December 2020 arXiv papers — page 100

Tonatiuh Hernández-Del-Toro, Carlos A. Reyes-García

A Brain Computer Interface based on imagined words can decode the word a subject is thinking on through brain signals to control an external device. In order to build a fully asynchronous Brain Computer Interface based on imagined words in electroencephalogram signals as source, we need to solve the problem of detecting the onset of the imagined words. Altho

Yukiko S. Shimizu, Eric J. Parish

This work presents the windowed space-time least-squares Petrov-Galerkin method (WST-LSPG) for model reduction of nonlinear parameterized dynamical systems. WST-LSPG is a generalization of the space-time least-squares Petrov-Galerkin method (ST-LSPG). The main drawback of ST-LSPG is that it requires solving a dense space-time system with a space-time basis t

Narayan Bhusal, Mukesh Gautam

Accurate estimation of power system dynamics is very important for the enhancement of power system reliability, resilience, security, and stability of power system. With the increasing integration of inverter-based distributed energy resources, the knowledge of power system dynamics has become more necessary and critical than ever before for proper control a

Daria V. Andreeva, Maxim Trushin, Anna Nikitina, Mariana C. F. Costa

Membranes are ubiquitous in nature with primary functions that include adaptive filtering and selective transport of chemical and molecular species. Being critical to cellular functions, they are also fundamental in many areas of science and technology. Of particular importance are the adaptive and programmable membranes that can change their permeability or

Xiaoyan Zhang, Pauline M. G. van Deursen, Wangyang Fu, Gregory F. Schneider

A wide range of approaches have been explored to meet the challenges of graphene nanostructure fabrication, all requiring complex and high-end nanofabrication platform and suffering from surface contaminations, potentially giving electrical noise and increasing the thickness of the atomically thin graphene membrane. Here, with the use of an electrical pulse

Xiaoyan Zhang, Qiushi Jing, Shen Ao, Grégory F. Schneider

This review provides a critical overview of current developments on nanoelectronic biochemical sensors based on graphene. Composed of a single layer of conjugated carbon atoms, graphene has outstanding high carrier mobility and low intrinsic electrical noise, but a chemically inert surface. Surface functionalization is therefore crucial to unravel graphene s

Odest Chadwicke Jenkins, Daniel Lopresti, Melanie Mitchell

The history of AI has included several "waves" of ideas. The first wave, from the mid-1950s to the 1980s, focused on logic and symbolic hand-encoded representations of knowledge, the foundations of so-called "expert systems". The second wave, starting in the 1990s, focused on statistics and machine learning, in which, instead of hand-programm

Suresh Venkatasubramanian, Nadya Bliss, Helen Nissenbaum, Melanie Moses

Innovations in AI have focused primarily on the questions of "what" and "how"-algorithms for finding patterns in web searches, for instance-without adequate attention to the possible harms (such as privacy, bias, or manipulation) and without adequate consideration of the societal context in which these systems operate. In part, this is driven

F. Aragón, J. E. V. Guzmán, L. Di G. Sigalotti, J. Klapp

An experimental and numerical smoothed particle hydrodynamics (SPH) analysis was performed for the convective flow arising from a horizontal, thin cylindrical heat source enclosed in a glycerin-filled, slender enclosure at low Rayleigh numbers ($1.18\leq {\rm Ra}\leq 242$). Both the experiments and the SPH calculations were performed for positive ($0.1\leqΔT

Razin Farhan Hussain, Alireza Pakravan, Mohsen Amini Salehi

Cloud-based Deep Neural Network (DNN) applications that make latency-sensitive inference are becoming an indispensable part of Industry 4.0. Due to the multi-tenancy and resource heterogeneity, both inherent to the cloud computing environments, the inference time of DNN-based applications are stochastic. Such stochasticity, if not captured, can potentially l

Tsung-Wei Chen, Hsiu-Chuan Hsu

We investigate the Drude model of spin dynamics in two-dimensional spin-orbit coupled systems. In the absence of an applied electric field, the spin aligns with the k-dependent effective magnetic field. The influence of disorder (the momentum relaxation time $τ$) on the system is considered. In the presence of an electric field, the change in momentum causes

Ian Foster, David Parkes, Stephan Zheng

The use of computational simulation is by now so pervasive in society that it is no exaggeration to say that continued U.S. and international prosperity, security, and health depend in part on continued improvements in simulation capabilities. What if we could predict weather two weeks out, guide the design of new drugs for new viral diseases, or manage new

Esther Elbaz Saban

A bijection $(l,r)$ between $M^2$ and $M$ is said to be a pairing function with no cycles, if any composition of its coordinate functions has no fixed point. We compute here the Grothendieck ring of the pairing function without cycles to be isomorphic to $\mathbb{Z}^2\simeq \mathbb{Z}[X]/(X-X^2)$. More generally, for any $n\in \mathbb{N}^*$ and any bijetion

