January 2022 arXiv papers — page 53

Oliver Friedrich, Ashmeet Singh, Olivier Doré

The holographic principle suggests that the Hilbert space of quantum gravity is locally finite-dimensional. Motivated by this point-of-view, and its application to the observable Universe, we introduce a set of numerical and conceptual tools to describe scalar fields with finite-dimensional Hilbert spaces, and to study their behaviour in expanding cosmologic

Patrick M. Lenggenhager, Xiaoxiong Liu, Titus Neupert, Tomáš Bzdušek

We analyze triply degenerate nodal points [or triple points (TPs) for short] in energy bands of crystalline solids. Specifically, we focus on spinless band structures, i.e., when spin-orbit coupling is negligible, and consider TPs formed along high-symmetry lines in the momentum space by a crossing of three bands transforming according to a 1D and a 2D irred

S. Bailey, L. A. Harland-Lang

We present a new calculation of $W^+ W^-$ production in the semi-exclusive channel, that is either with intact outgoing protons or rapidity gaps present in the final state, and with no colour flow between the colliding protons. This study provides the first complete prediction of the $W^+ W^-$ semi-exclusive cross section, as well as the breakdown between el

Miguel Frías-Pérez, Mari Carmen Bañuls

The transverse folding algorithm [Phys. Rev. Lett. 102, 240603] is a tensor network method to compute time-dependent local observables in out-of-equilibrium quantum spin chains that can sometimes overcome the limitations of matrix product states. We present a contraction strategy that makes use of the exact light cone structure of the tensor network represen

Markus A. Ebert, Stella T. Schindler, Iain W. Stewart, Yong Zhao

Transverse-momentum-dependent parton distribution functions (TMDs) can be studied from first principles by a perturbative matching onto lattice-calculable quantities: so-called lattice TMDs, which are a class of equal-time correlators that includes quasi-TMDs and TMDs in the Lorentz-invariant approach. We introduce a general correlator that includes as speci

Samuel Brieden, Héctor Gil-Marín, Licia Verde

The ShapeFit compression method has been shown to be a powerful tool to gain cosmological information from galaxy power spectra in an effective, model-independent way. Here we present its performance on the blind PT challenge mock products presented in [1]. Choosing a set-up similar to that of other participants to the blind challenge we obtained $\Delta \ln

Bin Liu, Dong Lai

We study the long-term orbital evolution of stars around a merging massive or supermassive black-hole (BH) binary, taking into account the general relativistic effect induced by the BH spin. When the BH spin is significant compared to and misaligned with the binary orbital angular momentum, the orbital axis ($\hat{\mathbf{l}}$) of the circumbinary star can u

T. Somboonpanyakul, M. McDonald, A. Noble, M. Aguena

We present the results of an analysis of Wide-field Infrared Survey Explorer (WISE) observations on the full 2500 deg^2 South Pole Telescope (SPT)-SZ cluster sample. We describe a process for identifying active galactic nuclei (AGN) in brightest cluster galaxies (BCGs) based on WISE mid-infrared color and redshift. Applying this technique to the BCGs of the

Elisa Bortolas

A tidal disruption event (TDE) occurs when a star is destroyed by the strong tidal shear of a massive black hole (MBH). The accumulation of TDE observations over the last years has revealed that post-starburst galaxies are significantly overrepresented in the sample of TDE hosts. Here we address the post-starburst preference by investigating the decline of T

Zachary Schutte, Amy Reines

Black hole driven outflows have been observed in some dwarf galaxies with active galactic nuclei (1), and likely play a role in heating and expelling gas (thereby suppressing star formation), as they do in larger galaxies (2). The extent to which black hole outflows can trigger star formation in dwarf galaxies is unclear, because work in this area has hither

Netta Engelhardt, Åsmund Folkestad

We show that the canonical purification of an evaporating black hole after the Page time consists of a short, connected, Lorentzian wormhole between two asymptotic boundaries, one of which is unitarily related to the radiation. This provides a quantitative and general realization of the predictions of ER=EPR in an evaporating black hole after the Page time;

Louise Welsh, Ryan Cooke, Michele Fumagalli, Max Pettini

We present precise abundance determinations of two near-pristine damped Ly$\alpha$ systems (DLAs) to assess the nature of the [O/Fe] ratio at [Fe/H] < -3 (i.e. <1/1000 of the solar metallicity). Prior observations indicate that the [O/Fe] ratio is consistent with a constant value, [O/Fe] ~ +0.4, when -3 < [Fe/H] < -2, but this ratio may increase when [Fe/H]

