April 2019 arXiv papers — page 114

Masato Kobayashi

We extend the author's formula (2011) of weighted counting of inversions on permutations to the one on alternating sign matrices. The proof is based on the sequential construction of alternating sign matrices from the unit matrix recently shown by Brualdi-Schroeder and the author (both 2017) independently.

Mohsen Soltanifar

In this paper, we consider the problem of order preservation under addition and multiplication operators over the vector space of univariate real-valued random variables. Consistent with the case of usual order over the real numbers-as constant random variables, we prove that the usual stochastic order is both additive and multiplicative. We additionally dis

Jacek Syska

The error probability of the discrimination of the Standard Model (SM) with massive neutrinos and its new physics (NP) model extension in experiments of the muon neutrino oscillation, following the pion decay $π^{+} \rightarrow μ^{+} + ν_μ$, is calculated. The stability of the estimation of the NP charged current coupling constant $\varepsilon_{R}$ is analys

William M. Kirby, Peter J. Love

Contextuality is an indicator of non-classicality, and a resource for various quantum procedures. In this paper, we use contextuality to evaluate the variational quantum eigensolver (VQE), one of the most promising tools for near-term quantum simulation. We present an efficiently computable test to determine whether or not the objective function for a VQE pr

Benharrat Belaïdi

In this paper, we deal with the growth of solutions of homogeneous linear complex differential equation by using the concept of lower [\textit{p,q}]-order and lower [\textit{p,q}]-type in a sector of the unit disc instead of the whole unit disc, and we obtain similar results as in the case of the unit disc.

Thomas Manzini, Yao Chong Lim, Yulia Tsvetkov, Alan W Black

Online texts -- across genres, registers, domains, and styles -- are riddled with human stereotypes, expressed in overt or subtle ways. Word embeddings, trained on these texts, perpetuate and amplify these stereotypes, and propagate biases to machine learning models that use word embeddings as features. In this work, we propose a method to debias word embedd

Leyla Isaeva, Giuseppe Barbalinardo, Davide Donadio, Stefano Baroni

We introduce a novel approach to model heat transport in solids, based on the Green-Kubo theory of linear response. It naturally bridges the Boltzmann kinetic approach in crystals and the Allen-Feldman model in glasses, leveraging interatomic force constants and normal-mode linewidths computed at mechanical equilibrium. At variance with molecular dynamics, o

Gwenaël Boué, Michael Efroimsky

We address the expressions for the rates of the Keplerian orbital elements within a two-body problem perturbed by the tides in both partners. The formulae for these rates have appeared in the literature in various forms, at times with errors. We reconsider, from scratch, the derivation of these rates and arrive at the Lagrange-type equations which, in some d

Rohan Chabra, Julian Straub, Chris Sweeney, Richard Newcombe

We propose a system that uses a convolution neural network (CNN) to estimate depth from a stereo pair followed by volumetric fusion of the predicted depth maps to produce a 3D reconstruction of a scene. Our proposed depth refinement architecture, predicts view-consistent disparity and occlusion maps that helps the fusion system to produce geometrically consi

Jesse Mu, Helen Yannakoudakis, Ekaterina Shutova

Most current approaches to metaphor identification use restricted linguistic contexts, e.g. by considering only a verb's arguments or the sentence containing a phrase. Inspired by pragmatic accounts of metaphor, we argue that broader discourse features are crucial for better metaphor identification. We train simple gradient boosting classifiers on repres

Olesia Krupnitska

We consider the spin-1/2 antiferromagnetic Heisenberg model on two one-dimensional frustrated lattices, double-tetrahedral chain and octahedral chain, with almost dispersionless (flat) lowest magnon band in a strong magnetic field. Using the localized magnons picture, we construct an effective description of the one-dimensional chains with triangle and squar

Valentin Khrulkov, Leyla Mirvakhabova, Evgeniya Ustinova, Ivan Oseledets

Computer vision tasks such as image classification, image retrieval and few-shot learning are currently dominated by Euclidean and spherical embeddings, so that the final decisions about class belongings or the degree of similarity are made using linear hyperplanes, Euclidean distances, or spherical geodesic distances (cosine similarity). In this work, we de

F. Pelusi, M. Sbragaglia, A. Scagliarini, M. Lulli

We explore the impact of geometrical corrugations on the near-wall flow properties of a soft-material driven in a confined rough microchannel. By means of numerical simulations, we perform a quantitative analysis of the relation between the flow rate $Φ$ and the wall stress $σ_w$ for a number of setups, by changing both the roughness values as well as the ro

