March 2020 arXiv papers — page 123

Ivan Agullo, Javier Olmedo, V. Sreenath

We introduce an extension of the standard inflationary paradigm on which the big bang singularity is replaced by an anisotropic bounce. Unlike in the big bang model, cosmological perturbations find an adiabatic regime in the past. We show that this scenario accounts for the observed quadrupolar modulation in the temperature anisotropies of the cosmic microwa

Spencer T. Stober, Stuart M. Harwood, Donny Greenberg, Tanvi P. Gujarati

Quantum chemistry applications on quantum computers currently rely heavily on the variational quantum eigensolver (VQE) algorithm. This hybrid quantum-classical algorithm aims at finding ground state solutions of molecular systems based on the variational principle. VQE calculations can be systematically implemented for perturbations to each molecular degree

Jie Wang, Victor Magron, Jean-Bernard Lasserre

This work is a follow-up and a complement to arXiv:1912.08899 [math.OC] for solving polynomial optimization problems (POPs). The chordal-TSSOS hierarchy that we propose is a new sparse moment-SOS framework based on term-sparsity and chordal extension. By exploiting term-sparsity of the input polynomials we obtain a two-level hierarchy of semidefinite program

Yi Xie, Cong Shi, Zhuohang Li, Jian Liu

As the popularity of voice user interface (VUI) exploded in recent years, speaker recognition system has emerged as an important medium of identifying a speaker in many security-required applications and services. In this paper, we propose the first real-time, universal, and robust adversarial attack against the state-of-the-art deep neural network (DNN) bas

Andrea Fuster, Sjors Heefer, Christian Pfeifer, Nicoleta Voicu

We investigate whether Szabo's metrizability theorem can be extended to Finsler spaces of indefinite signature. For smooth, positive definite Finsler metrics, this important theorem states that, if the metric is of Berwald type (i.e., its Chern-Rund connection defines an affine connection on the underlying manifold), then it is affinely equivalent to a R

Manuel Hohmann, Christian Pfeifer, Nicoleta Voicu

Applying the cosmological principle to Finsler spacetimes, we identify the Lie Algebra of symmetry generators of spatially homogeneous and isotropic Finsler geometries, thus generalising Friedmann-Lemaître-Robertson-Walker geometry. In particular, we find the most general spatially homogeneous and isotropic Berwald spacetimes, which are Finsler spacetimes th

Javad Fotouhi, Giacomo Taylor, Mathias Unberath, Alex Johnson

We present a novel methodology to detect imperfect bilateral symmetry in CT of human anatomy. In this paper, the structurally symmetric nature of the pelvic bone is explored and is used to provide interventional image augmentation for treatment of unilateral fractures in patients with traumatic injuries. The mathematical basis of our solution is on the incor

Hajime Fujita, Yu Kitabeppu, Ayato Mitsuishi

In this paper we discuss three distance functions on the set of convex bodies. In particular we study the convergence of Delzant polytopes, which are fundamental objects in symplectic toric geometry. By using these observations, we derive some convergence theorems for symplectic toric manifolds with respect to the Gromov-Hausdorff distance.

Lena Murchikova, Scott Tremaine

We address the claim of Weiss et al. (2018) that the radii of adjacent planets in Kepler multi-planet systems are correlated. We explore two simple toy models---in the first the radii of the planets are chosen at random from a single universal distribution, and in the second we postulate several types of system with distinct radius distributions. We show tha

Alexey A. Vladimirov

The rapidity anomalous dimension (RAD), or Collins-Soper kernel, defines the scaling properties of transverse momentum dependent distributions and can be extracted from the experimental data. I derive a self-contained nonperturbative definition that represents RAD without reference to a particular process. This definition makes possible exploration of the pr

Thodoris Lykouris, Vahab Mirrokni, Renato Paes Leme

We study "adversarial scaling", a multi-armed bandit model where rewards have a stochastic and an adversarial component. Our model captures display advertising where the "click-through-rate" can be decomposed to a (fixed across time) arm-quality component and a non-stochastic user-relevance component (fixed across arms). Despite the relative

James Healy, Carlos O. Lousto, Nicole Rosato

We explore different gauge choices in the moving puncture formulation in order to improve the accuracy of a linear momentum measure evaluated on the horizon of the remnant black hole produced by the merger of a binary. In particular, motivated by constant values studies, we design a gauge via a variable shift parameter $mη(\vec{r}(t))$ such that it takes a l