Jack Holguin, Ian Moult, Aditya Pathak, Massimiliano Procura

Final states in collider experiments are characterized by correlation functions, $\langle E(\vec n_1) \cdots E(\vec n_k) \rangle$, of the energy flow operator $ E(\vec n_i)$. We show that the top quark imprints itself as a peak in the three-point correlator at an angle $\zeta \sim m_t^2/p_T^2$, with $m_t$ the top quark mass and $p_T$ its transverse momentum,

Chao-Yuan Wu, Yanghao Li, Karttikeya Mangalam, Haoqi Fan

While today's video recognition systems parse snapshots or short clips accurately, they cannot connect the dots and reason across a longer range of time yet. Most existing video architectures can only process <5 seconds of a video without hitting the computation or memory bottlenecks. In this paper, we propose a new strategy to overcome this challenge. Inste

Tsung-Cheng Lu, En-Jui Kuo, Hung-Hwa Lin

The notion of entanglement has been useful for characterizing universal properties of quantum phases of matter. From the perspective of quantum information theory, it is tempting to ask whether their entanglement structures possess any operational meanings, e.g., quantifying the cost of preparing an entangled system via free operations such as the local oper

A. E. Watkins, H. Salo, E. Laurikainen, S. Díaz-García

The Spitzer Survey of Stellar Structure in Galaxies (S$^{4}$G) is a detailed study of over 2300 nearby galaxies in the near-infrared (NIR), which has been critical to our understanding of the detailed structures of nearby galaxies. Because the sample galaxies were selected only using radio-derived velocities, however, the survey favored late-type disk galaxi

Daniel Harlow, Ben Heidenreich, Matthew Reece, Tom Rudelius

The Weak Gravity Conjecture holds that in a theory of quantum gravity, any gauge force must mediate interactions stronger than gravity for some particles. This statement has surprisingly deep and extensive connections to many different areas of physics and mathematics. Several variations on the basic conjecture have been proposed, including statements that a

Zhangxing Bian, Allan Jabri, Alexei A. Efros, Andrew Owens

A range of video modeling tasks, from optical flow to multiple object tracking, share the same fundamental challenge: establishing space-time correspondence. Yet, approaches that dominate each space differ. We take a step towards bridging this gap by extending the recent contrastive random walk formulation to much denser, pixel-level space-time graphs. The m

Ruslan Nikolaev, Hassan Nadeem, Cathlyn Stone, Binoy Ravindran

While address space layout randomization (ASLR) has been extensively studied for user-space programs, the corresponding OS kernel's KASLR support remains very limited, making the kernel vulnerable to just-in-time (JIT) return-oriented programming (ROP) attacks. Furthermore, commodity OSs such as Linux restrict their KASLR range to 32 bits due to architectura

Rohit Girdhar, Mannat Singh, Nikhila Ravi, Laurens van der Maaten

Prior work has studied different visual modalities in isolation and developed separate architectures for recognition of images, videos, and 3D data. Instead, in this paper, we propose a single model which excels at classifying images, videos, and single-view 3D data using exactly the same model parameters. Our 'Omnivore' model leverages the flexibility of tr

Angela Aguglia, Bence Csajbók, Zsuzsa Weiner

Let $U$ be a set of polynomials of degree at most $k$ over $\mathbb{F}_q$, the finite field of $q$ elements. Assume that $U$ is an intersecting family, that is, the graphs of any two of the polynomials in $U$ share a common point. Adriaensen proved that the size of $U$ is at most $q^k$ with equality if and only if $U$ is the set of all polynomials of degree

Andrew Lobban, Andrew King

Accretion disc theory predicts that an AGN disc becomes self-gravitating and breaks up into stars at an outer radius $R_{\rm sg}$ ~ 12 light-days, with effectively no free parameter. We present evidence that the longer observed AGN light echoes are all close to 12d in the AGN rest frames. These observations give a stringent test of AGN disc theory. Further m

