October 2020 arXiv papers — page 5

Facundo Rodriguez, Antonio D. Montero-Dorta, Raul E. Angulo, M. Celeste Artale

In this work, we combine size and stellar mass measurements from the Sloan Digital Sky Server (SDSS) with the group finder algorithm of Rodriguez \& Merch\'an in order to determine the stellar and halo mass -- size relations of central and satellite galaxies separately. We show that, while central and satellite galaxies display similar stellar mass -- size r

Myles A. Mitchell, Christian Arnold, César Hernández-Aguayo, Baojiu Li

We study the effects of two popular modified gravity theories, which incorporate very different screening mechanisms, on the angular power spectra of the thermal (tSZ) and kinematic (kSZ) components of the Sunyaev-Zel'dovich effect. Using the first cosmological simulations that simultaneously incorporate both screened modified gravity and a complete galaxy f

Kevin Yang

The paper addresses probabilistic aspects of the KPZ equation and stochastic Burgers equation by providing a solution theory that builds on the energy solution theory Goncalves-Jara '14, Gubinelli-Jara '13, Gubinelli-Perkowski '18, Gubinelli-Perkowski '20. The perspective we adopt is to study the stochastic Burgers equation by writing its solution as a proba

Folkert K. de Vries, Elias Portoles, Giulia Zheng, Takashi Taniguchi

In the past two years, magic-angle twisted bilayer graphene has emerged as a uniquely versatile experimental platform that combines metallic, superconducting, magnetic and insulating phases in a single crystal. In particular the ability to tune the superconducting state with a gate voltage opened up intriguing prospects for novel device functionality. Here w

Yonadav Barry Ginat, Hagai B. Perets

We present a statistical approximate solution of the bound, non-hierarchical three-body problem, and extend it to a general analysis of encounters between hard binary systems and single stars. Any such encounter terminates when one of the three stars is ejected to infinity, leaving behind a remnant binary; the problem of binary-single star-scattering consist

Richard D. Ball, Emanuele R. Nocera, Rosalyn L. Pearson

We evaluate the uncertainties due to nuclear effects in global fits of proton parton distribution functions (PDFs) that utilise deep-inelastic scattering and Drell-Yan data on deuterium targets. To do this we use an iterative procedure to determine proton and deuteron PDFs simultaneously, each including the uncertainties in the other. We apply this procedure

Achilleas Passias, Daniël Prins

We classify supersymmetric warped AdS$_3 \times_w M_7$ backgrounds of Type IIA and Type IIB supergravity with non-constant dilaton, generic RR fluxes and magnetic NSNS flux, in terms of a dynamic $SU(3)$-structure on $M_7$. We illustrate our results by recovering several solutions with various amounts of supersymmetry. The dynamic $SU(3)$-structure includes

Jahan Claes, Eleanor Rieffel, Zhihui Wang

Randomized benchmarking (RB) is a powerful method for determining the error rate of experimental quantum gates. Traditional RB, however, is restricted to gatesets, such as the Clifford group, that form a unitary 2-design. The recently introduced character RB can benchmark more general gates using techniques from representation theory; up to now, however, thi

Martin Fluder, Christoph F. Uhlemann

Renormalization group flows are studied between 5d SCFTs engineered by $(p,q)$ 5-brane webs with large numbers of external 5-branes. A general expression for the free energy on $S^5$ in terms of single-valued trilogarithm functions is derived from their supergravity duals, which are characterized by the 5-brane charges and additional geometric parameters. Th

Yolanda Lozano, Carlos Nunez, Anayeli Ramirez, Stefano Speziali

We present a new infinite family of Type IIB backgrounds with an AdS$_2$ factor, preserving ${\cal N}=4$ SUSY. For each member of the family we propose a precise dual Super Conformal Quantum Mechanics (SCQM). We provide holographic expressions for the number of vacua (the "central charge"), Chern-Simons terms and other non-perturbative aspects of the SCQM. W

Shashank Shalgar, Irene Tamborra

Fast pairwise conversions of neutrinos may affect the flavor distribution in the core of neutrino-dense sources. We explore the interplay between collisions and fast conversions within a simplified framework that assumes angle-independent, direction-changing collisions in a neutrino gas that has no spatial inhomogeneity. Counter to expectations, we find that

Zoe L. de Beurs, Andrew Vanderburg, Christopher J. Shallue, Xavier Dumusque

Exoplanet detection with precise radial velocity (RV) observations is currently limited by spurious RV signals introduced by stellar activity. We show that machine learning techniques such as linear regression and neural networks can effectively remove the activity signals (due to starspots/faculae) from RV observations. Previous efforts focused on carefully

