December 2020 arXiv papers — page 101

Chung Koo Kim, Jonathan D. Denlinger, Asish K. Kundu, Genda Gu

Magnetism breaks the time reversal symmetry expected to open a Dirac gap in 3D topological insulators that consequently leads to quantum anomalous Hall effect. The most common approach of inducing ferromagnetic state is by doping magnetic 3$d$ elements into bulk of 3D topological insulators. In Cr$_{0.15}$(Bi$_{0.1}$Sb$_{0.9}$)$_{1.85}$Te$_3$, the material w

C. Hati, J. Kriewald, J. Orloff, A. M. Teixeira

Motivated by the recent experimental progress on the $B$-meson decay anomalies (in particular the angular observables in $B\to K^\ast\mu\mu$), we rely on a simplified-model approach to study the prospects of vector leptoquarks in what concerns numerous flavour observables, identifying several promising decay modes which would allow to (indirectly) probe such

Lourdes Juan, Andy Magid

Differential modules over a commutative differential ring R which are finitely generated projective as ring modules, with differential homomorphisms, form an additive category, so their isomorphism classes form a monoid. We study the quotient monoid of this monoid by the submonoid of isomorphism classes of free modules with component wise derivation. This qu

Joscha Diehl, Rosa Preiß, Michael Ruddy, Nikolas Tapia

Geometric features, robust to noise, of curves in Euclidean space are of great interest for various applications such as machine learning and image analysis. We apply the Fels-Olver's moving frame method (for geometric features) paired with the log-signature transform (for robust features) to construct a set of integral invariants under rigid motions for cur

Boris Pritychenko

Recent multi-messenger detection of the binary neutron star merger (GW170817) energized the astrophysical community and encouraged further research for determination of nuclear physics observables. Comprehensive studies of atomic nuclei in the cosmos provide an opportunity for investigating these astrophysical phenomena and acquiring complementary informatio

Nicolas Camps

We consider the cubic Schr\"odinger equation on the euclidean space perturbed by a short-range potential $V$. The presence of a negative simple eigenvalue for $-\Delta+V$ gives rise to a curve of small and localized nonlinear ground states that yield some time-periodic solutions known to be asymptotically stable in the energy space. We study the persistence

Lin Yen-Chen, Pete Florence, Jonathan T. Barron, Alberto Rodriguez

We present iNeRF, a framework that performs mesh-free pose estimation by "inverting" a Neural RadianceField (NeRF). NeRFs have been shown to be remarkably effective for the task of view synthesis - synthesizing photorealistic novel views of real-world scenes or objects. In this work, we investigate whether we can apply analysis-by-synthesis via NeRF for mesh

Artur d'Avila Garcez, Luis C. Lamb

Current advances in Artificial Intelligence (AI) and Machine Learning (ML) have achieved unprecedented impact across research communities and industry. Nevertheless, concerns about trust, safety, interpretability and accountability of AI were raised by influential thinkers. Many have identified the need for well-founded knowledge representation and reasoning

Benjamin V. Lehmann, Olivia G. Ross, Ava Webber, Stefano Profumo

We study the capture of light objects of arbitrary velocity by binary systems. Extending results for the capture of comets in the solar system, we develop a simple geometric characterization of the capture cross section, leading directly to the distribution of orbital parameters of captured objects. We use the same framework to study the lifetimes of these b

Dustin Morrill, Ryan D'Orazio, Reca Sarfati, Marc Lanctot

Driven by recent successes in two-player, zero-sum game solving and playing, artificial intelligence work on games has increasingly focused on algorithms that produce equilibrium-based strategies. However, this approach has been less effective at producing competent players in general-sum games or those with more than two players than in two-player, zero-sum

F. Bellini, M. Beretta, L. Cardani, P. Carniti

The production of ultra-pure raw material is a crucial step to ensure the required background level in rare event searches. In this work, we establish an innovative technique developed to produce high-purity (99.999%) granular zinc. We demonstrate the effectiveness of the refining procedure by measuring the internal contaminations of the purified zinc with a

Piyali Banerjee, Urjit Yajnik

Low scale leptogenesis scenarios are difficult to verify due to our inability to relate the parameters involved in the early universe processes with the low energy or collider observables. Here we show that one can in principle relate the parameters giving rise to the transient $CP$ violating phase involved in leptogenesis with those that can be deduced from

Francesco Calabrò, Gianluca Fabiani, Constantinos Siettos

We introduce a new numerical method based on machine learning to approximate the solution of elliptic partial differential equations with collocation using a set of sigmoidal functions. We show that a feedforward neural network with a single hidden layer with sigmoidal functions and fixed, random, internal weights and biases can be used to compute accurately