A. S. Johnson, D. Moreno-Mencía, E. B. Amuah, M. Menghini

In solids, the response of the lattice to photo-excitation is often described by the inertial evolution on an impulsively modified potential energy surface which leads to coherent motion. However, it remains unknown if vibrational coherence is sustained through a phase transition, during which coupling between modes can be strong and may lead to rapid loss o

Arnav Kapoor, Dipanwita Guhathakurta, Mehul Mathur, Rupanshu Yadav

NFT or Non-Fungible Token is a token that certifies a digital asset to be unique. A wide range of assets including, digital art, music, tweets, memes, are being sold as NFTs. NFT-related content has been widely shared on social media sites such as Twitter. We aim to understand the dominant factors that influence NFT asset valuation. Towards this objective, w

Michele Del Zotto, Jonathan J. Heckman, Shani Nadir Meynet, Robert Moscrop

We determine the higher symmetries of 5d SCFTs engineered from M-theory on a $\mathbb{C}^3 / \Gamma$ background for $\Gamma$ a finite subgroup of $SU(3)$. This resolves a longstanding question as to how to extract this data when the resulting singularity is non-toric (when $\Gamma$ is non-abelian) and/or not isolated (when the action of $\Gamma$ has fixed lo

Mannat Singh, Laura Gustafson, Aaron Adcock, Vinicius de Freitas Reis

Model pre-training is a cornerstone of modern visual recognition systems. Although fully supervised pre-training on datasets like ImageNet is still the de-facto standard, recent studies suggest that large-scale weakly supervised pre-training can outperform fully supervised approaches. This paper revisits weakly-supervised pre-training of models using hashtag

Ian Wong, Avi Shporer, Shreyas Vissapragada, Michael Greklek-McKeon

After observing WASP-12 in the second year of the primary mission, the Transiting Exoplanet Survey Satellite (TESS) revisited the system in late 2021 during its extended mission. In this paper, we incorporate the new TESS photometry into a reanalysis of the transits, secondary eclipses, and phase curve. We also present a new $K_s$-band occultation observatio

Tim D. Pearce, Ralf Launhardt, Robert Ostermann, Grant M. Kennedy

We know little about the outermost exoplanets in planetary systems, because our detection methods are insensitive to moderate-mass planets on wide orbits. However, debris discs can probe the outer-planet population, because dynamical modelling of observed discs can reveal properties of perturbing planets. We use four sculpting and stirring arguments to infer

Lloyd Montgomery, Clara Lüders, Walid Maalej

Organisations use issue tracking systems (ITSs) to track and document their projects' work in units called issues. This style of documentation encourages evolutionary refinement, as each issue can be independently improved, commented on, linked to other issues, and progressed through the organisational workflow. Commonly studied ITSs so far include GitHub, G

K. U. Can, A. Hannaford-Gunn, R. Horsley, Y. Nakamura

A major objective of lattice QCD is the computation of hadronic matrix elements. The standard method is to use three-point and four-point correlation functions. An alternative approach, requiring only the computation of two-point correlation functions is to use the Feynman-Hellmann theorem. In this talk we develop this method up to second order in perturbati

Stephan Martin

Nonparametric random coefficient (RC)-density estimation has mostly been considered in the marginal density case under strict independence of RCs and covariates. This paper deals with the estimation of RC-densities conditional on a (large-dimensional) set of control variables using machine learning techniques. The conditional RC-density allows to disentangle

Melih Bastopcu, S. Rasoul Etesami, Tamer Başar

We consider information dissemination over a network of gossiping agents (nodes). In this model, a source keeps the most up-to-date information about a time-varying binary state of the world, and $n$ receiver nodes want to follow the information at the source as accurately as possible. When the information at the source changes, the source first sends update

Alexandre Borovik, Zoltan Kocsis, Vladimir Kondratiev

Mathematics enters the period of change unprecedented in its history, perhaps even a revolution: a switch to use of computers as assistants and checkers in production of proofs. This requires rethinking traditional approaches to mathematics education which is struggling through a crisis of its own, socio-economic and political by its nature. The mathematical

Rajat Arora, Pratik Kakkar, Biswadip Dey, Amit Chakraborty

This work presents a physics-informed neural network (PINN) based framework to model the strain-rate and temperature dependence of the deformation fields in elastic-viscoplastic solids. To avoid unbalanced back-propagated gradients during training, the proposed framework uses a simple strategy with no added computational complexity for selecting scalar weigh

