January 2022 arXiv papers — page 111

Michael J. Catanzaro, Lee Przybylski, Eric S. Weber

We develop a method for calculating the persistence landscapes of affine fractals using the parameters of the corresponding transformations. Given an iterated function system of affine transformations that satisfies a certain compatibility condition, we prove that there exists an affine transformation acting on the space of persistence landscapes which inter

Zecang Gu, Xiaoqi Sun, Yuan Sun, Fuquan Zhang

Unsupervised clustering algorithm can effectively reduce the dimension of high-dimensional unlabeled data, thus reducing the time and space complexity of data processing. However, the traditional clustering algorithm needs to set the upper bound of the number of categories in advance, and the deep learning clustering algorithm will fall into the problem of l

Jacob Finkenrath, Constantia Alexandrou, Simone Bacchio, Martha Constantinou

Lattice QCD simulations directly at physical masses of dynamical light, strange and charm quarks are highly desirable especially to remove systematic errors due to chiral extrapolations. However such simulations are still challenging. We discuss the adaption of efficient algorithms, like multi-grid methods or higher order integrators, within the molecular dy

Amir Hussein, Shammur Absar Chowdhury, Ahmed Abdelali, Najim Dehak

The pervasiveness of intra-utterance code-switching (CS) in spoken content requires that speech recognition (ASR) systems handle mixed language. Designing a CS-ASR system has many challenges, mainly due to data scarcity, grammatical structure complexity, and domain mismatch. The most common method for addressing CS is to train an ASR system with the availabl

Angela A. Albanese, Claudio Mele

We determine multiplication and convolution topological algebras for classes of $\omega$-ultradifferentiable functions of Beurling type. Hypocontinuity and discontinuity of the multiplication and convolution mappings are also investigated.

Bernet E. Meijer, Shurong Yuan, Guanqun Cai, Richard J. Dixey

The deceptively simple inorganic salt ammonium sulfate undergoes a ferroelectric phase transition associated with a very large entropy change and both electrocaloric and barocaloric functionality. While the structural origins of the electrical polarisation are now well established, those of the entropy change have been controversial for over fifty years. Thi

William E. Carson, Austin Talbot, David Carlson

Deep autoencoders are often extended with a supervised or adversarial loss to learn latent representations with desirable properties, such as greater predictivity of labels and outcomes or fairness with respects to a sensitive variable. Despite the ubiquity of supervised and adversarial deep latent factor models, these methods should demonstrate improvement

Francesca D'Antona, Antonino P. Milone, Christian I. Johnson, Marco Tailo

We present Hubble Space Telescope (HST) photometric results for NGC 6402, a highly reddened very luminous Galactic globular cluster (GC). Recent spectroscopic observations of its red giant stars have shown a quite peculiar behavior in the chemistry of its multiple populations. These results have prompted UV and optical HST observations aimed at obtaining the

Daniel Huerga

We introduce a hybrid quantum-classical variational algorithm to simulate ground-state phase diagrams of frustrated quantum spin models in the thermodynamic limit. The method is based on a cluster-Gutzwiller ansatz where the wave function of the cluster is provided by a parameterized quantum circuit whose key ingredient is a two-qubit real XY gate allowing t

Xolani Maphisa, Robert Warmbier

The combination of pressure and vacancy defects are investigated to find the ideal conditions that would create meaningful $sp^3$ interlinking without causing severe damage to the single-walled carbon nanotubes (SWCNTs). Naturally occurring defects fail to induce interlinking. The introduction of vacancy type defects reduces the collapse pressure of the SWCN

Zhenwei Lyu, Nan Jiang, Kent Yagi

Recent gravitational wave observations allow us to probe gravity in the strong and dynamical field regime. In this paper, we focus on testing Einstein-dilaton Gauss-Bonnet gravity which is motivated by string theory. In particular, we use two new neutron star black hole binaries (GW200105 and GW200115). We also consider GW190814 which is consistent with both

Scott Perkins, Nicolas Yunes

Gravitational wave observations have great potential to reveal new information about the fundamental nature of gravity, but extracting that information can be difficult. One popular technique is the parametrized inspiral test of general relativity (a realization of the parametrized post-Einsteinian framework), where the gravitational waveform, as calculated

Klaus W. Hodapp, Scott E. Dahm, Watson P. Varricatt

We report a historic Ks-band light curve spanning over three decades of the FUor PGIR20dci recently discovered by Hillenbrand et al. (2021) . We find some minor variability of the object prior to the FUor outburst, an initial rather slow rise in brightness, followed in 2019 by a much steeper rise to the maximum.

