June 2020 arXiv papers — page 21

Steffen Czolbe, Oswin Krause, Ingemar Cox, Christian Igel

To train Variational Autoencoders (VAEs) to generate realistic imagery requires a loss function that reflects human perception of image similarity. We propose such a loss function based on Watson's perceptual model, which computes a weighted distance in frequency space and accounts for luminance and contrast masking. We extend the model to color images,

Zitian Chen, Zhiqiang Shen, Jiahui Yu, Erik Learned-Miller

After learning a new object category from image-level annotations (with no object bounding boxes), humans are remarkably good at precisely localizing those objects. However, building good object localizers (i.e., detectors) currently requires expensive instance-level annotations. While some work has been done on learning detectors from weakly labeled samples

Francesco Locatello, Dirk Weissenborn, Thomas Unterthiner, Aravindh Mahendran

Learning object-centric representations of complex scenes is a promising step towards enabling efficient abstract reasoning from low-level perceptual features. Yet, most deep learning approaches learn distributed representations that do not capture the compositional properties of natural scenes. In this paper, we present the Slot Attention module, an archite

DUNE Collaboration, B. Abi, R. Acciarri, M. A. Acero

The Deep Underground Neutrino Experiment is a next-generation neutrino oscillation experiment that aims to measure $CP$-violation in the neutrino sector as part of a wider physics program. A deep learning approach based on a convolutional neural network has been developed to provide highly efficient and pure selections of electron neutrino and muon neutrino

Peter H. Williams, Gustavo Pérez-Segurana, Ian R. Bailey, Sara Thorin

Electron bunch compressors formed of achromat arcs have a natural advantage over the more commonly used chicane compressors in that linearisation of the longitudinal phase space is of the correct sign to compensate for the curvature imprinted by rf acceleration. Here we extend the utility of arc compressors to enable variation of the longitudinal compaction

Alexander Pitchford, Andrey A. Rakhubovsky, Rick Mukherjee, Darren W. Moore

Nonclassical correlations provide a resource for many applications in quantum technology as well as providing strong evidence that a system is indeed operating in the quantum regime. Optomechanical systems can be arranged to generate nonclassical correlations (such as quantum entanglement) between the mechanical mode and a mode of travelling light. Here we p

Ping Zhou, Shing-Chi Leung, Zhiyuan Li, Ken'ichi Nomoto

Recent observations have shown a remarkable diversity of observational behaviors and explosion mechanisms in thermonuclear supernovae (SNe). An emerging class of peculiar thermonuclear SNe, called Type Iax, show photometric and spectroscopic behaviors distinct from normal Type Ia. Their origin remains highly controversial, but pure turbulent deflagration of

Mohammed Moucouf

We provide a novel recursive method, which does not require any assumption, to compute the entries of the kth power of a semicirculant matrix. As an application, a method for computing the entries of the kth power of r-circulant matrices is also presented.

Vaibhav Tiwari

The population analysis of compact binaries involves the reconstruction of some of the gravitational wave (GW) signal parameters, such as, the mass and the spin distribution, that gave rise to the observed data. This article introduces VAMANA, which reconstructs the binary black hole population using a mixture model and facilitates excellent density measurem

Angelo Esposito, Elena G. Ferreiro, Alessandro Pilloni, Antonio D. Polosa

The structure of exotic resonances that do not trivially fit the usual quark model expectations has been a matter of intense scientific debate during the last two decades. A possible way of estimating the size of these states is to study their behavior when immersed in QCD matter. Recently, LHCb has measured the relative abundance of the exotic $X(3872)$ ove

Alex Barron, Michael Christ, Benoit Pausader

We prove a sharp, global-in-time Strichartz estimate for the Schrödinger equation on the cylinder $\mathbb{R}\times\mathbb{T}$.

Julien Barrier, Piranavan Kumaravadivel, Roshan Krishna-Kumar, L. A. Ponomarenko

In quantizing magnetic fields, graphene superlattices exhibit a complex fractal spectrum often referred to as the Hofstadter butterfly. It can be viewed as a collection of Landau levels that arise from quantization of Brown-Zak minibands recurring at rational ($p/q$) fractions of the magnetic flux quantum per superlattice unit cell. Here we show that, in gra

P. Danev, D. Bakalov, V. I. Korobov, S. Schiller

Molecular hydrogen ions are of metrological relevance due to the possibility of precise theoretical evaluation of their spectrum and of external-field-induced shifts. In homonuclear molecular ions the electric dipole $E1$ transitions are strongly suppressed, and of primary laser spectroscopy interest is the electric quadrupole ($E2$) transition spectrum. In

