October 2020 arXiv papers — page 74

Yuanhao Xiong, Xuanqing Liu, Li-Cheng Lan, Yang You

Many optimizers have been proposed for training deep neural networks, and they often have multiple hyperparameters, which make it tricky to benchmark their performance. In this work, we propose a new benchmarking protocol to evaluate both end-to-end efficiency (training a model from scratch without knowing the best hyperparameter) and data-addition training

Ariel Avital, Klim Efremenko, Aryeh Kontorovich, David Toplin

We propose a non-parametric variant of binary regression, where the hypothesis is regularized to be a Lipschitz function taking a metric space to [0,1] and the loss is logarithmic. This setting presents novel computational and statistical challenges. On the computational front, we derive a novel efficient optimization algorithm based on interior point method

J. G. Gluschke, J. Seidl, H. H. Tan, C. Jagadish

Recent advances in bottom-up growth are giving rise to a range of new two-dimensional nanostructures. Hall effect measurements play an important role in their electrical characterization. However, size constraints can lead to device geometries that deviate significantly from the ideal of elongated Hall bars with currentless contacts. Many devices using these

Amir R. Nafchi, Eric Hamke, Cristina Pereyra, Ramiro Jordan

The Fractional Fourier Transform is a ubiquitous signal processing tool in basic and applied sciences. The Fractional Fourier Transform generalizes every property and application of the Fourier Transform. Despite the practical importance of the discrete fractional Fourier transform, its applications in digital communications have been elusive. The convolutio

J. Y-K. Cho, H. Th. Thrastarson, T. T. Koskinen, P. L. Read

We review the recent progress in understanding the jet structures on exoplanets as well as on and inside the Sun. The emphasis is on the more robust aspects of observation and numerical modeling that relate directly to jets. For the exoplanets, the primary focus is on hot-Jupiters since many more observations are available for them presently than other types

Loïc Toraille, Antoine Hilberer, Thomas Plisson, Margarita Lesik

We report the possibility to simultaneously perform wide-field nitrogen-vacancy (NV) diamond magnetic microscopy and synchrotron X-ray diffraction (XRD) measurements at high pressure. NV color centers are created on the culet of a diamond anvil which is integrated in a diamond anvil cell for static compression of the sample. The optically detected spin reson

R. Michiels, A. C. LaForge, M. Bohlen, C. Callegari

High-intensity extreme ultraviolet (XUV) pulses from a free-electron laser can be used to create a nanoplasma in clusters. In Ref. [Michiels et al. PCCP, 2020; 22: 7828-7834] we investigated the formation of excited states in an XUV-induced nanoplasma in ammonia clusters. In the present article we expand our previous study with a detailed analysis of the nan

Yayun Hu, G. Murthy, S. Rao, J. K. Jain

We develop a density functional treatment of non-interacting abelian anyons, which is capable, in principle, of dealing with a system of a large number of anyons in an external potential. Comparison with exact results for few particles shows that the model captures the behavior qualitatively and semi-quantitatively, especially in the vicinity of the fermioni

Chen Hu, Sha-Sha Li, Wei-Jian Guo, Sen Yang

We report on the results of a new spectroscopic monitoring campaign of the quasar PG 0026+129 at the Calar Alto Observatory 2.2m telescope from July 2017 to February 2020. Significant variations in the fluxes of the continuum and broad-emission lines, including H$β$ and He II, were observed in the first and third years, and clear time lags between them are m

Pengyu Chu, Zhaojian Li, Kyle Lammers, Renfu Lu

Robotic apple harvesting has received much research attention in the past few years due to growing shortage and rising cost in labor. One key enabling technology towards automated harvesting is accurate and robust apple detection, which poses great challenges as a result of the complex orchard environment that involves varying lighting conditions and foliage

Chenoa D. Tremblay, Malcolm D. Gray, Natasha Hurley-Walker, James A. Green

We present new molecular modelling for 14NO and 15NO and a deep, blind molecular line survey at low radio frequencies (99-129 MHz). This survey is the third in a series completed with the Murchison Widefield Array (MWA), but in comparison with the previous surveys, uses four times more data (17 hours vs. 4 hours) and is three times better in angular resoluti

Rahul Mohideen Kaja Mohideen, Pascal Peter, Tobias Alt, Joachim Weickert

Inpainting-based codecs store sparse, quantised pixel data directly and decode by interpolating the discarded image parts. This interpolation can be used simultaneously for efficient coding by predicting pixel data to be stored. Such joint inpainting and prediction approaches yield good results with simple components such as regular grids and Shepard interpo

