October 2020 arXiv papers — page 31

William Clark, Maani Ghaffari

Information gathered along a path is inherently submodular; the incremental amount of information gained along a path decreases due to redundant observations. In addition to submodularity, the incremental amount of information gained is a function of not only the current state but also the entire history as well. This paper presents the construction of the f

Karin Baur, Andrea Pasquali, Diego Velasco

We study alternating strand diagrams on the disk with an orbifold point. These are quotients by rotation of Postnikov diagrams on the disk, and we call them orbifold diagrams. We associate a quiver with potential to each orbifold diagram, in such a way that its Jacobian algebra and the one associated to the covering Postnikov diagram are related by a skew-gr

Juan Garcia-Bellido, Jose Francisco Nuño Siles, Ester Ruiz Morales

Gravitational wave detection from binary black hole (BBH) inspirals has become routine thanks to the LIGO/Virgo interferometers. The nature of these back holes remains uncertain. We study here the spin distributions of LIGO/Virgo black holes from the first catalogue GWTC-1 and the first four published BBH events from run O3. We compute the Bayes evidence for

Jorge Miguel-Ramiro, Alexander Pirker, Wolfgang Dür

Randomized benchmarking is a powerful technique to efficiently estimate the performance and reliability of quantum gates, circuits and devices. Here we propose to perform randomized benchmarking in a coherent way, where superpositions of different random sequences rather than independent samples are used. We show that this leads to a uniform and simple proto

Pietro Baratella, Clara Fernandez, Benedict von Harling, Alex Pomarol

On-shell amplitude methods have proven to be extremely efficient for calculating anomalous dimensions. We further elaborate on these methods to show that, by the use of an angular momentum decomposition, the one-loop anomalous dimensions can be reduced to essentially a sum of products of partial waves. We apply this to the SM EFT, and show how certain classe

Marco Benini, Marco Perin, Alexander Schenkel

This paper proposes a refinement of the usual concept of algebraic quantum field theories (AQFTs) to theories that are smooth in the sense that they assign to every smooth family of spacetimes a smooth family of observable algebras. Using stacks of categories, this proposal is realized concretely for the simplest case of 1-dimensional spacetimes, leading to

N. P. Gentile Fusillo, C. J. Manser, Boris T. Gänsicke, O. Toloza

White dwarfs with emission lines from gaseous debris discs are among the rarest examples of planetary remnant hosts, but at the same time they are key objects for studying the final evolutionary stage of planetary systems. Making use of the large number of white dwarfs identified in Gaia DR2, we are conducting a survey of planetary remnants and here we prese

Krista Lynne Smith, Michael Koss, Richard Mushotzky, O. Ivy Wong

We conducted 22~GHz 1" JVLA imaging of 100 radio-quiet X-ray selected AGN from the Swift-BAT survey. We find AGN-driven kiloparsec-scale radio structures inconsistent with pure star formation in 11 AGN. The host galaxies of these AGN lie significantly below the star-forming main sequence, indicating suppressed star formation. While these radio structures ten

Lucila Peralta Gavensky, Gonzalo Usaj, C. A. Balseiro

We study the transport properties of a voltage-biased Josephson junction where the BCS superconducting leads are coupled via the edges of a quantum Hall sample. In this scenario, an out of equilibrium Josephson current develops, which is numerically studied within the Floquet-Keldysh Green's function formalism. We particularly focus on the time-averaged curr

Gerrit Schellenberger, Laurence P. David, Jan Vrtilek, Ewan O'Sullivan

The fate of cooling gas in the centers of galaxy clusters and groups is still not well understood, as is also the case for the complex process of triggering active galactic nucleus (AGN) outbursts in their central dominant galaxies, and the consequent re-heating of the gas by the AGN jets. With the largest known reservoir of cold molecular gas of any group-d

Tyler D. Ellison, Kohtaro Kato, Zi-Wen Liu, Timothy H. Hsieh

We introduce the concepts of a symmetry-protected sign problem and symmetry-protected magic to study the complexity of symmetry-protected topological (SPT) phases of matter. In particular, we say a state has a symmetry-protected sign problem or symmetry-protected magic, if finite-depth quantum circuits composed of symmetric gates are unable to transform the

Wolfgang Enzi, Riccardo Murgia, Oliver Newton, Simona Vegetti

We derive joint constraints on the warm dark matter (WDM) half-mode scale by combining the analyses of a selection of astrophysical probes: strong gravitational lensing with extended sources, the Lyman-$\alpha$ forest, and the number of luminous satellites in the Milky Way. We derive an upper limit of $\lambda_{\rm hm}=0.089{\rm~Mpc~h^{-1} }$ at the 95 per c

