November 2020 arXiv papers — page 37

Manuel Garcia-Vara, Kaidi Hu, Cristina Postigo, Lluc Olmo

Bentazone, an herbicide widely applied in rice and cereal crops, is widespread in the aquatic environment. This study evaluated the capacity of Trametes versicolor to remove bentazone from water. The fungus was able to completely remove bentazone after three days at Erlenmeyer-scale incubation. Both laccase and cytochrome P450 enzymatic systems were involved

Michael F. Bietenholz, N. Bartel, M. Argo, R. Dua

We assemble a large set of 2-10 GHz radio flux density measurements and upper limits of 294 different supernovae (SNe), from the literature and our own and archival data. Only 31% of the SNe were detected. We characterize the SN lightcurves near the peak using a two-parameter model, with $t_{\rm pk}$ being the time to rise to a peak and $L_{\rm pk}$ the spec

Rassa Ghavami Modegh, Mehrab Hamidi, Saeed Masoudian, Amir Mohseni

COVID-19 is a virus with high transmission rate that demands rapid identification of the infected patients to reduce the spread of the disease. The current gold-standard test, Reverse-Transcription Polymerase Chain Reaction (RT-PCR), has a high rate of false negatives. Diagnosing from CT-scan images as a more accurate alternative has the challenge of disting

Varnith Chordia, Vijay Kumar BG

Accurate and efficient product classification is significant for E-commerce applications, as it enables various downstream tasks such as recommendation, retrieval, and pricing. Items often contain textual and visual information, and utilizing both modalities usually outperforms classification utilizing either mode alone. In this paper we describe our methodo

Felix Richards, Adeline Paiement, Xianghua Xie, Elisabeth Sola

Robustness to transformation is desirable in many computer vision tasks, given that input data often exhibits pose variance. While translation invariance and equivariance is a documented phenomenon of CNNs, sensitivity to other transformations is typically encouraged through data augmentation. We investigate the modulation of complex valued convolutional wei

D. G. Whelan, S. D. Chojnowski, J. Labadie-Bartz, J. Daglen

Prompted by X-ray detections from multiple surveys, we investigated the A-type star HD 63021 and found that it is a double-lined spectroscopic binary with highly variable emission associated with the primary star. Analysis of our multi-epoch spectroscopic observations, the majority of which were carried out on small aperture telescopes, indicates a very shor

Abdelghani Maddi, Yves Gingras

The aim of this paper is twofold:1)contribute to a better understanding of the place of women in Economics and Management disciplines by characterizing the difference in levels of scientific collaboration between men and women at the specialties level;2) Investigate the relationship between gender diversity and citation impact in Economics and Management. Ou

Boris Babenko, Akinori Mitani, Ilana Traynis, Naho Kitade

Diabetes-related retinal conditions can be detected by examining the posterior of the eye. By contrast, examining the anterior of the eye can reveal conditions affecting the front of the eye, such as changes to the eyelids, cornea, or crystalline lens. In this work, we studied whether external photographs of the front of the eye can reveal insights into both

Mahmoud Afifi, Marcus A. Brubaker, Michael S. Brown

While generative adversarial networks (GANs) can successfully produce high-quality images, they can be challenging to control. Simplifying GAN-based image generation is critical for their adoption in graphic design and artistic work. This goal has led to significant interest in methods that can intuitively control the appearance of images generated by GANs.

Tong Ke, Kejian J. Wu, Stergios I. Roumeliotis

In this paper, we present the RISE-SLAM algorithm for performing visual-inertial simultaneous localization and mapping (SLAM), while improving estimation consistency. Specifically, in order to achieve real-time operation, existing approaches often assume previously-estimated states to be perfectly known, which leads to inconsistent estimates. Instead, based

Abhijeet Melkani, S. J. van Enk

We consider the quantum theory of paraxial non-relativistic electron beams in non-uniform magnetic fields, such as the Glaser field. We find the wave function of an electron from such a beam and show that it is a joint eigenstate of two ($z$-dependent) commuting gauge-independent operators. This generalized Laguerre-Gaussian vortex beam has a phase that is s

Carlos Mauricio Villegas Burgos, Tianqi Yang, Nick Vamivakas, Yuhao Zhu

Deep learning using Convolutional Neural Networks (CNNs) has been shown to significantly out-performed many conventional vision algorithms. Despite efforts to increase the CNN efficiency both algorithmically and with specialized hardware, deep learning remains difficult to deploy in resource-constrained environments. In this paper, we propose an end-to-end f

