June 2020 arXiv papers — page 8

Jean-Baptiste Cordonnier, Andreas Loukas, Martin Jaggi

Attention layers are widely used in natural language processing (NLP) and are beginning to influence computer vision architectures. Training very large transformer models allowed significant improvement in both fields, but once trained, these networks show symptoms of over-parameterization. For instance, it is known that many attention heads can be pruned wi

Christian Gaetz, Katherine Tung

A well-known result of Stanley from 1980 implies that the weak order on a maximal parabolic quotient of the symmetric group $S_n$ has the Sperner property; this same property was recently established for the weak order on all of $S_n$ by Gaetz and Gao, resolving a long-open problem. In this paper we interpolate between these results by showing that the weak

Victor Beresnevich, Sanju Velani

In this chapter we introduce the theory of Diophantine approximation via a series of basic examples from information theory relevant to wireless communications. In particular, we discuss Dirichlet's theorem, badly approximable points, Dirichlet improvable and singular points, the metric (probabilistic) theory of Diophantine approximation including the Kh

Iván Blanco-Chacón

We propose and justify a generalised approach to prove the polynomial reduction of the RLWE to the PLWE problem attached to the ring of integers of a monogenic number field. We prove such equivalence in the case of the maximal totally real subextension of the 4p-th cyclotomic field, with p arbitrary prime.

Patrick Fraser

Quantum resource theory is a cutting-edge tool used to study practical implementations of quantum mechanical principles under realistic operational constraints. It does this by modelling quantum systems as restricted classes of possible or permissible experimental operations. Modal logic provides a formal tool for studying possibility and impossibility is a

Abdulkadir Şeker, Banu Diri, Halil Arslan

Open-source code development has become widespread in recent years. As a result, open-source software platforms have also become popular, and millions of developers from diverse locations are able to contribute to the same projects. On these platforms, various knowledge about them is obtained from user activity. This information is used in the form of develo

Ana M. Ospina, Emiliano Dall'Anese

Estimation of sensitivity matrices in electrical transmission systems allows grid operators to evaluate in real-time how changes in power injections reflect into changes in power flows. In this paper, we propose a robust low-rank minimization approach to estimate sensitivity matrices based on measurements of power injections and power flows. An online proxim

Andrea Mondelli, Paul Gazzillo, Yan Solihin

One of the most prevalent source of side channel vulnerabilities is the secret-dependent behavior of conditional branches (SDBCB). The state-of-the-art solution relies on Constant-Time Expressions, which require high programming effort and incur high performance overheads. In this paper, we propose SeMPE, an approach that relies on architecture support to el

Hadi Mahami, Navid Ghassemi, Mohammad Tayarani Darbandy, Afshin Shoeibi

Recent advancements in Artificial intelligence, especially deep learning, has changed many fields irreversibly by introducing state of the art methods for automation. Construction monitoring has not been an exception; as a part of construction monitoring systems, material classification and recognition have drawn the attention of deep learning and machine vi

Fanglin Linda Liu, Grace Kuo, Nick Antipa, Kyrollos Yanny

Light field microscopy (LFM) uses a microlens array (MLA) near the sensor plane of a microscope to achieve single-shot 3D imaging of a sample without any moving parts. Unfortunately, the 3D capability of LFM comes with a significant loss of lateral resolution at the focal plane. Placing the MLA near the pupil plane of the microscope, instead of the image pla

Giovanni Sutanto, Katharina Rombach, Yevgen Chebotar, Zhe Su

Robots need to be able to adapt to unexpected changes in the environment such that they can autonomously succeed in their tasks. However, hand-designing feedback models for adaptation is tedious, if at all possible, making data-driven methods a promising alternative. In this paper we introduce a full framework for learning feedback models for reactive motion

E. Bergou, Y. Diouane, V. Kungurtsev, C. W. Royer

Least squares form one of the most prominent classes of optimization problems, with numerous applications in scientific computing and data fitting. When such formulations aim at modeling complex systems, the optimization process must account for nonlinear dynamics by incorporating constraints. In addition, these systems often incorporate a large number of va

Junxian He, Taylor Berg-Kirkpatrick, Graham Neubig

Prototype-driven text generation uses non-parametric models that first choose from a library of sentence "prototypes" and then modify the prototype to generate the output text. While effective, these methods are inefficient at test time as a result of needing to store and index the entire training corpus. Further, existing methods often require heuri

Florian Huber, Luca Rossini

Vector autoregressive (VAR) models assume linearity between the endogenous variables and their lags. This assumption might be overly restrictive and could have a deleterious impact on forecasting accuracy. As a solution, we propose combining VAR with Bayesian additive regression tree (BART) models. The resulting Bayesian additive vector autoregressive tree (