Flavio Baccari, Remigiusz Augusiak, Ivan Šupić, Antonio Acín

Self-testing is a procedure for characterizing quantum resources with the minimal level of trust. Up to now it has been used as a device-independent certification tool for particular quantum measurements, channels, and pure entangled states. In this work we introduce the concept of self-testing more general entanglement structures. More precisely, we present

Néstor Merino-Díez, Alejandro Pérez Paz, Jingcheng Li, Manuel Vilas-Varela

Within the collection of surface-supported reactions currently accessible for the production of extended molecular nanostructures under ultra-high vacuum, Ullmann coupling has been the most successful in the controlled formation of covalent single C-C bonds. Particularly advanced control of this synthetic tool has been obtained by means of hierarchical react

Matthew Mould, Davide Gerosa

Binary black holes in which both spins are aligned with the binary's orbital angular momentum do not precess. However, the up-down configuration, in which the spin of the heavier (lighter) black hole is aligned (anti-aligned) with the orbital angular momentum, is unstable to spin precession at small orbital separations. We first cast the spin precession

Yoav Afik, Juan Ramón Muñoz de Nova

Entanglement is a central subject in quantum mechanics. Due to its genuine relativistic behavior and fundamental nature, high-energy colliders are attractive systems for the experimental study of fundamental aspects of quantum mechanics. We propose the detection of entanglement between the spins of top-antitop-quark pairs at the LHC, representing the first p

Manuel Arca Sedda

The detection of gravitational waves emitted during a neutron star - black hole merger and the associated electromagnetic counterpart will provide a wealth of information about stellar evolution nuclear matter, and General Relativity. While the theoretical framework about neutron star - black hole binaries formed in isolation is well established, the picture

Farida Farsian, Nicoletta Krachmalnicoff, Carlo Baccigalupi

In this work we present a Neural Network (NN) algorithm for the identification of the appropriate parametrization of diffuse polarized Galactic emissions in the context of Cosmic Microwave Background (CMB) $B$-mode multi-frequency observations. In particular, we have focused our analysis on low frequency foregrounds relevant for polarization observation: nam

Sara Rastello, Michela Mapelli, Ugo N. Di Carlo, Nicola Giacobbo

Young star clusters are likely the most common birthplace of massive stars across cosmic time and influence the formation of compact binaries in several ways. Here, we simulate the formation of black hole -- neutron star binaries (BHNSs) in young star clusters, by means of the binary population synthesis code \texttt{MOBSE} interfaced with the $N$-body code

Debasish Borah, Arnab Dasgupta, Kohei Fujikura, Sin Kyu Kang

We scrutinise the widely studied minimal scotogenic model of dark matter (DM) and radiative neutrino mass from the requirement of a strong first order electroweak phase transition (EWPT) and observable gravitational waves at future planned space based experiments. The scalar DM scenario is similar to inert scalar doublet extension of standard model where a s

Duff Neill, Felix Ringer

We develop two approaches to the problem of soft fragmentation of hadrons in a gauge theory for high energy processes. The first approach directly adapts the standard resummation of the parton distribution function's anomalous dimension (that of twist-two local operators) in the forward scattering regime, using $k_T$-factorization and BFKL theory, to the

John Coffey, Lindsay Forestell, David E. Morrissey, Graham White

New dark vector bosons that couple very feebly to regular matter can be created in the early universe and decay after the onset of big bang nucleosynthesis (BBN) or the formation of the cosmic microwave background (CMB) at recombination. The energy injected by such decays can alter the light element abundances or modify the power and frequency spectra of the

Ameen Ismail, Heather E. Logan, Yongcheng Wu

We study the experimental constraints on the Georgi-Machacek model from direct searches for the new Higgs bosons and measurements of the properties of the discovered 125 GeV Higgs boson. We apply these by interfacing the public codes HiggsBounds 5.2.0 and HiggsSignals 2.2.1, which implement a large collection of direct-search constraints on extra Higgs boson

Alejandro Ruipérez

We compute the first-order $α'$-corrections to a general family of supersymmetric heterotic backgrounds which describes a rotating superposition of a fundamental string and a momentum wave. We focus on a particular solution within this family that gives raise, upon dimensional reduction to five dimensions, to a black ring with two charges and one dipole

Alvaro Ballon Bordo, Finnian Gray, David Kubiznak

We extend the work on thermodynamics of Lorentzian NUTty solutions, by including simultaneously the effect of rotation and electromagnetic charges. Due to the fact that Misner strings carry electric charge, and similar to the non-rotating case, we observe an interesting interplay between the horizon and asymptotic charges. Namely, upon employing the Euclidea