Alex Samuel Bamunoba, Jonas Bergström

Let $q$ be a power of a prime number $p$, $\mathbb F_q$ be a finite field with $q$ elements and $\mathcal{G}$ be a subgroup of $(\mathbb F_q,+)$ of order $p$. We give an existence criterion and an algorithm for computing maximally $\mathcal{G}$-fixed c-Wieferich primes in $\mathbb F_q[T]$. Using the criterion, we study how c-Wieferich primes behave in $\math

A. Armatol, E. Armengaud, W. Armstrong, C. Augier

Precise characterization of detector time resolution is of crucial importance for next-generation cryogenic-bolometer experiments searching for neutrinoless double-beta decay, such as CUPID, in order to reject background due to pile-up of two-neutrino double-beta decay events. In this paper, we describe a technique developed to study the pile-up rejection ca

Jinho Choi

In this paper, for efficient data collection with limited bandwidth, data-aided sensing is applied to Gaussian process regression that is used to learn data sets collected from sensors in Internet-of-Things systems. We focus on the interpolation of sensors' measurements from a small number of measurements uploaded by a fraction of sensors using Gaussian proc

Seong Hun Lee, Javier Civera

We propose a novel method for estimating the global rotations of the cameras independently of their positions and the scene structure. When two calibrated cameras observe five or more of the same points, their relative rotation can be recovered independently of the translation. We extend this idea to multiple views, thereby decoupling the rotation estimation

Yan Liu, Yansha Deng, Maged Elkashlan, Arumugam Nallanathan

NarrowBand-Internet of Things (NB-IoT) is a new 3GPP radio access technology designed to provide better coverage for a massive number of low-throughput low-cost devices in delay-tolerant applications with low power consumption. To provide reliable connections with extended coverage, a repetition transmission scheme is introduced to NB-IoT during both Random

Deepali Jain, Atil Iscen, Ken Caluwaerts

Legged robots navigating crowded scenes and complex terrains in the real world are required to execute dynamic leg movements while processing visual input for obstacle avoidance and path planning. We show that a quadruped robot can acquire both of these skills by means of hierarchical reinforcement learning (HRL). By virtue of their hierarchical structure, o

Maximilian Filtenborg, Efstratios Gavves, Deepak Gupta

Classically, visual object tracking involves following a target object throughout a given video, and it provides us the motion trajectory of the object. However, for many practical applications, this output is often insufficient since additional semantic information is required to act on the video material. Example applications of this are surveillance and t

Hong-Yi Zhang

Many scalar field theories with attractive self-interactions support exceptionally long-lived, spatially localized and time-periodic field configurations called oscillons. A detailed study of their longevity is important for understanding their applications in cosmology. In this paper, we study gravitational effects on the decay rate and lifetime of dense os

Andrew Farley

New equations are derived which describe the evolution in curved spacetime of null geodesics with non-zero (complex) shear $\sigma$ and twist $\omega$ rates resembling Grishchuk's squeezed states evolution equations from inflationary cosmology. A ``squeeze" angle $\phi$ (obtained from the direction of the major axis of the elliptical cross section of the con

Abel Díaz Berenguer, Hichem Sahli, Boris Joukovsky, Maryna Kvasnytsia

Our motivating application is a real-world problem: COVID-19 classification from CT imaging, for which we present an explainable Deep Learning approach based on a semi-supervised classification pipeline that employs variational autoencoders to extract efficient feature embedding. We have optimized the architecture of two different networks for CT images: (i)

Cezar Lupu

In this paper, we give an elementary account into Zagier's formula for multiple zeta values involving Hoffman elements. Our approach allows us to obtain direct proof in a special case via rational zeta series involving the coefficient $\zeta(2n)$. This formula plays an important role in proving Hoffman's conjecture which asserts that every multiple zeta valu

Laura Natali, Saga Helgadottir, Onofrio M. Marago, Giovanni Volpe

Containment of epidemic outbreaks entails great societal and economic costs. Cost-effective containment strategies rely on efficiently identifying infected individuals, making the best possible use of the available testing resources. Therefore, quickly identifying the optimal testing strategy is of critical importance. Here, we demonstrate that machine learn

Pingakshya Goswami, Dinesh Bhatia

Floorplanning problem has been extensively explored for homogeneous FPGAs. Most modern FPGAs consist of heterogeneous resources in the form of configurable logic blocks, DSP blocks, BRAMs and more. Very little work has been done for heterogeneous FPGAs. In addition, features like partial reconfigurability allow on-the-fly changes to the executable design tha

Chao-Han Huck Yang, Linda Liu, Ankur Gandhe, Yile Gu

End-to-end automatic speech recognition (ASR) systems are increasingly popular due to their relative architectural simplicity and competitive performance. However, even though the average accuracy of these systems may be high, the performance on rare content words often lags behind hybrid ASR systems. To address this problem, second-pass rescoring is often a

Peter M. Higgins, Alexei Vernitski

We characterize the respective semigroups of mappings that preserve, or that preserve or reverse orientation of a finite cycle, in terms of their actions on oriented triples and oriented quadruples. This leads to a proof that the latter semigroup coincides with the semigroup of all mappings that preserve intersections of chords on the corresponding circle.