Kathryn M. Zurek

We propose a simple model of spacetime vacuum fluctuations motivated by AdS/CFT, where the vacuum is described by a thermal density matrix, $\rho = \frac{e^{-K}}{\mbox{Tr}(e^{-K})}$ with $K$ the modular Hamiltonian. In AdS/CFT, both the expectation value of $K$ and its fluctuations $\langle \Delta K^2 \rangle$ have been calculated; both obey an area law iden

Heiko Augustin, Niklaus Berger, Sebastian Dittmeier, David Maximilian Immig

Many years of research and development of High Voltage Monolithic Active Pixel Sensors (HVMAPS) have culminated in the final design for the Mu3e pixel sensor. MuPix10 is a fully monolithic sensor with an active pixel matrix size of $20\times20\,\mathrm{mm}^2$ produced in the $180\,\mathrm{nm}$ HV-CMOS process at TSI Semiconductors. The pixel size is $80\time

Shaanan Cohney, Ross Teixeira, Anne Kohlbrenner, Arvind Narayanan

Universities have been forced to rely on remote educational technology to facilitate the rapid shift to online learning. In doing so, they acquire new risks of security vulnerabilities and privacy violations. To help universities navigate this landscape, we develop a model that describes the actors, incentives, and risks, informed by surveying 49 educators a

Thibault Bertrand, Chiu Fan Lee

Active matter is not only indispensable to our understanding of diverse biological processes, but also provides a fertile ground for discovering novel physics. Many emergent properties impossible for equilibrium systems have been demonstrated in active systems. These emergent features include motility-induced phase separation, long-ranged ordered (collective

Rivu Gupta, Shashank Gupta, Shiladitya Mal, Aditi Sen De

In order to understand the resourcefulness of a natural quantum system in quantum communication tasks, we study the dense coding capacity (DCC) and teleportation fidelity (TF) of Haar uniformly generated random multipartite states of various ranks. We prove that when a rank-2 two-qubit state, a Werner state, and a pure state possess the same amount of entang

Bingyao Huang, Haibin Ling

Light-based adversarial attacks use spatial augmented reality (SAR) techniques to fool image classifiers by altering the physical light condition with a controllable light source, e.g., a projector. Compared with physical attacks that place hand-crafted adversarial objects, projector-based ones obviate modifying the physical entities, and can be performed tr

A. Schootemeijer, N. Langer, D. Lennon, C. J. Evans

Massive star evolution at low metallicity is closely connected to many fields in high-redshift astrophysics, but poorly understood. The Small Magellanic Cloud (SMC) is a unique laboratory to study this because of its metallicity of 0.2 Zsol, its proximity, and because it is currently forming stars. We used a spectral type catalog in combination with GAIA mag

Evangelos Paouris, Jasa Calogovic, Mateja Dumbovic, M. Leila Mays

The Effective Acceleration Model (EAM) predicts the Time-of-Arrival (ToA) of the Coronal Mass Ejection (CME) driven shock and the average speed within the sheath at 1 AU. The model is based on the assumption that the ambient solar wind interacts with the interplanetary CME (ICME) resulting in constant acceleration or deceleration. The upgraded version of the

Luiz F. C. Moraes, Andreia Saguia, Alan C. Santos, Marcelo S. Sarandy

The storage and transfer of energy through quantum batteries are key elements in quantum networks. Here, we propose a charger design based on transitionless quantum driving (TQD), which allows for inherent control over the battery charging time, with the speed of charging coming at the cost of the internal energy available to implement the dynamics. Moreover

Jakub Dolezal, Robert L. Jack

In systems of diffusing particles, we investigate large deviations of a time-averaged measure of clustering around one particle. We focus on biased ensembles of trajectories, which realise large-deviation events. The bias acts on a single particle, but elicits a response that spans the whole system. We analyse this effect through the lens of Macroscopic Fluc

Sebastian Schleißinger

Quantum probability theory and complex analysis for children.