A. N. Heinze, Larry Denneau, John L. Tonry, Steven J. Smartt

We estimate the total population of near-Earth objects (NEOs) in the Solar System, using an extensive, `Solar System to pixels' fake-asteroid simulation to debias detections of real NEOs by the ATLAS survey. Down to absolute magnitudes $H=25$ and 27.6 (diameters of $\sim 34$ and 10 meters, respectively, for 15% albedo), we find total populations of $(3.7

H. I. Nurdin, N. H. Amini, J. Chen

In this paper, we develop a system identification algorithm to identify a model for unknown linear quantum systems driven by time-varying coherent states, based on empirical single-shot continuous homodyne measurement data of the system's output. The proposed algorithm identifies a model that satisfies the physical realizability conditions for linear qua

Anna Mateo-Sanchis, Jordi Munoz-Mari, Manuel Campos-Taberner, Javier Garcia-Haro

In this work we evaluate multi-output (MO) Gaussian Process (GP) models based on the linear model of coregionalization (LMC) for estimation of biophysical parameter variables under a gap filling setup. In particular, we focus on LAI and fAPAR over rice areas. We show how this problem cannot be solved with standard single-output (SO) GP models, and how the pr

Anna Mateo-Sanchis, Maria Piles, Jordi Muñoz-Marí, Jose E. Adsuara

Developing accurate models of crop stress, phenology and productivity is of paramount importance, given the increasing need of food. Earth observation remote sensing data provides a unique source of information to monitor crops in a temporally resolved and spatially explicit way. In this study, we propose the combination of multisensor (optical and microwave

Masahiko Ueda

We introduce the concept of deformed zero-determinant strategies in repeated games. We then show that the Tit-for-Tat strategy in the repeated prisoner's dilemma game is a deformed zero-determinant strategy, which unilaterally equalizes the probability distribution functions of payoffs of two players.

Jose I. Liberati

We find a necessary and sufficient condition for the existence of the tensor product of modules over a Lie conformal algebra. We provide two algebraic constructions of the tensor product. We show the relation between tensor product and conformal linear maps. We prove commutativity of the tensor product.

C. D. Wilen, S. Abdullah, N. A. Kurinsky, C. Stanford

The central challenge in building a quantum computer is error correction. Unlike classical bits, which are susceptible to only one type of error, quantum bits ("qubits") are susceptible to two types of error, corresponding to flips of the qubit state about the $X$- and $Z$-directions. While the Heisenberg Uncertainty Principle precludes simultaneous monitori

N. A. Lopez, I. Y. Dodin

The metaplectic transform (MT), a generalization of the Fourier transform sometimes called the linear canonical transform, is a tool used ubiquitously in modern optics, for example, when calculating the transformations of light beams in paraxial optical systems. The MT is also an essential ingredient of the geometrical-optics modeling of caustics that was re

Kyle N. Edwards, Xiao Shen

Memristor-based computer architectures are becoming more attractive as a possible choice of hardware for the implementation of neural networks. However, at present, memristor technologies are susceptible to a variety of failure modes, a serious concern in any application where regular access to the hardware may not be expected or even possible. In this study

J. Q. Quach, K. E. McGhee, L. Ganzer, D. M. Rouse

The rate at which matter emits or absorbs light can be modified by its environment, as dramatically exemplified by the widely-studied phenomenon of superradiance. The reverse process, superabsorption, is harder to demonstrate due to the challenges of probing ultrafast processes, and has only been seen for small numbers of atoms. Its central idea - superexten

Amin Fakhari, Aditya Patankar, Nilanjan Chakraborty

Manipulation of objects by exploiting their contact with the environment can enhance both the dexterity and payload capability of robotic manipulators. A common way to manipulate heavy objects beyond the payload capability of a robot is to use a sequence of pivoting motions, wherein, an object is moved while some contact points between the object and a suppo

Shuang Liu, Qi Tang, Xian-Zhu Tang

A parallel cut-cell algorithm is described to solve the free-boundary problem of the Grad-Shafranov equation. The algorithm reformulates the free-boundary problem in an irregular bounded domain and its important aspects include a searching algorithm for the magnetic axis and separatrix, a surface integral along the irregular boundary to determine the boundar

Shyam Nandan, Sumit Kumar Ram, Guy Ouillon, Didier Sornette

Seismicity and faulting within the Earth crust are characterized by many scaling laws that are usually interpreted as qualifying the existence of underlying physical mechanisms associated with some kind of criticality in the sense of phase transitions. Using an augmented Epidemic-Type Aftershock Sequence (ETAS) model that accounts for the spatial variability

