March 2020 arXiv papers — page 102

Haoyuan Sun, David Grimsman, Jason R Marden

The submodular maximization problem is widely applicable in many engineering problems where objectives exhibit diminishing returns. While this problem is known to be NP-hard for certain subclasses of objective functions, there is a greedy algorithm which guarantees approximation at least 1/2 of the optimal solution. This greedy algorithm can be implemented w

Anh Dung Le, Alfred H. Mueller, Stéphane Munier

We implement a discretization of the one-dimensional branching Brownian motion in the form of a Monte Carlo event generator, designed to efficiently produce ensembles of realizations in which the rightmost lead particle at the final time $T$ is constrained to have a position $X$ larger than some predefined value $X_{\text{min}}$. The latter may be chosen arb

Matteo Brunelli, Daniel Malz, Albert Schliesser, Andreas Nunnenkamp

We consider an optomechanical cavity that is driven stroboscopically by a train of short pulses. By suitably choosing the inter-pulse spacing we show that ground-state cooling and mechanical squeezing can be achieved, even in the presence of mechanical dissipation and for moderate radiation-pressure interaction. We provide a full quantum-mechanical treatment

Chaoyue Niu, Danesh Tarapore, Klaus-Peter Zauner

Rapid progress in embedded computing hardware increasingly enables on-board image processing on small robots. This development opens the path to replacing costly sensors with sophisticated computer vision techniques. A case in point is the prediction of scene depth information from a monocular camera for autonomous navigation. Motivated by the aim to develop

Rahul Sharma, Krishna Somandepalli, Shrikanth Narayanan

An objective understanding of media depictions, such as inclusive portrayals of how much someone is heard and seen on screen such as in film and television, requires the machines to discern automatically who, when, how, and where someone is talking, and not. Speaker activity can be automatically discerned from the rich multimodal information present in the m

Narayanan Rengaswamy, Kaushik P. Seshadreesan, Saikat Guha, Henry D. Pfister

For space-based laser communications, when the mean photon number per received optical pulse is much smaller than one, there is a large gap between communications capacity achievable with a receiver that performs individual pulse-by-pulse detection, and the quantum-optimal "joint-detection receiver" that acts collectively on long codeword-blocks of m

Matteo Giordano, Kornel Kapas, Sandor D. Katz, Daniel Nogradi

The phase diagram and the location of the critical endpoint (CEP) of lattice QCD with unimproved staggered fermions on a $N_t=4$ lattice was determined fifteen years ago with the multiparameter reweighting method by studying Fisher zeros. We first reproduce the old result with an exact algorithm (not known at the time) and with statistics larger by an order

Erika Penzo, Anna Loiudice, Edward S. Barnard, Nicholas J. Borys

Förster Resonant Energy Transfer (FRET)-mediated exciton diffusion through artificial nanoscale building block assemblies could be used as a new optoelectronic design element to transport energy. However, so far nanocrystal (NC) systems supported only diffusion length of 30 nm, which are too small to be useful in devices. Here, we demonstrate a FRET-mediated

Nabil Iqbal, John McGreevy

It has long been expected that the 3d Ising model can be thought of as a string theory, where one interprets the domain walls that separate up spins from down spins as two-dimensional string worldsheets. The usual Ising Hamiltonian measures the area of these domain walls. This theory has string coupling of unit magnitude. We add new local terms to the Ising

Matthias Y. He, Eric B. Ford, Darin Ragozzine

The Kepler mission observed thousands of transiting exoplanet candidates around hundreds of thousands of FGK dwarf stars. He, Ford, & Ragozzine (2019) (arXiv:1907.07773) applied forward modeling to infer the distribution of intrinsic architectures of planetary systems, developed a clustered Poisson point process model for exoplanetary systems (SysSim) to rep

V. A. Masoura, I. Georgantopoulos, G. Mountrichas, C. Vignali

The combination of optical and mid-infrared (MIR) photometry has been extensively used to select red active galactic nuclei (AGNs). Our aim is to explore the obscuration properties of these red AGNs with both X-ray spectroscopy and spectral energy distributions (SEDs). In this study, we re-visit the relation between optical/MIR extinction and X-ray absorptio

Amira M. Eltony, Peng Shao, Seok-Hyun Yun

Load-bearing tissues are typically fortified by networks of protein fibers, often with preferential orientations. This fiber structure imparts the tissues with direction-dependent mechanical properties optimized to support specific external loads. To accurately model and predict tissues' mechanical response, it is essential to characterize the anisotropy on