Shaun V. Ault

Using lattice path counting arguments, we reproduce a well known formula for the number of standard Young tableaux. We also produce an interesting new formula for tableaux of height $\leq 3$ using the Fourier methods of Ault and Kicey.

Michael Pearce, Elena A. Erosheva

Rankings and scores are two common data types used by judges to express preferences and/or perceptions of quality in a collection of objects. Numerous models exist to study data of each type separately, but no unified statistical model captures both data types simultaneously without first performing data conversion. We propose the Mallows-Binomial model to c

Milan Žukovič, Dionissios T. Hristopulos

We introduce a Gibbs Markov random field for spatial data on Cartesian grids which is based on the generalized planar rotator (GPR) model. The GPR model generalizes the recently proposed modified planar rotator (MPR) model by including in the Hamiltonian additional terms that better capture realistic features of spatial data, such as smoothness, non-Gaussian

Gwangho Choi, Adley Gin, Judith Su

The ability to detect and identify molecules at high sensitivity without the use of labels or capture agents is important for medical diagnostics, threat identification, environmental monitoring, and basic science. Microtoroid optical resonators, when combined with noise reduction techniques, have been shown capable of label-free single molecule detection, h

Mouad Morabit, Guy Desaulniers, Andrea Lodi

Column generation is an iterative method used to solve a variety of optimization problems. It decomposes the problem into two parts: a master problem, and one or more pricing problems (PP). The total computing time taken by the method is divided between these two parts. In routing or scheduling applications, the problems are mostly defined on a network, and

Qiaoyu Tan, Ninghao Liu, Xiao Huang, Rui Chen

We introduce a novel masked graph autoencoder (MGAE) framework to perform effective learning on graph structure data. Taking insights from self-supervised learning, we randomly mask a large proportion of edges and try to reconstruct these missing edges during training. MGAE has two core designs. First, we find that masking a high ratio of the input graph str

Zhengfei Kuang, Kyle Olszewski, Menglei Chai, Zeng Huang

We present a novel method to acquire object representations from online image collections, capturing high-quality geometry and material properties of arbitrary objects from photographs with varying cameras, illumination, and backgrounds. This enables various object-centric rendering applications such as novel-view synthesis, relighting, and harmonized backgr

Sven Otto, Nazarii Salish

We propose a novel approximate factor model tailored for analyzing time-dependent curve data. Our model decomposes such data into two distinct components: a low-dimensional predictable factor component and an unpredictable error term. These components are identified through the autocovariance structure of the underlying functional time series. The model para

Marco Trombetti

The aim of this short note is to provide a proof to a statement of Sierpi\'nski concerning the number of possible sums of a series (of type $\lambda<\aleph_1$) of arbitrary ordinal numbers.

Abhi Mukherjee, Saurabh Niyogi, Sujoy Poddar

The purpose of this paper is to examine the model dependence of the stringent constraints on the gluino mass obtained from the Large Hadron Collider (LHC) experiments by analyzing the Run II data using specific simplified models based on several ad hoc sparticle spectra which cannot be realized even in the fairly generic pMSSM models. We first revisit the bo

Daniele Castorina, Giovanni Catino, Carlo Mantegazza

We derive an adaptation of Li & Yau estimates for positive solutions of semilinear heat equations on Riemannian manifolds with nonnegative Ricci tensor. We then apply these estimates to obtain a Harnack inequality and to discuss monotonicity, convexity, decay estimates and triviality of ancient and eternal solutions.

Antonio Politi, Paolo Politi, Stefano Iubini

The Discrete Nonlinear Schr\"odinger (DNLS) equation is a Hamiltonian model displaying an extremely slow relaxation process when discrete breathers appear in the system. In [Iubini S, Chirondojan L, Oppo G L, Politi A and Politi P 2019 Physical Review Letters 122 084102], it was conjectured that the frozen dynamics of tall breathers is due to the existence o

Iana Sudreau, Mathilde Auxois, Marion Servel, Éric Lécolier

Colloidal gels respond like soft solids at rest, whereas they flow like liquids under external shear. Starting from a fluidized state under an applied shear rate $\dot\gamma_{p}$, abrupt flow cessation triggers a liquid-to-solid transition during which the stress relaxes towards a so-called \textit{residual stress} $\sigma_{\rm res}$ that tallies a macroscop