Fuchang Gao, Boyu Zhang

Despite broad interest in applying deep learning techniques to scientific discovery, learning interpretable formulas that accurately describe scientific data is very challenging because of the vast landscape of possible functions and the "black box" nature of deep neural networks. The key to success is to effectively integrate existing knowledge or hypothese

Jernej Vivod

The increasing adoption of technology to augment or even replace traditional face-to-face learning has led to the development of a myriad of tools and platforms aimed at engaging the students and facilitating the teacher's ability to present new information. The IMapBook project aims at improving the literacy and reading comprehension skills of elementary sc

Chavit Denninnart

Cloud-based serverless computing systems, either public or privately provisioned, aim to provide the illusion of infinite resources and abstract users from details of the allocation decisions. With the goal of providing a low cost and a high QoS, the serverless computing paradigm offers opportunities that can be harnessed to attain the goals. Specifically, o

Elena Kreutzer, Walter M. Senn, Mihai A. Petrovici

In many normative theories of synaptic plasticity, weight updates implicitly depend on the chosen parametrization of the weights. This problem relates, for example, to neuronal morphology: synapses which are functionally equivalent in terms of their impact on somatic firing can differ substantially in spine size due to their different positions along the den

Mariana Mendes Guimarães, Flávio Vinícius Cruzeiro Martins, Rodrigo Ferreira da Silva

This work presents the facility location problem for maximum coverage in an emergency medical service called SAMU-BH, located in Belo Horizonte, Minas Gerais, Brazil. The purpose of the proposed model is to find the best locations for its ambulances in order to provide faster in-site assistance whenever necessary. First, it develops a mono-objective model to

Aditya Hebbar, Denis Karateev, Joao Penedones

We review unitarity and crossing constraints on scattering amplitudes for particles with spin in four dimensional quantum field theories. As an application we study two to two scattering of neutral spin 1/2 fermions in detail. Assuming Mandelstam analyticity of its scattering amplitude, we use the numerical S-matrix bootstrap method to estimate various non-p

Bram Bekker, Maarten Solleveld

Buildings are beautiful mathematical objects tying a variety of subjects in algebra and geometry together in a very direct sense. They form a natural bridge to visualising more complex principles in group theory. As such they provide an opportunity to talk about the inner workings of mathematics to a broader audience, but the visualisations could also serve

Hossein Jowhari

In this paper, we present a new simple degree-based estimator for the size of maximum matching in bounded arboricity graphs. When the arboricity of the graph is bounded by $\alpha$, the estimator gives a $\alpha+2$ factor approximation of the matching size. For planar graphs, we show the estimator does better and returns a $3.5$ approximation of the matching

Alexandra Puchko, Robert Link, Brian Hutchinson, Ben Kravitz

Earth system models (ESMs), which simulate the physics and chemistry of the global atmosphere, land, and ocean, are often used to generate future projections of climate change scenarios. These models are far too computationally intensive to run repeatedly, but limited sets of runs are insufficient for some important applications, like adequately sampling dis

Xiumin Shang, Ahmed Sabbir Arif, Marcelo Kallmann

In this paper we address feedback strategies for an autonomous virtual trainer. First, a pilot study was conducted to identify and specify feedback strategies for assisting participants in performing a given task. The task involved sorting virtual cubes according to areas of countries displayed on them. Two feedback strategies were specified. The first provi

Patricia Pauli, Johannes Köhler, Julian Berberich, Anne Koch

In this paper, we present a method to analyze local and global stability in offset-free setpoint tracking using neural network controllers and we provide ellipsoidal inner approximations of the corresponding region of attraction. We consider a feedback interconnection of a linear plant in connection with a neural network controller and an integrator, which a

Owen Bradley, George G. Batrouni, Richard T. Scalettar

The Holstein Hamiltonian describes fermions hopping on a lattice and interacting locally with dispersionless phonon degrees of freedom. In the low density limit, dressed quasiparticles, polarons and bipolarons, propagate with an effective mass. At higher densities, pairs can condense into a low temperature superconducting phase and, at or near commensurate f