Denis R. Candido, Gregory D. Fuchs, Ezekiel Johnston-Halperin, Michael E. Flatté

We propose an approach to realize a hybrid quantum system composed of a diamond nitrogen-vacancy (NV) center spin coupled to a magnon mode of the low-damping, low-moment organic ferrimagnet vanadium tetracyanoethylene. We derive an analytical expression for the spin-magnon cooperativity as a function of NV position under a micron-scale perpendicularly magnet

Zhishuai Guo, Yan Yan, Tianbao Yang

Stochastic gradient descent (SGD) has been widely studied in the literature from different angles, and is commonly employed for solving many big data machine learning problems. However, the averaging technique, which combines all iterative solutions into a single solution, is still under-explored. While some increasingly weighted averaging schemes have been

Alejandra M. P. Mendez, Claudia C. Montanari, Jorge E. Miraglia

We investigate scaling rules for the ionization cross sections of multicharged ions on molecules of biological interest. The cross sections are obtained using a methodology presented in [Mendez et al. J. Phys B (2020)], which considers distorted-wave calculations for atomic targets combined with a molecular stoichiometric model. We examine ions with nuclear

Songnian Chen, Shakeeb Khan, Xun Tang

We study the identification and estimation of treatment effect parameters in weakly separable models. In their seminal work, Vytlacil and Yildiz (2007) showed how to identify and estimate the average treatment effect of a dummy endogenous variable when the outcome is weakly separable in a single index. Their identification result builds on a monotonicity con

Lakshya Bhardwaj, Gabi Zafrir

We classify 5d N=1 gauge theories carrying a simple gauge group that can arise by mass-deforming 5d SCFTs and 6d SCFTs (compactified on a circle, possibly with a twist). For theories having a 6d UV completion, we determine the tensor branch data of the 6d SCFT and capture the twist in terms of the tensor branch data. We also determine the dualities between t

Marius de Leeuw, Chiara Paletta, Anton Pribytok, Ana L. Retore

We classify all regular solutions of the Yang-Baxter equation of eight-vertex type. Regular solutions correspond to spin chains with nearest-neighbour interactions. We find a total of four independent solutions. Two are related to the usual six- and eight-vertex models that have R-matrices of difference form. We find two completely new solutions of the Yang-

Bart Ripperda, Fabio Bacchini, Alexander Philippov

Hot spots, or plasmoids, forming due to magnetic reconnection in current sheets, are conjectured to power frequent X-ray and near-infrared flares from Sgr A*, the black hole in the center of our Galaxy. It is unclear how, where, and when current sheets form in black-hole accretion disks. We perform axisymmetric general-relativistic resistive magnetohydrodyna

Alexander Schäbe, Emilio Romano-Díaz, Cristiano Porciani, Aaron D. Ludlow

Modelling the molecular gas that is routinely detected through CO observations of high-redshift galaxies constitutes a major challenge for ab initio simulations of galaxy formation. We carry out a suite of cosmological hydrodynamic simulations to compare three approximate methods that have been used in the literature to track the formation and evolution of t

Tsuf Lichtman, Ryan Thorngren, Netanel H. Lindner, Ady Stern

We study effectively one-dimensional systems that emerge at the edge of a two-dimensional topologically ordered state, or at the boundary between two topologically ordered states. We argue that anyons of the bulk are associated with emergent symmetries of the edge, which play a crucial role in the structure of its phase diagram. Using this symmetry principle

Aron D. Kovacs, Harvey S. Reall

Effective field theory provides a way of parameterizing strong-field deviations from General Relativity that might be observable in the gravitational waves emitted in a black hole merger. To perform numerical simulations of mergers in such theories it is necessary that the equations be written in a form that admits a well-posed initial value formulation. We

Casey Cartwright

We report on the time evolution of a charged strongly coupled $N=4$ SYM plasma with an axial anomaly subjected to strong electromagnetic fields. The evolution of this plasma corresponds to a fully backreacted asymptotically AdS$_5$ solution to the Einstein-Maxwell-Chern-Simons theory. We explore the evolution of the axial current and production of axial char

Ramanjit Sohal, Eduardo Fradkin

We investigate the problem of intertwined orders in fractional Chern insulators by considering lattice fractional quantum Hall (FQH) states arising from pairing of composite fermions in the square-lattice Hofstadter model. At certain filling fractions, magnetic translation symmetry ensures the composite fermions form Fermi surfaces with multiple pockets, lea

Shireen Gangal, Jonathan R. Gaunt, Frank J. Tackmann, Eleni Vryonidou

The rapidity-dependent jet veto observables $\mathcal{T}_{Bj}$ and $\mathcal{T}_{Cj}$ provide a tight jet veto at central rapidity, gradually transitioning to a loose veto at forward rapidities. They divide the phase space into exclusive jet bins in a different way to the traditional jet veto observable $p_{Tj}$, and are advantageous to use under harsh pile-

Conrad Chan, Bernhard Mueller, Alexander Heger

Fallback in core-collapse supernovae plays a crucial role in determining the properties of the compact remnants and of the ejecta composition. We perform three-dimensional simulations of mixing and fallback for selected non-rotating supernova models to study how explosion energy and asymmetries correlate with the remnant mass, remnant kick, and remnant spin.

