March 2020 arXiv papers — page 128

Julie Stephany Berrio, Mao Shan, Stewart Worrall, James Ward

To navigate through urban roads, an automated vehicle must be able to perceive and recognize objects in a three-dimensional environment. A high-level contextual understanding of the surroundings is necessary to plan and execute accurate driving maneuvers. This paper presents an approach to fuse different sensory information, Light Detection and Ranging (lida

A. C. Bovik

In this rather informal paper and talk I will discuss my own experiences, feelings, and evolution as an Image Processing and Digital Video educator trying to navigate the Deep Learning revolution. I will discuss my own ups and downs of trying to deal with extremely rapid technological changes, and how I have reacted to, and dealt with consequent dramatic cha

Shi-min Liu, Hua Wu, Da-jun Zhang

Solutions of the classical and nonlocal Gross-Pitaevskii (GP) equation with a parabolic potential and a gain term are derived by using a second order nonisospectral Ablowitz-Kaup-Newell-Segur system and reduction technique of double Wronskians. Solutions of the classical GP equation show typical space-time localized characteristics. An interesting dynamics,

Pierre-Luc Dallaire-Demers, Michał Stęchły, Jerome F. Gonthier, Ntwali Toussaint Bashige

It is expected that the simulation of correlated fermions in chemistry and material science will be one of the first practical applications of quantum processors. Given the rapid evolution of quantum hardware, it is increasingly important to develop robust benchmarking techniques to gauge the capacity of quantum hardware specifically for the purpose of fermi

Zhong-Qiu Wang, DeLiang Wang

This study proposes a multi-microphone complex spectral mapping approach for speech dereverberation on a fixed array geometry. In the proposed approach, a deep neural network (DNN) is trained to predict the real and imaginary (RI) components of direct sound from the stacked reverberant (and noisy) RI components of multiple microphones. We also investigate th

Rosy Oh, Joseph H. T. Kim, Jae Youn Ahn

In auto insurance, a Bonus-Malus System (BMS) is commonly used as a posteriori risk classification mechanism to set the premium for the next contract period based on a policyholder's claim history. Even though recent literature reports evidence of a significant dependence between frequency and severity, the current BMS practice is to use a frequency-base

Changzeng Fu, Chaoran Liu, Carlos Toshinori Ishi, Yuichiro Yoshikawa

Text categorization is the task of assigning labels to documents written in a natural language, and it has numerous real-world applications including sentiment analysis as well as traditional topic assignment tasks. In this paper, we propose 5 different configurations for the semantic matrix-based memory neural network with end-to-end learning manner and eva

Ali Calim, Joaquin J. Torres, Mahmut Ozer, Muhammet Uzuntarla

Here we study the emergence of chimera states, a recently reported phenomenon referring to the coexistence of synchronized and unsynchronized dynamical units, in a population of Morris-Lecar neurons which are coupled by both electrical and chemical synapses, constituting a hybrid synaptic architecture, as in actual brain connectivity. This scheme consists of

Zheng Jiayin, Zheng Yingye, Hsu Li

Predicting risks of chronic diseases has become increasingly important in clinical practice. When a prediction model is developed in a given source cohort, there is often a great interest to apply the model to other cohorts. However, due to potential discrepancy in baseline disease incidences between different cohorts and shifts in patient composition, the r

Peng Lin, Wei Ren, Huijun Gao

In this paper, a distributed velocity-constrained consensus problem is studied for discrete-time multi-agent systems, where each agent's velocity is constrained to lie in a nonconvex set. A distributed constrained control algorithm is proposed to enable all agents to converge to a common point using only local information. {The gains of the algorithm for

Maria Chudnovsky, Cemil Dibek, Paul Seymour

A graph is strongly perfect if every induced subgraph H has a stable set that meets every nonempty maximal clique of H. The characterization of strongly perfect graphs by a set of forbidden induced subgraphs is not known. Here we provide several new minimal non-strongly-perfect graphs.