Louis Rowen, Yoav Segev

``Fusion rules'' are laws of multiplication among eigenspaces of an idempotent. We establish fusion rules for flexible power-associative algebras, following Albert. We define the notion of an axis in the noncommutative setting (compare with [HRS]) and accumulate information about pairs of axes. We also describe a class of noncommutative examples of flexible

O. R. Blanco-Garcia, A. Ciarma

The production of an intense, high energy and low emittance muon beam is interesting for a possible muon collider. The Low EMittance Muon Accelerator (LEMMA) team at the Istituto Nazionale di Fisica Nucleare (INFN), in Italy, is studying the production of a 22.5 GeV low emittance muon beam from a high energy positron beam at twice the muon energy impinging o

Valeri P. Frolov

We consider a nonlocal theory of a scalar massive field in a flat spacetime background in the presence of an external potential and construct WKB solutions for this theory. We use a model in which the kinetic part of the scalar field action is modified by changing $\Box$ to $\Box f(\Box)$ operator. We discuss conditions when the corresponding form factor $f$

Rui Shu, Tianpei Xia, Laurie Williams, Tim Menzies

Background: Machine learning-based security detection models have become prevalent in modern malware and intrusion detection systems. However, previous studies show that such models are susceptible to adversarial evasion attacks. In this type of attack, inputs (i.e., adversarial examples) are specially crafted by intelligent malicious adversaries, with the a

Yuxiang Guo, Jinhong Wang, Yu Liang, Xiong Xiao

We present the second prototype of a time-to-digital (TDC) ASIC for the upgrade of the ATLAS Monitored Drift Tube (MDT) detector for High-Luminosity LHC operations. Compared to the first prototype, triple modular redundancy has been implemented for the configuration and flow control logic. The total power consumption is increased by less than 10 mW while ach

Elisabeth R. Adams, Brian Jackson, Samantha Johnson, David R. Ciardi

Using the EVEREST photometry pipeline, we have identified 74 candidate ultra-short-period planets (orbital period P<1 d) in the first half of the K2 data (Campaigns 0-8 and 10). Of these, 33 candidates have not previously been reported. A systematic search for additional transiting planets found 13 new multi-planet systems, doubling the number known and repr

John Berge

If R is a nonseparating simple closed curve on the boundary of a genus two handlebody H and H[R] has incompressible boundary, then there exists a unique arc omega in bdry(H), meeting R only in its endpoints, such that, omega is isotopic in bdry(H), keeping its endpoints on R, to a nontrivial wave based at R in each Heegaard diagram of R on bdry(H) which has

Huang Huang, Marcus Dominguez-Kuhne, Jeffrey Ichnowski, Vishal Satish

Efficiently finding an occluded object with lateral access arises in many contexts such as warehouses, retail, healthcare, shipping, and homes. We introduce LAX-RAY (Lateral Access maXimal Reduction of occupancY support Area), a system to automate the mechanical search for occluded objects on shelves. For such lateral access environments, LAX-RAY couples a p

Anant V. Nori, Rahul Bera, Shankar Balachandran, Joydeep Rakshit

Deep Neural Network (DNN) inference is emerging as the fundamental bedrock for a multitude of utilities and services. CPUs continue to scale up their raw compute capabilities for DNN inference along with mature high performance libraries to extract optimal performance. While general purpose CPUs offer unique attractive advantages for DNN inference at both da

Lakmal Meegahapola, Salvador Ruiz-Correa, Daniel Gatica-Perez

Understanding food consumption patterns and contexts using mobile sensing is fundamental to build mobile health applications that require minimal user interaction to generate mobile food diaries. Many available mobile food diaries, both commercial and in research, heavily rely on self-reports, and this dependency limits the long term adoption of these apps b

Rika Antonova, Anastasiia Varava, Peiyang Shi, J. Frederico Carvalho

Deformable objects present a formidable challenge for robotic manipulation due to the lack of canonical low-dimensional representations and the difficulty of capturing, predicting, and controlling such objects. We construct compact topological representations to capture the state of highly deformable objects that are topologically nontrivial. We develop an a

Vaibhav Kumar, Barry Cardiff, Mark F Flanagan

Non-orthogonal multiple access (NOMA) is being widely considered as a potential candidate to enhance the spectrum utilization in beyond fifth-generation (B5G) communications. In this paper, we derive closed-form expressions for the ergodic rate and outage probability of a multiple-antenna-assisted NOMA-based cooperative relaying system (CRS-NOMA). We present