Jiaxuan You, Xiaobai Ma, Daisy Yi Ding, Mykel Kochenderfer

Machine learning with missing data has been approached in two different ways, including feature imputation where missing feature values are estimated based on observed values, and label prediction where downstream labels are learned directly from incomplete data. However, existing imputation models tend to have strong prior assumptions and cannot learn from

Zhentao Tan, Menglei Chai, Dongdong Chen, Jing Liao

Despite the recent success of face image generation with GANs, conditional hair editing remains challenging due to the under-explored complexity of its geometry and appearance. In this paper, we present MichiGAN (Multi-Input-Conditioned Hair Image GAN), a novel conditional image generation method for interactive portrait hair manipulation. To provide user co

Tilman Tröster, Marika Asgari, Chris Blake, Matteo Cataneo

We present constraints on extensions to the flat $\Lambda$CDM cosmological model by varying the spatial curvature $\Omega_K$, the sum of the neutrino masses $\sum m_\nu$, the dark energy equation of state parameter $w$, and the Hu-Sawicki $f(R)$ gravity $f_{R0}$ parameter. With the combined $3\times2$pt measurements of cosmic shear from the Kilo-Degree Surve

Hana Melanova

The traditional study of plane and space algebraic curves by looking at their tangent vectors, curvatures and torsions provides geometric, but unfortunately not sufficient information about individual curves in order to be able to distinguish between two different ones. The aim of this note is to generalize the classical concept of curvature and torsion to s

Pranay Gorantla, Ho Tat Lam, Nathan Seiberg, Shu-Heng Shao

We consider XY-spin degrees of freedom on an FCC lattice, such that the system respects some subsystem global symmetry. We then gauge this global symmetry and study the corresponding $U(1)$ gauge theory on the FCC lattice. Surprisingly, this $U(1)$ gauge theory is dual to the original spin system. We also analyze a similar $\mathbb{Z}_N$ gauge theory on that

Arman, Gargi Tyagi, Prasanta K. Panigrahi

The cat state is shown to `store' a single photon through the superposition of its orthogonal counterpart with itself, and an excited oscillator state. Photon addition leads to a $\pi $ phase shift at origin in the observed phase space interference of the Wigner function, which also displays negativity, controlled by the average photon number ($|\alpha|^2$)

Kartik Ahuja, Jun Wang, Amit Dhurandhar, Karthikeyan Shanmugam

Recently, invariant risk minimization (IRM) was proposed as a promising solution to address out-of-distribution (OOD) generalization. However, it is unclear when IRM should be preferred over the widely-employed empirical risk minimization (ERM) framework. In this work, we analyze both these frameworks from the perspective of sample complexity, thus taking a

Yuzi He, Keith Burghardt, Siyi Guo, Kristina Lerman

Explicit and implicit bias clouds human judgement, leading to discriminatory treatment of minority groups. A fundamental goal of algorithmic fairness is to avoid the pitfalls in human judgement by learning policies that improve the overall outcomes while providing fair treatment to protected classes. In this paper, we propose a causal framework that learns o

Roshan Reddy Yedla, Shiv Ram Dubey

Convolutional neural networks (CNNs) have shown very promising performance in recent years for different problems, including object recognition, face recognition, medical image analysis, etc. However, generally the trained CNN models are tested over the test set which is very similar to the trained set. The generalizability and robustness of the CNN models a

Adam Abed Abud, Giovanna Lehmann, Roland Sipos

Emerging high-performance storage technologies are opening up the possibility of designing new distributed data acquisition system architectures, in which the live acquisition of data and their processing are decoupled through a storage element. An example of these technologies is 3DXPoint, which promises to fill the gap between memory and traditional storag

Abdelhadi Benahmadi, Allal Ghanmi

We introduce two classes of $(p,q)$-It\^o--Hermite polynomials, the post-quantum analogs of the $q$-It\^o--Hermite polynomials introduced recently by Ismail and Zhang. We study their basic properties such as their operational formulas of Rodrigues type, the corresponding raising and lowering operators as well as their generating functions and the $(p,p$-diff

Fiona McCarthy, Mathew S. Madhavacheril

The cosmic infrared background (CIB) sourced by infrared emission from dusty star-forming galaxies is a valuable source of information on the star formation history of the Universe. In measurements of the millimeter sky at frequencies higher than $\sim 300$ GHz, the CIB and thermal emission from Galactic dust dominate. A limited understanding of the CIB cont