Peter B. Denton

Understanding the structure of the fermion mixing matrices is an important question in particle physics. The quark mixing matrix is approximately diagonal while the lepton mixing matrix has large off-diagonal elements. Attempting to understand these structures has been the focus of an large body of literature over the last several decades. In this article we

Axel Widmark, Khyati Malhan, Pablo F. de Salas, Sofia Sivertsson

We present a novel method for determining the total matter surface density of the Galactic disk by analysing the kinematics of a dynamically cold stellar stream that passes through or close to the Galactic plane. The method relies on the fact that the vertical component of energy for such stream stars is approximately constant, such that their vertical posit

Nicola T. Locatelli, Gianni Bernardi, Germano Bianchi, Riccardo Chiello

Fast radio bursts remain one of the most enigmatic astrophysical sources. Observations have significantly progressed over the last few years, thanks to the capabilities of new radio telescopes and the refurbishment of existing ones. Here we describe the upgrade of the Northern Cross radio telescope, operating in the 400-416~MHz frequency band, with the ultim

Benjamin Charles Germain Lee, Doug Downey, Kyle Lo, Daniel S. Weld

Research in human-centered AI has shown the benefits of systems that can explain their predictions. Methods that allow an AI to take advice from humans in response to explanations are similarly useful. While both capabilities are well-developed for transparent learning models (e.g., linear models and GA$^2$Ms), and recent techniques (e.g., LIME and SHAP) can

Ondrej Biza, Robert Platt, Jan-Willem van de Meent, Lawson L. S. Wong

Abstraction is crucial for effective sequential decision making in domains with large state spaces. In this work, we propose an information bottleneck method for learning approximate bisimulations, a type of state abstraction. We use a deep neural encoder to map states onto continuous embeddings. We map these embeddings onto a discrete representation using a

Sebastian J. Wetzel, Roger G. Melko, Joseph Scott, Maysum Panju

In this paper, we introduce interpretable Siamese Neural Networks (SNN) for similarity detection to the field of theoretical physics. More precisely, we apply SNNs to events in special relativity, the transformation of electromagnetic fields, and the motion of particles in a central potential. In these examples, the SNNs learn to identify datapoints belongin

Mandela Patrick, Yuki M. Asano, Polina Kuznetsova, Ruth Fong

In the image domain, excellent representations can be learned by inducing invariance to content-preserving transformations via noise contrastive learning. In this paper, we generalize contrastive learning to a wider set of transformations, and their compositions, for which either invariance or distinctiveness is sought. We show that it is not immediately obv

Karan P. Jain, Jerry Tang, Koushil Sreenath, Mark W. Mueller

Energy sources such as batteries do not decrease in mass after consumption, unlike combustion-based fuels. We present the concept of staging energy sources, i.e. consuming energy in stages and ejecting used stages, to progressively reduce the mass of aerial vehicles in-flight which reduces power consumption, and consequently increases flight time. A flight t

Ardavan Oskooi, Christopher Hogan, Alec M. Hammond, M. T. Homer Reid

We demonstrate neural-network runtime prediction for complex, many-parameter, massively parallel, heterogeneous-physics simulations running on cloud-based MPI clusters. Because individual simulations are so expensive, it is crucial to train the network on a limited dataset despite the potentially large input space of the physics at each point in the spatial

Charles Jin, Martin Rinard

We apply concepts from manifold regularization to develop new regularization techniques for training locally stable deep neural networks. Our regularizers are based on a sparsification of the graph Laplacian which holds with high probability when the data is sparse in high dimensions, as is common in deep learning. Empirically, our networks exhibit stability

Alessio Caciagli, Rajesh Singh, Darshana Joshi, R. Adhikari

We report experiments that show rapid crystallization of colloids tethered to an oil-water interface in response to laser illumination. This light-induced transition is due to a combination of long-ranged thermophoretic pumping and local optical binding. We show that the flow-induced force on the colloids can be described as the gradient of a potential. The