B. Tabone, B. Godard, G. Pineau des Forêts, S. Cabrit

Recent ALMA observations suggest that the highest velocity part of molecular protostellar jets are launched from the dust-sublimation regions of the accretion disks (<0.3 au). However, formation and survival of molecules in inner protostellar disk winds, in the presence of a harsh FUV radiation field and the absence of dust, remain unexplored. We aim at dete

Shlomo S. Razamat, Gabi Zafrir

We suggest three new ${\cal N}=1$ conformal dual pairs. First, we argue that the ${\cal N}=2$ $E_6$ Minahan-Nemeschansky (MN) theory with a $USp(4)$ subgroup of the $E_6$ global symmetry conformally gauged with an ${\cal N}=1$ vector multiplet and certain additional chiral multiplet matter resides at some cusp of the conformal manifold of an $SU(2)^5$ quiver

Kouyemon Iriye, Daisuke Kishimoto, Ran Levi

A generalised Postnikov tower for a space $X$ is a tower of principal fibrations with fibres generalised Eilenberg-MacLane spaces, whose inverse limit is weakly homotopy equivalent to $X$. In this paper we give a characterisation of a polyhedral product $Z_K(X,A)$ whose universal cover either admits a generalised Postnikov tower of finite length, or is a hom

Nishant Budhdev, Mun Choon Chan, Tulika Mitra

5G presents a unique set of challenges for cellular network architecture. The architecture needs to be versatile in order to handle a variety of use cases. While network slicing has been proposed as a way to provide such versatility, it is also important to ensure that slices do not adversely interfere with each other. In other words, isolation among network

C. R. O&#39;Dell, N. P. Abel, G. J. Ferland

Based on imaging and spectroscopic data, we develop a 3-D model for the Huygens Region of the Orion Nebula. Theta1OriC , the hottest star in the Trapezium, is surrounded by a wind-blown Central Bubble that opens SW into the Extended Orion Nebula. Outside of this feature lies a layer of ionized gas at about 0.4 pc from Theta1OriC. Both of these features are m

Osama Zwaid Alsulami, Khulood D. Alazwary, Sarah O. M. Saeed, Sanaa Hamid Mohamed

Optical wireless communication (OWC) systems have been the subject of a significant amount of interest as they can be used in sixth generation (6G) wireless communication to provide high data rates and support multiple users simultaneously. This paper investigates the impact of receiver orientation on resource allocation in optical wireless systems, using a

Nathan Vaughn, Leighton Wilson, Robert Krasny

We present an MPI + OpenACC implementation of the kernel-independent barycentric Lagrange treecode (BLTC) for fast summation of particle interactions on GPUs. The distributed memory parallelization uses recursive coordinate bisection for domain decomposition and MPI remote memory access to build locally essential trees on each rank. The particle interactions

Yuzhong Huang, Andres Abeliuk, Fred Morstatter, Pavel Atanasov

In a crowd forecasting system, aggregation is an algorithm that returns aggregated probabilities for each question based on the probabilities provided per question by each individual in the crowd. Various aggregation methods have been proposed, but simple strategies like linear averaging or selecting the best-performing individual remain competitive. With th

Mikołaj K. Schmidt, Christopher G. Poulton, Michael J. Steel

Quantum acoustodynamics (QAD) is a rapidly developing field of research, offering possibilities to realize and study macroscopic quantum-mechanical systems in a new range of frequencies, and implement transducers and new types of memories for hybrid quantum devices. Here we propose a novel design for a versatile diamond QAD cavity operating at GHz frequencie

Nathan Vaughn, Vikram Gavini, Robert Krasny

We present a real-space computational method called treecode-accelerated Green Iteration (TAGI) for all-electron Kohn-Sham Density Functional Theory. TAGI is based on a reformulation of the Kohn-Sham equations in which the eigenvalue problem in differential form is converted into a fixed-point problem in integral form by convolution with the modified Helmhol

P. R. C. Kent, Abdulgani Annaberdiyev, Anouar Benali, M. Chandler Bennett

We review recent advances in the capabilities of the open source ab initio Quantum Monte Carlo (QMC) package QMCPACK and the workflow tool Nexus used for greater efficiency and reproducibility. The auxiliary field QMC (AFQMC) implementation has been greatly expanded to include k-point symmetries, tensor-hypercontraction, and accelerated graphical processing

Simone Muselli

Let $C: y^2=f(x)$ be a hyperelliptic curve of genus $g\geq 1$, defined over a complete discretely valued field $K$, with ring of integers $O_K$. Under certain conditions on $C$, mild when residue characteristic is not $2$, we explicitly construct the minimal regular model with normal crossings $\mathcal{C}/O_K$ of $C$. In the same setting we determine a basi

Christophe Ley

The normal distribution is well-known for several results that it is the only to fulfil. The aim of the present paper is to show that many of these characterizations actually follow from the fact that the derivative of the log-density of the normal distribution is the (negative) identity function. This \emph{a priori} very simple yet surprising observation a

