November 2018 arXiv papers — page 44

Sean MacAvaney, Andrew Yates, Arman Cohan, Luca Soldaini

Many questions cannot be answered simply; their answers must include numerous nuanced details and additional context. Complex Answer Retrieval (CAR) is the retrieval of answers to such questions. In their simplest form, these questions are constructed from a topic entity (e.g., `cheese') and a facet (e.g., `health effects'). While topic matching has been tho

Iain Findlay

By interchanging the roles of the space and time coordinates, we describe a dual construction of the isotropic Landau-Lifshitz model, providing equal-space Poisson brackets and dual Hamiltonians conserved with respect to space-evolution. This construction is built in the Lax/zero-curvature formalism, where the duality between the space and time dependencies

Yacouba Boubacar Maïnassara, Othman Kadmiri, Bruno Saussereau

It is now widely accepted that, to model the dynamics of daily financial returns, volatility models have to incorporate the so-called leverage effect. We derive the asymptotic behaviour of the squared residuals autocovariances for the class of asymmetric power GARCH model when the power is unknown and is jointly estimated with the model's parameters. We then

Xin Zhu, Yang Yang, Xin-Dian Liu, Zhi-Qing Li

The transport properties and optical transmittance and absorption spectra for the nostoichiometric amorphous Indium Gallium Zinc Oxide (a-IGZO) films with Gallium and Zinc deficiencies are investigated. The resistivity and carrier concentration variation with temperature both reveal that the films possess degenerate semiconductor (or metal) characteristics.

Belén Tercero, Sara Cuadrado, Alicia López, Nathalie Brouillet

We investigate the chemical segregation of complex O-bearing species (including the largest and most complex ones detected to date in space) towards Orion KL, the closest high-mass star-forming region. The molecular line images obtained using the ALMA science verification data reveal a clear segregation of chemically related species depending on their differ

Etai Littwin, Lior Wolf

Normalization techniques play an important role in supporting efficient and often more effective training of deep neural networks. While conventional methods explicitly normalize the activations, we suggest to add a loss term instead. This new loss term encourages the variance of the activations to be stable and not vary from one random mini-batch to the nex

Xavier Brumwell, Paul Sinz, Kwang Jin Kim, Yue Qi

A general machine learning architecture is introduced that uses wavelet scattering coefficients of an inputted three dimensional signal as features. Solid harmonic wavelet scattering transforms of three dimensional signals were previously introduced in a machine learning framework for the regression of properties of small organic molecules. Here this approac

Alon Shoshan, Roey Mechrez, Lihi Zelnik-Manor

One of the key ingredients for successful optimization of modern CNNs is identifying a suitable objective. To date, the objective is fixed a-priori at training time, and any variation to it requires re-training a new network. In this paper we present a first attempt at alleviating the need for re-training. Rather than fixing the network at training time, we

Khyatti Gupta, Sonam Damani, Kedhar Nath Narahari

Jewelry has been an integral part of human culture since ages. One of the most popular styles of jewelry is created by putting together precious and semi-precious stones in diverse patterns. While technology is finding its way in the production process of such jewelry, designing it remains a time-consuming and involved task. In this paper, we propose a uniqu

Stéphane Fischler, Tanguy Rivoal

Given any non-polynomial $G$-function $F(z)=\sum_{k=0}^\infty A_k z^k$ of radius of convergence $R$ and in the kernel a $G$-operator $L_F$, we consider the $G$-functions $F_n^{[s]}(z)=\sum_{k=0}^\infty \frac{A_k}{(k+n)^s}z^k$ for every integers $s\ge 0$ and $n\ge 1$. These functions can be analytically continued to a domain $\mathcal{D}_F$ star-shaped at $0$

Barbara Plank, Sigrid Klerke, Zeljko Agic

In natural language processing, the deep learning revolution has shifted the focus from conventional hand-crafted symbolic representations to dense inputs, which are adequate representations learned automatically from corpora. However, particularly when working with low-resource languages, small amounts of symbolic lexical resources such as user-generated le

Pierre Touchard

In the spirit of the Ax-Kochen-Ershov principle, we show that in certain cases the burden of a Henselian valued field can be computed in terms of the burden of its residue field and that of its value group. To do so, we first see that the burden of such a field is equal to the burden of its RV-sort. These results are generalisations of a work of Chernikov an