Alis J. Deason, Denis Erkal, Vasily Belokurov, Azadeh Fattahi

We use a distribution function analysis to estimate the mass of the Milky Way out to 100 kpc using a large sample of halo stars. These stars are compiled from the literature, and the vast majority (~98%) have 6D phase-space information. We pay particular attention to systematic effects, such as the dynamical influence of the Large Magellanic Cloud (LMC), and

M. Costanzi, A. Saro, S. Bocquet, T. M. C. Abbott

We perform a joint analysis of the counts of redMaPPer clusters selected from the Dark Energy Survey (DES) Y1 data and multi-wavelength follow-up data collected within the 2500 deg$^2$ South Pole Telescope (SPT) SZ survey. The SPT follow-up data, calibrating the richness--mass relation of the optically selected redMaPPer catalog, enable the cosmological expl

Bo Yang

We motivate a close look on the usefulness of the Gaffnian and Haffnian quasihole manifold (null spaces of the respective model Hamiltonians) for well-known gapped fractional quantum Hall (FQH) phases. The conformal invariance of these subspaces are derived explicitly from microscopic many-body states. The resultant CFT description leads to an intriguing eme

Hans Peter Nilles, Saúl Ramos-Sánchez, Patrick K. S. Vaudrevange

String theory leads to a flavor scheme where modular symmetries play a crucial role. Together with the traditional flavor symmetries they combine to an eclectic flavor group, which we determine via outer automorphisms of the Narain space group. Unbroken flavor symmetries are subgroups of this eclectic group and their size depends on the location in moduli sp

Adam Falkowski, Martín González-Alonso, Oscar Naviliat-Cuncic

Precision measurements in allowed nuclear beta decays and neutron decay are reviewed and analyzed both within the Standard Model and looking for new physics. The analysis incorporates the most recent experimental and theoretical developments. The results are interpreted in terms of Wilson coefficients describing the effective interactions between leptons and

Zhi-Da Song, Biao Lian, Raquel Queiroz, Roni Ilan

The axion insulator is a higher-order topological insulator protected by inversion symmetry. We show that under quenched disorder respecting inversion symmetry {\it on average}, the topology of the axion insulator stays robust, and an intermediate metallic phase in which states are delocalized is unavoidable at the transition from an axion insulator to a tri

Jonathan Crass, Andrew Bechter, Brian Sands, David L. King

Enabling efficient injection of light into single-mode fibers (SMFs) is a key requirement in realizing diffraction-limited astronomical spectroscopy on ground-based telescopes. SMF-fed spectrographs, facilitated by the use of adaptive optics (AO), offer distinct advantages over comparable seeing-limited designs, including higher spectral resolution within a

Csaba Csáki, Sungwoo Hong, Yuri Shirman, Ofri Telem

In this work we extend the definition of asymptotic multi-particle states of the $S$-matrix, beyond the direct products of one-particle states. We identify new quantum numbers which we call pairwise helicities, or $q_{ij}$, associated with asymptotically separated pairs of particles. These signal the appearance of a new source of angular momentum, beyond the

Sandeep Kumar, Arghyadeep Paul, Bhargav Vaidya

Coronal mass ejections (CMEs) and high speed solar streams serve as perturbations to the background solar wind that have major implications in space weather dynamics. Therefore, a robust framework for accurate predictions of the background wind properties is a fundamental step towards the development of any space weather prediction toolbox. In this pilot stu

Michael Y. Grudić

Many astrophysical hydrodynamics simulations must account for gravity, and evaluating the gravitational field at the positions of all resolution elements can incur significant cost. Typical algorithms update the gravitational field at the position of each resolution element every time the element is updated hydrodynamically, but the actual required update fr

Malena Rice, Greg Laughlin

We present results from a new pipeline custom-designed to search for faint, undiscovered solar system bodies using full-frame image data from the NASA Transiting Exoplanet Survey Satellite (TESS) mission. This pipeline removes the baseline flux of each pixel before aligning and co-adding frames along plausible orbital paths of interest. We first demonstrate

Eric R. Coughlin, C. J. Nixon, Adam Ginsburg

Synchrotron-emitting, nonthermal filaments (NTFs) have been observed near the Galactic center for nearly four decades, yet their physical origin remains unclear. Here we investigate the possibility that NTFs are produced by the destruction of molecular clouds by the gravitational potential of the Galactic center. We show that this model predicts the formatio