Theodoros Tsiligkaridis

Reliably assessing model confidence in deep learning and predicting errors likely to be made are key elements in providing safety for model deployment, in particular for applications with dire consequences. In this paper, it is first shown that uncertainty-aware deep Dirichlet neural networks provide an improved separation between the confidence of correct a

Shyam H. Menon, Christoph Federrath, Pamela Klaassen, Rolf Kuiper

The ionizing radiation of massive stars sculpts the surrounding neutral gas into pillar-like structures. Direct signatures of star formation through outflows and jets are observed in these structures, typically at their tips. Recent numerical simulations have suggested that this star formation could potentially be triggered by photoionising radiation, drivin

Behzad Bozorgtabar, Dwarikanath Mahapatra, Guillaume Vray, Jean-Philippe Thiran

Deep anomaly detection models using a supervised mode of learning usually work under a closed set assumption and suffer from overfitting to previously seen rare anomalies at training, which hinders their applicability in a real scenario. In addition, obtaining annotations for X-rays is very time consuming and requires extensive training of radiologists. Henc

Leticia Pardo-Simón

A transcendental entire function is called criniferous if every point in its escaping set can eventually be connected to infinity by a curve of escaping points. Many transcendental entire functions with bounded singular set have this property, and this class has recently attracted much attention in complex dynamics. In the presence of escaping critical value

Sruti Bhagavatula, Lujo Bauer, Apu Kapadia

To protect against misuse of passwords compromised in a breach, consumers should promptly change affected passwords and any similar passwords on other accounts. Ideally, affected companies should strongly encourage this behavior and have mechanisms in place to mitigate harm. In order to make recommendations to companies about how to help their users perform

Hermann Schweizer, Maciej Besta, Torsten Hoefler

Atomic operations (atomics) such as Compare-and-Swap (CAS) or Fetch-and-Add (FAA) are ubiquitous in parallel programming. Yet, performance tradeoffs between these operations and various characteristics of such systems, such as the structure of caches, are unclear and have not been thoroughly analyzed. In this paper we establish an evaluation methodology, dev

Disi Ji, Padhraic Smyth, Mark Steyvers

We investigate the problem of reliably assessing group fairness when labeled examples are few but unlabeled examples are plentiful. We propose a general Bayesian framework that can augment labeled data with unlabeled data to produce more accurate and lower-variance estimates compared to methods based on labeled data alone. Our approach estimates calibrated s

Daniel Mulcahy, Peter Phelan

In this paper we prove two results which further classify smoothness properties of Hilbert schemes of points. This is done by counting classes of arrows on Young diagrams corresponding to monomial ideals, building on the approach taken by Jan Cheah to show smoothness in the 2 dimensional case. We prove sufficient conditions for points to be smooth on Hilbert

Richard A. Battye, Apostolos Pilaftsis, Dominic G. Viatic

The Two Higgs Doublet Model (2HDM) with spontaneously broken $Z_2$ symmetry predicts a production of domain walls at the electroweak scale. We derive cosmological constraints on model parameters for both Type-I and Type-II 2HDMs from the requirement that domain walls do not dominate the Universe by the present day. For Type-I 2HDMs, we deduce the lower bound

Dmitry Medvedev, Alexander D'yakonov

Data distillation is the problem of reducing the volume oftraining data while keeping only the necessary information. With thispaper, we deeper explore the new data distillation algorithm, previouslydesigned for image data. Our experiments with tabular data show thatthe model trained on distilled samples can outperform the model trainedon the original datase

Michael Sven Ferguson, Oded Zilberberg, Gianni Blatter

Steady-state observables, such as occupation numbers and currents, are crucial experimental signatures in open quantum systems. The time-convolutionless (TCL) master equation, which is both exact and time-local, is an ideal candidate for the perturbative computation of such observables. We develop a diagrammatic approach to evaluate the steady-state TCL gene

Ana Paulina Figueroa, Juan José Montellano-Ballesteros, Mika Olsen

We consider the following problem posed by Volkmann in 2007: How close to regular must a c-partite tournament be, to secure a strongly connected subtournament of order $c$? We give sufficient conditions on the regularity of balanced $c$-partite tournaments to assure the existence of strong maximal subtournament with minimum degree at least $\left\lfloor \fra

Hongyang Gao, Yi Liu, Shuiwang Ji

Pooling operations have shown to be effective on computer vision and natural language processing tasks. One challenge of performing pooling operations on graph data is the lack of locality that is not well-defined on graphs. Previous studies used global ranking methods to sample some of the important nodes, but most of them are not able to incorporate graph