A. S. Maniyar, M. Béthermin, G. Lagache

Modelling the anisotropies in the CIB on all the scales is a challenging task due to the complex nature of the galaxy evolution and thus often requires too many parameters in order to fit the observational data. In this paper, we present a new halo model for the anisotropies of the CIB using only four parameters. Our model connects the mass accretion on the

Michael P. Landry

We show that a veering triangulation $τ$ specifies a face $σ$ of the Thurston norm ball of a closed three-manifold, and computes the Thurston norm in the cone over $σ$. Further, we show that $τ$ collates exactly the taut surfaces representing classes in the cone over $σ$ up to isotopy. The analysis includes nonlayered veering triangulations and nonfibered fa

Subham Sekhar Sahoo, Subhashini Venugopalan, Li Li, Rishabh Singh

Symbolic techniques based on Satisfiability Modulo Theory (SMT) solvers have been proposed for analyzing and verifying neural network properties, but their usage has been fairly limited owing to their poor scalability with larger networks. In this work, we propose a technique for combining gradient-based methods with symbolic techniques to scale such analyse

Aliza Abraham, Luis A. Martinez-Tossas, Jiarong Hong

The current study uses large eddy simulations to investigate the transient response of a utility-scale wind turbine wake to dynamic changes in atmospheric and operational conditions, as observed in previous field-scale measurements. Most wind turbine wake investigations assume quasi-steady conditions, but real wind turbines operate in a highly stochastic atm

Akshay Bhardwaj, Daniel Slavin, John Walsh, James Freudenberg

The force transmitted from the front tires to the steering rack of a vehicle, called the rack force, plays an important role in the function of electric power steering (EPS) systems. Estimates of rack force can be used by EPS to attenuate road feedback and reduce driver effort. Further, estimates of the components of rack force (arising, for example, due to

Yi Wan, Abhishek Naik, Richard S. Sutton

We introduce learning and planning algorithms for average-reward MDPs, including 1) the first general proven-convergent off-policy model-free control algorithm without reference states, 2) the first proven-convergent off-policy model-free prediction algorithm, and 3) the first off-policy learning algorithm that converges to the actual value function rather t

Viraj Pandya, Rachel S. Somerville, Daniel Anglés-Alcázar, Christopher C. Hayward

Semi-analytic models (SAMs) are a promising means of tracking the physical processes associated with galaxy formation, but many of their approximations have not been rigorously tested. As part of the SMAUG (Simulating Multiscale Astrophysics to Understand Galaxies) project, we compare predictions from the FIRE-2 hydrodynamical "zoom-in" simulations t

Chang-Goo Kim, Eve C. Ostriker, Rachel S. Somerville, Greg L. Bryan

Large scale outflows in star-forming galaxies are observed to be ubiquitous, and are a key aspect of theoretical modeling of galactic evolution in a cosmological context, the focus of the SMAUG (Simulating Multiscale Astrophysics to Understand Galaxies) project. Gas blown out from galactic disks, similar to gas within galaxies, consists of multiple phases wi

Bhawna Motwani, Shy Genel, Greg L. Bryan, Chang-Goo Kim

Physical and chemical properties of the interstellar medium (ISM) at sub-galactic ($\sim$kpc) scales play an indispensable role in controlling the ability of gas to form stars. As part of the SMAUG (Simulating Multiscale Astrophysics to Understand Galaxies) project, in this paper, we use the TNG50 cosmological simulation to explore the physical parameter spa

Clinton DeW. Van Siclen

The effective conductivity of the infinite checkerboard (chessboard) and analogous higher-dimensional checkered structures, are considered. An algebraic expression is derived by accounting for the symmetries of the structures.

X. S. Wang, Arne Brataas, Roberto E. Troncoso

We investigate the role of disorder on the various topological magnonic phases present in deformed honeycomb ferromagnets. To this end, we introduce a bosonic Bott index to characterize the topology of magnon spectra in finite, disordered systems. The consistency between the Bott index and Chern number is numerically established in the clean limit. We demons

Mario Arduini, Lorenzo Noci, Federico Pirovano, Ce Zhang

Knowledge Graphs (KG) are gaining increasing attention in both academia and industry. Despite their diverse benefits, recent research have identified social and cultural biases embedded in the representations learned from KGs. Such biases can have detrimental consequences on different population and minority groups as applications of KG begin to intersect an

