July 2018 arXiv papers

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 structur

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

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

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

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

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

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 Rényi Differential Privacy (RDP) (Mironov, 2017) parameters for algorithms that: (1) subsample the dataset, and then (2) applies a r

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

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 $μ$m through 10 mm spectral energy distributions, we find that ${\sim}34$% of Lyman continuum pho

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

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. So

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,

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 $μ\to e γ, τ\to μγ, τ\to e γ$, electric dipole moments of the charged leptons $e,μ, τ$, and corrections to magnetic dipole moments of $g_μ-2$ and $g_e-2$. In this work we give a full analysis o

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

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

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 étale group scheme $A$ over $F$ such that $BA$ is stably rati

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

Sadok Kallel

We compute the Euler characteristic with compact supports $χ_c$ of the formal barycenter spaces with weights of a finite CW complex, connected or not. This reduces to the topological Euler characteristic $χ$ 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 mean

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

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

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 Schrödinger 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 obtained in

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 al

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

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

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

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

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

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

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

Ricard Ardevol-Pulpillo, H. -Thomas Janka, Oliver Just, Andreas Bauswein

We present a new, computationally efficient, energy-integrated approximation for neutrino effects in hot and dense astrophysical environments such as supernova cores and compact binary mergers and their remnants. Our new method, termed ILEAS for Improved Leakage-Equilibration-Absorption Scheme, improves the lepton-number and energy losses of traditional leak

Hayata Yamasaki, Alexander Pirker, Mio Murao, Wolfgang Dür

Multipartite quantum entanglement serves as a resource for spatially separated parties performing distributed quantum information processing. Any multipartite entangled state can be generated from appropriately distributed bipartite entangled states by local operations and classical communication (LOCC), and in this sense, any distributed process based on sh

Mark M. Wilde

This paper proposes a revised definition for the entanglement cost of a quantum channel $\mathcal{N}$. In particular, it is defined here to be the smallest rate at which entanglement is required, in addition to free classical communication, in order to simulate $n$ calls to $\mathcal{N}$, such that the most general discriminator cannot distinguish the $n$ ca

Hiroki Matsui, Fuminobu Takahashi

We study if eternal inflation is realized while satisfying the recently proposed string Swampland criteria concerning the range of scalar field excursion, $|Δϕ| < \mathcal{D} \cdot M_{\rm P}$, and the potential gradient, $|\nabla V| > c \cdot V/M_{\rm P}$, where $\mathcal{D}$ and $c$ are constants of order unity, and $M_{\rm P}$ is the reduced Planck mass. W

Gilberto Colangelo, Stefan Lanz, Heinrich Leutwyler, Emilie Passemar

The dispersive analysis of the decay $η\to3π$ is reviewed and thoroughly updated with the aim of determining the quark mass ratio ~$Q^2=(m_s^2-m_{ud}^2)/(m_d^2-m_u^2)$. With the number of subtractions we are using, the effects generated by the final state interaction are dominated by low energy $ππ$ scattering. Since the corresponding phase shifts are now ac

Katherine C. McCormick, Jonas Keller, Shaun C. Burd, David J. Wineland

The use of special quantum states to achieve sensitivities below the limits established by classically behaving states has enjoyed immense success since its inception. In bosonic interferometers, squeezed states, number states and cat states have been implemented on various platforms and have demonstrated improved measurement precision over interferometers b

Nazife Erkurşun-Özcan, Farrukh Mukhamedov

In order to successfully explore quantum systems which are perturbations of simple models, it is essential to understand the complexity of perturbation bounds. We must ask ourselves: How quantum many-body systems can be artificially engineered to produce the needed behavior. Therefore, it is convenient to make use of abstract framework to better understand c

Ai Guan

We introduce a notion of left homotopy for Maurer--Cartan elements in $L_{\infty}$-algebras and $A_{\infty}$-algebras, and show that it corresponds to gauge equivalence in the differential graded case. From this we deduce a short formula for gauge equivalence, and provide an entirely homotopical proof to Schlessinger--Stasheff&#39;s theorem. As an applicatio

Marco Golla, Christopher Scaduto

We classify the positive definite intersection forms that arise from smooth 4-manifolds with torsion-free homology bounded by positive integer surgeries on the right-handed trefoil. A similar, slightly less complete classification is given for the (2,5)-torus knot, and analogous results are obtained for integer surgeries on knots of slice genus at most two.