Connor Gibbs, Ryan Elmore, Bailey Fosdick

In the summer of 2017, the National Basketball Association reduced the number of total timeouts, along with other rule changes, to regulate the flow of the game. With these rule changes, it becomes increasingly important for coaches to effectively manage their timeouts. Understanding the utility of a timeout under various game scenarios, e.g., during an oppo

Fabijan Pavošević, Sharon Hammes-Schiffer

Automatic differentiation is a tool for numerically calculating derivatives of a given function up to machine precision. This tool is useful for quantum chemistry methods, which require the calculation of gradients either for the minimization of the energy with respect to wave function parameters or for the calculation of molecular responses to external pert

Oliver Tough, James Nolen

The Fleming-Viot particle system consists of $N$ identical particles diffusing in a domain $U \subset \mathbb{R}^d$. Whenever a particle hits the boundary $\partial U$, that particle jumps onto another particle in the interior. It is known that this system provides a particle representation for both the Quasi-Stationary Distribution (QSD) and the distributio

Zijian An, Kenneth Joseph

Donald Trump has tweeted thousands of times during his presidency. These public statements are an increasingly important way through which Trump communicates his political and personal views. A better understanding of the way the American public consumes and responds to these tweets is therefore critical. In the present work, we address both consumption of a

Michael D. Higgins, Chris H. Greene, Alejandro Kievsky, Michele Viviani

This work presents further analysis of the three- and four-neutron systems in the low energy regime using adiabatic hyperspherical methods. In our previous Phys. Rev. Lett. article (Phys. Rev. Lett. 125, 052501 (2020)), the low-energy behavior of these neutron systems was treated in the adiabatic approximation, neglecting the off-diagonal non-adiabatic coupl

Veronica Dexheimer, Krishna Aryal, Madison Wolf, Constantinos Constantinou

In this work, we investigate how the assumption of chemical equilibrium with leptons affects the deconfinement phase transition to quark matter. This is done within the framework of the Chiral Mean Field model (CMF) allowing for non-zero net strangeness, corresponding to the conditions found in astrophysical scenarios. We build 3-dimensional QCD phase diagra

Ovidiu Daescu, Ka Yaw Teo

Consider an input consisting of a set of $n$ disjoint triangular obstacles in $\mathbb{R}^3$ and a target point $t$ in the free space, all enclosed by a large sphere $S$ of radius $R$ centered at $t$. An articulated probe is modeled as two line segments $ab$ and $bc$ connected at point $b$. The length of $ab$ can be equal to or greater than $R$, while $bc$ i

Helmer H. Koppelman, Amina Helmi

When a subhalo interacts with a cold stellar stream it perturbs its otherwise nearly smooth distribution of stars, and this leads to the creation of a gap. The properties of such gaps depend on the parameters of the interaction. Their characterisation could thus lead to the determination of the mass spectrum of the perturbers and possibly reveal the existenc

Miroslav Bulíček, Victoria Patel, Yasemin Şengül, Endre Süli

We consider a system of evolutionary equations that is capable of describing certain viscoelastic effects in linearized yet nonlinear models of solid mechanics. The essence of the paper is that the constitutive relation, involving the Cauchy stress, the small strain tensor and the symmetric velocity gradient, is given in an implicit form. For a large class o

Zhaoyue Chen, Nick Koudas, Zhe Zhang, Xiaohui Yu

Machine Learning (ML) applications are proliferating in the enterprise. Relational data which are prevalent in enterprise applications are typically normalized; as a result, data has to be denormalized via primary/foreign-key joins to be provided as input to ML algorithms. In this paper, we study the implementation of popular nonlinear ML models, Gaussian Mi

Javiera Parada, Jeremy Heyl, Harvey Richer, Paul Ripoche

We introduce a new distance determination method using carbon-rich asymptotic giant branch stars (CS) as standard candles and the Large and Small Magellanic Clouds (LMC and SMC) as the fundamental calibrators. We select the samples of CS from the ($(J-K_{s})_0$, $J_0$) colour-magnitude diagrams, as, in this combination of filters, CS are bright and easy to i

J. M. Diederik Kruijssen, Steven N. Longmore, Mélanie Chevance

Extrasolar planets with sizes between that of the Earth and Neptune ($R_{\rm p}=1{-}4~{\rm R}_\oplus$) have a bimodal radius distribution. This 'planet radius valley' separates compact, rocky super-Earths ($R_{\rm p}=1.0{-}1.8~{\rm R}_\oplus$) from larger sub-Neptunes ($R_{\rm p}=1.8{-}3.5~{\rm R}_\oplus$) hosting a gaseous hydrogen-helium envelope around th

Matej Petković, Dragi Kocev, Blaž Škrlj, Sašo Džeroski

In this work, we propose two novel (groups of) methods for unsupervised feature ranking and selection. The first group includes feature ranking scores (Genie3 score, RandomForest score) that are computed from ensembles of predictive clustering trees. The second method is URelief, the unsupervised extension of the Relief family of feature ranking algorithms.