Matthias Eckardt, Jorge Mateu, Sonja Greven

We extend the generalised functional additive mixed model to include (functional) compositional covariates carrying relative information of a whole. Relying on the isometric isomorphism of the Bayes Hilbert space of probability densities with a subspace of the $L^2$, we include functional compositions as transformed functional covariates with constrained eff

Rotem Tzaban, Ron Mokady, Rinon Gal, Amit H. Bermano

The ability of Generative Adversarial Networks to encode rich semantics within their latent space has been widely adopted for facial image editing. However, replicating their success with videos has proven challenging. Sets of high-quality facial videos are lacking, and working with videos introduces a fundamental barrier to overcome - temporal coherency. We

Ryan Tanner, Kimberly Weaver

Using a series of 3D relativistic hydrodynamical simulations of active galactic nuclei (AGN) we investigate how AGN power, a clumpy ISM structure, and AGN jet angle with respect to the galactic disk affect the morphology and content of the resulting galactic outflow. For low power AGN across three orders of magnitude of AGN luminosities ($10^{41}-10^{43}$ er

Sukrit Ranjan, Sara Seager, Zhuchang Zhan, Daniel D. B. Koll

About 2.5 billion years ago, microbes learned to harness plentiful solar energy to reduce CO$_2$ with H$_2$O, extracting energy and producing O$_2$ as waste. O$_2$ production from this metabolic process was so vigorous that it saturated its photochemical sinks, permitting it to reach "runaway" conditions and rapidly accumulate in the atmosphere despite its r

Antonela Taverna, Eugenia Diaz-Gimenez, Ariel Zandivarez, Gary Mamon

Many catalogues of isolated compact groups of galaxies (CGs) have been extracted using Hickson's criteria to identify isolated, dense systems of galaxies, with at least three or four galaxies concordant in magnitude and redshift. But is not clear to what extent the catalogues of CGs are complete and reliable, relative to 3D truly isolated, dense groups. Usin

Keun Sup Shim, Brian Greskamp, Brian Towles, Bruce Edwards

Molecular dynamics (MD) simulation, a computationally intensive method that provides invaluable insights into the behavior of biomolecules, typically requires large-scale parallelization. Implementation of fast parallel MD simulation demands both high bandwidth and low latency for inter-node communication, but in current semiconductor technology, neither of

P. M. A van Ooijen, Erfan Darzidehkalani, Andre Dekker

Artificial intelligence (AI), especially deep learning, requires vast amounts of data for training, testing, and validation. Collecting these data and the corresponding annotations requires the implementation of imaging biobanks that provide access to these data in a standardized way. This requires careful design and implementation based on the current stand

Kai-Chieh Hsu, Allen Z. Ren, Duy Phuong Nguyen, Anirudha Majumdar

Safety is a critical component of autonomous systems and remains a challenge for learning-based policies to be utilized in the real world. In particular, policies learned using reinforcement learning often fail to generalize to novel environments due to unsafe behavior. In this paper, we propose Sim-to-Lab-to-Real to bridge the reality gap with a probabilist

Antti Kuusisto

We investigate the expressive power of a Turing-complete logic based on game-theoretic semantics. By defining suitable fragments and variants of the logic, we obtain a range of natural characterizations for some fundamental families of model classes.

James M Parks

In this paper we continue the investigation of finding the max/min polygons which can be inscribed in a given triangle. Here we are concerned with equilateral triangles. This may seem uninteresting or benign at first, but there are some surprises later.

Ke Yue, Schwarz Nicholas, Tischler Jonathan Z

The Laue diffraction microscopy experiment uses the polychromatic Laue micro-diffraction technique to examine the structure of materials with sub-micron spatial resolution in all three dimensions. During this experiment, local crystallographic orientations, orientation gradients and strains are measured as properties which will be recorded in HDF5 image form

Hee-Joong Chung

We calculate homological blocks for a knot in Seifert manifolds when the gauge group is $SU(N)$. We obtain the homological blocks with a given representation of the gauge group from the expectation value of the Wilson loop operator by analytically continuing the Chern-Simons level. We also obtain homological blocks with the analytically continued level and r

