May 2019 arXiv papers

Pengfei Yang, Xiuwen Xia, Hai He, Shaokang Li

Optical nonreciprocity is important in photonic information processing to route the optical signal or prevent the reverse flow of noise. By adopting the strong nonlinearity associated with a few atoms in a strongly coupled cavity QED system and an asymmetric cavity configuration, we experimentally demonstrate the nonreciprocal transmission between two counte

Alexander Litvinenko, Dmitry Logashenko, Raul Tempone, Gabriel Wittum

As groundwater is an essential nutrition and irrigation resource, its pollution may lead to catastrophic consequences. Therefore, accurate modeling of the pollution of the soil and groundwater aquifer is highly important. As a model, we consider a density-driven groundwater flow problem with uncertain porosity and permeability. This problem may arise in geot

Thomas Creutzig, Shashank Kanade, Robert McRae

We relate commutative algebras in braided tensor categories to braid-reversed tensor equivalences, motivated by vertex algebra representation theory. First, for $\mathcal{C}$ a braided tensor category, we give a detailed construction of the canonical algebra in $\mathcal{C}\boxtimes\mathcal{C}^\text{rev}$: if $\mathcal{C}$ is semisimple but not necessarily f

Tasos Moulinos, Marco Robalo, Bertrand Toën

In this work we study the failure of the HKR theorem over rings of positive and mixed characteristic. For this we construct a filtered circle interpolating between the usual topological circle and a formal version of it. By mapping to schemes we produce this way an interpolation, realized in practice by the existence of a natural filtration, from Hochschild

Raif M. Rustamov, James T. Klosowski

This paper introduces an approach for detecting differences in the first-order structures of spatial point patterns. The proposed approach leverages the kernel mean embedding in a novel way by introducing its approximate version tailored to spatial point processes. While the original embedding is infinite-dimensional and implicit, our approximate embedding i

Yi Xia, Junsoo Park, Vidvuds Ozoliņš, Chris Wolverton

Electron-phonon interaction (EPI) is presumably detrimental for thermoelectric performance in semiconductors because it limits carrier mobility. Here we show that enhanced EPI with strong energy dependence offers an intrinsic pathway to significant increase in the Seebeck coefficient and the thermoelectric power factor, particularly in the context of two-dim

Armin Seyeditabari, Narges Tabari, Shafie Gholizade, Wlodek Zadrozny

Word embeddings are one of the most useful tools in any modern natural language processing expert's toolkit. They contain various types of information about each word which makes them the best way to represent the terms in any NLP task. But there are some types of information that cannot be learned by these models. Emotional information of words are one

E. Valencia, D. Jena, Nuruzzaman, F. Akbar

Elastic neutrino scattering on electrons is a precisely-known purely leptonic process that provides a standard candle for measuring neutrino flux in conventional neutrino beams. Using a total sample of 810 neutino-electron scatters after background subtraction, the measurement reduces the normalization uncertainty on the muon neutrino NuMI flux between 2 and

Boris N. Oreshkin, Negar Rostamzadeh, Pedro O. Pinheiro, Christopher Pal

We address the problem of learning fine-grained cross-modal representations. We propose an instance-based deep metric learning approach in joint visual and textual space. The key novelty of this paper is that it shows that using per-image semantic supervision leads to substantial improvement in zero-shot performance over using class-only supervision. On top

Kiyoshi Igusa, Ralf Schiffler

We define a generalized version of the frieze variety introduced by Lee, Li, Mills, Seceleanu and the second author. The generalized frieze variety is an algebraic variety determined by an acyclic quiver and a generic specialization of cluster variables in the cluster algebra for this quiver. The original frieze variety is obtained when this specialization i

Jeffrey M. Hokanson, Paul G. Constantine

We introduce the Lipschitz matrix: a generalization of the scalar Lipschitz constant for functions with many inputs. Among the Lipschitz matrices compatible a particular function, we choose the smallest such matrix in the Frobenius norm to encode the structure of this function. The Lipschitz matrix then provides a function-dependent metric on the input space

Wei Zhang, Liron Stern, David Carlson, Douglas Bopp

Lasers with high spectral purity can enable a diverse application space, including precision spectroscopy, coherent high-speed communications, physical sensing, and manipulation of quantum systems. Already, meticulous design and construction of bench Fabry-Perot cavities has made possible dramatic achievements in active laser-linewidth reduction, predominant