David Handelman

An $(n-1)$-tuple $a = (a(1), \dots, a(n-1))$ consisting of positive integers is said to be asymptotically hollow if there exist infinitely many positive integers $N$ such that the convex hull, $K(a(n))$, in $n$-dimensional Euclidean space of $\{ 0,e_1, \dots, e_{n-1}, \alpha(N)^T\}$ is hollow (has no lattice points in its interior), where $e_i$ run over all

Paolo Braccia, Filippo Caruso, Leonardo Banchi

Quantum Machine Learning is where nowadays machine learning meets quantum information science. In order to implement this new paradigm for novel quantum technologies, we still need a much deeper understanding of its underlying mechanisms, before proposing new algorithms to feasibly address real problems. In this context, quantum generative adversarial learni

Zhaoyi Zhang, Songyang Cheng, Claudia Solis-Lemus

The accurate prediction of biological features from genomic data is paramount for precision medicine and sustainable agriculture. For decades, neural network models have been widely popular in fields like computer vision, astrophysics and targeted marketing given their prediction accuracy and their robust performance under big data settings. Yet neural netwo

Nicholas G. Vlamis

We prove that the mapping class group of a surface obtained from removing a Cantor set from either the 2-sphere, the plane, or the interior of the closed 2-disk has no proper countable-index subgroups. The proof is an application of the automatic continuity of these groups, which was established by Mann. As corollaries, we see that these groups do not contai

Oliver F. Thomas, Will McCutcheon, Dara P. S. McCutcheon

The challenging requirements of large scale quantum information processing using parametric heralded single photon sources involves maximising the interference visibility whilst maintaining an acceptable photon generation rate. By developing a general theoretical framework that allows us to include large numbers of spatial and spectral modes together with li

Massimo Borghi, Davide Bazzanella, Mattia Mancinelli, Lorenzo Pavesi

The temporal dynamics of integrated silicon resonators has been modeled using a set of equations coupling the internal energy, the temperature and the free carrier population. Owing to its simplicity, Newton's law of cooling is the traditional choice for describing the thermal evolution of such systems. In this work, we theoretically and experimentally prove

Kh. P. Gnatenko, V. M. Tkachuk

We consider graph states generated by operator of evolution with Ising Hamiltonian. The geometric measure of entanglement of a spin with other spins in the graph state is obtained analytically and quantified on IBM's quantum computer, IBM Q Valencia. The results of quantum calculations are in good agreement with the theoretical ones. We conclude that the geo

Zachary C. Brown, Nathaniel Robinson, David Wingate, Nancy Fulda

It is notoriously difficult to control the behavior of artificial neural networks such as generative neural language models. We recast the problem of controlling natural language generation as that of learning to interface with a pretrained language model, just as Application Programming Interfaces (APIs) control the behavior of programs by altering hyperpar

John Kalung Leung, Igor Griva, William G. Kennedy

This paper utilizes an ingenious text-based affective aware pseudo association method (AAPAM) to link disjoint users and items across different information domains and leverage them to make cross-domain content-based and collaborative filtering recommendations. This paper demonstrates that the AAPAM method could seamlessly join different information domain d

Navid Hashemi, Justin Ruths, Mahyar Fazlyab

Abstracting neural networks with constraints they impose on their inputs and outputs can be very useful in the analysis of neural network classifiers and to derive optimization-based algorithms for certification of stability and robustness of feedback systems involving neural networks. In this paper, we propose a convex program, in the form of a Linear Matri

Yan Jiang, Moritz to Baben, Yuankun Lin, Chris Littler

Through the positive role of alkali halides in realizing large area growth of transition metal-di-chalcogenide layers has been validated, the film-growth kinematics has not yet been fully established. This work presents a systematic analysis of the MoS$_2$ morphology for films grown under various pre-treatment conditions of the substrate with sodium chloride

John Southworth

V1022 Cas has been known as a spectroscopic binary for a century. It was found to be eclipsing based on photometry from the Hipparcos satellite, and an astrometric orbit was recently obtained from near-infrared interferometry. We present the first high-precision measurement of the radii of the stars based on light curves obtained by the TESS satellite. Combi

John Southworth

KX Cancri is an eclipsing binary containing two G-type stars with an orbital period of 31.2 d and an eccentricity of 0.47. These qualities make it a promising candidate for a benchmark solar-type binary system. We analyse the first light curve of this system to have complete coverage of both primary and secondary eclipses, obtained using the Transiting Exopl

Matthew J. Dolan, Tomasz P. Dutka, Raymond R. Volkas

We analyse the experimental limits on the breaking scale of Pati-Salam extensions of the Standard Model. These arise from the experimental limits on rare-meson decay processes mediated at tree-level by the vector leptoquark in the model. This leptoquark ordinarily couples to to both left- and right-handed SM fermions and therefore the meson decays do not exp

Steven Golovkine, Nicolas Klutchnikoff, Valentin Patilea

We propose a model-based clustering algorithm for a general class of functional data for which the components could be curves or images. The random functional data realizations could be measured with error at discrete, and possibly random, points in the definition domain. The idea is to build a set of binary trees by recursive splitting of the observations.