Cressida Cleland, Sean McGee

By combining H$α$ flux measurements from the Sloan Digital Sky Survey (SDSS) with UV flux observations from the Galaxy Evolution Explorer (GALEX), we examine the environmental dependence (through central/satellite distinction) of the rapid quenching and rejuvenation of galaxies. H$α$ emissions trace the most massive stars, thereby indicating star-formation o

Travis Dillon, Attila Sali

The forbidden number $\mathrm{forb}(m,F)$, which denotes the maximum number of unique columns in an $m$-rowed $(0,1)$-matrix with no submatrix that is a row and column permutation of $F$, has been widely studied in extremal set theory. Recently, this function was extended to $r$-matrices, whose entries lie in $\{0,1,\dots,r-1\}$. The combinatorics of the gen

Jorge Mellado Muñoz, Rahul Sawant, Anna Maffei, Xi Wang

We propose a method to realize the Frenkel-Kontorova model using an array of Rydberg dressed atoms. Our platform can be used to study this model with a range of realistic interatomic potentials. In particular, we concentrate on two types of interaction potentials: a springlike potential and a repulsive long-range potential. We numerically calculate the phase

A. A. Lima, G. M. Sotkov, M. Stanishkov

We study two families of composite twisted Ramond fields (made by products of two operators) in the $\cal {N}=(4,4)$ supersymmetric D1-D5 SCFT$_2$ deformed by a marginal modulus operator away from its $(T^4)^N/ S_N$ free orbifold point. We construct the large-$N$ contributions to the four-point functions with two composite operators and two deformation field

Nicolas Gauthier, Jonathan A. Sobota, Makoto Hashimoto, Heike Pfau

Quantum well states appear in metallic thin films due to the confinement of the wave function by the film interfaces. Using angle-resolved photoemission spectroscopy, we unexpectedly observe quantum well states in fractured single crystals of CeCoIn$_5$. We confirm that confinement occurs by showing that these states' binding energies are photon-energy i

Jia Wang, Ardita Kilaj, Lanhai He, Karol Długołęcki

Methyl vinyl ketone (C$_4$H$_6$O) is a volatile, labile organic compound of importance in atmospheric chemistry. We prepared a molecular beam of methyl vinyl ketone with a rotational temperature of 1.2(2)~K and demonstrated the spatial separation of the \emph{s-cis} and \emph{s-trans} conformers of methyl vinyl ketone using the electrostatic deflector. The r

Charles T. Sebens

This article compares treatments of the Stern-Gerlach experiment across different physical theories, building up to a novel analysis of electron spin measurement in the context of classical Dirac field theory. Modeling the electron as a classical rigid body or point particle, we can explain why the entire electron is always found at just one location on the

Hung Tan, Jacquelyn Noronha-Hostler, Nico Yunes

The observation of gravitational waves from an asymmetric binary opens the possibility for heavy neutron stars, but these pose challenges to models of the neutron star equation of state. We construct heavy neutron stars by introducing non-trivial structure in the speed of sound sourced by deconfined QCD matter, which cannot be well recovered by spectral repr

Anuj Tiwari, Santosh Devasia

Rapid transitions are important for quick response of consensus-based, multi-agent networks to external stimuli. While high-gain can increase response speed, potential instability tends to limit the maximum possible gain, and therefore, limits the maximum convergence rate to consensus during transitions. Since the update law for multi-agent networks with sym

John Bergdall, Brandon Levin, Tong Liu

We determine reductions of 2-dimensional, irreducible, semi-stable, and non-crystalline representations of $\mathrm{Gal}(\overline{\mathbb Q}_p/\mathbb Q_p)$ with Hodge--Tate weights $0 < k-1$ and with $\mathcal L$-invariant whose $p$-adic norm is sufficiently large, depending on $k$. Our main result provides the first systematic examples of the reductions f

Marco Bonvini

We consider the problem of quantifying the uncertainty on theoretical predictions based on perturbation theory due to missing higher orders. The most widely used approach, scale variation, is largely arbitrary and it has no probabilistic foundation, making it not suitable for robust data analysis. In 2011, Cacciari and Houdeau proposed a model based on a Bay

Ning Bao, Newton Cheng, Sergio Hernández-Cuenca, Vincent Paul Su

It was recently found that the stabilizer and hypergraph entropy cones coincide for four parties, leading to a conjecture of their equivalence at higher party numbers. In this note, we show this conjecture to be false by proving new inequalities obeyed by all hypergraph entropy vectors that exclude particular stabilizer states on six qubits. By further lever

