August 2022 arXiv papers — page 35

Eric C. Rowell

The topological model for quantum computation is an inherently fault-tolerant model built on anyons in topological phases of matter. A key role is played by the braid group, and in this survey we focus on a selection of ways that the mathematical study of braids is crucial for the theory. We provide some brief historical context as well, emphasizing ways tha

Tahir Javed, Kaushal Santosh Bhogale, Abhigyan Raman, Anoop Kunchukuttan

A cornerstone in AI research has been the creation and adoption of standardized training and test datasets to earmark the progress of state-of-the-art models. A particularly successful example is the GLUE dataset for training and evaluating Natural Language Understanding (NLU) models for English. The large body of research around self-supervised BERT-based l

L. Clifton Johnson, Tobin M. Wainer, Estephani E. TorresVillanueva, Anil C. Seth

We construct a catalog of star clusters from Hubble Space Telescope images of the inner disk of the Triangulum Galaxy (M33) using image classifications collected by the Local Group Cluster Search, a citizen science project hosted on the Zooniverse platform. We identify 1214 star clusters within the Hubble Space Telescope imaging footprint of the Panchromatic

Aditya Bhosale, Leslie Ying, Xiaoliang Zhang

It is technically challenging to design efficient transceiver coil arrays for foot and ankle imaging at ultrahigh fields due to the irregular geometry of the anatomy. Shortened wavelength because of the high operation frequency at ultrahigh fields increases phase variation, leading to inhomogeneous B1 distribution in the imaging sample. In this work, we prop

Doruk Aksoy, Megan J. McCarthy, Ian Geiger, Diran Apelian

Interfacial segregation and chemical short-range ordering influence the behavior of grain boundaries in complex concentrated alloys. In this study, we use atomistic modeling of a NbMoTaW refractory complex concentrated alloy to provide insight into the interplay between these two phenomena. Hybrid Monte Carlo and molecular dynamics simulations are performed

C. Pallis

We show how we can implement within Supergravity chaotic inflation in the presence of a pole of order one or two in the kinetic mixing of the inflaton sector. This pole arises due to the selected logarithmic Kahler potentials K, which parameterize hyperbolic manifolds with scalar curvature related to the coefficient -N of the logarithmic term. The associated

Nils Sturma, Mathias Drton, Dennis Leung

We consider the problem of testing a null hypothesis defined by equality and inequality constraints on a statistical parameter. Testing such hypotheses can be challenging because the number of relevant constraints may be on the same order or even larger than the number of observed samples. Moreover, standard distributional approximations may be invalid due t

Roberto Díaz, Alvaro Liendo

Our main result is the following: let X be a normal affine toric surface without torus factor. Then there exists a non-normal affine toric surface X' with automorphism group isomorphic to the automorphism group of X if and only if X is different from the affine plane. As a tool, we first provide a classification of normalized additive group actions on a non-

Sushant More

Log and square root transformations of target variable are routinely used in forecasting models to predict future sales. These transformations often lead to better performing models. However, they also introduce a systematic negative bias (under-forecasting). In this paper, we demonstrate the existence of this bias, dive deep into its root cause and introduc

Dominik Hellmann, Heinrich Päs, Erika Rani

In many theories of quantum gravity quantum fluctuations of spacetime may serve as an environment for decoherence. Here we study quantum-gravitational decoherence of high energy astrophysical neutrinos in the presence of fermionic dark sectors and for a realistic three neutrino scenario. We show how violation of global symmetries expected to arise in quantum

J. -P. Carneiro, B. Hanna, E. Podzeyev, L. Prost

A series of beam dynamic studies were performed in 2020-2021 at the PIP-II Injector Test Facility (PIP2IT) that has been built to validate the concept of the front-end of the PIP-II linac being constructed at Fermilab. PIP2IT is comprised of a 30-keV H- ion source, a 2 m-long Low Energy Beam Transport (LEBT), a 2.1- MeV CW RFQ, followed by a 10-m Medium Ener

Julian Zimmermann, Fabien Beguet, Daniel Guthruf, Bruno Langbehn

Single-shot diffraction imaging of isolated nanosized particles has seen remarkable success in recent years, yielding in-situ measurements with ultra-high spatial and temporal resolution. The progress of high-repetition-rate sources for intense X-ray pulses has further enabled recording datasets containing millions of diffraction images, which are needed for

Zheng Chen, Yura Malitsky

The emerging concept of Over-the-Air (OtA) computation has shown great potential for achieving resource-efficient data aggregation across large wireless networks. However, current research in this area has been limited to the standard many-to-one topology, where multiple nodes transmit data to a single receiver. In this study, we address the problem of apply

