January 2022 arXiv papers — page 85

Ornela F. Marioni, Mario G. Abadi, Stefan Gottlöber, Gustavo Yepes

More than 50 per cent of present-day massive disc galaxies show a rotating stellar bar. Their formation and dynamics have been widely studied both numerically and observationally. Although numerical simulations in the $\Lambda$CDM cosmological framework predict the formation of such stellar components, there seems to be a tension between theoretical and obse

F. Mernier, N. Werner, Y. Su, C. Pinto

Hot atmospheres pervading galaxy clusters, groups, and early-type galaxies are rich in metals, produced during epochs and diffused via processes that are still to be determined. While this enrichment has been routinely investigated in clusters, metals in lower mass systems are more challenging to probe with standard X-ray exposures and spectroscopy. In this

Adrian Scheppe, Michael Pak

Among the list of major threats to quantum computation, quantum decoherence poses one of the largest because it generates losses to the environment within a computational system which cannot be recovered via error correction methods. These methods require the assumption that the environmental interaction forces the qubit state into some linear combination of

Benjamin M. Janzen, Roland Gillen, Zbigniew Galazka, Janina Maultzsch

We employ a combined experimental-theoretical study of the first- and second-order Raman modes of monoclinic $\beta$-Ga$_{2}$O$_{3}$. The investigated materials is of particular interest due to its deep-UV bandgap paired with a high critical field strength, offering promising applications in power-electronics. A crucial prerequisite for the future developmen

Yu-An Chen, Yijia Xu

We argue that all locality-preserving mappings between fermionic observables and Pauli matrices on a two-dimensional lattice can be generated from the exact bosonization in Ref. [1], whose gauge constraints project onto the subspace of the toric code with emergent fermions. Starting from the exact bosonization and applying Clifford finite-depth generalized l

Luis C. Fernandez, Nathan J. Secrest, Megan C. Johnson, Henrique R. Schmitt

Using simultaneous Very Long Baseline Array and Neil Gehrels Swift Observatory X-ray Telescope observations of the active galactic nucleus (AGN) in NGC 2992 over a six-month observing campaign, we observed a large drop in core 5 cm radio luminosity, by a factor of $>3$, in tandem with factor of $>5$ increase in $2-10$ keV X-ray luminosity. While NGC 2992 has

Peyman Bateni, Jarred Barber, Raghav Goyal, Vaden Masrani

Modern deep learning requires large-scale extensively labelled datasets for training. Few-shot learning aims to alleviate this issue by learning effectively from few labelled examples. In previously proposed few-shot visual classifiers, it is assumed that the feature manifold, where classifier decisions are made, has uncorrelated feature dimensions and unifo

Vitaliy Kurlin

A periodic lattice in Euclidean space is the infinite set of all integer linear combinations of basis vectors. Any lattice can be generated by infinitely many different bases. This ambiguity was only partially resolved, but standard reductions remained discontinuous under perturbations modelling crystal vibrations. This paper completes a continuous classific

Hamed Hassani, Adel Javanmard

Successful deep learning models often involve training neural network architectures that contain more parameters than the number of training samples. Such overparametrized models have been extensively studied in recent years, and the virtues of overparametrization have been established from both the statistical perspective, via the double-descent phenomenon,

Clifford Cheung, Julio Parra-Martinez, Allic Sivaramakrishnan

We define a perturbatively calculable quantity--the on-shell correlator--which furnishes a unified description of particle dynamics in curved spacetime. Specializing to the case of flat and anti-de Sitter space, on-shell correlators coincide precisely with on-shell scattering amplitudes and boundary correlators, respectively. Remarkably, we find that symmetr

A. Malofeeva, A. Seleznev, G. Carraro

The identification of binary stars of different mass ratios in resolved stellar populations is a challenging task. We show how the photometric diagram constructed with the pseudo-colors (H-W2)-W1 vs W2-(BP-K) can be employed to estimate the binary and multiple star ratios and the distribution of their component mass ratio $q$ effectively. As an application,

Pablo M Sanchez-Alarcon, Yago Ascasibar Sequeiros

The aim of this paper is to describe a novel non-parametric noise reduction technique from the point of view of Bayesian inference that may automatically improve the signal-to-noise ratio of one- and two-dimensional data, such as e.g. astronomical images and spectra. The algorithm iteratively evaluates possible smoothed versions of the data, the smooth model

Andreas Schindewolf, Roman Bause, Xing-Yan Chen, Marcel Duda

Ultracold polar molecules offer strong electric dipole moments and rich internal structure, which makes them ideal building blocks to explore exotic quantum matter, implement novel quantum information schemes, or test fundamental symmetries of nature. Realizing their full potential requires cooling interacting molecular gases deeply into the quantum degenera

