arXiv papers from July 2018

A. Ulvestad, W. Cha, I. Calvo-Almazan, S. Maddali

Nanoscale heterogeneity (including size, shape, strain, and defects) significantly impacts material properties and how they function. Bragg coherent x-ray imaging methods have emerged as a powerful tool to investigate, in three-dimensional detail, the local material response to external stimuli in reactive environments, thereby enabling explorations of the s

Nanyu Chen, Min Liu, Ya Xu

We have seen a massive growth of online experiments at LinkedIn, and in industry at large. It is now more important than ever to create an intelligent A/B platform that can truly democratize A/B testing by allowing everyone to make quality decisions, regardless of their skillset. With the tremendous knowledge base created around experimentation, we are able

Mingxing Chen, M. Weinert

The k-projection method provides an approach to separate the contributions from different constituents in heterostructure systems and can act as an aid to connect the results of experiments and calculations. We show that the technique can be used to "unfold" the calculated electronic bands of interfaces and supercells, and provide local band structure by int

Tim Leathart, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer

Obtaining accurate and well calibrated probability estimates from classifiers is useful in many applications, for example, when minimising the expected cost of classifications. Existing methods of calibrating probability estimates are applied globally, ignoring the potential for improvements by applying a more fine-grained model. We propose probability calib

V. N. Zirakashvili, V. S. Ptuskin

We investigate acceleration of cosmic rays by shocks and accretion flows in galaxy clusters. Numerical results for spectra of accelerated particles and nonthermal emission are presented. It is shown that the acceleration of protons and nuclei in the nearby galaxy cluster Virgo can explain the observed spectra of ultra high energy cosmic rays.

Stephen Romansky, Cheng Chen, Baljeet Malhotra, Abram Hindle

On the worldwide web, not only are webpages connected but source code is too. Software development is becoming more accessible to everyone and the licensing for software remains complicated. We need to know if software licenses are being maintained properly throughout their reuse and evolution. This motivated the development of the Sourcerer's Apprentice, a

V. De la Luz, E. P. Balanzario, T. Tsiftsi

Solar flares are one of the most energetic events in the solar system, their impact on Earth at ground level and its atmosphere remains under study. The repercussions of this phenomenon in our technological infrastructure includes radio blackouts and errors in geopositional and navigation systems that are considered natural hazards in ever more countries. Oc

Jean-Pierre Macquart, Ron Ekers

We examine how the various observable statistical properties of the FRB population relate back to their fundamental physical properties in a model independent manner. We analyse the flux density and fluence distributions of Fast Radio Bursts (FRBs) as a tool to investigate their luminosity distance distribution and the evolution of their prevalence throughou

Bheema Lingam Chittari, Nicolas Leconte, Srivani Javvaji, Jeil Jung

We investigate the bandwidth compression due to out of plane pressure of the moire flatbands near charge neutrality in twisted bilayer graphene for a continuous range of small rotation angles of up to $\sim2.5^{\circ}$. The flatband bandwidth minima angles are found to grow linearly with interlayer coupling {\omega} and decrease with Fermi velocity. Applicat

Teresa M. Pegan, David W. Winkler, Mark F. Haussmann, Maren N. Vitousek

Organisms are frequently exposed to challenges during development, such as poor weather and food shortage. Such challenges can initiate the hormonal stress response, which involves secretion of glucocorticoids. Although the hormonal stress response helps organisms deal with challenges, long-term exposure to high levels of glucocorticoids can have morphologic

Paul Sheridan, Mikael Onsjö, Claudia Becerra, Sergio Jimenez

Collaborative filtering based recommender systems have proven to be extremely successful in settings where user preference data on items is abundant. However, collaborative filtering algorithms are hindered by their weakness against the item cold-start problem and general lack of interpretability. Ontology-based recommender systems exploit hierarchical organ

Hui Li, Zihua Xin, Junxian Liu, Jiali Wu

By using of the first-principles calculations based on density functional theory, a novel monolayer planar structure named C64-graphyne is predicted. Tetratomic and hexatomic rings, as well as C-C triple bonds exist in this new stable structure with the lattice parameter of 9.291 {\AA}. The carbon hexatomic ring in C64-graphyne contains two quite distinct C-

Yan Sun, Dongfang Xu, Derrick Wing Kwan Ng, Linglong Dai

In this paper, we investigate the resource allocation algorithm design for multicarrier solar-powered unmanned aerial vehicle (UAV) communication systems. In particular, the UAV is powered by solar energy enabling sustainable communication services to multiple ground users. We study the joint design of the three-dimensional (3D) aerial trajectory and the wir