Francesco Di Giovanni

We study the Ricci flow on $\mathbb{R}^{4}$ starting at an SU(2)-cohomogeneity 1 metric $g_{0}$ whose restriction to any hypersphere is a Berger metric. We prove that if $g_{0}$ has no necks and is bounded by a cylinder, then the solution develops a global Type-II singularity and converges to the Bryant soliton when suitably dilated at the origin. This is th

Matthieu Calvez, Bert Wiest

The goal of this mostly expository paper is to present several candidates for hyperbolic structures on irreducible Artin-Tits groups of spherical type and to elucidate some relations between them. Most constructions are algebraic analogues of previously known hyperbolic structures on Artin braid groups coming from natural actions of these groups on curve gra

Albert Chau, Man-Chun Lee

We produce complete bounded curvature solutions to Kähler-Ricci flow with existence time estimates, assuming only that the initial data is a smooth \K metric uniformly equivalent to another complete bounded curvature \K metric. We obtain related flow results for non-smooth as well as degenerate initial conditions. We also obtain a stability result for comple

Hu Xu, Bing Liu, Lei Shu, Philip S. Yu

Question-answering plays an important role in e-commerce as it allows potential customers to actively seek crucial information about products or services to help their purchase decision making. Inspired by the recent success of machine reading comprehension (MRC) on formal documents, this paper explores the potential of turning customer reviews into a large

Olivia K. Donaldson, Timothy J. Rupert

Nanocrystalline metal alloys show great potential as structural materials, but are often only available in small volumes such as thin films or powders. However, recent research has suggested that dopant segregation and grain boundary structural transitions between states known as complexions can dramatically alter grain size stability and potentially enable

Naum M. Khutoryansky

A new approach to building explicit time-marching stencil computation schemes for the transient 2D acoustic wave equation is implemented. It is based on using Poisson's formula and its three time level modification combined with polynomial stencil interpolation of the solution at each time-step and exact integration. The time-stepping algorithm consists

John Baptist Gauci, Tomaz Pisanski, Irene Sciriha

In this paper the problem of the existence of regular nut graphs is addressed. A generalization of Fowler's Construction which is a local enlargement applied to a vertex in a graph is introduced to generate nut graphs of higher order. Let $N(ρ)$ denote the set of integers $n$ such that there exists a regular nut graph of degree $ρ$ and order $n$. It is p

Peter Potash

One popular method for quantitatively evaluating the utility of sentence embeddings involves using them in downstream language processing tasks that require sentence representations as input. One simple such task is classification, where the sentence representations are used to train and test models on several classification datasets. We argue that by evalua

Ognjen Milatovic

We give a sufficient condition for the essential self-adjointness of a perturbation of the square of the magnetic Laplacian on an infinite weighted graph. The main result is applicable to graphs whose degree function is not necessarily bounded. The result allows perturbations that are not necessarily bounded from below by a constant.

Wissam Bejjani, Mehmet R. Dogar, Matteo Leonetti

Physics-based manipulation in clutter involves complex interaction between multiple objects. In this paper, we consider the problem of learning, from interaction in a physics simulator, manipulation skills to solve this multi-step sequential decision making problem in the real world. Our approach has two key properties: (i) the ability to generalize and tran

Maria Pittou, George Rahonis

One of the key aspects in component-based design is specifying the software architecture that characterizes the topology and the permissible interactions of the components of a system. To achieve well-founded design there is need to address both the qualitative and non-functional aspects of architectures. In this paper we study the qualitative and quantitati

Bharat Joshi, Sharmin Rahman, Michail Kalaitzakis, Brennan Cain

A plethora of state estimation techniques have appeared in the last decade using visual data, and more recently with added inertial data. Datasets typically used for evaluation include indoor and urban environments, where supporting videos have shown impressive performance. However, such techniques have not been fully evaluated in challenging conditions, suc

Brian Coyle, Daniel Mills, Vincent Danos, Elham Kashefi

The search for an application of near-term quantum devices is widespread. Quantum Machine Learning is touted as a potential utilisation of such devices, particularly those which are out of the reach of the simulation capabilities of classical computers. In this work, we propose a generative Quantum Machine Learning Model, called the Ising Born Machine (IBM),

Rick Durrett, Dong Yao

We consider a contact process on $Z^d$ with two species that interact in a symbiotic manner. Each site can either be vacant or occupied by individuals of species $A$ and/or $B$. Multiple occupancy by the same species at a single site is prohibited. The name symbiotic comes from the fact that if only one species is present at a site then that particle dies wi