Tatiana Brailovskaya, Ramon van Handel

We show that, under mild assumptions, the spectrum of a sum of independent random matrices is close to that of the Gaussian random matrix whose entries have the same mean and covariance. This nonasymptotic universality principle yields sharp matrix concentration inequalities for general sums of independent random matrices when combined with the Gaussian theo

Pedro V. Paraguassú, Rui Aquino, Lucianno Defaveri, Welles A. M. Morgado

In the derivation of the thermodynamics of overdamped systems, one ignores the kinetic energy contribution, since the velocity is a slow variable. In this paper, we show that the kinetic energy needs to be present in the calculation of the heat distribution to have a correct correspondence between the underdamped and overdamped cases, meaning that the veloci

Andreas Fring

I will provide a pedagogical introduction to non-Hermitian quantum systems that are PT-symmetric, that is they are left invariant under a simultaneous parity transformation (P) and time-reversal (T). I will explain how generalised versions of this antilinear symmetry can be utilised to explain that these type of systems possess real eigenvalue spectra in par

Rahul Singh, Hannah Zhou

A core challenge in causal inference is how to extrapolate long term effects, of possibly continuous actions, from short term experimental data. It arises in artificial intelligence: the long term consequences of continuous actions may be of interest, yet only short term rewards may be collected in exploration. For this estimand, called the long term dose re

Gihyuk Cho, Rafael A. Porto, Zixin Yang

The linear- and quadratic-in-spin contributions to the binding potential and gravitational-wave flux from binary systems are derived to next-to-next-to-leading order in the Post-Newtonian (PN) expansion of general relativity, including finite-size and tail effects. The calculation is carried out through the worldline effective field theory framework. We find

M. I. Eremets, V. S. Minkov, A. P. Drozdov, P. P. Kong

Since the discovery of superconductivity at 200 K in H3S [1] similar or higher transition temperatures, Tcs, have been reported for various hydrogen-rich compounds under ultra-high pressures [2]. Superconductivity was experimentally proved by different methods, including electrical resistance, magnetic susceptibility, optical infrared, and nuclear resonant s

Joseph Bakarji, Kathleen Champion, J. Nathan Kutz, Steven L. Brunton

A central challenge in data-driven model discovery is the presence of hidden, or latent, variables that are not directly measured but are dynamically important. Takens' theorem provides conditions for when it is possible to augment these partial measurements with time delayed information, resulting in an attractor that is diffeomorphic to that of the origina

Vladimir Garanzha, Liudmila Kudryavtseva, Lennard Kamenski

We consider the construction of a polyhedral Delaunay partition as a limit of the sequence of power diagrams (radical partitions). The dual Voronoi diagram is obtained as a limit of the sequence of weighted Delaunay partitions. The problem is reduced to the construction of two dual convex polyhedra, inscribed and superscribed around a circular paraboloid, as

Alexander E. Black, Jesús A. De Loera, Niklas Lütjeharms, Raman Sanyal

Motivated by the analysis of the performance of the simplex method we study the behavior of families of pivot rules of linear programs. We introduce normalized-weight pivot rules which are fundamental for the following reasons: First, they are memory-less, in the sense that the pivots are governed by local information encoded by an arborescence. Second, many

Daniel W. Cranston

Fix a graph $G$, a list-assignment $L$ for $G$, and $L$-colorings $\alpha$ and $\beta$. An $L$-recoloring sequence, starting from $\alpha$, recolors a single vertex at each step, so that each resulting intermediate coloring is a proper $L$-coloring. An $L$-recoloring sequence transforms $\alpha$ to $\beta$ if its initial coloring is $\alpha$ and its final co

Honghe Jin

Hyperparameter plays an essential role in the fitting of supervised machine learning algorithms. However, it is computationally expensive to tune all the tunable hyperparameters simultaneously especially for large data sets. In this paper, we give a definition of hyperparameter importance that can be estimated by subsampling procedures. According to the impo

K L Navaneet, Soroush Abbasi Koohpayegani, Ajinkya Tejankar, Hamed Pirsiavash

Feature regression is a simple way to distill large neural network models to smaller ones. We show that with simple changes to the network architecture, regression can outperform more complex state-of-the-art approaches for knowledge distillation from self-supervised models. Surprisingly, the addition of a multi-layer perceptron head to the CNN backbone is b

Almut Burchard, Galia Dafni, Ryan Gibara

We study the decreasing rearrangement of functions in VMO, and show that for rearrangeable functions, the mapping f -> f* preserves vanishing mean oscillation. Moreover, as a map on BMO, while bounded, it is not continuous, but continuity holds at points in VMO (under certain conditions). This also applies to the symmetric decreasing rearrangement. Many exam