Shayan Alikhanloo, Michael Hinz

We construct self-adjoint Laplacians and symmetric Markov semigroups on hyperbolic attractors, endowed with Gibbs $u$-measures. If the measure has full support, we can also conclude the existence of an associated symmetric diffusion process. In the special case of partially hyperbolic diffeomorphisms induced by geodesic flows on negatively curved manifolds t

Raffaele Folino, Luis F. López Ríos, Ramón G. Plaza

The generalized Allen-Cahn equation, \[ u_t=\varepsilon^2(D(u)u_x)_x-\frac{\varepsilon^2}2D'(u)u_x^2-F'(u), \] with nonlinear diffusion, $D = D(u)$, and potential, $F = F(u)$, of the form \[ D(u) = |1-u^2|^{m}, \quad \text{or} \quad D(u) = |1-u|^{m}, \quad m >1, \] and \[ F(u)=\frac{1}{2n}|1-u^2|^{n}, \qquad n\geq2, \] respectively, is studied. These choices

Georgios Chintzoglou, Bart De Pontieu, Juan Martínez-Sykora, Viggo Hansteen

We propose and employ a novel empirical method for determining chromospheric plage regions, which seems to better isolate plage from its surrounding regions compared to other methods commonly used. We caution that isolating plage from its immediate surroundings must be done with care in order to successfully mitigate statistical biases that, for instance, ca

Hanine Awada, Michele Bolognesi, Robert Laterveer, Claudio Pedrini

We show that cubic fourfolds with lattice of algebraic 2-cycles of rank greater than 19 have abelian and finite dimensional (in the sense of Kimura) Chow motive. This also implies Abelianity and finite dimensionality of the motive of related hyperKahler varieties, such as the Fano variety of lines and the LLSvS 8fold. A similar remark allows us to show the A

Antonio Concha, Suresh Thenozhi, Ramón O. Jiménez-Betancourt, S. K. Gadi

This paper proposes an automatic tuning algorithm for a sliding mode controller (SMC) based on the Ackermann's formula, that attenuates the structural vibrations of a seismically excited building equipped with an Active Tuned Mass Damper (ATMD) mounted on its top floor. The switching gain and sliding surface of the SMC are designed through the proposed tunin

Alec Dektor, Abram Rodgers, Daniele Venturi

We present a new rank-adaptive tensor method to compute the numerical solution of high-dimensional nonlinear PDEs. The method combines functional tensor train (FTT) series expansions, operator splitting time integration, and a new rank-adaptive algorithm based on a thresholding criterion that limits the component of the PDE velocity vector normal to the FTT

David Hicks, Michael J. Mehl, Marco Esters, Corey Oses

The AFLOW Library of Crystallographic Prototypes has been extended to include a total of 1,100 common crystal structural prototypes (510 new ones with Part 3), comprising all of the inorganic crystal structures defined in the seven-volume Strukturbericht series published in Germany from 1937 through 1943. We cover a history of the Strukturbericht designation

Bakht Zaman, Luis Miguel Lopez Ramos, Baltasar Beferull-Lozano

Identifying the topology underlying a set of time series is useful for tasks such as prediction, denoising, and data completion. Vector autoregressive (VAR) model-based topologies capture dependencies among time series and are often inferred from observed spatio-temporal data. When data are affected by noise and/or missing samples, topology identification an

Jonathan Angle, Ari Palczewski, Charles E. Reece, Fred A. Stevies

Accurate SIMS measurement of nitrogen in niobium relies on the use of closely equivalent standards, made by ion implantation, to convert nitrogen signal intensity to nitrogen content by determination of relative sensitivity factors (RSF). Accurate RSF values for ppm-range nitrogen contents are increasingly critical, as more precision is sought in processes f

Alina Kochocki, Volodymyr Takhistov, Alexander Kusenko, Nathan Whitehorn

In ten years of observations, the IceCube neutrino observatory has revealed a neutrino sky in tension with previous expectations for neutrino point source emissions. Astrophysical objects associated with hadronic processes might act as production sites for neutrinos, observed as point sources at Earth. Instead, a nearly isotropic flux of astrophysical neutri

Federico Vismara, Tommaso Benacchio, Luca Bonaventura

We propose and analyze a seamless extended Discontinuous Galerkin (DG) discretization of advection-diffusion equations on semi-infinite domains. The semi-infinite half line is split into a finite subdomain where the model uses a standard polynomial basis, and a semi-unbounded subdomain where scaled Laguerre functions are employed as basis and test functions.

