December 2020 arXiv papers — page 63

Sherman Lo, Peter Watson, Peter Dueben, Ritabrata Dutta

The accurate prediction of precipitation is important to allow for reliable warnings of flood or drought risk in a changing climate. However, to make trust-worthy predictions of precipitation, at a local scale, is one of the most difficult challenges for today's weather and climate models. This is because important features, such as individual clouds and hig

Chinonso Nwankwo, Weizhong Dai

In this research work, an explicit Runge-Kutta-Fehlberg (RKF) time integration with a fourth-order compact finite difference scheme in space and a high order analytical approximation of the optimal exercise boundary is employed for solving the regime-switching pricing model. In detail, we recast the free boundary problem into a system of nonlinear partial di

Daniel Reyes Nozaleda, Piergiulio Tempesta, Giorgio Tondo

We show that the theory of classical Hamiltonian systems admitting separating variables can be formulated in the context of ($\omega, \mathscr{H}$) structures. They are symplectic manifolds endowed with a compatible Haantjes algebra $\mathscr{H}$, namely an algebra of (1,1)-tensor fields with vanishing Haantjes torsion. A special class of coordinates, called

T. A. Isaev, A. V. Zaitsevskii, A. Oleynichenko, E. Eliav

Radium compounds have attracted recently considerable attention due to both development of experimental techniques for high-precision laser spectroscopy of molecules with short-lived nuclei and amenability of certain radium compounds for direct cooling with lasers. Currently, radium monofluoride (RaF) is one of the most studied molecules among the radium com

Gyula Magyarkuti

An elementary approach to Banach-Tarski paradox is presented. Very small amount of algebra and measure theory is required. -- A Hausdorff- \'es a Banach-Tarski paradoxon elemi megk\"ozel\'it\'ese.

Steven Platt

In recent years, network function virtualization and a software defined focus has allowed networks to become flexible and extensible in ways not possible previously. Although network modeling tools such as NS-2, NS-3, and OMNet++ have been extended with modules and code to support the absolute latest wireless protocols and medium access standards - there has

Frank Dellaert, Lin Yen-Chen

Besides the COVID-19 pandemic and political upheaval in the US, 2020 was also the year in which neural volume rendering exploded onto the scene, triggered by the impressive NeRF paper by Mildenhall et al. (2020). Both of us have tried to capture this excitement, Frank on a blog post (Dellaert, 2020) and Yen-Chen in a Github collection (Yen-Chen, 2020). This

Zeyuan Allen-Zhu, Yuanzhi Li

We formally study how ensemble of deep learning models can improve test accuracy, and how the superior performance of ensemble can be distilled into a single model using knowledge distillation. We consider the challenging case where the ensemble is simply an average of the outputs of a few independently trained neural networks with the SAME architecture, tra

Stavros Argyrios Papadakis, Vasiliki Petrotou

Assume D is a simplicial sphere, and k_1 is a field. We say that D is generically anisotropic over k_1 if, for a certain purely transcendental field extension k of k_1, a certain Artinian reduction A of the Stanley-Reisner ring k[D] has the following property: All nonzero homogeneous elements u of A of degree less or equal to (dim D +1)/2 have nonzero square

Petr A. Golovach, Daniël Paulusma, Erik Jan van Leeuwen

Paths $P_1,\ldots,P_k$ in a graph $G=(V,E)$ are mutually induced if any two distinct $P_i$ and $P_j$ have neither common vertices nor adjacent vertices (except perhaps their end-vertices). The Induced Disjoint Paths problem is to decide if a graph $G$ with $k$ pairs of specified vertices $(s_i,t_i)$ contains $k$ mutually induced paths $P_i$ such that each $P

Lu Meng, Bo Wang, Shi-Lin Zhu

In this work, we investigate the SU(3) flavor symmetry, heavy quark spin symmetry and their breaking effects in the di-meson systems. We prove the existence of the $[\bar{D}_{s}^{*}D_{s}^{*}]^{0^{++}}$, $[\bar{D}_{s}^{*}D_{s}/\bar{D}_{s}^{}D_{s}^*]^{1^{+-}}$, and $[\bar{D}_{s}^{*}D_{s}^{*}]^{1^{+-}}$ bound states as the consequence of two prerequisites in th

Dhruv Shah, Benjamin Eysenbach, Gregory Kahn, Nicholas Rhinehart

We propose a learning-based navigation system for reaching visually indicated goals and demonstrate this system on a real mobile robot platform. Learning provides an appealing alternative to conventional methods for robotic navigation: instead of reasoning about environments in terms of geometry and maps, learning can enable a robot to learn about navigation

Qiang Zhang, Tete Xiao, Alexei A. Efros, Lerrel Pinto

At the heart of many robotics problems is the challenge of learning correspondences across domains. For instance, imitation learning requires obtaining correspondence between humans and robots; sim-to-real requires correspondence between physics simulators and the real world; transfer learning requires correspondences between different robotics environments.