Cédric Colas, Joost Huizinga, Vashisht Madhavan, Jeff Clune

Quality-Diversity (QD) algorithms, and MAP-Elites (ME) in particular, have proven very useful for a broad range of applications including enabling real robots to recover quickly from joint damage, solving strongly deceptive maze tasks or evolving robot morphologies to discover new gaits. However, present implementations of MAP-Elites and other QD algorithms

Michael L. Goodman, Chiman Kwan, Bulent Ayhan, Eric L. Shang

All three components of the current density are required to compute the heating rate due to free magnetic energy dissipation. Here we present a first test of a new model developed to determine if the times of increases in the resistive heating rate in active region (AR) photospheres are correlated with the subsequent occurrence of M and X flares in the coron

Qianggong Zhang, Yanyang Gu, Michalkiewicz Mateusz, Mahsa Baktashmotlagh

In conventional formulations of multilayer feedforward neural networks, the individual layers are customarily defined by explicit functions. In this paper we demonstrate that defining individual layers in a neural network \emph{implicitly} provide much richer representations over the standard explicit one, consequently enabling a vastly broader class of end-

Pedro Alonso, Kumar Shridhar, Denis Kleyko, Evgeny Osipov

Recent advances in Deep Learning have led to a significant performance increase on several NLP tasks, however, the models become more and more computationally demanding. Therefore, this paper tackles the domain of computationally efficient algorithms for NLP tasks. In particular, it investigates distributed representations of n-gram statistics of texts. The

Thomas Spooner, Rahul Savani

We show that adversarial reinforcement learning (ARL) can be used to produce market marking agents that are robust to adversarial and adaptively-chosen market conditions. To apply ARL, we turn the well-studied single-agent model of Avellaneda and Stoikov [2008] into a discrete-time zero-sum game between a market maker and adversary. The adversary acts as a p

Teresa Crespo

We determine the Hopf Galois structures on a Galois field extension of degree twice an odd prime square and classify the corresponding left braces. Besides we determine the separable field extensions of degree twice an odd prime square allowing a cyclic Hopf Galois structure and the number of these structures.

Yizhou Wang, Zhongyu Jiang, Xiangyu Gao, Jenq-Neng Hwang

Radar is usually more robust than the camera in severe driving scenarios, e.g., weak/strong lighting and bad weather. However, unlike RGB images captured by a camera, the semantic information from the radar signals is noticeably difficult to extract. In this paper, we propose a deep radar object detection network (RODNet), to effectively detect objects purel

Eleni-Alexandra Kontou, Ko Sanders

This review summarizes the current status of the energy conditions in general relativity and quantum field theory. We provide a historical review and a summary of technical results and applications, complemented with a few new derivations and discussions. We pay special attention to the role of the equations of motion and to the relation between classical an

Alexander Pavlis, Christina Psaroudaki

We investigate the propagation of magnetic skyrmions on elastically deformable geometries by employing imaginary time quantum field theory methods. We demonstrate that the Euclidean action of the problem carries information of the elements of the surface space metric, and develop a description of the skyrmion dynamics in terms of a set of collective coordina

Hang Chen, Vahan Huroyan, Stephen Kobourov, Myroslav Kryven

We consider 15 properties of labeled random graphs that are of interest in the graph-theoretical and the graph mining literature, such as clustering coefficients, centrality measures, spectral radius, degree assortativity, treedepth, treewidth, etc. We analyze relationships and correlations between these properties. Whereas for graphs on a small number of ve

Thomas Schweigler, Marek Gluza, Mohammadamin Tajik, Spyros Sotiriadis

Gaussian models provide an excellent effective description of many quantum many-body systems ranging from condensed matter systems all the way to neutron stars. Gaussian states are common at equilibrium when the interactions are weak. Recently it was proposed that they can also emerge dynamically from a non-Gaussian initial state evolving under non-interacti

Marco Morucci, Vittorio Orlandi, Sudeepa Roy, Cynthia Rudin

We propose a matching method for observational data that matches units with others in unit-specific, hyper-box-shaped regions of the covariate space. These regions are large enough that many matches are created for each unit and small enough that the treatment effect is roughly constant throughout. The regions are found as either the solution to a mixed inte

Piaomu Liu

In different areas of research, multiple recurrent competing risks (RCR) are often observed on the same observational unit. For instance, different types of cancer relapses are observed on the same patient and several types of component failures are observed in the same reliability system. When a terminal event (TE) such as death is also observed on the same