Inkyu Sa, Marija Popovic, Raghav Khanna, Zetao Chen

We present a novel weed segmentation and mapping framework that processes multispectral images obtained from an unmanned aerial vehicle (UAV) using a deep neural network (DNN). Most studies on crop/weed semantic segmentation only consider single images for processing and classification. Images taken by UAVs often cover only a few hundred square meters with e

Joel Hutchinson, Joseph Maciejko

Rashba spin-orbit coupling appears in 2D systems lacking inversion symmetry, and causes the spin-splitting of otherwise degenerate energy bands into an upper and lower helicity band. In this paper, we explore how impurity scattering affects transport in the ultra-low-density regime where electrons are confined to the lower helicity band. A previous study has

Fenglei Fan, Jinjun Xiong, Ge Wang

Recently, deep learning has achieved huge successes in many important applications. In our previous studies, we proposed quadratic/second-order neurons and deep quadratic neural networks. In a quadratic neuron, the inner product of a vector of data and the corresponding weights in a conventional neuron is replaced with a quadratic function. The resultant qua

PROSPECT Collaboration, J. Ashenfelter, A. B. Balantekin, C. Baldenegro

The Precision Reactor Oscillation and Spectrum Experiment, PROSPECT, is designed to make both a precise measurement of the antineutrino spectrum from a highly-enriched uranium reactor and to probe eV-scale sterile neutrinos by searching for neutrino oscillations over meter-long baselines. PROSPECT utilizes a segmented $^6$Li-doped liquid scintillator detecto

Ryan M. Corey, Andrew C. Singer

We consider the problem of separating speech sources captured by multiple spatially separated devices, each of which has multiple microphones and samples its signals at a slightly different rate. Most asynchronous array processing methods rely on sample rate offset estimation and resampling, but these offsets can be difficult to estimate if the sources or mi

Yubo Wang, Zhen Song, Valerio De Angelis, Sanjeev Srivastava

In metropolitan areas populated with commercial buildings, electric power supply is stringent especially during business hours. Demand side management using battery is a promising solution to mitigate peak demands, however long payback time creates barriers for large scale adoption. In this paper, we have developed a design phase battery life-cycle cost asse

Ahmed K. Ibrahim, Thomas Vojta

We investigate the quantum phase transitions of a disordered nanowire from superconducting to metallic behavior by employing extensive Monte Carlo simulations. To this end, we map the quantum action onto a (1+1)-dimensional classical XY model with long-range interactions in imaginary time. We then analyze the finite-size scaling behavior of the order paramet

Carlos Molina-Jimenez, Ioannis Sfyrakis, Ellis Solaiman, Irene Ng

Recently, decentralised (on-blockchain) platforms have emerged to complement centralised (off-blockchain) platforms for the implementation of automated, digital (smart) contracts. However, neither alternative can individually satisfy the requirements of a large class of applications. On-blockchain platforms suffer from scalability, performance, transaction c

Sangwoo Park, Cassie Meeker, Lynne M. Weber, Lauri Bishop

Wearable robotic hand rehabilitation devices can allow greater freedom and flexibility than their workstation-like counterparts. However, the field is generally lacking effective methods by which the user can operate the device: such controls must be effective, intuitive, and robust to the wide range of possible impairment patterns. Even when focusing on a s

Dmitriy Balakin, Alexander Belinsky, Anatoly S. Chirkin

The currently used ghost image schemes traditionally involve two-mode entangled light states or incoherent radiation. Here, application of four-mode entangled light states is considered. It is shown that multiplexed ghost images (MGI) formed by four-mode entangled quantum light states have mutual spatial correlations determined by the 8th order field correla

Kevin F. Garrity

Finite temperature disordered solid solutions and magnetic materials are difficult to study directly using first principles calculations, due to the large unit cells and many independent samples that are required. In this work, we develop a combined cluster expansion and atomic displacement expansion, which we fit to first principles energies, forces, and st

Biplav Srivastava, Francesca Rossi

A new wave of decision-support systems are being built today using AI services that draw insights from data (like text and video) and incorporate them in human-in-the-loop assistance. However, just as we expect humans to be ethical, the same expectation needs to be met by automated systems that increasingly get delegated to act on their behalf. A very import

Thomas Norman Dam

In this paper we consider the massless translation invariant Nelson model with ultraviolet cutoff. It is proven that the fiber operators have no ground state if there is no infrared cutoff.