Patryk Lipka-Bartosik, Paul Skrzypczyk

Quantum catalysis is a fascinating concept which demonstrates that certain transformations can only become possible when given access to a specific resource that has to be returned unaffected. It was first discovered in the context of entanglement theory and since then applied in a number of resource-theoretic frameworks, including quantum thermodynamics. Al

Raphael Bousso, Elizabeth Wildenhain

For the first time, a gravitational calculation was recently shown to yield the Page curve for the entropy of Hawking radiation, consistent with unitary evolution. However, the calculation takes as essential input Hawking&#39;s result that the radiation entropy becomes large at late times. We call this apparent contradiction the state paradox. We exhibit its

Elizabeth Milićević, Petra Schwer, Anne Thomas

We characterize the nonemptiness and dimension problems for an affine Deligne-Lusztig variety $X_x(b)$ in the affine flag variety in terms of galleries that are positively folded with respect to a chimney. If the parabolic subgroup associated to the Newton point of b has rank 1, we then prove nonemptiness for a certain class of Iwahori-Weyl group elements x

Helmer H. Koppelman, Amina Helmi

The {\it Gaia} mission has provided the largest catalogue ever of sources with tangential velocity information. However, using this catalogue for dynamical studies is difficult because most of the stars lack line-of-sight velocity measurements. Recently, we presented a selection of $\sim 10^7$ halo stars with accurate distances that have been selected based

Hirotsugu Fujii, Cyrille Marquet, Kazuhiro Watanabe

For studying small-$x$ gluon saturation in forward dijet production in high-energy dilute-dense collisions, the improved TMD (ITMD) factorization formula was recently proposed. In the Color Glass Condensate (CGC) framework, it represents the leading term of an expansion in inverse powers of the hard scale. It contains the leading-twist TMD factorization form

Stan Alama, Lia Bronsard, Ihsan Topaloglu, Andres Zuniga

We consider the minimization of an energy functional given by the sum of a density perimeter and a nonlocal interaction of Riesz type with exponent $α$, under volume constraint, where the strength of the nonlocal interaction is controlled by a parameter $γ$. We show that for a wide class of density functions the energy admits a minimizer for any value of $γ$

Rodolfo Capdevilla, David Curtin, Yonatan Kahn, Gordan Krnjaic

The longstanding muon g-2 anomaly may indicate the existence of new particles that couple to muons, which could either be light (< GeV) and weakly coupled, or heavy (>> 100 GeV) with large couplings. If light new states are responsible, upcoming intensity frontier experiments will discover further evidence of new physics. However, if heavy particles are resp

Basem Kamal El-Menoufi, Stephan J. Huber, Jonathan P. Manuel

We consider a generic first-order phase transition at finite temperature and investigate to what extent a population of primordial black holes, of variable masses, can affect the rate of bubble nucleation. Using a thin-wall approximation, we construct the Euclidean configurations that describe transition at finite temperature. After the transition, the remna

Tejinder P. Singh

We have recently proposed a new matrix dynamics at the Planck scale, building on the theory of trace dynamics. This is a Lagrangian dynamics in which the matrix degrees of freedom are made from Grassmann numbers, and the Lagrangian is trace of a matrix polynomial. Matrices made from even grade elements of the Grassmann algebra are called bosonic, and those m

Andy Buckley, Anders Kvellestad, Are Raklev, Pat Scott

The evaluation of higher-order cross-sections is an important component in the search for new physics, both at hadron colliders and elsewhere. For most new physics processes of interest, total cross-sections are known at next-to-leading order (NLO) in the strong coupling $α_s$, and often beyond, via either higher-order terms at fixed powers of $α_s$, or mult

Nathaniel Starkman, Jagjit Sidhu, Harrison Winch, Glenn Starkman

Macroscopic dark matter (macros) is a broad class of alternative candidates to particle dark matter. These candidates would transfer energy to matter primarily through elastic scattering. A sufficiently large macro passing through the atmosphere would produce a straight channel of ionized plasma. If the cross-section of the macro is $σ_x \gtrapprox 6 \times

Janosz W. Dewberry, Henrik N. Latter, Gordon I. Ogilvie, Sebastien Fromang

Trapped inertial oscillations (r-modes) provide a promising explanation for high-frequency quasi-periodic oscillations (HFQPOs) observed in the emission from black hole X-ray binary systems. An eccentricity (or warp) can excite r-modes to large amplitudes, but concurrently the oscillations are likely damped by magnetohydrodynamic (MHD) turbulence driven by t