Hui Liu, Ion Cosma Fulga, Janos K. Asboth

Anderson localization in two-dimensional topological insulators takes place via the so-called levitation and pair annihilation process. As disorder is increased, extended bulk states carrying opposite topological invariants move towards each other in energy, reducing the size of the topological gap, eventually meeting and localizing. This results in a topolo

Julian Huber, Peter Kirton, Stefan Rotter, Peter Rabl

The effect of PT-symmetry breaking in coupled systems with balanced gain and loss has recently attracted considerable attention and has been demonstrated in various photonic, electrical and mechanical systems in the classical regime. Here we generalize the definition of PT symmetry to finite-dimensional open quantum systems, which are described by a Markovia

Raphael Bennett-Tennenhaus, Amit Shah

We fill a gap in the literature regarding `transport of structure' for (n+2)-angulated, n-exact, n-abelian and n-exangulated categories appearing in (classical and higher) homological algebra. As an application of our main results, we show that a skeleton of one of these kinds of categories inherits the same structure in a canonical way, up to equivalence. I

Ecenaz Erdemir, Pier Luigi Dragotti, Deniz Gunduz

Internet of things (IoT) devices are becoming increasingly popular thanks to many new services and applications they offer. However, in addition to their many benefits, they raise privacy concerns since they share fine-grained time-series user data with untrusted third parties. In this work, we study the privacy-utility trade-off (PUT) in time-series data sh

Ali G. Moghaddam, Alireza Qaiumzadeh, Anna Dyrdał, Jamal Berakdar

We investigate spin-charge conversion phenomena in hybrid structures of topological insulator (TI) thin films and magnetic insulators. We find an anisotropic inverse spin-galvanic effect (ISGE) that yields a highly tunable spin-orbit torque (SOT). Concentrating on the quasiballistic limit, we also predict a giant anisotropic magnetoresistance (AMR) at low do

Pantelis E. Eleftheriou, Alex Savatovsky

We explore &#34;semibounded&#34; expansions of arbitrary ordered groups; namely, expansions that do not define a field on the whole universe. We show that if $\mathcal R=\langle R, <, +, \dots\rangle$ is a semibounded o-minimal structure and $P\subseteq R$ a set satisfying certain tameness conditions, then $\langle \cal R, P\rangle$ remains semibounded. Exam

Yada Pruksachatkun, Phil Yeres, Haokun Liu, Jason Phang

We introduce jiant, an open source toolkit for conducting multitask and transfer learning experiments on English NLU tasks. jiant enables modular and configuration-driven experimentation with state-of-the-art models and implements a broad set of tasks for probing, transfer learning, and multitask training experiments. jiant implements over 50 NLU tasks, incl

Varun Kumar, Ashutosh Choudhary, Eunah Cho

Language model based pre-trained models such as BERT have provided significant gains across different NLP tasks. In this paper, we study different types of transformer based pre-trained models such as auto-regressive models (GPT-2), auto-encoder models (BERT), and seq2seq models (BART) for conditional data augmentation. We show that prepending the class labe

Hsin-Ping Huang, Junyi Jessy Li

Implicit discourse relations are not only more challenging to classify, but also to annotate, than their explicit counterparts. We tackle situations where training data for implicit relations are lacking, and exploit domain adaptation from explicit relations (Ji et al., 2015). We present an unsupervised adversarial domain adaptive network equipped with a rec

Mahbub Alam, Anish Ghosh

We prove a quantitative theorem for Diophantine approximation by rational points on spheres. Our results are valid for arbitrary unimodular lattices and we further prove &#39;spiraling&#39; results for the direction of approximates. These results are quantitative generalizations of the Khintchine-type theorem on spheres proved by Kleinbock and Merrill.

Andrew Allan, Jose Groh, Andrea Mehner, Nathan Smith

We investigate a suspected very massive star in one of the most metal-poor dwarf galaxies, PHL~293B. Excitingly, we find the sudden disappearance of the stellar signatures from our 2019 spectra, in particular the broad H lines with P~Cygni profiles that have been associated with a massive luminous blue variable (LBV) star. Such features are absent from our s

Hery Randriamaro

Determining the number of pieces after cutting a cake is a classical problem. Roberts (1887) provided an exact solution by computing the number of chambers contained in a plane cut by lines. About 88 years later, Zaslavsky (1975) even computed the f-polynomial of a hyperplane arrangement, and consequently deduced the number of chambers of that latter. Recent