Emanuele Dalsasso, Loïc Denis, Florence Tupin

Speckle reduction is a key step in many remote sensing applications. By strongly affecting synthetic aperture radar (SAR) images, it makes them difficult to analyse. Due to the difficulty to model the spatial correlation of speckle, a deep learning algorithm with self-supervision is proposed in this paper: SAR2SAR. Multi-temporal time series are leveraged an

Joseph W. Cutler, Daniel R. Licata, Norman Danner

A typical way of analyzing the time complexity of functional programs is to extract a recurrence expressing the running time of the program in terms of the size of its input, and then to solve the recurrence to obtain a big-O bound. For recurrence extraction to be compositional, it is also necessary to extract recurrences for the size of outputs of helper fu

Ali Hirsa, Weilong Fu

We investigate solving partial integro-differential equations (PIDEs) using unsupervised deep learning in this paper. To price options, assuming underlying processes follow Levy processes, we require to solve PIDEs. In supervised deep learning, pre-calculated labels are used to train neural networks to fit the solution of the PIDE. In an unsupervised deep le

Ghislain Haine, Denis Matignon, Anass Serhani

The anisotropic and heterogeneous $N$-dimensional wave equation, controlled and observed at the boundary, is considered as a port-Hamiltonian system. A recent structure-preserving mixed Galerkin method is applied, leading directly to a finite-dimensional port-Hamiltonian system: its numerical analysis is carried out in a general framework. Optimal choices of

Yukio Ohsawa, Masaharu Tsubokura

The spreading of virus infection is here simulated over artificial human networks. The real-space urban life of people is modeled as a modified scale-free network with constraints. A scale-free network has been adopted in several studies for modeling on-line communities so far but is modified here for the aim to represent peoples' social behaviors where

Yue Wu, Terry J. Lyons, Kate E. A. Saunders

The availability of mobile technologies has enabled the efficient collection prospective longitudinal, ecologically valid self-reported mood data from psychiatric patients. These data streams have potential for improving the efficiency and accuracy of psychiatric diagnosis as well predicting future mood states enabling earlier intervention. However, missing

Tim Uhlemann, Sebastian Cammerer, Alexander Span, Sebastian Dörner

Motivated by the recent success of end-to-end training of communications in the wireless domain, we strive to adapt the end-to-end-learning idea from the wireless case (i.e., linear) to coherent optical fiber links (i.e., nonlinear). Although, at first glance, it sounds like a straightforward extension, it turns out that several pitfalls exist - in terms of

Tommaso Micallo, Vittorio Vitale, Marcello Dalmonte, Pierre Fromholz

We study the disconnected entanglement entropy, $S^D$, of the Su-Schrieffer-Heeger model. $S^D$ is a combination of both connected and disconnected bipartite entanglement entropies that removes all area and volume law contributions, and is thus only sensitive to the non-local entanglement stored within the ground state manifold. Using analytical and numerica

Sam Young, Adrian S. Hamers

By performing Monte Carlo simulations of the evolution of binary primordial black hole (PBH) systems, we estimate the effect of distant encounters with single PBHs upon the coalescence time and merger rate of binary PBHs. We find that, for models where PBHs compose a large fraction of dark matter, $f_\mathrm{PBH}\sim 1$, the expected fractional change in coa

Asta Heinesen

We investigate number count statistics as measures for transition to homogeneity of the matter distribution in the Universe and analyse how such statistics might be `dressed' by the assumed survey selection function. Since the estimated survey selection function -- which ideally accounts for selection bias in the observed distribution -- is partially deg

Hon Man Yau, Nan Su

The applicability of artificial neural networks (ANNs) is typically limited to the models they are trained with and little is known about their generalizability, which is a pressing issue in the practical application of trained ANNs to unseen problems. Here, by using the task of identifying phase transitions in spin models, we establish a systematic generali

A. Mozers, L. Busaite, D. Osite, M. Auzinsh

We investigated experimentally and theoretically angular momentum alignment-to-orientation conversion created by the joint interaction of laser radiation and an external magnetic field with atomic rubidium at room temperature. In particular we were interested in alignment-to-orientation conversion in atomic ground state. Experimentally the laser frequency wa

Manuel Trashorras, Juan García-Bellido, Savvas Nesseris

We explore the possibility that Dark Matter (DM) may be explained by a non-uniform background of approximately stellar-mass clusters of Primordial Black Holes (PBHs), by simulating the evolution them from recombination to the present with over 5000 realisations using a Newtonian $ N $-body code. We compute the cluster rate of evaporation, and extract the bin