Spiros Cotsakis, Dimitrios Trachilis

We study the problem of the instability of inhomogeneous radiation universes in quadratic lagrangian theories of gravity written as a system of evolution equations with constraints. We construct formal series expansions and show that the resulting solutions have a smaller number of arbitrary functions than that required in a general solution. These results c

Ying Zhou, Dingke Tang, Dehan Kong, Linbo Wang

A key challenge in causal inference from observational studies is the identification and estimation of causal effects in the presence of unmeasured confounding. In this paper, we introduce a novel approach for causal inference that leverages information in multiple outcomes to deal with unmeasured confounding. The key assumption in our approach is conditiona

Dominique Mattei

A complex smooth prime Fano threefold $X$ of genus $9$ is related via projective duality to a quartic plane curve $\Gamma$. We use this setup to study the restriction of rank $2$ stable sheaves with prescribed Chern classes on $X$ to an anticanonical $K3$ surface $S\subset X$. Varying the threefold $X$ containing $S$ gives a rational Lagrangian fibration $$\

Joao Magueijo

We examine the status of the Chern-Simons (or Kodama) state from the point of view of a formulation of gravity that uses only real connection and metric variables and a real action. We may package the {\it real} connection variables into the complex Self-Dual Ashtekar connection (and will do so to make contact with previous work), but that operation is essen

Moein Sorkhei, Gustav Eje Henter, Hedvig Kjellström

Autonomous agents, such as driverless cars, require large amounts of labeled visual data for their training. A viable approach for acquiring such data is training a generative model with collected real data, and then augmenting the collected real dataset with synthetic images from the model, generated with control of the scene layout and ground truth labelin

Jane S. Greaves, William Bains, Janusz J. Petkowski, Sara Seager

We published spectra of phosphine molecules in Venus' clouds, following open-science principles in releasing data and scripts (with community input leading to ALMA re-processing, now benefiting multiple projects). Some misconceptions about de-trending of spectral baselines have also emerged, which we address here. Using the JCMT PH3-discovery data, we show t

Maret Einasto

The largest galaxy systems in the cosmic web are superclusters, overdensity regions of galaxies, groups, clusters, and filaments. Low-density regions around superclusters are called basins of attraction or cocoons. In my talk I discuss the properties of galaxies, groups, and filaments in the A2142 supercluster and its cocoon at redshift $z \approx 0.09$. Coc

Michael G. Kapteyn, Jacob V. R. Pretorius, Karen E. Willcox

A unifying mathematical formulation is needed to move from one-off digital twins built through custom implementations to robust digital twin implementations at scale. This work proposes a probabilistic graphical model as a formal mathematical representation of a digital twin and its associated physical asset. We create an abstraction of the asset-twin system

P. V. Sriluckshmy, Max Nusspickel, Edoardo Fertitta, George H. Booth

Quantum embedding approaches involve the self-consistent optimization of a local fragment of a strongly correlated system, entangled with the wider environment. The `energy-weighted' density matrix embedding theory (EwDMET) was established recently as a way to systematically control the resolution of the fragment-environment coupling, and allow for true quan

Filipp N. Rybakov, Anastasiia Pervishko, Olle Eriksson, Egor Babaev

Here by combining a symmetry-based analysis with numerical computations we predict a new kind of magnetic ordering - antichiral ferromagnetism. The relationship between chiral and antichiral magnetic order is conceptually similar to the relationship between ferromagnetic and antiferromagnetic order. Without loss of generality, we focus our investigation on c

N. Saffold, T. Aramaki, R. Bird, M. Boezio

The General Antiparticle Spectrometer (GAPS) is an Antarctic balloon experiment designed for low-energy (0.1$-$0.3 GeV/$n$) cosmic antinuclei as signatures of dark matter annihilation or decay. GAPS is optimized to detect low-energy antideuterons, as well as to provide unprecedented sensitivity to low-energy antiprotons and antihelium nuclei. The novel GAPS

Grisha Spektor, Eva Prinz, Michael Hartelt, Anna-Katharina Mahro

Orbital angular momentum of light is a core feature in photonics. Its confinement to surfaces using plasmonics has unlocked many phenomena and potential applications. Here we introduce the reflection from structural boundaries as a new degree of freedom to generate and control plasmonic orbital angular momentum. We experimentally demonstrate plasmonic vortex

S. Ajmal, M. Rehman, F. Tahir

In this article, we study the two body gluino decays $\tilde{g} \rightarrow \tilde{u}_i \bar{u}_g$, $\tilde{g} \rightarrow \tilde{d}_i \bar{d}_g$ with $i=1,2,...6$ and $g=1,2,3$ in the Minimal Supersymmetric Standard Model (MSSM) with quark flavour violation (QFV). At the outset, constraints on QFV parameters $\delta _{ij}^{U/D(LR)}$ and $\delta _{ij}^{U/D(R