Clémence Prévost, Konstantin Usevich, Pierre Comon, David Brie

We propose a novel approach for hyperspectral super-resolution, that is based on low-rank tensor approximation for a coupled low-rank multilinear (Tucker) model. We show that the correct recovery holds for a wide range of multilinear ranks. For coupled tensor approximation, we propose two SVD-based algorithms that are simple and fast, but with a performance

Naoki Genra, Toshiro Kuwabara

We construct explicitly strong generators of the affine $\mathcal{W}$-algebra $\mathcal{W}^{K-N}(\mathfrak{sl}_N, f_{sub})$ of subregular type $A$. Moreover, we are able to describe the OPEs between them at critical level. We also give a description the affine $\mathcal{W}$-algebra $\mathcal{W}^{-N}(\mathfrak{sl}_N, f_{sub})$ in terms of certain fermionic fi

L. P. M. I. Sampath, M. Hotz, H. B. Gooi, W. Utschick

The day-ahead energy and reserve management with transmission restrictions and voltage security limits is a challenging task for large-scale power systems in the presence of real-time variations caused by the uncertain demand and the fluctuating power output of renewable energy sources (RESs). The proposed formulation in this work supports joint scheduling o

Marian Cors, Oliver Wrede, Anne-Caroline Genix, Dario Anselmetti

We study the swelling and shrinking behavior of core-shell microgels adsorbed on silicon wafers. In these systems, the core is made of cross-linked poly(N isopropylmethacrylamide) and the shell consists of cross linked poly(N-n propylacrylamide). In suspension, these particles exhibit an extended linear swelling behavior in the temperature interval between t

Mark Lacy, Suchetana Chatterjee, Avinanda Chakraborty, Brian Mason

The Sunyaev-Zeldovich Effect (SZE) can be used to detect the hot bubbles in the intergalactic medium blown by energetic winds from AGN and starbursts. By directly constraining the kinetic luminosity, age and total energy of the outflow, it offers the promise of greatly increasing our understanding of the effects of wind feedback on galaxy evolution. Detectin

Michael Roberts, Jack Spencer

Selective segmentation involves incorporating user input to partition an image into foreground and background, by discriminating between objects of a similar type. Typically, such methods involve introducing additional constraints to generic segmentation approaches. However, we show that this is often inconsistent with respect to common assumptions about the

Noga Alon, Clara Shikhelman

For graphs $G$ and $T$, and a family of graphs $\mathcal{F}$ let $\mathrm{ex}(G,T,\mathcal{F})$ denote the maximum possible number of copies of $T$ in an $\mathcal{F}$-free subgraph of $G$. We investigate the algorithmic aspects of calculating and estimating this function. We show that for every graph $T$, finite family $\mathcal{F}$ and constant $\epsilon>0

Hamza Jaffali, Frédéric Holweck

In this paper, we study the nature of entanglement in quantum Grover's and Shor's algorithms. So far, the authors who have been interested in this problem have approached the question quantitatively by introducing entanglement measures (numerical ones most of the time). One can ask a different question: what about a qualitative measure of entanglement ? In o

Yueyun Hu, Bastien Mallein, Michel Pain

To study the depinning transition in the limit of strong disorder, Derrida and Retaux (2014) introduced a discrete-time max-type recursive model. It is believed that for a large class of recursive models, including Derrida and Retaux' model, there is a highly non-trivial phase transition. In this article, we present a continuous-time version of Derrida and R

John Pardon

We briefly survey the Hilbert--Smith Conjecture, and we include a proof of it in dimension two (where it is originally due to Montgomery--Zippin).

Dongdong Chen, Mingming He, Qingnan Fan, Jing Liao

Image dehazing aims to recover the uncorrupted content from a hazy image. Instead of leveraging traditional low-level or handcrafted image priors as the restoration constraints, e.g., dark channels and increased contrast, we propose an end-to-end gated context aggregation network to directly restore the final haze-free image. In this network, we adopt the la

Simon Zihlmann, Péter Makk, Sebastián Castilla, Jörg Gramich

We report on non-equilibrium properties of graphene probed by superconducting tunnel spectroscopy. A hexagonal boron nitride (hBN) tunnel barrier in combination with a superconducting Pb contact is used to extract the local energy distribution function of the quasiparticles in graphene samples in different transport regimes. In the cases where the energy dis

Joseph R. Nelson, Richard J. Needs, Chris J. Pickard

Cazorla et al. [preceding comment] criticize our recent results on the high-PT phase diagram of CaF2 (Phys. Rev. B 95, 054118 (2017)). According to our analysis, Cazorla et al. have not converged their calculations with respect to simulation cell size, undermining the comment's conclusions about both the high-T behaviour of the P-62m-CaF2 polymorph, and the