Timothy Clifton, Pedro Carrilho, Pedro G. S. Fernandes, David J. Mulryne

In this paper we study the observational constraints that can be imposed on the coupling parameter, $\hat α$, of the regularized version of the 4-dimensional Einstein-Gauss-Bonnet theory of gravity. We use the scalar-tensor field equations of this theory to perform a thorough investigation of its slow-motion and weak-field limit, and apply our results to obs

Michal Szanecki, Andrzej Niedzwiecki, Chris Done, Lukasz Klepczarek

We investigate constraints for the size and location of the X-ray source in 1H 0707-495 determined from the shape of the relativistically smeared reflection from the accretion disc. We develop a new code to model an extended X-ray source and we apply it to all archival XMM observations of 1H 0707-495. Contrary to Wilkins et al. we find that the relativistic

Rui Zhu, Baolin Tan, Yingna Su, Hui Tian

We have performed microwave diagnostics of the magnetic field strengths in solar flare loops based on the theory of gyrosynchrotron emission. From Nobeyama Radioheliograph observations of three flare events at 17 and 34 GHz, we obtained the degree of circular polarization and the spectral index of microwave flux density, which were then used to map the magne

Ravi Kiran, Madhumita Roy, Syed Abbas, A. Taraphder

One of the critical measures to control infectious diseases is a lockdown. Once past the lockdown stage in many parts of the world, the crucial question now concerns the effects of relaxing the lockdown and finding the best ways to implement further lockdown(s), if required, to control the spread. With the relaxation of lockdown, people migrate to different

Thomas M. Moerland, Joost Broekens, Aske Plaat, Catholijn M. Jonker

Sequential decision making, commonly formalized as optimization of a Markov Decision Process, is a key challenge in artificial intelligence. Two successful approaches to MDP optimization are reinforcement learning and planning, which both largely have their own research communities. However, if both research fields solve the same problem, then we might be ab

Can Gokler

We give a partial answer to the question whether the Schrodinger equation can be derived from the Newtonian mechanics of a particle in a potential subject to a random force. We show that the fluctuations around the classical motion of a one dimensional harmonic oscillator subject to a random force can be described by the Schrodinger equation for a period of

Sam L. Polk, Bruce M. Boghosian

In this work, we modify the affine wealth model of wealth distributions to examine the effects of nonconstant redistribution on the very wealthy. Previous studies of this model, restricted to flat redistribution schemes, have demonstrated the presence of a phase transition to a partially wealth-condensed state, or "partial oligarchy," at the critical

Aria Shahverdi, Mahammad Shirinov, Dana Dachman-Soled

We demonstrate the feasibility of database reconstruction under a cache side-channel attack on SQLite. Specifically, we present a Flush+Reload attack on SQLite that obtains approximate (or "noisy") volumes of range queries made to a private database. We then present several algorithms that, taken together, reconstruct nearly the exact database in var

A. Y. Potekhin, D. A. Zyuzin, D. G. Yakovlev, M. V. Beznogov

Ages and thermal luminosities of neutron stars, inferred from observations, can be interpreted with the aid of the neutron star cooling theory to gain information on the properties of superdense matter in neutron-star interiors. We present a survey of estimated ages, surface temperatures and thermal luminosities of middle-aged neutron stars with relatively w

Andrei Ionut Damian, Laurentiu Piciu, Cosmin Mihai Marinescu

In retail vertical industries, businesses are dealing with human limitation of quickly understanding and adapting to new purchasing behaviors. Moreover, retail businesses need to overcome the human limitation of properly managing a massive selection of products/brands/categories. These limitations lead to deficiencies from both commercial (e.g. loss of sales

Nick Luiken, Tristan van Leeuwen

We consider regularized least-squares problems of the form $\min_{x} \frac{1}{2}\Vert Ax - b\Vert_2^2 + \mathcal{R}(Lx)$. Recently, Zheng et al., 2019, proposed an algorithm called Sparse Relaxed Regularized Regression (SR3) that employs a splitting strategy by introducing an auxiliary variable $y$ and solves $\min_{x,y} \frac{1}{2}\Vert Ax - b\Vert_2^2 + \f

Jonathan Simone

In this article, we completely classify torus bundles over the circle that bound 4-manifolds with the rational homology of the circle. Along the way, we classify certain integral surgeries along chain links that bound rational homology balls and explore a connection to 3-braid closures whose double branched covers bound rational homology 4-balls.