Ben Van Dusen, Christoph Vogelsang, Joseph Taylor, Eva Cauet

Preparing future physics teachers for the demanding nature of their profession is an important and complex endeavor. Teacher education systems must provide a structure for the coherent professional development of prospective teachers. Worldwide, physics teacher education is organized in different ways, but have to face similar challenges, like the relation b

Gregory J. Gilbert

Grazing transits present a special problem for statistical studies of exoplanets. Even though grazing planetary orbits are rare (due to geometric selection effects), for many low to moderate signal-to-noise cases, a significant fraction of the posterior distribution is nonetheless consistent with a grazing geometry. A failure to accurately model grazing tran

Ye He, Krishnakumar Balasubramanian, Murat A. Erdogdu

We analyze the oracle complexity of sampling from polynomially decaying heavy-tailed target densities based on running the Unadjusted Langevin Algorithm on certain transformed versions of the target density. The specific class of closed-form transformation maps that we construct are shown to be diffeomorphisms, and are particularly suited for developing effi

Prathik R Kaundinya, Kamal Choudhary, Surya R. Kalidindi

Machine learning (ML) based models have greatly enhanced the traditional materials discovery and design pipeline. Specifically, in recent years, surrogate ML models for material property prediction have demonstrated success in predicting discrete scalar-valued target properties to within reasonable accuracy of their DFT-computed values. However, accurate pre

Rodrigo Avalos, Jorge Lira, Nicolas Marque

In this paper, we study the coupled Einstein constraint equations on complete manifolds through the conformal method, focusing on non-compact manifolds with flexible asymptotics. This is physically well-motivated by standard cosmological space-times with non-compact Cauchy hypersurfaces, which favour general bounded geometry manifolds rather than a specific

Haonan Zhang

Let $\mathbb{G}$ be a locally compact quantum group with dual $\widehat{\mathbb{G}}$. Suppose that the left Haar weight $\varphi$ and the dual left Haar weight $\widehat{\varphi}$ are tracial, e.g. $\mathbb{G}$ is a unimodular Kac algebra. We prove that for $1<p\le 2 \le q<\infty$, the Fourier multiplier $m_{x}$ is bounded from $L_p(\widehat{\mathbb{G}},\wid

Konstantinos N. Gourgouliatos, Davide De Grandis, Andrei Igoshev

Neutron stars host the strongest magnetic fields that we know of in the Universe. Their magnetic fields are the main means of generating their radiation, either magnetospheric or through the crust. Moreover, the evolution of the magnetic field has been intimately related to explosive events of magnetars, which host strong magnetic fields, and their persisten

Charles Brooker, Giuseppe Tronci

The tissue source of type I collagen is critical to ensure scalability and regulation-friendly clinical translation of new medical device prototypes. However, the selection of a commercial source of collagen that fulfils both aforementioned requirements and is compliant with new manufacturing routes is challenging. This study investigates the effect that typ

Dae Woong Ham, Kosuke Imai, Lucas Janson

Conjoint analysis is a popular experimental design used to measure multidimensional preferences. Researchers examine how varying a factor of interest, while controlling for other relevant factors, influences decision-making. Currently, there exist two methodological approaches to analyzing data from a conjoint experiment. The first focuses on estimating the

Charul Paliwal, Pravesh Biyani

Currently, fixed static sensing is a primary way to monitor environmental data like air quality in cities. However, to obtain a dense spatial coverage, a large number of static monitors are required, thereby making it a costly option. Dense spatiotemporal coverage can be achieved using only a fraction of static sensors by deploying them on the moving vehicle

Małgorzata Zinkiewicz, Magdalena Grzeszczyk, Łucja Kipczak, Tomasz Kazimierczuk

The dielectric environment of atomically-thin monolayer (ML) of semiconducting transition metal dichalcogenides affects both the electronic band gap and the excitonic binding energy in the ML. We investigate the effect of the environment on the in-plane magnetic field brightening of neutral and charged dark exciton emissions in the WSe$_2$ ML. The monolayers

Rafael Jurado, Gonzalo Arranz, Oscar Flores, Manuel García-Villalba

We report direct numerical simulations of a pair of wings in horizontal tandem configuration, to analyze the effect of their aspect ratio on the flow and the aerodynamic performance of the system. The wings are immersed in a uniform free-stream at Reynolds number Re = 1000, and they undergo heaving and pitching oscillation with Strouhal number St = 0.7. The