Anurag Koul, Varun V. Kumar, Alan Fern, Somdeb Majumdar

Learning and planning with latent space dynamics has been shown to be useful for sample efficiency in model-based reinforcement learning (MBRL) for discrete and continuous control tasks. In particular, recent work, for discrete action spaces, demonstrated the effectiveness of latent-space planning via Monte-Carlo Tree Search (MCTS) for bootstrapping MBRL dur

Daniel T. Payne, Paolo Barone, Lara Benfatto, Fulvio Parmigiani

The complex Fermi surfaces of transition-metal dichalcogenides (TMDCs) challenge the standard Peierls-instability-driven charge-density-wave (CDW) formation. Recently, evidence has been accumulating of a prominent role of ionic thermal fluctuations, which frozen out below $T_{CDW}$ inducing a periodic lattice distortion (PLD). We focus on $2H$-NbSe$_2$, disp

P. S. Athiray, Amy R. Winebarger, Patrick Champey, Ken Kobayashi

The Marshall Grazing Incidence Spectrometer {\it MaGIXS} is a sounding rocket experiment that will observe the soft X-ray spectrum of the Sun from 24 - 6.0 Å (0.5 - 2.0 keV) and is scheduled for launch in 2021. Component and instrument level calibrations for the {\it MaGIXS} instrument are carried out using the X-ray and Cryogenic Facility (XRCF) at NASA Mar

Jason Parker

In a previous paper, the author and his collaborators studied the phenomenon of isotropy in the context of single-sorted equational theories, and showed that the isotropy group of the category of models of any such theory encodes a notion of inner automorphism for the theory. Using results from the treatment of combination problems in term rewriting theory,

Andrew Singletary, Karl Klingebiel, Joseph Bourne, Andrew Browning

Artificial potential fields (APFs) and their variants have been a staple for collision avoidance of mobile robots and manipulators for almost 40 years. Its model-independent nature, ease of implementation, and real-time performance have played a large role in its continued success over the years. Control barrier functions (CBFs), on the other hand, are a mor

Tristan K Truttmann, Fengdeng Liu, Javier Garcia Barriocanal, Richard D. James

SrSnO3 (SSO) is an emerging ultra-wide bandgap (UWBG) semiconductor with potential for highpower applications. In-plane compressive strain was recently shown to stabilize the high temperature tetragonal phase of SSO at room temperature (RT) which exists at T > 1062 K in bulk. Here, we report on the study of strain relaxation in epitaxial, tetragonal phase of

James M. Polson, Cameron G. Hastie

Monte Carlo simulations are used to study the conformational behavior of a semiflexible polymer confined to cylindrical and conical channels. The channels are sufficiently narrow that the conditions for the Odijk regime are marginally satisfied. For cylindrical confinement, we examine polymers with a single knot of topology $3_1$, $4_1$, or $5_1$, as well as

Ali C. Kheirabadi, Ryozo Nagamune

This paper implements a recently developed social hierarchy-based distributed economic model predictive control (DEMPC) algorithm in floating offshore wind farms for the purpose of power maximization. The controller achieves this objective using the concept of yaw and induction-based turbine repositioning (YITuR), which minimizes the overlap areas between ad

Tong Shen, Yuan Liu, Yang Yu, Brenda Rubenstein

Finite temperature auxiliary field-based Quantum Monte Carlo methods, including Determinant Quantum Monte Carlo (DQMC) and Auxiliary Field Quantum Monte Carlo (AFQMC), have historically assumed pivotal roles in the investigation of the finite temperature phase diagrams of a wide variety of multidimensional lattice models and materials. Despite their utility,

Congyu Wu

In this paper we explore previously unidentified connections between relational event model (REM) from the field of network science and inverse reinforcement learning (IRL) from the field of machine learning with respect to their ability to characterize sequences of directed social interaction events in group settings. REM is a conventional approach to tackl

Kuno Kim, Akshat Jindal, Yang Song, Jiaming Song

We propose a new framework for Imitation Learning (IL) via density estimation of the expert's occupancy measure followed by Maximum Occupancy Entropy Reinforcement Learning (RL) using the density as a reward. Our approach maximizes a non-adversarial model-free RL objective that provably lower bounds reverse Kullback-Leibler divergence between occupancy m

Congyu Wu, Amanda N. Barczyk, R. Cameron Craddock, Gabriella M. Harari

Loneliness is a widely affecting mental health symptom and can be mediated by and co-vary with patterns of social exposure. Using momentary survey and smartphone sensing data collected from 129 Android-using college student participants over three weeks, we (1) investigate and uncover the relations between momentary loneliness experience and companionship ty