Vaishaal Shankar, Alex Fang, Wenshuo Guo, Sara Fridovich-Keil

We investigate the connections between neural networks and simple building blocks in kernel space. In particular, using well established feature space tools such as direct sum, averaging, and moment lifting, we present an algebra for creating &#34;compositional&#34; kernels from bags of features. We show that these operations correspond to many of the buildi

Omri Azencot, N. Benjamin Erichson, Vanessa Lin, Michael W. Mahoney

Recurrent neural networks are widely used on time series data, yet such models often ignore the underlying physical structures in such sequences. A new class of physics-based methods related to Koopman theory has been introduced, offering an alternative for processing nonlinear dynamical systems. In this work, we propose a novel Consistent Koopman Autoencode

Emiel Lorist, Zoe Nieraeth

We prove that scalar-valued sparse domination of a multilinear operator implies vector-valued sparse domination for tuples of quasi-Banach function spaces, for which we introduce a multilinear analogue of the UMD condition. This condition is characterized by the boundedness of the multisublinear Hardy-Littlewood maximal operator and goes beyond examples in w

Ankit Shah, Samir Wadhwania, Julie Shah

Defining sound and complete specifications for robots using formal languages is challenging, while learning formal specifications directly from demonstrations can lead to over-constrained task policies. In this paper, we propose a Bayesian interactive robot training framework that allows the robot to learn from both demonstrations provided by a teacher, and

S. Bragin, A. Di Piazza

The process of electron-positron annihilation into two photons in the presence of an intense classical plane wave of an arbitrary shape is investigated analytically by employing light-cone quantization and by taking into account the effects of the plane wave exactly. We introduce a general description of second-order 2-to-2 scattering processes in a plane-wa

Chenguang Wang, Simon Tindemans, Kaikai Pan, Peter Palensky

State estimation is of considerable significance for the power system operation and control. However, well-designed false data injection attacks can utilize blind spots in conventional residual-based bad data detection methods to manipulate measurements in a coordinated manner and thus affect the secure operation and economic dispatch of grids. In this paper

Julian Busch, Jiaxing Pi, Thomas Seidl

Message passing neural networks have recently evolved into a state-of-the-art approach to representation learning on graphs. Existing methods perform synchronous message passing along all edges in multiple subsequent rounds and consequently suffer from various shortcomings: Propagation schemes are inflexible since they are restricted to $k$-hop neighborhoods

David Kozak, Stephen Becker, Alireza Doostan, Luis Tenorio

We present a stochastic descent algorithm for unconstrained optimization that is particularly efficient when the objective function is slow to evaluate and gradients are not easily obtained, as in some PDE-constrained optimization and machine learning problems. The algorithm maps the gradient onto a low-dimensional random subspace of dimension $\ell$ at each

Yifei Yi, Zhesen Yang

In this paper, we study the conditions under which on-site dissipations can induce non-Hermitian skin modes in non-Hermitian systems. When the original Hermitian Hamiltonian has spinless time-reversal symmetry, it is impossible to have skin modes; on the other hand, if the Hermitian Hamiltonian has spinful time-reversal symmetry, skin modes can be induced by

Igor Chekhovskoy, Sergey Medvedev, Irina Vaseva, Egor Sedov

We propose a new method for finding discrete eigenvalues for the direct Zakharov-Shabat problem, based on moving in the complex plane along the argument jumps of the function $a(ζ)$, the localization of which does not require great accuracy. It allows to find all discrete eigenvalues taking into account their multiplicity faster than matrix methods and conto

Hamid Mousavi, Jakob Drefs, Florian Hirschberger, Jörg Lücke

Latent variable models (LVMs) represent observed variables by parameterized functions of latent variables. Prominent examples of LVMs for unsupervised learning are probabilistic PCA or probabilistic SC which both assume a weighted linear summation of the latents to determine the mean of a Gaussian distribution for the observables. In many cases, however, obs

J. Newman, S. Tsuruta, A. C. Liebmann, H. Kunieda

The 1.5 Seyfert galaxy NGC 3227 has been observed by several X-ray missions. We carried out a combined analysis of the data obtained by more recent major observations of the source: two observations performed by XMM-Newton in 2000 and 2006 and six observations performed by Suzaku in 2008. A unified model, which is consistent with all eight observations by th

Yusuke Kimura

We discuss a method for classifying the singularity types of 1/2 Calabi-Yau 3-folds, a family of rational elliptic 3-folds introduced in a previous study in relation to various U(1) factors in 6D F-theory models. A projective dual pair of del Pezzo manifolds recently studied by Mukai is used to analyze the singularity types. In particular, we studied the max