Jingyuan Wang, Ke Tang, Kai Feng, Xin Li

Objectives: We aim to assess the impact of temperature and relative humidity on the transmission of COVID-19 across communities after accounting for community-level factors such as demographics, socioeconomic status, and human mobility status. Design: A retrospective cross-sectional regression analysis via the Fama-MacBeth procedure is adopted. Setting: We u

M. H. Kim, O. Adriani, E. Berti, L. Bonechi

Transverse single-spin asymmetries of very forward neutral pions generated in polarized $p + p$ collisions allow us to understand the production mechanism in terms of perturbative and non-perturbative strong interactions. During 2017 the RHICf Collaboration installed an electromagnetic calorimeter in the zero-degree region of the STAR detector at the Relativ

Balázs Keszegh, Nathan Lemons, Ryan R. Martin, Dömötör Pálvölgyi

A subfamily $\mathcal{G}\subseteq \mathcal{F}\subseteq 2^{[n]}$ of sets is a non-induced (weak) copy of a poset $P$ in $\mathcal{F}$ if there exists a bijection $i:P\rightarrow \mathcal{G}$ such that $p\le_P q$ implies $i(p)\subseteq i(q)$. In the case where in addition $p\le_P q$ holds if and only if $i(p)\subseteq i(q)$, then $\mathcal{G}$ is an induced (s

J. M. Maillet, G. Niccoli, L. Vignoli

Using the framework of the quantum separation of variables (SoV) for higher rank quantum integrable lattice models [1], we introduce some foundations to go beyond the obtained complete transfer matrix spectrum description, and open the way to the computation of matrix elements of local operators. This first amounts to obtain simple expressions for scalar pro

Vida Dujmović, Louis Esperet, Gwenaël Joret, Cyril Gavoille

We show that there exists an adjacency labelling scheme for planar graphs where each vertex of an $n$-vertex planar graph $G$ is assigned a $(1+o(1))\log_2 n$-bit label and the labels of two vertices $u$ and $v$ are sufficient to determine if $uv$ is an edge of $G$. This is optimal up to the lower order term and is the first such asymptotically optimal resul

Felix Cheysson, Gabriel Lang

This paper presents a parametric estimation method for ill-observed linear stationary Hawkes processes. When the exact locations of points are not observed, but only counts over time intervals of fixed size, methods based on the likelihood are not feasible. We show that spectral estimation based on Whittle's method is adapted to this case and provides consis

Seunghwan Lee, Donghyeon Cho, Jiwon Kim, Tae Hyun Kim

In this study, we propose a self-supervised video denoising method called "restore-from-restored." This method fine-tunes a pre-trained network by using a pseudo clean video during the test phase. The pseudo clean video is obtained by applying a noisy video to the baseline network. By adopting a fully convolutional neural network (FCN) as the baselin

Seunghwan Lee, Dongkyu Lee, Donghyeon Cho, Jiwon Kim

In this study, we propose a simple and effective fine-tuning algorithm called "restore-from-restored", which can greatly enhance the performance of fully pre-trained image denoising networks. Many supervised denoising approaches can produce satisfactory results using large external training datasets. However, these methods have limitations in using i

Kaicheng Yu, Rene Ranftl, Mathieu Salzmann

Weight sharing promises to make neural architecture search (NAS) tractable even on commodity hardware. Existing methods in this space rely on a diverse set of heuristics to design and train the shared-weight backbone network, a.k.a. the super-net. Since heuristics and hyperparameters substantially vary across different methods, a fair comparison between them

Guoxing Lin

This paper proposes an effective diffusion equation method to analyze nuclear magnetic resonance (NMR) relaxation. NMR relaxation is a spin system recovery process, where the evolution of the spin system is affected by the random field due to Hamiltonians, such as dipolar couplings. The evolution of magnetization can be treated as a random walk in phase spac

V. L. Quito, Rebecca Flint

Floquet engineering is a powerful tool that drives materials with periodic light. Traditionally, the light is monochromatic, with amplitude, frequency, and polarization varied. We introduce Floquet engineering via unpolarized light built from quasi-monochromatic light, and show how it can modify strongly correlated systems, while preserving the original symm

Zhongdong Liu, Liang Huang, Bin Li, Bo Ji

The Age-of-Information (AoI) is a new performance metric recently proposed for measuring the freshness of information in information-update systems. In this work, we conduct a systematic and comparative study to investigate the impact of scheduling policies on the AoI performance in single-server queues and provide useful guidelines for the design of AoI-eff

J. John Soundar Jerome, Sébastien Thevenin, Mickaël Bourgoin, Jean-Philippe Matas

The so-called Landau-Levich-Deryaguin problem treats the coating flow dynamics of a thin viscous liquid film entrained by a moving solid surface. In this context, we use a simple experimental set-up consisting of a partially-immersed rotating disc in a liquid tank to study the role of inertia, and also curvature, on liquid entrainment. Using water and UCON$^

Martin Nicholson

An identity is proved connecting two finite sums of inverse tangents. This identity is discretized version of Jacobi's imaginary transformation for the modular angle from the theory of elliptic functions. Some other related identities are discussed.