Ramiro M. dos Santos, Wiliam F. da Cunha, William F. Giozza, Rafael T. de Sousa Júnior

The electronic and structural properties of Janus MoSSe/MoX$_2$ (X=S,Se) in-plane heterojunctions, endowed with single-atom vacancies, were studied using density functional theory calculations. The stability of these structures was verified from cohesion energy calculations. Results showed that single-atom vacancies induce the appearance of flat midgap state

Jan Frahm

For a simple real Lie group $G$ with Heisenberg parabolic subgroup $P$, we study the corresponding degenerate principal series representations. For a certain induction parameter the kernel of the conformally invariant system of second order differential operators constructed by Barchini, Kable and Zierau is a subrepresentation which turns out to be the minim

Santiago Laplagne, Marcelo Valdettaro

We study the boundary of the cone of real polynomials that can be decomposed as a sum of squares (SOS) of real polynomials. This cone is included in the cone of nonnegative polynomials and both cones share a part of their boundary, which corresponds to polynomials that vanish at at least one point. We focus on the part of the boundary which is not shared, co

Ryan Blything, Valerio Biscione, Jeffrey Bowers

Han et al. (2020) reported a behavioral experiment that assessed the extent to which the human visual system can identify novel images at unseen retinal locations (what the authors call "intrinsic translation invariance") and developed a novel convolutional neural network model (an Eccentricity Dependent Network or ENN) to capture key aspects of the

David Azriel, Yosef Rinott

An analyst is given a training set consisting of regression datasets $D_j$ of different sizes, which are distributed according to some $G_j$, $j=1,\ldots,\cal J$, where the distributions $G_j$ are assumed to form a random sample generated by some common source. In particular, the $D_j$'s have a common set of covariates and they are all labeled. The training

R. Claes, J. Kluska, H. Van Winckel, M. Min

With the advent of interferometric instruments with 4 telescopes at the VLTI and 6 telescopes at CHARA, the scientific possibility arose to routinely obtain milli-arcsecond scale images of the observed targets. Such an image reconstruction process is typically performed in a Bayesian framework where the function to minimize is made of two terms: the datalike

Mélanie M. Bay, Silvia Vignolini, Kevin Vynck

PyLlama is a handy Python toolkit to compute the electromagnetic reflection and transmission properties of arbitrary multilayered linear media, including the case of anisotropy. Relying on a $4 \times 4$-matrix formalism, PyLlama implements not only the transfer matrix method, that is the most popular choice in existing codes, but also the scattering matrix

Walid Hariri, Ali Narin

The new coronavirus disease (COVID-19) has been declared a pandemic since March 2020 by the World Health Organization. It consists of an emerging viral infection with respiratory tropism that could develop atypical pneumonia. Experts emphasize the importance of early detection of those who have the COVID-19 virus. In this way, patients will be isolated from

Chin-Wei Huang, Ricky T. Q. Chen, Christos Tsirigotis, Aaron Courville

Flow-based models are powerful tools for designing probabilistic models with tractable density. This paper introduces Convex Potential Flows (CP-Flow), a natural and efficient parameterization of invertible models inspired by the optimal transport (OT) theory. CP-Flows are the gradient map of a strongly convex neural potential function. The convexity implies

Etienne Jambon-Puillet, Pier Giuseppe Ledda, François Gallaire, P. -T. Brun

Pendant drops suspended on the underside of a wet substrate are known to accumulate fluid from the surrounding thin liquid film, a process that often results in dripping. The growth of such drops is hastened by their ability to translate over an otherwise uniform horizontal film. Here we show that this scenario is surprisingly reversed when the substrate is

Hannah R. Schwartz

In this short note, for each non-zero integer n, we construct a 4-manifold containing a smoothly concordant pair of spheres with a common dual of square n but no automorphism carrying one sphere to the other. Our examples, besides showing that the square zero assumption on the dual is necessary in Gabai's and Schneiderman-Teichner's versions of the 4

Dayi Li, Pauline Barmby

We demonstrate the power of Gibbs point process models from the spatial statistics literature when applied to studies of resolved galaxies. We conduct a rigorous analysis of the spatial distributions of objects in the star formation complexes of M33, including giant molecular clouds (GMCs) and young stellar cluster candidates (YSCCs). We choose a hierarchica