Sushanta Tripathy

Recent measurements in high-multiplicity pp and p-A collisions have revealed that these small collision systems exhibit collective-like behaviour, formerly thought to be achievable only in heavy-ion collisions. To understand the origins of these unexpected phenomena, event shape observables can be exploited, as they serve as a powerful tool to disentangle so

Hanhan Li, Ariel Gordon, Hang Zhao, Vincent Casser

We present a method for jointly training the estimation of depth, ego-motion, and a dense 3D translation field of objects relative to the scene, with monocular photometric consistency being the sole source of supervision. We show that this apparently heavily underdetermined problem can be regularized by imposing the following prior knowledge about 3D transla

Olga Zolotareva, Reza Nasirigerdeh, Julian Matschinske, Reihaneh Torkzadehmahani

Aggregating transcriptomics data across hospitals can increase sensitivity and robustness of differential expression analyses, yielding deeper clinical insights. As data exchange is often restricted by privacy legislation, meta-analyses are frequently employed to pool local results. However, if class labels are inhomogeneously distributed between cohorts, th

Simon Kornblith, Ting Chen, Honglak Lee, Mohammad Norouzi

Previous work has proposed many new loss functions and regularizers that improve test accuracy on image classification tasks. However, it is not clear whether these loss functions learn better representations for downstream tasks. This paper studies how the choice of training objective affects the transferability of the hidden representations of convolutiona

Ryne Beeson, N. Sri Namachchivaya, Nicolas Perkowski

This paper considers the approximation of the continuous time filtering equation for the case of a multiple timescale (slow-intermediate, and fast scales) that may have correlation between the slow-intermediate process and the observation process. The signal process is considered fully coupled, taking values in $\mathbb{R^{m}} \times \mathbb{R^{n}}$ and with

Robert Alicki, David Gelbwaser-Klimovsky, Alejandro Jenkins, Elizabeth von Hauff

We propose a dynamical theory of how the chemical energy stored in a battery generates the electromotive force (emf). In this picture, the battery's half-cell acts as an engine, cyclically extracting work from its underlying chemical disequilibrium. We show that the double layer at the electrode-electrolyte interface can exhibit a rapid self-oscillation that

Anand A. Rajasekar, Karthik Raman, Balaraman Ravindran

One challenging and essential task in biochemistry is the generation of novel molecules with desired properties. Novel molecule generation remains a challenge since the molecule space is difficult to navigate through, and the generated molecules should obey the rules of chemical valency. Through this work, we propose a novel method, which we call unitMCTS, t

Juan Hernandez, Robert C. Myers, Shan-Ming Ruan

We examine holographic complexity in the doubly holographic model introduced in [arXiv:2006.04851][arXiv:2010.00018] to study quantum extremal islands. We focus on the holographic complexity=volume (CV) proposal for boundary subregions in the island phase. Exploiting the Fefferman-Graham expansion of the metric and other geometric quantities near the brane,

Panagiotis Paraskevas Filntisis, Niki Efthymiou, Gerasimos Potamianos, Petros Maragos

We present our winning submission to the First International Workshop on Bodily Expressed Emotion Understanding (BEEU) challenge. Based on recent literature on the effect of context/environment on emotion, as well as visual representations with semantic meaning using word embeddings, we extend the framework of Temporal Segment Network to accommodate these. O

Gary Wolfowicz, F. Joseph Heremans, Christopher P. Anderson, Shun Kanai

Defects with associated electron and nuclear spins in solid-state materials have a long history relevant to quantum information science going back to the first spin echo experiments with silicon dopants in the 1950s. Since the turn of the century, the field has rapidly spread to a vast array of defects and host crystals applicable to quantum communication, s

Devidutta Gahan, Ng. K. Francis

Till today lepton flavor violation has not been observed in processes involving charged leptons. Hence, a search for it is under hot pursuit both in theories and experiments. In our current work, we investigate the rates of rare decay processes such as $\tau \rightarrow \mu \gamma$ in SU(5) SUSY GUT and found that it satisfies the current bound and is one or

E. Solano, M. C. Gálvez-Ortiz, E. L. Martín, I. M. Gómez Muñoz

Ultracool dwarfs encompass a wide variety of compact stellar-like objects with spectra classified as late-M, L, T and Y. Most of them have been discovered using wide-field imaging surveys. The Virtual Observatory has proven to be of great utility to efficiently exploit these astronomical resources. We aim to validate a Virtual Observatory methodology designe

Scott B. Lindstrom, Bruno F. Lourenço, Ting Kei Pong

We construct a general framework for deriving error bounds for conic feasibility problems. In particular, our approach allows one to work with cones that fail to be amenable or even to have computable projections, two previously challenging barriers. For the purpose, we first show how error bounds may be constructed using objects called one-step facial resid