Bernard van Heck, Tim Fuchs, Jaimy Plugge, Wim A. Bosch

We report recent progress towards the realization of a sub-mK, low-vibration environment at the bottom stage of a dry dilution refrigerator for use in mechanical tests of quantum mechanics. Using adiabatic nuclear demagnetization, we have cooled a silicon cantilever force sensor to $T\approx 1$ mK. The temperature of the tip-holder of the cantilever chip was

Mrinal Kanti Roychowdhury, Karoly Simon

Quantization dimension has been computed for many invariant measures of dynamically defined fractals having well separated cylinders, that is, in the cases when the so-called Open Set Condition (OSC) holds. To attack the same problem in case of heavy overlaps between the cylinders, we consider a family of self-similar measures, for which the underlying Itera

Golan Bel, Boian S. Alexandrov, Alan R. Bishop, Kim Ø. Rasmussen

Nonlinear isolated and coupled oscillators are extensively studied as prototypical nonlinear dynamics models. Much attention has been devoted to oscillator synchronization or the lack thereof. Here, we study the synchronization and stability of coupled driven-damped Helmholtz-Duffing oscillators in bi-stability regimes. We find that despite the fact that the

Ben Chugg, Peter Henderson, Jacob Goldin, Daniel E. Ho

Entropy regularization is known to improve exploration in sequential decision-making problems. We show that this same mechanism can also lead to nearly unbiased and lower-variance estimates of the mean reward in the optimize-and-estimate structured bandit setting. Mean reward estimation (i.e., population estimation) tasks have recently been shown to be essen

Harbir Antil, Hugo Díaz, Tian Jing, Armin Schikorra

Motivated by problems where jumps across lower dimensional subsets and sharp transitions across interfaces are of interest, this paper studies the properties of fractional bounded variation ($BV$)-type spaces. Two different natural fractional analogs of classical $BV$ are considered: $BV^\alpha$, a space induced from the Riesz-fractional gradient that has be

Shantenu Jha, Vincent R. Pascuzzi, Matteo Turilli

Increasingly, scientific discovery requires sophisticated and scalable workflows. Workflows have become the ``new applications,'' wherein multi-scale computing campaigns comprise multiple and heterogeneous executable tasks. In particular, the introduction of AI/ML models into the traditional HPC workflows has been an enabler of highly accurate modeling, typi

Aline Weber, Blossom Metevier, Yuriy Brun, Philip S. Thomas

Recent research has shown that seemingly fair machine learning models, when used to inform decisions that have an impact on peoples' lives or well-being (e.g., applications involving education, employment, and lending), can inadvertently increase social inequality in the long term. This is because prior fairness-aware algorithms only consider static fairness

Guangyao Dou, Zheng Zhou

Using Machine Learning and Deep Learning to predict cognitive tasks from electroencephalography (EEG) signals has been a fast-developing area in Brain-Computer Interfaces (BCI). However, during the COVID-19 pandemic, data collection and analysis could be more challenging. The remote experiment during the pandemic yields several challenges, and we discuss the

Gustavo H. Silvestre, Felipe Crasto de Lima, Juliana S. Bernardes, Adalberto Fazzio

The development of electronic devices based on the functionalization of (nano)cellulose platforms relies upon an atomistic understanding of the structural, and electronic properties of the combined system, cellulose/functional element. In this work, we present a theoretical study of the nanocellulose/graphene interface (nCL/G) based on first-principles calcu

Vladimir Kozlov

We give a quite simple approach how to prove the absence of loops in bifurcation branches of water waves in rotational case with arbitrary vorticity distribution. The supporting flow may contain stagnation points and critical layers and water surface is allowed to be overhanging. Monotonicity properties of the free surface are presented. Especially simple cr

Donggeun Tak, Matthew Baumgart, Nicholas L. Rodd, Elisa Pueschel

For decades, searches for electroweak-scale dark matter (DM) have been performed without a definitive detection. This lack of success may hint that DM searches have focused on the wrong mass range. A proposed candidate beyond the canonical parameter space is ultra-heavy DM (UHDM). In this work, we consider indirect UHDM annihilation searches for masses betwe

Torkan Gholamalizadeh, Faezeh Moshfeghifar, Zachary Ferguson, Teseo Schneider

Developing computational models of the human jaw acquired from cone-beam computed tomography (CBCT) scans is time-consuming and labor-intensive. Besides, a quantitative comparison is not attainable in the literature due to the involved manual tasks and the lack of surface/volumetric meshes. We share an open-access repository of 17 patient-specific finite-ele