Tianyuan Jin, Pan Xu, Jieming Shi, Xiaokui Xiao

Thompson sampling is one of the most widely used algorithms for many online decision problems, due to its simplicity in implementation and superior empirical performance over other state-of-the-art methods. Despite its popularity and empirical success, it has remained an open problem whether Thompson sampling can match the minimax lower bound $Ω(\sqrt{KT})$

Philip Sperl, Jan-Philipp Schulze, Konstantin Böttinger

Inspired by recent advances in coverage-guided analysis of neural networks, we propose a novel anomaly detection method. We show that the hidden activation values contain information useful to distinguish between normal and anomalous samples. Our approach combines three neural networks in a purely data-driven end-to-end model. Based on the activation values

J. M. Munoz-Castaneda, L. Santamaria-Sanz, M. Donaire, M. Tello-Fraile

In this paper we study the system of a scalar quantum field confined between two plane, isotropic, and homogeneous parallel plates at thermal equilibrium. We represent the plates by the most general lossless and frequency-independent boundary conditions that satisfy the conditions of isotropy and homogeneity and are compatible with the unitarity of the quant

Sean Eberhard, Freddie Manners, Rudi Mrazović

Hall and Paige conjectured in 1955 that a finite group $G$ has a complete mapping if and only if its Sylow $2$-subgroups are trivial or noncyclic. This conjecture was proved in 2009 by Wilcox, Evans, and Bray using the classification of finite simple groups and extensive computer algebra. Using a completely different approach motivated by the circle method f

Mao Ye, Chengyue Gong, Lizhen Nie, Denny Zhou

Recent empirical works show that large deep neural networks are often highly redundant and one can find much smaller subnetworks without a significant drop of accuracy. However, most existing methods of network pruning are empirical and heuristic, leaving it open whether good subnetworks provably exist, how to find them efficiently, and if network pruning ca

Katrin Becker, Daniel Butter

Motivated by recent efforts to encode 11D supergravity in 4D N=1 superfields, we introduce a general covariant framework relevant for describing any higher dimensional supergravity theory in external 4D N=1 superspace with n additional internal coordinates. The superspace geometry admits both external and internal diffeomorphisms and provides the superfields

Aliaksei Kachanovich, Ulrich Nierste, Ivan Nišandžić

We consider a Higgs portal model in which the 125-GeV Higgs boson mixes with a light singlet mediator $h_2$ coupling to particles of a Dark Sector and study potential $b\to s h_2$ decays in the Belle II experiment. Multiplying the gauge-dependent off-shell Standard-Model $b$-$s$-Higgs vertex with the sine of the Higgs mixing angle does not give the correct $

Jacob Bernstein, Francesco Maggi

By employing the method of moving planes in a novel way we extend some classical symmetry and rigidity results for smooth minimal surfaces to surfaces that have singularities of the sort typically observed in soap films.

Joshua Aurand, Yu-Jui Huang

This paper studies optimal consumption, investment, and healthcare spending under Epstein-Zin preferences. Given consumption and healthcare spending plans, Epstein-Zin utilities are defined over an agent&#39;s random lifetime, partially controllable by the agent as healthcare reduces mortality growth. To the best of our knowledge, this is the first time Epst

Vaishali Ingale, Pushpender Singh

Multiple-choice machine reading comprehension is difficult task as its required machines to select the correct option from a set of candidate or possible options using the given passage and question.Reading Comprehension with Multiple Choice Questions task,required a human (or machine) to read a given passage, question pair and select the best one option fro

Sabrina Pauli

We use Macaulay2 for several enriched counts in GW(k). First, we compute the count of lines on a general cubic surface using Macaulay2 over Fp in GW(Fp) for p a prime number and over the rational numbers Q in GW(Q). This gives a new proof for the fact that the count of lines on a cubic surface is 3+12h in GW(k) where h denotes the hyperbolic form. Then, we c

Tianyu Wang, Julian Whitman, Matthew Travers, Howie Choset

Snake robots have the potential to maneuver through tightly packed and complex environments. One challenge in enabling them to do so is the complexity in determining how to coordinate their many degrees-of-freedom to create purposeful motion. This is especially true in the types of terrains considered in this work: environments full of unmodeled features tha

Robert Mieth, Matt Roveto, Yury Dvorkin

Existing electricity market designs assume risk neutrality and lack risk-hedging instruments, which leads to suboptimal market outcomes and reduces the overall market efficiency. This paper enables risk-trading in the chance-constrained stochastic electricity market by introducing Arrow-Debreu Securities (ADS) and derives a risk-averse market-clearing model