Tuan Q. Do, W. F. Kao, Ing-Chen Lin

Effect of non-canonical scalar fields on the CMB imprints of the anisotropic inflation will be discussed in details in this paper. In particular, we are able to obtain the general formalism of the angular power spectra in the scalar perturbations, tensor perturbations, cross-correlations, and linear polarization in the context of the anisotropic inflation mo

Meng Zhang, Deepanshu Vasal

Network utility maximization (NUM) is a general framework for designing distributed optimization algorithms for large-scale networks. An economic challenge arises in the presence of strategic agents' private information. Existing studies proposed (economic) mechanisms but largely neglected the issue of large-scale implementation. Specifically, they requi

Tianfei Zhou, Wenguan Wang, Siyuan Qi, Haibin Ling

Rapid progress has been witnessed for human-object interaction (HOI) recognition, but most existing models are confined to single-stage reasoning pipelines. Considering the intrinsic complexity of the task, we introduce a cascade architecture for a multi-stage, coarse-to-fine HOI understanding. At each stage, an instance localization network progressively re

Célestin Coquidé, Włodzimierz Lewoniewski

Nowadays, information describing navigation behaviour of internet users are used in several fields, e-commerce, economy, sociology and data science. Such information can be extracted from different knowledge bases, including business-oriented ones. In this paper, we propose a new model for the PageRank, CheiRank and 2DRank algorithm based on the use of click

Angel Garcia-Chung

In this paper we show the relation between $sp(4,\mathbb{R})$, the Lie algebra of the symplectic group, and the elements of the symplectic group $Sp(4,\mathbb{R})$. We use this relation to provide a classical analog of the squeeze operator $\widehat{S}(ζ)$. This classical squeeze matrix shares some similarities with the correlation matrix ${\bf V}^{(2)}$ and

Lars Jaffke, Paloma T. Lima, Daniel Lokshtanov

We provide a polynomial-time algorithm for b-Coloring on graphs of constant clique-width. This unifies and extends nearly all previously known polynomial time results on graph classes, and answers open questions posed by Campos and Silva [Algorithmica, 2018] and Bonomo et al. [Graphs Combin., 2009]. This constitutes the first result concerning structural par

Tianfei Zhou, Shunzhou Wang, Yi Zhou, Yazhou Yao

In this paper, we present a novel Motion-Attentive Transition Network (MATNet) for zero-shot video object segmentation, which provides a new way of leveraging motion information to reinforce spatio-temporal object representation. An asymmetric attention block, called Motion-Attentive Transition (MAT), is designed within a two-stream encoder, which transforms

David N. Sibley, Pablo Llombart, Eva G. Noya, Andrew J. Archer

Close to the triple point, the surface of ice is covered by a thin liquid layer (so-called quasi-liquid layer) which crucially impacts growth and melting rates. Experimental probes cannot observe the growth processes below this layer, and classical models of growth by vapor deposition do not account for the formation of premelting films. Here, we develop a m

Thibault Buhet, Emilie Wirbel, Andrei Bursuc, Xavier Perrotton

To navigate safely in urban environments, an autonomous vehicle (ego vehicle) must understand and anticipate its surroundings, in particular the behavior and intents of other road users (neighbors). Most of the times, multiple decision choices are acceptable for all road users (e.g., turn right or left, or different ways of avoiding an obstacle), leading to

Fabrizio Del Gaudio, Ricardo Fonseca, Luis O. Silva, Thomas Grismayer

Photon bursts with a wavelength smaller than the plasma inter-particle distance can drive plasma wakes via Compton scattering. We investigate this fundamental process analytically and numerically for different photon frequencies, photon flux, and plasma magnetization. Our results show that Langmuir and extraordinary modes are driven efficiently when the phot

Alice Plebe, Mauro Da Lio

This paper proposes a strategy for visual prediction in the context of autonomous driving. Humans, when not distracted or drunk, are still the best drivers you can currently find. For this reason we take inspiration from two theoretical ideas about the human mind and its neural organization. The first idea concerns how the brain uses a hierarchical structure

David Marco Sommer, Liwei Song, Sameer Wagh, Prateek Mittal

The right to be forgotten, also known as the right to erasure, is the right of individuals to have their data erased from an entity storing it. The status of this long held notion was legally solidified recently by the General Data Protection Regulation (GDPR) in the European Union. Consequently, there is a need for mechanisms whereby users can verify if ser