Philipp F. M. Baumann, Michael Schomaker, Enzo Rossi

The notion that an independent central bank reduces a country&#39;s inflation is a controversial hypothesis. To date, it has not been possible to satisfactorily answer this question because the complex macroeconomic structure that gives rise to the data has not been adequately incorporated into statistical analyses. We develop a causal model that summarizes

Pierre Sikivie

In the late 1970&#39;s, the axion was proposed as a solution to the Strong CP Problem, i.e. the puzzle why the strong interactions conserve parity P and the product CP of charge conjugation and parity in spite of the fact that the Standard Model of elementary particles as a whole violates those symmetries. The original axion was soon ruled out by laboratory

Deshun Hong, Naween Anand, Changjiang Liu, Haihua Liu

Synthesis of crystallographically well-defined thin films of topological materials is important for unraveling their mesoscale quantum properties and for device applications. Mn$_3$Ge, an antiferromagnetic Weyl semimetal with a chiral magnetic structure on a Kagome lattice, is expected to have enhanced Berry curvature around Weyl nodes near the Fermi energy,

A. J. Sanchez-Fernandez, L. F. Romero, G. Bandera, S. Tabik

Digital Elevation Models (DEMs) are important datasets for modelling the line of sight, such as radio signals, sound waves and human vision. These are commonly analyzed using rotational sweep algorithms. However, such algorithms require large numbers of memory accesses to 2D arrays which, despite being regular, result in poor data locality in memory. Here, w

Olivier Benoist, John Christian Ottem

A cohomology class of a smooth complex variety of dimension $n$ has coniveau $\geq c$ if it vanishes in the complement of a closed subvariety of codimension $\geq c$, and has strong coniveau $\geq c$ if it comes by proper pushforward from the cohomology of a smooth variety of dimension $\leq n-c$. We show that these two notions differ in general, both for in

D. G. Suárez-Forero, F. Riminucci, V. Ardizzone, M. de Giorgi

Exciton-polaritons are mixed light-matter particles offering a versatile solid state platform to study many-body physical effects. In this work we demonstrate an electrically controlled polariton laser, in a compact, easy-to-fabricate and integrable configuration, based on a semiconductor waveguide. Interestingly, we show that polariton lasing can be achieve

Hongzheng Li, Heyan Huang

Back translation (BT) has been widely used and become one of standard techniques for data augmentation in Neural Machine Translation (NMT), BT has proven to be helpful for improving the performance of translation effectively, especially for low-resource scenarios. While most works related to BT mainly focus on European languages, few of them study languages

Maxim Nefedov

The perturbatively-stable scheme of Next-to-Leading order (NLO) calculations of cross-sections for multi-scale hard-processes in DIS-like kinematics is developed in the framework of High-Energy Factorization. The evolution equation for unintegrated PDF, which resums $\log 1/z$-corrections to the coefficient function in the Leading Logarithmic approximation t

O. Adriani, E. Berti, L. Bonechi, M. Bongi

In this paper, we report the measurement of the energy flow, the cross section and the average inelasticity of forward neutrons (+ antineutrons) produced in $\sqrt{s} = 13$ TeV proton-proton collisions. These quantities are obtained from the inclusive differential production cross section, measured using the LHCf Arm2 detector at the CERN Large Hadron Collid

Rudi Horn, Simon Fowler, James Cheney

Relational lenses are a modern approach to the view update problem in relational databases. As introduced by Bohannon et al. (2006), relational lenses allow the definition of updatable views by the composition of lenses performing individual transformations. Horn et al. (2018) provided the first implementation of incremental relational lenses, which demonstr

Micha Sharir, Noam Solomon, Oleg Zlydenko

We study incidences between points and algebraic curves in three dimensions, taken from a family $C$ of curves that have almost two degrees of freedom, meaning that every pair of curves intersect in $O(1)$ points, for any pair of points $p$, $q$, there are only $O(1)$ curves of $C$ that pass through both points, and a pair $p$, $q$ of points admit a curve of

Evgenii Zheltonozhskii, Chaim Baskin, Yaniv Nemcovsky, Brian Chmiel

Even though deep learning has shown unmatched performance on various tasks, neural networks have been shown to be vulnerable to small adversarial perturbations of the input that lead to significant performance degradation. In this work we extend the idea of adding white Gaussian noise to the network weights and activations during adversarial training (PNI) t

Lukas J. Fiderer, Jonas Schuff, Daniel Braun

Quantum metrology promises unprecedented measurement precision but suffers in practice from the limited availability of resources such as the number of probes, their coherence time, or non-classical quantum states. The adaptive Bayesian approach to parameter estimation allows for an efficient use of resources thanks to adaptive experiment design. For its pra