Gregorio Carullo, Gunnar Riemenschneider, Ka Wa Tsang, Alessandro Nagar

We introduce a novel test of General Relativity in the strong-field regime of a binary black hole coalescence. Combining information coming from Numerical Relativity simulations of coalescing black hole binaries with a Bayesian reconstruction of the gravitational wave signal detected in LIGO-Virgo interferometric data, allows one to test theoretical predicti

Jin-Wei Wang, Xiao-Jun Bi, Peng-Fei Yin, Zhao-Huan Yu

We investigate the effect of fermionic electroweak multiplet dark matter models on the stability of the electroweak vacuum using two-loop renormalization group equations (RGEs) and one-loop matching conditions. Such a treatment is crucial to obtain reliable conclusions, compared with one-loop RGEs and tree-level matching conditions. In addition, we find that

BESIII Collaboration, M. Ablikim, M. N. Achasov, S. Ahmed

The cross section of the process $e^{+} e^{-} \rightarrow K^{+} K^{-}$ is measured at a number of center-of-mass energies $\sqrt{s}$ from 2.00 to 3.08 GeV with the BESIII detector at the Beijing Electron Positron Collider (BEPCII). The results provide the best precision achieved so far. A resonant structure around 2.2 GeV is observed in the cross section lin

Joseph R. Nelson, Richard J. Needs, C. J. Pickard

We recently proposed a high-pressure and high-temperature P-62m-symmetry polymorph for CaF2 on the basis of ab-initio random structure searching and density-functional theory calculations [Phys. Rev. B 95, 054118 (2017)]. We revisit this polymorph using both ab-initio and classical molecular dynamics simulations. The structure undergoes a phase transition to

Marc Bosch, Kevin Foster, Gordon Christie, Sean Wang

The increasingly common use of incidental satellite images for stereo reconstruction versus rigidly tasked binocular or trinocular coincident collection is helping to enable timely global-scale 3D mapping; however, reliable stereo correspondence from multi-date image pairs remains very challenging due to seasonal appearance differences and scene change. Prom

Yunhui Guo, Honghui Shi, Abhishek Kumar, Kristen Grauman

Transfer learning, which allows a source task to affect the inductive bias of the target task, is widely used in computer vision. The typical way of conducting transfer learning with deep neural networks is to fine-tune a model pre-trained on the source task using data from the target task. In this paper, we propose an adaptive fine-tuning approach, called S

Janne Gröhn

Let $f_1,f_2$ be linearly independent solutions of $f''+Af=0$, where the coefficient $A$ is an analytic function in the open unit disc $\mathbb{D}$ of $\mathbb{C}$. It is shown that many properties of this differential equation can be described in terms of the subharmonic auxiliary function $u=-\log\, (f_1/f_2)^{\#}$. For example, the case when $\sup_{z\in\m

Adara M. Blaga, Antonella Nannicini

We generalize the notion of metallic structure in the pseudo-Riemannian setting, define the metallic Norden structure and study its integrability. We consider metallic maps between metallic manifolds and give conditions under which they are constant. We also construct a metallic natural connection recovering as particular case the Ganchev and Mihova connecti

Ilaria Maccari, Lara Benfatto, Claudio Castellani

We study the effect of uncorrelated random disorder on the temperature dependence of the superfluid stiffness in the two-dimensional classical XY model. By means of a perturbative expansion in the disorder potential, equivalent to the T-matrix approximation, we provide an extension of the effective-medium-theory result able to describe the low-temperature st

Victor Kac, Johan van de Leur

We construct all polynomial tau-functions of the BKP, DKP and MDKP hierarches.

Dhruv Singhal, Jessy Paterson, Dimitri Tainoff, Jacques Richard

The 3$\omega$ method is a dynamic measurement technique developed for determining the thermal conductivity of thin films or semi-infinite bulk materials. A simplified model is often applied to deduce the thermal conductivity from the slope of the real part of the ac temperature amplitude as a function of the logarithm of frequency, which in-turn brings a lim

Saulo Carneiro

It is shown that the postulation of a minimum length for the horizons of a black hole leads to lower bounds for the electric charges and magnetic moments of elementary particles. If the minimum length has the order of the Planck scale, these bounds are given, respectively, by the electronic charge and by $\mu \sim 10^{-21} \mu_B$. The latter implies that the