Yu-Xiang Wang, Borja Balle, Shiva Kasiviswanathan

We study the problem of subsampling in differential privacy (DP), a question that is the centerpiece behind many successful differentially private machine learning algorithms. Specifically, we provide a tight upper bound on the R\'enyi Differential Privacy (RDP) (Mironov, 2017) parameters for algorithms that: (1) subsample the dataset, and then (2) applies a

Benshuai Lyu, Ann Dowling

Jet installation causes jet noise to be amplified significantly at low frequencies and its physical mechanism must be understood to develop effective aircraft noise reduction strategies. A hybrid semi-empirical prediction model has recently been developed based on the instability-wave-scattering mechanism. However, its validity and accuracy remain to be test

Thomas Norman Dam, Jacob Schach Møller

In this paper we investigate a family of models for a qubit interacting with a bosonic field. More precisely, we find asymptotic limits of the Hamiltonian as the strength of the interaction tends to infinity. The main result has two applications. First of all, we show that self-energy renormalisation schemes similar to that of the Nelson model will never giv

R. B. Jadrich, B. A. Lindquist, T. M. Truskett

We demonstrate the utility of an unsupervised machine learning tool for the detection of phase transitions in off-lattice systems. We focus on the application of principal component analysis (PCA) to detect the freezing transitions of two-dimensional hard-disk and three-dimensional hard-sphere systems as well as liquid-gas phase separation in a patchy colloi

R. B. Jadrich, B. A. Lindquist, W. D. Pineros, D. Banerjee

We outline how principal component analysis (PCA) can be applied to particle configuration data to detect a variety of phase transitions in off-lattice systems, both in and out of equilibrium. Specifically, we discuss its application to study 1) the nonequilibrium random organization (RandOrg) model that exhibits a phase transition from quiescent to steady-s

Ryan M. Corey, Naoki Tsuda, Andrew C. Singer

In real-time listening enhancement applications, such as hearing aid signal processing, sounds must be processed with no more than a few milliseconds of delay to sound natural to the listener. Listening devices can achieve better performance with lower delay by using microphone arrays to filter acoustic signals in both space and time. Here, we analyze the tr

O. Kyriienko, H. Sigurdsson, T. C. H. Liew

A lattice of locally bistable driven-dissipative cavity polaritons is found theoretically to effectively simulate the Ising model, also enabling an effective transverse field. We benchmark the system performance for spin glass problems, and study the scaling of the ground state energy deviation and success probability as a function of system size. As particu

Brian C. Seymour, Kent Yagi

Binary pulsars allow us to carry out precision tests of gravity and have placed stringent bounds on a broad class of theories beyond general relativity. Current and future radio telescopes, such as FAST, SKA, and MeerKAT, may find a new astrophysical system, a pulsar orbiting around a black hole, which will provide us a new source for probing gravity. In thi

Breanna A. Binder, Matthew S. Povich

We present a multiwavelength study of 28 Galactic massive star-forming H II regions. For 17 of these regions, we present new distance measurements based on Gaia DR2 parallaxes. By fitting a multicomponent dust, blackbody, and power-law continuum model to the 3.6 $\mu$m through 10 mm spectral energy distributions, we find that ${\sim}34$% of Lyman continuum p

Dhruv Mubayi, Andrew Suk

Motivated by the Erdos-Szekeres convex polytope conjecture in $R^d$, we initiate the study of the following induced Ramsey problem for hypergraphs. Given integers $ n > k \geq 5$, what is the minimum integer $g_k(n)$ such that any $k$-uniform hypergraph on $g_k(n)$ vertices with the property that any set of $k + 1$ vertices induces 0, 2, or 4 edges, contains

Jianwei Feng, Dong Huang

Deep Neural Networks(DNNs) require huge GPU memory when training on modern image/video databases. Unfortunately, the GPU memory is physically finite, which limits the image resolutions and batch sizes that could be used in training for better DNN performance. Unlike solutions that require physically upgrade GPUs, the Gradient CheckPointing(GCP) training trad

Vanessa Barros, Lingmin Liao, Jerome Rousseau

In this paper, we study the behaviour of the shortest distance between orbits and show that under some rapidly mixing conditions, the decay of the shortest distance depends on the correlation dimension. For irrational rotations, we prove a different behaviour depending on the irrational exponent of the angle of the rotation. For random processes, this proble