Qiyuan Chen, Raed Al Kontar, Maher Nouiehed, Jessie Yang

Cost-sensitive classification is critical in applications where misclassification errors widely vary in cost. However, over-parameterization poses fundamental challenges to the cost-sensitive modeling of deep neural networks (DNNs). The ability of a DNN to fully interpolate a training dataset can render a DNN, evaluated purely on the training set, ineffectiv

Jin Koda, Linda Watson, Francoise Combes, Monica Rubio

We report a CO(3-2) detection of 23 molecular clouds in the extended ultraviolet (XUV) disk of the spiral galaxy M83 with ALMA. The observed 1kpc^2 region is at about 1.24 times the optical radius (R25) of the disk, where CO(2-1) was previously not detected. The detection and non-detection, as well as the level of star formation (SF) activity in the region,

Ruochen Yin, Huapeng Wu, Ming Li, Yong Cheng

Robotic peg-in-hole assembly represents a critical area of investigation in robotic automation. The fusion of reinforcement learning (RL) and deep neural networks (DNNs) has yielded remarkable breakthroughs in this field. However, existing RL-based methods grapple with delivering optimal performance under the unique environmental and mission constraints of f

Renate Kupke, R. Deno Stelter, Amirul Hasan, Arun Surya

SCALES is a high-contrast, infrared coronagraphic imager and integral field spectrograph (IFS) to be deployed behind the W.M. Keck Observatory adaptive optics system. A reflective optical design allows diffraction-limited imaging over a large wavelength range (1.0 - 5.0 microns). A microlens array-based IFS coupled with a lenslet reformatter ("slenslit") all

T. G. Khunjua, K. G. Klimenko, R. N. Zhokhov

The (2+1)-dimensional generalized massless Thirring model with 4-component Fermi-fields is investigated by the Hartree-Fock method. The Lagrangian of this model is constructed from two different four-fermion structures. One of them takes into account the vector$\times$vector channel of fermion interaction with coupling constant $G_v$, the other - the scalar$

Kosuke Yamato

For spectrally positive L\'evy processes killed on exiting the half-line, existence of a quasi-stationary distribution is characterized by the exponential integrability of the exit time, the Laplace exponent and the non-negativity of the scale functions. It is proven that if there is a quasi-stationary distribution, there are necessarily infinitely many ones

Carlos A. Cadavid, Paulina Hoyos, Jay Jorgenson, Lejla Smajlović

We derive an explicit formula for the fundamental solution $K_{T_{q+1}}(x,x_{0};t)$ to the discrete-time diffusion equation on the $(q+1)$-regular tree $T_{q+1}$ in terms of the discrete $I$-Bessel function. We then use the formula to derive an explicit expression for the fundamental solution $K_{X}(x,x_{0};t)$ to the discrete-time diffusion equation on any

Henning S. Mortveit, Ryan Pederson

We present mathematical techniques for exhaustive studies of long-term dynamics of asynchronous biological system models. Specifically, we extend the notion of $\kappa$-equivalence developed for graph dynamical systems to support systematic analysis of all possible attractor configurations that can be generated when varying the asynchronous update order (Mac

S. J. Thomson

Many-body localisation is believed to be generically unstable in quantum systems with continuous non-Abelian symmetries, even in the presence of strong disorder. Breaking these symmetries can stabilise the localised phase, leading to the emergence of an extensive number of quasi-locally conserved quantities known as local integrals of motion, or $l$-bits. Us

Pierfrancesco Urbani

Models of confluent tissues are built out of tessellations of the space (both in two and three dimensions) in which the cost function is constructed in such a way that individual cells try to optimize their volume and surface in order to reach a target shape. At zero temperature, many of these models exhibit a rigidity transition that separates two phases: a

Chakravarthi Jada, Lokesh Ch. R. S, Ashok Urlana, Shridi Swamy Yerubandi

Nature is an inhabitant for enormous number of species. All the species do perform complex activities with simple and elegant rules for their survival. The property of emergence of collective behavior is remarkably supporting their activities. One form of the collective behaviour is the swarm intelligence -- all agents poses same rules and capabilities. This

Ernest Alsina Ballester

This work aims to identify the relevant physical processes in shaping the intensity and polarization patterns of the solar K I D lines through spectral syntheses, placing particular emphasis on the D2 line. The theoretical Stokes profiles were obtained by numerically solving the radiative transfer problem for polarized radiation considering one-dimensional s