Denis Erkal, Alis J. Deason, Vasily Belokurov, Xiang-Xiang Xue

A wealth of recent studies have shown that the LMC is likely massive, with a halo mass $>10^{11} M_\odot$. One consequence of having such a nearby and massive neighbour is that the inner Milky Way is expected to be accelerated with respect to our Galaxy's outskirts (beyond $\sim 30$ kpc). In this work we compile a sample of $\sim 500$ stars with radial veloc

Mélanie Chevance, J. M. Diederik Kruijssen, Mark R. Krumholz, Brent Groves

It is a major open question which physical processes stop the accretion of gas onto giant molecular clouds (GMCs) and limit the efficiency at which gas is converted into stars within these GMCs. While feedback from supernova explosions has been the popular feedback mechanism included in simulations of galaxy formation and evolution, `early' feedback mechanis

Sebastian Wagner-Carena, Ji Won Park, Simon Birrer, Philip J. Marshall

In the past few years, approximate Bayesian Neural Networks (BNNs) have demonstrated the ability to produce statistically consistent posteriors on a wide range of inference problems at unprecedented speed and scale. However, any disconnect between training sets and the distribution of real-world objects can introduce bias when BNNs are applied to data. This

L. L. Zhao, D. W. Hogg, M. Bedell, D. A. Fischer

Excalibur is a non-parametric, hierarchical framework for precision wavelength-calibration of spectrographs. It is designed with the needs of extreme-precision radial velocity (EPRV) in mind, which require that instruments be calibrated or stabilized to better than $10^{-4}$ pixels. Instruments vary along only a few dominant degrees of freedom, especially EP

Ramón Aguado

Following the demonstration of semiconductor-based Josephson junctions which are fully tuneable by electrical means, new routes have been opened for the study of hybrid semiconductor-superconductor qubits. These include semiconductor-based transmon qubits, single-spin Andreev qubits, and fault-tolerant topological qubits based on Majorana zero modes. In this

Ethan M. Alt, Matthew A. Psioda, Joseph G. Ibrahim

Given the cost and duration of phase III and phase IV clinical trials, the development of statistical methods for go/no-go decisions is vital. In this paper, we introduce a Bayesian methodology to compute the probability of success based on the current data of a treatment regimen for the multivariate linear model. Our approach utilizes a Bayesian seemingly u

Xiaoyi Dong, Dongdong Chen, Jianmin Bao, Chuan Qin

Modern deep neural networks(DNNs) are vulnerable to adversarial samples. Sparse adversarial samples are a special branch of adversarial samples that can fool the target model by only perturbing a few pixels. The existence of the sparse adversarial attack points out that DNNs are much more vulnerable than people believed, which is also a new aspect for analyz

B. A. Kniehl, V. N. Velizhanin

We compute the nonplanar contribution to the universal anomalous dimension of the SU(4)-singlet twist-two operators in N=4 supersymmetric Yang-Mills theory at four loops through Lorentz spin 18. From this, we numerically evaluate the nonplanar contribution to the four-loop lightlike cusp anomalous dimension and derive the transcendental $\zeta_3$ and $\zeta_

L. F. Quezada, Shi-Hai Dong

In this work we propose a quantum version of a generalized Monty Hall game, that is, one in which the parameters of the game are left free, and not fixed on its regular values. The developed quantum scheme is then used to study the expected payoff of the player, using both a separable and an entangled initial-state. In the two cases, the classical mixed-stra

Xiao Wang, Fa Peng Huang, Xinmin Zhang

The energy budget of cosmological first-order phase transition is essential for the gravitational wave spectra. Most of the previous studies are based on the bag model with same sound velocity in the symmetric and broken phase. We study the energy budget and the corresponding gravitational wave spectra beyond the bag model, where the sound velocities could b

Julian Reichert, Thomas Voigtmann

We derive equations of motion for the mean-squared displacement (MSD) of an active Brownian particle (ABP) in a crowded environment modeled by a dense system of passive Brownian particles, and of a passive tracer particle in a dense active-Brownian particle system, using a projection-operator scheme. The interaction of the tracer particle with the dense host

Nisha Chandramoorthy, Qiqi Wang

This paper proves that shadowing solutions can be almost surely nonphysical. This finding invalidates the argument that small perturbations in a chaotic system can only have a small impact on its statistical behavior. This theoretical finding has implications for many applications in which chaotic mechanics plays an important role. It suggests, for example,

Samuele Tosatto, Georgia Chalvatzaki, Jan Peters

Parameterized movement primitives have been extensively used for imitation learning of robotic tasks. However, the high-dimensionality of the parameter space hinders the improvement of such primitives in the reinforcement learning (RL) setting, especially for learning with physical robots. In this paper we propose a novel view on handling the demonstrated tr