Alexander Watson

The computational cost of video game graphics is increasing and hardware for processing graphics is struggling to keep up. This means that computer scientists need to develop creative new ways to improve the performance of graphical processing hardware. Deep learning techniques for video super-resolution can enable video games to have high quality graphics w

Vladimir Calvera, Chong Wang

Triangular lattice quantum antiferromagnet has recently emerged to be a promising playground for realizing Dirac spin liquids (DSLs) -- a class of highly entangled quantum phases hosting emergent gauge fields and gapless Dirac fermions. While previous theories and experiments focused mainly on $S=1/2$ spin systems, more recently signals of a DSL were detecte

Akshay Shetty, Derek Knowles, Grace Xingxin Gao

Inter-robot communication enables multi-robot systems to coordinate and execute complex missions efficiently. Thus, maintaining connectivity of the communication network between robots is essential for many multi-robot systems. In this paper, we present a trajectory planner for connectivity maintenance of a multi-robot system. We first define a weighted undi

Federico Bianchi, Bingqing Yu, Jacopo Tagliabue

Word embeddings (e.g., word2vec) have been applied successfully to eCommerce products through~\textit{prod2vec}. Inspired by the recent performance improvements on several NLP tasks brought by contextualized embeddings, we propose to transfer BERT-like architectures to eCommerce: our model -- ~\textit{Prod2BERT} -- is trained to generate representations of p

L. Fabbietti, V. Mantovani Sarti, O. Vazquez Doce

The strong interaction among hadrons has been measured in the past by scattering experiments. Although this technique has been extremely successful in providing information about the nucleon-nucleon and pion-nucleon interactions, when unstable hadrons are considered the experiments become more challenging. In the last few years, the analysis of correlations

Mohammad Reza Besharati, Mohammad Izadi

Smart Cities, with their problems and challenges, is an emerging smart paradigm. To achieve better quality and usability levels, we need engineering solutions to support smart cities' soft-layer development. Statics, dynamics and generative semantics are involved, but segregating Coordination Protocols from the other semantics could act as a complexity manag

Eugene Serebryany, Sourav Chowdhury, Nicki E. Watson, Arthur McClelland

Cataract is one of the most prevalent protein aggregation disorders and still the biggest cause of vision loss worldwide. The human lens, in its core region, lacks turnover of any cells or cellular components; it has therefore evolved remarkable mechanisms for resisting protein aggregation for a lifetime. We now report that one such mechanism relies on an un

Celina M. H. de Figueiredo, Alexsander A. de Melo, Fabiano S. Oliveira, Ana Silva

The computational complexity of the MaxCut problem restricted to interval graphs has been open since the 80's, being one of the problems proposed by Johnson on his Ongoing Guide to NP-completeness, and has been settled as NP-complete only recently by Adhikary, Bose, Mukherjee and Roy. On the other hand, many flawed proofs of polynomiality for MaxCut on the m

Ahmad K. Omar, Katherine Klymko, Trevor GrandPre, Phillip L. Geissler

Motility-induced phase separation (MIPS), the phenomenon in which purely repulsive active particles undergo a liquid-gas phase separation, is among the simplest and most widely studied examples of a nonequilibrium phase transition. Here, we show that states of MIPS coexistence are in fact only metastable for three-dimensional active Brownian particles over a

Jeremias Aguilera-Damia, Louise M. Anderson, Evan Coleman

A solvable current-current deformation of the worldsheet theory of strings on $AdS_3$ has been recently conjectured to be dual to an irrelevant deformation of the spacetime orbifold CFT, commonly referred to as single-trace $T\bar{T}$. These deformations give rise to a family of bulk geometries which realize a non-trivial flow towards the UV. For a particula

Amin Barzegar, Anuj Kankani, Salvatore Mandrà, Helmut G. Katzgraber

Optimization plays a significant role in many areas of science and technology. Most of the industrial optimization problems have inordinately complex structures that render finding their global minima a daunting task. Therefore, designing heuristics that can efficiently solve such problems is of utmost importance. In this paper we benchmark and improve the t