Konstantin T. Matchev, Prasanth Shyamsundar, Jordan Smolinsky

We propose a novel quantum technique to search for unmodeled anomalies in multidimensional binned collider data. We propose associating an Ising lattice spin site with each bin, with the Ising Hamiltonian suitably constructed from the observed data and a corresponding theoretical expectation. In order to capture spatially correlated anomalies in the data, we

Weixin Wang, Taeyoung Lee

In this paper, a new probability distribution, referred to as the matrix Fisher-Gaussian (MFG) distribution, is proposed on the nonlinear manifold $\mathrm{SO}(3)\times\mathbb{R}^n$. It is constructed by conditioning a (9+n)-variate Gaussian distribution from the ambient Euclidean space into $\mathrm{SO}(3)\times\mathbb{R}^n$, while imposing a certain geomet

G. Kruzic, T. Oishi, D. Vale, N. Paar

Magnetic dipole (M1) excitations build not only a fundamental mode of nucleonic transitions, but they are also relevant for nuclear astrophysics applications. We have established a theory framework for description of M1 transitions based on the relativistic nuclear energy density functional. For this purpose the relativistic quasiparticle random phase approx

Dominik Kufel, Alan D. Sokal

We solve analytically the differential equations for a skier on a circular hill and for a particle on a loop-the-loop track when the hill or track is endowed with a coefficient of kinetic friction $μ$. For each problem, we determine the exact &#34;phase diagram&#34; in the two-dimensional parameter plane.

Marcus C. Christiansen, Christian Furrer

In the presence of monotone information, the stochastic Thiele equation describing the dynamics of state-wise prospective reserves is closely related to the classic martingale representation theorem. When the information utilized by the insurer is non-monotone, the classic martingale theory does not apply. By taking an infinitesimal approach, we derive a gen

Luca Amendola, Shinji Tsujikawa

We argue that the $Λ$CDM tensions of the Hubble-Lemaitre expansion rate $H_0$ and the clustering normalization $σ_8$ can be eased, at least in principle, by considering an interaction between dark energy and dark matter in such a way to induce a small and positive early effective equation of state and a weaker gravity. For a dark energy scalar field $ϕ$ inte

Dimitris Fotakis, Loukas Kavouras, Grigorios Koumoutsos, Stratis Skoulakis

We consider the online Min-Sum Set Cover (MSSC), a natural and intriguing generalization of the classical list update problem. In Online MSSC, the algorithm maintains a permutation on $n$ elements based on subsets $S_1, S_2, \ldots$ arriving online. The algorithm serves each set $S_t$ upon arrival, using its current permutation $π_{t}$, incurring an access c

Dániel Ágoston Bálint

We consider a general set $\mathcal{X}$ of adapted nonnegative stochastic processes in infinite continuous time. $\mathcal{X}$ is assumed to satisfy mild convexity conditions, but in contrast to earlier papers need not contain a strictly positive process. We introduce two boundedness conditions on $\mathcal{X}$ -- DSV corresponds to an asymptotic $L^0$-bound

Micaela Oertel, Aurélien Pascal, Marco Mancini, Jerome Novak

Neutrinos play an important role in compact star astrophysics: neutrino-heating is one of the main ingredients in core-collapse supernovae, neutrino-matter interactions determine the composition of matter in binary neutron star mergers and have among others a strong impact on conditions for heavy element nucleosynthesis and neutron star cooling is dominated

R. Puebla, Y. Ban, J. F. Haase, M. B. Plenio

Quantum sensors typically translate external fields into a periodic response whose frequency is then determined by analyses performed in Fourier space. This allows for a linear inference of the parameters that characterize external signals. In practice, however, quantum sensors are able to detect fields only in a narrow range of amplitudes and frequencies. A

Jarek Duda

While standard estimation assumes that all datapoints are from probability distribution of the same fixed parameters $θ$, we will focus on maximum likelihood (ML) adaptive estimation for nonstationary time series: separately estimating parameters $θ_T$ for each time $T$ based on the earlier values $(x_t)_{t<T}$ using (exponential) moving ML estimator $θ_T=\a

Jonas H. Fritz, Basile Nguyen, Udo Seifert

Biomolecular processes are typically modeled using chemical reaction networks coupled to infinitely large chemical reservoirs. A difference in chemical potential between these reservoirs can drive the system into a non-equilibrium steady state (NESS). In reality, these processes take place in finite systems containing a finite number of molecules. In such sy