Pierre Degond, Maxime Herda, Sepideh Mirrahimi

We study several Fokker-Planck equations arising from a stochastic chemical kinetic system modeling a gene regulatory network in biology. The densities solving the Fokker-Planck equations describe the joint distribution of the messenger RNA and micro RNA content in a cell. We provide theoretical and numerical evidences that the robustness of the gene express

Chengliang Dai, Shuo Wang, Yuanhan Mo, Kaichen Zhou

Machine learning has been widely adopted for medical image analysis in recent years given its promising performance in image segmentation and classification tasks. As a data-driven science, the success of machine learning, in particular supervised learning, largely depends on the availability of manually annotated datasets. For medical imaging applications,

M. Reza J. Harandi, Hamid. D. Taghirad

Finding the general solution of partial differential equations (PDEs) is essential for controller design in newly developed methods. Interconnection and damping assignment passivity based control (IDA-PBC) is one of such methods in which the solution to corresponding PDEs which are called matching equations, is needed to apply it in practice. In this paper,

Colin Ingalls, Adam Logan

A collection $S = \{D_1,\ldots, D_n\}$ of divisors in a smooth variety $X$ is an {\em arrangement} if intersections of all subsets of $S$ are smooth. We show that a double cover of $X$ ramified on an arrangement has a crepant resolution under additional hypotheses. Namely, we assume that all intersection components that change the canonical divisor when blow

Marco Iglesias, Yuchen Yang

We propose a new regularisation strategy for the classical ensemble Kalman inversion (EKI) framework. The strategy consists of: (i) an adaptive choice for the regularisation parameter in the update formula in EKI, and (ii) criteria for the early stopping of the scheme. In contrast to existing approaches, our parameter choice does not rely on additional tunin

J. C. Correa, H. Laverde-Rojas, F. Marmolejo-Ramos, J. Tejada

Citations are often used as a metric of the impact of scientific publications. Here, we examine how the number of downloads from Sci-hub as well as various characteristics of publications and their authors predicts future citations. Using data from 12 leading journals in economics, consumer research, neuroscience, and multidisciplinary research, we found tha

Hang Zhao, Qijin She, Chenyang Zhu, Yin Yang

We solve a challenging yet practically useful variant of 3D Bin Packing Problem (3D-BPP). In our problem, the agent has limited information about the items to be packed into the bin, and an item must be packed immediately after its arrival without buffering or readjusting. The item's placement also subjects to the constraints of collision avoidance and p

Jan Kumlin, Kevin Kleinbeck, Nina Stiesdal, Hannes Busche

We study the dynamics of a single excitation coherently shared amongst an ensemble of atoms and coupled to a one-dimensional wave guide. The coupling between the matter and the light field gives rise to collective phenomena such as superradiant states with an enhanced initial decay rate, but also to the coherent exchange of the excitation between the atoms.

Gianluigi Bodo, Fabrizo Tavecchio, Lorenzo Sironi

We investigate with relativistic MHD simulations the dissipation physics of BL Lac jets, by studying the synchrotron polarization signatures of particles accelerated by the kink instability in a magnetically-dominated plasma column. The nonlinear stage of the kink instability generates current sheets, where particles can be efficiently accelerated via magnet

Arvind Arun Dev, Peter Dunne, Thomas M. Hermans, Bernard Doudin

The frictional forces of a viscous liquid flow are a major energy loss issue and severely limit microfluidics practical use. Reducing this drag by more than a few tens of percent remain illusive. Here, we show how cylindrical liquid-in-liquid flow leads to drag reduction of 60-99% for sub mm and mm sized channels, irrespective of whether the viscosity of the

Aekta Aggarwal, Ganesh Vaidya, G. D. Veerappa Gowda

Godunov type numerical schemes for the class of hyperbolic systems, admitting non-classical $δ-$ shocks are proposed. It is shown that the numerical approximations converge to the solution and preserve the physical properties of the system such as positive density and bounded velocity. The scheme has been extended to positivity preserving and velocity bound

Carmine Abate, Matteo Busi, Stelios Tsampas

The most prominent formal criterion for secure compilation is full abstraction, the preservation and reflection of contextual equivalence. Recent work introduced robust compilation, defined as the preservation of robust satisfaction of hyperproperties, i.e., their satisfaction against arbitrary attackers. In this paper, we initially set out to compare these