Guo-Niu Han

The Euler numbers occur in the Taylor expansion of $\tan(x)+\sec(x)$. Since Stieltjes, continued fractions and Hankel determinants of the even Euler numbers, on the one hand, of the odd Euler numbers, on the other hand, have been widely studied separately. However, no Hankel determinants of the (mixed) Euler numbers have been obtained and explicitly calculat

Joel W. LeBlanc, Brian J. Thelen, Alfred O. Hero

Many mathematical imaging problems are posed as non-convex optimization problems. When numerically tractable global optimization procedures are not available, one is often interested in testing ex post facto whether or not a locally convergent algorithm has found the globally optimal solution. When the problem is formulated in terms of maximizing the likelih

Piotr Kubala, Michał Cieśla, Robert M. Ziff

We study random sequential adsorption (RSA) of a class of solids that can be obtained from a cube by specific cutting of its vertices, in order to find out how the transition from tetrahedral to octahedral symmetry affects the densities of the resulting jammed packings. We find that in general solids of octahedral symmetry form less dense packing, however, t

Jonathan Glöckle

The dominant energy condition imposes a restriction on initial value pairs found on a spacelike hypersurface of a Lorentzian manifold. In this article, we study the space of initial values that satisfy this condition strictly. To this aim, we introduce an index difference for initial value pairs and compare it to its classical counterpart for Riemannian metr

Guenter Nimtz, Horst Aichmann

We begin the Article with confusing citations in published papers on the question recently: how much time does a wave packet spend in a tunnelling barrier? ..a particle tunnelling through a barrier appears to do so in zero time 1. .. The pulse transit through the barrier itself seems to be instantaneous 2. ..tunnelling is unlike to be an instantaneous proces

Elliot Meyerson, Risto Miikkulainen

As deep learning applications continue to become more diverse, an interesting question arises: Can general problem solving arise from jointly learning several such diverse tasks? To approach this question, deep multi-task learning is extended in this paper to the setting where there is no obvious overlap between task architectures. The idea is that any set o

Anik Chattopadhyay, Arunava Banerjee

In many animal sensory pathways, the transformation from external stimuli to spike trains is essentially deterministic. In this context, a new mathematical framework for coding and reconstruction, based on a biologically plausible model of the spiking neuron, is presented. The framework considers encoding of a signal through spike trains generated by an ense

Stefano Iubini

I study heat and norm transport in a one-dimensional lattice of linear Schrödinger oscillators with conservative stochastic perturbations. Its equilibrium properties are the same of the Discrete Nonlinear Schrödinger equation in the limit of vanishing nonlinearity. When attached to external classical reservoirs that impose nonequilibrium conditions, the chai

Isaac Konan

In a recent paper, Dousse introduced a refinement of Siladić's theorem on partitions, where parts occur in two primary and three secondary colors. Her proof used the method of weighted words and $q$-difference equations. The purpose of this paper is to give a bijective proof of a generalization of Dousse's theorem from two primary colors to an arbitr

Patrick Concha, Evelyn Rodríguez

In this work we study a non-relativistic three dimensional Chern-Simons gravity theory based on an enlargement of the Extended Bargmann algebra. A finite non-relativistic Chern-Simons gravity action is obtained through the non-relativistic contraction of a particular $U(1)$ enlargement of the so-called AdS-Lorentz algebra. We show that the non-relativistic g

An Khuong Doan

If $X$ is a projective variety and $G$ is an algebraic group acting algebraically on $X$, we provide a counter-example to the existence of a $G$-equivariant extension on the formal semi-universal deformation of $X$.

Anna Duwenig, Heath Emerson

An early result of Noncommutative Geometry was Connes' observation in the 1980's that the Dirac-Dolbeault cycle for the $2$-torus $\mathbb{T}^2$, which induces a Poincaré self-duality for $\mathbb{T}^2$, can be 'quantized' to give a spectral triple and a K-homology class in $KK_0(A_θ\otimes A_θ, \mathbb{C})$ providing the co-unit for a Poinca

Michael Anastos, Alan Frieze

In this paper we consider the existence of Hamilton cycles in the random graph $G=G_{n,m}^{δ\geq 3}$. This a random graph chosen uniformly from the set of graphs with vertex set $[n]$, $m$ edges and minimum degree at least 3. Our ultimate goal is to prove that if $m=cn$ and $c>3/2$ is constant then $G$ is Hamiltonian w.h.p. In an earlier paper the second aut

Alex Debrecht, Jonathan Carroll-Nellenback, Adam Frank, Eric G. Blackman

The role of radiation pressure in shaping exoplanet photoevaporation remains a topic of contention. Radiation pressure from the exoplanet's host star has been proposed as a mechanism to drive the escaping atmosphere into a "cometary" tail and explain the high velocities observed in systems where mass loss is occurring. In this paper we present re