Mikkel Stockmann, Inger Jørgensen, Sune Toft, Christopher J. Conselice

We examine the Fundamental Plane (FP) and mass-to-light ratio ($M/L$) scaling relations using the largest sample of massive quiescent galaxies at $1.5<z<2.5$ to date. The FP ($r_{e}, \sigma_{e}, I_{e}$) is established using $19$ $UVJ$ quiescent galaxies from COSMOS with $Hubble$ $Space$ $Telescope$ $(HST)$ $H_{F160W}$ rest-frame optical sizes and X-shooter a

Mansooreh Karami, Ahmadreza Mosallanezhad, Michelle V Mancenido, Huan Liu

Neural network-based embeddings have been the mainstream approach for creating a vector representation of the text to capture lexical and semantic similarities and dissimilarities. In general, existing encoding methods dismiss the punctuation as insignificant information; consequently, they are routinely treated as a predefined token/word or eliminated in th

Mattia Di Mauro, Silvia Manconi, Michela Negro, Fiorenza Donato

Numerous extended sources around Galactic pulsars have shown significant $\gamma$-ray emission from GeV to TeV energies, revealing hundreds of TeV energy electrons scattering off of the underlying photon fields through inverse Compton scattering (ICS). HAWC TeV gamma-ray observations of few-degree extended emission around the pulsars Geminga and Monogem, and

Wenlong Yuan, Lucas M. Macri, Bradley M. Peterson, Adam G. Riess

We derive a distance of $D = 16.6 \pm 0.3$~Mpc ($\mu=31.10\pm0.04$~mag) to the archetypal narrow-line Seyfert 1 galaxy NGC 4051 based on Cepheid Period--Luminosity relations and new Hubble Space Telescope multiband imaging. We identify 419 Cepheid candidates and estimate the distance at both optical and near-infrared wavelengths using subsamples of precisely

Santanu Pal, Prakash Sharma, Hitesh J. Changlani, Sumiran Pujari

In the XY regime of the XXZ Heisenberg model phase diagram, we demonstrate that the origin of magnetically ordered phases is influenced by the presence of solvable points with exact quantum coloring ground states featuring a quantum-classical correspondence. Using exact diagonalization and density matrix renormalization group calculations, for both the squar

Steffen Borgwardt, Felix Happach, Stetson Zirkelbach

The separability of clusters is one of the most desired properties in clustering. There is a wide range of settings in which different clusterings of the same data set appear. We are interested in applications where there is a need for an explicit, gradual transition of one separable clustering into another one. This transition should be a sequence of simple

S. Mucesh, W. G. Hartley, A. Palmese, O. Lahav

We demonstrate that highly accurate joint redshift-stellar mass probability distribution functions (PDFs) can be obtained using the Random Forest (RF) machine learning (ML) algorithm, even with few photometric bands available. As an example, we use the Dark Energy Survey (DES), combined with the COSMOS2015 catalogue for redshifts and stellar masses. We build

Jenny Calahan, Edwin Bergin, Ke Zhang, Richard Teague

The thermal structure of protoplanetary disks is a fundamental characteristic of the system that has wide reaching effects on disk evolution and planet formation. In this study, we constrain the 2D thermal structure of the protoplanetary disk TW Hya structure utilizing images of seven CO lines. This includes new ALMA observations of 12CO J=2-1 and C18O J=2-1

Soumak Maitra, Raghunathan Srianand, Prakash Gaikwad, Nishikanta Khandai

The Ly$\alpha$ forest decomposed into Voigt profile components allow us to study clustering properties of the intergalactic medium and its dependence on various physical quantities. Here, we report the first detections of probability excess of low-z (i.e z<0.48) Ly$\alpha$ absorber triplets over a scale of $r_\parallel\leq8$pMpc with a maximum amplitude of $

Christopher Wilson, Rachel Bean

We study the impact of cosmological scale modifications to General Relativity on the dynamics of halos within voids by comparing N-body simulations incorporating Hu-Sawicki $f(R)$ gravity, with $|f_{R0}|=10^{-6}$ and $10^{-5}$, to those of $\Lambda$CDM. By examining the radial velocity statistics within voids classified based on their size and density-profil

Donovan Buterakos, Sankar Das Sarma

Charge noise remains the primary obstacle to the development of quantum information technologies with semiconductor spin qubits. We use an exact analytical calculation to determine the effects of quasistatic charge noise on a ring of three equally spaced exchange-coupled quantum dots. We calculate the disorder-averaged return probability from a specific init

Christoph Berke, Evangelos Varvelis, Simon Trebst, Alexander Altland

From the perspective of many body physics, the transmon qubit architectures currently developed for quantum computing are systems of coupled nonlinear quantum resonators. A significant amount of intentional frequency detuning (disorder) is required to protect individual qubit states against the destabilizing effects of nonlinear resonator coupling. Here we i

Laura M. Harbach, Sofia P. Moschou, Cecilia Garraffo, Jeremy J. Drake

Stellar wind and photon radiation interactions with a planet can cause atmospheric depletion, which may have a potentially catastrophic impact on a planet's habitability. While the implications of photoevaporation on atmospheric erosion have been researched to some degree, studies of the influence of the stellar wind on atmospheric loss are in their infancy.