Vishwa Vijay Singh, Liliane Biskupek, Jürgen Müller, Mingyue Zhang

Lunar Laser Ranging (LLR) measures the distance between observatories on Earth and retro-reflectors on Moon since 1970. In this paper, we study the effect of non-tidal station loading (NTSL) in the analysis of LLR data. We add the non-tidal loading effect provided by three data centres: the German Research Centre for Geosciences (GFZ), the International Mass

Eric Buffenoir

We develop a possibilistic semantic formalism for quantum phenomena from an operational perspective. This semantic system is based on a Chu duality between preparation processes and yes/no tests, the target space being a three-valued set equipped with an informational interpretation. A basic set of axioms is introduced for the space of states. This basic set

Anjana Jayaraman, Junhyuk Kang, Megan A. Jamiolkowski, William R. Wagner

Continuous-flow ventricular assist devices (VADs) have been an increasingly common, life-saving therapy for advanced heart-failure patients, but elevate the risk of thrombosis due to a combination of non-physiological hemodynamics and synthetic biomaterials. Limited work has been done to address platelet adhesion and aggregation on artificial surfaces under

Alexandru Ţifrea, Eric Stavarache, Fanny Yang

Deep neural networks often predict samples with high confidence even when they come from unseen classes and should instead be flagged for expert evaluation. Current novelty detection algorithms cannot reliably identify such near OOD points unless they have access to labeled data that is similar to these novel samples. In this paper, we develop a new ensemble

Siegfried Hörmann, Fatima Jammoul

We consider functional data which are measured on a discrete set of observation points. Often such data are measured with additional noise. We explore in this paper the factor structure underlying this type of data. We show that the latent signal can be attributed to the common components of a corresponding factor model and can be estimated accordingly, by b

L. G. Poniatowski, J. O. Sundqvist, N. D. Kee, S. P. Owocki

Vigorous mass loss in the classical Wolf-Rayet (WR) phase is important for the late evolution and final fate of massive stars. We develop spherically symmetric time-dependent and steady-state hydrodynamical models of the radiation-driven wind outflows and associated mass loss from classical WR stars. The simulations are based on combining the opacities typic

Matteo Braglia, Xingang Chen, Dhiraj Kumar Hazra

The stochastic gravitational wave background (SGWB) offers a new opportunity to observe signals of primordial features from inflationary models. We study their detectability with future space-based gravitational waves experiments, focusing our analysis on the frequency range of the LISA mission. We compute gravitational wave spectra from primordial features

Ben Moews, Romeel Davé, Sourav Mitra, Sultan Hassan

While cosmological dark matter-only simulations relying solely on gravitational effects are comparably fast to compute, baryonic properties in simulated galaxies require complex hydrodynamic simulations that are computationally costly to run. We explore the merging of an extended version of the equilibrium model, an analytic formalism describing the evolutio

Kevin A. Madsen, Piet W. Brouwer, Patrik Recher, Peter G. Silvestrov

The interaction of a magnetic insulator with the helical electronic edge of a two-dimensional topological insulator has been shown to lead to many interesting phenomena. One of these is that for a suitable orientation of the magnetic anisotropy axis, the exchange coupling to an easy-plane magnet has no effect on DC electrical transport through a helical edge

Matthias Hofmann, James B. Kennedy, Delio Mugnolo, Marvin Plümer

We establish metric graph counterparts of Pleijel's theorem on the asymptotics of the number of nodal domains $\nu_n$ of the $n$-th eigenfunction(s) of a broad class of operators on compact metric graphs, including Schr\"odinger operators with $L^1$-potentials and a variety of vertex conditions as well as the $p$-Laplacian with natural vertex conditions, and

Lasma Alberte, Claudia de Rham, Sumer Jaitly, Andrew J. Tolley

We apply positivity bounds directly to a $U(1)$ gauge theory with charged scalars and charged fermions, i.e. QED, minimally coupled to gravity. Assuming that the massless $t$-channel pole may be discarded, we show that the improved positivity bounds are violated unless new physics is introduced at the parametrically low scale $\Lambda_{\rm new} \sim (e m M_{

Andrea Simonelli, Samuel Rota Bulò, Lorenzo Porzi, Peter Kontschieder

Pseudo-LiDAR-based methods for monocular 3D object detection have received considerable attention in the community due to the performance gains exhibited on the KITTI3D benchmark, in particular on the commonly reported validation split. This generated a distorted impression about the superiority of Pseudo-LiDAR-based (PL-based) approaches over methods workin