Camille Laurent, Matthieu Léautaud

We consider a transport equation by a gradient vector field with a small viscous perturbation --$εΔ_g$. We study uniform observability (resp. controllability) properties in the (singular) vanishing viscosity limit $ε\rightarrow 0^+$, that is, the possibility of having a uniformly bounded observation constant (resp. control cost). We prove with a series of ex

Antonios Antoniadis, Christian Coester, Marek Elias, Adam Polak

Machine-learned predictors, although achieving very good results for inputs resembling training data, cannot possibly provide perfect predictions in all situations. Still, decision-making systems that are based on such predictors need not only to benefit from good predictions but also to achieve a decent performance when the predictions are inadequate. In th

Jean Lagacé, Simon St-Amant

We obtain a complete asymptotic expansion for the eigenvalues of the Dirichlet-to-Neumann maps associated with Schrödinger operators on compact Riemannian surfaces with boundary. For the zero potential, we recover the well-known spectral asymptotics for the Steklov problem. For nonzero potentials, we obtain new geometric invariants determined by the spectrum

Wesley J. Maddox, Gregory Benton, Andrew Gordon Wilson

Neural networks appear to have mysterious generalization properties when using parameter counting as a proxy for complexity. Indeed, neural networks often have many more parameters than there are data points, yet still provide good generalization performance. Moreover, when we measure generalization as a function of parameters, we see double descent behaviou

Hemanshu Kaul, Jeffrey A. Mudrock, Michael J. Pelsmajer

In 1980, Albertson and Berman introduced partial coloring. In 2000, Albertson, Grossman, and Haas introduced partial list coloring. Here, we initiate the study of partial coloring for an insightful generalization of list coloring introduced in 2015 by Dvořák and Postle, DP-coloring (or correspondence coloring). We consider the DP-coloring analogue of the Par

M. Golebiewski, P. Gruszecki, M. Krawczyk, A. E. Serebryannikov

The Talbot effect has been known in optics since XIX century and found various technological applications. In this paper, we demonstrate with the help of micromagnetic simulations this self-imaging phenomenon for spin waves propagating in a thin ferromagnetic film magnetized out-of-plane. We show that the main features of the obtained Talbot carpets for spin

Jorge Cayao, Mónica Benito, Guido Burkard

Recent achievements in the field of gate defined semiconductor quantum dots reinforce the concept of a spin-based quantum computer consisting of nodes of locally connected qubits which communicate with each other via superconducting circuit resonator photons. In this work we theoretically demonstrate a versatile set of quantum gates between adjacent spin qub

P. S. Pal, Sebastian Deffner

Physical scenarios that require a relativistic treatment are ubiquitous in nature, ranging from cosmological objects to charge carriers in Dirac materials. Interestingly all of these situations have in common that the systems typically operate very far from thermal equilibrium. Therefore, if and how the framework of stochastic thermodynamics applies at relat

Aleksei Ustimenko, Liudmila Prokhorenkova

In this paper, we introduce a powerful and efficient framework for direct optimization of ranking metrics. The problem is ill-posed due to the discrete structure of the loss, and to deal with that, we introduce two important techniques: stochastic smoothing and novel gradient estimate based on partial integration. We show that classic smoothing approaches ma

M. J. Duff

In a September 1976 PRL Eguchi and Freund considered two topological invariants: the Pontryagin number $P \sim \int d^4x \sqrt{g}R^* R$ and the Euler number $χ\sim \int d^4x \sqrt{g}R^* R^*$ and posed the question: to what anomalies do they contribute? They found that $P$ appears in the integrated divergence of the axial fermion number current, thus providin

Jian Tang, Sampsa Vihonen, TseChun Wang

Opaque detectors are a recently proposed novel detector concept where an opaque scintillator aligned with wavelength-shifting fibers is used to enable the discrimination of electron neutrinos and antineutrinos with a rather low energy threshold. In this work, we investigate the potential effects of the enhanced detection capabilities of the opaque detectors

Joss Wiese, Jolijn Onvlee, Sebastian Trippel, Jochen Küpper

Strong-field photoelectron momentum imaging of the prototypical biomolecule indole was disentangled in a combined experimental and computational approach. Experimentally, strong control over the molecules enabled the acquisition of photoelectron momentum distributions in the molecular frame for a well-defined, narrow range of incident intensities. A novel, h