Fabrizio Canfora, Stefano Carignano, Marcela Lagos, Massimo Mannarelli

We construct analytic (3+1)-dimensional inhomogeneous and topologically non-trivial pion systems using chiral perturbation theory. We discuss the effect of isospin asymmetry with vanishing electromagnetic interactions as well as some particular configurations with non-vanishing electromagnetic interactions. The inhomogeneous configurations of the pion fields

B. King

Nonlinear Compton scattering is calculated for the collision of an electron with a plane wave pulse. A mid infra-red (IR) peak arises in the photon spectrum due to long-range interference associated with the pulse envelope. The case of a flat-top pulse is studied as a toy model for pulse envelope effects and reduced to two final-state momentum integrations;

Robin G. Tress, Mattia C. Sormani, Rowan J. Smith, Simon C. O. Glover

To investigate how molecular clouds react to different environmental conditions at a galactic scale, we present a catalogue of giant molecular clouds resolved down to masses of $\sim 10$~M$_{\odot}$ from a simulation of the entire disc of an interacting M51-like galaxy and a comparable isolated galaxy. Our model includes time-dependent gas chemistry, sink pa

Matthias Heller, Andreas von Manteuffel, Robert M. Schabinger, Hubert Spiesberger

We perform a dedicated study of the $q \bar{q}$-initiated two-loop electroweak-QCD Drell-Yan scattering amplitude in dimensional regularization schemes for vanishing light quark and lepton masses. For the relative order $\alpha$ and $\alpha_s$ one-loop Standard Model corrections, details of our comparison to the original literature are given. The infrared po

Zhaopeng Guo, Dayu Yan, Haohao Sheng, Simin Nie

Quantum spin Hall (QSH) effect with great promise for the potential application in spintronics and quantum computing has attracted extensive research interest from both theoretical and experimental researchers. Here, we predict monolayer Ta$_2$Pd$_3$Te$_5$ can be a QSH insulator based on first-principles calculations. The interlayer binding energy in the lay

Xiaomeng Liu, J. I. A. Li, Kenji Watanabe, Takashi Taniguchi

In fermionic systems, superconductivity and superfluidity are enabled through the condensation of fermion pairs. The nature of this condensate can be tuned by varying the pairing strength, with weak coupling yielding a BCS-like condensate and strong coupling resulting in a BEC-like process. However, demonstration of this cross-over has remained elusive in el

Eslam Khalaf, Patrick Ledwith, Ashvin Vishwanath

When two graphene sheets are twisted relative to each other by a small angle, enhanced correlations lead to superconductivity whose origin remains under debate. Here, we derive some general constraints on superconductivity in twisted bilayer graphene (TBG), independent of its underlying mechanism. Neglecting weak coupling between valleys, the global symmetry

Chen Gao, Yichang Shih, Wei-Sheng Lai, Chia-Kai Liang

We present a method for estimating Neural Radiance Fields (NeRF) from a single headshot portrait. While NeRF has demonstrated high-quality view synthesis, it requires multiple images of static scenes and thus impractical for casual captures and moving subjects. In this work, we propose to pretrain the weights of a multilayer perceptron (MLP), which implicitl

Atsushi Ono, Sumio Ishihara

Antiferromagnets exhibit distinctive characteristics such as ultrafast dynamics and robustness against perturbative fields, thereby attracting considerable interest in fundamental physics and technological applications. Recently, it was revealed that the N\'eel vector can be switched by a current-induced staggered (N\'eel) spin-orbit torque in antiferromagne

Johannes Kopf, Xuejian Rong, Jia-Bin Huang

We present an algorithm for estimating consistent dense depth maps and camera poses from a monocular video. We integrate a learning-based depth prior, in the form of a convolutional neural network trained for single-image depth estimation, with geometric optimization, to estimate a smooth camera trajectory as well as detailed and stable depth reconstruction.