Jan Friedrich, Simone Göttlich, Elena Rossi

We present a multilane traffic model based on balance laws, where the nonlocal source term is used to describe the lane changing rate. The modelling framework includes the consideration of local and nonlocal flux functions. Based on a Godunov type numerical scheme, we provide BV estimates and a discrete entropy inequality. Together with the $L^1$-contractivi

Robin Corgier, Luca Pezzè, Augusto Smerzi

We propose a scheme for trapped atom interferometry using an interacting Bose-Einstein condensate. The condensate is controlled and spatially split in two confined external momentum modes through a series Bragg pulses. The proposed scheme (i) allows the generation of large entanglement in a trapped-interferometer configuration via one-axis twisting dynamic i

C. Pellet-Mary, P. Huillery, M. Perdriat, A. Tallaire

The electronic spins of the nitrogen-vacancy centers (NV centers) in Chemical-Vapor-Deposition (CVD) grown diamonds form ideal probes of magnetic fields and temperature, as well as promising qu-bits for quantum information processing. Studying and controlling the magnetic environment of NV centers in such high purity crystals is thus essential for these appl

Tarik Kazaz, Jac Romme, Gerard J. M. Janssen, Alle-Jan van der Veen

The presence of rich scattering in indoor and urban radio propagation scenarios may cause a high arrival density of multipath components (MPCs). Often the MPCs arrive in clusters at the receiver, where MPCs within one cluster have similar angles and delays. The MPCs arriving within a single cluster are typically unresolvable in the delay domain. In this pape

Zhen-Tao Zhang, Dong E. Liu

Reading out Majorana bound states (MBSs) is essential both to verify their non-Abelian property and to realize topological quantum computation. Here, we construct a protocol to measure the parity of two MBSs in a Majorana island coupled to double quantum dot (DQD). The parity information is mapped to the charge state of the DQD through Landau-Zener transitio

Charles Guille-Escuret, Baptiste Goujaud, Manuela Girotti, Ioannis Mitliagkas

The study of first-order optimization algorithms (FOA) typically starts with assumptions on the objective functions, most commonly smoothness and strong convexity. These metrics are used to tune the hyperparameters of FOA. We introduce a class of perturbations quantified via a new norm, called *-norm. We show that adding a small perturbation to the objective

Sutapa Saha, Tamal Guha, Some Sankar Bhattacharya, Manik Banik

The framework of distributed computing, consisting of several spatially separated input-output servers, has immense importance in distant data manipulation. One of the most challenging parts of this setting is to optimize the use of information transmission lines among distant servers. In this work, we have modeled such a physically motivated distributed com

Peize Sun, Yi Jiang, Enze Xie, Wenqi Shao

Object detection has recently achieved a breakthrough for removing the last one non-differentiable component in the pipeline, Non-Maximum Suppression (NMS), and building up an end-to-end system. However, what makes for its one-to-one prediction has not been well understood. In this paper, we first point out that one-to-one positive sample assignment is the k

Theresa C. Anderson, Bingyang Hu

In this paper, we prove a structure theorem for the infinite union of $n$-adic doubling measures via techniques which involve far numbers. Our approach extends the results of Wu in 1998, and as a by product, we also prove a classification result related to normal numbers.

Yann Rollin

We prove that every smoothly immersed 2-torus of $\mathbb{R}^4$ can be approximated, in the C0-sense, by immersed polyhedral Lagrangian tori. In the case of a smoothly immersed (resp. embedded) Lagrangian torus of $\mathbb{R}^4$, the surface can be approximated in the C1-sense by immersed (resp. embedded) polyhedral Lagrangian tori. Similar statements are pr

Andrea Lekkas, Peter Schneider-Kamp, Isabelle Augenstein

The effectiveness of a language model is influenced by its token representations, which must encode contextual information and handle the same word form having a plurality of meanings (polysemy). Currently, none of the common language modelling architectures explicitly model polysemy. We propose a language model which not only predicts the next word, but als

Arnaud Maret

This note investigates the dynamics of the mapping class group action on the character variety of super-maximal representations of the fundamental group of a punctured sphere into $\text{PSL}(2,\mathbb{R})$, discovered by Deroin and Tholozan. We apply symplectic methods developed by Goldman and Xia to prove that the action is ergodic.