Emely Wiegand, Ping-Yi Wen, Per Delsing, Io-Chun Hoi

We investigate three types of amplification processes for light fields coupling to an atom near the end of a one-dimensional semi-infinite waveguide. We consider two setups where a drive creates population inversion in the bare or dressed basis of a three-level atom and one setup where the amplification is due to higher-order processes in a driven two-level

A. Hallenbert, G. G. Plunk

The tertiary instability is believed to be important for governing magnetised plasma turbulence under conditions of strong zonal flow generation, near marginal stability. In this work, we investigate its role for a collisionless strongly driven fluid model, self-consistently derived as a limit of gyrokinetics. It is found that a region of absolute stability

Paul Manneville, Masaki Shimizu

In line with Pomeau's conjecture about the relevance of directed percolation (DP) to turbulence onset/decay in wall-bounded flows, we propose a minimal stochastic model dedicated to the interpretation of the spatially intermittent regimes observed in channel flow before its return to laminar flow. Numerical simulations show that a regime with bands obliquely

Eliab D. Malefahlo, Matt J. Jarvis, Mario G. Santos, Sarah V. White

We present the 1.4GHz radio luminosity functions (RLFs) of galaxies in the COSMOS field, measured above and below the $5\sigma$ detection threshold, using a Bayesian model-fitting technique. The radio flux-densities from VLA-COSMOS 3-GHz data, are extracted at the position of stellar mass-limited near-infrared (NIR) galaxies. We fit a local RLF model, which

Frank Lechermann

The novel nickelate superconductors of infinite-layer type feature challenging electronic pecularities in the normal-state phase diagram with doping. Distinct many-body behavior and different dispersion regimes of the entangled $\{$Ni-$d_{z^2}$, Ni-$d_{x^2-y^2}$$\}$ orbital sector give rise to highly rich physics, which is here studied for the case of the Nd

Martin Guay, Mouhacine Benosman

This paper proposes a finite-time Newton seeking control design for systems described by unknown multivariable static maps. The Newton seeking system has an averaged system that implements a Newton continuous-time algorithm. The averaged Newton seeking system is shown to achieve finite-time stability of the unknown optimum of the static map. An averaging ana

M. Malliaris, S. Shelah

This is a short expository account of the regularity lemma for stable graphs proved by the authors, with some comments on the model theoretic context, written for a general logical audience.

Xinpeng Wang, Chandan Yeshwanth, Matthias Nießner

We address the task of indoor scene generation by generating a sequence of objects, along with their locations and orientations conditioned on a room layout. Large-scale indoor scene datasets allow us to extract patterns from user-designed indoor scenes, and generate new scenes based on these patterns. Existing methods rely on the 2D or 3D appearance of thes

Juan Souto, Thi Hanh Vo

Given two closed curves in a surface, we propose an algorithm to detect whether they are of the same type or not.

Matthew Proctor, María Blanco de Paz, Dario Bercioux, Aitzol García-Etxarri

We study the topological properties of a kagome plasmonic metasurface, modelled with a coupled dipole method which naturally includes retarded long range interactions. We demonstrate the system supports an obstructed atomic limit phase through the calculation of Wilson loops. Then we characterise the hierarchy of topological boundary modes hosted by the subw

Yilun Du, Yinan Zhang, Hong-Xing Yu, Joshua B. Tenenbaum

We present a method, Neural Radiance Flow (NeRFlow),to learn a 4D spatial-temporal representation of a dynamic scene from a set of RGB images. Key to our approach is the use of a neural implicit representation that learns to capture the 3D occupancy, radiance, and dynamics of the scene. By enforcing consistency across different modalities, our representation

Amparo Gil, Javier Segura, Nico M. Temme

Some special functions are particularly relevant in applied probability and statistics. For example, the incomplete beta function is the cumulative central beta distribution. In this paper, we consider the inversion of the central Student's-$t$ distribution which is a particular case of the central beta distribution. The inversion of this distribution functi

Andrew P. Furmanski, Christopher Hilgenberg

Modern neutrino detectors, particularly the large liquid argon time projection chambers (LAr TPCs) at SBN and DUNE, provide an unprecedented amount of information about GeV-scale interactions. By taking advantage of the excellent spatial and calorimetric resolution as well as the low tracking thresholds provided by LAr TPCs, we present a novel method of esti

Albert Garreta, Alexei Miasnikov, Denis Ovchinnikov

We study systems of polynomial equations in infinite finitely generated commutative associative rings with an identity element. For each such ring $R$ we obtain an interpretation by systems of equations of a ring of integers $O$ of a finite field extension of either $\mathbb{Q}$ or $\mathbb{F}_p(t)$, for some prime $p$ and variable $t$. This implies that the