Miguel A. F. Sanjuan

Machine learning and deep learning techniques are contributing much to the advancement of science. Their powerful predictive capabilities appear in numerous disciplines, including chaotic dynamics, but they miss understanding. The main thesis here is that prediction and understanding are two very different and important ideas that should guide us about the p

Noam Elron, Shahar S. Yuval, Dmitry Rudoy, Noam Levy

Many image restoration techniques are highly dependent on the degradation used during training, and their performance declines significantly when applied to slightly different input. Blind and universal techniques attempt to mitigate this by producing a trained model that can adapt to varying conditions. However, blind techniques to date require prior knowle

Svetlana V. Postolova, Alexey Yu. Mironov, Víctor Barrena, Jose Benito-Llorens

We study the electronic densities of states (DOS) of strongly disordered superconducting thin films of TiN. We find, using Scanning Tunneling Microscopy (STM) that the DOS decreases towards the Fermi level in the normal phase obtained by applying magnetic fields. The DOS shows spatial fluctuations whose length scale is related to the energy dependent DOS and

Jason Olsthoorn, Edmund W. Tedford, Gregory A. Lawrence

We investigate the convective cooling of a fluid with a quadratic equation of state by performing three-dimensional direct numerical simulations of a flow with a fixed top-boundary temperature, which is lower than the initial fluid temperature. We consider fluid temperatures near the density maximum, where the nonlinearity is expected to be important. When t

M. V. Dolgopolik

We present a unified study of first and second order necessary and sufficient optimality conditions for minimax and Chebyshev optimisation problems with cone constraints. First order optimality conditions for such problems can be formulated in several different forms: in terms of a linearised problem, in terms of Lagrange multipliers (KKT-points), in terms o

Martin Lustig

We define train track maps for graphs-of-groups $\cal G$ and exhibit the precise conditions under which the fundamental finiteness properties known for classical train track maps extend to this generalization. These finiteness properties are the crucial tool to control the decrease of illegal turns under iteration of the train track map, and they are a princ

G. Sala, M. B. Stone, Binod K. Rai, A. F. May

The magnetic excitation spectrum of the quantum magnet YbCl$_3$ is studied with inelastic neutron scattering. The spectrum exhibits an unusually sharp feature within a broad continuum, as well as conventional spin waves. By including both transverse and longitudinal channels of the neutron response, linear spin wave theory with a single Heisenberg interactio

Charles Millard, Aaron T Hess, Boris Mailhé, Jared Tanner

The Approximate Message Passing (AMP) algorithm efficiently reconstructs signals which have been sampled with large i.i.d. sub-Gaussian sensing matrices. Central to AMP is its &#34;state evolution&#34;, which guarantees that the difference between the current estimate and ground truth (the &#34;aliasing&#34;) at every iteration obeys a Gaussian distribution

Olivier J. Walther, Steven M. Radil, David Russell, Marie Trémolières

Modern armed conflicts have a tendency to cluster together and spread geographically. However, the geography of most conflicts remains under-studied. To fill this gap, this article presents a new indicator that measures two key geographical properties of subnational political violence: the conflict intensity within a region on the one hand, and the spatial d

Francisco J Beron-Vera, Philippe Miron

Inertial particles (i.e. with mass and of finite size) immersed in a fluid in motion are unable to adapt their velocities to the carrying flow and thus they have been the subject of much interest in fluid mechanics. In this paper we consider an ocean setting with inertial particles elastically connected forming a network that floats at the interface with the

Mariano Real, Daniel Gresta, Christian Reichl, Jurgen Weis

We measure the thermoelectric response of Corbino structures in the quantum Hall effect regime and compare it with a theoretical analysis. The measured thermoelectric voltages are qualitatively and quantitatively simulated based upon the independent measurement of the conductivity indicating that they originate predominantly from the electron diffusion. Elec

Victor Veitch, Anisha Zaveri

It is a truth universally acknowledged that an observed association without known mechanism must be in want of a causal estimate. However, causal estimation from observational data often relies on the (untestable) assumption of `no unobserved confounding&#39;. Violations of this assumption can induce bias in effect estimates. In principle, such bias could in

Juba Bouaziz, Filipe Souza Mendes Guimarães, Samir Lounis

Many-body phenomena are paramount in physics. In condensed matter, their hallmark is considerable on a wide range of material characteristics spanning electronic, magnetic, thermodynamic and transport properties. They potentially imprint non-trivial signatures in spectroscopic measurements, such as those assigned to Kondo, excitonic and polaronic features, w