Maryam Khosravian, J. L. Lado

Quasiperiodicity has long been known to be a potential platform to explore exotic phenomena, realizing an intricate middle point between ordered solids and disordered matter. In particular, quasiperiodic structures are promising playgrounds to engineer critical wavefunctions, a powerful starting point to engineer exotic correlated states. Here we show that s

Alexey Teplinsky

We introduce a new concept of interval rearrangement ensembles (IRE), which is a generalization of interval exchange transformations (IET). This construction expands the space of IETs in accordance with the natural duality that we pinpoint. Induction of Rauzy\,--\,Veech kind is applicable to IREs. It is conjugate to the reverse operation by the duality menti

Xavier de Carné de Carnavalet, Paul C. van Oorschot

TLS is an end-to-end protocol designed to provide confidentiality and integrity guarantees that improve end-user security and privacy. While TLS helps defend against pervasive surveillance of intercepted unencrypted traffic, it also hinders several common beneficial operations typically performed by middleboxes on the network traffic. Consequently, various m

Qingjie Meng, Jacqueline Matthew, Veronika A. Zimmer, Alberto Gomez

Deep neural networks exhibit limited generalizability across images with different entangled domain features and categorical features. Learning generalizable features that can form universal categorical decision boundaries across domains is an interesting and difficult challenge. This problem occurs frequently in medical imaging applications when attempts ar

Stefan Berg-Johansen, Martin Neugebauer, Andrea Aiello, Gerd Leuchs

Recently, it was shown that vector beams can be utilized for fast kinematic sensing via measurements of their global polarization state [Optica 2(10), 864 (2015)]. The method relies on correlations between the spatial and polarization degrees of freedom of the illuminating field which result from its nonseparable mode structure. Here, we extend the method to

Pavel Záviška, Pavel Rajmic, Ondřej Mokrý

The paper deals with the hitherto neglected topic of audio dequantization. It reviews the state-of-the-art sparsity-based approaches and proposes several new methods. Convex as well as non-convex approaches are included, and all the presented formulations come in both the synthesis and analysis variants. In the experiments the methods are evaluated using the

Umang Mathur, Andreas Pavlogiannis, Mahesh Viswanathan

Concurrent programs are notoriously hard to write correctly, as scheduling nondeterminism introduces subtle errors that are both hard to detect and to reproduce. The most common concurrency errors are (data) races, which occur when memory-conflicting actions are executed concurrently. Consequently, considerable effort has been made towards developing efficie

Jinlong Fan, Jing Zhang, Stephen J. Maybank, Dacheng Tao

Wide field-of-view (FOV) cameras, which capture a larger scene area than narrow FOV cameras, are used in many applications including 3D reconstruction, autonomous driving, and video surveillance. However, wide-angle images contain distortions that violate the assumptions underlying pinhole camera models, resulting in object distortion, difficulties in estima

Priyanka Shende, Manish Purohit

We consider the problem of allocating indivisible objects to agents when agents have strict preferences over objects. There are inherent trade-offs between competing notions of efficiency, fairness and incentives in assignment mechanisms. It is, therefore, natural to consider mechanisms that satisfy two of these three properties in their strongest notions, w

Anton Nazarov, Pavel Nikitin, Olga Postnova

We consider the Plancherel measure on irreducible components of tensor powers of the spinor representation of so(2n+1). The irreducible representations correspond to the generalized Young diagrams. With respect to this measure the probability of an irreducible representation is the product of its multiplicity and dimension, divided by the total dimension of

Srivatsan Chakram, Andrew E. Oriani, Ravi K. Naik, Akash V. Dixit

Multimode cavity quantum electrodynamics ---where a two-level system interacts simultaneously with many cavity modes---provides a versatile framework for quantum information processing and quantum optics. Due to the combination of long coherence times and large interaction strengths, one of the leading experimental platforms for cavity QED involves coupling

Alexis Macq, Maxence Reberol, François Henrotte, Pierre-Alexandre Beaufort

Cross field generation is often used as the basis for the construction of block-structured quadrangular meshes, and the field singularities have a key impact on the structure of the resulting meshes. In this paper, we extend Ginzburg-Landau cross field generation methods with a new formulation that allows a user to impose inner singularities. The cross field

Mengdan Zhu, Bing Ren, Ryland Richards, Matthew Suriawinata

Renal cell carcinoma (RCC) is the most common renal cancer in adults. The histopathologic classification of RCC is essential for diagnosis, prognosis, and management of patients. Reorganization and classification of complex histologic patterns of RCC on biopsy and surgical resection slides under a microscope remains a heavily specialized, error-prone, and ti