Alice Zurlo, Lucas A. Cieza, Sebastián Pérez, Valentin Christiaens

We present Adaptive Optics (AO) near infrared (NIR) observations using VLT/NACO and Keck/NIRC2 of ODISEA targets. ODISEA is an ALMA survey of the entire population of circumstellar discs in the Ophiuchus molecular cloud. From the whole sample of ODISEA we select all the discs that are not already observed in the NIR with AO and that are observable with NACO

Gregory M. Green, Hans-Walter Rix, Leon Tschesche, Douglas Finkbeiner

We develop a data-driven model to map stellar parameters (effective temperature, surface gravity and metallicity) accurately and precisely to broad-band stellar photometry. This model must, and does, simultaneously constrain the passband-specific dust reddening vector in the Milky Way. The model uses a neural network to learn the (de-reddened) absolute magni

Eyal Leviatan, David F. Mross

The fractionalization of microscopic degrees of freedom is a remarkable manifestation of strong interactions in quantum many-body systems. Analytical studies of this phenomenon are primarily based on two distinct frameworks: field theories of partons and emergent gauge fields, or coupled arrays of one-dimensional quantum wires. We unify these approaches for

Mario Martone

We derive explicit formulae to compute the $a$ and $c$ central charges of four dimensional $\mathcal{N}=2$ superconformal field theories (SCFTs) directly from Coulomb branch related quantities. The formulae apply at arbitrary rank. We also discover general properties of the low-energy limit behavior of the flavor symmetry of $\mathcal{N}=2$ SCFTs which culmi

Xinyang Wang, Igor A. Shovkovy, Lang Yu, Mei Huang

By making use of an explicit representation for the imaginary part of the photon polarization tensor in terms of transitions between the Landau levels of light quarks, we study the angular dependence of direct photon emission from a strongly magnetized quark-gluon plasma. Because of the magnetic field, the leading order photon rate comes from the three proce

Zhaoyu Han, Steven A. Kivelson, Hong Yao

We analyze the quantum phase diagram of the Holstein-Hubbard model using an asymptotically exact strong-coupling expansion. We find all sorts of interesting phases including a pair-density wave (PDW), a charge 4e (and even a charge 6e) superconductor, regimes of phase separation, and a variety of distinct charge-density-wave (CDW), spin-density-wave (SDW) an

Haider Alhazmi, Doojin Kim, Kyoungchul Kong, Gopolang Mohlabeng

The dark matter interpretation for a recent observation of excessive electron recoil events at the XENON1T detector seems challenging because its velocity is not large enough to give rise to recoiling electrons of $\mathcal{O}({\rm keV})$. Fast-moving or boosted dark matter scenarios are receiving attention as a remedy for this issue, rendering the dark matt

Alexander C. Jenkins, Mairi Sakellariadou

Primordial black holes (PBHs) are of fundamental interest in cosmology and astrophysics, and have received much attention as a dark matter candidate and as a potential source of gravitational waves. One possible PBH formation mechanism is the gravitational collapse of cosmic strings. Thus far, the entirety of the literature on PBH production from cosmic stri

Minh C. Tran, Yuan Su, Daniel Carney, Jacob M. Taylor

Simulating the dynamics of quantum systems is an important application of quantum computers and has seen a variety of implementations on current hardware. We show that by introducing quantum gates implementing unitary transformations generated by the symmetries of the system, one can induce destructive interference between the errors from different steps of

Yawei Li, Wen Li, Martin Danelljan, Kai Zhang

In this paper, we tackle the problem of convolutional neural network design. Instead of focusing on the design of the overall architecture, we investigate a design space that is usually overlooked, i.e. adjusting the channel configurations of predefined networks. We find that this adjustment can be achieved by shrinking widened baseline networks and leads to

Dan Hendrycks, Steven Basart, Norman Mu, Saurav Kadavath

We introduce four new real-world distribution shift datasets consisting of changes in image style, image blurriness, geographic location, camera operation, and more. With our new datasets, we take stock of previously proposed methods for improving out-of-distribution robustness and put them to the test. We find that using larger models and artificial data au

Chi-An Yeh, Muralikrishnan Gopalakrishnan Meena, Kunihiko Taira

We present a network-based modal analysis technique that identifies key dynamical paths along which perturbations amplify over a time-varying base flow. This analysis is built upon the Katz centrality, which reveals the flow structures that can effectively spread perturbations over a time-evolving network of vortical interactions on the base flow. Motivated

Evan Zheran Liu, Milad Hashemi, Kevin Swersky, Parthasarathy Ranganathan

Program execution speed critically depends on increasing cache hits, as cache hits are orders of magnitude faster than misses. To increase cache hits, we focus on the problem of cache replacement: choosing which cache line to evict upon inserting a new line. This is challenging because it requires planning far ahead and currently there is no known practical