Tsung-Yu Hsieh, Suhang Wang, Yiwei Sun, Vasant Honavar

Time series data is prevalent in a wide variety of real-world applications and it calls for trustworthy and explainable models for people to understand and fully trust decisions made by AI solutions. We consider the problem of building explainable classifiers from multi-variate time series data. A key criterion to understand such predictive models involves e

Luis Silvestre

For any $\alpha \in (0,1)$, we construct an example of a solution to a parabolic equation with measurable coefficients in two space dimensions which has an isolated singularity and is not better that $C^\alpha$. We prove that there exists no solution to a fully nonlinear uniformly parabolic equation, in any dimension, which has an isolated singularity where

Erik J. Gustafson, Henry Lamm

Preparing strongly-coupled particle states on quantum computers requires large resources. In this work, we show how classical sampling coupled with projection operators can be used to compute Minkowski matrix elements without explicitly preparing these states on the quantum computer. We demonstrate this for the 2+1d $\mathbb{Z}_2$ lattice gauge theory on sma

M. Perna, S. Arribas, M. Pereira Santaella, L. Colina

Ultraluminous infrared galaxies (ULIRGs) are characterised by extreme starburst (SB) and AGN activity, and are therefore ideal laboratories for studying the outflow phenomena. We have recently started a project called Physics of ULIRGs with MUSE and ALMA (PUMA), which is a survey of 25 nearby (z < 0.165) ULIRGs observed with the integral field spectrograph M

Liang-Chieh Chen, Huiyu Wang, Siyuan Qiao

The Wide Residual Networks (Wide-ResNets), a shallow but wide model variant of the Residual Networks (ResNets) by stacking a small number of residual blocks with large channel sizes, have demonstrated outstanding performance on multiple dense prediction tasks. However, since proposed, the Wide-ResNet architecture has barely evolved over the years. In this wo

Mozhdeh Rouhsedaghat, Yifan Wang, Shuowen Hu, Suya You

A non-parametric low-resolution face recognition model for resource-constrained environments with limited networking and computing is proposed in this work. Such environments often demand a small model capable of being effectively trained on a small number of labeled data samples, with low training complexity, and low-resolution input images. To address thes

Natesh Reddy, Pranaydeep Singh, Muktabh Mayank Srivastava

When performing Polarity Detection for different words in a sentence, we need to look at the words around to understand the sentiment. Massively pretrained language models like BERT can encode not only just the words in a document but also the context around the words along with them. This begs the questions, "Does a pretrain language model also automaticall

Ovidiu Daescu, Ka Yaw Teo

An articulated probe is modeled in the plane as two line segments, $ab$ and $bc$, joined at $b$, with $ab$ being very long, and $bc$ of some small length $r$. We investigate a trajectory planning problem involving the articulated two-segment probe where the length $r$ of $bc$ can be customized. Consider a set $P$ of simple polygonal obstacles with a total of

Ilya Sklyar, Anna Piunova, Yulan Liu

Recent research shows end-to-end ASR systems can recognize overlapped speech from multiple speakers. However, all published works have assumed no latency constraints during inference, which does not hold for most voice assistant interactions. This work focuses on multi-speaker speech recognition based on a recurrent neural network transducer (RNN-T) that has

Steven Chaplick, Petr A. Golovach, Tim A. Hartmann, Dušan Knop

We investigate the parameterized complexity of the recognition problem for the proper $H$-graphs. The $H$-graphs are the intersection graphs of connected subgraphs of a subdivision of a multigraph $H$, and the properness means that the containment relationship between the representations of the vertices is forbidden. The class of $H$-graphs was introduced as

Arturo Rodriguez Fanlo

The aim of this paper is to generalize and improve two of the main model-theoretic results of "Stable group theory and approximate subgroups" by E. Hrushovski to the context of piecewise hyperdefinable sets. The first one is the existence of Lie models. The second one is the stabilizer theorem. In the process, a systematic study of the structure of piecewise

Subhankar Khatua, Sarvesh Srinivasan, R. Ganesh

Magnets with frustration often show accidental degeneracies, characterized by a large classical ground-state space (CGSS). Quantum fluctuations may `select' one of these ground states -- a phenomenon labeled `order by (quantum) disorder' in literature. In this article, we examine the mechanism(s) by which such state selection takes place. We argue that a mag