Ertugrul Basar

The wireless revolution has already started with the specified vision, overall objectives, and the first official 3GPP release of 5th generation (5G) wireless networks. Despite the development of several modern communication technologies, since the beginning of the modern era of digital communications, we have been mostly conveying information by altering th

Dimitri Tainoff, Anaïs Proudhom, Céline Tur, Thierry Crozes

We report the design, elaboration and measurements of an innovative planar thermoelectric (TE) devices made of a large array of small mechanically suspended nanogenerators (nanoTEG). The miniaturized TE generators based on SiN membranes are arranged in series and/or in parallel depending on the expected final resistance adapted to the one of the load. The mi

Christian Wilms, Simone Frintrop

We propose a novel approach for class-agnostic object proposal generation, which is efficient and especially well-suited to detect small objects. Efficiency is achieved by scale-specific objectness attention maps which focus the processing on promising parts of the image and reduce the amount of sampled windows strongly. This leads to a system, which is $33\

Oleg Chalykh, Maxime Fairon

We suggest a Hamiltonian formulation for the spin Ruijsenaars-Schneider system in the trigonometric case. Within this interpretation, the phase space is obtained by a quasi-Hamiltonian reduction performed on (the cotangent bundle to) a representation space of a framed Jordan quiver. For arbitrary quivers, analogous varieties were introduced by Crawley-Boevey

Jian-Huang She, Dan Grecu

A new challenge to quantitative finance after the recent financial crisis is the study of credit valuation adjustment (CVA), which requires modeling of the future values of a portfolio. In this paper, following recent work in [Weinan E(2017), Han(2017)], we apply deep learning to attack this problem. The future values are parameterized by neural networks, an

Tatiana Shpakova, Francis Bach, Anton Osokin

We consider the structured-output prediction problem through probabilistic approaches and generalize the "perturb-and-MAP" framework to more challenging weighted Hamming losses, which are crucial in applications. While in principle our approach is a straightforward marginalization, it requires solving many related MAP inference problems. We show that for log

Conor Durkan, George Papamakarios, Iain Murray

Likelihood-free inference refers to inference when a likelihood function cannot be explicitly evaluated, which is often the case for models based on simulators. Most of the literature is based on sample-based `Approximate Bayesian Computation' methods, but recent work suggests that approaches based on deep neural conditional density estimators can obtain sta

Antoine Oustry, Carmen Cardozo, Patrick Panciatici, Didier Henrion

This paper assesses the transient stability of a synchronous machine connected to an infinite bus through the notion of invariant sets. The problem of computing a conservative approximation of the maximal positive invariant set is formulated as a semi-definitive program based on occupation measures and Lasserre's relaxation. An extension of the proposed meth

Alexander Iksanov, Bastien Mallein

L\'evy-type perpetuities being the a.s. limits of particular generalized Ornstein-Uhlenbeck processes are a natural continuous-time generalization of discrete-time perpetuities. These are random variables of the form $S:=\int_{[0,\infty)}e^{-X_{s-}}{\mathrm{d}}Z_s$, where $(X,Z)$ is a two-dimensional L\'evy process, and $Z$ is a drift-free L\'evy process of

Rafael L. Delgado, A. Dobado, D. Espriu, C. Garcia-Garcia

We study the production of vector resonances at the LHC via $WZ$ scattering processes and explore the sensitivities to these resonances for the expected future LHC luminosities. The electroweak chiral Lagrangian and the Inverse Amplitude Method (IAM) are used for analyzing a dynamically generated vector resonance, whose origin would be the (hypothetically st

Yunming Xiao, Bin Wu

Cooperation is ubiquitous across all levels of biological systems ranging from microbial communities to human societies. It, however, seemingly contradicts the evolutionary theory, since cooperators are exploited by free-riders and thus are disfavored by natural selection. Many studies based on evolutionary game theory have tried to solve the puzzle and figu

Maxime Fairon

We study multiplicative quiver varieties associated to specific extensions of cyclic quivers with $m\geq 2$ vertices. Their global Poisson structure is characterised by quasi-Hamiltonian algebras related to these quivers, which were studied by Van den Bergh for an arbitrary quiver. We show that the spaces are generically isomorphic to the case $m=1$ correspo

Dmytro Pavlichenko, Diego Rodriguez, Max Schwarz, Christian Lenz

Autonomous dual-arm manipulation is an essential skill to deploy robots in unstructured scenarios. However, this is a challenging undertaking, particularly in terms of perception and planning. Unstructured scenarios are full of objects with different shapes and appearances that have to be grasped in a very specific manner so they can be functionally used. In