A. Adare, C. Aidala, N. N. Ajitanand, Y. Akiba

Asymmetric nuclear collisions of $p$$+$Al, $p$$+$Au, $d$$+$Au, and $^{3}$He$+$Au at $\sqrt{s_{_{NN}}}=200$ GeV provide an excellent laboratory for understanding particle production, as well as exploring interactions among these particles after their initial creation in the collision. We present measurements of charged hadron production $dN_{\rm ch}/dη$ in al

Ruth Birch, Siyang Wang, Vivian Tong, Thomas Benjamin Britton

We explore the distribution, morphology and structure of zirconium hydrides formed using different cooling rates through the solid state Zr+[H] --> Zr + hydride transus, in fine and blocky alpha Zircaloy-4. We observe that cooling rate and grain size control the phase and distribution of hydrides. The blocky alpha (coarse grain, > 200 micrometer) Zircaloy-4,

Bruno Rossi, Stanislav Chren

Data analytics and data science play a significant role in nowadays society. In the context of Smart Grids (SG), the collection of vast amounts of data has seen the emergence of a plethora of data analysis approaches. In this paper, we conduct a Systematic Mapping Study (SMS) aimed at getting insights about different facets of SG data analysis: application s

Mengmi Zhang, Gabriel Kreiman

Can we infer intentions from a person&#39;s actions? As an example problem, here we consider how to decipher what a person is searching for by decoding their eye movement behavior. We conducted two psychophysics experiments where we monitored eye movements while subjects searched for a target object. We defined the fixations falling on non-target objects as

Fernando Peñaranda, Ramón Aguado, Pablo San-Jose, Elsa Prada

A key property of Majorana zero modes is their protection against local perturbations. In the standard picture, this protection is guaranteed by a high degree of spatial nonlocality of the Majoranas, namely a suppressed wave-function overlap, in the topological phase. However, a careful characterisation of resilience to local noise goes beyond mere spatial s

Nicholas Phat Nguyen

We present a more general proof that cyclotomic polynomials are irreducible over Q and other number fields that meet certain conditions. The proof provides a new perspective that ties together well-known results, as well as some new consequences, including a necessary condition for the algebraic solution by radicals of certain irreducible polynomials.

Xinyu Yao, Joshua Pepper, B. Scott Gaudi, Jonathan Labadie-Bartz

During the TESS prime mission, 74% of the sky area will only have an observational baseline of 27 days. For planets with orbital periods longer than 13.5 days, TESS can only capture one or two transits, and the planet ephemerides will be difficult to determine from TESS data alone. Follow-up observations of transits of these candidates will require precise e

Igor Halperin, Matthew Dixon

We propose a simple non-equilibrium model of a financial market as an open system with a possible exchange of money with an outside world and market frictions (trade impacts) incorporated into asset price dynamics via a feedback mechanism. Using a linear market impact model, this produces a non-linear two-parametric extension of the classical Geometric Brown

Michael Andrews, Manfred Paulini, Sergei Gleyzer, Barnabas Poczos

This paper describes the construction of novel end-to-end image-based classifiers that directly leverage low-level simulated detector data to discriminate signal and background processes in pp collision events at the Large Hadron Collider at CERN. To better understand what end-to-end classifiers are capable of learning from the data and to address a number o

Hassan Najafi Alishah

We introduce an algorithm to find possible constants of motion for a given replicator equation. The algorithm is inspired by Dirac geometry and a Hamiltonian description for the replicator equations with such constants of motion, up to a time re-parametrization, is provided using Dirac$\backslash$big-isotropic structures. Using the equivalence between replic

Mengfei He, Sidney R. Nagel

In forced wetting, a rapidly moving surface drags with it a thin layer of trailing fluid as it is plunged into a second fluid bath. Using high-speed interferometry, we find characteristic structure in the thickness of this layer with multiple thin flat triangular structures separated by much thicker regions. These features, depending on liquid viscosity and