Yue Zhao, Leman Akoglu

Given an unsupervised outlier detection (OD) algorithm, how can we optimize its hyperparameter(s) (HP) on a new dataset, without any labels? In this work, we address this challenging hyperparameter optimization for unsupervised OD problem, and propose the first systematic approach called HPOD that is based on meta-learning. HPOD capitalizes on the prior perf

Xinran Liu, Yikun Bai, Yuzhe Lu, Andrea Soltoggio

Measuring similarities between different tasks is critical in a broad spectrum of machine learning problems, including transfer, multi-task, continual, and meta-learning. Most current approaches to measuring task similarities are architecture-dependent: 1) relying on pre-trained models, or 2) training networks on tasks and using forward transfer as a proxy f

Edgard Muñoz-Coreas, Himanshu Thapliyal

In this work, we provide an overview of circuits for quantum computing. We introduce gates used in quantum computation and then present resource cost measurements used to evaluate circuits made from these gates. We then illustrate how the gates shown are then combined into quantum circuits for basic arithmetic functions. Architectures for addition, subtracti

Yuxuan Zhang, Daoheng Niu, Alireza Shabani, Hassan Shapourian

Defining metrics for near-term quantum computing processors has been an integral part of the quantum hardware research and development efforts. Such quantitative characteristics are not only useful for reporting the progress and comparing different quantum platforms, but also essential for identifying the bottlenecks and designing a technology roadmap. Most

Marco Fabbrichesi, Roberto Floreanini, Emidio Gabrielli

The measurement of quantum entanglement can provide a new and most sensitive probe to physics beyond the Standard Model. We use the concurrence of the top-quark pair spin states produced at colliders to constrain the magnetic dipole term in the coupling between top quark and gluons, that of $\tau$-lepton pairs spin states to bound contact interactions and th

Isaac Layton, Jonathan Oppenheim, Zachary Weller-Davies

We study the back-reaction of quantum systems onto classical ones. Taking the starting point that semi-classical physics should be described at all times by a point in classical phase space and a quantum state in Hilbert space, we consider an unravelling approach, describing the system in terms of a classical-quantum trajectory. We derive the general form of

Tara Fetherolf, Joshua Pepper, Emilie Simpson, Stephen R. Kane

During its 2-year Prime Mission, TESS observed over 232,000 stars at a 2-min cadence across ~70% of the sky. These data provide a record of photometric variability across a range of astrophysically interesting time scales, probing stellar rotation, stellar binarity, and pulsations. We have analyzed the TESS 2-min light curves to identify periodic variability

N. I. Polushkin

Achieving the compositionally ordered state in a substitutional alloy of two or more species can often be even critical for improving its functional properties. To produce a highly ordered alloy, a longtime high-temperature (up to T=1000 K) treatment of the alloy is typically necessary because of insufficient vacancy concentration (c_v) and their mobility. H

Asvin G

In this note, we prove a criteria for supersingularity when the variety has a large automorphism group and a perfect bilinear pairing. This criteria unifies and extends many known results on the supersingularity of curves and varieties and in particular, applies to a large family of Artin-Schreier curves.

Mocho Go, Hideyuki Tachibana

Following the success in language domain, the self-attention mechanism (transformer) is adopted in the vision domain and achieving great success recently. Additionally, as another stream, multi-layer perceptron (MLP) is also explored in the vision domain. These architectures, other than traditional CNNs, have been attracting attention recently, and many meth

Nicolas Sanchis-Gual, Juan Calderón Bustillo, Carlos Herdeiro, Eugen Radu

We present a systematic study of the dynamics and gravitational-wave emission of head-on collisions of spinning vector boson stars, known as Proca stars. To this aim we build a catalogue of about 800 numerical-relativity simulations of such systems. We find that the wave-like nature of bosonic stars has a large impact on the gravitational-wave emission. In p

Kevin Singh, Conor E. Bradley, Shraddha Anand, Vikram Ramesh

Scaling up invariably error-prone quantum processors is a formidable challenge. While quantum error correction ultimately promises fault-tolerant operation, the required qubit overhead and error thresholds are daunting, and many codes break down under correlated noise. Recent proposals have suggested a complementary approach based on co-located, auxiliary 's

Aleix Gimenez-Grau, Edoardo Lauria, Pedro Liendo, Philine van Vliet

We use the numerical bootstrap to study conformal line defects with $O(2)$ global symmetry. Our results are very general and capture in particular conformal line defects originating from bulk CFTs with a continuous global symmetry, which can either be preserved or partially broken by the presence of the defect. We begin with an agnostic approach and perform