Yalong Cao, Jacob Gross, Dominic Joyce

This paper concerns orientability of moduli spaces of Spin(7)-instantons on compact 8-manifolds $X$ with Spin(7)-structure for the Lie groups SU($m$) and U($m$), and of moduli spaces of coherent sheaves on Calabi-Yau 4-folds. Such orientations are needed to define enumerative invariants 'counting' Spin(7) instantons, or coherent sheaves on Calabi-Yau 4-folds

Peter Gangl, Samuel Amstutz

The topological derivative represents the sensitivity of a domain-dependent functional with respect to a local perturbation of the domain and is a valuable tool in topology optimization. Motivated by an application from electrical engineering, we derive the topological derivative for an optimization problem which is constrained by the quasilinear equation of

Roland Schnaubelt, Martin Spitz

We establish a comprehensive local wellposedness theory for the quasilinear Maxwell system with interfaces in the space of piecewise $H^m$-functions for $m \geq 3$. The system is equipped with instantaneous and piecewise regular material laws and perfectly conducting interfaces and boundaries. We also provide a blow-up criterion in the Lipschitz norm and pro

Halil Mutuk

In this work, we obtained energy levels of one dimensional quartic anharmonic oscillator by using neural network system. Quartic anharmonic oscillator is a very important tool in quantum mechanics and also in quantum field theory. Our results are in good agreement in high accuracy with the reference studies.

Alexandra Kozyreva, Ehud Nakar, Roni Waldman

In the present study, we systematically explore the effect of the radioactive 56Ni and its mixing properties in the ejecta on the plateau of Type IIP supernovae (SNe). We evaluate the importance of 56Ni in shaping light curves of SNe IIP by simulating light curves for two red supergiant models using different amounts of 56Ni and with different types of mixin

Seishiro Ono, Youichi Yanase, Haruki Watanabe

The systematic diagnosis of band topology enabled by the method of "symmetry indicators" underlies the recent advances in the search for new materials realizing topological crystalline insulators. Such an efficient method has been missing for superconductors because the band structure in the superconducting phase is not usually available. In this work, we es

Cătălina Cangea, Arturas Grauslys, Pietro Liò, Francesco Falciani

Classifying chemicals according to putative modes of action (MOAs) is of paramount importance in the context of risk assessment. However, current methods are only able to handle a very small proportion of the existing chemicals. We address this issue by proposing an integrative deep learning architecture that learns a joint representation from molecular stru

Francois Gelis, Naoto Tanji

In the McLerran-Venugopalan model, correlators of Wilson lines are given by an average over a Gaussian ensemble of random color sources. In numerical implementations, these averages are approximated by a Monte-Carlo sampling. In this paper, we study the statistical error made with such a sampling, with emphasis on the momentum dependence of this error. Using

Yair Shenfeld, Ramon van Handel

At the heart of convex geometry lies the observation that the volume of convex bodies behaves as a polynomial. Many geometric inequalities may be expressed in terms of the coefficients of this polynomial, called mixed volumes. Among the deepest results of this theory is the Alexandrov-Fenchel inequality, which subsumes many known inequalities as special case

John Haslegrave, Vladas Sidoravicius, Laurent Tournier

We consider ballistic annihilation, a model for chemical reactions first introduced in the 1980's physics literature. In this particle system, initial locations are given by a renewal process on the line, motions are ballistic - i.e. each particle is assigned an i.i.d. constant velocity - and collisions between pairs of particles result in mutual annihilatio

Masato Arai, Filip Blaschke, Minoru Eto, Norisuke Sakai

It is important to obtain (nearly) massless localized modes for the low-energy four-dimensional effective field theory in the brane-world scenario. We propose a mechanism for bosonic zero modes using the field-dependent kinetic function in the classical field theory set-up. As a particularly simple case, we consider a domain wall in five dimensions, and show

B. B. Baizakov, A. Bouketir, S. M. Al-Marzoug, H. Bahlouli

Modulation instability (MI) in continuous media described by a system of two cubic-quintic nonlinear Schr\"odinger equations (NLSE) has been investigated with a focus on revealing the contribution of the quintic nonlinearity to the development of MI in its linear and nonlinear stages. For the linear stage we derive analytic expression for the MI gain spectru

Cyril Bénézet, Jérémie Bonnefoy, Jean-François Chassagneux, Shuoqing Deng

In this work, we present a numerical method based on a sparse grid approximation to compute the loss distribution of the balance sheet of a financial or an insurance company. We first describe, in a stylised way, the assets and liabilities dynamics that are used for the numerical estimation of the balance sheet distribution. For the pricing and hedging model