Fangdi Wen, Tsung-Chi Wu, Xiaoran Liu, Michael Terilli

Frustrated rare-earth pyrochlore titanates, Yb$_2$Ti$_2$O$_7$, and Tb$_2$Ti$_2$O$_7$ have been proposed as promising candidates to realize quantum spin ice (QSI). Multiple exotic quantum phases, including Coulombic ferromagnet, quantum valence-bond solid, and quadrupolar ordering, have been predicted to emerge in the QSI state upon application of a (111)-ori

Bennett Palmer, Alvaro Pampano

We study critical surfaces for a surface energy which contains the squared $L^2$ norm of the difference of the mean curvature $H$ and the spontaneous curvature $c_o$, coupled to the elastic energy of the boundary curve. We investigate the existence of equilibria with $H\equiv -c_o$. When $c_o \ge 0$ we characterize those cases where the infimum of this energ

Sylvain Zalczer

We consider the random Dirac operators for which we have proved Anderson localization in arXiv:1812.01868. We use the Wegner estimate we have got in that paper to prove Lipschitz regularity of the density of states. Since usual methods for Schr\"odinger operators do not work in this case, we give a new one based on the Helffer-Sj\"ostrand formula.

Gábor Drótos, Emilio Hernández-García, Cristóbal López

To characterize local finite-time properties associated with transient chaos in open dynamical systems, we introduce an escape rate and fractal dimensions suitable for this purpose in a coarse-grained description. We numerically illustrate that these quantifiers have a considerable spread across the domain of the dynamics, but their spatial variation, especi

Vlatko Vedral

Unperformed measurements have no results. Unobserved results can affect future measurements.

Mason J. Guffey, Alfred Y. Wong

A scheme is presented to catalyze nuclear fusion by the excitation of the localized surface plasmon resonance (LSPR) of an Au nanobipyramid (NBP) by ultrafast (femtosecond) laser pulses. The effect utilizes the exceptionally high electric field enhancement provided by the Au NBP LSPR, localized to nm^3 volumes and fs time scales, to produce a ponderomotive f

Sayan Bhattacharya, Fabrizio Grandoni, David Wajc

Nearly thirty years ago, Bar-Noy, Motwani and Naor [IPL'92] conjectured that an online $(1+o(1))\Delta$-edge-coloring algorithm exists for $n$-node graphs of maximum degree $\Delta=\omega(\log n)$. This conjecture remains open in general, though it was recently proven for bipartite graphs under \emph{one-sided vertex arrivals} by Cohen et al.~[FOCS'19]. In a

P. B. Ivanov, J. C. B. Papaloizou

We consider the evolution of a binary system interacting due to tidal effects without restriction on the orientation of the orbital, and where significant, spin angular momenta, and orbital eccentricity. We work in the low tidal forcing frequency regime in the equilibrium tide approximation. Internal degrees of freedom are fully taken into account for one co

Alexander Björling, Lucas A. B. Marçal, José Solla-Gullón, Jesper Wallentin

Bragg Coherent Diffraction Imaging (BCDI) is a powerful strain imaging tool, often limited by beam-induced sample instability for small particles and high power densities. Here, we devise and validate an adapted diffraction volume assembly algorithm, capable of recovering three-dimensional datasets from particles undergoing uncontrolled and unknown rotations

Francisco Ferreira da Silva, Ariana Torres-Knoop, Tim Coopmans, David Maier

Long-distance quantum communication via entanglement distribution is of great importance for the quantum internet. However, scaling up to such long distances has proved challenging due to the loss of photons, which grows exponentially with the distance covered. Quantum repeaters could in theory be used to extend the distances over which entanglement can be d

Afef Cherni, Sandrine Anthoine, Caroline Chaux

Nuclear Magnetic Resonance (NMR) spectroscopy is an efficient technique to analyze chemical mixtures in which one acquires spectra of the chemical mixtures along one ore more dimensions. One of the important issues is to efficiently analyze the composition of the mixture, this is a classical Blind Source Separation (BSS) problem. The poor resolution of NMR s

Cathelijne ter Burg, Kay Joerg Wiese

Mean-field theory is an approximation replacing an extended system by a few variables. For depinning of elastic manifolds, these are the position of its center of mass $u$, and the statistics of the forces $F(u)$. There are two proposals to model the latter: as a random walk (ABBM model), or as uncorrelated forces at integer $u$ (discretized particle model,