Tatsuya Kaneko, Zhiyuan Sun, Yuta Murakami, Denis Golež

We investigate the bulk photovoltaic effect, which rectifies light into electric current, in a collective quantum state with correlation driven electronic ferroelectricity. We show via explicit real-time dynamical calculations that the effect of the applied electric field on the electronic order parameter leads to a strong enhancement of the bulk photovoltai

Joachim Sicking, Maximilian Pintz, Maram Akila, Tim Wirtz

We propose DenseHMM - a modification of Hidden Markov Models (HMMs) that allows to learn dense representations of both the hidden states and the observables. Compared to the standard HMM, transition probabilities are not atomic but composed of these representations via kernelization. Our approach enables constraint-free and gradient-based optimization. We pr

R. Anusha, Blesson Mathew, B. Shridharan, R. Arun

We report the first systematic study to identify and characterize a sample of classical Ae stars in the Galaxy. The spectra of these stars were retrieved from the A-star catalog using the Large sky Area Multi-Object fiber Spectroscopic Telescope (LAMOST) survey. We identified the emission-line stars in this catalog from which 159 are confirmed as classical A

Christian Maes, Kasper Meerts, Ward Struyve

We consider non-relativistic point-particles coupled to Einstein gravity and their canonical quantization. From the resulting Wheeler-DeWitt wave equation we determine a quantum version of geometrodynamics, where the coupled evolution of particle positions and 3-metric is guided by the wave function. We find that this quantum dynamics implies a quantum exten

Jingbo Zhou, Shuangli Li, Liang Huang, Haoyi Xiong

Accurately predicting the binding affinity between drugs and proteins is an essential step for computational drug discovery. Since graph neural networks (GNNs) have demonstrated remarkable success in various graph-related tasks, GNNs have been considered as a promising tool to improve the binding affinity prediction in recent years. However, most of the exis

Jan-David Hardtke

We give a proof of the well-known fact that the category of nearness spaces is bireflective in the category of merotopic spaces which uses Zorn's Lemma instead of the usual construction by transfinite induction.

Inês Aniceto, Daniel Hasenbichler, Christopher J. Howls, Christopher J. Lustri

Transseries expansions build upon ordinary power series methods by including additional basis elements such as exponentials and logarithms. Alternative summation methods can then be used to "resum" series to obtain more efficient approximations, and have been successfully widely applied in the study of continuous linear and nonlinear, single and multidimensi

Marco De Angelis, Marco Behrendt, Liam Comerford, Yuanjin Zhang

We present an algorithm for the forward propagation of intervals through the discrete Fourier transform. The algorithm yields best-possible bounds when computing the amplitude of the Fourier transform for real and complex valued sequences. We show that computing the exact bounds of the amplitude can be achieved with an exhaustive examination of all possible

Philipp Stürmer, Mikael Nilsson Tengstrand, Rashi Sachdeva, Stephanie M. Reimann

In this work, we present the study of the stationary structures and the breathing mode behavior of a two-dimensional self-bound binary Bose droplet. We employ an analytical approach using a variational ansatz with a super-Gaussian trial order parameter and compare it with the numerical solutions of the extended Gross-Pitaevskii equation. We find that the sup

Tobias Barker, Christophe Prange

In this short paper we prove the global regularity of solutions to the Navier-Stokes equations under the assumption that slightly supercritical quantities are bounded. As a consequence, we prove that if a solution $u$ to the Navier-Stokes equations blows-up, then certain slightly supercritical Orlicz norms must become unbounded. This partially answers a conj

Fabian Bach

The paper aims to give an overview of various approaches to statistical disclosure control based on random noise that are currently being discussed for official population statistics and censuses. A particular focus is on a stringent delineation between different concepts influencing the discussion: we separate clearly between risk measures, noise distributi

Debam Biswas, Zhelun Chen

In the paper "Uniformity of Mordell-Lang" by Vesselin Dimitrov, Philipp Habegger and Ziyang Gao (arXiv:2001.10276), they use Silverman-Tate's Height Inequality and they give a proof of the same which makes use of Cartier divisors and hence drops the flatness assumption of structure morphisms of compactified abelian schemes. However, their proof makes use of