Michael Lutter, Johannes Silberbauer, Joe Watson, Jan Peters

In this work, we examine a spectrum of hybrid model for the domain of multi-body robot dynamics. We motivate a computation graph architecture that embodies the Newton Euler equations, emphasizing the utility of the Lie Algebra form in translating the dynamical geometry into an efficient computational structure for learning. We describe the used virtual param

Stephen H. Lubow, Richard L. White, Bernie Shiao

We use the Gaia DR2 catalog to improve the astrometric accuracy of about 1.7 billion objects in Pan-STARRS1 Data Release 2 (PS1 DR2). We also obtain proper motions for these PS1 objects. The cross match between Gaia and PS1 reveals residuals that are correlated on a scale of about 1 arcmin. We apply a spatially adaptive correction algorithm for all PS1 objec

Dara Bahri, Che Zheng, Yi Tay, Donald Metzler

Work in information retrieval has largely been centered around ranking and relevance: given a query, return some number of results ordered by relevance to the user. The problem of result list truncation, or where to truncate the ranked list of results, however, has received less attention despite being crucial in a variety of applications. Such truncation is

Gilles Parez, Riccarda Bonsignori, Pasquale Calabrese

The time evolution of the entanglement entropy is a key concept to understand the structure of a non-equilibrium quantum state. In a large class of models, such evolution can be understood in terms of a semiclassical picture of moving quasiparticles spreading the entanglement throughout the system. However, it is not yet known how the entanglement splits bet

Dalila Rivero, Vinicius S. de Angelis, Camila Beli, Michelle Moreno

We explore a scheme for guiding cold atoms through a hollow Bessel beam generated by a single axicon and a lens from a 2D magneto-optical trap toward a science chamber. We compare the Bessel beam profiles measured along the optical axis to a numerical propagation of the beam's wavefront, and we show how it is affected by diffraction during the passage th

Ilze Amanda Auzina, Jakub M. Tomczak

Many real-life problems are represented as a black-box, i.e., the internal workings are inaccessible or a closed-form mathematical expression of the likelihood function cannot be defined. For continuous random variables likelihood-free inference problems can be solved by a group of methods under the name of Approximate Bayesian Computation (ABC). However, a

Mo Yu, Xiaoxiao Guo, Yufei Feng, Xiaodan Zhu

Commonsense reasoning simulates the human ability to make presumptions about our physical world, and it is an indispensable cornerstone in building general AI systems. We propose a new commonsense reasoning dataset based on human's interactive fiction game playings as human players demonstrate plentiful and diverse commonsense reasoning. The new dataset

Mykhailo Azarkh, Katharina Keller, Mian Qi, Adelheid Godt

Relaxation-induced dipolar modulation enhancement (RIDME) is a pulse EPR technique that is particularly suitable to determine distances between paramagnetic centers with a broad EPR spectrum, e.g. metal-ion-based ones. As far as high-spin systems (S > 1/2) are concerned, the RIDME experiment provides not only the basic dipolar frequency but also its overtone

Abigail H. Chown, Victoria Scowcroft, Stijn Wuyts

The Cepheid Leavitt Law (LL), also known as the Period-Luminosity relation, is a crucial tool for assembling the cosmic distance ladder. By combining data from the OGLE-IV catalogue with mid-infrared photometry from the Spitzer Space Telescope, we have determined the $3.6$ $μ$m and $4.5$ $μ$m LLs for the Magellanic Clouds using around 5000 fundamental-mode C

A. Albert, D. Bošnjaković, S. Dujko, Z. Donkó

The relaxation of the distribution function of the electrons drifting under the influence of a homogeneous electric field in noble gases is known to take place over an extended spatial domain at `intermediate' values of the reduced electric field, $E/N$. We investigate the transport of electrons in Ar and N$_2$ gases, as well as in their mixtures at such

Honglei Li, Huayang Song, Shufang Su, Wei Su

In this work, we study the implication of Higgs precision measurements at future Higgs factories on the MSSM parameter space, focusing on the dominant stop sector contributions. We perform a multi-variable fit to both the signal strength for various Higgs decay channels at Higgs factories and the Higgs mass. The chi-square fit results show sensitivity to mA,

V. M. A. Gómez-González, Y. D. Mayya, J. A. Toalá, S. J. Arthur

We present the analysis of archival Very Large Telescope (VLT) Multi Unit Spectroscopic Explorer (MUSE) observations of the interacting galaxies NGC 4038/39 (a.k.a. the Antennae) at a distance of 18.1 Mpc. Up to 38 young star-forming complexes with evident contribution from Wolf-Rayet (WR) stars are unveiled. We use publicly available templates of Galactic W