Antonio Rago, Emanuele Albini, Pietro Baroni, Francesca Toni

One of the most pressing issues in AI in recent years has been the need to address the lack of explainability of many of its models. We focus on explanations for discrete Bayesian network classifiers (BCs), targeting greater transparency of their inner workings by including intermediate variables in explanations, rather than just the input and output variabl

Fredrik Viklund, Yilin Wang

We study foliations by chord-arc Jordan curves of the twice punctured Riemann sphere $\mathbb C \smallsetminus \{0\}$ using the Loewner-Kufarev equation. We associate to such a foliation a function on the plane that describes the "local winding" along each leaf. Our main theorem is that this function has finite Dirichlet energy if and only if the Loewner dri

Suvrat Raju

We review recent progress on the information paradox. We explain why exponentially small correlations in the radiation emitted by a black hole are sufficient to resolve the original paradox put forward by Hawking. We then describe a refinement of the paradox that makes essential reference to the black-hole interior. This analysis leads to a broadly-applicabl

Yung-Kun Liu, Pisin Chen, Yuan Fang

Flying plasma mirrors induced by intense lasers has been proposed as a promising way to generate few-cycle EUV or X-ray lasers. In addition, if such a relativistic plasma mirror can accelerate, then it would serve as an analog black hole to investigate the information loss paradox associated with the black hole Hawking evaporation. Among these applications,

Ranyiliu Chen, Zhixin Song, Xuanqiang Zhao, Xin Wang

Estimating the difference between quantum data is crucial in quantum computing. However, as typical characterizations of quantum data similarity, the trace distance and quantum fidelity are believed to be exponentially-hard to evaluate in general. In this work, we introduce hybrid quantum-classical algorithms for these two distance measures on near-term quan

Yulei Qin, Hao Zheng, Yun Gu, Xiaolin Huang

Training convolutional neural networks (CNNs) for segmentation of pulmonary airway, artery, and vein is challenging due to sparse supervisory signals caused by the severe class imbalance between tubular targets and background. We present a CNNs-based method for accurate airway and artery-vein segmentation in non-contrast computed tomography. It enjoys superi

Emanuele Albini, Piyawat Lertvittayakumjorn, Antonio Rago, Francesca Toni

Despite the recent, widespread focus on eXplainable AI (XAI), explanations computed by XAI methods tend to provide little insight into the functioning of Neural Networks (NNs). We propose a novel framework for obtaining (local) explanations from NNs while providing transparency about their inner workings, and show how to deploy it for various neural architec

Sejin Kim, Michal Kazmierski, Benjamin Haibe-Kains

Accurate survival prediction is crucial for development of precision cancer medicine, creating the need for new sources of prognostic information. Recently, there has been significant interest in exploiting routinely collected clinical and medical imaging data to discover new prognostic markers in multiple cancer types. However, most of the previous studies

Flavio B. Gonçalves, Barbara C. C. Dias

This paper proposes a new methodology to perform Bayesian inference for a class of multidimensional Cox processes in which the intensity function is piecewise constant. Poisson processes with piecewise constant intensity functions are believed to be suitable to model a variety of point process phenomena and, given its simpler structure, are expected to provi

Stefan Antusch, Johannes Rosskopp

It has been proposed that the coherent propagation of long-lived heavy neutrino mass eigenstates can lead to an oscillating rate of lepton number conserving (LNC) and violating (LNV) events, as a function of the distance between the production and displaced decay vertices. We discuss this phenomenon, which we refer to as heavy neutrino-antineutrino oscillati

Dominic Verdon

Let G and G' be monoidally equivalent compact quantum groups, and let H be a Hopf-Galois object realising a monoidal equivalence between these groups' representation categories. This monoidal equivalence induces an equivalence Chan(G) -> Chan(G'), where Chan(G) is the category whose objects are finite-dimensional C*-algebras with an action of G and whose mor

Trung-Hieu Tran, Long Phan, Truong-Son Nguyen, Tien-Huy Nguyen

This paper proposed several transformer-based approaches for Reliable Intelligence Identification on Vietnamese social network sites at VLSP 2020 evaluation campaign. We exploit both of monolingual and multilingual pre-trained models. Besides, we utilize the ensemble method to improve the robustness of different approaches. Our team achieved a score of 0.937

Vincent Tan, Stefan Zohren

We introduce a novel covariance estimator for portfolio selection that adapts to the non-stationary or persistent heteroskedastic environments of financial time series by employing exponentially weighted averages and nonlinearly shrinking the sample eigenvalues through cross-validation. Our estimator is structure agnostic, transparent, and computationally fe

Lingda Wang, Bingcong Li, Huozhi Zhou, Georgios B. Giannakis

This paper studies the adversarial graphical contextual bandits, a variant of adversarial multi-armed bandits that leverage two categories of the most common side information: \emph{contexts} and \emph{side observations}. In this setting, a learning agent repeatedly chooses from a set of $K$ actions after being presented with a $d$-dimensional context vector