V. Golyshev, D. van Straten, D. Zagier

We show that a version of dimensional interpolation for the Riemann--Roch--Hirzebruch formalism in the case of a grassmannian leads to an expression for the Euler characteristic of line bundles in terms of a Selberg integral. We propose a way to interpolate higher Bessel equations, their wedge powers, and monodromies thereof to non--integer orders, and link

Mladen Bestvina, Koji Fujiwara, Derrick Wigglesworth

We prove the Farrell-Jones conjecture for free-by-cyclic groups. The proof uses recently developed geometric methods for establishing the Farrell-Jones Conjecture.

Kenneth Marino, Mohammad Rastegari, Ali Farhadi, Roozbeh Mottaghi

Visual Question Answering (VQA) in its ideal form lets us study reasoning in the joint space of vision and language and serves as a proxy for the AI task of scene understanding. However, most VQA benchmarks to date are focused on questions such as simple counting, visual attributes, and object detection that do not require reasoning or knowledge beyond what

Dennis Wei, Karthikeyan Natesan Ramamurthy, Flavio du Pin Calmon

This paper considers fair probabilistic binary classification where the outputs of primary interest are predicted probabilities, commonly referred to as scores. We formulate the problem of transforming scores to satisfy fairness constraints that are linear in conditional means of scores while minimizing a cross-entropy objective. The formulation can be appli

Jesús Martín Romero, Mauricio Bellini

We study a traversable wormhole originated by a transformation over the 4D Dymnikova metric which describes analytic Black-Holes (BH). By using a transformation of coordinates which is adapted from the used in the Einstein-Rosen bridge, we study a specific family of geodesics in which a test particle with non-zero electric charge induces an effective magneti

Loredana Bellantuono, Romuald A. Janik, Jakub Jankowski, Hesam Soltanpanahi

We study various dynamical aspects of systems possessing a first order phase transition in their phase diagram. We isolate three qualitatively distinct types of theories depending on the structure of instabilities and the nature of the low temperature phase. The non-equilibrium dynamics is modeled by a dual gravitational theory in 3+1 dimension which is coup

CMS Collaboration

A statistical combination of searches for heavy resonances decaying to pairs of bosons or leptons is presented. The data correspond to an integrated luminosity of 35.9 fb$^{-1}$ collected during 2016 by the CMS experiment at the LHC in proton-proton collisions at a center-of-mass energy of 13 TeV. The data are found to be consistent with expectations from th

Huibin Chang, Ziqin Rong, Pablo Enfedaque, Stefano Marchesini

Spectroscopic ptychography is a powerful technique to determine the chemical composition of a sample with high spatial resolution. In spectro-ptychography, a sample is rastered through a focused x-ray beam with varying photon energy so that a series of phaseless diffraction data are recorded. Each chemical component in the material under investigation has a

Field Rogers, Mengjiao Xiao, Kerstin M. Perez, Steven Boggs

The first lithium-drifted silicon (Si(Li)) detectors to satisfy the unique geometric, performance, and cost requirements of the General Antiparticle Spectrometer (GAPS) experiment have been produced by Shimadzu Corporation. The GAPS Si(Li) detectors will form the first large-area, relatively high-temperature Si(Li) detector system with sensitivity to X-rays

Adam Gali

Nitrogen-vacancy center in diamond is a solid state defect qubit with favorable coherence time up to room temperature which could be harnessed in several quantum enhanced sensor and quantum communication applications, and has a potential in quantum simulation and computing. The quantum control largely depends on the intricate details about the electronic str

Li-yao Xia, Yannick Zakowski, Paul He, Chung-Kil Hur

"Interaction trees" (ITrees) are a general-purpose data structure for representing the behaviors of recursive programs that interact with their environments. A coinductive variant of "free monads," ITrees are built out of uninterpreted events and their continuations. They support compositional construction of interpreters from "event hand

A. Diaz, C. A. Argüelles, G. H. Collin, J. M. Conrad

We review the status of searches for sterile neutrinos in the $\sim 1$ eV range, with an emphasis on the latest results from short baseline oscillation experiments and how they fit within sterile neutrino oscillation models. We present global fit results to a three-active-flavor plus one-sterile-flavor model (3+1), where we find an improvement of $Δχ^2=35$ f