Junsung Choi, Vuk Marojevic, Carl B. Dietrich, Jeffrey H. Reed

As 5G communication technology develops, vehicular communications that require high reliability, low latency, and massive connectivity are drawing increasing interest from those in academia and industry. Due to these developing technologies, vehicular communication is not limited to vehicle components in the forms of Vehicle-to-Vehicle (V2V) or Vehicle-to-In

Daniel Karlsson, Robert van Leeuwen, Yaroslav Pavlyukh, Enrico Perfetto

The interaction of electrons with quantized phonons and photons underlies the ultrafast dynamics of systems ranging from molecules to solids, and it gives rise to a plethora of physical phenomena experimentally accessible using time-resolved techniques. Green's function methods offer an invaluable interpretation tool since scattering mechanisms of growin

Mori Watanabe, Sanghyun Lee, Takuya Asano, Takashi Ibe

We have performed magnetotransport measurements in CeTe$_{3}$ thin films down to $0.2~{\rm K}$. It is known that CeTe$_{3}$ has two magnetic transitions at $T_{\rm N1} \approx 3~{\rm K}$ and $T_{\rm N2} \approx 1~{\rm K}$. A clear Shubnikov-de-Haas (SdH) oscillation was observed at $4~{\rm K}$, demonstrating the strong two-dimensional nature in this material

Eugene Kharitonov, Rahma Chaabouni

Sequence-to-sequence (seq2seq) learners are widely used, but we still have only limited knowledge about what inductive biases shape the way they generalize. We address that by investigating how popular seq2seq learners generalize in tasks that have high ambiguity in the training data. We use SCAN and three new tasks to study learners' preferences for mem

Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh

We present a series of new and more favorable margin-based learning guarantees that depend on the empirical margin loss of a predictor. We give two types of learning bounds, both distribution-dependent and valid for general families, in terms of the Rademacher complexity or the empirical $\ell_\infty$ covering number of the hypothesis set used. Furthermore,

Jack Morava

We use Andrew Baker's analysis of the cofiber of the endomorphism of the $p$-adic elliptic spectrum ($p>3$) defined by multiplication by the `Hasse invariant' $E_{p-1}$ to present its completion away from the locus of ordinary elliptic curves as a sum of roughly $p/12$ copies (indexed by supesingular elliptic curves) of $p$-adic lifts of the height t

Peter T. H. Pang, Tim Dietrich, Ingo Tews, Chris Van Den Broeck

At supranuclear densities, explored in the core of neutron stars, a strong phase transition from hadronic matter to more exotic forms of matter might be present. To test this hypothesis, binary neutron-star mergers offer a unique possibility to probe matter at densities that we can not create in any existing terrestrial experiment. In this work, we show that

Etienne Le Masson, Tuomas Sahlsten

We give a quantitative estimate for the quantum mean absolute deviation on hyperbolic surfaces of finite area in terms of geometric parameters such as the genus, number of cusps and injectivity radius. It implies a delocalisation result of quantum ergodicity type for eigenfunctions of the Laplacian on hyperbolic surfaces of finite area that Benjamini-Schramm

Tom Bachmann

We show that the category of motivic spaces with transfers along finite flat morphisms, over a perfect field, satisfies all the properties we have come to expect of good categories of motives. In particular we establish the analog of Voevodsky's cancellation theorem.

Chika O. Okafor

I study labor markets in which firms both hire via referrals and are race blind or color-blind. I develop an employment model showing that despite initial equality in ability, employment, wages, and network structure, minorities receive disproportionately fewer jobs through referrals and lower expected wages, simply because their social group is smaller. Thi

Francisco S. Ponciano-Ojeda, Fraser D. Logue, Ifan G. Hughes

We present a detailed spectroscopic investigation of a thermal $^{87}$Rb atomic vapour in a magnetic field of 1.5~T in the Voigt geometry. We fit experimental spectra for all Stokes parameters with our theoretical model \textit{ElecSus} and find very good quantitative agreement, with RMS errors of $\sim 1.5$\% in all cases. We extract the magnetic field stre

Henk Bruin, Benjamin Vejnar

We study the complexity of the classification problem of conjugacy on dynamical systems on some compact metrizable spaces. Especially we prove that the conjugacy equivalence relation of interval dynamical systems is Borel bireducible to isomorphism equivalence relation of countable graphs. This solves a special case of the Hjorth's conjecture which state

Jiaxi Ying, José Vinícius de M. Cardoso, Daniel P. Palomar

We consider the problem of learning a sparse graph under the Laplacian constrained Gaussian graphical models. This problem can be formulated as a penalized maximum likelihood estimation of the Laplacian constrained precision matrix. Like in the classical graphical lasso problem, recent works made use of the $\ell_1$-norm regularization with the goal of promo