Xiaomin Li

Given a real number $α\in (0,1)$, we define the Webster sequence of density $α$ to be $W_α= (\lceil(n-1/2) / α\rceil)_{n\in\mathbb{N}}$, where $\lceil x \rceil$ is the ceiling function. It is known that if $α$ and $β$ are irrational with $α+ β= 1$, then $W_α$ and $W_β$ partition $\mathbb{N}$. On the other hand, an analogous result for three-part partitions d

Angelos Katharopoulos, Apoorv Vyas, Nikolaos Pappas, François Fleuret

Transformers achieve remarkable performance in several tasks but due to their quadratic complexity, with respect to the input&#39;s length, they are prohibitively slow for very long sequences. To address this limitation, we express the self-attention as a linear dot-product of kernel feature maps and make use of the associativity property of matrix products

Tristan Knoth, Di Wang, Adam Reynolds, Jan Hoffmann

This article presents liquid resource types, a technique for automatically verifying the resource consumption of functional programs. Existing resource analysis techniques trade automation for flexibility -- automated techniques are restricted to relatively constrained families of resource bounds, while more expressive proof techniques admitting value-depend

Zorawar Wadiasingh, Cecilia Chirenti

Quasi-periodic oscillations inferred during rare magnetar giant flare tails were initially interpreted as torsional oscillations of the neutron star (NS) crust, and have been more recently described as global core+crust perturbations. Similar frequencies are also present in high signal-to-noise magnetar short bursts. In magnetars, disturbances of the field a

Pardeep Kumar, Thakshila M. Herath, Vadym Apalkov

We study theoretically interaction of a bilayer graphene with a circularly polarized ultrafast optical pulse of a single oscillation at an oblique incidence. The normal component of the pulse breaks the inversion symmetry of the system and opens up a dynamical band-gap, due to which a valley-selective population of the conduction band becomes sensitive to th

Vladimir O. Soloviev

The constraint algebra is derived in the second order tetrad Hamiltonian formalism of the bigravity. This is done by a straightforward calculation without involving any insights, implicit functions, and Dirac brackets. The tetrad approach is the only way to present the bigravity action as a linear functional of lapses and shifts, and the Hassan-Rosen transfo

Sourav Chatterjee

The confinement of quarks is one of the enduring mysteries of modern physics. There is a longstanding physics heuristic that confinement is a consequence of `unbroken center symmetry&#39;. This article gives mathematical confirmation of this heuristic, by rigorously defining of center symmetry in lattice gauge theories and proving that a theory is confining

Jean-Baptiste Alayrac, Adrià Recasens, Rosalia Schneider, Relja Arandjelović

Videos are a rich source of multi-modal supervision. In this work, we learn representations using self-supervision by leveraging three modalities naturally present in videos: visual, audio and language streams. To this end, we introduce the notion of a multimodal versatile network -- a network that can ingest multiple modalities and whose representations ena

Anirudh Goyal, Alex Lamb, Phanideep Gampa, Philippe Beaudoin

Modeling a structured, dynamic environment like a video game requires keeping track of the objects and their states declarative knowledge) as well as predicting how objects behave (procedural knowledge). Black-box models with a monolithic hidden state often fail to apply procedural knowledge consistently and uniformly, i.e., they lack systematicity. For exam

En-Hung Chao, Antoine Gérardin, Jeremy R. Green, Renwick J. Hudspith

We perform a lattice QCD calculation of the hadronic light-by-light contribution to $(g-2)_μ$ at the SU(3) flavor-symmetric point $m_π=m_K\simeq 420\,$MeV. The representation used is based on coordinate-space perturbation theory, with all QED elements of the relevant Feynman diagrams implemented in continuum, infinite Euclidean space. As a consequence, the e

Tomoki Tanaka, Yohichi Suzuki, Shumpei Uno, Rudy Raymond

Recently we find several candidates of quantum algorithms that may be implementable in near-term devices for estimating the amplitude of a given quantum state, which is a core sub- routine in various computing tasks such as the Monte Carlo methods. One of those algorithms is based on the maximum likelihood estimate with parallelized quantum circuits. In this

Kohji Nishimura, Hidetoshi Nishimori, Helmut G. Katzgraber

The Griffiths-McCoy singularity is a phenomenon characteristic of low-dimensional disordered quantum spin systems, in which the magnetic susceptibility shows singular behavior as a function of the external field even within the paramagnetic phase. We study whether this phenomenon is observed in the transverse-field Ising model with disordered ferromagnetic i