Sergio Benvenuti, Ivan Garozzo, Gabriele Lo Monaco

We consider $3d$ $\mathcal{N}\!=\!2$ gauge theories with fundamental matter plus a single field in a rank-$2$ representation. Using iteratively a process of "deconfinement" of the rank-$2$ field, we produce a sequence of Seiberg-dual quiver theories. We detail this process in two examples with zero superpotential: $Usp(2N)$ gauge theory with an antisymmetric

Zi-Yao Zhang, Odysseas Pappas, Alin Achim

In this paper, an optimization model using Cauchy regularization is proposed for simultaneous SAR image reconstruction and autofocusing. A coordinate descent framework in which the desired image and the phase errors are optimized alternatively is designed to solve the model. For the subproblem of estimating the image, we utilize the techniques of Wirtinger c

Vladislav Belyaev, Aleksandra Malysheva, Aleksei Shpilman

The task object tracking is vital in numerous applications such as autonomous driving, intelligent surveillance, robotics, etc. This task entails the assigning of a bounding box to an object in a video stream, given only the bounding box for that object on the first frame. In 2015, a new type of video object tracking (VOT) dataset was created that introduced

Barnaby Martin, Daniël Paulusma, Siani Smith

A graph class is hereditary if it is closed under vertex deletion. We give examples of NP-hard, PSPACE-complete and NEXPTIME-complete problems that become constant-time solvable for every hereditary graph class that is not equal to the class of all graphs.

Sibasish Banerjee, Pietro Longhi, Mauricio Romo

We study BPS states of 5d $\mathcal{N}=1$ $SU(2)$ Yang-Mills theory on $S^1\times \mathbb{R}^4$. Geometric engineering relates these to enumerative invariants for the local Hirzebruch surface $\mathbb{F}_0$. We illustrate computations of Vafa-Witten invariants via exponential networks, verifying fiber-base symmetry of the spectrum at certain points in moduli

T. Mitchell Roddenberry, Santiago Segarra, Anastasios Kyrillidis

We study the role of the constraint set in determining the solution to low-rank, positive semidefinite (PSD) matrix sensing problems. The setting we consider involves rank-one sensing matrices: In particular, given a set of rank-one projections of an approximately low-rank PSD matrix, we characterize the radius of the set of PSD matrices that satisfy the mea

Onirban Islam, Alexander Strohmaier

This article gives global microlocalisation constructions for normally hyperbolic operators on a vector bundle over a globally hyperbolic spacetime in geometric terms. As an application, this is used to generalise the Duistermaat-H\"{o}rmander construction of Feynman propagators, therefore incorporating the most important non-scalar geometric operators. It i

Sofian Chaybouti, Achraf Saghe, Aymen Shabou

This paper introduces MIX, a multi-task deep learning approach to solve open-ended question-answering. First, we design our system as a multi-stage pipeline of 3 building blocks: a BM25-based Retriever to reduce the search space, a RoBERTa-based Scorer, and an Extractor to rank retrieved paragraphs and extract relevant text spans, respectively. Eventually, w

François Sicard, Alberto Striolo

Antiagglomerants (AAs) are surface active molecules widely used in the rubber and petroleum industry, among others. In the petroleum industry, it is believed that AAs strongly adsorb to the surface of hydrate particles to prevent the growth of clathrate hydrate within oil pipelines. Small changes in their molecular structures can strongly affect the thermody

Luca A. Thiede, Mario Krenn, AkshatKumar Nigam, Alan Aspuru-Guzik

Computer-aided design of molecules has the potential to disrupt the field of drug and material discovery. Machine learning, and deep learning, in particular, have been topics where the field has been developing at a rapid pace. Reinforcement learning is a particularly promising approach since it allows for molecular design without prior knowledge. However, t

Maxim Jeffs

We consider a definition of the Fukaya category of a singular hypersurface proposed by Auroux, given by localizing the Fukaya category of a nearby fiber at Seidel's natural transformation, and show that this possesses several desirable properties. Firstly, we prove an A-side analog of Orlov's derived Kn\"orrer periodicity theorem by showing that Auroux's cat

Fabien Péan, Philippe Favre, Orcun Goksel

Reverse Shoulder Arthroplasty (RSA) has become a very common procedure for shoulder joint replacement, even for scenarios where an anatomical reconstruction would traditionally be used. In this study, we investigate joint reaction forces and scapular kinematics for rotator cuff tears of different tendons with and without a reverse prosthesis. Available motio

Aleksandra Malysheva, Daniel Kudenko, Aleksei Shpilman

Over recent years, deep reinforcement learning has shown strong successes in complex single-agent tasks, and more recently this approach has also been applied to multi-agent domains. In this paper, we propose a novel approach, called MAGNet, to multi-agent reinforcement learning that utilizes a relevance graph representation of the environment obtained by a