Hanwen Wu, Hongwei Xi

Programs are more distributed and concurrent today than ever before, and structural communications are at the core. Constructing and debugging such programs are hard due to the lack of formal specification/verification of concurrency. This work formalizes the first multiparty dependent session types as an expressive and practical type discipline for enforcin

Zheng Ma, Salvatore Torquato

The quantitative characterization of the microstructure of random heterogeneous media in $d$-dimensional Euclidean space $\mathbb{R}^d$ via a variety of $n$-point correlation functions is of great importance, since the respective infinite set determines the effective physical properties of the media. In particular, surface-surface $F_{ss}$ and surface-void $

Gabriel de Souza P. Moreira, Felipe Ferreira, Adilson Marques da Cunha

News recommender systems are aimed to personalize users experiences and help them to discover relevant articles from a large and dynamic search space. Therefore, news domain is a challenging scenario for recommendations, due to its sparse user profiling, fast growing number of items, accelerated item's value decay, and users preferences dynamic shift. Some p

Ahmad Zein Assi

I study the deformation of the topological string by $\bar\Omega$, the complex conjugate of the $\Omega$-deformation. Namely, I identify $\bar\Omega$ in terms of a physical state in the string spectrum and verify that the deformed Yang-Mills and ADHM actions are reproduced. This completes the study initiated recently [1] where we show that $\bar\Omega$ decou

Maria Lucia Fania, Margherita Lelli-Chiesa, Joan Pons-Llopis

In this paper we construct Ulrich bundles of low rank on three-dimensional scrolls (with respect to the tautological line bundle). We pay special attention to the four types of threefold scrolls in $\mathbb{P}^5$ which were classified in [Ott92].

Sheng-Wen Li

Macroscopic many-body systems always exhibit irreversible behaviors together with the entropy increase. However, the underlying microscopic dynamics of the many-body system, either the (quantum) von Neumann or (classical) Liouville equation, guarantees the entropy of an isolated system does not change with time. Notice that, in practical measurements, usuall

F. Hermann, P. Pfaffelhuber

A $p$-jump process is a piecewise deterministic Markov process with jumps by a factor of $p$. We prove a limit theorem for such processes on the unit interval. Via duality with respect to probability generating functions, we deduce limiting results for the survival probabilities of time-homogeneous branching processes with arbitrary offspring distributions,

Mehdi Badie

In this article we study the annihilating-ideal graph of the ring $C(X)$. We have tried to associate the graph properties of $\mathbb{AG}(X)$, the ring properties of $C(X)$ and the topological properties of $X$. We have shown that $ X $ has an isolated point \ff $ \mathbb{R} $ is a direct summand of $ C(X) $ if and only if $ \mathbb{AG}(X) $ is not triangula

Amin Aboubrahim, Tarek Ibrahim, Ahmad Itani, Pran Nath

A correlated analysis of observables arising from loop induced effects from a vectorlike generation is given. The observables include flavor changing radiative decays $\mu\to e \gamma, \tau\to \mu \gamma, \tau\to e \gamma$, electric dipole moments of the charged leptons $e,\mu, \tau$, and corrections to magnetic dipole moments of $g_\mu-2$ and $g_e-2$. In th

Iztok Peterin, Ismael G. Yero

A digraph $D$ is an efficient closed domination digraph if there exists a subset $S$ of $V(D)$ for which the closed out-neighborhoods centered in vertices of $S$ form a partition of $V(D)$. In this work we deal with efficient closed domination digraphs among several product of digraphs. We completely describe the efficient closed domination digraphs among le

Samuel Abreu, Ruth Britto, Claude Duhr, Einan Gardi

We propose a general coaction for families of integrals appearing in the evaluation of Feynman diagrams, such as multiple polylogarithms and generalized hypergeometric functions. We further conjecture a link between this coaction and graphical operations on Feynman diagrams. At one-loop order, there is a basis of integrals for which this correspondence is fu

Javad Rahimipour Anaraki, Saeed Samet, Mahdi Eftekhari, Chang Wook Ahn

Feature selection and attribute reduction are crucial problems, and widely used techniques in the field of machine learning, data mining and pattern recognition to overcome the well-known phenomenon of the Curse of Dimensionality, by either selecting a subset of features or removing unrelated ones. This paper presents a new feature selection method that effi

Seyed Ali Hosseini Mansoori, Viktor Jahnke, Mohammad M. Qaemmaqami, Yaithd D. Olivas