Marilena Loverde, Zachary J. Weiner

After their generation, cosmological backgrounds of gravitational waves propagate nearly freely but for the expansion of the Universe and the anisotropic stress of free-streaming particles. Primordial signals -- both that from inflation and the infrared spectrum associated to subhorizon production mechanisms -- would carry clean information about the cosmolo

Sarah Schneider, Lukas Burgholzer, Robert Wille

Executing quantum algorithms on a quantum computer requires compilation to representations that conform to all restrictions imposed by the device. Due to devices' limited coherence times and gate fidelities, the compilation process has to be optimized as much as possible. To this end, an algorithm's description first has to be synthesized using the device's

M. Michael Denner, Frank Schindler

We derive the response of non-Hermitian topological phases with intrinsic point gap topology to localized magnetic flux insertions. In two spatial dimensions, we identify the necessary and sufficient conditions for a flux skin effect that localizes an extensive number of in-gap modes at a flux core. In three dimensions, we furthermore establish the existence

Aidan Chatwin-Davies, Achim Kempf, Petar Simidzija

In this companion to our letter (arXiv:2208.10514), we elaborate the full details of the predicted corrections to the primordial scalar and tensor power spectra that arise from quantum gravity-motivated, natural, covariant ultraviolet cutoffs. We implement these cutoffs by covariantly restricting the fields which are summed over in the path integrals for the

Ruihua Fan, Rahul Sahay, Ashvin Vishwanath

We propose a new formula that extracts the quantum Hall conductance from a single (2+1)D gapped wavefunction. The formula applies to general many-body systems that conserve particle number, and is based on the concept of modular flow: i.e., unitary dynamics generated from the entanglement structure of the wavefunction. The formula is shown to satisfy all for

Liliya L. R. Williams, Jens Hjorth

Self-gravitating Newtonian systems consisting of a very large number of particles have generally defied attempts to describe them using statistical mechanics. This is paradoxical since many astronomical systems, or simulations thereof, appear to have universal, equilibrium structures for which no physical basis exist. A decade ago we showed that extremizing

Kyohei Mukaida, Masaki Yamada

High-energy standard model (SM) particles in the early Universe are generated by the decay of heavy long-lived particles. The subsequent thermalization occurs through the splitting of high-energy primary particles into lower-energy daughters in primordial thermal plasma. The principal example of such processes is reheating after inflation caused by the decay

Vincenzo Cirigliano, Andreas Crivellin, Martin Hoferichter, Matthew Moulson

Precision tests of first-row unitarity of the Cabibbo-Kobayashi-Maskawa matrix currently display two intriguing tensions, both at the $3\sigma$ level. First, combining determinations of $V_{ud}$ from superallowed $\beta$ decays with $V_{us}$ from kaon decays suggests a deficit in the unitarity relation. At the same time, a tension of similar significance has

Batoul Banihashemi, Ted Jacobson, Andrew Svesko, Manus Visser

Due to a well-known, but curious, minus sign in the Gibbons-Hawking first law for the static patch of de Sitter space, the entropy of the cosmological horizon is reduced by the addition of Killing energy. This minus sign raises the puzzling question how the thermodynamics of the static patch should be understood. We argue the confusion arises because of a mi

Michael Weis, Stefanie Walch, Daniel Seifried, Shashwata Ganguly

We simulate the formation of molecular clouds in colliding flows of warm neutral medium with the adaptive mesh refinement code {\sc Flash}. We include a chemical network to treat heating and cooling and to follow the formation of molecular gas. For the forming molecular clumps and cores in four different simulations with varying initial magnetic field streng

Axel Widmark, Michael Korsmeier, Tim Linden

Cold gas forms a significant mass fraction of the Milky Way disk, but is its most uncertain baryonic component. The density and distribution of cold gas is of critical importance for Milky Way dynamics, as well as models of stellar and galactic evolution. Previous studies have used correlations between gas and dust to obtain high-resolution measurements of c

Marco Fazzi, Suvendu Giri

$N$ M5-branes probing the intersection between the orbifold $\mathbb{C}^2/\Gamma_\text{ADE}$ and an $E_8$ wall give rise to 6d $(1,0)$ SCFTs known as ADE-type orbi-instantons. At fixed $N$ and order of the orbifold, each element of $\text{Hom}(\Gamma_\text{ADE},E_8)$ defines a different SCFT. The SCFTs are connected by Higgs branch RG flows, which genericall

Jong Yeon Lee, Wenjie Ji, Zhen Bi, Matthew P. A. Fisher

Measurements allow efficient preparation of interesting quantum many-body states with long-range entanglement, conditioned on additional transformations based on measurement outcomes. Here, we demonstrate that the so-called conformal quantum critical points (CQCP) can be obtained by performing general single-site measurements in an appropriate basis on the c