Gaetano Geck, Jens Keppeler, Thomas Schwentick, Christopher Spinrath

The paper studies the rewriting problem, that is, the decision problem whether, for a given conjunctive query $Q$ and a set $\mathcal{V}$ of views, there is a conjunctive query $Q'$ over $\mathcal{V}$ that is equivalent to $Q$, for cases where the query, the views, and/or the desired rewriting are acyclic or even more restricted. It shows that, if $Q$ itself

Wen-Qing Wei, Feng Wan, Yousef I. Salamin, Jie-Ru Ren

An all-optical method of ultrafast spin rotation is put forward to precisely manipulate the polarization of relativistic charged particle beams of leptons or ions. In particular, laser-driven dense ultrashort beams are manipulated via single-shot interaction with a co-propagating moderate temporally asymmetric (frequency-chirped or subcycle THz) laser pulse.

E. V. Arbuzova

In the conventional cosmology masses of the stable supersymmetric relics, candidates for the dark matter (DM) particles, should be typically below 1 TeV. This is in conflict with the LHC bounds on the low energy SUSY. However, in $R^2$-gravity the masses of the stable particles with the interaction strength typical for SUSY could be much higher depending upo

Žiga Krajnik, Johannes Schmidt, Vincent Pasquier, Enej Ilievski

We analytically compute the full counting statistics of charge transfer in a classical automaton of interacting charged particles. Deriving a closed-form expression for the moment generating function with respect to a stationary equilibrium state, we employ asymptotic analysis to infer the structure of charge current fluctuations for a continuous range of ti

Utku Evci, Bart van Merriënboer, Thomas Unterthiner, Max Vladymyrov

The architecture and the parameters of neural networks are often optimized independently, which requires costly retraining of the parameters whenever the architecture is modified. In this work we instead focus on growing the architecture without requiring costly retraining. We present a method that adds new neurons during training without impacting what is a

Catherine Zucker, Alyssa A. Goodman, João Alves, Shmuel Bialy

For decades we have known that the Sun lies within the Local Bubble, a cavity of low-density, high-temperature plasma surrounded by a shell of cold, neutral gas and dust. However, the precise shape and extent of this shell, the impetus and timescale for its formation, and its relationship to nearby star formation have remained uncertain, largely due to low-r

Andrey Kutuzov, Samia Touileb, Petter Mæhlum, Tita Ranveig Enstad

We describe NorDiaChange: the first diachronic semantic change dataset for Norwegian. NorDiaChange comprises two novel subsets, covering about 80 Norwegian nouns manually annotated with graded semantic change over time. Both datasets follow the same annotation procedure and can be used interchangeably as train and test splits for each other. NorDiaChange cov

Andreas Lindner, Khoirul Faiq Muzakka

We match the electroweak chiral Lagrangian with two singlet scalars to the next-to-minimal composite Higgs model with $ SO(6)/SO(5) $ coset structure and extract the scalar divergences to one loop. Assuming the additional scalar to be heavy, we integrate it out and perform a matching to the well-established electroweak chiral Lagrangian with one light Higgs.

Yunfan Ye, Renjiao Yi, Zhiping Cai, Kai Xu

Learning-based edge detection has hereunto been strongly supervised with pixel-wise annotations which are tedious to obtain manually. We study the problem of self-training edge detection, leveraging the untapped wealth of large-scale unlabeled image datasets. We design a self-supervised framework with multi-layer regularization and self-teaching. In particul

Carlos Rodriguez-Pardo, Elena Garces

We present SeamlessGAN, a method capable of automatically generating tileable texture maps from a single input exemplar. In contrast to most existing methods, focused solely on solving the synthesis problem, our work tackles both problems, synthesis and tileability, simultaneously. Our key idea is to realize that tiling a latent space within a generative net

Nenad Tomasev, Ioana Bica, Brian McWilliams, Lars Buesing

Despite recent progress made by self-supervised methods in representation learning with residual networks, they still underperform supervised learning on the ImageNet classification benchmark, limiting their applicability in performance-critical settings. Building on prior theoretical insights from ReLIC [Mitrovic et al., 2021], we include additional inducti

Ben-Hur Francisco Cardoso, Sebastián Gonçalves, José Roberto Iglesias

If wealthier people have advantages in having higher returns than poor, inequality will unequivocally increase, but is equal opportunity enough to prevent it? According to several models in economics and econophysics, no. They all display wealth concentration as a peculiar feature of its dynamics, even though no individual can have repeating gains advantage.