Paul G Blackwell

Motivated by applications in movement ecology, in this paper I propose a new class of integrated continuous-time hidden Markov models in which each observation depends on the underlying state of the process over the whole interval since the previous observation, not only on its current state. This class gives a new representation of a range of existing model

Mandy Guo, Qinlan Shen, Yinfei Yang, Heming Ge

This paper presents an effective approach for parallel corpus mining using bilingual sentence embeddings. Our embedding models are trained to produce similar representations exclusively for bilingual sentence pairs that are translations of each other. This is achieved using a novel training method that introduces hard negatives consisting of sentences that a

D. M. Myers, S. Mukherjee, J. Beaumariage, M. Steger

The transport distance of excitons in exciton-polariton systems has previously been assumed to be very small ($\lesssim 1~μ$m). The sharp spatial profiles observed when generating polaritons by non-resonant optical excitation show that this assumption is generally true. In this paper, however, we show that the transport distances of excitons in two-dimension

Lukas Emmert, Rupert L. Frank, Tobias König

We consider the liquid drop model for nuclei interacting with a neutralizing homogeneous background of electrons. The regime we are interested in is when the fraction between the electronic and the nuclear charge density is small. We show that in this dilute limit the thermodynamic ground state energy is given to leading order by that of an isolated nucleus.

Corentin Fierobe

On an elliptic billard, we study a complex reflexion law introduced by A. Glutsyuk in order to state that the locus of the circumcenters of triangular orbits is an ellipse.

Brent Cody

Hellsten \cite{MR2026390} gave a characterization of $Π^1_n$-indescribable subsets of a $Π^1_n$-indescribable cardinal in terms of a natural filter base: when $κ$ is a $Π^1_n$-indescribable cardinal, a set $S\subseteqκ$ is $Π^1_n$-indescribable if and only if $S\cap C\neq\emptyset$ for every $n$-club $C\subseteq κ$. We generalize Hellsten&#39;s characterizat

Youness Mansar

This work describes our winning solution for the Chalearn LAP In-painting Competition Track 3 - Fingerprint Denoising and In-painting. The objective of this competition is to reduce noise, remove the background pattern and replace missing parts of fingerprint images in order to simplify the verification made by humans or third-party software. In this paper,

Tingran Gao, Shahar Z. Kovalsky, Doug M. Boyer, Ingrid Daubechies

We demonstrate applications of the Gaussian process-based landmarking algorithm proposed in [T. Gao, S.Z. Kovalsky, and I. Daubechies, SIAM Journal on Mathematics of Data Science (2019)] to geometric morphometrics, a branch of evolutionary biology centered at the analysis and comparisons of anatomical shapes, and compares the automatically sampled landmarks

F. Damiani, L. Prisinzano, I. Pillitteri, G. Micela

Sco OB2 is the nearest OB association, extending over approximately 2000 sq.deg. on the sky. Only its brightest members are already known (from Hipparcos) across its entire size, while studies of its lower-mass population refer only to small portions of its extent. In this work we exploit the capabilities of Gaia DR2 measurements to search for Sco OB2 member

ATLAS Collaboration

A search for new phenomena in events with two same-charge leptons or three leptons and jets identified as originating from $b$-quarks in a data sample of 36.1 fb$^{-1}$ of $pp$ collisions at $\sqrt{s}= 13$ TeV recorded by the ATLAS detector at the Large Hadron Collider is reported. No significant excess is found and limits are set on vector-like quark, four-

Jan F. Haase, Andrea Smirne, Jan Kołodyński, Rafał Demkowicz-Dobrzański

The laws of quantum mechanics allow to perform measurements whose precision supersedes results predicted by classical parameter estimation theory. That is, the precision bound imposed by the central limit theorem in the estimation of a broad class of parameters, like atomic frequencies in spectroscopy or external magnetic field in magnetometry, can be overco