We use the complexity = action (CA) conjecture to study the full-time dependence of holographic complexity in anisotropic black branes. We find that the time behaviour of holographic complexity of anisotropic systems shares a lot of similarities with the behaviour observed in isotropic systems. In particular, the holographic complexity remains constant for s

V. Anastassopoulos, S. Aune, K. Barth, A. Belov

We report on a new search for solar chameleons with the CERN Axion Solar Telescope (CAST). A GridPix detector was used to search for soft X-ray photons in the energy range from 200 eV to 10 keV from converted solar chameleons. No signiffcant excess over the expected background has been observed in the data taken in 2014 and 2015. We set an improved limit on

Nassim Nicholas Taleb

This paper applies risk analysis to medical problems, through the properties of nonlinear responses (convex or concave). It shows 1) necessary relations between the nonlinearity of dose-response and the statistical properties of the outcomes, particularly the effect of the variance (i.e., the expected frequency of the various results and other properties suc

Shoaib Akram, Jennifer B. Sartor, Kathryn S. McKinley, Lieven Eeckhout

Non-volatile memory (NVM) has the potential to disrupt the boundary between memory and storage, including the abstractions that manage this boundary. Researchers comparing the speed, durability, and abstractions of hybrid systems with DRAM, NVM, and disk to traditional systems typically use simulation, which makes it easy to evaluate different hardware techn

Adam J. Finley, Sean P. Matt, Victor See

The rotational evolution of cool stars is governed by magnetised stellar winds which slow the stellar rotation during their main sequence lifetimes. Magnetic variability is commonly observed in Sun-like stars, and the changing strength and topology of the global field is expected to affect the torque exerted by the stellar wind. We present three different me

Andrea Zaccaria, Michela del Vicario, Walter Quattrociocchi, Antonio Scala

Users online tend to acquire information adhering to their system of beliefs and to ignore dissenting information. Such dynamics might affect page popularity. In this paper we introduce an algorithm, that we call PopRank, to assess both the Impact of Facebook pages as well as users' Engagement on the basis of their mutual interactions. The ideas behind the P

Mandar Gogate, Ahsan Adeel, Ricard Marxer, Jon Barker

Human auditory cortex excels at selectively suppressing background noise to focus on a target speaker. The process of selective attention in the brain is known to contextually exploit the available audio and visual cues to better focus on target speaker while filtering out other noises. In this study, we propose a novel deep neural network (DNN) based audiov

Seyed Mehdi Iranmanesh, Hadi Kazemi, Sobhan Soleymani, Ali Dabouei

In this paper, we present a deep coupled framework to address the problem of matching sketch image against a gallery of mugshots. Face sketches have the essential in- formation about the spatial topology and geometric details of faces while missing some important facial attributes such as ethnicity, hair, eye, and skin color. We propose a cou- pled deep neur

Cong Gao, Xingtong Liu, Michael Peven, Mathias Unberath

Robotic surgery has been proven to offer clear advantages during surgical procedures, however, one of the major limitations is obtaining haptic feedback. Since it is often challenging to devise a hardware solution with accurate force feedback, we propose the use of "visual cues" to infer forces from tissue deformation. Endoscopic video is a passive sensor th

Federico Scavia

Let $F$ be a field of characteristic zero admitting a biquadratic field extension. We give an example of a torus $G$ over $F$ whose classifying stack $BG$ is stably rational and such that $\{BG\}\{G\}\neq 1$ in the Grothendieck ring of algebraic stacks over $F$. We also give an example of a finite \'etale group scheme $A$ over $F$ such that $BA$ is stably ra

Euaggelos E. Zotos, Fredy L. Dubeibe, Guillermo A. González

The dynamics of a test particle in a non-spinning binary black hole system of equal masses is numerically investigated. The binary system is modeled in the context of the pseudo-Newtonian circular restricted three-body problem, such that the primaries are separated by a fixed distance and move in a circular orbit around each other. In particular, the Paczy\'

Michael Hahn, Frank Keller

Research on human reading has long documented that reading behavior shows task-specific effects, but it has been challenging to build general models predicting what reading behavior humans will show in a given task. We introduce NEAT, a computational model of the allocation of attention in human reading, based on the hypothesis that human reading optimizes a

Stephen R. Kane, Sarah J. Deveny

The search for exoplanets has encompassed a broad range of stellar environments, from single stars in the solar neighborhood to multiple stars and various open clusters. The stellar environment has a profound effect on planet formation and stability evolution and is thus a key component of exoplanetary studies. Dense stellar environments, such as those found