Pim van der Hoorn, Gabor Lippner, Elchanan Mossel

A $d$-regular graph on $n$ nodes has at most $T_{\max} = \frac{n}{3} \tbinom{d}{2}$ triangles. We compute the leading asymptotics of the probability that a large random $d$-regular graph has at least $c \cdot T_{\max}$ triangles, and provide a strong structural description of such graphs. When $d$ is fixed, we show that such graphs typically consist of many

A. Kastberg, T. Aoki, B. K. Sahoo, Y. Sakemi

We propose a method for measuring parity violation in neutral atoms. It is an adaptation of a seminal work by Fortson [Phys. Rev. Lett. {\bf 70}, 2383 (1993)], proposing a scheme for a single trapped ion. In our version, a large sample of neutral atoms should be localised in an optical lattice overlapping a grid of detection sites, all tailored as the single

Monika Leibscher, Thomas F. Giesen, Christiane P. Koch

Three-wave mixing spectroscopy of chiral molecules, which exist in left-handed and right-handed conformations, allows for enantio-selective population transfer despite random orientation of the molecules. This is based on constructive interference of the three-photon pathways for one enantiomer and destructive one for the other. We prove here that three mutu

Nadav Dym, Shahar Ziv Kovalsky

In recent years, several branch-and-bound (BnB) algorithms have been proposed to globally optimize rigid registration problems. In this paper, we suggest a general framework to improve upon the BnB approach, which we name Quasi BnB. Quasi BnB replaces the linear lower bounds used in BnB algorithms with quadratic quasi-lower bounds which are based on the quad

Pravakar Roy, Nicolai Häni, Jun-Jee Chao, Volkan Isler

Image to image translation is the problem of transferring an image from a source domain to a different (but related) target domain. We present a new unsupervised image to image translation technique that leverages the underlying semantic information for object transfiguration and domain transfer tasks. Specifically, we present a generative adversarial learni

Lei Yu, Ling Liu, Calton Pu, Mehmet Emre Gursoy

Deep learning techniques based on neural networks have shown significant success in a wide range of AI tasks. Large-scale training datasets are one of the critical factors for their success. However, when the training datasets are crowdsourced from individuals and contain sensitive information, the model parameters may encode private information and bear the

Cathrin Elich, Francis Engelmann, Theodora Kontogianni, Bastian Leibe

Recent deep learning models achieve impressive results on 3D scene analysis tasks by operating directly on unstructured point clouds. A lot of progress was made in the field of object classification and semantic segmentation. However, the task of instance segmentation is less explored. In this work, we present 3D-BEVIS, a deep learning framework for 3D seman

G. Fabbiano, A. Paggi, M. Elvis

A recent ALMA study of the Seyfert 2 Active Galactic Nucleus (AGN) NGC 2110 by Rosario et al. (2019) has reported a remarkable lack of CO 2-1 emission from the circumnuclear region, where optical lines and H2 emission are observed, leading to the suggestion of excitation of the molecular clouds by the AGN. Since interaction with X-ray photons could be the ca

Aswin P. Vijayan, Scott J. Clay, Peter A. Thomas, Robert M. Yates

We implement a detailed dust model into the L-Galaxies semi-analytical model which includes: injection of dust by type II and type Ia supernovae (SNe) and AGB stars; grain growth in molecular clouds; and destruction due to supernova-induced shocks, star formation, and reheating. Our grain growth model follows the dust content in molecular clouds and the inte

Ivan Chio, Roland Roeder

Associated to any finite simple graph $Γ$ is the chromatic polynomial $P_Γ(q)$ whose complex zeroes are called the chromatic zeros of $Γ$. A hierarchical lattice is a sequence of finite simple graphs $\{Γ_n\}_{n=0}^\infty$ built recursively using a substitution rule expressed in terms of a generating graph. For each $n$, let $μ_n$ denote the probability meas

Chun-Yuan Li, Zong-Guo Si, Yu-Feng Zhou

In an extended effective operator framework of isospin violating interactions with light mediators, we investigate the compatibility of the candidate signal of the CDMS-II-Si with the latest constraints from DarkSide-50 and XENON-1T, etc. We show that the constraints from DarkSide-50 which utilizes Argon as the target is complementary to that from XENON-1T w