Dorian Baudry, Romain Gautron, Emilie Kaufmann, Odalric-Ambryn Maillard

In this paper we study a multi-arm bandit problem in which the quality of each arm is measured by the Conditional Value at Risk (CVaR) at some level alpha of the reward distribution. While existing works in this setting mainly focus on Upper Confidence Bound algorithms, we introduce a new Thompson Sampling approach for CVaR bandits on bounded rewards that is

Guo-Yi Zhu, Markus Heyl

Disorder-free localization has recently emerged as a mechanism for ergodicity breaking in homogeneous lattice gauge theories. In this work we show that this mechanism can lead to unconventional states of quantum matter as the absence of thermalization lifts constraints imposed by equilibrium statistical physics. We study a Kitaev honeycomb model in a skew ma

Rodrigo Tenorio, David Keitel, Alicia M. Sintes

Searches for continuous gravitational waves from unknown sources attempt to detect long-lasting gravitational radiation by identifying Doppler-modulated signatures in the data. Semicoherent methods allow for wide parameter space surveys, identifying interesting regions to be followed up using more sensitive (and computationally expensive) tools. Thus, it is

Daniel Spitz, Anna Wienhard

Persistent homology provides a robust methodology to infer topological structures from point cloud data. Here we explore the persistent homology of point clouds embedded into a probabilistic setting, exploiting the theory of point processes. We introduce measures on the space of persistence diagrams and the self-similar scaling of a one-parameter family of t

Ali Hasan Md. Linkon, Md. Mahir Labib, Faisal Haque Bappy, Soumik Sarker

Automatic detection and recognition of banknotes can be a very useful technology for people with visual difficulties and also for the banks itself by providing efficient management for handling different paper currencies. Lightweight models can easily be integrated into any handy IoT based gadgets/devices. This article presents our experiments on several sta

Latif Salum

This paper shows that P = NP = PSPACE. It also tackles Graph Isomorphism.

Yunang Chen, Amrita Roy Chowdhury, Ruizhe Wang, Andrei Sabelfeld

Trigger-action platforms (TAPs) allow users to connect independent web-based or IoT services to achieve useful automation. They provide a simple interface that helps end-users create trigger-compute-action rules that pass data between disparate Internet services. Unfortunately, TAPs introduce a large-scale security risk: if they are compromised, attackers wi

Abdusattar Kurban, Yong-Feng Huang, Jin-Jun Geng, Hong-Shi Zong

The ground state of matter may be strange quark matter (SQM), not hadronic matter. A whole sequence of SQM objects, ranging from strange quark stars and strange quark dwarfs to strange quark planets, can stably exist according to this SQM hypothesis. A strange dwarf has a mass similar to that of a normal white dwarf but could harbor an extremely dense SQM co

Patrick Tinsley, Adam Czajka, Patrick Flynn

Generative adversarial networks (GANs) are able to generate high resolution photo-realistic images of objects that "do not exist." These synthetic images are rather difficult to detect as fake. However, the manner in which these generative models are trained hints at a potential for information leakage from the supplied training data, especially in the conte

Hai-Liang Wu

Determinants with Legendre symbol entries have close relations with character sums and elliptic curves over finite fields. In recent years, Sun, Krachun and his cooperators studied this topic. In this paper, we confirm some conjectures posed by Sun and investigate some related topics. For instance, given any integers $c,d$ with $d\ne0$ and $c^2-4d\ne0$, we s

Daria Kern, Andre Mastmeyer

This paper discusses current methods and trends for 3D bounding box detection in volumetric medical image data. For this purpose, an overview of relevant papers from recent years is given. 2D and 3D implementations are discussed and compared. Multiple identified approaches for localizing anatomical structures are presented. The results show that most researc

Yu Yao, Klaas E. Stephan

In this paper, we address technical difficulties that arise when applying Markov chain Monte Carlo (MCMC) to hierarchical models designed to perform clustering in the space of latent parameters of subject-wise generative models. Specifically, we focus on the case where the subject-wise generative model is a dynamic causal model (DCM) for fMRI and clusters ar

Francesco D'Eramo, Nejc Košnik, Federico Pobbe, Aleks Smolkovič

We investigate scenarios with $\mathcal{O}(1\mathrm{\,TeV})$ scalar leptoquarks that act as portals between the Standard Model and Dark Matter. We assume that Dark Matter is a scalar singlet $S$ which couples to a scalar leptoquark $\Delta$ and the Higgs boson via the terms in the scalar potential. In addition, the leptoquark is endowed with Yukawa couplings