Avery Bailey, Jeremy Goodman

The orbital period of the hot Jupiter WASP-12b is apparently changing. We study whether this reflects orbital decay due to tidal dissipation in the star, or apsidal precession of a slightly eccentric orbit. In the latter case, a third body or other perturbation would be needed to sustain the eccentricity against tidal dissipation in the planet itself. We hav

Ahsan Adeel, Mandar Gogate, Amir Hussain, William M. Whitmer

This paper proposes a novel lip-reading driven deep learning framework for speech enhancement. The proposed approach leverages the complementary strengths of both deep learning and analytical acoustic modelling (filtering based approach) as compared to recently published, comparatively simpler benchmark approaches that rely only on deep learning. The propose

Muhammad Waleed Gondal, Bernhard Schölkopf, Michael Hirsch

While implicit generative models such as GANs have shown impressive results in high quality image reconstruction and manipulation using a combination of various losses, we consider a simpler approach leading to surprisingly strong results. We show that texture loss alone allows the generation of perceptually high quality images. We provide a better understan

Mbavhalelo Mulokwe, João P. Rodrigues

We study the three dimensional O(N) invariant bosonic vector model with a $\frac{\lambda}{N}(\phi^{a}\phi^{a})^{2}$ interaction at its infrared fixed point, using a bilocal field approach and in an $1/N$ expansion. We identify a (negative energy squared) bound state in its spectrum about the large $N$ conformal background. At the critical point this is ident

Sadok Kallel

We compute the Euler characteristic with compact supports $\chi_c$ of the formal barycenter spaces with weights of a finite CW complex, connected or not. This reduces to the topological Euler characteristic $\chi$ when the weights of the singular points are less than one. As foresighted by A. Malchiodi, our formula is related to the Leray-Schauder degree for

Everton M. C. Abreu, Jorge Ananias Neto, Albert C. R. Mendes, Rodrigo M. de Paula

In this letter we have shown that a possible connection between the LQG Immirzi parameter and the area of a punctured surface can emerge depending on the thermostatistics theory previously chosen. Starting from the Boltzmann-Gibbs entropy, the Immirzi parameter can be reobtained. Using the Kaniadakis statistics, which is an important non-Gaussian statistics,

Seyed Mostafa Kia, Christian F. Beckmann, Andre F. Marquand

Most brain disorders are very heterogeneous in terms of their underlying biology and developing analysis methods to model such heterogeneity is a major challenge. A promising approach is to use probabilistic regression methods to estimate normative models of brain function using (f)MRI data then use these to map variation across individuals in clinical popul

Sobhan Soleymani, Ali Dabouei, Seyed Mehdi Iranmanesh, Hadi Kazemi

In this paper a novel cross-device text-independent speaker verification architecture is proposed. Majority of the state-of-the-art deep architectures that are used for speaker verification tasks consider Mel-frequency cepstral coefficients. In contrast, our proposed Siamese convolutional neural network architecture uses Mel-frequency spectrogram coefficient

Ali Dabouei, Sobhan Soleymani, Hadi Kazemi, Seyed Mehdi Iranmanesh

Performing recognition tasks using latent fingerprint samples is often challenging for automated identification systems due to poor quality, distortion, and partially missing information from the input samples. We propose a direct latent fingerprint reconstruction model based on conditional generative adversarial networks (cGANs). Two modifications are appli

Moshe Babaioff, Sigal Oren

We study a variant of Vickrey's classic bottleneck model. In our model there are $n$ agents and each agent strategically chooses when to join a first-come-first-served observable queue. Agents dislike standing in line and they take actions in discrete time steps: we assume that each agent has a cost of $1$ for every time step he waits before joining the queu

Mengnan Du, Ninghao Liu, Xia Hu

Interpretable machine learning tackles the important problem that humans cannot understand the behaviors of complex machine learning models and how these models arrive at a particular decision. Although many approaches have been proposed, a comprehensive understanding of the achievements and challenges is still lacking. We provide a survey covering existing

H. S. Vieira, V. B. Bezerra, C. R. Muniz, M. S. Cunha

We obtain the wave functions associated to the quantum Newtonian universe with a cosmological constant which is described by the Schr\"{o}dinger equation and discuss some aspects of its dynamics for all forms of energy density, namely, matter, radiation, vacuum, dark energy, and quintessence. These wave functions of the quantum Newtonian universe are obtaine