Błażej Ruba

It is shown that the free energy associated to a finite dimensional Airy structure is an analytic function at each finite order of the $\hbar$ expansion. Semiclassical series itself is in general divergent. Calculations are facilitated by putting the topological recursion equations into a form exhibiting more explicitly the semiclassical geometry. This formu

Yajuan Si, Mari Palta, Maureen Smith

Electronic health records (EHRs) are increasingly used for clinical and comparative effectiveness research, but suffer from missing data. Motivated by health services research on diabetes care, we seek to increase the quality of EHRs by focusing on missing values of longitudinal glycosylated hemoglobin (A1c), a key risk factor for diabetes complications and

S. Jin, E. Daddi, G. E. Magdis, D. Liu

We report Atacama Large Millimetre Array (ALMA) observations of four high-redshift dusty star-forming galaxy candidates selected from far-Infrared (FIR)/submm observations in the COSMOS field. We securely detect all galaxies in the continuum and spectroscopically confirm them at z=3.62--5.85 using ALMA 3mm line scans, detecting multiple CO and/or [CI] transi

Stephanie M. Lukin, Claire Bonial, Clare R. Voss

We describe the task of Visual Understanding and Narration, in which a robot (or agent) generates text for the images that it collects when navigating its environment, by answering open-ended questions, such as 'what happens, or might have happened, here?'

Leonid Faybusovich, Cunlu Zhou

We consider some important computational aspects of the long-step path-following algorithm developed in our previous work and show that a broad class of complicated optimization problems arising in quantum information theory can be solved using this approach. In particular, we consider one difficult and important optimization problem in quantum key distribut

Galen Dorpalen-Barry, Jang Soo Kim, Victor Reiner

Hyperplane arrangements dissect $\mathbb{R}^n$ into connected components called chambers, and a well-known theorem of Zaslavsky counts chambers as a sum of nonnegative integers called Whitney numbers of the first kind. His theorem generalizes to count chambers within any cone defined as the intersection of a collection of halfspaces from the arrangement, lea

David Lafferty, Alexander Rothkopf

We explore the in-medium properties of heavy-quarkonium states at finite baryo-chemical potential and finite transverse momentum based on a modern complex-valued potential model. Our starting point is a novel, rigorous derivation of the generalized Gauss law for in-medium quarkonium, combining the non-perturbative physics of the vacuum bound state with a wea

S. Cipolla, C. Di Fiore, P. Zellini

In this work we introduce and study novel Quasi Newton minimization methods based on a Hessian approximation Broyden Class-\textit{type} updating scheme, where a suitable matrix $\tilde{B}_k$ is updated instead of the current Hessian approximation $B_k$. We identify conditions which imply the convergence of the algorithm and, if exact line search is chosen,

Apurva Seth, Prahlad Vaidyanathan

A C*-algebra is said to be K-stable if its nonstable K-groups are naturally isomorphic to the usual K-theory groups. We study continuous $C(X)$-algebras, each of whose fibers are K-stable. We show that such an algebra is itself K-stable under the assumption that the underlying space $X$ is compact, metrizable, and of finite covering dimension.

Michael C. Brennan, Daniele Bigoni, Olivier Zahm, Alessio Spantini

We propose a framework for solving high-dimensional Bayesian inference problems using \emph{structure-exploiting} low-dimensional transport maps or flows. These maps are confined to a low-dimensional subspace (hence, lazy), and the subspace is identified by minimizing an upper bound on the Kullback--Leibler divergence (hence, structured). Our framework provi

Ting-Kam Leonard Wong, Jiaowen Yang

Optimal transport and information geometry both study geometric structures on spaces of probability distributions. Optimal transport characterizes the cost-minimizing movement from one distribution to another, while information geometry originates from coordinate-invariant properties of statistical inference. Their connections and applications in statistics

Sebastian Bahamonde, Mihai Marciu, Prabir Rudra

In this work we have investigated the dynamics of a recent modification to the general theory of relativity, the energy-momentum squared gravity model $f(R,\mathbf{T^2})$, where $R$ represents the scalar curvature and $\mathbf{T^2}$ the square of the energy-momentum tensor. By using dynamical system analysis for various types of gravity functions $f(R,\mathb

Matthias Löwe, Kristina Schubert

We show how to exactly reconstruct the block structure at the critical line in the so-called Ising block model. This model was re-introduced by Berthet, Rigollet and Srivastava in a recent paper. There the authors show how to exactly reconstruct blocks away from the critical line and they give an upper and a lower bound on the number of observations one need