Andrea Richaud, Vittorio Penna, Alexander L. Fetter

We study the massive point-vortex model introduced in Ref. [Phys. Rev. A 101, 013630 (2020)], which describes two-dimensional point vortices of one species that have small cores of a different species. We derive the relevant Lagrangian itself, based on the time-dependent variational method with a two-component Gross-Pitaevskii (GP) trial function. The result

Gintare Karolina Dziugaite, Shai Ben-David, Daniel M. Roy

To date, there has been no formal study of the statistical cost of interpretability in machine learning. As such, the discourse around potential trade-offs is often informal and misconceptions abound. In this work, we aim to initiate a formal study of these trade-offs. A seemingly insurmountable roadblock is the lack of any agreed upon definition of interpre

Julian Reichert, Suvendu Mandal, Thomas Voigtmann

We derive a mode-coupling theory (MCT) to describe the dynamics of tracer particles in dense systems of active Brownian particles (ABPs) in two spatial dimensions. The ABP undergo translational and rotational Brownian dynamics, and are equipped with a fixed self-propulsion speed along their orientational vector that describes their active motility. The resul

Noah W. Tuchow, Jason T. Wright

Future exoplanet direct imaging missions, such as HabEx and LUVOIR, will select target stars to maximize the number of Earth-like exoplanets that can have their atmospheric compositions characterized. Because one of these missions' aims is to detect biosignatures, they should also consider the expected biosignature yield of planets around these stars. In thi

Andrew Hassell, Jan Rozendaal

We consider wave equations with time-independent coefficients that have $C^{1,1}$ regularity in space. We show that, for nontrivial ranges of $p$ and $s$, the standard inhomogeneous initial value problem for the wave equation is well posed in Sobolev spaces $\mathcal{H}^{s,p}_{FIO}(\mathbb{R}^{n})$ over the Hardy spaces $\mathcal{H}^{p}_{FIO}(\mathbb{R}^{n})

Luca Di Luzio, Ramona Gröber, Paride Paradisi

The impact of axion-like particles (ALPs) on the search of permanent electric dipole moments (EDMs) of molecules, atoms, nuclei and nucleons is systematically investigated. We classify first the full set of CP-violating Jarlskog invariants emerging in the ALP effective field theory (EFT) containing operators up to dimension-5. Then, we evaluate the leading s

Cristina Ana-Maria Anghel, Nathan Geer, Bertrand Patureau-Mirand

We examine two different m-traces in the category of representations over the quantum Lie superalgebra associated to $\mathfrak{sl}(m|n)$ at root of unity. The first m-trace is on the ideal of projective modules and leads to new Extended Topological Quantum Field Theories. The second m-trace is on the ideal of perturbative typical modules. We consider the qu

Sukruti Bansal, Silvia Nagy, Antonio Padilla, Ivonne Zavala

Recent progress in understanding de Sitter spacetime in supergravity and string theory has led to the development of a four dimensional supergravity with spontaneously broken supersymmetry allowing for de Sitter vacua, also called de Sitter supergravity. One approach makes use of constrained (nilpotent) superfields, while an alternative one couples supergrav

Quang H. Le, Kamal Youcef-Toumi, Dzmitry Tsetserukou, Ali Jahanian

In design of instance segmentation networks that reconstruct masks, segmentation is often taken as its literal definition -- assigning each pixel a label. This has led to thinking the problem as a template matching one with the goal of minimizing the loss between the reconstructed and the ground truth pixels. Rethinking reconstruction networks as a generator

Yong-Wei Li, Lei Li

We consider a microscopic collision model, i.e., a quantum system interacts with a hierarchical environment consisting of an auxiliary system and a reservoir. We show how the non-Markovian character of the system is influenced by the coupling strength of system-auxiliary system and auxiliary system-reservoir, initial system-environment correlations and the c

Mateo Dutra, Álvaro Suárez, Martín Monteiro, Arturo C. Marti

While Bernoulli's equation is one of the most frequently mentioned topics in Physics literature and other means of dissemination, it is also one of the least understood. Oddly enough, in the wonderful book "Turning the world inside out" [1], Robert Ehrlich proposes a demonstration that consists of blowing a quarter dollar coin into a cup, incorrectly explain

Kay Kirkpatrick, Simone Rademacher, Benjamin Schlein

We consider the many-body quantum evolution of a factorized initial data, in the mean-field regime. We show that fluctuations around the limiting Hartree dynamics satisfy large deviation estimates, that are consistent with central limit theorems that have been established in the last years.