Zahra Baghali Khanian, Kohdai Kuroiwa, Debbie Leung

This paper is concerned with quantum data compression of asymptotically many independent and identically distributed copies of ensembles of mixed quantum states. The encoder has access to a side information system. The figure of merit is per-copy or local error criterion. Rate-distortion theory studies the trade-off between the compression rate and the per-c

Marek Lewicki, Ville Vaskonen

We estimate the gravitational wave spectra generated in strongly supercooled phase transitions by bubble collisions and fluid motion. We derive analytically in the thin-wall approximation the efficiency factor that determines the share of the energy released in the transition between the scalar field and the fluid. We perform numerical simulations including

Martina Stojić

Given a Hopf algebra $H$, Brzezi\'nski and Militaru have shown that each braided commutative Yetter-Drinfeld $H$-module algebra $A$ gives rise to an associative $A$-bialgebroid structure on the smash product algebra $A \sharp H$. They also exhibited an antipode map making $A\sharp H$ the total algebra of a Lu's Hopf algebroid over $A$. However, the published

Alexandra Sasha Luccioni, David Rolnick

ImageNet-1k is a dataset often used for benchmarking machine learning (ML) models and evaluating tasks such as image recognition and object detection. Wild animals make up 27% of ImageNet-1k but, unlike classes representing people and objects, these data have not been closely scrutinized. In the current paper, we analyze the 13,450 images from 269 classes th

Jefferson Bastos, Claudio Buzzi, Paulo Santana

The introduction of concepts of Game Theory and Ordinary Differential Equations into Biology gave birth to the field of Evolutionary Stable Strategies, with applications in Biology, Genetics, Politics, Economics and others. In special, the model composed by two players having two pure strategies each results in a planar cubic vector field with an invariant o

Honglu Jiang, Haotian Yu, Xiuzhen Cheng, Jian Pei

A large amount of high-dimensional and heterogeneous data appear in practical applications, which are often published to third parties for data analysis, recommendations, targeted advertising, and reliable predictions. However, publishing these data may disclose personal sensitive information, resulting in an increasing concern on privacy violations. Privacy

The JWST Transiting Exoplanet Community Early Release Science Team, Eva-Maria Ahrer, Lili Alderson, Natalie M. Batalha

Carbon dioxide (CO2) is a key chemical species that is found in a wide range of planetary atmospheres. In the context of exoplanets, CO2 is an indicator of the metal enrichment (i.e., elements heavier than helium, also called "metallicity"), and thus formation processes of the primary atmospheres of hot gas giants. It is also one of the most promising specie

LHCb Collaboration

Jet fragmentation functions are measured for the first time in proton-proton collisions for charged pions, kaons, and protons within jets recoiling against a $Z$ boson. The charged-hadron distributions are studied longitudinally and transversely to the jet direction for jets with transverse momentum 20 $< p_{\textrm{T}} < 100$ GeV and in the pseudorapidity r

Zohar Nussinov, Gerardo Ortiz

We establish, in the spirit of the Lieb-Schultz-Mattis theorem, lower bounds on the spectral degeneracy of quantum systems with higher (Gauge Like) symmetries with rather generic physical boundary conditions in an arbitrary number of spatial dimensions. Contrary to applying twists or equivalent adiabatic operations, we exploit the effects of modified boundar

ANTARES Collaboration, A. Albert, S. Alves, M. André

In this work, a search for nuclearites of strange quark matter by using nine years of ANTARES data taken in the period 2009-2017 is presented. The passage through matter of these particles is simulated %according to the model of de R\'{u}jula and Glashow taking into account a detailed description of the detector response to nuclearites and of the data acquis

Jake Gonzalez, Ngan V. T. Nguyen, Tommy Dang

This paper presents VisFCAC, a visual analysis system that displays family structures along with clinical attribute of family members to effectively uncover patterns related to suicide deaths for submission to the BioVis 2020 Data Challenge. VisFCAC facilitates pattern tracing to offer insight on potential clinical attributes that might connect suicide death

Fernanda B. J. R. Dallaqua, Álvaro Luiz Fazenda, Fabio A. Faria

Rainforests play an important role in the global ecosystem. However, significant regions of them are facing deforestation and degradation due to several reasons. Diverse government and private initiatives were created to monitor and alert for deforestation increases from remote sensing images, using different ways to deal with the notable amount of generated