Vincent Drach, Tadeusz Janowski, Claudio Pica, Sasa Prelovsek

We calculate the coupling between a vector resonance and two Goldstone bosons in $SU(2)$ gauge theory with $N_f=2$ Dirac fermions in the fundamental representation. The considered theory can be used to construct a minimal Composite Higgs models. The coupling is related to the width of the vector resonance and we determine it by simulating the scattering of t

Kevin Lin, Lijuan Wang, Zicheng Liu

We present a new method, called MEsh TRansfOrmer (METRO), to reconstruct 3D human pose and mesh vertices from a single image. Our method uses a transformer encoder to jointly model vertex-vertex and vertex-joint interactions, and outputs 3D joint coordinates and mesh vertices simultaneously. Compared to existing techniques that regress pose and shape paramet

Gabriel Istrate

We investigate Kantian equilibria in finite normal form games, a class of non-Nashian, morally motivated courses of action that was recently proposed in the economics literature. We highlight a number of problems with such equilibria, including computational intractability, a high price of miscoordination, and expensive/problematic extension to general norma

Tathagata Ghosh, Huai-Ke Guo, Tao Han, Hongkai Liu

We consider a non-Abelian dark SU(2)$_{\rm D}$ model where the dark sector couples to the Standard Model (SM) through a Higgs portal. We investigate two different scenarios of the dark sector scalars with $Z_2$ symmetry, with Higgs portal interactions that can introduce mixing between the SM Higgs boson and the SM singlet scalars in the dark sector. We utili

Hyojoong Kim, Nakwoo Kim

We revisit non-rotating, dyonically charged, and supersymmetric AdS$_4$ black holes, which are solutions of $\mathcal{N}=2$ gauged supergravity with vector- and hyper-multplets. Uplifting the near horizon solutions to $D=11$ supergravity on seven-dimensional Sasaki-Einstein manifolds, we show that dyonic AdS$_4$ black holes correspond to AdS$_2$ solutions wi

Yucheng Wang, Xu Xia, Yongjian Wang, Zuohuan Zheng

A mobility edge (ME) in energy separating extended from localized states is a central concept in understanding various fundamental phenomena like the metal-insulator transition in disordered systems. In one-dimensional quasiperiodic systems, there exist a few models with exact MEs, and these models are beneficial to provide exact understanding of ME physics.

Satish K. Panda, Haris Cheong, Tin A. Tun, Sripad K. Devella

The optic nerve head (ONH) typically experiences complex neural- and connective-tissue structural changes with the development and progression of glaucoma, and monitoring these changes could be critical for improved diagnosis and prognosis in the glaucoma clinic. The gold-standard technique to assess structural changes of the ONH clinically is optical cohere

Robert Young

Minimal surfaces in $\mathbb{R}^n$ can be locally approximated by graphs of harmonic functions, i.e., functions that are critical points of the Dirichlet energy, but no analogous theorem is known for $H$-minimal surfaces in the three-dimensional Heisenberg group $\mathbb{H}$, which are known to have singularities. In this paper, we introduce a definition of

N. Mohammedi

Lie algebra valued equations translating the integrability of a general two-dimensional Wess-Zumino-Witten model are given. We found simple solutions to these equations and identified three types of new integrable non-linear sigma models. One of them is a modified Yang-Baxter sigma model supplemented with a Wess-Zumino-Witten term.

Nikolai Tsvetkov, Byeong Cheul Moon, Jeung Ku Kang, Muhammad Ejaz Khan

Halide perovskite light absorbers have great advantages for photovoltaics such as efficient solar energy absorption, but charge accumulation and recombination at the interface with an electron transport layer (ETL) remains a major challenge in realizing their full potential. Here we report the experimental realization of a zipper-like interdigitated interfac

Victor V. Flambaum, Liangliang Su, Lei Wu, Bin Zhu

Due to the low nuclear recoils, sub-GeV dark matter (DM) is usually beyond the sensitivity of the conventional DM direct detection experiments. The boosted and Migdal scattering mechanisms have been proposed as two new complementary avenues to search for light DM. In this work, we consider the momentum-transfer effect in the DM-nucleus scattering to derive t

T. Leitner, A. Born, I. Bidermane, R. Ovsyannikov

In this work, we present the CoESCA station for electron-electron coincidence spectroscopy from surfaces, built in a close collaboration between Uppsala University and Helmholtz-Zentrum Berlin at the BESSY II synchrotron facility in Berlin, Germany. We start with a detailed overview of previous work in the field of electron-electron coincidences, before we d

David Brewster, Reuven Hodges, Alexander Yong

We define and study proper permutations. Properness is a geometrically natural necessary criterion for a Schubert variety to be Levi-spherical. We prove the probability that a random permutation is proper goes to zero in the limit.