Tongzhou Mu, Jiayuan Gu, Zhiwei Jia, Hao Tang

We study how to learn a policy with compositional generalizability. We propose a two-stage framework, which refactorizes a high-reward teacher policy into a generalizable student policy with strong inductive bias. Particularly, we implement an object-centric GNN-based student policy, whose input objects are learned from images through self-supervised learnin

Jesus Ruiz-Santaquiteria, Alberto Velasco-Mata, Noelia Vallez, Gloria Bueno

Closed-circuit television (CCTV) systems are essential nowadays to prevent security threats or dangerous situations, in which early detection is crucial. Novel deep learning-based methods have allowed to develop automatic weapon detectors with promising results. However, these approaches are mainly based on visual weapon appearance only. For handguns, body p

Rishabh Poddar, Sukrit Kalra, Avishay Yanai, Ryan Deng

Many organizations stand to benefit from pooling their data together in order to draw mutually beneficial insights -- e.g., for fraud detection across banks, better medical studies across hospitals, etc. However, such organizations are often prevented from sharing their data with each other by privacy concerns, regulatory hurdles, or business competition. We

Jinyuan Jia, Binghui Wang, Neil Zhenqiang Gong

In the era of deep learning, a user often leverages a third-party machine learning tool to train a deep neural network (DNN) classifier and then deploys the classifier as an end-user software product or a cloud service. In an information embedding attack, an attacker is the provider of a malicious third-party machine learning tool. The attacker embeds a mess

Jacopo Marcheselli, Denis Chateau, Frederic Lerouge, Patrice Baldeck

Computational modeling and accurate simulations of localized surface plasmon resonance (LSPR) absorption properties are reported for gold nanobipyramids (GNBs), a class of metal nanoparticle that features highly tunable, geometrydependent optical properties. GNB bicone models with spherical tips performed best in reproducing experimental LSPR spectra while t

Zhuangzhuang Dai, Muhamad Risqi U. Saputra, Chris Xiaoxuan Lu, Niki Trigoni

Positional estimation is of great importance in the public safety sector. Emergency responders such as fire fighters, medical rescue teams, and the police will all benefit from a resilient positioning system to deliver safe and effective emergency services. Unfortunately, satellite navigation (e.g., GPS) offers limited coverage in indoor environments. It is

Gemma J. Anderson, Jim A. Gaffney, Brian K. Spears, Peer-Timo Bremer

Large-scale numerical simulations are used across many scientific disciplines to facilitate experimental development and provide insights into underlying physical processes, but they come with a significant computational cost. Deep neural networks (DNNs) can serve as highly-accurate surrogate models, with the capacity to handle diverse datatypes, offering tr

Igor Todoshchenko, Masahiro Kamada, Jukka-Pekka Kaikkonen, Yongping Liao

Low dimensional fermionic quantum systems are exceptionally interesting because they reveal distinctive physical phenomena, including among others, topologically protected excitations, edge states, frustration, and fractionalization. Two-dimensional $^3$He has indeed shown a remarkable variety of phases including the unusual quantum spin liquid. Our aim was

Henry Kenlay, Dorina Thanou, Xiaowen Dong

Graph neural networks are experiencing a surge of popularity within the machine learning community due to their ability to adapt to non-Euclidean domains and instil inductive biases. Despite this, their stability, i.e., their robustness to small perturbations in the input, is not yet well understood. Although there exists some results showing the stability o

Alfredo Braunstein, Giovanni Catania, Luca Dall'Asta, Anna Paola Muntoni

We propose a novel approach to the inverse Ising problem which employs the recently introduced Density Consistency approximation (DC) to determine the model parameters (couplings and external fields) maximizing the likelihood of given empirical data. This method allows for closed-form expressions of the inferred parameters as a function of the first and seco

David Trilling, Carey Lisse, Dale P. Cruikshank, Joshua P. Emery

In its 16 years of scientific measurements, the Spitzer Space Telescope performed a number of ground-breaking infrared measurements of Solar System objects. In this second of two papers, we describe results from Spitzer observations of asteroids, dust rings, and planets that provide new insight into the formation and evolution of our Solar System. The key Sp

Gerard Gilmore, Gudrun Tausch-Pebody

Einstein became world-famous on 7 November 1919, following press publication of a meeting held in London on 6 November 1919 where the results were announced of two British expeditions led by Eddington, Dyson and Davidson to measure how much background starlight is bent as it passes the Sun. Three data sets were obtained: two showed the measured deflection ma

Gilles Pisier

We show that a QWEP von Neumann algebra has the weak* positive approximation property if and only if it is seemingly injective in the following sense: there is a factorization of the identity of $M$ $$Id_M=vu: M{\buildrel u\over\longrightarrow} B(H) {\buildrel v\over\longrightarrow} M$$ with $u$ normal, unital, positive and $v$ completely contractive. As a c