Kyohei Otsu, Guillaume Matheron, Sourish Ghosh, Olivier Toupet

We present a light-weight body-terrain clearance evaluation algorithm for the automated path planning of NASA's Mars 2020 rover. Extraterrestrial path planning is challenging due to the combination of terrain roughness and severe limitation in computational resources. Path planning on cluttered and/or uneven terrains requires repeated safety checks on all th

Dmitry O. Krimer, Mikhail Pletyukhov

By example of the nonlinear Kerr-mode driven by a laser, we show that hysteresis phenomena in systems featuring a driven-dissipative phase transition (DPT) can be accurately described in terms of just two collective, dissipative Liouvillian eigenmodes. The key quantities are just two components of a nonabelian geometric connection, even though a single param

Laura Paladino

Let $\mathcal{E}$ be an elliptic curve defined over a number field $K$. Let $m$ be a positive integer. We denote by ${\mathcal{E}}[m]$ the $m$-torsion subgroup of $\mathcal{E}$ and by $K_m:=K({\mathcal{E}}[m])$ the number field obtained by adding to $K$ the coordinates of the points of ${\mathcal{E}}[m]$. We describe the fields $K_5$, when $\mathcal{E}$ is a

Luigi De Marco, Giacomo Valtolina, Kyle Matsuda, William G. Tobias

It has long been expected that quantum degenerate gases of molecules would open access to a wide range of phenomena in molecular and quantum sciences. However, the very complexity that makes ultracold molecules so enticing has made reaching degeneracy an outstanding experimental challenge over the past decade. We now report the production of a Fermi degenera

Sankha S. Chakrabarty, Pierre Sikivie

Caustic rings of dark matter with $\textit{tricusp}$ cross-section were predicted to lie in the galactic disk. Their radii increase on cosmological time scales at a rate of order $1$ kpc/Gyr. When a caustic ring passes through the orbit of a star, the orbit is strongly perturbed. We find that a star moving in a nearly circular orbit is first attracted toward

Giorgio Parisi, Itamar Procaccia, Carmel Shor, Jacques Zylberg

In thermal glasses at temperatures sufficiently lower than the glass transition, the constituent particles are trapped in their cages for sufficiently long time such that their {\em time-averaged positions} can be determined before diffusion and structural relaxation takes place. The effective forces are those that hold these average positions in place. In n

Bruno Gois Mateus, Matias Martinez

Context: During the last years, developers of mobile applications have the possibility to use new paradigms and tools for developing mobile applications. For instance, since 2017 Android developers have the official support to write Android applications using Kotlin language. Kotlin is programming language fully interoperable with Java that combines object-o

Xiaoou Ding, Hongzhi Wang, Jiaxuan Su, Jianzhong Li

Data quality plays a key role in big data management today. With the explosive growth of data from a variety of sources, the quality of data is faced with multiple problems. Motivated by this, we study the multiple data quality improvement on completeness, consistency and currency in this paper. For the proposed problem, we introduce a 4-step framework, name

Samuel P. Wallen, Michael R. Haberman

Acoustic non-reciprocity has been shown to enable a plethora of effects analogous to phenomena seen in quantum physics and electromagnetics, such as immunity from back-scattering and unidirectional band gaps, which could lead to the design of direction-dependent acoustic devices. One way to break reciprocity is by spatiotemporally modulating material propert

Sam Corbett-Davies, Johann D. Gaebler, Hamed Nilforoshan, Ravi Shroff

The field of fair machine learning aims to ensure that decisions guided by algorithms are equitable. Over the last decade, several formal, mathematical definitions of fairness have gained prominence. Here we first assemble and categorize these definitions into two broad families: (1) those that constrain the effects of decisions on disparities; and (2) those

Alexandros Stergiou, Ronald Poppe

Many videos depict people, and it is their interactions that inform us of their activities, relation to one another and the cultural and social setting. With advances in human action recognition, researchers have begun to address the automated recognition of these human-human interactions from video. The main challenges stem from dealing with the considerabl

Thang Doan, Joao Monteiro, Isabela Albuquerque, Bogdan Mazoure

Generative Adversarial Networks (GANs) can successfully approximate a probability distribution and produce realistic samples. However, open questions such as sufficient convergence conditions and mode collapse still persist. In this paper, we build on existing work in the area by proposing a novel framework for training the generator against an ensemble of d