Rouven Frassek

In this note we relate the Hamiltonian of the integrable non-compact spin $s$ XXZ chain to the Markov generator of a stochastic particle process. The hopping rates of the continuous-time process are identified with the ones of a q-Hahn asymmetric zero range model. The main difference with the asymmetric simple exclusion process (ASEP), which can be mapped to

Gary T. Horowitz, Don Marolf, Jorge E. Santos, Diandian Wang

We argue that one can nucleate a traversable wormhole via a nonperturbative process in quantum gravity. To support this, we construct spacetimes in which there are instantons giving a finite probability for a test cosmic string to break and produce two particles on its ends. One should be able to replace the particles with small black holes with only small c

Wolfgang Schmaltz

The Steenrod problem for closed orientable manifolds was solved completely by Thom. Following this approach, we solve the Steenrod problem for closed orientable orbifolds, proving that the rational homology groups of a closed orientable orbifold have a basis consisting of classes represented by suborbifolds whose normal bundles have fiberwise trivial isotrop

Anirban Bhattacharjee, Yogesh Barve, Aniruddha Gokhale, Takayuki Kuroda

Users of cloud platforms often must expend significant manual efforts in the deployment and orchestration of their services on cloud platforms due primarily to having to deal with the high variabilities in the configuration options for virtualized environment setup and meeting the software dependencies for each service. Despite the emergence of many DevOps c

Alexandra Porter, Mary Wootters

Motivated by applications in distributed storage and distributed computation, we introduce embedded index coding (EIC). EIC is a type of distributed index coding in which nodes in a distributed system act as both senders and receivers of information. We show how embedded index coding is related to index coding in general, and give characterizations and bound

Shishir Khandelwal, Maximilian P. E. Lock, Mischa P. Woods

The theory of relativity associates a proper time with each moving object via its world line. In quantum theory however, such well-defined trajectories are forbidden. After introducing a general characterisation of quantum clocks, we demonstrate that, in the weak-field, low-velocity limit, all "good" quantum clocks experience time dilation as dictate

Thomas Zdyrski, John McGreevy

We use hydrodynamic techniques to analyze the one-dimensional propagation of solitons in gated graphene on an arbitrary uniform background current. Results are derived for both the Fermi liquid and Dirac fluid regimes. We find that these solutions satisfy the Korteweg-de Vries-Burgers equation. Viscous dissipation and ohmic heating are included, causing the

Haoyu Guo, Yingfei Gu, Subir Sachdev

We compute the transport and chaos properties of lattices of quantum Sachdev-Ye-Kitaev islands coupled by single fermion hopping, and with the islands coupled to a large number of local, low energy phonons. We find two distinct regimes of linear-in-temperature ($T$) resistivity, and describe the crossover between them. When the electron-phonon coupling is we

M. L. Boyer, B. F. Williams, B. Aringer, Y. Chen

We analyze resolved stellar near-infrared photometry of 21 HST fields in M31 to constrain the impact of metallicity on the formation of carbon stars. Observations of nearby galaxies show that the carbon stars are increasingly rare at higher metallicity. Models indicate that carbon star formation efficiency drops due to the decrease in dredge-up efficiency in

M. M. Fausnaugh, P. J. Vallely, C. S. Kochanek, B. J. Shappee

We present early time light curves of Type Ia supernovae observed in the first six sectors of TESS data. Ten of these supernovae were discovered by ASAS-SN, seven by ATLAS, six by ZTF, and one by \textit{Gaia}. For nine SNe with sufficient dynamic range ($>$3.0 mag from detection to peak), we fit power law models and search for signatures of companion stars.

Hao Geng, Sebastian Grieninger, Andreas Karch

We calculate the entanglement entropy of the de-Sitter (dS) static patch in the context of the DS/dS correspondence. Interestingly, we find that there exists a one parameter family of bulk minimal surfaces that all have the same area. Two of them have appeared earlier in the literature. All of them correctly calculate the dS entropy. One surface yields the e

Osama Zwaid Alsulami, Mohammed T. Alresheedi, Jaafar M. H. Elmirghani

Providing uplink high data rate is one of the big concerns in visible light communication (VLC) systems. This paper introduces an uplink VLC system based on an infrared transmitter with beam steering to provide high data rates. In this work, a 4 branches angle diversity receiver (ADR) is used and the resultant delay spread and SNR are examined. The proposed

Thomas Berlok, Christoph Pfrommer

High redshift, massive halos are observed to have sustained, high star formation rates, which require that the amount of cold gas in the halo is continuously replenished. The cooling time scale for the hot virialized halo gas is too long to provide the source of cold gas. Supersonic, cold streams have been invoked as a mechanism for feeding massive halos at