Daniel Han-Kwan, Mikaela Iacobelli

Vlasov equations can be formally derived from N-body dynamics in the mean-field limit. In some suitable singular limits, they may themselves converge to fluid dynamics equations. Motivated by this heuristic, we introduce natural scalings under which the incompressible Euler equations can be rigorously derived from N-body dynamics with repulsive Coulomb inter

Amrita Goswami, Indranil Saha Dalal, Jayant K. Singh

Hydrodynamic flow can have complex and far-reaching consequences on the rate of homogenous nucleation. We present a general formalism for calculating the nucleation rates of simply sheared systems. We have derived an extension to the conventional Classical Nucleation Theory, explicitly embodying the shear rate. Seeded Molecular Dynamics simulations form the

J. K. Ahn, B. Beckford, M. Campbell, S. H. Chen

We report the first search for the $K_L \to π^0 γ$ decay, which is forbidden by Lorentz invariance, using the data from 2016 to 2018 at the J-PARC KOTO experiment. With a single event sensitivity of $(7.1\pm 0.3_{\rm stat.} \pm 1.6_{\rm syst.})\times 10^{-8}$, no candidate event was observed in the signal region. The upper limit on the branching fraction was

Viacheslav V. Saenko

The problem of calculating the Mittag-Leffler function $E_{ρ,μ} (z)$ is considered in the paper. To solve this problem integral representations for the function $E_{ρ,μ}(z)$ are transformed in such a way that they could not contain complex variables and parameters. Integral representations written in this form allow one to use standard methods of numerical i

Angelos Filos, Panagiotis Tigas, Rowan McAllister, Nicholas Rhinehart

Out-of-training-distribution (OOD) scenarios are a common challenge of learning agents at deployment, typically leading to arbitrary deductions and poorly-informed decisions. In principle, detection of and adaptation to OOD scenes can mitigate their adverse effects. In this paper, we highlight the limitations of current approaches to novel driving scenes and

János Pach, Gábor Tardos, Géza Tóth

We call a multigraph {\em non-homotopic} if it can be drawn in the plane in such a way that no two edges connecting the same pair of vertices can be continuously transformed into each other without passing through a vertex, and no loop can be shrunk to its end-vertex in the same way. It is easy to see that a non-homotopic multigraph on $n>1$ vertices can hav

Francesca Balestrieri, Alexis Johnson, Rachel Newton

Let $k$ be a number field. We give an explicit bound, depending only on $[k:\mathbf{Q}]$ and the discriminant of the Néron--Severi lattice, on the size of the Brauer group of a K3 surface $X/k$ that is geometrically isomorphic to the Kummer surface attached to a product of isogenous CM elliptic curves. As an application, we show that the Brauer--Manin set fo

Antoine C. Petit, Gabriele Pichierri, Melvyn B. Davies, Anders Johansen

The dynamical stability of tightly packed exoplanetary systems remains poorly understood. While for a two-planet system a sharp stability boundary exists, numerical simulations of three and more planet systems show that they can experience instability on timescales up to billions of years. Moreover, an exponential trend between the planet orbital separation

Erica Bertolini, Nicola Maggiore

The 4D Maxwell theory with single-sided planar boundary is considered. As a consequence of the presence of the boundary, two broken Ward identities are recovered, which, on-shell, give rise to two conserved currents living on the edge. A Kaç-Moody algebra formed by a subset of the bulk fields is obtained with central charge proportional to the inverse of the

Marek Szydlowski, Adam Krawiec

The cosmological observations suggest that the presently accelerating universe should be filled by an exotic form of matter, violating the strong energy condition, of unknown nature and origin. We propose the viscous dark matter of a source of acceleration in the form of Chaplygin gas which is characterized by equation of state in the phenomenological form $

Yu. V. Krasnikova, S. C. Furuya, V. N. Glazkov, K. Yu. Povarov

We report low temperature electron spin resonance experimental and theoretical studies of an archetype $S=1/2$ strong-rung spin ladder material (C$_{5}$H$_{12}$N)$_{2}$CuBr$_{4}$. Unexpected dynamics is detected deep in the Tomonaga-Luttinger spin liquid regime. Close to the point where the system is half-magnetized (and believed to be equivalent to a gaples