W. F. Fortino, G. M. Bernstein, P. H. Bernardinelli, M. Aguena

Stochastic field distortions caused by atmospheric turbulence are a fundamental limitation to the astrometric accuracy of ground-based imaging. This distortion field is measurable at the locations of stars with accurate positions provided by the Gaia DR2 catalog; we develop the use of Gaussian process regression (GPR) to interpolate the distortion field to a

Carey Lisse, James Bauer, Dale Cruikshank, Josh Emery

In its 16 years of scientific measurements, the Spitzer Space Telescope performed a number of ground breaking and key infrared measurements of Solar System objects near and far. Targets ranged from the smallest planetesimals to the giant planets, and have helped us reform our understanding of these objects while also laying the groundwork for future infrared

Rohini S. Giles, Thomas K. Greathouse, Bertrand Bonfond, G. Randall Gladstone

11 transient bright flashes were detected in Jupiter's atmosphere using the UVS instrument on the Juno spacecraft. These bright flashes are only observed in a single spin of the spacecraft and their brightness decays exponentially with time, with a duration of ~1.4 ms. The spectra are dominated by H2 Lyman band emission and based on the level of atmospheric

Elyes Balti, Brian K. Johnson

In this work, we provide a framework analysis of dual-hop hybrid Millimeter Wave Radio Frequency (RF)/Free Space Optical (FSO) MIMO relaying system. The source is equipped with multiple antennas and employs conjugate beamforming while the destination consists of multiple apertures with selection combining. The system also consists of a relay operating at amp

Rebekka Koch, Alvise Bastianello, Jean-Sébastien Caux

We consider the 1d interacting Bose gas in the presence of time-dependent and spatially inhomogeneous contact interactions. Within its attractive phase, the gas allows for bound states of an arbitrary number of particles, which are eventually populated if the system is dynamically driven from the repulsive to the attractive regime. Building on the framework

Ayan Chakrabarti, Roch Guérin, Chenyang Lu, Jiangnan Liu

To deploy machine learning-based algorithms for real-time applications with strict latency constraints, we consider an edge-computing setting where a subset of inputs are offloaded to the edge for processing by an accurate but resource-intensive model, and the rest are processed only by a less-accurate model on the device itself. Both models have computation

David H. Wu

$\hat{Z}$-invariants, which can reconstruct the analytic continuation of the SU(2) Chern-Simons partition functions via Borel resummation, were discovered by GPV and have been conjectured to be a new homological invariant of 3-manifolds which can shed light onto the superconformal and topologically twisted index of 3d $\mathcal{N}=2$ theories proposed by GPP

Zhiqiang Zhong, Cheng-Te Li, Jun Pang

Recently, increasing attention has been paid to heterogeneous graph representation learning (HGRL), which aims to embed rich structural and semantic information in heterogeneous information networks (HINs) into low-dimensional node representations. To date, most HGRL models rely on hand-crafted meta-paths. However, the dependency on manually-defined meta-pat

Ernesto Araya Valdivia

We consider a latent space model for random graphs where a node $i$ is associated to a random latent point $X_i$ on the Euclidean unit ball. The probability that an edge exists between two nodes is determined by a ``link'' function, which corresponds to a dot product kernel. For a given class $\F$ of spherically symmetric distributions for $X_i$, we consider

Andreas Thum, Diddo Diddens, Andreas Heuer

Polymer electrolytes are intensely investigated for use as solid electrolytes in next generation lithium-ion and lithium-metal batteries. However, little is known about the structural and dynamical properties of polymer electrolytes close to electrode surfaces. Here, a PEO-LiTFSI polymer electrolyte, confined between two oppositely charged graphite-like elec

Alessia Patton, Pablo Antolin, Josef Kiendl, Alessandro Reali

This work focuses on an efficient stress recovery procedure for laminated composite curved structures, which relies on Isogeometric Analysis (IGA) and equilibrium. Using a single element through the thickness in combination with a calibrated layerwise integration rule or a homogenized approach, the 3D solid isogeometric modeling grants an inexpensive and acc

Paul Raymond-Robichaud

We provide a rigorous definition of local realism. We show that the universal wave function cannot be a complete description of a local reality. Finally, we construct a local-realistic model for quantum theory.