Riccardo Grazzi, Luca Franceschi, Massimiliano Pontil, Saverio Salzo

We study a general class of bilevel problems, consisting in the minimization of an upper-level objective which depends on the solution to a parametric fixed-point equation. Important instances arising in machine learning include hyperparameter optimization, meta-learning, and certain graph and recurrent neural networks. Typically the gradient of the upper-le

I. El Mellah, V. Grinberg, J. O. Sundqvist, F. A. Driessen

In high mass X-ray binaries (HMXBs), an accreting compact object orbits a high mass star which loses mass through a dense and inhomogeneous wind. Using the compact object as an X-ray backlight, the time variability of the absorbing column density in the wind can be exploited in order to shed light on the micro-structure of the wind and obtain unbiased stella

Yi-Fan Zhao, Ruoxi Zhang, Ruobing Mei, Ling-Jie Zhou

The quantum anomalous Hall (QAH) state is a two-dimensional topological insulating state that has quantized Hall resistance of h/Ce2 and vanishing longitudinal resistance under zero magnetic field, where C is called the Chern number. The QAH effect has been realized in magnetic topological insulators (TIs) and magic-angle twisted bilayer graphene. Despite co

Alexander Belton, Dominique Guillot, Apoorva Khare, Mihai Putinar

The composition operators preserving total non-negativity and total positivity for various classes of kernels are classified, following three themes. Letting a function act by post composition on kernels with arbitrary domains, it is shown that such a composition operator maps the set of totally non-negative kernels to itself if and only if the function is c

Ainesh Bakshi, Adarsh Prasad

We obtain robust and computationally efficient estimators for learning several linear models that achieve statistically optimal convergence rate under minimal distributional assumptions. Concretely, we assume our data is drawn from a $k$-hypercontractive distribution and an $ε$-fraction is adversarially corrupted. We then describe an estimator that converges

Jianzhun Du, Joseph Futoma, Finale Doshi-Velez

We present two elegant solutions for modeling continuous-time dynamics, in a novel model-based reinforcement learning (RL) framework for semi-Markov decision processes (SMDPs), using neural ordinary differential equations (ODEs). Our models accurately characterize continuous-time dynamics and enable us to develop high-performing policies using a small amount

Gaurav Singh, Raghwendra Kumar, Debabrata Biswas

The maximum current that can be transported across a vacuum diode is limited by forces arising due to space charge. In a planar diode configuration, the space charge limited (SCL) current density from a planar emitting patch is given by the Child-Langmuir (CL) law $J_{CL} \sim V_g^{3/2}/D^2$ where $V_g$ is the potential difference across the diode and $D$ is

Harry Pei

A patient player privately observes a persistent state that directly affects his myopic opponents&#39; payoffs, and can be one of the several commitment types that plays the same mixed action in every period. I characterize the set of environments under which the patient player obtains at least his commitment payoff in all equilibria regardless of his stage-

Sang Michael Xie, Tengyu Ma, Percy Liang

We focus on prediction problems with structured outputs that are subject to output validity constraints, e.g. pseudocode-to-code translation where the code must compile. While labeled input-output pairs are expensive to obtain, &#34;unlabeled&#34; outputs, i.e. outputs without corresponding inputs, are freely available (e.g. code on GitHub) and provide infor

Roberto Esposito, Mattia Cerrato, Marco Locatelli

In this paper we propose a variant of the linear least squares model allowing practitioners to partition the input features into groups of variables that they require to contribute similarly to the final result. The output allows practitioners to assess the importance of each group and of each variable in the group. We formally show that the new formulation

Vaibhav Kumar Jena

In this article, we present a novel Carleman estimate for ultrahyperbolic operators, in $ \mathbb{R}^m_t \times \mathbb{R}^n_x $. Then, we use a special case of this estimate to obtain improved observability results for wave equations with time-dependent lower order terms. The key improvements are: (1) we obtain smaller observation regions compared to standa

A. Mukhammadiev, D. Tiwari, G. Apaaboah, P. Giordano

It is well-known that the notion of limit in the sharp topology of sequences of Colombeau generalized numbers $\widetilde{\mathbb{R}}$ does not generalize classical results. E.g.~the sequence $\frac{1}{n}\not\to0$ and a sequence $(x_{n})_{n\in\mathbb{N}}$ converges \emph{if} and only if $x_{n+1}-x_{n}\to0$. This has several deep consequences, e.g.~in the stu