Aliakbar Abolhasani, Harry Goodhew

We present a systematic prescription for calculating cosmological correlation functions for models with derivative interactions through the wavefunction of the universe and compare this result with the "in-in" formalism -- canonical approach. The key step in this procedure is to perform the path integral over conjugate momenta after which a straightforward g

Michael Björklund, Alexander Gorodnik

Minkowski's First Theorem and Dirichlet's Approximation Theorem provide upper bounds on certain minima taken over lattice points contained in domains of Euclidean spaces. We study the distribution of such minima and show, under some technical conditions, that they exhibit Weibull asymptotics with respect to different natural measures on the space of unimodul

Guillaume Staerman, Eric Adjakossa, Pavlo Mozharovskyi, Vera Hofer

The increasing automation in many areas of the Industry expressly demands to design efficient machine-learning solutions for the detection of abnormal events. With the ubiquitous deployment of sensors monitoring nearly continuously the health of complex infrastructures, anomaly detection can now rely on measurements sampled at a very high frequency, providin

Lian Wu, Runlian Xia, Dejian Zhou

In this paper, we establish noncommutative Burkholder inequalities with asymmetric diagonals in symmetric operator spaces. Our proof mainly relies on a new complex interpolation result on asymmetric vector valued spaces and a duality approach. We include as well the asymmetric versions of noncommutative Johnson-Schechtman inequalities.

Michele Vischi, Luca Ferialdi, Andrea Trombettoni, Angelo Bassi

The Continuous Spontaneous Localization (CSL) model is an alternative formulation of quantum mechanics which introduces a noise coupled non linearly to the wave function to account for its collapse. We consider CSL effects on quantum computers made of superconducting transmon qubits. As a direct effect CSL reduces quantum superpositions of the computational

Leah Epstein, Alexandra Lassota, Asaf Levin, Marten Maack

Makespan minimization on parallel identical machines is a classical and intensively studied problem in scheduling, and a classic example for online algorithm analysis with Graham's famous list scheduling algorithm dating back to the 1960s. In this problem, jobs arrive over a list and upon an arrival, the algorithm needs to assign the job to a machine. The go

Olivier Berné, Émilie Habart, Els Peeters, Alain Abergel

Massive stars disrupt their natal molecular cloud material through radiative and mechanical feedback processes. These processes have profound effects on the evolution of interstellar matter in our Galaxy and throughout the Universe, from the era of vigorous star formation at redshifts of 1-3 to the present day. The dominant feedback processes can be probed b

Luca Teodori, Kfir Blum, Emanuele Castorina, Marko Simonović

We make a number of comments regarding modeling degeneracies in strong lensing measurements of the Hubble parameter $H_0$. The first point concerns the impact of weak lensing associated with different segments of the line of sight. We show that external convergence terms associated with the lens-source and observer-lens segments need to be included in cosmog

V. S. Morales-Salgado, H. Martínez-Huerta, P. I. Ramírez-Baca

We investigate whether the discrepancy between observed galactic rotation curves and those predicted from baryonic matter can be interpreted as the manifestation of an emergent entropic force. Starting from a minimal statistical framework, we derive an effective radial force from a stationary solution of the Fokker-Planck equation under simple and physically

Matteo Antonio Scrugli, Bojan Blažica, Paolo Meloni

The new generation of wireless technologies, fitness trackers, and devices with embedded sensors can have a big impact on healthcare systems and quality of life. Among the most crucial aspects to consider in these devices are the accuracy of the data produced and power consumption. Many of the events that can be monitored, while apparently simple, may not be

Christoph Kehle, João P. G. Ramos

We show novel types of uniqueness and rigidity results for Schr\"odinger equations in either the nonlinear case or in the presence of a complex-valued potential. As our main result we obtain that the trivial solution $u=0$ is the only solution for which the assumptions $u(t=0)\vert_{D}=0, u(t=T)\vert_{D}=0$ hold, where $D\subset \mathbb{R}^d$ are certain sub

Carlos A. Argüelles, Toni Bertólez-Martínez, Jordi Salvado

Light sterile neutrinos have been motivated by anomalies observed in short-baseline neutrino experiments.Among them, radioactive-source and reactor experiments have provided evidence and constraints, respectively, for electron neutrino disappearance compatible with an eV-scale neutrino. The results from these observations are seemingly in conflict. This lett

Ivan di Stefano, Paolo Cappuccio, Luciano Iess

BepiColombo ESA/JAXA mission is currently in its 7 year cruise phase towards Mercury. The Mercury orbiter radioscience experiment (MORE), one of the 16 experiments of the mission, will start its scientific investigation during the superior solar conjunction (SSC) in March 2021 with a test of general relativity (GR). Other solar conjunctions will follow durin