Sugan D. Murugan, Dheeraj Kumar, Subhro Bhattacharjee, Samriddhi Sankar Ray

Linking thermodynamic variables like temperature $T$ and the measure of chaos, the Lyapunov exponents $λ$, is a question of fundamental importance in many-body systems. By using nonlinear fluid equations in one and three dimensions, we prove that in thermalised flows $λ\propto \sqrt{T}$, in agreement with results from frustrated spin systems. This reveals an

John Terning, Christopher B. Verhaaren

While the evidence for dark matter continues to grow, the nature of the dark matter remains a mystery. A dark $U(1)_D$ gauge theory can have a small kinetic mixing with the visible photon which provides a portal to the dark sector. Magnetic monopoles of the dark $U(1)_D$ can obtain small magnetic couplings to our photon through this kinetic mixing. This coup

Louise Welsh, Ryan Cooke, Michele Fumagalli

The most metal-poor, high redshift damped Lyman-alpha systems (DLAs) provide a window to study some of the first few generations of stars. In this paper, we present a novel model to investigate the chemical enrichment of the near-pristine DLA population. This model accounts for the mass distribution of the enriching stellar population, the typical explosion

Tanner Trickle, Zhengkang Zhang, Kathryn M. Zurek

Scattering of light dark matter with sub-eV energy deposition can be detected with collective excitations in condensed matter systems. When dark matter has spin-independent couplings to atoms or ions, it has been shown to efficiently excite phonons. Here we show that, if dark matter couples to the electron spin, magnon excitations in materials with magnetic

Xiaoyi Mai, Zhenyu Liao

This article provides, through theoretical analysis, an in-depth understanding of the classification performance of the empirical risk minimization framework, in both ridge-regularized and unregularized cases, when high dimensional data are considered. Focusing on the fundamental problem of separating a two-class Gaussian mixture, the proposed analysis allow

Mario Krenn, Florian Häse, AkshatKumar Nigam, Pascal Friederich

The discovery of novel materials and functional molecules can help to solve some of society's most urgent challenges, ranging from efficient energy harvesting and storage to uncovering novel pharmaceutical drug candidates. Traditionally matter engineering -- generally denoted as inverse design -- was based massively on human intuition and high-throughput

Marinus Gottschau, Felix Happach, Marcus Kaiser, Clara Waldmann

Budget Minimization is a scheduling problem with precedence constraints, i.e., a scheduling problem on a partially ordered set of jobs $(N, \unlhd)$. A job $j \in N$ is available for scheduling, if all jobs $i \in N$ with $i \unlhd j$ are completed. Further, each job $j \in N$ is assigned real valued costs $c_{j}$, which can be negative or positive. A schedu

Irfan Glogić, Maciej Maliborski, Birgit Schörkhuber

We consider the focusing cubic wave equation in the energy supercritical case, i.e., in dimensions $d \geq 5$. For this model an explicit nontrivial self-similar blowup solution was recently found by the first and third author in \cite{GlogicSchoerkhuber}. Furthermore, the solution is proven to be co-dimension one stable in $d=7$. In this paper, we study the

X. Chen, T. Gehrmann, E. W. N. Glover, A. Huss

The four-lepton decay mode of the Higgs boson allows for a clean kinematic reconstruction, thereby enabling precision studies of the Higgs boson properties and of its production dynamics. We compute the NNLO QCD corrections to fiducial cross sections relevant to this decay mode in the gluon-fusion production of a Higgs boson in association with a hadronic je

Lucy Li, Bijeeta Pal, Junade Ali, Nick Sullivan

To prevent credential stuffing attacks, industry best practice now proactively checks if user credentials are present in known data breaches. Recently, some web services, such as HaveIBeenPwned (HIBP) and Google Password Checkup (GPC), have started providing APIs to check for breached passwords. We refer to such services as compromised credential checking (C

Yair Carmon, Aditi Raghunathan, Ludwig Schmidt, Percy Liang

We demonstrate, theoretically and empirically, that adversarial robustness can significantly benefit from semisupervised learning. Theoretically, we revisit the simple Gaussian model of Schmidt et al. that shows a sample complexity gap between standard and robust classification. We prove that unlabeled data bridges this gap: a simple semisupervised learning

Changxu Liu, Mikhail V. Rybin, Peng Mao, Shuang Zhang

When the feature size of photonic structures becomes comparable or even smaller than the wavelength of light, the fabrication imperfections inevitably introduce disorder that may eliminate many functionalities of subwavelength photonic devices. Here we suggest a novel concept to achieve a robust bandgap which can endure disorder beyond 30 as a result of the