Larry Rolen, Zack Tripp, Ian Wagner, Samuel Wilson

Dyson famously provided combinatorial explanations for Ramanujan&#39;s partition congruences modulo $5$ and $7$ via his rank function, and postulated that an invariant explaining all of Ramanujan&#39;s congruences modulo $5$, $7$, and $11$ should exist. Garvan and Andrews-Garvan later discovered such an invariant called the crank, fulfilling Dyson&#39;s goal

Samuel Thomas, Wanzhu Tu

Hamiltonian Monte Carlo (HMC) is a powerful tool for Bayesian computation. In comparison with the traditional Metropolis-Hastings algorithm, HMC offers greater computational efficiency, especially in higher dimensional or more complex modeling situations. To most statisticians, however, the idea of HMC comes from a less familiar origin, one that is based on

Jing Dong, Xin T. Tong

Langevin diffusion (LD) is one of the main workhorses for sampling problems. However, its convergence rate can be significantly reduced if the target distribution is a mixture of multiple densities, especially when each component concentrates around a different mode. Replica exchange Langevin diffusion (ReLD) is a sampling method that can circumvent this iss

Yugen Lin, Yu Gao, Tianjun Li

We propose an $SU(3)_C\times SU(2)_L\times U(1)_{Y}\times U(1)_{B-L}$ model, in which the neutrino masses and mixings can be generated via Type-I seesaw mechanism after $U(1)_{B-L}$ breaking. A light mediator emerges and enables non-standard interaction that violates the lepton number. We show that the non-standard neutrino interaction emerges in this model,

Florian Hörsch, Zoltán Szigeti

Fortier et al. proposed several research problems on packing arborescences. Some of them were settled in that article and others were solved later by Matsuoka and Tanigawa and by Gao and Yang. The last open problem is settled in this article. We show how to turn an inductive idea used in the latter two articles into a simple proof technique that allows to re

Rouzbeh Allahverdi, Mustafa A. Amin, Asher Berlin, Nicolás Bernal

It is commonly assumed that the energy density of the Universe was dominated by radiation between reheating after inflation and the onset of matter domination 54,000 years later. While the abundance of light elements indicates that the Universe was radiation dominated during Big Bang Nucleosynthesis (BBN), there is scant evidence that the Universe was radiat

Kirby Hermansen, Sean M. Couch, Luke F. Roberts, Hendrik Schatz

Radioactive isotopes produced in core-collapse supernovae (CCSNe) provide useful insights into the underlying processes driving the collapse mechanism and the origins of elemental abundances. Their study generates a confluence of major physics research, including experimental measurements of nuclear reaction rates, astrophysical modeling, and $γ$-ray observa

Ya Deng

In 1988 Simpson extended the Donaldson-Uhlenbeck-Yau theorem to the context of Higgs bundles, and as an application he proved a uniformization theorem which characterizes complex projective manifolds and quasi-projective curves whose universal coverings are complex unit balls. In this paper we give a necessary and sufficient condition for quasi-projective ma

Lichao Sun

Recently, advanced NLP models have seen a surge in the usage of various applications. This raises the security threats of the released models. In addition to the clean models&#39; unintentional weaknesses, {\em i.e.,} adversarial attacks, the poisoned models with malicious intentions are much more dangerous in real life. However, most existing works currentl

Andreas Debrouwere

We give a complete solution to the Borel-Ritt problem in non-uniform spaces $\mathscr{A}^-_{(M)}(S)$ of ultraholomorphic functions of Beurling type, where $S$ is an unbounded sector of the Riemann surface of the logarithm and $M$ is a strongly regular weight sequence. Namely, we characterize the surjectivity and the existence of a continuous linear right inv

Wanxing Lin, Shi-Dong Liang, Jiesen Li, Dao-Xin Yao

One novel family of two-dimensional IV-V compounds have been proposed, whose dynamical stabilities and electronic properties have been systematically investigated using the density functional theory. Extending from our previous work, two phases of carbon phosphorus bilayers α- and β-C$_{2}$P$_{2}$ have been proposed. Both of them are dynamically stable and t

Fabio Silva Botelho

This article develops optimality conditions for a large class of non-smooth variational models. The main results are based on standard tools of functional analysis and calculus of variations. Firstly we address a model with equality constraints and, in a second step, a more general model with equality and inequality constraints, always in a general Banach sp

Biplob Bhattacherjee, Rhitaja Sengupta

This work is a study of some possible background sources in the XENON1T environment which might affect the energy spectrum of electronic recoil events in the lower side and might contribute to the observed excess. We have identified some additional possible backgrounds, like $^{41}$Ca, $^{49}$V, $^{63}$Ni, $^{106}$Ru and $^{125}$Sb coming from cosmogenic pro