M. Reza Parsa, Changho Kim, Alexander J. Wagner

At first glance the definition of mass and momentum appears to be uniquely defined. We show here, however, that this certainty can be misleading for many coarse grained systems. We show that particularly the fluctuating properties of common definitions of momentum in coarse grained methods like lattice gas and lattice Boltzmann do not agree with a fundamenta

Yi Hu, Patrick Charbonneau

The phase diagram of the two-dimensional ANNNI model has long been theoretically debated. Extremely long structural correlations and relaxation times further result in numerical simulations making contradictory predictions. Here, we introduce a numerical transfer matrix treatment that bypasses these problems, and thus overcome various ambiguities in the phas

Sudipta Bhattacharya

In this paper, a novel non-parametric method for estimation of expectation and maximum value of the variance function is proposed for recurrent events where intensity of event occurrence changes with the occurrence of each higher order event. These kinds of recurrent events are often observed in clinical trials for cardio-vascular events and also in many soc

Pavel Galashin, Thomas Lam

We relate the mixed Hodge structure on the cohomology of open positroid varieties (in particular, their Betti numbers over $\mathbb{C}$ and point counts over $\mathbb{F}_q$) to Khovanov--Rozansky homology of associated links. We deduce that the mixed Hodge polynomials of top-dimensional open positroid varieties are given by rational $q,t$-Catalan numbers. Vi

Juliana García-Mejía, David Charbonneau, Daniel Fabricant, Jonathan M. Irwin

We report on the status of the Tierras Observatory, a refurbished 1.3-m ultra-precise fully-automated photometer located at the F. L. Whipple Observatory atop Mt. Hopkins, Arizona. Tierras is designed to limit systematic errors, notably precipitable water vapor (PWV), to 250 ppm, enabling the characterization of terrestrial planet transits orbiting $< 0.3 \,

Hojjat Rakhshani, Lhassane Idoumghar, Soheila Ghambari, Julien Lepagnot

Deep neural networks have recently drawn considerable attention to build and evaluate artificial learning models for perceptual tasks. Here, we present a study on the performance of the deep learning models to deal with global optimization problems. The proposed approach adopts the idea of the neural architecture search (NAS) to generate efficient neural net

Oliver Sheridan-Methven, Michael Giles

For numerical approximations to stochastic differential equations using the Euler-Maruyama scheme, we propose incorporating approximate random variables computed using low precisions, such as single and half precision. We propose and justify a model for the rounding error incurred, and produce an average case error bound for two and four way differences, app

Ewout van den Berg, Zlatko K. Minev, Kristan Temme

Measurements on current quantum processors are subject to hardware imperfections that lead to readout errors. These errors manifest themselves as a bias in quantum expectation values. Here, we propose a very simple method that forces the bias in the expectation value to appear as a multiplicative factor that can be measured directly and removed at the cost o

Simon Hirlaender, Niky Bruchon

Reinforcement learning holds tremendous promise in accelerator controls. The primary goal of this paper is to show how this approach can be utilised on an operational level on accelerator physics problems. Despite the success of model-free reinforcement learning in several domains, sample-efficiency still is a bottle-neck, which might be encompassed by model

Philippe Grangier

It is known that "quantum non locality", leading to the violation of Bell's inequality and more generally of classical local realism, can be attributed to the conjunction of two properties, that we call here elementary locality and predictive completeness. Taking this point of view, we show again that quantum mechanics violates predictive completeness, allow

Anwita Bhowmik, Rupam Barman

Let $q$ be a prime power such that $q\equiv 1\pmod{4}$. The Paley graph of order $q$ is the graph with vertex set as the finite field $\mathbb{F}_q$ and edges defined as, $ab$ is an edge if and only if $a-b$ is a non-zero square in $\mathbb{F}_q$. We attempt to construct a similar graph of order $n$, where $n\in\mathbb{N}$. For suitable $n$, we construct the

Jonathan Jaquette, Jean-Philippe Lessard, Akitoshi Takayasu

In this paper, we study the global dynamics of a class of nonlinear Schr\"odinger equations using perturbative and non-perturbative methods. We prove the semi-global existence of solutions for initial conditions close to constant. That is, solutions will exist for all positive time or all negative time. The existence of an open set of initial data which limi