Joewie J. Koh, Barton Rhodes

Domain generation algorithms (DGAs) are frequently employed by malware to generate domains used for connecting to command-and-control (C2) servers. Recent work in DGA detection leveraged deep learning architectures like convolutional neural networks (CNNs) and character-level long short-term memory networks (LSTMs) to classify domains. However, these classif

Sandip Mandal, D. V. Khakhar

We study the flow of equal-volume binary granular mixtures of spheres and dumbbells with different aspect ratios down a rough inclined plane, using the discrete element method. We consider two types of mixtures -- in the first type the particles of the two species have equal volume but different aspect ratios (EV) and in the second type they have variable vo

B. V. Kryzhanovsky, L. B. Litinskii

For a 1D Ising model, we obtained an exact expression for the spectral density in an n-vicinity of the ground state and explained why our n-vicinity method with the Gaussian approximation of the spectral density did not applicable in this case. We also found an analytical expression for the distribution of magnetization at an arbitrary temperature. When the

Giovanni Abramo, Ciriaco Andrea D'Angelo, Flavia Di Costa, Marco Solazzi

This work investigates public-private research collaboration between Italian universities and domestic industry, applying a bibliometric type of approach. The study is based on an exhaustive listing of all co-authored publications in international journals that are jointly realized by Italian university scientists and researchers in the private sector: this

Shahin Pourbahrami

Making a simple model by choosing a limited number of features with the purpose of reducing the computational complexity of the algorithms involved in classification is one of the main issues in machine learning and data mining. The aim of Feature Selection (FS) is to reduce the number of redundant and irrelevant features and improve the accuracy of classifi

David Thomas, Ryan Hunt, Neil Drummond, Manus Hayne

Excitonic complexes in type-II quantum-ring heterostructures may be considered as artificial atoms due to the confinement of only one charge-carrier type in an artificial nucleus. Binding energies of excitons, trions, and biexcitons in these nanostructures are then effectively ionization energies of these artificial atoms. The binding energies reported here

Sven Bachmann, Alex Bols, Wojciech De Roeck, Martin Fraas

We relate explicitly the adiabatic curvature -- in flux space -- of an interacting Hall insulator with nondegenerate ground state to various linear response coefficients, in particular the Kubo response and the adiabatic response. The flexibility of the setup, allowing for various driving terms and currents, reflects the topological nature of the adiabatic c

Kazem Bitaghsir Fadafan, Farideh Kazemian, Andreas Schmitt

We study dense nuclear and quark matter within a single microscopic approach, namely the holographic Sakai-Sugimoto model. Nuclear matter is described via instantons in the bulk, and we show that instanton interactions are crucial for a continuous connection of chirally broken and chirally symmetric phases. The continuous path from nuclear to quark matter in

Libing Huang, Alexandru Kristály, Wei Zhao

The paper is devoted to sharp uncertainty principles (Heisenberg-Pauli-Weyl, Caffarelli-Kohn-Nirenberg and Hardy inequalities) on forward complete Finsler manifolds endowed with an arbitrary measure. Under mild assumptions, the existence of extremals corresponding to the sharp constants in the Heisenberg-Pauli-Weyl and Caffarelli-Kohn-Nirenberg inequalities

Giovanni Abramo, Ciriaco Andrea D'Angelo, Alessandro Caprasecca

The state of the art on the issue of sex differences in research efficiency agrees in recognizing higher performances for males, however there are divergences in explaining the possible causes. One of the causes advanced is that there are sex differences in the availability of aptitude at the "high end". By comparing sex differences in concentration and perf

Irene Giacomelli, Somesh Jha, Ross Kleiman, David Page

We study the problem of privacy-preserving machine learning (PPML) for ensemble methods, focusing our effort on random forests. In collaborative analysis, PPML attempts to solve the conflict between the need for data sharing and privacy. This is especially important in privacy sensitive applications such as learning predictive models for clinical decision su

Alexandre Sabard, Tanvir Hussain

The heat-treatment of a number of gas atomised aluminium alloys prior to cold spraying recently showed that the resultant microstructural modification was accompanied by an improvement in deposition; however, the relationship between the microstructural homogenisation occurring after recrystallisation and the increase in deposition efficiency and particle-pa

F. Cappuzzello, C. Agodi, M. Cavallaro, D. Carbone

The article describes the main achievements of the NUMEN project together with an updated and detailed overview of the related R&D activities and theoretical developments. NUMEN proposes an innovative technique to access the nuclear matrix elements entering the expression of the lifetime of the double beta decay by cross section measurements of heavy-ion ind