Lázaro Alonso, David Bermudez, Thomas Gorin

We consider the statistics of overlaps between a mixed state and its image under random unitary transformations. Choosing the transformations from the unitary group with its invariant (Haar) measure, the distribution of overlaps depends only on the eigenvalues of the mixed state. This allows one to estimate these eigenvalues from the overlap statistics. In t

Geert Kapteijns, Wencheng Ji, Carolina Brito, Matthieu Wyart

We present a model and protocol that enable the generation of extremely stable computer glasses at minimal computational cost. The protocol consists of an instantaneous quench in an augmented potential energy landscape, with particle radii as additional degrees of freedom. We demonstrate how our glasses' mechanical stability, which is readily tunable in our

Zheng Dong, Cong Liu

The scheduling and schedulability analysis of real-time directed acyclic graph (DAG) task systems have received much recent attention. The DAG model can accurately represent intra-task parallelim and precedence constraints existing in many application domains. Existing techniques show that analyzing the DAG model is fundamentally more challenging compared to

Yair Lavi

We formulate conjectures regarding the maximum value and maximizing matrices of the permanent and of diagonal products on the set of stochastic matrices with bounded rank. We formulate equivalent conjectures on upper bounds for these functions for nonnegative matrices based on their rank, row sums and column sums. In particular we conjecture that the permane

Sara Rezaei Kh., Coryn A. L. Bailer-Jones, David W. Hogg, Mathias Schultheis

Large stellar surveys are sensitive to interstellar dust through the effects of reddening. Using extinctions measured from photometry and spectroscopy, together with three-dimensional (3D) positions of individual stars, it is possible to construct a three-dimensional dust map. We present the first continuous map of the dust distribution in the Galactic disk

D. J. K. Buisson, M. L. Parker, E. Kara, R. V. Vasudevan

We present two new NuSTAR observations of the narrow line Seyfert 1 (NLS1) galaxy Mrk 766 and give constraints on the two scenarios previously proposed to explain its spectrum and that of other NLS1s: relativistic reflection and partial covering. The NuSTAR spectra show a strong hard (>15 keV) X-ray excess, while simultaneous soft X-ray coverage of one of th

Mikhail Denissenya, Eric V. Linder

Cosmic acceleration may be due to modified gravity, with effective field theory or property functions describing the theory. Connection to cosmological observations through practical parametrization of these functions is difficult and also faces the issue that not all assumed time dependence or parts of parameter space give a stable theory. We investigate th

Rajesh Kumar Gupta, Sameer Murthy, Caner Nazaroglu

Squashed toric sigma models are a class of sigma models whose target space is a toric manifold in which the torus fibration is squashed away from the fixed points so as to produce a neck-like region. The elliptic genera of squashed toric-Calabi-Yau manifolds are known to obey the modular transformation property of holomorphic Jacobi forms, but have an explic

Warren R. Morningstar, Yashar D. Hezaveh, Laurence Perreault Levasseur, Roger D. Blandford

We use convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to estimate the parameters of strong gravitational lenses from interferometric observations. We explore multiple strategies and find that the best results are obtained when the effects of the dirty beam are first removed from the images with a deconvolution performed with an RNN

Cen Zhang, Shuang-Yong Zhou

Weak vector boson scattering (VBS) is a sensitive probe of new physics effects in the electroweak symmetry breaking. Currently, experimental results at the LHC are interpreted in the effective field theory approach, where possible deviations from the Standard Model in the quartic-gauge-boson couplings are often described by 18 dimension-8 operators. By assum

Iñaki García-Etxebarria, Miguel Montero

Anomalies can be elegantly analyzed by means of the Dai-Freed theorem. In this framework it is natural to consider a refinement of traditional anomaly cancellation conditions, which sometimes leads to nontrivial extra constraints in the fermion spectrum. We analyze these more refined anomaly cancellation conditions in a variety of theories of physical intere

M. Kourniotis, M. Kraus, M. L. Arias, L. Cidale

The advanced stages of several high-mass stars are characterized by episodic mass loss shed during phases of instability. Key for assigning these stars a proper evolutionary state is to assess the composition and geometry of their ejecta alongside the stellar properties. We selected five hot LBV candidates in M33 to refine their classification, investigate t

Pierre-Antoine Poulhazan, Cecilia Scannapieco, Peter Creasey

We present an update to the chemical enrichment component of the smoothed-particle hydrodynamics model for galaxy formation presented in Scannapieco et al. (2005) in order to address the needs of modelling galactic chemical evolution in realistic cosmological environments. Attribution of the galaxy-scale abundance patterns to individual enrichment mechanisms