Onur Karatalay, Ioannis Psaromiligkos, Benoit Champagne

Device-to-device (D2D) communication is an enabling technology for fog computing by allowing the sharing of computation resources between mobile devices. However, temperature variations in the device CPUs affect the computation resources available for task offloading, which unpredictably alters the processing time and energy consumption. In this paper, we ad

Mingzhe Guo, Zhipeng Zhang, Heng Fan, Liping Jing

We introduce a novel backbone architecture to improve target-perception ability of feature representation for tracking. Specifically, having observed that de facto frameworks perform feature matching simply using the outputs from backbone for target localization, there is no direct feedback from the matching module to the backbone network, especially the sha

M. Zahradnik, M. Kiaba, S. Espinoza, M. Rebarz

We have studied ultrafast dynamics of thin films of LaCoO$_3$ and La$_{0.5}$Sr$_{0.5}$CoO$_3$ with femtosecond pump-probe ellipsometry in the energy range of 1.6-3.4 eV. We have observed a large pump-induced transfer of spectral weight in LaCoO$_3$ that corresponds to an insulator-to-metal transition. The photo-induced metallic state initially relaxes via a

F. Akbar, A. Ghosh, S. Young, S. Akhter

We compare different neural network architectures for Machine Learning (ML) algorithms designed to identify the neutrino interaction vertex position in the MINERvA detector. The architectures developed and optimized by hand are compared with the architectures developed in an automated way using the package "Multi-node Evolutionary Neural Networks for Deep Le

S. Brendle

The Ricci flow is a natural evolution equation for Riemannian metrics on a given manifold. The main goal is to understand singularity formation. In his spectacular 2002 breakthrough, Perelman achieved a qualitative understanding of singularity formation in dimension $3$. More precisely, Perelman showed that every finite-time singularity to the Ricci flow in

Mihael Petač, Julien Lavalle, Karsten Jedamzik

The discovery of black-hole-binary mergers through their gravitational wave (GW) emission has reopened the exciting possibility that dark matter is made, at least partly, of primordial black holes (PBHs). However, this scenario is challenged by many observational probes that set bounds on the relative PBH abundance across a broad range of viable PBH masses.

Zahraa Mohsen

A four blocks cycle C(k1,k2,k3,k4) is an oriented cycle formed by the union of four internally disjoint directed paths of lengths k1,k2,k3 and k4 respectively. El Mniny proved that if D is a digraph having a spanning out-tree T with no subdivisions of C(k, 1, 1, 1), then the chromatic number of D is at most 8^{3}k. In this paper, we will improve this bound t

Zhiming Lin

Graph embedding techniques have led to significant progress in recent years. However, present techniques are not effective enough to capture the patterns of networks. This paper propose neighbor2vec, a neighbor-based sampling strategy used algorithm to learn the neighborhood representations of node, a framework to gather the structure information by feature

Mauricio Jacobo Romero, André Freitas

In this article, we analyse how decentralised digital infrastructures can provide a fundamental change in the structure and dynamics of organisations. The works of R.H.Coase and M. Olson, on the nature of the firm and the logic of collective action, respectively, are revisited under the light of these emerging new digital foundations. We also analyse how the

Manfred Kraus

We report on our recent calculation for the off-shell $t\bar{t}b\bar{b}$ process in the di-lepton decay channel at the LHC. Our results take into account NLO QCD corrections for the complete $pp\to e^+\nu_e\mu^- \bar{\nu}_\mu b\bar{b}b\bar{b}$ process, and include all double, single and non-resonant contributions. We investigate the size of the corrections a

Helmut Prodinger

Skew Dyck paths are like Dyck paths, but an additional south-west step $(-1,-1)$ is allowed, provided that the path does not intersect itself. Lattice paths with catastrophes can drop from any level to the origin in just one step. We combine these two ideas. The analysis is strictly based on generating functions, and the kernel method is used.