Yakir Aharonov, Daniel Rohrlich

We revisit the "counterfactual quantum communication" of Salih et al. [1], who claim that an observer "Bob" can send one bit of information to a second observer "Alice" without any physical particle traveling between them. We show that a locally conserved, massless current - specifically, a current of modular angular momentum, $L_z$ mod 2$\hbar$ - carries th

J. I. Katz

Variations of the dispersion (DM) and rotation (RM) measures of FRB 121102 indicate magnetic fields $\sim$ 3--17 mG in the dispersing plasma. The electron density may be $\sim 10^4\,$cm$^{-3}$. The observed time scales $\sim 1$ year constrain the size of the plasma cloud. Increasing DM excludes simple models involving an expanding supernova remnant, and the

Keller VandeBogert

Two ideals $I$ and $J$ are called transverse if $I \cap J = IJ$. We show that the obstructions defined by Avramov for classes of (sequentially) transverse ideals in regular local rings are always $0$. In particular, we compute an explicit free resolution and Koszul homology for all such ideals. Moreover, we construct an explicit trivial Massey operation on t

Frederik Benirschke, Benjamin Dozier, Samuel Grushevsky

For a linear subvariety $M$ of a stratum of meromorphic differentials, we investigate its closure in the multi-scale compactification constructed by Bainbridge-Chen-Gendron-Grushevsky-M\"oller. We prove various restrictions on the type of defining linear equations in period coordinates for $M$ near its boundary, and prove that the closure is locally a toric

Hidenobu Yajima, Makito Abe, Sadegh Khochfar, Kentaro Nagamine

We present results from a new cosmological hydrodynamics simulation campaign of protocluster (PC) regions, FOREVER22: FORmation and EVolution of galaxies in Extremely-overdense Regions motivated by SSA22. The simulations cover a wide range of cosmological scales using three different zoom set-ups in a parent volume of $(714.2~\rm cMpc)^{3}$: PCR (Proto-Clust

Thiago Altair, Larissa M. Sartori, Fabio Rodrigues, Marcio G. B. de Avellar

Certain subterranean environments of Earth have naturally accumulated long-lived radionuclides, such as 238U, 232Th and 40K, near the presence of liquid water. In these natural radioactive environments (NRE), water radiolysis can produce chemical species of biological importance, such as H2. Although the proposal of radioactive decay as an alternative source

K. L. Seyler, A. de la Torre, Z. Porter, E. Zoghlin

An anomalous optical second-harmonic generation (SHG) signal was previously reported in Sr$_2$IrO$_4$ and attributed to a hidden odd-parity bulk magnetic state. Here we investigate the origin of this SHG signal using a combination of bulk magnetic susceptibility, magnetic-field-dependent SHG rotational anisotropy, and overlapping wide-field SHG imaging and a

Roman V. Buniy, Stephen D. H. Hsu

For any choice of initial state and weak assumptions about the Hamiltonian, large isolated quantum systems undergoing Schrodinger evolution spend most of their time in macroscopic superposition states. The result follows from von Neumann's 1929 Quantum Ergodic Theorem. As a specific example, we consider a box containing a solid ball and some gas molecules. R

Florian Tramèr, Dan Boneh

We demonstrate that differentially private machine learning has not yet reached its "AlexNet moment" on many canonical vision tasks: linear models trained on handcrafted features significantly outperform end-to-end deep neural networks for moderate privacy budgets. To exceed the performance of handcrafted features, we show that private learning requires eith

Pierre-Antoine Bernard, Nicolas Crampe, Dounia Shaaban Kabakibo, Luc Vinet

The generic Heun operator of Lie type is identified as a certain $BC$-Gaudin magnet Hamiltonian in a magnetic field. By using the modified algebraic Bethe ansatz introduced to diagonalize such Gaudin models, we obtain the spectrum of the generic Heun operator of Lie type in terms of the Bethe roots of inhomogeneous Bethe equations. We show also that these Be

Camille Eloy

We use exceptional field theory to compute Kaluza-Klein mass spectra around ${\rm AdS_{3}}$ vacua that sit in half-maximal gauged supergravity in three dimensions. The formalism applies to any vacuum that arises from a consistent truncation of higher-dimensional supergravity, no matter what symmetries are preserved. We illustrate its efficiency by computing

Stephan Foldes, Russ Woodroofe

We characterize supersolvable lattices in terms of a certain modular type relation. McNamara and Thomas earlier characterized this class of lattices as those graded lattices having a maximal chain that consists of left-modular elements. Our characterization replaces the condition of gradedness with a second modularity condition on the maximal chain of left-m