Nitin Agarwal, M Gopi

We present a new meshing algorithm called guided and augmented meshing, GAMesh, which uses a mesh prior to generate a surface for the output points of a point network. By projecting the output points onto this prior and simplifying the resulting mesh, GAMesh ensures a surface with the same topology as the mesh prior but whose geometric fidelity is controlled

Magdalena Djordjevic, Stefan Stojku, Dusan Zigic, Bojana Ilic

High $p_\perp$ theory and data are commonly used to study high $p_\perp$ parton interactions with QGP, while low $p_\perp$ data and corresponding models are employed to infer QGP bulk properties. On the other hand, with a proper description of high $p_\perp$ parton-medium interactions, high $p_\perp$ probes become also powerful tomography tools, since they a

Jiachen Jiang, Soroush Vosoughi

Social media has shaken the foundations of our society, unlikely as it may seem. Many of the popular tools used to moderate harmful digital content, however, have received widespread criticism from both the academic community and the public sphere for middling performance and lack of accountability. Though social media research is thought to center primarily

L. Kaltenegger, J. Pepper

Transit observations have found the majority of exoplanets to date. Spectroscopic observations of transits and eclipses are the most commonly used tool to characterize exoplanet atmospheres and will be used in the search for life. However, an exoplanet's orbit must be aligned with our line of sight to observe a transit. Here we ask, from which stellar va

Yize Dong, S. Valenti, K. A. Bostroem, D. J. Sand

We present multi-band photometry and spectroscopy of SN 2018cuf, a Type IIP ("P" for plateau) supernova (SN) discovered by the Distance Less Than 40 Mpc survey (DLT40) within 24 hours of explosion. SN 2018cuf appears to be a typical Type IIP SN, with an absolute $V$-band magnitude of $-$16.73 $\pm$ 0.32 at maximum and a decline rate of 0.21 $\pm$ 0.0

Francesco Calura, Michele Bellazzini, Annibale D'Ercole

We present a suite of three-dimensional, high-resolution hydrodynamic simulations that follow the evolution of a massive (10^7 M_sun) pressure confined, star-forming neutral gas cloud moving through a hot intra-cluster medium (ICM). The main goal of the analysis is to get theoretical insight into the lifetimes and evolution of stellar systems like the recent

Daniel Perrefort, Yike Zhang, Lluís Galbany, W. M. Wood-Vasey

The use of Type Ia Supernovae (SNe Ia) to measure cosmological parameters has grown significantly over the past two decades. However, there exists a significant diversity in the SN Ia population that is not well understood. Over-luminous SN 1991T-like and sub-luminous SN 1991bg-like objects are two characteristic examples of peculiar SNe. The identification

Samrat Mukhopadhyay

In this paper we theoretically study exact recovery of sparse vectors from compressed measurements by minimizing a general nonconvex function that can be decomposed into the sum of single variable functions belonging to a class of smooth nonconvex sparsity promoting functions. Null space property (NSP) and restricted isometry property (RIP) are used as key t

Siddhant Solanki, Thomas Kupfer, Omer Blaes, Elmé Breedt

We analyse Kepler/K2 lightcurve data of the AM CVn system HP Librae. We detect with confidence four photometric periodicities in the system: the orbital frequency, both positive and negative superhumps, and the positive apsidal precession frequency of the accretion disc. This is only the second time that the apsidal precession frequency has ever been directl

Nazar Burmasov

The ALICE experiment at the LHC is undergoing a major upgrade during the Long Shutdown 2 (2019-2021). In particular, the Time Projection Chamber (TPC) is being equipped with new GEM-based readout chambers and the readout electronics of several detectors are being replaced with faster and more flexible technology. This will allow ALICE to read out most of the

Wei Wei, E. A. Huerta

We introduce deep learning time-series forecasting for gravitational wave detection of binary neutron star mergers. This method enables the identification of these signals in real advanced LIGO data up to 30 seconds before merger. When applied to GW170817, our deep learning forecasting method identifies the presence of this gravitational wave signal 10 secon

Jason Phang, Jungkyu Park, Krzysztof J. Geras

Saliency maps that identify the most informative regions of an image for a classifier are valuable for model interpretability. A common approach to creating saliency maps involves generating input masks that mask out portions of an image to maximally deteriorate classification performance, or mask in an image to preserve classification performance. Many vari

James B. Dent, Bhaskar Dutta, Jayden L. Newstead, Ian M. Shoemaker

Non-relativistic Dark Matter (DM) can be accelerated by scattering on high-energy cosmic-ray (CR) electrons. This process leads to a sub-population of relativistic or semi-relativistic DM which extends the experimental reach for direct detection in the sub-GeV mass regime. In this paper we examine the current and future potential of this mechanism for constr