Pedro Araújo, Taísa Martins, Letícia Mattos, Walner Mendonça

For graphs $G$ and $H$, we write $G \overset{\mathrm{rb}}{\longrightarrow} H $ if any proper edge-coloring of $G$ contains a rainbow copy of $H$, i.e., a copy where no color appears more than once. Kohayakawa, Konstadinidis and the last author proved that the threshold for $G(n,p) \overset{\mathrm{rb}}{\longrightarrow}H$ is at most $n^{-1/m_2(H)}$. Previous

Ehsan Latif, Ramviyas Parasuraman

Localization of a wireless mobile device or a robot in indoor and GPS-denied environments is a difficult problem, particularly in dynamic scenarios where traditional cameras and LIDAR-based alternative sensing and localization modalities may fail. We propose a method for estimating the location of a mobile robot in relation to static wireless sensor nodes (W

Ioachim G. Dusa, Tilo Wettig

Recently, S\'a, Ribeiro and Prosen introduced complex spacing ratios to analyze eigenvalue correlations in non-Hermitian systems. At present there are no analytical results for the probability distribution of these ratios in the limit of large system size. We derive an approximation formula for the Ginibre universality class of random matrix theory which con

Søren Fiig Jarner, Michael Preisel

In this paper we analyse the five-factor capital market model of Munk et al.(2004). The model features a Vasicek interest rate model, an equity index with mean-reverting excess return and an index for realized inflation with mean-reverting expectation. The primary aim of the analysis is to facilitate so-called exact simulation from the model on a set of disc

Jonathan Koh, Erwan Koch, Anthony C. Davison

Severe thunderstorms cause substantial economic and human losses in the United States. Simultaneous high values of convective available potential energy (CAPE) and storm relative helicity (SRH) are favorable to severe weather, and both they and the composite variable $\mathrm{PROD}=\sqrt{\mathrm{CAPE}} \times \mathrm{SRH}$ can be used as indicators of severe

Andrea Montanari, Yuchen Wu

We consider a class of statistical estimation problems in which we are given a random data matrix ${\boldsymbol X}\in {\mathbb R}^{n\times d}$ (and possibly some labels ${\boldsymbol y}\in{\mathbb R}^n$) and would like to estimate a coefficient vector ${\boldsymbol \theta}\in{\mathbb R}^d$ (or possibly a constant number of such vectors). Special cases includ

Philip Tosteson

For a fixed algebraic variety $X$, curve class $\alpha \in N_1(X)$, and genus $g \in \mathbb N$, we consider the sequence of $S_n$ representations obtained from the homology of the Kontsevich space of stable maps to $X$, $\bar M_{g,n}(X,\alpha)$. Using the category of finite sets and surjections, we prove a representation stability theorem that governs the b

David Wellnitz, Guillermo Preisser, Vincenzo Alba, Jerome Dubail

The operator space entanglement entropy, or simply 'operator entanglement' (OE), is an indicator of the complexity of quantum operators and of their approximability by Matrix Product Operators (MPO). We study the OE of the density matrix of 1D many-body models undergoing dissipative evolution. It is expected that, after an initial linear growth reminiscent o

Vrushabh Zinage, Efstathios Bakolas

Learning and synthesizing stabilizing controllers for unknown nonlinear control systems is a challenging problem for real-world and industrial applications. Koopman operator theory allows one to analyze nonlinear systems through the lens of linear systems and nonlinear control systems through the lens of bilinear control systems. The key idea of these method

Jader E. Brasil, Josue Knorst, Artur O. Lopes

$M_n(\mathbb{C})$ denotes the set of $n$ by $n$ complex matrices. Consider continuous time quantum semigroups $\mathcal{P}_t= e^{t\, \mathcal{L}}$, $t \geq 0$, where $\mathcal{L}:M_n(\mathbb{C}) \to M_n(\mathbb{C})$ is the infinitesimal generator. If we assume that $\mathcal{L}(I)=0$, we will call $e^{t\, \mathcal{L}}$, $t \geq 0$ a quantum Markov semigroup.