Gene S. Kopp

We prove an analogue of Kronecker's second limit formula for a continuous family of "indefinite zeta functions". Indefinite zeta functions were introduced in the author's previous paper as Mellin transforms of indefinite theta functions, as defined by Zwegers. Our formula is valid in dimension g=2 at s=1 or s=0. For a choice of parameters obeying a certain s

Alexandre Daoud

We investigate a question of Burns and Sano concerning the structure of the module of Euler systems for a general $p$-adic representation. Assuming the weak Leopoldt conjecture, and the vanishing of $\mu$-invariants of natural Iwasawa modules, we obtain an Iwasawa-theoretic classification criterion for Euler systems which can be used to study this module. Th

Derek Singh, Shuzhong Zhang

This paper expands the work on distributionally robust newsvendor to incorporate moment constraints. The use of Wasserstein distance as the ambiguity measure is preserved. The infinite dimensional primal problem is formulated; problem of moments duality is invoked to derive the simpler finite dimensional dual problem. An important research question is: How d

Jeffrey Cohen, Clark Alexander

We analyze 3,171 US common stocks to create an efficient portfolio based on the Chicago Quantum Net Score (CQNS) and portfolio optimization. We begin with classical solvers and incorporate quantum annealing. We add a simulated bifurcator as a new classical solver and the new D-Wave Advantage(TM) quantum annealing computer as our new quantum solver.

Wei Zhou, Simon Berger, Ralf Schlüter, Hermann Ney

To join the advantages of classical and end-to-end approaches for speech recognition, we present a simple, novel and competitive approach for phoneme-based neural transducer modeling. Different alignment label topologies are compared and word-end-based phoneme label augmentation is proposed to improve performance. Utilizing the local dependency of phonemes,

Sebastian Goette, Johannes Nordström, Don Zagier

We analyse the possible ways of gluing twisted products of circles with asymptotically cylindrical Calabi-Yau manifolds to produce manifolds with holonomy G_2, thus generalising the twisted connected sum construction of Kovalev and Corti, Haskins, Nordstr\"om, Pacini. We then express the extended nu-invariant of Crowley, Goette, and Nordstr\"om arXiv:1505.02

Marzieh Eidi, Amirhossein Farzam, Wilmer Leal, Areejit Samal

The relations, rather than the elements, constitute the structure of networks. We therefore develop a systematic approach to the analysis of networks, modelled as graphs or hypergraphs, that is based on structural properties of (hyper)edges, instead of vertices. For that purpose, we utilize so-called network curvatures. These curvatures quantify the local st

Adam Doliwa, Runliang Lin, Zhe Wang

The discrete non-commutative Darboux system of equations with self-consistent sources is constructed, utilizing both the vectorial fundamental (binary Darboux) transformation and the method of additional independent variables. Then the symmetric reduction of discrete Darboux equations with sources is presented. In order to provide a simpler version of the re

Daniel Fernex, Bernd R. Noack, Richard Semaan

We propose a universal method for data-driven modeling of complex nonlinear dynamics from time-resolved snapshot data without prior knowledge. Complex nonlinear dynamics govern many fields of science and engineering. Data-driven dynamic modeling often assumes a low-dimensional subspace or manifold for the state. We liberate ourselves from this assumption by

Gregory Yauney, Jack Hessel, David Mimno

Images can give us insights into the contextual meanings of words, but current image-text grounding approaches require detailed annotations. Such granular annotation is rare, expensive, and unavailable in most domain-specific contexts. In contrast, unlabeled multi-image, multi-sentence documents are abundant. Can lexical grounding be learned from such docume

Alexey Lebedev, Vladimir Lebedev, Nikita Polyanskii

In this paper, we discuss two-stage encoding algorithms capable of correcting a fraction of asymmetric errors. Suppose that the encoder transmits $n$ binary symbols $(x_1,\ldots,x_n)$ one-by-one over the Z-channel, in which a 1 is received only if a 1 is transmitted. At some designated moment, say $n_1$, the encoder uses noiseless feedback and adjusts furthe

Cory Hayes, Matthew Marge

We are interested in the design of autonomous robot behaviors that learn the preferences of users over continued interactions, with the goal of efficiently executing navigation behaviors in a way that the user expects. In this paper, we discuss our work in progress to modify a general model for robot navigation behaviors in an exploration task on a per-user

Nuno Picado, Paulo Eduardo Oliveira

Let $\mathcal{M}$ be a compact manifold of $\mathbb{R}^d$. The goal of this paper is to decide, based on a sample of points, whether the interior of $\mathcal{M}$ is empty or not. We divide this work in two main parts. Firstly, under a dependent sample which may or may not contain some noise within, we characterize asymptotic properties of an interior detect