Remington O. Sexton, William Matzko, Nicholas Darden, Gabriela Canalizo

We present Bayesian AGN Decomposition Analysis for SDSS Spectra (BADASS), an open source spectral analysis code designed for automatic detailed deconvolution of AGN and host galaxy spectra, implemented in Python, and designed for the next generation of large scale surveys. BADASS simultaneously fits all spectral components, including power-law continuum, ste

Mario Cadelano, Jianxing Chen, Cristina Pallanca, Alina G. Istrate

We report on the discovery of the companion star to the millisecond pulsar J1631+3627F in the globular cluster M13. By means of a combination of optical and near-UV high-resolution observations obtained with the Hubble Space Telescope, we identified the counterpart at the radio source position. Its location in the color-magnitude diagrams reveals that the co

F. Yusef-Zadeh, M. Wardle, C. Heinke, R. Arendt

The recent detection of an X-ray filament associated with the radio filament G0.173-0.42 adds to four other nonthermal radio filaments with X-ray counterparts, amongst the more than 100 elongated radio structures that have been identified as synchrotron-emitting radio filaments in the inner couple of degrees of the Galactic center. The synchrotron mechanism

J. Dexter, D. Lutz, T. T. Shimizu, J. Shangguan

Radial velocity monitoring has revealed the presence of moving broad emission lines in some quasars, potentially indicating the presence of a sub-parsec binary system. Phase-referenced, near-infrared interferometric observations could map out the binary orbit by measuring the photocenter difference between a broad emission line and the hot dust continuum. We

Callum Bellhouse, Sean L. McGee, Rory Smith, Bianca M. Poggianti

We present the first study of the effect of ram-pressure "unwinding" the spiral arms of cluster galaxies. We study 11 ram-pressure stripped galaxies from GASP (GAs Stripping Phenomena in galaxies) in which, in addition to more commonly observed "jellyfish" features, dislodged material also appears to retain the original structure of the spira

Anna Hackenbroich, Ana Hudomal, Norbert Schuch, B. Andrei Bernevig

We propose and study a wave function describing an interacting three-dimensional fractional chiral hinge insulator (FCHI) constructed by Gutzwiller projection of two non-interacting second order topological insulators with chiral hinge modes at half filling. We use large-scale variational Monte Carlo computations to characterize the model states via the enta

Lorenzo Posti, Benoit Famaey, Gabriele Pezzulli, Filippo Fraternali

Galaxy scaling laws, such as the Tully-Fisher, mass-size and Fall relations, can provide extremely useful clues on our understanding of galaxy formation in a cosmological context. Some of these relations are extremely tight and well described by one single parameter (mass), despite the theoretical existence of secondary parameters such as spin and concentrat

Jennifer Cano, Shiang Fang, J. H. Pixley, Justin H. Wilson

Twisting van der Waals heterostructures to induce correlated many-body states provides a novel tuning mechanism in solid-state physics. In this work, we theoretically investigate the fate of the surface Dirac cone of a three-dimensional topological insulator subject to a superlattice potential. Using a combination of diagrammatic perturbation theory, lattice

Marius B. Eide, Benedetta Ciardi, Yu Feng, Tiziana Di Matteo

To investigate the potential abundance and impact of nuclear black holes (BHs) during reionization, we generate a neural network that estimates their masses and accretion rates by training it on 23 properties of galaxies harbouring them at $z=6$ in the cosmological hydrodynamical simulation Massive-Black II. We then populate all galaxies in the simulation fr

Ernesto Campos, Aly Nasrallah, Jacob Biamonte

Variational quantum algorithms dominate gate-based applications of modern quantum processors. The so called, {\it layer-wise trainability conjecture} appears in various works throughout the variational quantum computing literature. The conjecture asserts that a quantum circuit can be trained piece-wise, e.g.~that a few layers can be trained in sequence to mi

Mireia Montes, Raúl Infante-Sainz, Alberto Madrigal-Aguado, Javier Román

The existence of long-lived galaxies lacking dark matter represents a challenge to our understanding of how galaxies form. Here, we present evidence that explains the lack of dark matter in one of such galaxies: NGC1052-DF4. Deep optical imaging of the system has detected tidal tails in this object caused by its interaction with its neighbouring galaxy NGC10

Andrina Nicola, Carlos García-García, David Alonso, Jo Dunkley

Cosmic shear is one of the most powerful probes of Dark Energy, targeted by several current and future galaxy surveys. Lensing shear, however, is only sampled at the positions of galaxies with measured shapes in the catalog, making its associated sky window function one of the most complicated amongst all projected cosmological probes of inhomogeneities, as