Andrés Ortiz, Francisco J. Martinez-Murcia, Marco A. Formoso, Juan Luis Luque

Objective dyslexia diagnosis is not a straighforward task since it is traditionally performed by means of the intepretation of different behavioural tests. Moreover, these tests are only applicable to readers. This way, early diagnosis requires the use of specific tasks not only related to reading. Thus, the use of Electroencephalography (EEG) constitutes an

Stefano Foffa, Riccardo Sturani, William J. Torres Bobadilla

A factorisation property of Feynman diagrams in the context the Effective Field Theory approach to the compact binary problem has been recently employed to efficiently determine the static sector of the potential at fifth post-Newtonian (5PN) order. We extend this procedure to the case of non-static diagrams and we use it to fix, by means of elementary algeb

Aleks Reinhardt, Bingqing Cheng

The phase diagram of water harbours many mysteries: some of the phase boundaries are fuzzy, and the set of known stable phases may not be complete. Starting from liquid water and a comprehensive set of 50 ice structures, we compute the phase diagram at three hybrid density-functional-theory levels of approximation, accounting for thermal and nuclear fluctuat

Daan Rutten, Jaron Sanders

The statistics of strongly interacting, ultracold Rydberg gases are governed by the interplay of two factors: geometrical restrictions induced by blockade effects, and quantum mechanical effects. To shed light on their relative roles in the statistics of Rydberg gases, we compare three models in this paper: a quantum mechanical model describing the excitatio

Kouhei Nakaji, Naoki Yamamoto

In this paper, we propose the quantum semi-supervised generative adversarial network (qSGAN). The system is composed of a quantum generator and a classical discriminator/classifier (D/C). The goal is to train both the generator and the D/C, so that the latter may get a high classification accuracy for a given dataset. The generator needs neither any data loa

Jan Harms, Filippo Ambrosino, Lorella Angelini, Valentina Braito

Monitoring of vibrational eigenmodes of an elastic body excited by gravitational waves was one of the first concepts proposed for the detection of gravitational waves. At laboratory scale, these experiments became known as resonant-bar detectors first developed by Joseph Weber in the 1960s. Due to the dimensions of these bars, the targeted signal frequencies

Nataša Trkulja, David Starobinski, Randall A. Berry

Cellular Vehicle-to-Everything (C-V2X) networks are increasingly adopted by automotive original equipment manufacturers (OEMs). C-V2X, as defined in 3GPP Release 14 Mode 4, allows vehicles to self-manage the network in absence of a cellular base-station. Since C-V2X networks convey safety-critical messages, it is crucial to assess their security posture. Thi

Noah Golowich, Sarath Pattathil, Constantinos Daskalakis

We study the question of obtaining last-iterate convergence rates for no-regret learning algorithms in multi-player games. We show that the optimistic gradient (OG) algorithm with a constant step-size, which is no-regret, achieves a last-iterate rate of $O(1/\sqrt{T})$ with respect to the gap function in smooth monotone games. This result addresses a questio

Wenlin Chen, Samuel Horvath, Peter Richtarik

It is well understood that client-master communication can be a primary bottleneck in Federated Learning. In this work, we address this issue with a novel client subsampling scheme, where we restrict the number of clients allowed to communicate their updates back to the master node. In each communication round, all participating clients compute their updates

Daniel Harsono, Matthijs van der Wiel, Per Bjerkeli, Jon Ramsey

Physical processes that govern the star and planet formation sequence influence the chemical composition and evolution of protoplanetary disks. To understand the chemical composition of protoplanets, we need to constrain the composition and structure of the disks from whence they are formed. We aim to determine the molecular abundance structure of the young

Shuang Wang, Hakan Ferhatosmanoglu

We present PPQ-trajectory, a spatio-temporal quantization based solution for querying large dynamic trajectory data. PPQ-trajectory includes a partition-wise predictive quantizer (PPQ) that generates an error-bounded codebook with autocorrelation and spatial proximity-based partitions. The codebook is indexed to run approximate and exact spatio-temporal quer

Benjamin Braun, Derek Hanely

For each integer partition $\mathbf{q}$ with $d$ parts, we denote by $\Delta_{(1,\mathbf{q})}$ the lattice simplex obtained as the convex hull in $\mathbb{R}^d$ of the standard basis vectors along with the vector $-\mathbf{q}$. For $\mathbf{q}$ with two distinct parts such that $\Delta_{(1,\mathbf{q})}$ is reflexive and has the integer decomposition property

Sarah Braun, Sebastian Albrecht, Sergio Lucia

Many autonomous control systems are frequently exposed to attacks, so methods for attack identification are crucial for a safe operation. To preserve the privacy of the subsystems and achieve scalability in large-scale systems, identification algorithms should not require global model knowledge. We analyze a previously presented method for hierarchical attac