Xiao-Ming Zhang, Man-Hong Yung

Optical neural network (ONN) is emerging as an attractive proposal for machine-learning applications, enabling high-speed computation with low-energy consumption. However, there are several challenges in applying ONN for industrial applications, including the realization of activation functions and maintaining stability. In particular, the stability of ONNs

Wenjie Zhang, Peipei Wang, Brian Skinner, Ran Bi

The thermoelectric Hall effect is the generation of a transverse heat current upon applying an electric field in the presence of a magnetic field. Here we demonstrate that the thermoelectric Hall conductivity $α_{xy}$ in the three-dimensional Dirac semimetal ZrTe$_5$ acquires a robust plateau in the extreme quantum limit of magnetic field. The plateau value

Frederic Barraquand, Olivier Gimenez

Most mechanistic predator-prey modelling has involved either parameterization from process rate data or inverse modelling. Here, we take a median road: we aim at identifying the potential benefits of combining datasets, when both population growth and predation processes are viewed as stochastic. We fit a discrete-time, stochastic predator-prey model of the

Jianbo Chen, Michael I. Jordan, Martin J. Wainwright

The goal of a decision-based adversarial attack on a trained model is to generate adversarial examples based solely on observing output labels returned by the targeted model. We develop HopSkipJumpAttack, a family of algorithms based on a novel estimate of the gradient direction using binary information at the decision boundary. The proposed family includes

Yannick Sire, Susanna Terracini, Stefano Vita

We consider a class of equations in divergence form with a singular/degenerate weight $$-\mathrm{div}(|y|^a A(x,y)\nabla u)=|y|^a f(x,y)\; \quad\textrm{or} \ \textrm{div}(|y|^aF(x,y))\;.$$ Under suitable regularity assumptions for the matrix $A$ and $f$ (resp. $F$) we prove Hölder continuity of solutions which are even in $y\in\mathbb{R}$, and possibly of th

Andrew Drozdov, Pat Verga, Mohit Yadav, Mohit Iyyer

We introduce deep inside-outside recursive autoencoders (DIORA), a fully-unsupervised method for discovering syntax that simultaneously learns representations for constituents within the induced tree. Our approach predicts each word in an input sentence conditioned on the rest of the sentence and uses inside-outside dynamic programming to consider all possib

Yuying Zhu, Guoxin Wang, Börje F. Karlsson

Named entity recognition (NER) in Chinese is essential but difficult because of the lack of natural delimiters. Therefore, Chinese Word Segmentation (CWS) is usually considered as the first step for Chinese NER. However, models based on word-level embeddings and lexicon features often suffer from segmentation errors and out-of-vocabulary (OOV) words. In this

Bruno Bertini, Pavel Kos, Tomaz Prosen

We consider a class of quantum lattice models in $1+1$ dimensions represented as local quantum circuits that enjoy a particular "dual-unitarity" property. In essence, this property ensures that both the evolution "in time" and that "in space" are given in terms of unitary transfer matrices. We show that for this class of circuits, gen

Erika M. Holmbeck, Anna Frebel, G. C. McLaughlin, Matthew R. Mumpower

The astrophysical production site of the heaviest elements in the universe remains a mystery. Incorporating heavy element signatures of metal-poor, $r$-process enhanced stars into theoretical studies of $r$-process production can offer crucial constraints on the origin of heavy elements. In this study, we introduce and apply the "Actinide-Dilution with M

Robert L. Jack

We analyse large deviations of the magnetisation in two models of growing clusters. The models have symmetry-breaking transitions, so the typical magnetisation of a growing cluster may be either positive or negative, with equal probability. For large clusters, the magnetisation obeys a large deviation principle. We show that the corresponding rate function i

Nicholas Woolsey, Rong-Rong Chen, Mingyue Ji

We propose capacity-achieving schemes for private information retrieval (PIR) from uncoded databases (DBs) with both homogeneous and heterogeneous storage constraints. In the PIR setting, a user queries a set of DBs to privately download a message, where privacy implies that no one DB can infer which message the user desires. In general, a PIR scheme is comp

Bernard Carr, Sebastien Clesse, Juan García-Bellido

If primordial black holes (PBHs) formed at the quark-hadron epoch, their mass must be close to the Chandrasekhar limit, this also being the characteristic mass of stars. If they provide the dark matter (DM), the collapse fraction must be of order the cosmological baryon-to-photon ratio $\sim 10^{-9}$, which suggests a scenario in which a baryon asymmetry is