Kamak Ebadi, Yun Chang, Matteo Palieri, Alex Stephens

Simultaneous Localization and Mapping (SLAM) in large-scale, unknown, and complex subterranean environments is a challenging problem. Sensors must operate in off-nominal conditions; uneven and slippery terrains make wheel odometry inaccurate, while long corridors without salient features make exteroceptive sensing ambiguous and prone to drift; finally, spuri

A. Zamora, N. Lad, M. H. Szymanska

We study the dynamics of vortices in a two-dimensional, non-equilibrium system, described by the compact Kardar-Parisi-Zhang equation, after a sudden quench across the critical region. Our exact numerical solution of the phase-ordering kinetics shows that the unique interplay between non-equilibrium and the variable degree of spatial anisotropy leads to diff

Lorenzo Di Pietro, Marco Serone

We study the conformal window of QCD using perturbation theory, starting from the perturbative upper edge and going down as much as we can towards the strongly coupled regime. We do so by exploiting the available five-loop computation of the $\overline{{\rm MS}}$ $\beta$-function and employing Borel resummation techniques both for the ordinary perturbative s

Jonathan Squire, Philip F. Hopkins

We develop simple, physically motivated models for drag-induced dust-gas streaming instabilities, which are thought to be crucial for clumping grains to form planetesimals in protoplanetary disks. The models explain, based on the physics of gaseous epicyclic motion and dust-gas drag forces, the most important features of the streaming instability and its sim

L. Baudis, Y. Biondi, M. Galloway, F. Girard

For the first time, a small dual-phase (liquid/gas) xenon time projection chamber was equipped with a top array of silicon photomultipliers for light and charge readout. Here we describe the instrument in detail, as well as the data processing and the event position reconstruction algorithms. We obtain a spatial resolution of ~1.5 mm in the horizontal plane.

C. A. Cremonini, P. A. Grassi, S. Penati

We study supersymmetric Wilson loops from a geometrical perspective. To this end, we propose a new formulation of these operators in terms of an integral form associated to the immersion of the loop into a supermanifold. This approach provides a unifying description of Wilson loops preserving different sets of supercharges, and clarifies the flow between the

Benjamin P. M. Laevens, Olav ten Bosch, Frank P. Pijpers, Wilfried G. J. H. M. van Sark

This paper presents a classical estimation problem for calculating the energy generated by photovoltaic solar energy systems in the Netherlands, on a daily, annual and regional basis. We identify two data sources to construct our methodology: pvoutput, an online portal with solar energy yield measurements, and modelled irradiance data, from the Royal Netherl

Nir Mandelker, Frank C. van den Bosch, Daisuke Nagai, Avishai Dekel

We present an analytic toy model for the radiation produced by the interaction between the cold streams thought to feed massive halos at high redshift and their hot CGM. We begin by deriving cosmologically motivated parameters for the streams as they enter the halo virial radius, $R_{\rm v}$, as a function of halo mass and redshift. For $10^{12}M_{\odot}$ ha

Catarina Cosme, Maíra Dutra, Teng Ma, Yongcheng Wu

We study the freeze-in production of Feebly Interacting Massive Particle (FIMP) dark matter candidates through a neutrino portal. We consider a hidden sector comprised of a fermion and a complex scalar, with the lightest one regarded as a FIMP candidate. We implement the Type-I Seesaw mechanism for generating the masses of the Standard Model (SM) neutrinos a

Lukas Janssen, Wei Wang, Michael M. Scherer, Zi Yang Meng

The coupling between fermionic matter and gauge fields plays a fundamental role in our understanding of nature, while at the same time posing a challenging problem for theoretical modeling. In this situation, controlled information can be gained by combining different complementary approaches. Here, we study a confinement transition in a system of $N_f$ flav

Adrian Bulat, Brais Martinez, Georgios Tzimiropoulos

This paper proposes Binary ArchitecTure Search (BATS), a framework that drastically reduces the accuracy gap between binary neural networks and their real-valued counterparts by means of Neural Architecture Search (NAS). We show that directly applying NAS to the binary domain provides very poor results. To alleviate this, we describe, to our knowledge, for t

A. A. Antoniou, R. A. C. Edmonds, B. Kubik, C. O&#39;Neill

A numerical semigroup $S$ is a cofinite, additively-closed subset of the nonnegative integers that contains $0$. In this paper, we initiate the study of atomic density, an asymptotic measure of the proportion of irreducible elements in a given ring or semigroup, for semigroup algebras. It is known that the atomic density of the polynomial ring $\mathbb{F}_q[