Charlotte Ward, Suvi Gezari, Sara Frederick, Erica Hammerstein

A supermassive black hole (SMBH) ejected from the potential well of its host galaxy via gravitational wave recoil carries important information about the mass ratio and spin alignment of the pre-merger SMBH binary. Such a recoiling SMBH may be detectable as an active galactic nucleus (AGN) broad line region offset by up to 10\,kpc from a disturbed host galax

Matteo Fael, Kay Schönwald, Matthias Steinhauser

We compute the relation between the pole mass and the kinetic mass of a heavy quark to three loops. Using the known relation between the pole and the $\overline{\rm MS}$ mass we obtain precise conversion relations between the $\overline{\rm MS}$ and kinetic masses. The kinetic mass is defined via the moments of the spectral function for the scattering involv

David Sutter, Giacomo Nannicini, Tobias Sutter, Stefan Woerner

We present a quantum algorithm to solve dynamic programming problems with convex value functions. For linear discrete-time systems with a $d$-dimensional state space of size $N$, the proposed algorithm outputs a quantum-mechanical representation of the value function in time $O(T \gamma^{dT}\mathrm{polylog}(N,(T/\varepsilon)^{d}))$, where $\varepsilon$ is th

R Krishnan

We classify the constraints on a stationary point of the potential invariant under a finite group into intrinsic and extrinsic based on whether they are independent of the coefficients in the potential or not. We find that the symmetry group of a set of stationary points can be larger than that of the potential and the stabilizer under this group generates i

Mario Herrero-Valea, Raquel Santos-Garcia, Anna Tokareva

We formulate Positivity Bounds for scattering amplitudes including exchange of massless particles. We generalize the standard construction through dispersion relations to include the presence of a branch cut along the real axis in the complex plane for the Maldestam variable $s$. In general, validity of these bounds require the cancellation of divergences in

Arne Heimendahl, Markus Heinrich, David Gross

Stabiliser operations occupy a prominent role in fault-tolerant quantum computing. They are defined operationally: by the use of Clifford gates, Pauli measurements and classical control. These operations can be efficiently simulated on a classical computer, a result which is known as the Gottesman-Knill theorem. However, an additional supply of magic states

Ryunosuke Maeda, Tsuyoshi Inoue, Yasuo Fukui

Young massive clusters (YMCs) are dense aggregates of young stars, which are essential to galaxy evolution, owing to their ultraviolet radiation, stellar winds, and supernovae. The typical mass and radius of YMCs are M~10^4 M_sun and R~1 pc, respectively, indicating that many stars are located in a small region. The formation of YMC precursor clouds may be d

Aliki Litsa, Katherine Freese, Evangelos I. Sfakianakis, Patrick Stengel

We propose a new way of studying the Higgs potential at extremely high energies. The Standard Model (SM) Higgs boson, as a light spectator field during inflation in the early Universe, can acquire large field values from its quantum fluctuations which vary among different causal (Hubble) patches. Such a space dependence of the Higgs after the end of inflatio

Sergio Martin-Alvarez, Harley Katz, Debora Sijacki, Julien Devriendt

Despite their ubiquity, there are many open questions regarding galactic and cosmic magnetic fields. Specifically, current observational constraints cannot rule out if magnetic fields observed in galaxies were generated in the Early Universe or are of astrophysical nature. Motivated by this we use our magnetic tracers algorithm to investigate whether the sig

Philippe Brax, Kunio Kaneta, Yann Mambrini, Mathias Pierre

We generalize dark matter production to a two-metric framework whereby the physical metric, which couples to the Standard Model (SM), is conformally and/or disformally related to the metric governing the gravitational dynamics. We show that this setup is naturally present in many Ultra Violet (UV) constructions, from K\"ahler moduli fields to tensor-portal m

Masha Baryakhtar, Marios Galanis, Robert Lasenby, Olivier Simon

Black hole superradiance is a powerful probe of light, weakly-coupled hidden sector particles. Many candidate particles, such as axions, generically have self-interactions that can influence the evolution of the superradiant instability. As pointed out in arXiv:1604.06422 in the context of a toy model, much of the existing literature on spin-0 superradiance

Sunny Vagnozzi, Abraham Loeb, Michele Moresco

The question of whether Cosmic Microwave Background (CMB) temperature and polarization data from Planck favor a spatially closed Universe with curvature parameter $\Omega_K<0$ has been the subject of recent intense discussions. Attempts to break the geometrical degeneracy combining Planck data with external datasets such as Baryon Acoustic Oscillation (BAO)