Megan Griffin-Pickering, Mikaela Iacobelli

Systems of Vlasov-Poisson type are kinetic models describing dilute plasma. The structure of the model differs according to whether it describes the electrons or positively charged ions in the plasma. In contrast to the electron case, where the well-posedness theory for Vlasov-Poisson systems is well established, the well-posedness theory for ion models has

Chen Wu, Yinong Guo, Haonan Guo, Jingwen Yuan

In order to mitigate the spread of COVID-19, Wuhan was the first city to implement strict lockdown policy in 2020. Even though numerous researches have discussed the travel restriction between cities and provinces, few studies focus on the effect of transportation control inside the city due to the lack of the measurement and available data in Wuhan. Since t

Young-Jin Park, Kyuyong Shin, Kyung-Min Kim

Graph representation learning is gaining popularity in a wide range of applications, such as social networks analysis, computational biology, and recommender systems. However, different with positive results from many academic studies, applying graph neural networks (GNNs) in a real-world application is still challenging due to non-stationary environments. T

K. Jotsaroop, Saurabh Shrivastava

In this paper we investigate the boundedness properties of bilinear multiplier operators associated with unimodular functions of the form $m(ξ,η)=e^{i ϕ(ξ-η)}$. We prove that if $ϕ$ is a $C^1(\mathbb R^n)$ real-valued non-linear function, then for all exponents $p,q,r$ lying outside the local $L^2-$range and satisfying the Hölder's condition $\frac{1}{p}

Gunther Leobacher, Christoph Reisinger, Wolfgang Stockinger

In this paper, we first establish well-posedness results for one-dimensional McKean-Vlasov stochastic differential equations (SDEs) and related particle systems with a measure-dependent drift coefficient that is discontinuous in the spatial component, and a diffusion coefficient which is a Lipschitz function of the state only. We only require a fairly mild c

Carsten Maple, Peter Davies, Kerstin Eder, Chris Hankin

Existing approaches to cyber security and regulation in the automotive sector cannot achieve the quality of outcome necessary to ensure the safe mass deployment of advanced vehicle technologies and smart mobility systems. Without sustainable resilience hard-fought public trust will evaporate, derailing emerging global initiatives to improve the efficiency, s

Stefano Mandelli, Elenia Manzan, Aniello Mennella, Francesco Cavaliere

We present the design, manufacturing, and testing of a 37-element array of corrugated feedhorns for Cosmic Microwave Background (CMB) measurements between $140$ and $170$ GHz. The array was designed to be coupled to Kinetic Inductance Detector arrays, either directly (for total power measurements) or through an orthomode transducer (for polarization measurem

Mattias Nordin, Mårten Schultzberg

Recently, there as been an increasing interest in the use of heavily restricted randomization designs which enforces balance on observed covariates in randomized controlled trials. However, when restrictions are strict, there is a risk that the treatment effect estimator will have a very high mean squared error. In this paper, we formalize this risk and prop

Simone Cerreia-Vioglio, Fabio Maccheroni, Massimo Marinacci, Aldo Rustichini

The Boltzmann distribution describes a single parameter (temperature) family of probability distributions over a state space; at any given temperature, the ratio of probabilities of two states depends on their difference in energy. The same family is known in other disciplines (economics, psychology, computer science) with different names and interpretations

Andreas Klos, Marius Rosenbaum, Wolfram Schiffmann

The full loss of thrust of an aircraft requires fast and reliable decisions of the pilot. If no published landing field is within reach, an emergency landing field must be selected. The choice of a suitable emergency landing field denotes a crucial task to avoid unnecessary damage of the aircraft, risk for the civil population as well as the crew and all pas

Jian Tang, Tse-Chun Wang

Neutrino models based on flavour symmetries provide the natural way to explain the origin of tiny neutrino masses. At the dawn of precision measurements of neutrino mixing parameters, neutrino mass models can be constrained and examined by on-going and up-coming neutrino experiments. We present a supplemental tool Flavour Symmetry Embedded (FaSE) for General

Tong Yang, Jizhou Li, Yikai Zhao, Kaicheng Yang

Flow scheduling is crucial in data centers, as it directly influences user experience of applications. According to different assumptions and design goals, there are four typical flow scheduling problems/solutions: SRPT, LAS, Fair Queueing, and Deadline-Aware scheduling. When implementing these solutions in commodity switches with limited number of queues, t

Matt Landreman, Rogerio Jorge

We have recently demonstrated that by expanding in small distance from the magnetic axis compared to the major radius, stellarator shapes with low neoclassical transport can be generated efficiently. To extend the utility of this new design approach, here we evaluate measures of magnetohydrodynamic interchange stability within the same expansion. In particul