Gerard Awanou

We consider mesh functions which are discrete convex in the sense that their central second order directional derivatives are positive. Analogous to the case of a uniformly bounded sequence of convex functions, we prove that the uniform limit on compact subsets of discrete convex mesh functions which are uniformly bounded is a continuous convex function. Fur

Zhaohuan Zhu, Shangjia Zhang, Yan-Fei Jiang, Akimasa Kataoka

ALMA surveys have suggested that the dust in Class II disks may not be enough to explain the averaged solid mass in exoplanets, under the assumption that the mm disk continuum emission is optically thin. This optically thin assumption seems to be supported by recent DSHARP observations where the measured optical depths of spatially resolved disks are mostly

V. M. Kalari, J. S. Vink, W. de Wit, N. J. Bastian

The formation of the most massive stars in the Universe remains an unsolved problem. Are they able to form in relative isolation in a manner similar to the formation of solar-type stars, or do they necessarily require a clustered environment? In order to shed light on this important question, we study the origin of two very massive stars (VMS): the O2.5If*/W

André de Oliveira Gomes, Michael A. Högele

We establish Freidlin-Wentzell results for a nonlinear ordinary differential equation starting close to the stable state $0$, say, subject to a perturbation by a stochastic integral which is driven by an $\varepsilon$-small and $(1/\varepsilon)$-accelerated Lévy process with exponentially light jumps. For this purpose we derive a large deviations principle f

Prasad Jayanti, Siddhartha Jayanti, Anup Joshi

In light of recent advances in non-volatile main memory technology, Golab and Ramaraju reformulated the traditional mutex problem into the novel {\em Recoverable Mutual Exclusion} (RME) problem. In the best known solution for RME, due to Golab and Hendler from PODC 2017, a process incurs at most $O(\frac{\log n}{\log \log n})$ remote memory references (RMRs)

Kathlén Kohn, Kristian Ranestad

We show that there is a unique hypersurface of minimal degree passing through the non-faces of a polytope which is defined by a simple hyperplane arrangement. This generalizes the construction of the adjoint curve of a polygon by Wachspress in 1975. The defining polynomial of our adjoint hypersurface is the adjoint polynomial introduced by Warren in 1996. Th

Karl Däubel

The Ring Loading Problem emerged in the 1990s to model an important special case of telecommunication networks (SONET rings) which gained attention from practitioners and theorists alike. Given an undirected cycle on $n$ nodes together with non-negative demands between any pair of nodes, the Ring Loading Problem asks for an unsplittable routing of the demand

Leon Balents, Oleg A. Starykh

We study the transverse dynamical spin susceptibility of the two dimensional U(1) spinon Fermi surface spin liquid in a small applied Zeeman field. We show that both short-range interactions, present in a generic Fermi liquid, as well as gauge fluctuations, characteristic of the U(1) spin liquid, qualitatively change the result based on the frequently assume

Toshiya Namikawa, Yuji Chinone, Hironao Miyatake, Masamune Oguri

We present the first measurement of cross-correlation between the lensing potential, reconstructed from cosmic microwave background (CMB) {\it polarization} data, and the cosmic shear field from galaxy shapes. This measurement is made using data from the POLARBEAR CMB experiment and the Subaru Hyper Suprime-Cam (HSC) survey. By analyzing an 11~deg$^2$ overla

Toshiya Namikawa, Shohei Saga, Daisuke Yamauchi, Atsushi Taruya

We present robust constraints on the stochastic gravitational waves (GWs) at Mpc scales from the cosmic microwave background (CMB) data. CMB constraints on GWs are usually characterized as the tensor-to-scalar ratio, assuming specifically a power-law form of the primordial spectrum, and are obtained from the angular spectra of CMB. Here, we relax the assumpt

Dennise García-Beltrán, Óscar Guajardo

The purpose of this work is to study Lie superalgebroid structures on the space of superdifferential $1$-forms over the supermanifolds whose superfunctions are the differential forms on its underlying manifold. These superalgbroids are constructed from graded Poisson structures defined on the latter superalgebra.