Donald J. Hejna, Pieter Abbeel, Lerrel Pinto

Learning long-range behaviors on complex high-dimensional agents is a fundamental problem in robot learning. For such tasks, we argue that transferring learned information from a morphologically simpler agent can massively improve the sample efficiency of a more complex one. To this end, we propose a hierarchical decoupling of policies into two parts: an ind

Shane Farnsworth

Jordan algebras were first introduced in an effort to restructure quantum mechanics purely in terms of physical observables. In this paper we explain why, if one attempts to reformulate the internal structure of the standard model of particle physics geometrically, one arrives naturally at a discrete internal geometry that is coordinatized by a Jordan algebr

Alexander Kolpakov, Stefano Riolo, Leone Slavich

This paper shows that many hyperbolic manifolds obtained by glueing arithmetic pieces embed into higher-dimensional hyperbolic manifolds as codimension-one totally geodesic submanifolds. As a consequence, many Gromov--Pyatetski-Shapiro and Agol--Belolipetsky--Thomson non-arithmetic manifolds embed geodesically. Moreover, we show that the number of commensura

Shiro Tamiya, Sho Koh, Yuya O. Nakagawa

The variational quantum eigensolver (VQE) is an algorithm to find eigenenergies and eigenstates of systems in quantum chemistry and quantum many-body physics. The VQE is one of the most promising applications of near-term quantum devices to investigate such systems. Here we propose an extension of the VQE to calculate the nonadiabatic couplings of molecules

Hong Yang, Hayate Nakano, Hosho Katsura

We theoretically demonstrate that interacting symmetry-protected topological (SPT) phases can be realized with ultracold spinful bosonic atoms loaded on the lattices which have a flat band at the bottom of the band structure. Ground states of such systems are not conventional Mott insulators in the sense that the ground states possess not only spin fluctuati

Aldo Pacchiano, My Phan, Yasin Abbasi-Yadkori, Anup Rao

We study bandit model selection in stochastic environments. Our approach relies on a meta-algorithm that selects between candidate base algorithms. We develop a meta-algorithm-base algorithm abstraction that can work with general classes of base algorithms and different type of adversarial meta-algorithms. Our methods rely on a novel and generic smoothing tr

Allen Liu, Renato Paes Leme, Jon Schneider

In the contextual pricing problem a seller repeatedly obtains products described by an adversarially chosen feature vector in $\mathbb{R}^d$ and only observes the purchasing decisions of a buyer with a fixed but unknown linear valuation over the products. The regret measures the difference between the revenue the seller could have obtained knowing the buyer

Alvise Bastianello, Jacopo De Nardis, Andrea De Luca

We consider the out-of-equilibrium dynamics of an interacting integrable system in the presence of an external dephasing noise. In the limit of large spatial correlation of the noise, we develop an exact description of the dynamics of the system based on a hydrodynamic formulation. This results in an additional term to the standard generalized hydrodynamics

C. R. Wie

Three unit spheres were used to represent the two-qubit pure states. The three spheres are named the base sphere, entanglement sphere, and fiber sphere. The base sphere and entanglement sphere represent the reduced density matrix of the base qubit and the non-local entanglement measure, concurrence, while the fiber sphere represents the fiber qubit via a sim

Sai Sidhardh, Sansit Patnaik, Fabio Semperlotti

This study presents a comprehensive framework for constitutive modeling of a frame-invariant fractional-order approach to nonlocal thermoelasticity in solids. For this purpose, thermodynamic and mechanical balance laws are derived for nonlocal solids modeled using the fractional-order continuum theory. This includes revisiting the Cauchy&#39;s hypothesis for

Sajjad Hussain Mirza, Rahul Singh, Peter Forck, Bernd Lorentz

Closed orbit feedback (COFB) systems used for the global orbit correction rely on the pseudo-inversion of the orbit response matrix (ORM). A mismatch between the model ORM used in the controller and the actual machine ORM can affect the performance of the feedback system. In this paper, the typical sources of such model mismatch such as acceleration ramp ORM

Francesco Croce, Matthias Hein

The field of defense strategies against adversarial attacks has significantly grown over the last years, but progress is hampered as the evaluation of adversarial defenses is often insufficient and thus gives a wrong impression of robustness. Many promising defenses could be broken later on, making it difficult to identify the state-of-the-art. Frequent pitf