Martin Burger, Jan-Frederik Pietschmann, Marie-Therese Wolfram

We consider the problem of estimating the density of buyers and vendors in a nonlinear parabolic price formation model using measurements of the price and the transaction rate. Our approach is based on a work by Puel et al., see \cite{Puel2002}, and results in a optimal control problem. We analyse this problems and provide stability estimates for the control

Bryan Wilder, Eric Ewing, Bistra Dilkina, Milind Tambe

Real-world applications often combine learning and optimization problems on graphs. For instance, our objective may be to cluster the graph in order to detect meaningful communities (or solve other common graph optimization problems such as facility location, maxcut, and so on). However, graphs or related attributes are often only partially observed, introdu

Thijs Vogels, Sai Praneeth Karimireddy, Martin Jaggi

We study gradient compression methods to alleviate the communication bottleneck in data-parallel distributed optimization. Despite the significant attention received, current compression schemes either do not scale well or fail to achieve the target test accuracy. We propose a new low-rank gradient compressor based on power iteration that can i) compress gra

Jonathan Uesato, Jean-Baptiste Alayrac, Po-Sen Huang, Robert Stanforth

Recent work has uncovered the interesting (and somewhat surprising) finding that training models to be invariant to adversarial perturbations requires substantially larger datasets than those required for standard classification. This result is a key hurdle in the deployment of robust machine learning models in many real world applications where labeled data

Igor Andreoni, Daniel A. Goldstein, Shreya Anand, Michael W. Coughlin

The first two months of the third Advanced LIGO and Virgo observing run (2019 April-May) showed that distant gravitational wave (GW) events can now be readily detected. Three candidate mergers containing neutron stars (NS) were reported in a span of 15 days, all likely located more than 100 Mpc away. However, distant events such as the three new NS mergers a

Dennis Hansen, Jelle Hartong, Niels A. Obers

We present a systematic technique to expand the Einstein-Hilbert Lagrangian in inverse powers of the speed of light squared. The corresponding result for the non-relativistic gravity Lagrangian is given up to next-to-next-to-leading order. The techniques are universal and can be used to expand any Lagrangian theory whose fields are a function of a given para

Phillip Andreae

We introduce multi-torsion, a spectral invariant generalizing Ray-Singer analytic torsion. We define multi-torsion for compact manifolds with a certain local geometric product structure that gives a bigrading on differential forms. We prove that multi-torsion is metric-independent in a suitable sense. Our definition of multi-torsion is inspired by an interpr

Cyril Renevey

In this review we aim to describe the most stringent tests of the strong equivalence principle, the fundamental principle of General Relativity, using pulsar timing. For this purpose, we first construct the parametrized post-Newtonian and post-Keplerian formalism together with their parameters. Then we constrain the post-Newtonian parameters associated to th

Antonio F. Costa, Cam Van Quach Hongler

This paper is devoted to prove the existence of $q$-periodic alternating projections of prime alternating $q$-periodic knots. The main tool is the Menasco-Thistlethwaite's Flyping theorem. Let $K$ be an oriented prime alternating knot that is $q$-periodic with $q\geq 3$, i.e. $K$ admits a symmetry that is a rotation of order $q$. Then $K$ has an alternat

Beatrice à kerblom, Elias Castegren, Tobias Wrigstad

The array is a fundamental data structure that provides an efficient way to store and retrieve non-sparse data contiguous in memory. Arrays are important for the performance of many memory-intensive applications due to the design of modern memory hierarchies: contiguous storage facilitates spatial locality and predictive access patterns which enables prefetc

Nathan Canen, Kyungchul Song

Structural models that admit multiple reduced forms, such as game-theoretic models with multiple equilibria, pose challenges in practice, especially when parameters are set-identified and the identified set is large. In such cases, researchers often choose to focus on a particular subset of equilibria for counterfactual analysis, but this choice can be hard

A. Emin Orhan, Xaq Pitkow

Training recurrent neural networks (RNNs) is a hard problem due to degeneracies in the optimization landscape, a problem also known as vanishing/exploding gradients. Short of designing new RNN architectures, previous methods for dealing with this problem usually boil down to orthogonalization of the recurrent dynamics, either at initialization or during the

Giorgio Galanti, Fulvio Piccinini, Fabrizio Tavecchio, Marco Roncadelli

Surprisingly, the contribution to the cosmic opacity to UHE ($E>10^{18} \, \rm eV$) $γ$-rays has been systematically computed so far for the $γγ\to e^+e^-$ and $γγ\to e^+ e^- e^+ e^-$ processes alone. We go a step further by systematically evaluating the additional opacity brought about by other leptons and hadrons. We find that the dominant channels are tho