Ovidiu I. Patu, Andreas Klumper

We investigate the one-dimensional mixture of scalar bosons and spin polarized fermions interacting through a $\delta$-function potential. Using a thermodynamic description derived by employing a lattice embedding of the continuum model and the quantum transfer matrix method we perform a detailed analysis of the contact and quantum critical behaviour. We sho

Mikhail Karchevskiy, Insaf Ashrapov, Leonid Kozinkin

One of the most important applications of seismic reflection is the hydrocarbon exploration which is closely related to salt deposits analysis. This problem is very important even nowadays due to it's non-linear nature. Taking into account the recent developments in deep learning networks TGS-NOPEC Geophysical Company hosted the Kaggle competition for salt d

Giovanni Abramo, Ciriaco Andrea D'Angelo

We are witnessing a rapid trend towards the adoption of exercises for evaluation of national research systems, generally based on the peer review approach. They respond to two main needs: stimulating higher efficiency in research activities by public laboratories, and realizing better allocative efficiency in government funding of such institutions. However

Abhijnan Chakraborty, Gourab K Patro, Niloy Ganguly, Krishna P. Gummadi

To help their users to discover important items at a particular time, major websites like Twitter, Yelp, TripAdvisor or NYTimes provide Top-K recommendations (e.g., 10 Trending Topics, Top 5 Hotels in Paris or 10 Most Viewed News Stories), which rely on crowdsourced popularity signals to select the items. However, different sections of a crowd may have diffe

Dongsu Bak, Seulgi Kim, Hyunsoo Min, Jeong-Pil Song

We study time evolution of Schrodinger-Newton system using the self-consistent Crank-Nicolson method to understand the dynamical characteristics of nonlinear systems. Compactifying the radial coordinate by a new one, which brings the spatial infinity to a finite value, we are able to impose the boundary condition at infinity allowing for a numerically exact

Ramon Antoine, Francesc Perera, Hannes Thiel

We previously showed that abstract Cuntz semigroups form a closed symmetric monoidal category. This automatically provides additional structure in the category, such as a composition and an external tensor product, for which we give concrete constructions in order to be used in applications. We further analyse the structure of not necessarily commutative Cu-

Rohitash Chandra, Konark Jain, Arpit Kapoor, Ashray Aman

Due to the need for robust uncertainty quantification, Bayesian neural learning has gained attention in the era of deep learning and big data. Markov Chain Monte-Carlo (MCMC) methods typically implement Bayesian inference which faces several challenges given a large number of parameters, complex and multimodal posterior distributions, and computational compl

Ioannis Karatzas, Walter Schachermayer, Bertram Tschiderer

We revisit the variational characterization of diffusion as entropic gradient flux and provide for it a probabilistic interpretation based on stochastic calculus. It was shown by Jordan, Kinderlehrer, and Otto that, for diffusions of Langevin-Smoluchowski type, the Fokker-Planck probability density flow minimizes the rate of relative entropy dissipation, as

Franziska Stief, Johannes Löhner-Böttcher, Wolfgang Schmidt, Tilo Steinmetz

Granular convective motions reach into the lower solar atmosphere, typically causing photospheric spectral lines to exhibit a differential line shift. This Doppler shift to shorter wavelength is commonly known as convective blueshift. We performed systematic observations of the quiet Sun with the Laser Absolute Reference Spectrograph (LARS) at the German Vac

Sandhya Choubey, Debajyoti Dutta, Dipyaman Pramanik

Active-sterile neutrino mixing is known to affect the neutrino oscillation probabilities at both short as well as long-baselines. In particular, constraints on active-sterile neutrino oscillation parameters can be obtained from long-baseline experiments such as T2HK and DUNE. We present here existence of fake solution in the appearance channel for the 3+1 sc

Mina Baghani, Saeedeh Parsaeefard, Mahsa Derakhshani, Walid Saad

In this paper, facilitated via the flexible software defined structure of the radio access units in 5G, we propose a novel dynamic multiple access technology selection among orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) techniques for each subcarrier. For this setup, we formulate a joint resource allocation problem where a new se

Julius Strake, Franz Kaiser, Farnaz Basiri, Henrik Ronellenfitsch

The failure of a single link can degrade the operation of a supply network up to the point of complete collapse. Yet, the interplay between network topology and locality of the response to such damage is poorly understood. Here, we study how topology affects the redistribution of flow after the failure of a single link in linear flow networks with a special

