate and massive stars drive fast and powerful isotropic winds that interact with the winds of nearby stars in star clusters and the surrounding interstellar medium (ISM). Wind-ISM collisions generate astrospheres around these stars that contain hot $T\sim 10^7$ K gas that adiabatically expands. As individual bubbles expand and collide they become un

John A. Regan, Zoltán Haiman, John H. Wise, Brian W. O'Shea

The formation of supermassive stars has generally been studied under the assumption of rapid accretion of pristine metal-free gas. Recently it was found, however, that gas enriched to metallicities up to $Z \sim 10^{-3}$ Z$_{\odot}$ can also facilitate supermassive star formation, as long as the total mass infall rate onto the protostar remains sufficiently

Elliott Gesteau, Monica Jinwoo Kang

We formulate the baby universe construction rigorously by giving a primordial role to the algebra of observables of quantum gravity rather than the Hilbert space. Utilizing diffeomorphism invariance, we study baby universe creation and annihilation via change in topology. We then construct the algebra of boundary observables for holographic theories and show

Kamal Gupta, Justin Lazarow, Alessandro Achille, Larry Davis

We address the problem of scene layout generation for diverse domains such as images, mobile applications, documents, and 3D objects. Most complex scenes, natural or human-designed, can be expressed as a meaningful arrangement of simpler compositional graphical primitives. Generating a new layout or extending an existing layout requires understanding the rel

Allan Jabri, Andrew Owens, Alexei A. Efros

This paper proposes a simple self-supervised approach for learning a representation for visual correspondence from raw video. We cast correspondence as prediction of links in a space-time graph constructed from video. In this graph, the nodes are patches sampled from each frame, and nodes adjacent in time can share a directed edge. We learn a representation

María Anguiano

This paper deals with the homogenization of the $p$-Laplacian reaction-diffusion problems in a domain containing periodically distributed holes of size $\varepsilon$, with a dynamical boundary condition of pure-reactive type. We generalize our previous results established in the case where the diffusion is modeled by the Laplacian operator, i.e., with $p=2$.

Yuval Atzmon, Felix Kreuk, Uri Shalit, Gal Chechik

People easily recognize new visual categories that are new combinations of known components. This compositional generalization capacity is critical for learning in real-world domains like vision and language because the long tail of new combinations dominates the distribution. Unfortunately, learning systems struggle with compositional generalization because

Konstantinos Pelechrinis, Wayne Winston

Streaks of success have always fascinated people and a lot of research has been conducted to identify whether the "hot hand" effect is real. While sports have provided an appropriate platform for studying this phenomenon, the majority of existing literature examines scenarios in a vacuum with results that might or might not be applicable in the wild.

Artur Souza, Luigi Nardi, Leonardo B. Oliveira, Kunle Olukotun

While Bayesian Optimization (BO) is a very popular method for optimizing expensive black-box functions, it fails to leverage the experience of domain experts. This causes BO to waste function evaluations on bad design choices (e.g., machine learning hyperparameters) that the expert already knows to work poorly. To address this issue, we introduce Bayesian Op

Haoxiang Wang, Ruoyu Sun, Bo Li

Gradient-based meta-learning (GBML) with deep neural nets (DNNs) has become a popular approach for few-shot learning. However, due to the non-convexity of DNNs and the bi-level optimization in GBML, the theoretical properties of GBML with DNNs remain largely unknown. In this paper, we first aim to answer the following question: Does GBML with DNNs have globa

Jason Miller, Scott Sheffield, Wendelin Werner

We study the structure of the Liouville quantum gravity (LQG) surfaces that are cut out as one explores a conformal loop-ensemble CLE$_{κ'}$ for $κ'$ in $(4,8)$ that is drawn on an independent $γ$-LQG surface for $γ^2=16/κ'$. The results are similar in flavor to the ones from our paper dealing with CLE$_κ$ for $κ$ in $(8/3,4)$, where the loops of

Elias R. Most, L. Jens Papenfort, Lukas R. Weih, Luciano Rezzolla

The recent detection of GW190814 featured the merger of a binary with a primary having a mass of $\sim 23\,M_{\odot}$ and a secondary with a mass of $\sim 2.6\,M_{\odot}$. While the primary was most likely a black hole, the secondary could be interpreted as either the lightest black hole or the most massive neutron star ever observed, but also as the indicat

A. Palmese, J. deVicente, M. E. S. Pereira, J. Annis

We present a measurement of the Hubble constant $H_0$ using the gravitational wave (GW) event GW190814, which resulted from the coalescence of a 23 $M_\odot$ black hole with a 2.6 $M_\odot$ compact object, as a standard siren. No compelling electromagnetic counterpart has been identified for this event, thus our analysis accounts for thousands of potential h

Christina Gao, Jia Liu, Lian-Tao Wang, Xiao-Ping Wang

The XENON1T collaboration has observed an excess in electronic recoil events below $5~\mathrm{keV}$ over the known background, which could originate from beyond-the-Standard-Model physics. The solar axion is a well-motivated model that has been proposed to explain the excess, though it has tension with astrophysical observations. The axions traveled from the

Guillermo Ballesteros, Julián Rey, Marco Taoso, Alfredo Urbano

We consider the impact of quantum diffusion on inflationary dynamics during an ultra-slow-roll phase, which can be of particular significance for the formation of primordial black holes. We show, by means of a fully analytical approach, that the power spectrum of comoving curvature perturbations computed in stochastic inflation matches precisely, at the line