Davide Cellai, Trevor Fitzpatrick

Measurement and management of credit concentration risk is critical for banks and relevant for micro-prudential requirements. While several methods exist for measuring credit concentration risk within institutions, the systemic effect of different institutions' exposures to the same counterparties has been less explored so far. In this paper, we propose

Ivan Almeida, Rodrigo Nemmen

Outflows produced by a supermassive black hole (SMBH) can have important feedback effects in its host galaxy. An unresolved question is the nature and properties of winds from SMBHs accreting at low rates in low-luminosity active galactic nuclei (LLAGNs). We performed two-dimensional numerical, hydrodynamical simulations of radiatively inefficient accretion

Zoran Ristivojevic

We develop an alternative description to solve the problem of the ground-state energy of the Lieb-Liniger model that describes one-dimensional bosons with contact repulsion. For this integrable model we express the Lieb integral equation in the representation of Chebyshev polynomials. The latter form is convenient to efficiently obtain very precise numerical

D0 Collaboration

We study the production of the exotic charged charmonium-like state $Z_c^{\pm}(3900)$ in $p \bar p$ collisions through the sequential process $ψ(4260) \rightarrow Z_c^{\pm}(3900) π^{\mp}$, $Z_c^{\pm}(3900) \rightarrow J/ψπ^{\pm}$. Using the subsample of candidates originating from semi-inclusive weak decays of $b$-flavored hadrons, we measure the invariant m

Sara Saeedi, Manami Sasaki, Beate Stelzer, Lorenzo Ducci

A previous study of the X-ray luminosity function of the X-ray sources in the field of the Draco dwarf spheroidal (dSph) galaxy indicated the presence of a population of unknown X-ray sources in the soft energy range of 0.5-2 keV. In 2015, Draco dSph was observed again in twenty-six deep XMM-Newton, observations providing an opportunity for a new study of th

Yifeng Fan, Tingran Gao, Zhizhen Zhao

We develop in this paper a novel intrinsic classification algorithm -- multi-frequency class averaging (MFCA) -- for classifying noisy projection images obtained from three-dimensional cryo-electron microscopy (cryo-EM) by the similarity among their viewing directions. This new algorithm leverages multiple irreducible representations of the unitary group to

G. de La Vieuville, D. Bina, R. Pello, G. Mahler

We present the results obtained with VLT/MUSE on the faint-end of the Lyman-alpha luminosity function (LF) based on deep observations of four lensing clusters. The precise aim of the present study is to further constrain the abundance of Lyman-alpha emitters (LAEs) by taking advantage of the magnification provided by lensing clusters. We blindly selected a s

Halaleh Kamari, Sylvie Huet, Marie-Luce Taupin

In this paper, we propose an R package, called RKHSMetaMod, that implements a procedure for estimating a meta-model of a complex model. The meta-model approximates the Hoeffding decomposition of the complex model and allows us to perform sensitivity analysis on it. It belongs to a reproducing kernel Hilbert space that is constructed as a direct sum of Hilber

Evgeni Dimitrov, Xuan Wu

In this paper we prove an analogue of the Komlós-Major-Tusnády (KMT) embedding theorem for random walk bridges. The random bridges we consider are constructed through random walks with i.i.d jumps that are conditioned on the locations of their endpoints. We prove that such bridges can be strongly coupled to Brownian bridges of appropriate variance when the j

Ming Yan, Michael A. Calkins, Stefano Maffei, Keith Julien

Numerical simulations of quasi-static magnetoconvection with a vertical magnetic field are carried out up to a Chandrasekhar number of $Q=10^8$ over a broad range of Rayleigh numbers $Ra$. Three magnetoconvection regimes are identified: two of the regimes are magnetically-constrained in the sense that a leading-order balance exists between the Lorentz and bu

Eugene Kharitonov, Rahma Chaabouni, Diane Bouchacourt, Marco Baroni

There is growing interest in studying the languages that emerge when neural agents are jointly trained to solve tasks requiring communication through a discrete channel. We investigate here the information-theoretic complexity of such languages, focusing on the basic two-agent, one-exchange setup. We find that, under common training procedures, the emergent

Willian M. H. Natori, Roderich Moessner, Johannes Knolle

We study the effect of a magnetic field on the low energy description of Mott insulators with strong spin-orbit (SO) coupling. In contrast to the standard case of the Hubbard model without SO coupling, we show that Peierls phases can modulate the magnetic exchange at leading order in the interaction. Our mechanism crucially depends on the existence of distin