D. S. Akerib, C. W. Akerlof, S. K. Alsum, N. Angelides

Deep underground environments are ideal for low background searches due to the attenuation of cosmic rays by passage through the earth. However, they are affected by backgrounds from $γ$-rays emitted by $^{40}$K and the $^{238}$U and $^{232}$Th decay chains in the surrounding rock. The LUX-ZEPLIN (LZ) experiment will search for dark matter particle interacti

Zackory Erickson, Henry M. Clever, Vamsee Gangaram, Greg Turk

Robotic assistance presents an opportunity to benefit the lives of many people with physical disabilities, yet accurately sensing the human body and tracking human motion remain difficult for robots. We present a multidimensional capacitive sensing technique that estimates the local pose of a human limb in real time. A key benefit of this sensing method is t

Raluca Rufu, Oded Aharonson

Current lunar origin scenarios suggest that Earth's Moon may have resulted from the merger of two (or more) smaller moonlets. Dynamical studies of multiple moons find that these satellite systems are not stable, resulting in moonlet collision or loss of one or more of the moonlets. We perform Smoothed Particle Hydrodynamic (SPH) impact simulations of two

Wentong Liao, Cuiling Lan, Wenjun Zeng, Michael Ying Yang

Scene graph generation aims to provide a semantic and structural description of an image, denoting the objects (with nodes) and their relationships (with edges). The best performing works to date are based on exploiting the context surrounding objects or relations,e.g., by passing information among objects. In these approaches, to transform the representatio

Shaon Sahoo, Dayasindhu Dey, Sudip Kumar Saha, Manoranjan Kumar

A Heisenberg spin-$s$ chain with alternating ferromagnetic ($-J_1^F<0$) and antiferromagnetic ($J_1^A>0$) nearest-neighbor (NN) interactions, exhibits the Dimer and spin-$2s$ Haldane phases in the limits $J_1^F/J_1^A \rightarrow 0$ and $J_1^F/J_1^A \rightarrow \infty$ respectively. These two phases are understood to be topologically equivalent. Induction of

Dan Kondratyuk, Milan Straka

We present UDify, a multilingual multi-task model capable of accurately predicting universal part-of-speech, morphological features, lemmas, and dependency trees simultaneously for all 124 Universal Dependencies treebanks across 75 languages. By leveraging a multilingual BERT self-attention model pretrained on 104 languages, we found that fine-tuning it on a

Linying Zhang, Yixin Wang, Anna Ostropolets, Jami J. Mulgrave

The treatment effects of medications play a key role in guiding medical prescriptions. They are usually assessed with randomized controlled trials (RCTs), which are expensive. Recently, large-scale electronic health records (EHRs) have become available, opening up new opportunities for more cost-effective assessments. However, assessing a treatment effect fr

Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber, François Petitjean

Over the past one hundred years, the classic teaching methodology of &#34;see one, do one, teach one&#34; has governed the surgical education systems worldwide. With the advent of Operation Room 2.0, recording video, kinematic and many other types of data during the surgery became an easy task, thus allowing artificial intelligence systems to be deployed and

Katsuhiko Yamamoto, Toshio Irino, Shoko Araki, Keisuke Kinoshita

In this study, we propose a new concept, the gammachirp envelope distortion index (GEDI), based on the signal-to-distortion ratio in the auditory envelope, SDRenv to predict the intelligibility of speech enhanced by nonlinear algorithms. The objective of GEDI is to calculate the distortion between enhanced and clean-speech representations in the domain of a

Muhammad Ali, Piotr Sapiezynski, Miranda Bogen, Aleksandra Korolova

The enormous financial success of online advertising platforms is partially due to the precise targeting features they offer. Although researchers and journalists have found many ways that advertisers can target---or exclude---particular groups of users seeing their ads, comparatively little attention has been paid to the implications of the platform&#39;s a

C. Giunti

We consider a scenario with unitary mixing of the three light standard neutrinos and a non-unitary mixing contribution of a heavier massive neutrino that can generate short-baseline neutrino oscillations. We show that this scenario predicts constant flavor-changing probabilities at short-baseline distances. Therefore, it cannot explain the spectral distortio

Amit Chakraborty, Sung Hak Lim, Mihoko M. Nojiri

Classification of jets with deep learning has gained significant attention in recent times. However, the performance of deep neural networks is often achieved at the cost of interpretability. Here we propose an interpretable network trained on the jet spectrum $S_{2}(R)$ which is a two-point correlation function of the jet constituents. The spectrum can be d

Babette Döbrich, Joerg Jaeckel, Tommaso Spadaro

The exploration of long-lived particles in the MeV-GeV region is a formidable task but it may provide us a unique access to dark sectors. Fixed-target facilities with sufficiently energetic and intense proton beams are an ideal tool for this challenge. In this work we show that the production rate of Axion-Like-Particles (ALPs) coupled pre-dominantly to phot