Haixiang Zhang, Zeyu Zheng, Javad Lavaei

We propose new sequential simulation-optimization algorithms for general convex optimization via simulation problems with high-dimensional discrete decision space. The performance of each choice of discrete decision variables is evaluated via stochastic simulation replications. If an upper bound on the overall level of uncertainties is known, our proposed si

Sepideh Bakhoda, Hossein Shojaie, Thomas Thiemann

A generally covariant $U(1)^3$ gauge theory describing the $G_N \to 0$ limit of Euclidean general relativity is an interesting test laboratory for general relativity, specially because the algebra of the Hamiltonian and diffeomorphism constraints of this limit is isomorphic to the algebra of the corresponding constraints in general relativity. In the present

Romain Egele, Prasanna Balaprakash, Venkatram Vishwanath, Isabelle Guyon

Developing high-performing predictive models for large tabular data sets is a challenging task. The state-of-the-art methods are based on expert-developed model ensembles from different supervised learning methods. Recently, automated machine learning (AutoML) is emerging as a promising approach to automate predictive model development. Neural architecture s

Z. C. Zhang, B. J. Xiao, Z. S. Ji, Y. Wang

The Experimental Advanced Superconducting Tokamak (EAST), a nation-level large-scale scientific project of China, plays a key role for the research of peaceful utilizations of fusion energy. The safety and interlock system (SIS) is in charge of the supervision and control of all the EAST components involved in the protection of human and tokamak from potenti

Ridam Pal, Rohan Pandey, Vaibhav Gautam, Kanav Bhagat

The COVID-19 pandemic has put immense pressure on health systems which are further strained due to the misinformation surrounding it. Under such a situation, providing the right information at the right time is crucial. There is a growing demand for the management of information spread using Artificial Intelligence. Hence, we have exploited the potential of

Viktor Stojkoski

Recent studies suggest that the emergence of cooperative behavior can be explained by generalized reciprocity, a behavioral mechanism based on the principle of "help anyone if helped by someone". In complex systems, the cooperative dynamics is largely determined by the network structure which dictates the interactions among neighboring individuals. Despite a

G. M. Gorman, M. K. Warrens, S. J. Bradshaw, T. C. Killian

We demonstrate magnetic confinement of an ultracold neutral plasma (UCNP) created at the null of a biconic cusp, or quadrupole magnetic field. Initially, the UCNP expands due to electron thermal pressure. As the plasma encounters stronger fields, expansion slows and the density distribution molds to the field. UCNP electrons are strongly magnetized over most

Alex H. Ardila

In this paper, we investigate the global well-posedness and $H^{1}$ scattering theory for a 3d energy-critical Schr\"odinger equation under the influence of magnetic dipole interaction $\lambda_{1}|u|^{2}u+\lambda_{2}(K\ast|u|^{2})u$, where $K$ is the dipole-dipole interaction kernel. Our proof of global well-posedness result is based on the argument of Zhan

Long Pham, Jan Hoffmann

Being a fully automated technique for resource analysis, automatic amortized resource analysis (AARA) can fail in returning worst-case cost bounds of programs, fundamentally due to the undecidability of resource analysis. For programmers who are unfamiliar with the technical details of AARA, it is difficult to predict whether a program can be successfully an

G. Bezhanishvili, L. Carai, P. Morandi

We introduce an endofunctor $H$ on the category $bal$ of bounded archimedean $\ell$-algebras and show that there is a dual adjunction between the category $Alg(H)$ of algebras for $H$ and the category $Coalg(V)$ of coalgebras for the Vietoris endofunctor $V$ on the category of compact Hausdorff spaces. We also introduce an endofunctor $Hu$ on the reflective

Sepideh Bakhoda, Thomas Thiemann

If one replaces the constraints of the Ashtekar-Barbero $SU(2)$ gauge theory formulation of Euclidean gravity by their $U(1)^3$ version, one arrives at a consistent model which captures significant structure of its $SU(2)$ version. In particular, it displays a non trivial realisation of the hypersurface deformation algebra which makes it an interesting testi

Samuël Borza

We compute the distortion coefficients of the $\alpha$-Grushin plane. They are expressed in terms of generalised trigonometric functions. Estimates for the distortion coefficients are then obtained and a conjecture of a synthetic curvature condition for the generalised Grushin planes is suggested.