Sungrim Moon, Huan He, Hongfang Liu, Jungwei W. Fan

Background: Extractive question-answering (EQA) is a useful natural language processing (NLP) application for answering patient-specific questions by locating answers in their clinical notes. Realistic clinical EQA can have multiple answers to a single question and multiple focus points in one question, which are lacking in the existing datasets for developm

Emil M. Prodanov

The parametric cubic van der Waals polynomial $p V^3 - (R T + b p) V^2 + a V - a b$ is analysed mathematically and some new generic features (theoretically, for any substance) are revealed - if the pressure is not allowed to take negative values [temperatures not lower than $1/(4Rb)$], the localization intervals of the three volumes on the isobar-isotherm ar

John Southworth

V498 Cyg is an early-B-type binary known to show eclipses on a period of 3.48 d, and two sets of spectral lines. We present the discovery of a second set of eclipses, on a 1.44-d period, in the light curve of this object from the Transiting Exoplanet Survey Satellite (TESS). We develop a model of the light curve to simultaneously fit the properties of both e

John Southworth, Francesca Faedi

A transiting planetary system was discovered independently by two groups, under the names WASP-86 (Faedi et al. 2016) and KELT-12 (Stevens et al. 2017). The properties of the system determined in these works were very different, most tellingly a variation of a factor of three in the measured radius of the planet. We suggest that the system be named WASP-86/K

Dmitry Kosolobov

Asymmetric Numeral Systems (ANS) is a class of entropy encoders that had an immense impact on the data compression, substituting arithmetic and Huffman coding. It was studied by different authors but the precise asymptotics of its redundancy (in relation to the entropy) was not completely understood. We obtain optimal bounds for the redundancy of the tabled

Lorenz Fuchs, Denis Kochan, Christian Baumgartner, Simon Reinhardt

Most of 2D superconductors are of type II, i.e., they are penetrated by quantized vortices when exposed to out-of-plane magnetic fields. In presence of a supercurrent, a Lorentz-like force acts on the vortices, leading to drift and dissipation. The current-induced vortex motion is impeded by pinning at defects, enabling the use of superconductors to generate

Xue-shuai Jiao, Kai-bao Chen

We make a systematic calculation for polarized vector meson production in semi-inclusive lepton-nucleon deep inelastic scattering $e^-N\to e^-VX$. We consider the general case of neutral current electroweak interactions at high energies which give rise to parity-violating effects. We present a general kinematic analysis for the process and show that the cros

Ulrich Mosel, Kai Gallmeister

The GiBUU model is used to obtain information on possible neutrino-nucleus events at the proposed Forward Physics Facility (FPF) at CERN. An FPF neutrino program could contribute to fundamental questions such as formation times, color transparency and the EMC effect for neutrinos.

Jan Oldenziel

We measured signals of low amplitudes originating from cosmic rays, using two rectangular-block scintillation detectors at various positions. The signals were analyzed by a slightly modified signal analyzer from project 'MuonLab', designed to measure the lifetime and velocity of muons from cosmic radiation in high school education. In our experiment we focus

Yuhang Zeng, Dahai Yan, Wen Hu, Jiancheng Wang

The $\gamma$-ray spectral feature of the blazar 1ES 0502+675 is investigated by using Fermi Large Area Telescope (Fermi-LAT) Pass 8 data (between 100 MeV and 300 GeV) covering from 2008 August to 2021 April. A significant ($\sim4\sigma$) hardening at $\sim$ 1 GeV is found in the $\gamma$-ray spectrum during a moderately flaring state (MJD 55050-55350). The p

Nikos Fayard, Adrien Bouscal, Jeremy Berroir, Alban Urvoy

Coupling quantum emitters and nanostructures, in particular cold atoms and waveguides, has recently raised a large interest due to unprecedented possibilities of engineering light-matter interactions. However, the implementation of these promising concepts has been hampered by various theoretical and experimental issues. In this work, we propose a new type o

Debottam Mandal, Kamal Das, Amit Agarwal

The recent discovery of the quantum nonlinear Hall effect has revived the field of nonlinear transport. Here, we predict magnetic field-induced nonlinear Hall effect in time-reversal symmetric Weyl semimetal. We show that the interplay of the band geometric quantities, such as the Berry curvature, and the magnetic part of the Lorentz force can give rise to f

Doan Duy Vo, Russell Butler

Markerless motion capture has become an active field of research in computer vision in recent years. Its extensive applications are known in a great variety of fields, including computer animation, human motion analysis, biomedical research, virtual reality, and sports science. Estimating human posture has recently gained increasing attention in the computer

Byung Hee An, Youngjin Cho

We provide an explicit presentation of the automorphism group of an edge-separated CLTTF Artin group.