Warren R. Morningstar, Sharad M. Vikram, Cusuh Ham, Andrew Gallagher

Automatic Differentiation Variational Inference (ADVI) is a useful tool for efficiently learning probabilistic models in machine learning. Generally approximate posteriors learned by ADVI are forced to be unimodal in order to facilitate use of the reparameterization trick. In this paper, we show how stratified sampling may be used to enable mixture distribut

Daniel Selsam, Simon Hudon, Leonardo de Moura

Functional programming languages are particularly well-suited for building automated reasoning systems, since (among other reasons) a logical term is well modeled by an inductive type, traversing a term can be implemented generically as a higher-order combinator, and backtracking is dramatically simplified by persistent datastructures. However, existing pure

Chak Hei Lo, Mikhail V. Menshikov, Andrew R. Wade

We give conditions under which near-critical stochastic processes on the half-line have infinitely many or finitely many cutpoints, generalizing existing results on nearest-neighbour random walks to adapted processes with bounded increments satisfying appropriate conditional increment moments conditions. We apply one of these results to deduce that a class o

Stefan Glock, Benny Sudakov

In 1994, Erdős, Gyárfás and Łuczak posed the following problem: given disjoint vertex sets $V_1,\dots,V_n$ of size~$k$, with exactly one edge between any pair $V_i,V_j$, how large can $n$ be such that there will always be an independent transversal? They showed that the maximal $n$ is at most $(1+o(1))k^2$, by providing an explicit construction with these pa

Yi Xiong, Phani Karamched, Chi-Toan Nguyen, David M Collins

There is a long standing technological problem in which a stress dwell during cyclic loading at room temperature in Ti causes a significant fatigue life reduction. It is thought that localised time dependent plasticity in soft grains oriented for easy plastic slip leads to load shedding and an increase in stress within a neighbouring hard grain poorly orient

Igor Shalyminov, Alessandro Sordoni, Adam Atkinson, Hannes Schulz

Domain adaptation has recently become a key problem in dialogue systems research. Deep learning, while being the preferred technique for modeling such systems, works best given massive training data. However, in the real-world scenario, such resources aren&#39;t available for every new domain, so the ability to train with a few dialogue examples can be consi

Quan Zhao, Wei Jiang, Weizhu Bao

We propose an energy-stable parametric finite element method (ES-PFEM) for simulating solid-state dewetting of thin films in two dimensions via a sharp-interface model, which is governed by surface diffusion and contact line (point) migration together with proper boundary conditions. By reformulating the relaxed contact angle condition into a Robin-type boun

Johann Cigler, Christian Krattenthaler

We prove evaluations of Hankel determinants of linear combinations of moments of orthogonal polynomials (or, equivalently, of generating functions for Motzkin paths), thus generalising known results for Catalan numbers.

Xingze Qiu, Jie Zou, Xiaodong Qi, Xiaopeng Li

We present an efficient approach to precisely simulate tight binding models with optical lattices, based on programmable digital-micromirror-device (DMD) techniques. Our approach consists of a subroutine of Wegner-flow enabled precise extraction of a tight-binding model for a given optical potential, and a reverse engineering step of adjusting the potential

David Reifert, Martins Kokainis, Andris Ambainis, Vyacheslavs Kashcheyevs

Mesoscopic integrated circuits achieving high-fidelity control of elementary quantum systems require new methodology for benchmarking. We offer circuit-level statistical description of rare-error accumulation in terms of a universal random-walk model for on-demand electron transfer. For a high-fidelity single-electron circuit, realized in the experiment as a

Daniel Kang, Deepti Raghavan, Peter Bailis, Matei Zaharia

ML models are increasingly deployed in settings with real world interactions such as vehicles, but unfortunately, these models can fail in systematic ways. To prevent errors, ML engineering teams monitor and continuously improve these models. We propose a new abstraction, model assertions, that adapts the classical use of program assertions as a way to monit

Qiuling Yang, Alireza Sadeghi, Gang Wang, Georgios B. Giannakis

Distributed renewable generation, elastic loads, and purposeful manipulation of meter readings challenge the monitoring and control of today&#39;s power systems (PS). In this context, to maintain a comprehensive view of the system in real time, fast and robust state estimation (SE) methods are urgently needed. Conventional PSSE solvers typically entail minim

Ion Necoara

In this paper we consider stochastic composite convex optimization problems with the objective function satisfying a stochastic bounded gradient condition, with or without a quadratic functional growth property. These models include the most well-known classes of objective functions analyzed in the literature: non-smooth Lipschitz functions and composition o