Benjamin Crinquand, Benoît Cerutti, Guillaume Dubus, Kyle Parfrey

Context: The origin of ultra-rapid flares of very high-energy radiation from active galactic nuclei remains elusive. Magnetospheric processes, occurring in the close vicinity of the central black hole, could account for these flares. Aims: We aim to bridge the gap between simulations and observations by synthesizing gamma-ray lightcurves in order to characte

Max Hird, Samuel Livingstone, Giacomo Zanella

We study a recently introduced gradient-based Markov chain Monte Carlo method based on 'Barker dynamics'. We provide a full derivation of the method from first principles, placing it within a wider class of continuous-time Markov jump processes. We then evaluate the Barker approach numerically on a challenging ill-conditioned logistic regression example with

Erhan Bayraktar, Suman Chakraborty, Xin Zhang

We determine the size of $k$-core in a large class of dense graph sequences. Let $G_n$ be a sequence of undirected, $n$-vertex graphs with edge weights $\{a^n_{i,j}\}_{i,j \in [n]}$ that converges to a kernel $W:[0,1]^2\to [0,+\infty)$ in the cut metric. Keeping an edge $(i,j)$ of $G_n$ with probability $\min \{ {a^n_{i,j}}/{n},1 \}$ independently, we obtain

Oumaima Bencheikh, Benjamin Jourdain

We are interested in the approximation in Wasserstein distance with index $\rho\ge 1$ of a probability measure $\mu$ on the real line with finite moment of order $\rho$ by the empirical measure of $N$ deterministic points. The minimal error converges to $0$ as $N\to+\infty$ and we try to characterize the order associated with this convergence. In \cite{xuber

Quentin Bonnefoy, Peter Cox, Emilian Dudas, Tony Gherghetta

We consider a 5D extension of the DFSZ axion model that addresses both the axion quality and fermion mass hierarchy problems, and predicts flavour-dependent, off-diagonal axion-fermion couplings. The axion is part of a 5D complex scalar field charged under a U(1)$_{PQ}$ symmetry that is spontaneously broken in the bulk, and is insensitive to explicit PQ brea

Cong Han, Yi Luo, Chenda Li, Tianyan Zhou

Leveraging additional speaker information to facilitate speech separation has received increasing attention in recent years. Recent research includes extracting target speech by using the target speaker's voice snippet and jointly separating all participating speakers by using a pool of additional speaker signals, which is known as speech separation using sp

Andrei Cozma, Christoph Reisinger

In this short paper, we study the simulation of a large system of stochastic processes subject to a common driving noise and fast mean-reverting stochastic volatilities. This model may be used to describe the firm values of a large pool of financial entities. We then seek an efficient estimator for the probability of a default, indicated by a firm value belo

Jan Weinreich, Nicholas J. Browning, O. Anatole von Lilienfeld

Free energies govern the behavior of soft and liquid matter, and improving their predictions could have a large impact on the development of drugs, electrolytes or homogeneous catalysts. Unfortunately, it is challenging to devise an accurate description of effects governing solvation such as hydrogen-bonding, van der Waals interactions, or conformational sam

Ilias Diakonikolas, Daniel M. Kane

We study the problem of PAC learning halfspaces with Massart noise. Given labeled samples $(x, y)$ from a distribution $D$ on $\mathbb{R}^{d} \times \{ \pm 1\}$ such that the marginal $D_x$ on the examples is arbitrary and the label $y$ of example $x$ is generated from the target halfspace corrupted by a Massart adversary with flipping probability $\eta(x) \

Michael Kagan

Image-based jet analysis is built upon the jet image representation of jets that enables a direct connection between high energy physics and the fields of computer vision and deep learning. Through this connection, a wide array of new jet analysis techniques have emerged. In this text, we survey jet image based classification models, built primarily on the u

Sebastian Bergmann, Sascha Kissel, Christof Kuelske

We consider the soft-core Widom-Rowlinson model for particles with spins and holes, on a Cayley tree of order $d$ (which has $d + 1$ nearest neighbours), depending on repulsion strength $\beta$ between particles of different signs and on an activity parameter $\lambda$ for particles. We analyse Gibbsian properties of the time-evolved intermediate Gibbs measu

Daniel Bruegmann

Geometric vertex algebras are a simplified version of Huang's geometric vertex operator algebras. We give a self-contained account of the equivalence of geometric vertex algebras with Z-graded vertex algebras.