Ning Fang, Ruth Birch, T. Ben Britton

Microstructural analysis with electron backscatter diffraction (EBSD) involves sectioning and polishing to create a flat and preparation-artifact free surface. The quality of EBSD analysis is often dependant on this step, and this motivates us to explore how broad ion beam (BIB) milling can be optimised for the preparation of zircaloy-4 with different grain

F. F. Santos

In this work, we explore the holographic entanglement entropy with an infinite strip region of the boundary in Horndeski gravity. In our prescription we consider the spherically and planar topologies black holes in the AdS$_{4}$/CFT$_{3}$ scenario. In such framework, we show the behavior of the entanglement entropy in function of the Horndeski parameters. Su

Hui Xu, Joel Cohen, Richard Davis, Gennady Samorodnitsky

A surprising result of Pillai and Meng (2016) showed that a transformation $\sum_{j=1}^n w_j X_j/Y_j$ of two iid centered normal random vectors, $(X_1,\ldots, X_n)$ and $(Y_1,\ldots, Y_n)$, $n>1$, for any weights $0\leq w_j\leq 1$, $ j=1,\ldots, n$, $\sum_{j=1}^n w_j=1$, has a Cauchy distribution regardless of any correlations within the normal vectors. The

Shih-Ying Hsu, Sheng-Yuan Liu, Tie Liu, Dipen Sahu

The presence of complex organic molecules (COMs) in the interstellar medium (ISM) is of great interest since it may link to the origin and prevalence of life in the universe. Aiming to investigate the occurrence of COMs and their possible origins, we conducted a chemical census toward a sample of protostellar cores as part of the ALMA Survey of Orion Planck

Hiromi Tanaka

We investigate the non-elementary computational complexity of a family of substructural logics without contraction. With the aid of the technique pioneered by Lazi\'c and Schmitz (2015), we show that the deducibility problem for full Lambek calculus with exchange and weakening ($\mathbf{FL}_{\mathbf{ew}}$) is not in Elementary (i.e., the class of decision pr

Amanda Duarte, Samuel Albanie, Xavier Giró-i-Nieto, Gül Varol

Systems that can efficiently search collections of sign language videos have been highlighted as a useful application of sign language technology. However, the problem of searching videos beyond individual keywords has received limited attention in the literature. To address this gap, in this work we introduce the task of sign language retrieval with free-fo

Li Haopeng, Ke Qiuhong, Gong Mingming, Tom Drummond

Modern video summarization methods are based on deep neural networks that require a large amount of annotated data for training. However, existing datasets for video summarization are small-scale, easily leading to over-fitting of the deep models. Considering that the annotation of large-scale datasets is time-consuming, we propose a multimodal self-supervis

Suyun Zhao, Zhigang Dai, Xizhao Wang, Peng Ni

Rule-based classifier, that extract a subset of induced rules to efficiently learn/mine while preserving the discernibility information, plays a crucial role in human-explainable artificial intelligence. However, in this era of big data, rule induction on the whole datasets is computationally intensive. So far, to the best of our knowledge, no known method f

Dimitrios Katsinis

We show that the integrability of the $SO(N)/SO(N-1)$ Principal Chiral Model (PCM) originates from the Pohlmeyer reduction of the $O(N)$ Non Linear Sigma Model (NLSM). In particular, we show that the Lax pair of the PCM is related upon redefinitions and identification of parameters to the zero curvature condition, which is a consequence of the flatness of th

Luca Martinelli

Latest results on inclusive top-quark pair production cross-sections are presented using collision data collected by ATLAS and CMS experiments at the LHC. Inclusive and differential measurements of top-quark pair production cross-sections from ATLAS and CMS are presented in the resolved and boosted kinematic regions. The cross-sections are measured as a func

Zongliang Du, Tianchen Cui, Chang Liu, Weisheng Zhang

Explicit topology optimization methods have received ever-increasing interest in recent years. In particular, a 188-line Matlab code of the two-dimensional (2D) Moving Morphable Component (MMC)-based topology optimization method was released by Zhang et al. (Struct Multidiscip Optim 53(6):1243-1260, 2016). The present work aims to propose an efficient and ea

Anastasia Natsiou, Sean O'Leary

The rise of deep learning algorithms has led many researchers to withdraw from using classic signal processing methods for sound generation. Deep learning models have achieved expressive voice synthesis, realistic sound textures, and musical notes from virtual instruments. However, the most suitable deep learning architecture is still under investigation. Th