Sayan Mitra

Fluctuation measurements of hadron yields at heavy-ion collisions can reproduce the phase transition parameters of QCD matter. The fluctuation results produce accurate parameters near zero baryonic chemical potential($μ_B$) being very sensitive in that region. In this work, using the Hadron Resonance Gas Model(HRG), we determine the freeze-out temperatures o

Makis Arsenis, Odysseas Drosis, Robert Kleinberg

Free order prophet inequalities bound the ratio between the expected value obtained by two parties each selecting a value from a set of independent random variables: a "prophet" who knows the value of each variable and may select the maximum one, and a "gambler" who is free to choose the order in which to observe the values but must select on

Sergio A. Carrillo, Miguel Hurtado

The aim of this paper is to present a new simple recurrence for Appell and Sheffer sequences in terms of the linear functional that defines them, and to explain how this is equivalent to several well-known characterizations appearing in the literature. We also give several examples, including integral representations of the inverse operators associated to Be

Mustapha Azreg-Aïnou

We show that there are two or more procedures to generalize the known four-dimensional transformation, aiming to generate cylindrically rotating charged exact solutions, to higher dimensional spacetimes . In the one procedure, presented in Eur. Phys. J. C (2019) \textbf{79}:668, one uses a non-trivial, non-diagonal, Minkowskian metric $\barη_{ij}$ to derive

David Wan, Zhengping Jiang, Chris Kedzie, Elsbeth Turcan

In this work, we focus on improving ASR output segmentation in the context of low-resource language speech-to-text translation. ASR output segmentation is crucial, as ASR systems segment the input audio using purely acoustic information and are not guaranteed to output sentence-like segments. Since most MT systems expect sentences as input, feeding in longer

Seyed Majid Azimi, Maximilian Kraus, Reza Bahmanyar, Peter Reinartz

In this paper, we address various challenges in multi-pedestrian and vehicle tracking in high-resolution aerial imagery by intensive evaluation of a number of traditional and Deep Learning based Single- and Multi-Object Tracking methods. We also describe our proposed Deep Learning based Multi-Object Tracking method AerialMPTNet that fuses appearance, tempora

Michael Chiang, Davide Michieletto, Chris A. Brackley, Nattaphon Rattanavirotkul

Lamina-associated domains (LADs) cover a large part of the human genome and are thought to play a major role in shaping the nuclear architectural landscape. Here, we perform polymer simulations, microscopy and mass spectrometry to dissect the roles played by heterochromatin- and lamina-mediated interactions in nuclear organisation. Our model explains the con

Vatsal Patel, Sarth Kanani, Tapan Pathak, Pankesh Patel

Smart doorbells have been playing an important role in protecting our modern homes. Existing approaches of sending video streams to a centralized server (or Cloud) for video analytics have been facing many challenges such as latency, bandwidth cost and more importantly users' privacy concerns. To address these challenges, this paper showcases the ability

Matthew Tivnan, J. Webster Stayman

Manifold learning using deep neural networks been shown to be an effective tool for building sophisticated prior image models that can be applied to noise reduction in low-dose CT. We propose a new iterative CT reconstruction algorithm, called Manifold Reconstruction of Differences (MRoD), which combines physical and statistical models with a data-driven pri

Brendan Kochunas, Krishna Garikipati, Matthew Duschenes, Thomas Folk

Presently, models for the parameterization of cross sections for nodal diffusion nuclear reactor calculations at different conditions using histories and branches are developed from reactor physics expertise and by trial and error. In this paper we describe the development and application of a novel graph theoretic approach (GTA) to develop the expressions f

Brennan de Neeve, Thanh Long Nguyen, Tanja Behrle, Jonathan Home

Stabilization of encoded logical qubits using quantum error correction is key to the realization of reliable quantum computers. While qubit codes require many physical systems to be controlled, oscillator codes offer the possibility to perform error correction on a single physical entity. One powerful encoding for oscillators is the grid state or GKP encodin

Ehsan Nowroozi, Ali Dehghantanha, Reza M. Parizi, Kim-Kwang Raymond Choo

Image forensic plays a crucial role in both criminal investigations (e.g., dissemination of fake images to spread racial hate or false narratives about specific ethnicity groups) and civil litigation (e.g., defamation). Increasingly, machine learning approaches are also utilized in image forensics. However, there are also a number of limitations and vulnerab

Alessio Rocci

In June 1888, Oliver Heaviside received by mail an officially unpublished pamphlet, which was written and printed by the American author Willard J. Gibbs around 1881-1884. This original document is preserved in the Dibner Library of the History of Science and Technology at the Smithsonian Institute in Washington DC. Heaviside studied Gibbs's work very ca

Niclas Boehmer, Robert Bredereck, Piotr Faliszewski, Rolf Niedermeier

We study the parameterized complexity of counting variants of Swap- and Shift-Bribery problems, focusing on the parameterizations by the number of swaps and the number of voters. We show experimentally that Swap-Bribery offers a new approach to the robustness analysis of elections.