Sven Heydenreich, Laila Linke, Pierre Burger, Peter Schneider

In this work, which is the first of a series to prepare a cosmological parameter analysis with third-order cosmic shear statistics, we model both the shear three-point correlation functions $\Gamma^{(i)}$ and the third-order aperture statistics $\langle\mathcal{M}_\mathrm{ap}^3\rangle$ from the BiHalofit bispectrum model and validate these statistics with a

Stanisław W. Biber, Alan R. Champneys, Robert Szalai

Inspired by the turf-ball interaction in golf, this paper seeks to understand the bounce of a ball that can be modelled as a rigid sphere and the surface as supplying an elasto-plastic contact force in addition to Coulomb friction. A general formulation is proposed that models the finite time interval of bounce from touch-down to lift-off. Key to the analysi

Benoit Tallon, Thomas Brunet, John H. Page

We show how resonant (near-field) coupling affects wave transport in disordered media through ultrasonic experiments in concentrated suspensions. The samples consist of resonant emulsions in which oil droplets are suspended in a liquid gel. By varying the droplet concentration, the limits of the Independent Scattering Approximation are experimentally demonst

Arjun Dey, Joan R. Najita, S. E. Koposov, J. Josephy-Zack

We present DESI observations of the inner halo of M31, which reveal the kinematics of a recent merger - a galactic immigration event - in exquisite detail. Of the 11,416 sources studied in 3.75 hour of on-sky exposure time, 7,438 are M31 sources with well measured radial velocities. The observations reveal intricate coherent kinematic structure in the positi

D Maneesh Reddy, Divyanshi Dwivedi, Pradeep Kumar Yemula, Mayukha Pal

With the commitment to climate, globally many countries started reducing brownfield energy production and strongly opting towards green energy resources. However, the optimal allocation of distributed energy resources (DERs) in electrical distribution systems still pertains as a challenging issue to attain the maximum benefits. It happens due to the systems

Valerio Gilles, Danielius Banys, Mark A. McCulloch, Lucio Piccirillo

Superconducting parametric amplifiers are commonly fabricated using planar transmission lines with a non-linear inductance provided by either Josephson junctions or the intrinsic kinetic inductance of the thin film. However, Banys et al. [1] reported non-linear behaviour in a niobium pillbox cavity, hypothesising that below Tc, the pair iris-bulk resonator w

Fabiano Pereira de Oliveira, Christiane Gresse von Wangenheim, Jean C. R. Hauck

TMIC is an App Inventor extension for the deployment of ML models for image classification developed with Google Teachable Machine in educational settings. Google Teachable Machine, is an intuitive visual tool that provides workflow-oriented support for the development of ML models for image classification. Aiming at the usage of models developed with Google

Lorenzo Miretti, Emil Björnson, David Gesbert

In a recent work, we studied a novel precoding design for cell-free networks called team minimum mean-square error (TMMSE) precoding, which rigorously generalizes centralized MMSE precoding to distributed operations based on transmitter-specific channel state information (CSI). Despite its flexibility in handling different cooperation regimes at the CSI shar

Mohammadreza Sabzehali, Amir Hossein Rabieeb, Mahdi Alibeigia, Amir Mosavi

In the present study, the effects of flight-Mach number, flight altitude, fuel types, and intake air temperature on thrust specific fuel consumption, thrust, intake air mass flow rate, thermal and propulsive efficiecies, as well as the exergetic efficiency and the exergy destruction rate in F135 PW100 engine are investigated. Based on the results obtained in

Arnaud Mazier, Sidaty El Hadramy, Jean-Nicolas Brunet, Jack S. Hale

This new approach allows the user to experiment with model choices easily and quickly without requiring in-depth expertise, as constitutive models can be modified by one line of code only. This ease in building new models makes SOniCS ideal to develop surrogate, reduced order models and to train machine learning algorithms for uncertainty quantification or t

Idris Assani

Let $T$ be the map defined on $\N=\{1,2,3, ...\}$ by $T(n) = \frac{n}{2} $ if $n$ is even and by $T(n) = \frac{3n+1}{2}$ if $n$ is odd. Consider the dynamical system $(\N, 2^{\N}, T,\mu)$ where $\mu$ is the counting measure. This dynamical system $(\N, 2^{\N}, T, \mu)$ has the following properties. \begin{enumerate} \item There exists an invariant finite mea

Zuguang Gu

The R package ecosystem is expanding fast and dependencies among packages in the ecosystem are becoming more complex. In this study, we explored the package dependencies from a new aspect. We applied a new metric named "dependency heaviness" which measures the number of additional strong dependencies that a package uniquely contributes to its child or downst