STAR Collaboration, J. Adam, L. Adamczyk, J. R. Adams

In this letter, measurements of the shared momentum fraction ($z_{\rm{g}}$) and the groomed jet radius ($R_{\rm{g}}$), as defined in the SoftDrop algorihm, are reported in \pp collisions at $\sqrt{s} = 200$ GeV collected by the STAR experiment. These substructure observables are differentially measured for jets of varying resolution parameters from $R = 0.2

Jianxing Sun, Xinyu Jiang, Patricia B. Weisensee

Lubricant-infused surfaces (LISs) can promote stable dropwise condensation and improve heat transfer rates due to a low nucleation free-energy barrier and high droplet mobility. Topographical differences in the oil surface cause water microdroplets to rigorously self-propel long distances, continuously redistributing the oil film and potentially refreshing t

So Okada

We obtain some new results on the unimodal sequences of the real values of rational functions by polynomials with positive integer coefficients. Thus, we introduce the notion of merged-log-concavity of rational functions. Roughly speaking, the notion extends Stanley's $q$-log-concavity of polynomials. We construct explicit merged-log-concave rational functio

Danel Ahman, Matija Pretnar

We explore asynchronous programming with algebraic effects. We complement their conventional synchronous treatment by showing how to naturally also accommodate asynchrony within them, namely, by decoupling the execution of operation calls into signalling that an operation&#39;s implementation needs to be executed, and interrupting a running computation with

Yusheng Xiang, Tianqing Su, Xiaole Liu, Marcus Geimer

The fleet management of mobile working machines with the help of connectivity can increase not only safety but also productivity. However, rare mobile working machines have taken advantage of V2X. Moreover, no one published the simulation results that are suitable for evaluating the performance of the ad-hoc network at a working site on the highway where is

Markus Loecher

The default variable-importance measure in random Forests, Gini importance, has been shown to suffer from the bias of the underlying Gini-gain splitting criterion. While the alternative permutation importance is generally accepted as a reliable measure of variable importance, it is also computationally demanding and suffers from other shortcomings. We propos

Kenneth L. Schepler, Murat Yessenov, Yertay Zhiyenbayev, Ayman F. Abouraddy

We introduce the unique class of propagation-invariant surface plasmon polaritons (SPPs) representing pulsed surface wave packets propagating along unpatterned metal-dielectric interfaces and are localized in all dimensions - with potentially subwavelength transverse spatial widths. The characteristic features of such linear diffraction-free, dispersion-free

Huangjun Zhu

The uncertainty principle imposes a fundamental limit on predicting the measurement outcomes of incompatible observables even if complete classical information of the system state is known. The situation is different if one can build a quantum memory entangled with the system. Zero uncertainty states (in contrast with minimum uncertainty states) are peculiar

Madhurima Pandey, Debasish Majumdar, Amit Dutta Banik, Ashadul Halder

Violation of equivalence principle predicts that neutrinos of different flavor couple differently with gravity. Such a scenario can give rise to gravity induced flavor oscillations in addition to the usual mass flavor neutrino oscillations during the neutrino propagation. Even if the equivalence principle is indeed violated, their measure will be extremely s

Dario Benedetti, Sylvain Carrozza, Reiko Toriumi, Guillaume Valette

We study the double- and triple-scaling limits of a complex multi-matrix model, with $\mathrm{U}(N)^2\times \mathrm{O}(D)$ symmetry. The double-scaling limit amounts to taking simultaneously the large-$N$ (matrix size) and large-$D$ (number of matrices) limits while keeping the ratio $N/\sqrt{D}=M$ fixed. The triple-scaling limit consists in taking the large

Aitor Martin-Gomez, Thomas Eisenstecken, Gerhard Gompper, Roland G. Winkler

The conformational and dynamical properties of active polymers in solution are determined by the nature of the activity, and the behavior of polymers with self-propelled, active Brownian particle-type monomers differs qualitatively from that of polymers with monomers driven externally by colored noise forces. We present simulation and theoretical results for

Cong Yue, Zhongle Xie, Meihui Zhang, Gang Chen

In emerging applications such as blockchains and collaborative data analytics, there are strong demands for data immutability, multi-version accesses, and tamper-evident controls. This leads to three new index structures for immutable data, namely Merkle Patricia Trie (MPT), Merkle Bucket Tree (MBT), and Pattern-Oriented-Split Tree (POS-Tree). Although these

Naifu Zhang, Meixia Tao

Federated learning (FL) is a promising technique that enables many edge devices to train a machine learning model collaboratively in wireless networks. By exploiting the superposition nature of wireless waveforms, over-the-air computation (AirComp) can accelerate model aggregation and hence facilitate communication-efficient FL. Due to channel fading, power