Ailisi Li, Jiaqing Liang, Yanghua Xiao

It's hard for neural MWP solvers to deal with tiny local variances. In MWP task, some local changes conserve the original semantic while the others may totally change the underlying logic. Currently, existing datasets for MWP task contain limited samples which are key for neural models to learn to disambiguate different kinds of local variances in questions

Vitonofrio Crismale, Stefano Rossi, Paola Zurlo

Local actions of $\mathbb{P}_\mathbb{N}$, the group of finite permutations on $\mathbb{N}$, on quasi-local algebras are defined and proved to be $\mathbb{P}_\mathbb{N}$-abelian. It turns out that invariant states under local actions are automatically even, and extreme invariant states are strongly clustering. Tail algebras of invariant states are shown to ob

Alberto Del Pia

Sparse PCA is the optimization problem obtained from PCA by adding a sparsity constraint on the principal components. Sparse PCA is NP-hard and hard to approximate even in the single-component case. In this paper we settle the computational complexity of sparse PCA with respect to the rank of the covariance matrix. We show that, if the rank of the covariance

Zach Branson, Xinran Li, Peng Ding

Power analyses are an important aspect of experimental design, because they help determine how experiments are implemented in practice. It is common to specify a desired level of power and compute the sample size necessary to obtain that power. Such calculations are well-known for completely randomized experiments, but there can be many benefits to using oth

Ann-Kathrin Dombrowski, Klaus-Robert Müller, Wolf Christian Müller

The application of machine learning (ML) techniques, especially neural networks, has seen tremendous success at processing images and language. This is because we often lack formal models to understand visual and audio input, so here neural networks can unfold their abilities as they can model solely from data. In the field of physics we typically have model

Simcha Brownson, Asa F. L. Bluck, Roberto Maiolino, Gareth C. Jones

We develop a 2D inclined rotating disc model, which we apply to the stellar velocity maps of 1862 galaxies taken from the MaNGA survey (SDSS public Data Release 15). We use a random forest classifier to identify the kinematic parameters that are most connected to galaxy quenching. We find that kinematic parameters that relate predominantly to the disc (such

Anastasia Natsiou, Sean O'Leary

The synthesis of sound via deep learning methods has recently received much attention. Some problems for deep learning approaches to sound synthesis relate to the amount of data needed to specify an audio signal and the necessity of preserving both the long and short time coherence of the synthesised signal. Visual time-frequency representations such as the

Cristian Cazacu, David Krejcirik, Nguyen Lam, Ari Laptev

We establish improved Hardy inequalities for the magnetic $p$-Laplacian due to adding nontrivial magnetic fields. We also prove that for Aharonov-Bohm magnetic fields the sharp constant in the Hardy inequality becomes strictly larger than in the case of a magnetic-free $p$-Laplacian. We also post some remarks with open problems.

Zahraa Mohsen, Hussein Mourtada

We prove two partition identities which are dual to the Rogers-Ramanujan identities. These identities are inspired by (and proved using) a correspondence between three kinds of objects: a new type of partitions (neighborly partitions), monomial ideals and some infinite graphs.

Gabriel Zapata, Tomás Urruzola, Oscar A. Sampayo, Lucía Duarte

The extension of the standard model with new high-scale weakly coupled physics involving right-handed neutrinos in an effective field theory framework (SMNEFT) allows for a systematic study of heavy neutrinos phenomenology in current and future experiments. We exploit the outstanding angular resolution in future lepton colliders to study the sensitivity of f

Duarte Fontes, Jorge C. Romão

In the complex 2-Higgs-Doublet Model (C2HDM), the mass $m_3$ of the heaviest neutral scalar $h_3$ is usually chosen as a derived parameter. We investigate one-loop corrections to $m_3$ and their impact on decays of $h_3$. Very fine-tuned regions of the parameter space can be found where such corrections are large, not due to subtraction schemes, but rather d

Ching-Chun Chang

Recent advances in deep learning have led to a paradigm shift in the field of reversible steganography. A fundamental pillar of reversible steganography is predictive modelling which can be realised via deep neural networks. However, non-trivial errors exist in inferences about some out-of-distribution and noisy data. In view of this issue, we propose to con

Jincheng Lu, Zi Wang, Jiebin Peng, Chen Wang

Thermodynamic uncertainty relation, quantifying a trade-off among average current, the associated fluctuation (precision), and entropy production (cost), has been formulated in nonequilibrium steady state and various stochastic systems. Herein, we study the thermodynamic uncertainty relation in generic thermoelectric heat engines under a periodic control pro