Hua-Bi Zeng, Hai-Qing Zhang

We study the critical exponents in the universal scaling laws of a holographic non-equilibrium steady state nearby its critical point of phase transition, which is driven by an AC electric field sitting in the boundary of the bulk. The applied electric filed drives the initial superconducting state into a non-equilibrium steady state with vanishing condensat

Jie Chen, Ronny Luss

Stochastic gradient descent (SGD), which dates back to the 1950s, is one of the most popular and effective approaches for performing stochastic optimization. Research on SGD resurged recently in machine learning for optimizing convex loss functions and training nonconvex deep neural networks. The theory assumes that one can easily compute an unbiased gradien

J. Bernabeu, A. Segarra

CP asymmetries for neutrino oscillations in matter can be disentangled into the matter-induced CPT-odd (T-invariant) component and the genuine T-odd (CPT-invariant) component. For their understanding in terms of the relevant ingredients, we develop a new perturbative expansion in both $Δm^2_{21},\, |a| \ll |Δm^2_{31}|$ without any assumptions between $Δm^2_{

Eric Larsen, Sébastien Lachapelle, Yoshua Bengio, Emma Frejinger

This paper offers a methodological contribution at the intersection of machine learning and operations research. Namely, we propose a methodology to quickly predict expected tactical descriptions of operational solutions (TDOSs). The problem we address occurs in the context of two-stage stochastic programming where the second stage is demanding computational

Carles Sánchez, Gary M. Bernstein

Powerful current and future cosmological constraints using high precision measurements of the large-scale structure of galaxies and its weak gravitational lensing effects rely on accurate characterization of the redshift distributions of the galaxy samples using only broadband imaging. We present a framework for constraining both the redshift probability dis

Alexander Moroz, Andrey E. Miroshnichenko

Recently developed general constraint polynomial approach is shown to replace a set of algebraic equations of the functional Bethe Ansatz method by a single polynomial constraint. As the proof of principle, the usefulness of the method is demonstrated for a number of quasi-exactly solvable (QES) potentials of the Schrödinger equation, such as two different s

Alexander Zhdanok

In this paper, we study Markov chains (MC) on topological spaces within the framework of the operator approach. We extend the Markov operator from the space of countably additive measures to the space of finitely additive measures. Cesaro means for a Markov sequence of measures and their asymptotic behavior in the weak topology are considered. It is proved e

Matteo Escudé, Ludvig Sinander

A strictly strategy-proof mechanism is one that asks agents to use strictly dominant strategies. In the canonical one-dimensional mechanism design setting with private values, we show that strict strategy-proofness is equivalent to strict monotonicity plus the envelope formula, echoing a well-known characterisation of (weak) strategy-proofness. A consequence

Antonio F. Galvao, Jiaying Gu, Stanislav Volgushev

Nonlinear panel data models with fixed individual effects provide an important set of tools for describing microeconometric data. In a large class of such models (including probit, proportional hazard and quantile regression to name just a few) it is impossible to difference out individual effects, and inference is usually justified in a `large n large T&#39

Xiang-Yu Li, Axel Brandenburg, Gunilla Svensson, Nils Haugen

We investigate the effect of turbulence on the combined condensational and collisional growth of cloud droplets by means of high resolution direct numerical simulations of turbulence and a superparticle approximation for droplet dynamics and collisions. The droplets are subject to turbulence as well as gravity, and their collision and coalescence efficiencie

Louis Carlier, Joachim Kock

We introduce a notion of antipode for monoidal (complete) decomposition spaces, inducing a notion of weak antipode for their incidence bialgebras. In the connected case, this recovers the usual notion of antipode in Hopf algebras. In the non-connected case it expresses an inversion principle of more limited scope, but still sufficient to compute the Möbius f

Koen van den Dungen

We improve our previous results on indefinite Kasparov modules, which provide a generalisation of unbounded Kasparov modules modelling non-symmetric and non-elliptic (e.g. hyperbolic) operators. In particular, we can weaken the assumptions that are imposed on indefinite Kasparov modules. Using a new theorem by Lesch and Mesland on the self-adjointness and re