Huilai Zhang, Ran Huang, Sheng-Dian Zhang, Ying Li

Non-Hermitian systems, with symmetric or antisymmetric Hamiltonians under the parity-time ($\mathcal{PT}$) operations, can have entirely real eigenvalues. This fact has led to surprising discoveries such as loss-induced lasing and topological energy transfer. A merit of anti-$\mathcal{PT}$ systems is free of gain, but in recent efforts on making anti-$\mathc

Alberto Marcone, Manlio Valenti

We investigate the uniform computational content of the open and clopen Ramsey theorems in the Weihrauch lattice. While they are known to be equivalent to $\mathrm{ATR_0}$ from the point of view of reverse mathematics, there is not a canonical way to phrase them as multivalued functions. We identify 8 different multivalued functions (5 corresponding to the o

F. Belgiorno, S. L. Cacciatori, A. Farahat, A. Viganò

We take into account two further physical models which play an utmost importance in the framework of Analogue Gravity. We first consider Bose--Einstein condensates (BEC) and then surface gravity waves in water. Our approach is based on the use of the master equation we introduced in a previous work. A more complete analysis of the singular perturbation probl

Debajyoti Choudhuri, Jiabin Zuo

In this paper, we investigate the existence of nontrivial weak solutions for the Prandtl-Batchelor type free boundary value elliptic problem driven by a power nonlinearity. The algebraic topology approach will be used to establish the existence of solutions of approximate problem, while variational techniques will be used to determine the existence of major

Thomas Stringham

Researchers are often interested in linking individuals between two datasets that lack a common unique identifier. Matching procedures often struggle to match records with common names, birthplaces or other field values. Computational feasibility is also a challenge, particularly when linking large datasets. We develop a Bayesian method for automated probabi

Guodu Chen

We show the existence of $n$-complements for generalized pairs with additional Diophantine approximation properties when the coefficients of boundaries belong to a DCC set.

F. Belgiorno, S. L. Cacciatori, A. Viganò

We consider further on the problem of the analogue Hawking radiation. We propose a fourth order ordinary differential equation, which allows to discuss the problem of Hawking radiation in analogue gravity in a unified way, encompassing fluids and dielectric media. In a suitable approximation, involving weak dispersive effects, WKB solutions are obtained far

B. Feigin, M. Jimbo, E. Mukhin, I. Vilkoviskiy

The deformed $\mathcal W$ algebras of type $\textsf{A}$ have a uniform description in terms of the quantum toroidal $\mathfrak{gl}_1$ algebra $\mathcal E$. We introduce a comodule algebra $\mathcal K$ over $\mathcal E$ which gives a uniform construction of basic deformed $\mathcal W$ currents and screening operators in types $\textsf{B},\textsf{C},\textsf{D}

Horacio Guerra

We classify the simple restricted modules for the minimal $p$-envelope of the non-graded, non-restricted Hamiltonian Lie algebra $H(2; (1,1); Φ(1))$ over an algebraically closed field $k$ of characteristic $p \geq 5$. We also give the restrictions of these modules to a subalgebra isomorphic to the first Witt Algebra, a result stated in [S. Herpel and D. Stew

Georgios Georgakis, Ren Li, Srikrishna Karanam, Terrence Chen

We consider the problem of estimating a parametric model of 3D human mesh from a single image. While there has been substantial recent progress in this area with direct regression of model parameters, these methods only implicitly exploit the human body kinematic structure, leading to sub-optimal use of the model prior. In this work, we address this gap by p

Ruiwen Shu

This paper studies the large time behavior of aggregation-diffusion equations. For one spatial dimension with certain assumptions on the interaction potential, the diffusion index $m$, and the initial data, we prove the convergence to the unique steady state as time goes to infinity (equilibration), with an explicit algebraic rate. The proof is based on a un

Anna C. Tasolamprou, Despoina Mentzaki, Zacharias Viskadourakis, Eleftherios N. Economou

We present a cost-effective, eco-friendly and accessible method for fabricating three-dimensional, ultralight and flexible millimeter-scale metasurfaces using a household 3D printer. In particular, we fabricate conductive Spilt Ring Resonators (SRRs) in a free-standing form, employing the so-called Fused Deposition Modeling 3D printing technique. We experime

S. Wandel, F. Boschini, E. H. da Silva Neto, L. Shen

Superconductivity and charge density waves (CDW) are competitive, yet coexisting orders in cuprate superconductors. To understand their microscopic interdependence, a probe capable of discerning their interaction on its natural length and time scales is necessary. We use ultrafast resonant soft x-ray scattering to track the transient evolution of CDW correla