Andreas Nugaard Holm, Barbara Plank, Dustin Wright, Isabelle Augenstein

Citation count prediction is the task of predicting the number of citations a paper has gained after a period of time. Prior work viewed this as a static prediction task. As papers and their citations evolve over time, considering the dynamics of the number of citations a paper will receive would seem logical. Here, we introduce the task of sequence citation

Dmitry Karlovets

The possibilities to accelerate vortex electrons with orbital angular momentum (OAM) to relativistic energies and to produce vortex ions, protons, and other charged particles crucially depend on whether the OAM is conserved during the acceleration and on how phase space of the wave packet evolves. We show that both the OAM and a mean emittance of the packet,

Manal, Ali Hasan Md. Linkon, Md. Mahir Labib, Marium-E-Jannat

In today's world, Neural Style Transfer (NST) has become a trendsetting term. NST combines two pictures, a content picture and a reference image in style (such as the work of a renowned painter) in a way that makes the output image look like an image of the material, but rendered with the form of a reference picture. However, there is no study using the artw

Chia-Wei Tang, Chao-Lin Liu, Po-Sen Chiu

The information provided by historical documents has always been indispensable in the transmission of human civilization, but it has also made these books susceptible to damage due to various factors. Thanks to recent technology, the automatic digitization of these documents are one of the quickest and most effective means of preservation. The main steps of

Hyunju Go

According to 't Hooft, restoring Poincar\'e invariance in a holographic cellular automaton (CA) requires two distinct evolution laws that commute. We explore how this is realized in the AdS/CFT framework, assuming commutativity as a fundamental principle--much like general covariance once did--for encoding curvature. In our setup, physical processes in a giv

Yi-Yu Lin, Jia-Rui Sun, Yuan Sun

We investigate the relations between bit thread, entanglement distillation and entanglement of purification in the holographic framework. Specifically, we give a bit thread interpretation for the one-shot entanglement distillation (OSED) tensor network, which can be understood as reconstructing the geometric structure of the bulk spacetime from the entanglem

K. E. Siewierska, G. Atcheson, A. Jha, K. Esien

The ruthenium content of half-metallic Mn$_2$Ru$_x$Ga thin films, with a biaxially-strained inverse Heusler structure, controls the ferrimagnetism that determines their magnetic and electronic properties. An extensive study of Mn$_y$Ru$_x$Ga films on MgO (100) substrates with $1.8 \leq y \leq 2.6$ and $x = 0.5$, 0.7 or 0.9, including crystallographic, magnet

Shen-Song Wan, Daize Li, Bonan Zhang, Marco Ruggieri

We study the effect of periodic boundary conditions on chiral symmetry breaking and its restoration in Quantum Chromodynamics. As an effective model of the effective potential for the quark condensate, we use the quark-meson model, while the theory is quantized in a cubic box of size $L$. After specifying a renormalization prescription for the vacuum quark l

Marta Prada

Dirac carriers in graphene are commonly characterized by a pseudospin degree of freedom, arising from the degeneracy of the two inequivalent sublattices. The inherent chirality of the quasiparticles leads to a topologically non-trivial band structure, where the in-plane component of sublattice spin and momentum are intertwined. Equivalently, sublattice imbal

Deepthi S. Prabhu, Annapurni Subramaniam, Snehalata Sahu

In this study, we identified and characterized the hot and luminous UV-bright stars in the globular cluster NGC 2808. We combined data from the Ultra Violet Imaging Telescope (UVIT) on-board the Indian space satellite, AstroSat, with the Hubble Space Telescope UV Globular Cluster Survey (HUGS) data for the central region (within $\sim$ $\ang[angle-symbol-ove

E. González Egea, R. Raddi, D. Koester, L. K. Rogers

Spectroscopic observations of white dwarfs reveal that many of them are polluted by exoplanetary material, whose bulk composition can be uniquely probed this way. We present a spectroscopic and photometric analysis of the DA white dwarf WDJ181417.84$-$735459.83, an object originally identified to have a strong infrared excess in the 2MASS and WISE catalogues

Muxin Han, Hongguang Liu

We propose a new model of the spherical symmetric quantum black hole in the reduced phase space formulation. We deparametrize gravity by coupling to the Gaussian dust which provides the material coordinates. The foliation by dust coordinates covers both the interior and exterior of the black hole. After the spherical symmetry reduction, our model is a 1+1 di