Supreeth Narasimhaswamy, Trung Nguyen, Minh Hoai

We investigate a new problem of detecting hands and recognizing their physical contact state in unconstrained conditions. This is a challenging inference task given the need to reason beyond the local appearance of hands. The lack of training annotations indicating which object or parts of an object the hand is in contact with further complicates the task. W

Martin Wortman, Ernest Kee, Pranav Kannan

The design and operation of protective systems is an essential engineering responsibility. Ensuring public safety, while essential, must be accomplished at a feasible cost and within government regulation. Hence, protective system design and operational decisions must be evaluated with respect to benefit (both enterprise profit and social benefit) and cost (

Xingkang He, Ehsan Hashemi, Karl H. Johansson

We study how to design a secure observer-based distributed controller such that a group of vehicles can achieve accurate state estimates and formation control even if the measurements of a subset of vehicle sensors are compromised by a malicious attacker. We propose an architecture consisting of a resilient observer, an attack detector, and an observer-based

Kyle B. Sheppard, Luis Welbanks, Avi Mandell, Nikku Madhusudhan

We present a comprehensive analysis of the 0.3--5\,$μ$m transit spectrum for the inflated hot Jupiter HAT-P-41b. The planet was observed in transit with Hubble STIS and WFC3 as part of the Hubble Panchromatic Comparative Exoplanet Treasury (PanCET) program, and we combine those data with warm \textit{Spitzer} transit observations. We extract transit depths f

Zalán Borsos, Yunpeng Li, Beat Gfeller, Marco Tagliasacchi

A crucial aspect for the successful deployment of audio-based models "in-the-wild" is the robustness to the transformations introduced by heterogeneous acquisition conditions. In this work, we propose a method to perform one-shot microphone style transfer. Given only a few seconds of audio recorded by a target device, MicAugment identifies the transf

Nipun Sadvilkar, Mark Neumann

In this paper, we present a rule-based sentence boundary disambiguation Python package that works out-of-the-box for 22 languages. We aim to provide a realistic segmenter which can provide logical sentences even when the format and domain of the input text is unknown. In our work, we adapt the Golden Rules Set (a language-specific set of sentence boundary ex

Zalán Borsos, Marco Tagliasacchi, Andreas Krause

Active learning is an effective technique for reducing the labeling cost by improving data efficiency. In this work, we propose a novel batch acquisition strategy for active learning in the setting where the model training is performed in a semi-supervised manner. We formulate our approach as a data summarization problem via bilevel optimization, where the q

Patrick A. Lee

A recent paper on the insulating state of monolayer WTe2 reported the observation of large oscillations in the conductivity that are periodic in 1/B, resembling quantum oscillations in metals. This remarkable observation has inspired suggestions of exotic physics such as spin-charge separation. We show that a rather more conventional but still nontrivial exp

Kostas Ferles, Jon Stephens, Isil Dillig

Several real-world libraries (e.g., reentrant locks, GUI frameworks, serialization libraries) require their clients to use the provided API in a manner that conforms to a context-free specification. Motivated by this observation, this paper describes a new technique for verifying the correct usage of context-free API protocols. The key idea underlying our te

Hao Pang, Tobias Haecker, Alexandre Bense, Tobias Haist

In this work, a numerical modal decomposition approach is applied to model the optical field of laser light after propagating through a highly multi-mode fiber. The algorithm for the decomposition is based on the reconstruction of measured intensity profiles along the laser beam caustic with consideration of intermodal degrees of coherence derived from spect

Jiaming Chen

Let $\mathbb{V}$ be a polarized variation of integral Hodge structure on a smooth complex quasi-projective variety $S$. In this paper, we show that the union of the non-factor special subvarieties for $(S, \mathbb{V})$, which are of Shimura type with dominant period maps, is a finite union of special subvarieties of $S$. This generalizes previous results of

Tony Zhao, Jaeyoung Choi, Gerald Friedland

Cross-modal retrieval relies on accurate models to retrieve relevant results for queries across modalities such as image, text, and video. In this paper, we build upon previous work by tackling the difficulty of evaluating models both quantitatively and qualitatively quickly. We present DIME (Dataset, Index, Model, Embedding), a modality-agnostic tool that h