Christian Gleissner, Roberto Pignatelli, Carlos Rito

We give an algorithm that, for a given value of the geometric genus $p_g,$ computes all regular product-quotient surfaces with abelian group that have at most canonical singularities and have canonical system with at most isolated base points. We use it to show that there are exactly two families of such surfaces with canonical map of degree $32$. We also co

Maya Olszewski, Jeff Meder, Emmanuel Kieffer, Raphaël Bleuse

Chaotic attractors are solutions of deterministic processes, of which the topology can be described by templates. We consider templates of chaotic attractors bounded by a genus-1 torus described by a linking matrix. This article introduces a novel and unique tool to validate a linking matrix, to optimize the compactness of the corresponding template and to d

Christian A. Yates, George Chappelle

There are numerous scenarios in which populations of cells migrate in crowded environments. Typical examples include wound healing, cancer growth and embryo development. In these crowded environments cells are able to interact with each other in a variety of ways. These include excluded volume interactions, adhesion, repulsion, cell signalling, pushing and p

Fabian Guignard, Michele Lovallo, Mohamed Laib, Jean Golay

In this paper, the time dynamics of the daily means of wind speed measured in complex mountainous regions are investigated. For 293 measuring stations distributed over all Switzerland, the Fisher information measure and the Shannon entropy power are calculated. The results reveal a clear relationship between the computed measures and both the elevation of th

Guido Gherardi, Paolo Maffezioli, Eugenio Orlandelli

We prove a generalization of Maehara&#39;s lemma to show that the extensions of classical and intuitionistic first-order logic with a special type of geometric axioms, called singular geometric axioms, have Craig&#39;s interpolation property. As a corollary, we obtain a direct proof of interpolation for (classical and intuitionistic) first-order logic with i

Carlos Perez-Delgado, Sai Vinjanampathy

Quantum algorithms that can speed up certain tasks, such as factorisation and unstructured search, have driven a decades-long development of quantum computers and quantum technologies. Yet, outside specialized applications, quantum computers are believed to offer no advantage over classical computers. Here, we present a method which exploits quantum effects

N. D. Tsigkri-DeSmedt, I. Koulierakis, G. Karakos, A. Provata

The effects of nonlocal and reflecting connectivities have been previously investigated in coupled Leaky Integrate-and-Fire (LIF) elements, which assimilate the exchange of electrical signals between neurons. In this work we investigate the effect of diagonal coupling inspired by findings in brain neuron connectivity. Multi-chimera states are reported both f

S. A. Bonometto, R. Mainini, M. Mezzetti

Large primordial Black Hole (PBH) formation is enhanced if strongly coupled scalar and spinor fields ($Φ$ and $ψ$) are a stable cosmic component since the primeval radiative expansion (SCDEW models). In particular, we show that PBH formation is easier at a specific time, i.e., when the asymptotic mass $m_H$, acquired by the $ψ$ field at the higgs scale, beco

Andrea Esuli, Lucas May Petry, Chiara Renso, Vania Bogorny

Semantic trajectories are high level representations of user movements where several aspects related to the movement context are represented as heterogeneous textual labels. With the objective of finding a meaningful similarity measure for semantically enriched trajectories, we propose Traj2User, a Word2Vec-inspired method for the generation of a vector repr

Christopher P Barrington-Leigh

This paper describes a fundamental and empirically conspicuous problem inherent to surveys of human feelings and opinions in which subjective responses are elicited on numerical scales. The paper also proposes a solution. The problem is a tendency by some individuals -- particularly those with low levels of education -- to simplify the response scale by cons

Filippo Cesi

The Laplacian of a (weighted) Cayley graph on the Weyl group $W(B_n)$ is a $N\times N$ matrix with $N = 2^n n!$ equal to the order of the group. We show that for a class of (weighted) generating sets, its spectral gap (lowest nontrivial eigenvalue), is actually equal to the spectral gap of a $2n \times 2n$ matrix associated to a $2n$-dimensional permutation

Tobias Grafke

Rare transitions in stochastic processes can often be rigorously described via an underlying large deviation principle. Recent breakthroughs in the classification of reversible stochastic processes as gradient flows have led to a connection of large deviation principles to a generalized gradient structure. Here, we show that, as a consequence, metastable tra