Santeri Karppinen, Matti Vihola

Conditional particle filters (CPFs) are powerful smoothing algorithms for general nonlinear/non-Gaussian hidden Markov models. However, CPFs can be inefficient or difficult to apply with diffuse initial distributions, which are common in statistical applications. We propose a simple but generally applicable auxiliary variable method, which can be used togeth

A. Marie d'Avigneau, S. S. Singh, L. M. Murray

Developing efficient MCMC algorithms is indispensable in Bayesian inference. In parallel tempering, multiple interacting MCMC chains run to more efficiently explore the state space and improve performance. The multiple chains advance independently through local moves, and the performance enhancement steps are exchange moves, where the chains pause to exchang

Olivier Besson

We analyze the distribution of the signal to noise ratio (SNR) loss at the output of an adaptive filter which is trained with samples that do not share the same covariance matrix as the samples for which the filter is foreseen. Our objective is to find an accurate approximation of the distribution of the SNR loss which has a similar form as in the case of no

Simon Ollander, Friedrich-Wilhelm Bode, Marcus Baum

Global navigation satellite systems provide accurate positioning nearly worldwide. However, in the urban canyons of dense cities, buildings block and reflect the signals, causing multipath errors. To mitigate multipath errors, knowledge of the distribution of the reflection delays is important. Measurements of this distribution have been done in several dens

Tatsuki Kuwagaki

A sheaf quantization is a sheaf associated to a Lagrangian brane. By using the results of exact WKB analysis, we sheaf-quantize spectral curves over the Novikov ring under some assumptions on the behavior of Stokes curves. For Schrödinger equations, we prove that the local system associated to the sheaf quantization (microlocalization a.k.a. abelianization)

Kaidi Jin, Tianwei Zhang, Chao Shen, Yufei Chen

Deep Neural Networks are well known to be vulnerable to adversarial attacks and backdoor attacks, where minor modifications on the input are able to mislead the models to give wrong results. Although defenses against adversarial attacks have been widely studied, investigation on mitigating backdoor attacks is still at an early stage. It is unknown whether th

Andrew Ellis, David J. Freeman

Experiments suggest that people fail to take into account interdependencies between their choices -- they do not broadly bracket. Researchers often instead assume that people narrowly bracket, but existing designs do not test it. We design a novel experiment and revealed preference tests for how someone brackets their choices. In portfolio allocation under r

Miguel Costa-Gomes, Georgios Gerasimou

Inertia and context-dependent choice effects are well-studied classes of behavioural phenomena. While much is known about these effects in isolation, little is known about whether one of them "dominates" the other when both can potentially be present. Knowledge of any such dominance is relevant for effective choice architecture and descriptive modell

Ansgar Denner, Giovanni Pelliccioli

The measurement of polarization fractions of massive gauge bosons at the LHC provides an important check of the Standard Model and in particular of the Electroweak Symmetry Breaking mechanism. Owing to the unstable character of $\text{W}$ and $\text{Z}$ bosons, devising a theoretical definition for polarized signals is not straightforward and always subject

Hendrik Kähler, Daniel Platz, Silvan Schmid

The coupling of micro- or nanomechanical resonators via a shared substrate is intensively exploited to built systems for fundamental studies and practical applications. So far, the focus has been on devices operating in the kHz regime with a spring-like coupling. At resonance frequencies above several 10 MHz, wave propagation in the solid substrate becomes r

Gilad Bavly, Yuval Heller, Amnon Schreiber

We consider games in which players search for a hidden prize, and they have asymmetric information about the prize location. We study the social payoff in equilibria of these games. We present sufficient conditions for the existence of an equilibrium that yields the first-best payoff (i.e., the highest social payoff under any strategy profile), and we charac

Bruno Lecouat, Jean Ponce, Julien Mairal

We introduce a general framework for designing and training neural network layers whose forward passes can be interpreted as solving non-smooth convex optimization problems, and whose architectures are derived from an optimization algorithm. We focus on convex games, solved by local agents represented by the nodes of a graph and interacting through regulariz

Yue Xiu, Jun Zhao, Chau Yuen, Zhongpei Zhang

In this letter, secure beamforming in a multiple intelligent reflecting surfaces (IRSs)-aided millimeter-wave (mmWave) system is investigated. In this system, the secrecy rate is maximized by controlling the on-off status of each IRS as well as optimizing the phase shift matrix of the IRSs. This problem is posed as a joint optimization problem of transmit be