Mikael Chala, Arsenii Titov

We compute the one-loop running of the dimension-six CP-even Higgs operators in the Standard Model effective field theory involving the right-handed component of the would-be Dirac neutrinos. We discuss the implications of a large Dirac neutrino magnetic dipole moment. In particular, we demonstrate that a neutrino magnetic moment explaining the recent XENON1

Saptarshi Sinha, Deep Nath, Soumen Roy

The maintenance of cooperation in the presence of spatial restrictions has been studied extensively. It is well-established that the underlying graph topology can significantly influence the outcome of games on graphs. Maintenance of cooperation could be difficult, especially in the absence of spatial restrictions. The evolution of cooperation would naturall

Guojun Zhang, Kaiwen Wu, Pascal Poupart, Yaoliang Yu

Differential games, in particular two-player sequential zero-sum games (a.k.a. minimax optimization), have been an important modeling tool in applied science and received renewed interest in machine learning due to many recent applications, such as adversarial training, generative models and reinforcement learning. However, existing theory mostly focuses on

Constantin Philippenko, Aymeric Dieuleveut

We introduce a framework - Artemis - to tackle the problem of learning in a distributed or federated setting with communication constraints and device partial participation. Several workers (randomly sampled) perform the optimization process using a central server to aggregate their computations. To alleviate the communication cost, Artemis allows to compres

Sambaran Banerjee

I study the potential role of young massive (YMCs) and open star clusters (OCs) in assembling stellar-mass binary black holes (BBHs) which would be detectable as persistent gravitational-wave (GW) sources by the forthcoming LISA mission. The energetic dynamical interactions inside star clusters make them factories of assembling BBHs and other types of double

Dongge Han, Michael Wooldridge, Alex Rogers, Olga Ohrimenko

Submodular functions have been a powerful mathematical model for a wide range of real-world applications. Recently, submodular functions are becoming increasingly important in machine learning (ML) for modelling notions such as information and redundancy among entities such as data and features. Among these applications, a key question is payoff allocation,

Emily Wenger, Josephine Passananti, Arjun Bhagoji, Yuanshun Yao

Backdoor attacks embed hidden malicious behaviors into deep learning models, which only activate and cause misclassifications on model inputs containing a specific trigger. Existing works on backdoor attacks and defenses, however, mostly focus on digital attacks that use digitally generated patterns as triggers. A critical question remains unanswered: can ba

J. Todd Hoeksema, William P. Abbett, David J. Bercik, Mark C. M. Cheung

The Coronal Global Evolutionary Model (CGEM) provides data-driven simulations of the magnetic field in the solar corona to better understand the build-up of magnetic energy that leads to eruptive events. The CGEM project has developed six capabilities. CGEM modules (1) prepare time series of full-disk vector magnetic field observations to (2) derive the chan

Haojian Li, Marius Junge, Nicholas LaRacuente

This paper extends the Bakry-Émery theorem connecting the Ricci curvature and log-Sobolev inequalities to the matrix-valued setting. Using tools from noncommuative geometry, it is shown that for a right invariant second order differential operator on a compact Lie group, a lower bound for a matrix-valued modified log-Sobolev inequality is equivalent to a uni

Lei Zu, Guan-Wen Yuan, Lei Feng, Yi-Zhong Fan

Recently, the XENON1T experiment has reported the possible detection of an excess in the electronic recoil spectrum. Such an excess may indicate the presence of new physics. In this work, we suggest that the scattering of mirror electrons with ordinary electrons through photon$-$mirror photon kinetic mixing with parameter $ε\sim 10^{-12}(n_{\rm e'}/0.2{\

Michael Zevin, Mario Spera, Christopher P. L. Berry, Vicky Kalogera

On August 14, 2019, the LIGO and Virgo detectors observed GW190814, a gravitational-wave signal originating from the merger of a $\simeq 23 M_\odot$ black hole with a $\simeq 2.6 M_\odot$ compact object. GW190814's compact-binary source is atypical both in its highly asymmetric masses and in its lower-mass component lying between the heaviest known neutr

Kieran Leschinski, Eric Gendron

AnisoCADO is a Python package for generating images of the point spread function (PSF) for the european extremely large telescope (ELT). The code allows the user to set many of the most important atmospheric and observational parameters that influence the shape and strehl ratio of the resulting PSF, including but not limited to: the atmospheric turbulence pr

Yacine Ali-Haïmoud, Tristan L. Smith, Chiara M. F. Mingarelli

Pulsar timing arrays (PTAs) are currently the only experiments directly sensitive to gravitational waves with decade-long periods. Within the next five to ten years, PTAs are expected to detect the stochastic gravitational-wave background (SGWB) collectively sourced by inspiralling supermassive black hole binaries. It is expected that this background is most

Ranny Budnik, Hyungjin Kim, Oleksii Matsedonskyi, Gilad Perez

We study the recent \XeT excess in context of solar scalar, specifically in the framework of Higgs-portal and the relaxion model. We show that $m_ϕ= 1.9\,\keV$ and $g_{ϕe}=2.4\times 10^{-14}$ can explain the observed excess in science run 1 (SR1) analysis in the 1-7 keV range. When translated into the scalar-Higgs mixing angle, the corresponding mixing angle

Tatjana Chavdarova, Matteo Pagliardini, Sebastian U. Stich, Francois Fleuret

Generative Adversarial Networks are notoriously challenging to train. The underlying minmax optimization is highly susceptible to the variance of the stochastic gradient and the rotational component of the associated game vector field. To tackle these challenges, we propose the Lookahead algorithm for minmax optimization, originally developed for single obje