Jiahui Jia, Xu He, Arsalan Akhtar, Gervasi Herranz

Engineering oxygen octahedra rotation patterns in $ABO_3$ perovskites is a powerful route to design functional materials. Here we propose a strategy that exploits point defects that create local electric dipoles and couple to the oxygen sublattice, enabling direct actuation on the rotational degrees of freedom. This approach, which relies on substituting an

Yiwei Chen, Gongxin Yao, Yong Liu, Hongye Su

Photon-efficient imaging with the single-photon light detection and ranging (LiDAR) captures the three-dimensional (3D) structure of a scene by only a few detected signal photons per pixel. However, the existing computational methods for photon-efficient imaging are pre-tuned on a restricted scenario or trained on simulated datasets. When applied to realisti

Athena Karsa, Masoud Ghalaii, Stefano Pirandola

Quantum target detection aims to utilise quantum technologies to achieve performances in target detection not possible through purely classical means. Quantum illumination is an example of this, based on signal-idler entanglement, promising a potential 6 dB advantage in error exponent over its optimal classical counterpart. So far, receiver designs achieving

Dalia Saha, Abhik Kumar Sanyal

In the recent years, a host of modified gravity models have been proposed as alternatives to the dark energy. A quantum theory of gravity also requires to modify `General Theory of Relativity'. In the present article, we consider five different modified theories of gravity, and compare inflationary parameters with recent data sets released by two Planck coll

ATLAS Collaboration

A search for long-lived charginos produced either directly or in the cascade decay of heavy prompt gluino states is presented. The search is based on proton-proton collision data collected at a centre-of-mass energy of $\sqrt{s}$ = 13 TeV between 2015 and 2018 with the ATLAS detector at the LHC, corresponding to an integrated luminosity of 136 fb$^{-1}$. Lon

Fabricio S. Lozano-Negro, Marcos A. Ferreyra-Ortega, Denise Bendersky, Lucas Fernández-Alcázar

Through an appropriate election of the molecular orbital basis, we show analytically that the molecular dissociation occurring in a Heyrovsky reaction can be interpreted as a Quantum Dynamical Phase Transition, i.e., an analytical discontinuity in the molecular energy spectrum induced by the catalyst. The metallic substrate plays the role of an environment t

Massimiliano Luca, Bruno Lepri, Enrique Frias-Martinez, Andra Lutu

Most of the studies related to human mobility are focused on intra-country mobility. However, there are many scenarios (e.g., spreading diseases, migration) in which timely data on international commuters are vital. Mobile phones represent a unique opportunity to monitor international mobility flows in a timely manner and with proper spatial aggregation. Thi

Michele Bennett, Karin Hayes, Ewa J. Kleczyk, Rajesh Mehta

Data scientists and statisticians are often at odds when determining the best approach, machine learning or statistical modeling, to solve an analytics challenge. However, machine learning and statistical modeling are more cousins than adversaries on different sides of an analysis battleground. Choosing between the two approaches or in some cases using both

Mark Anthony Carroll, Giampaolo D'Alessandro, Gian Luca Lippi, Gian-Luca Oppo

We deconstruct and address a comment to Carroll et al. [Phys Rev Lett 126, 063902 (2021)] (PRL) that has been posted on arXiv appearing as two versions [arXiv:2106.15242v1] and [arXiv:2106.15242v2]. This comment claimed that a term in the model presented in the PRL had been incorrectly omitted and that, hence, the laser threshold predicted by the model in th

Tanmay Tushar Chowhan, Sushan Konar, Sarmistha Banik

We investigate the combined evolution of the dipolar surface magnetic field (B$_{s}$) and the spin-period (P$_s$) of known magnetars and high magnetic field (B$_s$ $ \gtrsim 10^{13}$~G) radio pulsars. We study the long term behaviour of these objects assuming a simple ohmic dissipation of the magnetic field. Identifying the regions (in the P$_s$-B$_s$ plane)

Hanna L. B. Boström, William R. Brant

Octahedral tilting is key to the structure and functionality of perovskites. Here we show how these distortions manifest in the related Prussian blue analogues (PBAs): cyanide versions of double perovskites with formula A$_x$M[M$^{\prime}$(CN)$_6$]$_{1-y}\Box _y\cdot n$H$_2$O (A = alkali metal, M and M$^{\prime}$ = transition metals, $\Box$ = vacancy/defect)