Scott Collier, Eric Perlmutter

We develop a new approach to extracting the physical consequences of S-duality of four-dimensional $\mathcal{N}=4$ super Yang-Mills (SYM) and its string theory dual, based on $SL(2,\mathbb{Z})$ spectral theory. We observe that CFT observables $\mathcal{O}$, invariant under $SL(2,\mathbb{Z})$ transformations of a complexified gauge coupling $\tau$, admit a un

Paolo Cappuccio, Ivan di Stefano, Gael Cascioli, Luciano Iess

The ESA/JAXA BepiColombo mission, launched on 20 October 2018, is currently in cruise toward Mercury. The Mercury Orbiter Radio-science Experiment (MORE), one of the 16 experiments of the mission, will exploit range and range-rate measurements collected during superior solar conjunctions to better constrain the post-Newtonian parameter ${\gamma}$. The MORE r

Kwangho Choiy

We transfer Knapp-Stein $R$-groups for unitary weakly unramified characters between a $p$-adic quasi-split group and its non-quasi-split inner forms, and provide the structure of those $R$-groups for a general connected reductive group over a $p$-adic field. This work supports previous studies on the behavior of $R$-groups between inner forms, and extends Ke

Yuyan Chen, Yanghua Xiao, Bang Liu

Interpreting the predictions of existing Question Answering (QA) models is critical to many real-world intelligent applications, such as QA systems for healthcare, education, and finance. However, existing QA models lack interpretability and provide no feedback or explanation for end-users to help them understand why a specific prediction is the answer to a

Kwangho Choiy

We study the compatibility of Arthur's conjecture for $R$-groups in the restriction of discrete series representations from Levi subgroups of a $p$-adic group to those of its closed subgroup having the same derived group. The compatibility is conditional as it holds under the conjectural local Langlands correspondence in general. This work is applied to seve

Dmitry S. Shaposhnikov, Alexander V. Rodin, Alexander S. Medvedev, Anna A. Fedorova

We present a new implementation of the hydrological cycle scheme into a general circulation model of the Martian atmosphere. The model includes a semi-Lagrangian transport scheme for water vapor and ice, and accounts for microphysics of phase transitions between them. The hydrological scheme includes processes of saturation, nucleation, particle growth, subl

Niema Moshiri

Epidemic simulations require the ability to sample contact networks from various random graph models. Existing methods can simulate city-scale or even country-scale contact networks, but they are unable to feasibly simulate global-scale contact networks due to high memory consumption. NiemaGraphGen (NGG) is a memory-efficient graph generation tool that enabl

Orphée Collin, Benedikt Jahnel, Wolfgang König

The interacting quantum Bose gas is a random ensemble of many Brownian bridges (cycles) of various lengths with interactions between any pair of legs of the cycles. It is one of the standard mathematical models in which a proof for the famous Bose-Einstein condensation phase transition is sought for. We introduce a simplified version of the model with an org

Maria Sygletou, Stefania Benedetti, Alessandro di Bona, Maurizio Canepa

Understanding the interaction between plasmonic nanoparticles and transparent conductive oxides is instrumental to the development of next-generation photovoltaic, opto-electronic and energy-efficient solid-state lighting devices. We investigated the optical response of hybrid media composed of gold nanoparticles deposited on aluminum-doped zinc oxide thin f

Akanksha Gautam, Kavita Dorai, Arvind

In this work, we study the dynamics of quantum coherence (total coherence, global coherence and local coherence) evolving under a local PT-symmetric Hamiltonian in maximally entangled bipartite and tripartite states. Our results indicate that quantum coherence in the bipartite state oscillates in the unbroken phase regime of the PT-symmetric Hamiltonian. Int

Xu Li, Di Zhang, Shun Zhou

In this paper, we continue to construct the low-energy effective field theories (EFTs) of the canonical seesaw models, which are natural extensions of the Standard Model (SM) to accommodate tiny but nonzero neutrino masses. Different from three right-handed neutrino singlets in the type-I seesaw model, the Higgs triplet in the type-II seesaw model participat

Dmitry S. Shaposhnikov, Alexander S. Medvedev, Alexander V. Rodin, Erdal Yiğit

Simulations with the Max Planck Institute Martian general circulation model for Martian years 28 and 34 reveal details of the water "pump" mechanism and the role of gravity wave (GW) forcing. Water is advected to the upper atmosphere mainly by upward branches of the meridional circulation: in low latitudes during equinoxes and over the south pole during sols

Paul H Frampton

Steven Weinberg, renowned particle theorist and Nobel laureate, passed away in July 2021. We discuss selections of his work on effective field theory, electroweak unification, and symmetry related topics. We then add a few memories of Weinberg at Harvard University then at the University of Texas, Austin.