Maciej Zgirski, Marek Foltyn, Alexander Savin, Konrad Norowski

We study correlated switchings of superconducting nanobridge probed with train of current pulses. For pulses with low repetition rate each pulse transits the superconducting bridge to normal state with probability $P$ independent of the outcomes in the preceding pulses. We show that with reduction of the time interval between pulses long range correlation be

Xavier Calmet, Roberto Casadio, Folkert Kuipers

In this paper we consider a static and regular fluid generating a locally spherically symmetric and time-independent space-time and calculate the leading quantum corrections to the metric to first order in curvature. Starting from a singularity free classical solution of general relativity, we show that singularities can be introduced in the curvature invari

Clément Dupont, Daniel Juteau

We construct and study a motivic lift of a spectral sequence associated to a stratified scheme, recently discovered by Petersen in the context of mixed Hodge theory and $\ell$-adic Galois representations. The original spectral sequence expresses the compactly supported cohomology of an open stratum in terms of the compactly supported cohomology of the closur

Piotr Nowakowski, Tomasz Filipczak

Let $C(\lambda )\subset \lbrack 0,1]$ denote the central Cantor set generated by a sequence $ \lambda = \left( \lambda_{n} \right) \in \left( 0,\frac{1}{2} \right) ^{\mathbb{N}}$. By the known trichotomy, the difference set $ C(\lambda )-C(\lambda )$ of $C(\lambda )$ is one of three possible sets: a finite union of closed intervals, a Cantor set, and a Canto

Yongxin Yao, Feng Zhang, Cai-Zhuang Wang, Kai-Ming Ho

Rapid progress in noisy intermediate-scale quantum (NISQ) computing technology has led to the development of novel resource-efficient hybrid quantum-classical algorithms, such as the variational quantum eigensolver (VQE), that can address open challenges in quantum chemistry, physics and material science. Proof-of-principle quantum chemistry simulations for

Alexandre Lartaux

Let $f$ be an arithmetic function, $V\geqslant 1$ a real number and $$\Delta_V(n,f) := \sup\limits_{\substack{u \in \mathbb{R}\\ v \in [0,V]}}{\Big|\sum\limits_{\substack{d\mid n \\ {\rm e}^{u}<d\leqslant {\rm e}^{u+v}}}{f(d)}\Big|}{\rm .}$$ In a paper published in 2012, La Bret\`eche and Tenenbaum investigated weighted moments of $\Delta_1(n,f)$ where $f$ i

Joseph W. Baron, Tobias Galla

In his seminal work in the 1970s, Robert May suggested that there is an upper limit to the number of species that can be sustained in stable equilibrium by an ecosystem. This deduction was at odds with both intuition and the observed complexity of many natural ecosystems. The so-called stability-diversity debate ensued, and the discussion about the factors c

Jonas Hetz

Let $G$ be a finite group of Lie type. In order to determine the character table of $G$, Lusztig developed the theory of character sheaves. In this framework, one has to find the transformation between two bases for the space of class functions on $G$, one of them being the irreducible characters of $G$, the other one consisting of characteristic functions a

Andrei Tetenov

We consider self-similar continua possessing finite intersection property and prove intersection graph criterion for self-similar dendrites, finite order Theorem for such continua satisfying open set condition in $\mathbb{R}^n$ and parameter matching Theorem which states that all Jordan arcs starting from a intersection point in such continuum on a plane sho

Niko Lietzén, Lauri Viitasaari, Pauliina Ilmonen

We consider a complex-valued linear mixture model, under discrete weakly stationary processes. We recover latent components of interest, which have undergone a linear mixing. We study asymptotic properties of a classical unmixing estimator, that is based on simultaneous diagonalization of the covariance matrix and an autocovariance matrix with lag $τ$. Our m

George Kourousias, Fulvio Billè, Roberto Borghes, Antonio Alborini

X-Ray Fluorescence (XRF) scanning is a widespread technique of high importance and impact since it provides chemical composition maps crucial for several scientific investigations. There are continuous requirements for larger, faster and highly resolved acquisitions in order to study complex structures. Among the scientific applications that benefit from it,

Yu He, Yun Cai, Yuan-Chen Guo, Zheng-Ning Liu

Traditional indoor scene synthesis methods often take a two-step approach: object selection and object arrangement. Current state-of-the-art object selection approaches are based on convolutional neural networks (CNNs) and can produce realistic scenes for a single room. However, they cannot be directly extended to synthesize style-compatible scenes for multi