Dillon Brout, Samuel Hinton, Daniel Scolnic

Recent cosmological analyses (e.g., JLA, Pantheon) of Type Ia Supernova (SNIa) have propagated systematic uncertainties into a covariance matrix and either binned or smoothed the systematic vectors in redshift space. We demonstrate that systematic error budgets of these analyses can be improved by a factor of $\sim1.5\times$ with the use of unbinned and unsm

Yaojia Wang, Shuoying Yang, Pranava K. Sivakumar, Brenden R. Ortiz

Materials with transition metals in triangular lattices are of great interest for their potential combination of strong correlation, exotic magnetism and electronic topology. Kagome nets are of particular importance since the discovery of geometrically frustrated magnetism and topological band structures in crystals like Herbertsmithite and Fe3Sn2, respectiv

Andrew Nemec, Andreas Klappenecker

We show how to construct hybrid quantum-classical codes from subsystem codes by encoding the classical information into the gauge qudits using gauge fixing. Unlike previous work on hybrid codes, we allow for two separate minimum distances, one for the quantum information and one for the classical information. We give an explicit construction of hybrid codes

Mengye Ren, Eleni Triantafillou, Kuan-Chieh Wang, James Lucas

Despite impressive progress in deep learning, generalizing far beyond the training distribution is an important open challenge. In this work, we consider few-shot classification, and aim to shed light on what makes some novel classes easier to learn than others, and what types of learned representations generalize better. To this end, we define a new paradig

Sharada Mohanty, Erik Nygren, Florian Laurent, Manuel Schneider

Efficient automated scheduling of trains remains a major challenge for modern railway systems. The underlying vehicle rescheduling problem (VRSP) has been a major focus of Operations Research (OR) since decades. Traditional approaches use complex simulators to study VRSP, where experimenting with a broad range of novel ideas is time consuming and has a huge

Yuzhe Xiao, Chenghao Wan, Jad Salman, Ian J. Maywar

All spectrometers rely on some mechanism to achieve spectral selectivity; common examples include gratings, prisms, and interferometers with moving mirrors. We experimentally demonstrated and validated a spectroscopic technique -- here dubbed Planck spectroscopy -- that measures the spectral emissivity of a surface using only a temperature-controlled stage a

Hong-Jian He, Yu-Chen Wang, Jiaming Zheng

We propose a new candidate of GeV scale inelastic dark matter (DM). Our construction has an anomaly-free $U(1)_X^{}$ gauge group with dark photon mediator, and can realize either scalar or fermionic inelastic DM. It is highly predictive and testable. We study the scattering rate of light inelastic DM with electrons in the XENON1T experiment and with nuclei i

Daisuke Kawata, Junichi Baba, Jason A. S. Hunt, Ralph Schönrich

Using a numerical simulation of an isolated barred disc galaxy, we first demonstrate that the resonances of the inner bar structure induce more prominent features in the action space distribution for the kinematically hotter stars, which are less sensitive to the local perturbation, such as the transient spiral arms. Then, we analyse the action distribution

Niko Zielinski, Sebastian Wolf, Robert Brunngräber

Thanks to their well-defined shape and mostly isolated locations, Bok globules are suitable objects for studying the physics of low-mass star formation. To study the magnetic field of the prototypical Bok globule B335, we obtained a spatially resolved polarization map with SOFIA/HAWC+ at a wavelength of 214$\,\mu$m. For the first time, these observations rev

Grigorios Fournodavlos, Igor Rodnianski, Jared Speck

For $(t,x) \in (0,\infty)\times\mathbb{T}^D$, the generalized Kasner solutions are a family of explicit solutions to various Einstein-matter systems that start out smooth but then develop a Big Bang singularity as $t \downarrow 0$, i.e., curvature blowup along a spacelike hypersurface. The family is parameterized by the Kasner exponents $\widetilde{q}_1,\cdo

Alejandro Díaz-Caro, Octavio Malherbe

In a recent paper, a realizability technique has been used to give a semantics of a quantum lambda calculus. Such a technique gives rise to an infinite number of valid typing rules, without giving preference to any subset of those. In this paper, we introduce a valid subset of typing rules, defining an expressive enough quantum calculus. Then, we propose a c

Paolo Piergentili, Wenlin Li, Riccardo Natali, David Vitali

We establish a method for the determination of the single-photon optomechanical coupling rate, which characterizes the radiation pressure interaction in an optomechanical system. The estimation of the rate with which a mechanical oscillator, initially in a thermal state, undergoes a Hopf bifurcation, and reaches a limit cycle, allows us to determine the sing

Jan-Frederik Mennemann, Igor E. Mazets, Marine Pigneur, Hans Peter Stimming

We present a detailed analysis of the relaxation dynamics in an extended bosonic Josephson junction. We show that stochastic classical field simulations using Gross-Pitaevskii equations in three spatial dimensions reproduce the main experimental findings of M. Pigneur et al., Phys. Rev. Lett. 120, 173601 (2018). We give an analytic solution describing the sh