Romain Géneaux, Hung-Tzu Chang, Adam M. Schwartzberg, Hugo J. B. Marroux

Attosecond transient absorption spectroscopy (ATAS) is used to observe photoexcited dynamics with outstanding time resolution. The main experimental challenge of this technique is that high-harmonic generation sources show significant instabilities, resulting in sub-par sensitivity when compared to other techniques. This paper proposes edge-pixel referencing

Floris Geerts, Thomas Muñoz, Cristian Riveros, Domagoj Vrgoč

Linear algebra algorithms often require some sort of iteration or recursion as is illustrated by standard algorithms for Gaussian elimination, matrix inversion, and transitive closure. A key characteristic shared by these algorithms is that they allow looping for a number of steps that is bounded by the matrix dimension. In this paper we extend the matrix qu

Modesar Shakoor, Chung Hae Park

A novel finite element framework is proposed for the numerical simulation of two phase flows with surface tension. The Level-Set (LS) method with piece-wise quadratic (P2) interpolation for the liquid-gas interface is used in order to reach higher-order convergence rates in regions with smooth interface. A balanced-force implementation of the continuum surfa

Pavan C. Madhusudana, Neil Birkbeck, Yilin Wang, Balu Adsumilli

We consider the problem of conducting frame rate dependent video quality assessment (VQA) on videos of diverse frame rates, including high frame rate (HFR) videos. More generally, we study how perceptual quality is affected by frame rate, and how frame rate and compression combine to affect perceived quality. We devise an objective VQA model called Space-Tim

Aitik Gupta, Aadit Agarwal

The outbreak of COVID-19 has forced everyone to stay indoors, fabricating a significant drop in physical activeness. Our work is constructed upon the idea to formulate a backbone mechanism, to detect levels of activeness in real-time, using a single monocular image of a target person. The scope can be generalized under many applications, be it in an intervie

Suryanarayana Sankagiri, Xuechao Wang, Sreeram Kannan, Pramod Viswanath

Longest-chain blockchain protocols, such as Bitcoin, guarantee liveness even when the number of actively participating users is variable, i.e., they are adaptive. However, they are not safe under network partitions, i.e., they do not guarantee finality. On the other hand, classical blockchain protocols, like PBFT, achieve finality but not adaptivity. Indeed,

Alexandre Salas-Bernárdez, Felipe J. Llanes-Estrada, Juan Escudero-Pedrosa, Jose Antonio Oller

Effective Field Theories (EFTs) constructed as derivative expansions in powers of momentum, in the spirit of Chiral Perturbation Theory (ChPT), are a controllable approximation to strong dynamics as long as the energy of the interacting particles remains small, as they do not respect exact elastic unitarity. This limits their predictive power towards new phy

Vyacheslav Babych, Nataliya Golovashchuk

Applying geometric methods of $2$-dimensional cell complex theory, we construct a Galois covering of a bimodule problem satisfying some structure, triangularity and finiteness conditions in order to describe the objects of finite representation type. Each admitted bimodule problem $\mathcal A$ is endowed with a quasi multiplicative basis. The main result sho

Damián Aparicio-Sánchez, Santiago Escobar, Catherine Meadows, Jose Meseguer

We present a framework suited to the analysis of cryptographic protocols that make use of time in their execution. We provide a process algebra syntax that makes time information available to processes, and a transition semantics that takes account of fundamental properties of time. Additional properties can be added by the user if desirable. This timed prot

Cristian Mariani

The Mass Density approach to GRW (GRWm for short) has been widely discussed in the quantum foundations literature. A crucial feature of GRWm is the introduction of a relation of accessibility for mass, which allows to explain the determinacy of experimental outcomes thus also addressing the tails problem of GRW. However, the relation of accessibility leaves

Levi Kassel, Michael Werman

Neural networks are a powerful framework for foreground segmentation in video acquired by static cameras, segmenting moving objects from the background in a robust way in various challenging scenarios. The premier methods are those based on supervision requiring a final training stage on a database of tens to hundreds of manually segmented images from the sp

Fei Gao, Jan M. Pawlowski

We map out the QCD phase structure at finite temperature and chemical potential for 2-flavour and 2 + 1-flavour QCD. This is done within a generalised functional approach to QCD put forward in arXiv:2002.07500 [hep-ph]. Specifically we compute the quark propagator and the finite-temperature and density fluctuations of the gluon propagator and the quark-gluon

Denis Rustand, Janet van Niekerk, Håvard Rue, Christophe Tournigand

Two-part joint models for a longitudinal semicontinuous biomarker and a terminal event have been recently introduced based on frequentist estimation. The biomarker distribution is decomposed into a probability of positive value and the expected value among positive values. Shared random effects can represent the association structure between the biomarker an