Laura Hermosa Muñoz, Isabel Márquez, Sara Cazzoli, Josefa Masegosa

Outflows play a major role in the evolution of galaxies. However, we do not have yet a complete picture of their properties (extension, geometry, orientation and clumpiness). For low-luminosity Active Galactic Nuclei (AGNs), in particular, low-ionisation nuclear emission line regions (LINERs), the rate of outflows and their properties are largely unknown. Th

Mohammed Oualid Attaoui, Hanene Azzag, Mustapha Lebbah, Nabil Keskes

The analysis of data streams has received considerable attention over the past few decades due to sensors, social media, etc. It aims to recognize patterns in an unordered, infinite, and evolving stream of observations. Clustering this type of data requires some restrictions in time and memory. This paper introduces a new data stream clustering method (IMOC-

Aurelienne A. S. Jorge, Iuri da Silva Diniz, Vander L. S. Freitas, Izabelly C. Costa

There are several criteria for building up networks from time series related to different points in geographical space. The most used criterion is the Global-Threshold (GT). Using a weather radar dataset, this paper shows that the Backbone (BB) - a local-threshold criterion - generates networks whose geographical configuration is complementary to the GT netw

Manling Li, Ruochen Xu, Shuohang Wang, Luowei Zhou

Vision-language (V+L) pretraining models have achieved great success in supporting multimedia applications by understanding the alignments between images and text. While existing vision-language pretraining models primarily focus on understanding objects in images or entities in text, they often ignore the alignment at the level of events and their argument

Mohammed Oualid Attaoui, Hazem Fahmy, Fabrizio Pastore, Lionel Briand

Deep neural networks (DNNs) have demonstrated superior performance over classical machine learning to support many features in safety-critical systems. Although DNNs are now widely used in such systems (e.g., self driving cars), there is limited progress regarding automated support for functional safety analysis in DNN-based systems. For example, the identif

Anirban Roy, Alexander van Engelen, Vera Gluscevic, Nicholas Battaglia

As cosmic microwave background (CMB) photons traverse the Universe, anisotropies can be induced via Thomson scattering (proportional to the integrated electron density; optical depth) and inverse Compton scattering (proportional to the integrated electron pressure; thermal Sunyaev-Zel'dovich effect). Measurements of anisotropy in optical depth $\tau$ and Com

Evgeniya A. Bondar, David Casas, Mikhail V. Volkov

A deterministic finite automaton in which every non-empty set of states occurs as the image of the whole state set under the action of a suitable input word is called completely reachable. We characterize such automata in terms of graphs and trees.

Simone Novario

A generic K3 surface of degree 2t is a general complex projective K3 surface whose Picard group is generated by the class of an ample divisor whose with respect to the intersection form is 2t. We show that if X is the Hilbert square of a generic K3 surface of degree 2t, with $t > 2$, such that X admits an ample divisor with $q_X(D)=2$, where $q_X$ Beauville-

Mathieu Baudet, Alberto Sonnino, Michal Krol

Zef was recently proposed to extend the low-latency, Byzantine-Fault Tolerant (BFT) payment protocol FastPay with anonymous coins. This report explores further extensions of FastPay and Lef beyond payments. We start by off-chain assets (e.g. NFTs). We introduce the idea of on-demand BFT consensus instances throught the example of atomic swaps between account

Christina Giannoula, Ivan Fernandez, Juan Gómez-Luna, Nectarios Koziris

Several manufacturers have already started to commercialize near-bank Processing-In-Memory (PIM) architectures. Near-bank PIM architectures place simple cores close to DRAM banks and can yield significant performance and energy improvements in parallel applications by alleviating data access costs. Real PIM systems can provide high levels of parallelism, lar

Valentyna Kovalenko, Maiia Marienko, Alisa Sukhikh

The study examines the problem of using augmented and virtual reality in the process of blended learning in general secondary education. The study analyzes the meaning of the concept of "blended learning". The conceptual principles of blended learning are considered. The definition of augmented and virtual reality is given. The mixed reality is considered as

Dominik Sidler, Vasil Rokaj, Michael Ruggenthaler, Angel Rubio

An analytic closed form solution is derived for the bound states of electrons subject to a static, inhomogeneous ($1/r$-decaying) magnetic field, including the Zeeman interaction. The solution provides access to many-body properties of a two-dimensional, non-interacting, electron gas in the thermodynamic limit. Radially distorted Landau levels can be identif

Aidan Herderschee, Radu Roiban, Fei Teng

The AdS boundary correlators and their dual correlation functions of boundary operators have been the main dynamic observables of the holographic duality relating a bulk AdS theory and a boundary conformal field theory. We show that tree-level AdS boundary correlators for generic states can be expressed as nonlocal differential operators of a certain structu

Manpreet Singh Jattana, Fengping Jin, Hans De Raedt, Kristel Michielsen

We present and analyze large-scale simulation results of a hybrid quantum-classical variational method to calculate the ground state energy of the anti-ferromagnetic Heisenberg model. Using a massively parallel universal quantum computer simulator, we observe that a low-depth-circuit ansatz advantageously exploits the efficiently preparable N\'{e}el initial