Mauro Cirio, Nathan Shammah, Neill Lambert, Simone De Liberato

The ground state of a cavity-electron system in the ultrastrong coupling regime is characterized by the presence of virtual photons. If an electric current flows through this system, the modulation of the light-matter coupling induced by this non-equilibrium effect can induce an extra-cavity photon emission signal, even when electrons entering the cavity do

Thiago Dias, Bo-Yu Pan

A symmetric planar central configuration of the Newtonian six-body problem $x$ is called cross central configuration if there are precisely four bodies on a symmetry line of $x$. We use complex algebraic geometry and Groebner basis theory to prove that for a generic choice of positive real masses $m_1,m_2,m_3,m_4,m_5=m_6$ there is a finite number of cross ce

Elizaveta V. Melik-Gaykazyan, Kirill L. Koshelev, Jae-Hyuck Choi, Sergey S. Kruk

We employ structured light for the second-harmonic generation from subwavelength AlGaAs nanoparticles that support both electric and magnetic multipolar Mie resonances. The vectorial structure of the pump beam allows addressing selectively Mie-resonant modes and control the strength of the generated nonlinear fields. We observe experimentally the enhancement

Yupeng Li, Chao An, Chenqiang Hua, Xuliang Chen

Topological superconductivity with Majorana bound states, which are critical to implement nonabelian quantum computation, may be realized in three-dimensional semimetals with nontrivial topological feature, when superconducting transition occurs in the bulk. Here, we report pressure-induced superconductivity in a transition-metal dipnictide NbAs2. The emerge

Juha Vaara, Michael V. Romalis

Indirect spin-spin interactions between nuclei bound in a molecule are well-known in nuclear magnetic resonance, but such interactions between unbound atoms are less well studied and are often assumed to be zero. We present the first precision calculation of this interaction between 129Xe and 3He nuclei in a gas. Relativistic, state-of-the-art electronic str

Marco Franciosi

We study families of scrolls containing a given rational curve and families of rational curves contained in a fixed scroll via a stratification in terms of the degree of the induced map onto P^1 and we prove that there is no rational normal scroll of minimal degree and of dimension <=n/2 containing a general binary curve inP^n.

Vedran Dunjko, Jacob M. Taylor, Hans J. Briegel

In recent times, there has been much interest in quantum enhancements of machine learning, specifically in the context of data mining and analysis. Reinforcement learning, an interactive form of learning, is, in turn, vital in artificial intelligence-type applications. Also in this case, quantum mechanics was shown to be useful, in certain instances. Here, w

R. Bezrukavnikov, M. Rovinsky

Let $F$ be an infinite division ring, $V$ be a left $F$-vector space, $r>0$ be an integer. We study the structure of the representation of the linear group $\mathrm{GL}_F(V)$ in the vector space of formal finite linear combinations of $r$-dimensional vector subspaces of $V$ with coefficients in a field $K$. This gives a series of natural examples of irreduci

Raghavendra Selvan, Thomas Kipf, Max Welling, Antonio Garcia-Uceda Juarez

Graph refinement, or the task of obtaining subgraphs of interest from over-complete graphs, can have many varied applications. In this work, we extract trees or collection of sub-trees from image data by, first deriving a graph-based representation of the volumetric data and then, posing the tree extraction as a graph refinement task. We present two methods

Siddharth Barman, Sanath Kumar Krishnamurthy

We study Fisher markets that admit equilibria wherein each good is integrally assigned to some agent. While strong existence and computational guarantees are known for equilibria of Fisher markets with additive valuations, such equilibria, in general, assign goods fractionally to agents. Hence, Fisher markets are not directly applicable in the context of ind

Étienne Fouvry, Maksym Radziwiłł

We show that if an essentially arbitrary sequence supported on an interval containing $x$ integers, is convolved with a tiny Siegel-Walfisz-type sequence supported on an interval containing $\exp((\log x)^{\varepsilon})$ integers then the resulting multiplicative convolution has (in a weak sense) level of distribution $x^{1/2 + 1/66 - \varepsilon}$ as $x$ go

Veronica Tozzo, Federico Tomasi, Margherita Squillario, Annalisa Barla

Complex systems may contain heterogeneous types of variables that interact in a multi-level and multi-scale manner. In this context, high-level layers may considered as groups of variables interacting in lower-level layers. This is particularly true in biology, where, for example, genes are grouped in pathways and two types of interactions are present: pathw