Andrea Testa, Francesco Farina, Giuseppe Notarstefano

In this paper we deal with a network of computing agents with local processing and neighboring communication capabilities that aim at solving (without any central unit) a submodular optimization problem. The cost function is the sum of many local submodular functions and each agent in the network has access to one function in the sum only. In this \emph{dist

Aidan N. Gomez, Ivan Zhang, Siddhartha Rao Kamalakara, Divyam Madaan

Neural networks are easier to optimise when they have many more weights than are required for modelling the mapping from inputs to outputs. This suggests a two-stage learning procedure that first learns a large net and then prunes away connections or hidden units. But standard training does not necessarily encourage nets to be amenable to pruning. We introdu

Vojtěch Kovařík, Dominik Seitz, Viliam Lisý, Jan Rudolf

We provide a formal definition of depth-limited games together with an accessible and rigorous explanation of the underlying concepts, both of which were previously missing in imperfect-information games. The definition works for an arbitrary extensive-form game and is not tied to any specific game-solving algorithm. Moreover, this framework unifies and sign

Luis A. Correa, Buqing Xu, Benjamin Morris, Gerardo Adesso

The reaction-coordinate mapping is a useful technique to study complex quantum dissipative dynamics into structured environments. In essence, it aims to mimic the original problem by means of an 'augmented system', which includes a suitably chosen collective environmental coordinate---the 'reaction coordinate'. This composite then couples to

Freddy Lecue, Jiaoyan Chen, Jeff Z. Pan, Huajun Chen

Transfer learning aims at building robust prediction models by transferring knowledge gained from one problem to another. In the semantic Web, learning tasks are enhanced with semantic representations. We exploit their semantics to augment transfer learning by dealing with when to transfer with semantic measurements and what to transfer with semantic embeddi

Rasmus S. L. Hansen, Alexei Yu. Smirnov

In supernovae neutrinos are emitted from a region with a width $r_{\rm eff}$ of a few kilometers (rather than from a surface of infinitesimal width). We study the effect of integration (averaging) over such an extended emission region on collective oscillations. The averaging leads to additional suppression of the correlation (off-diagonal element of the den

Jeffrey M. Ede, Richard Beanland

Compressed sensing algorithms are used to decrease electron microscope scan time and electron beam exposure with minimal information loss. Following successful applications of deep learning to compressed sensing, we have developed a two-stage multiscale generative adversarial neural network to complete realistic 512$\times$512 scanning transmission electron

Shigehiro Yasui, Chandrasekhar Chatterjee, Muneto Nitta

We study surface effects of neutron $^{3}P_{2}$ superfluids in neutron stars. $^{3}P_{2}$ superfluids are in uniaxial nematic (UN), D$_{2}$ biaxial nematic (BN), or D$_{4}$ BN phase, depending on the strength of magnetic fields from small to large. We suppose a neutron $^{3}P_{2}$ superfluid in a ball with a spherical boundary. Adopting a suitable boundary c

Siddhartha Mishra, Carlos Parés-Pulido, Kyle G. Pressel

We propose a WENO finite difference scheme to approximate anelastic flows, and scalars advected by them, on staggered grids. In contrast to existing WENO schemes on staggered grids, the proposed scheme is designed to be arbitrarily high-order accurate as it judiciously combines ENO interpolations of velocities with WENO reconstructions of spatial derivatives

Francesco Locatello, Gabriele Abbati, Tom Rainforth, Stefan Bauer

Recently there has been a significant interest in learning disentangled representations, as they promise increased interpretability, generalization to unseen scenarios and faster learning on downstream tasks. In this paper, we investigate the usefulness of different notions of disentanglement for improving the fairness of downstream prediction tasks based on

Dmitry Arkhangelsky, Vasily Korovkin

We develop an estimator for applications where the variable of interest is endogenous and researchers have access to aggregate instruments. Our method addresses the critical identification challenge -- unobserved confounding, which renders conventional estimators invalid. Our proposal relies on a new data-driven aggregation scheme that eliminates the unobser

Liyuan Xu, Junya Honda, Gang Niu, Masashi Sugiyama

Uncoupled regression is the problem to learn a model from unlabeled data and the set of target values while the correspondence between them is unknown. Such a situation arises in predicting anonymized targets that involve sensitive information, e.g., one's annual income. Since existing methods for uncoupled regression often require strong assumptions on