Carlos De Breuck, Andreas Lundgren, Bjorn Emonts, Sthabile Kolwa

We present the detection of [CII] 158um emission from the Spiderweb galaxy at z=2.1612 using the Atacama Pathfinder EXperiment. The line profile splits into an active galactic nucleus (AGN) and circum galacic medium (CGM) component previously identified in CO and [CI]. We find that these individual [CII] components are consistent in terms of CO and far-IR lu

I. I. Baltaeva, I. D. Rakhimov, M. M. Khasanov

This paper is dedicated to finding the solutions of the equation of the loaded modified Korteweg-de Vries. By the way, it is shown to find the solutions via $(G'/G)$-expansion method that is one of the most effective ways of finding solutions.

Rui Chen, Zhuoran Fang, Johannes E. Fröch, Peipeng Xu

Programmable photonic integrated circuits (PICs) have recently gained significant interest due to their potential in creating next-generation technologies ranging from artificial neural networks and microwave photonics to quantum information processing. The fundamental building block of such programmable PICs is a tunable 2 x 2 switch, traditionally controll

Gregory Vereshchagin, Liang Li, Damien Bégué

The composition of relativistic outflows producing gamma-ray bursts is a long standing open question. One of the main arguments in favor of magnetically dominated outflows is the absence of photospheric component in their broadband time resolved spectra, with such notable example as GRB 080916C. Here, we perform a time-resolved analysis of this burst and con

Salvatore Citraro, Michael S. Vitevitch, Massimo Stella, Giulio Rossetti

Knowledge in the human mind exhibits a dualistic vector/network nature. Modelling words as vectors is key to natural language processing, whereas networks of word associations can map the nature of semantic memory. We reconcile these paradigms - fragmented across linguistics, psychology and computer science - by introducing FEature-Rich MUltiplex LEXical (FE

Md Ashad Alam, Hui Shen, Hong-Wen Deng

Many statistical machine approaches could ultimately highlight novel features of the etiology of complex diseases by analyzing multi-omics data. However, they are sensitive to some deviations in distribution when the observed samples are potentially contaminated with adversarial corrupted outliers (e.g., a fictional data distribution). Likewise, statistical

Woojin Kwon, Kate Pattle, Sarah Sadavoy, Charles L. H. Hull

We present 850 $\mu$m polarimetric observations toward the Serpens Main molecular cloud obtained using the POL-2 polarimeter on the James Clerk Maxwell Telescope (JCMT) as part of the B-fields In STar-forming Region Observations (BISTRO) survey. These observations probe the magnetic field morphology of the Serpens Main molecular cloud on about 6000 au scales

Xing Ai, Zhihong Zhang, Luzhe Sun, Junchi Yan

Quantum machine learning is a fast-emerging field that aims to tackle machine learning using quantum algorithms and quantum computing. Due to the lack of physical qubits and an effective means to map real-world data from Euclidean space to Hilbert space, most of these methods focus on quantum analogies or process simulations rather than devising concrete arc

Mark Nicholas Finean, Luka Petrović, Wolfgang Merkt, Ivan Marković

Over the years, the separate fields of motion planning, mapping, and human trajectory prediction have advanced considerably. However, the literature is still sparse in providing practical frameworks that enable mobile manipulators to perform whole-body movements and account for the predicted motion of moving obstacles. Previous optimisation-based motion plan

Qingzhao Zhang, Shengtuo Hu, Jiachen Sun, Qi Alfred Chen

Trajectory prediction is a critical component for autonomous vehicles (AVs) to perform safe planning and navigation. However, few studies have analyzed the adversarial robustness of trajectory prediction or investigated whether the worst-case prediction can still lead to safe planning. To bridge this gap, we study the adversarial robustness of trajectory pre

M. Knorr, J. M. Manceau, J. Mornhinweg, J. Nespolo

The ultrafast scattering dynamics of intersubband polaritons in dispersive cavities embedding GaAs/AlGaAs quantum wells are studied directly within their band structure using a non-collinear pump-probe geometry with phase-stable mid-infrared pulses. Selective excitation of the lower polariton at a frequency of ~25 THz and at a finite in-plane momentum, $k_{|

Yannick Düren, Johannes Lederer, Li-Xuan Qin

Deep sequencing has become one of the most popular tools for transcriptome profiling in biomedical studies. While an abundance of computational methods exists for "normalizing" sequencing data to remove unwanted between-sample variations due to experimental handling, there is no consensus on which normalization is the most suitable for a given data set. To a