Xiaoshuai Fan, Xin Li, Zhibo Chen

As a commonly-used image compression format, JPEG has been broadly applied in the transmission and storage of images. To further reduce the compression cost while maintaining the quality of JPEG images, lossless transcoding technology has been proposed to recompress the compressed JPEG image in the DCT domain. Previous works, on the other hand, typically red

Anindya Ghatak

In this article, we attempt to introduce the "Multiplier algebra" associated to the Fock representation that arising from the left-cancellative semigroup $\mathcal{S}$ (denoted by $M(\mathcal{S})$) by adopting the concept of multiplier algebra of a $C^*$-algebra. Then, we investigate the basic properties and examples of the multiplier algebras. In order to m

Ziyue Zhu

We consider the noir classification problem by exploring noir attributes and what films are likely to be regarded as noirish from the perspective of a wide Internet audience. We use a dataset consisting of more than 30,000 films with relevant tags added by users of MovieLens, a web-based recommendation system. Based on this data, we develop a statistical mod

Yixiao Zhang, Junyan Jiang, Gus Xia, Simon Dixon

Lyric interpretations can help people understand songs and their lyrics quickly, and can also make it easier to manage, retrieve and discover songs efficiently from the growing mass of music archives. In this paper we propose BART-fusion, a novel model for generating lyric interpretations from lyrics and music audio that combines a large-scale pre-trained la

Dhruv Bhasin, Sayar Karmakar, Moumanti Podder, Souvik Roy

Different versions of percolation games on $\mathbb{Z}^{2}$, with parameters $p$ and $q$ that indicate, respectively, the probability with which a site in $\mathbb{Z}^{2}$ is labeled a trap and the probability with which it is labeled a target, are shown to have probability $0$ of culminating in draws when $p+q > 0$. We show that, for fixed $p$ and $q$, the

Dimitris Stripelis, Umang Gupta, Nikhil Dhinagar, Greg Ver Steeg

Federated training of large deep neural networks can often be restrictive due to the increasing costs of communicating the updates with increasing model sizes. Various model pruning techniques have been designed in centralized settings to reduce inference times. Combining centralized pruning techniques with federated training seems intuitive for reducing com

Andrea D. Weibel, Enci Wang, Simon J. Lilly

In this paper we estimate the "star formation change parameter", SFR$_{79}$, which characterizes the current SFR relative to the average during the last 800 Myr, for $\sim$ 300'000 galaxies selected from the Sloan Digital Sky Survey (SDSS). The goals are to examine, in a much larger and independent sample, the trends previously reported in a sample of star-f

Joshua Bundt, Michael Davinroy, Ioannis Agadakos, Alina Oprea

Binary analyses based on deep neural networks (DNNs), or neural binary analyses (NBAs), have become a hotly researched topic in recent years. DNNs have been wildly successful at pushing the performance and accuracy envelopes in the natural language and image processing domains. Thus, DNNs are highly promising for solving binary analysis problems that are typ

Jamie Menjay Lin, Siargey Pisarchyk, Juhyun Lee, David Tian

We introduce an efficient video segmentation system for resource-limited edge devices leveraging heterogeneous compute. Specifically, we design network models by searching across multiple dimensions of specifications for the neural architectures and operations on top of already light-weight backbones, targeting commercially available edge inference engines.

Nick Whiteley, Annie Gray, Patrick Rubin-Delanchy

The Manifold Hypothesis is a widely accepted tenet of Machine Learning which asserts that nominally high-dimensional data are in fact concentrated near a low-dimensional manifold, embedded in high-dimensional space. This phenomenon is observed empirically in many real world situations, has led to development of a wide range of statistical methods in the last

S. M. M. Rasouli, S. Jalalzadeh, P. V. Moniz

We present a brief description of noncompactified higher-dimensional theories from the perspective of general relativity. More concretely, the Space-Time-Matter theory, or Induced Matter theory, and the reduction procedure used to construct the modified Brans-Dicke theory and the modified S\'{a}ez-Ballester theory are briefly explained. Finally, we apply the

Timo Schick, Jane Dwivedi-Yu, Zhengbao Jiang, Fabio Petroni

Textual content is often the output of a collaborative writing process: We start with an initial draft, ask for suggestions, and repeatedly make changes. Agnostic of this process, today's language models are trained to generate only the final result. As a consequence, they lack several abilities crucial for collaborative writing: They are unable to update ex

Felix Kramer, Carl D Modes

The observation, design and analysis of mesh-like networks in bionics, polymer physics and biological systems has brought forward an extensive catalog of fascinating structures of which a subgroup share a particular, yet critically under appreciated attribute: being embedded in space such that one wouldn't be able to pull them apart without prior removal of