Joon Young Park, Janghyun Jo, Jennifer A. Sears, Young-June Kim

Combining various two-dimensional materials into novel van der Waals (vdW) heterostructures has been shown to lead to new emergent quantum systems. A novel heterostructure composed of a vdW topological insulator (TI) such as Bi$_{2}$Se$_{3}$ with a quantum spin liquid (QSL) such as $\alpha$-RuCl$_{3}$ is of great interest for the potential for the chiral Dir

Mitt Shah, Nandit Pujara

Software quality is one of the essential aspects of a software. With increasing demand, software designs are becoming more complex, increasing the probability of software defects. Testers improve the quality of software by fixing defects. Hence the analysis of defects significantly improves software quality. The complexity of software also results in a highe

Jiaju Zhang, M. A. Rajabpour

We investigate the energy eigenstate R\'enyi entropy of generic bipartition in the fermionic, bosonic, and spin-1/2 XY chains. When the gap of the theory is large or all the momenta of the excited quasiparticles are large, the R\'enyi entropy takes a universal form, which is independent of the model, the quasiparticle momenta, and the subsystem connectedness

Simon Becker, Anders Hansen

We address the open problem of determining which classes of time-dependent linear Schr\"odinger equations and focusing and defocusing cubic and quintic non-linear Schr\"odinger equations (NLS) on unbounded domains that can be computed by an algorithm. We demonstrate how such an algorithm in general does not exist, yielding a substantial classification theory

Joachim Toft, Divyang Bhimani, Ramesh Manna

We deduce trace properties for modulation spaces of Gelfand-Shilov distributions. We use these properties to show that pseudo-differential operators with amplitudes in suitable modulation spaces, agree with pseudo-differential operators of normal type whose symbols belong to (other) modulation spaces.

Alastair Reid, Luke Church, Shaked Flur, Sarah de Haas

Formal verification of software is a bit of a niche activity: it is only applied to the most safety-critical or security-critical software and it is typically only performed by specialized verification engineers. This paper considers whether it would be possible to increase adoption of formal methods by integrating formal methods with developers' existing pr

Fergus Simpson, Vidhi Lalchand, Carl Edward Rasmussen

Gaussian Process (GPs) models are a rich distribution over functions with inductive biases controlled by a kernel function. Learning occurs through the optimisation of kernel hyperparameters using the marginal likelihood as the objective. This classical approach known as Type-II maximum likelihood (ML-II) yields point estimates of the hyperparameters, and co

Phan Nhut Huan, Nguyen Le Anh, Bui Minh Loc, Isaac Vidana

Differential cross sections of ($p,n$) and ($^3$He,$t$) charge-exchange reactions leading to the excitation of the isobaric analog state (IAS) of the target nucleus are calculated with the distorted wave Born approximation. The $G$-matrix double-folding method is employed to determine the nucleus-nucleus optical potential within the framework of the Lane mod

Kartik Paigwar, Lokesh Krishna, Sashank Tirumala, Naman Khetan

In this paper, with a view toward fast deployment of locomotion gaits in low-cost hardware, we use a linear policy for realizing end-foot trajectories in the quadruped robot, Stoch $2$. In particular, the parameters of the end-foot trajectories are shaped via a linear feedback policy that takes the torso orientation and the terrain slope as inputs. The corre

Javier Fuentes-Martin, Pedro Ruiz-Femenia, Avelino Vicente, Javier Virto

$\tt DsixTools$ is a Mathematica package for the handling of the Standard Model Effective Field Theory (SMEFT) and the Low-energy Effective Field Theory (LEFT) with operators up to dimension six, both at the algebraic and numerical level. $\tt DsixTools$ contains a visually accessible and operationally convenient repository of all operators and parameters of

Yuval Moskovitch, H. V. Jagadish

Counts of attribute-value combinations are central to the profiling of a dataset, particularly in determining fitness for use and in eliminating bias and unfairness. While counts of individual attribute values may be stored in some dataset profiles, there are too many combinations of attributes for it to be practical to store counts for each combination. In

Gianira N. Alfarano, Martino Borello, Alessandro Neri, Alberto Ravagnani

We develop three approaches of combinatorial flavour to study the structure of minimal codes and cutting blocking sets in finite geometry, each of which has a particular application. The first approach uses techniques from algebraic combinatorics, describing the supports in a linear code via the Alon-F\"uredi Theorem and the Combinatorial Nullstellensatz. Th

R. A. Bailey, Peter J. Cameron, Michael Kinyon, Cheryl E. Praeger

In an earlier paper by three of the present authors and Csaba Schneider, it was shown that, for $m\ge2$, a set of $m+1$ partitions of a set $\Omega$, any $m$ of which are the minimal non-trivial elements of a Cartesian lattice, either form a Latin square (if $m=2$), or generate a join-semilattice of dimension $m$ associated with a diagonal group over a base