Tobe Deprez

We study class $\mathcal S$ for locally compact groups. We characterize locally compact groups in this class as groups having an amenable action on a boundary that is small at infinity, generalizing a theorem of Ozawa. Using this characterization, we provide new examples of groups in class $\mathcal S$ and prove unique prime factorization results for group v

Wei He

We study a relation between asymptotic spectra of the quantum mechanics problem with a four components elliptic function potential, the Darboux-Treibich-Verdier (DTV) potential, and the Omega background deformed N=2 supersymmetric SU(2) QCD models with four massive flavors in the Nekrasov-Shatashvili limit. The weak coupling spectral solution of the DTV pote

Santiago Estrada, Ran Lu, Sailesh Conjeti, Ximena Orozco-Ruiz

Purpose: Development of a fast and fully automated deep learning pipeline (FatSegNet) to accurately identify, segment, and quantify abdominal adipose tissue on Dixon MRI from the Rhineland Study - a large prospective population-based study. Method: FatSegNet is composed of three stages: (i) consistent localization of the abdominal region using two 2D-Competi

Giovanni S. Alberti, Yves Capdeboscq

This paper addresses enforcing non-vanishing constraints for solutions to a second order elliptic partial differential equation by appropriate choices of boundary conditions. We show that, in dimension $d\geq2$, under suitable regularity assumptions, the family of $2d$ solutions such that their Jacobian has maximal rank in the domain is both open and dense.

Steven Holtzen, Todd Millstein, Guy Van den Broeck

The computational burden of probabilistic inference remains a hurdle for applying probabilistic programming languages to practical problems of interest. In this work, we provide a semantic and algorithmic foundation for efficient exact inference on discrete-valued finite-domain imperative probabilistic programs. We leverage and generalize efficient inference

Peng-Cheng Lin, Wan-Lei Zhao

Recently, graph based nearest neighbor search gets more and more popular on large-scale retrieval tasks. The attractiveness of this type of approaches lies in its superior performance over most of the known nearest neighbor search approaches as well as its genericness to various metrics. In this paper, the role of two strategies, namely hierarchical structur

Ankurjyoti Chutia, Azizul Hoque, Jyotishman Kalita

We produce two families of rank zero quadratic twists of the Mordell curve $y^2=x^3+2$. At the end, we give numerical examples supporting the result.

Fabio Botelho

This article develops a new primal dual formulation for the Kirchhoff-Love non-linear plate model. At first we establish a duality principle which includes sufficient conditions of global optimality through the dual formulation. At this point we highlight this first duality principle is specially suitable for the case in which the membrane stress tensor is n

Alexandre Barreira, Dylan Nelson, Annalisa Pillepich, Volker Springel

We measure power spectrum response functions in the presence of baryonic physical processes using separate universe simulations with the IllustrisTNG galaxy formation model. The response functions describe how the small-scale power spectrum reacts to long-wavelength perturbations and they can be efficiently measured with the separate universe technique by ab

Manuel Friedrich, Martin Kružík, Jan Valdman

We consider metric gradient flows and their discretizations in time and space. We prove an abstract convergence result for time-space discretizations and identify their limits as curves of maximal slope. As an application, we consider a finite element approximation of a quasistatic evolution for viscoelastic von Kármán plates. Computational experiments are p

B. Soret, P. Popovski, K. Stern

One of the main novelties in 5G is the flexible Time Division Duplex (TDD) frame, which allows adaptation to the latency requirements. However, this flexibility is not sufficient to support heterogeneous latency requirements, in which different traffic instances have different switching requirements between Uplink (UL) and Downlink (DL). This is visible in a

Bing-Dong Wan, Cong-Feng Qiao

By studying the $η_c$ exclusive decay to double glueballs, we introduce a model to mimic phenomenologically the gluon-pair-vacuum interaction vertices, namely the $0^{++}$ model. Based on this model, we study glueball production in pseudoscalar quarkonium decays, explicitly $η_c \to f_0(1500)η(1405)$, $η_b\to f_0(1500)η(1405)$ and $η_b\to f_0(1710)η(1405)$ p

Jeremias Knoblauch, Jack Jewson, Theodoros Damoulas

We advocate an optimization-centric view on and introduce a novel generalization of Bayesian inference. Our inspiration is the representation of Bayes&#39; rule as infinite-dimensional optimization problem (Csiszar, 1975; Donsker and Varadhan; 1975, Zellner; 1988). First, we use it to prove an optimality result of standard Variational Inference (VI): Under t