Ankit Izardar, Claude Ederer

We use first-principles-based calculations to investigate the interplay between chemical order and the magnetic properties of $L1_0$ FeNi. In particular, we investigate how deviations from perfect chemical order affect the energy difference between the paramagnetic and ferromagnetic states as well as the important magneto-crystalline anisotropy energy. Our c

Ziv Aharoni, Dor Tsur, Ziv Goldfeld, Haim Henry Permuter

Calculating the capacity (with or without feedback) of channels with memory and continuous alphabets is a challenging task. It requires optimizing the directed information (DI) rate over all channel input distributions. The objective is a multi-letter expression, whose analytic solution is only known for a few specific cases. When no analytic solution is pre

Kingman Cheung, Adil Jueid, Ying-nan Mao, Stefano Moretti

We analyze CP-violating effects in both Electric Dipole Moment (EDM) measurements and future analyses at the Large Hadron Collider (LHC) assuming a Two-Higgs-Doublet Model (2HDM) with &#34;soft&#34; CP-violation. Our analysis of EDMs and current LHC constraints shows that, in the case of a 2HDM Type II and Type III, an $\mathcal{O}(0.1)$ CP-violating phase i

Pedro Cabalar, Jorge Fandinno, Torsten Schaub, Philipp Wanko

Characterizing hybrid ASP solving in a generic way is difficult since one needs to abstract from specific theories. Inspired by lazy SMT solving, this is usually addressed by treating theory atoms as opaque. Unlike this, we propose a slightly more transparent approach that includes an abstract notion of a term. Rather than imposing a syntax on terms, we keep

Zhilin Chen, Foad Sohrabi, Ya-Feng Liu, Wei Yu

This paper considers a massive random access problem in which a large number of sporadically active devices wish to communicate with a base station (BS) equipped with massive multiple-input multiple-output (MIMO) antennas. Each device is preassigned a unique signature sequence, and the BS identifies the active devices by detecting which sequences are transmi

Hiroshi Ohki, Shohei Uemura, Risa Watanabe

We study the modular invariance in magnetized torus models. Modular invariant flavor model is a recently proposed hypothesis for solving the flavor puzzle, where the flavor symmetry originates from modular invariance. In this framework coupling constants such as Yukawa couplings are also transformed under the flavor symmetry. We show that the low-energy effe

Ivan Fursov, Alexey Zaytsev, Nikita Kluchnikov, Andrey Kravchenko

Deep learning models suffer from a phenomenon called adversarial attacks: we can apply minor changes to the model input to fool a classifier for a particular example. The literature mostly considers adversarial attacks on models with images and other structured inputs. However, the adversarial attacks for categorical sequences can also be harmful. Successful

Victoria Volodina, Edward Wheatcroft, Henry Wynn

District heating is a network of pipes through which heat is delivered from a centralised source. It is expected to play an important role in the decarbonisation of the energy sector in the coming years. In district heating, heat is traditionally generated through fossil fuels, often with combined heat and power (CHP) units. However, increasingly, waste heat

Carlos Pérez, Eduard Roure Perdices

The Hardy-Littlewood maximal operator satisfies the classical Sawyer-type estimate $$ \left \Vert \frac{Mf}{v}\right \Vert_{L^{1,\infty}(uv)} \leq C_{u,v} \Vert f \Vert_{L^{1}(u)}, $$ where $u\in A_1$ and $uv\in A_{\infty}$. We prove a novel extension of this result to the general restricted weak type case. That is, for $p>1$, $u\in A_p^{\mathcal R}$, and $u

Dong-Kyum Kim, Youngkyoung Bae, Sangyun Lee, Hawoong Jeong

This Letter presents a neural estimator for entropy production, or NEEP, that estimates entropy production (EP) from trajectories of relevant variables without detailed information on the system dynamics. For steady state, we rigorously prove that the estimator, which can be built up from different choices of deep neural networks, provides stochastic EP by o

Frederik vom Ende

Motivated by reachability questions in coherently controlled open quantum systems coupled to a thermal bath, as well as recent progress in the field of thermo-/vector-majorization we generalize classical majorization from unital quantum channels to channels with an arbitrary fixed point $D$ of full rank. Such channels preserve some Gibbs-state and thus play

Jean Cappello, Vincent d&#39;Herbemont, Anke Lindner, Olivia du Roure

Being able to precisely characterize the mechanical properties of soft microparticles is essential for numerous situations from the understanding of the flow of biological fluids to the development of soft micro-robots. Here we present a simple measurement technique for the Poisson&#39;s ratio of soft micron-sized hydrogels in the presence of a surrounding l