Sibi Catley-Chandar, Thomas Tanay, Lucas Vandroux, Aleš Leonardis

High dynamic range (HDR) imaging is of fundamental importance in modern digital photography pipelines and used to produce a high-quality photograph with well exposed regions despite varying illumination across the image. This is typically achieved by merging multiple low dynamic range (LDR) images taken at different exposures. However, over-exposed regions a

Leonhard Helminger, Roberto Azevedo, Abdelaziz Djelouah, Markus Gross

Recently, significant progress has been made in learned image and video compression. In particular the usage of Generative Adversarial Networks has lead to impressive results in the low bit rate regime. However, the model size remains an important issue in current state-of-the-art proposals and existing solutions require significant computation effort on the

Omer Sabary, Daniella Bar-Lev, Yotam Gershon, Alexander Yucovich

This paper tackles two problems that fall under the study of coding for insertions and deletions. These problems are motivated by several applications, among them is reconstructing strands in DNA-based storage systems. Under this paradigm, a word is transmitted over some fixed number of identical independent channels and the goal of the decoder is to output

Beatrice Da Lio, Carlos Faurby, Xiaoyan Zhou, Ming Lai Chan

On-demand single-photon sources emitting pure and indistinguishable photons at the telecommunication wavelength are a critical asset towards the deployment of fiber-based quantum networks. Indeed, single photons may serve as flying qubits, allowing communication of quantum information over long distances. Self-assembled InAs quantum dots embedded in GaAs con

Alexander Deisting

A hybrid readout Time Projection Chamber (TPC) has a simultaneous optical- and charge readout. The optical readout provides 2D images of particle tracks in the active volume, whilst the charge readout provides additional information on the particle position perpendicular to the image plane. A hybrid readout TPC working at high pressure is an attractive devic

Florian Merchie, Damien Ernst

In business retention, churn prevention has always been a major concern. This work contributes to this domain by formalizing the problem of churn prediction in the context of online gambling as a binary classification task. We also propose an algorithmic answer to this problem based on recurrent neural network. This algorithm is tested with online gambling d

E. Yu. Bunkova

We give an explicit solution to the problem of differentiation of hyperelliptic functions in genus 4 case. We describe explicitly the polynomial Lie algebras and polynomial dynamical systems connected to this problem.

George Sullivan, Luke Burns

Whilst academic, commercial and policy literature on financial exclusion is extensive and wide-ranging, there have been very few attempts to quantify and measure localised financial exclusion anywhere in the world. This is a subject of growing importance in modern UK society with the withdrawal of cash infrastructure and a shift towards online banking. This

Christoph Daube, Joachim Gross, Robin A. A. Ince

Transfer Entropy, a generalisation of Granger Causality, promises to measure "information transfer" from a source to a target signal by ignoring self-predictability of a target signal when quantifying the source-target relationship. A simple example for signals with such self-predictability are narrowband signals. These are both thought to be intrinsically g

Christian Ponte-Fernández, Jorge González-Domínguez, María J. Martín

Epistasis is a phenomenon in which a phenotype outcome is determined by the interaction of genetic variation at two or more loci and it cannot be attributed to the additive combination of effects corresponding to the individual loci. Although it has been more than 100 years since William Bateson introduced this concept, it still is a topic under active resea

Mark J. Loeffler, Beau S. Prince

In an effort to better understand the role dark material plays in the reflectance spectrum of carbonaceous asteroids, we performed laboratory studies focusing on quantifying how the addition of relevant dark material (graphite, magnetite and troilite) can alter the ultraviolet-visible and near-infrared spectrum of a neutral silicate mineral. We find that add

Hideyuki Saio, Donald W. Kurtz

R-mode oscillations in a rotating star produce characteristic signatures in a Fourier amplitude spectrum at frequencies related with the rotation frequency, which can be, in turn, used to obtain the surface rotation rate of the star. Some binary stars observed by Kepler indicate the presence of r~modes that are probably excited by the tidal effect. In this p

Hadrien Vroylandt, Pierre Monmarché

Generalized Langevin equations with non-linear forces and position-dependent linear friction memory kernels, such as commonly used to describe the effective dynamics of coarse-grained variables in molecular dynamics, are rigorously derived within the Mori-Zwanzig formalism. A fluctuation-dissipation theorem relating the properties of the noise to the memory