Xue Li, Alan Bundy, Eugene Philalithis

Human beliefs change, but so do the concepts that underpin them. The recent Abduction, Belief Revision and Conceptual Change (ABC) repair system combines several methods from automated theory repair to expand, contract, or reform logical structures representing conceptual knowledge in artificial agents. In this paper we focus on conceptual change: repair not

Héctor Suárez, Armando Reyes

In this paper, we introduce the concept of $\Sigma$-semicommutative ring, for $\Sigma$ a finite family of endomorphisms of a ring $R$. We relate this class of rings with other classes of rings such that Abelian, reduced, $\Sigma$-rigid, nil-reversible and rings satisfying the $\Sigma$-skew reflexive nilpotent property. Also, we study some ring-theoretical pr

Thomas Henzel, Chockalingam Senthilnathan, Tal Cohen

The reciprocal theorems of Maxwell and Betti are foundational in mechanics but have so far been restricted to infinitesimal deformations in elastic bodies. In this manuscript, we present a reciprocal theorem that relates solutions of a specific class of large deformation boundary value problems for incompressible bodies; these solutions are shown to identica

Derek Shank, Dante Komater, Timothy C. Beers, Vinicius M. Placco

Orbital characteristics based on Gaia Early Data Release 3 astrometric parameters are analyzed for ${\sim} 8,000$ metal-poor stars ([Fe/H] $\leq -0.8$) compiled from the RAdial Velocity Experiment (RAVE) Data Release 6. Selected as metal-poor candidates based on broadband photometry, RAVE collected moderate-resolution ($R \sim 7,500$) spectra in the region o

Md. Rafiul Biswas, Hazrat Ali, Raian Ali, Zubair Shah

Background: Vaccination programs are effective only when a significant percentage of people are vaccinated. However, vaccine acceptance varies among communities around the world. Social media usage is arguably one of the factors affecting public attitudes towards vaccines. Objective: This study aims to identify if the social media usages factors can be used

Michael S. Medford, Natasha S. Abrams, Jessica R. Lu, Peter Nugent

Microlensing events have historically been discovered throughout the Galactic bulge and plane by surveys designed solely for that purpose. We conduct the first multi-year search for microlensing events on the Zwicky Transient Facility (ZTF), an all-sky optical synoptic survey that observes the entire visible Northern sky every few nights. We discover 60 high

V. D. Zaporozhets, Y. Oba, A. Michels, K. L. Metlov

Micromagnetic small-angle neutron scattering theory is well established for analyzing spin-misalignment scattering data of bulk ferromagnets. Here, this theory is extended to allow for a global uniaxial magnetic anisotropy (texture) of the material, in addition to the already included random zero-average local anisotropy. Macroscopic cross-sections and spin-

Nikita Nemkov, Vassili Fedotov

The time derivative of the charge density is linked to the current density by the continuity equation. However, it features only the longitudinal part of a current density, which is known to produce no radiation. This fact usually remains unnoticed though it poses a seemingly serious paradox, suggesting that the temporal variation of a charge density should

Robert Powel, B. Alex Brown, Jason D. Holt, Andrew Klose

The hyperfine coupling constants of the proton dripline odd-odd $^{40}$Sc nucleus were deduced from the hyperfine spectrum of the $3d4s\,^3\text{D}_2$\,$\leftrightarrow$\,$3d4p\,^3\text{F}^\circ_3$ transition in Sc II, measured by the bunched beam collinear laser spectroscopy technique. The ground state magnetic dipole and electric quadrupole moments were de

Young-Gwan Choi, Manh-Ha Doan, Gyung-Min Choi, Maxim N. Chernodub

Recently, much interest has emerged in fluid-like electric charge transport in various solid-state systems. The hydrodynamic behavior of the electronic fluid reveals itself as a decrease of the electrical resistance with increasing temperature (the Gurzhi effect) in narrow conducting channels, polynomial scaling of the resistance as a function of the channel

Sumit R. Das, Shaun Hampton, Sinong Liu

We consider the entanglement entropy of an arbitrary subregion in a system of $N$ non-relativistic fermions in $2+1$ dimensions in Lowest Landau Level (LLL) states. Using the connection of these states to those of an auxiliary $1+1$ dimensional fermionic system, we derive an expression for the leading large-$N$ contribution in terms of the expectation value

Nicolas Vaskou

In this paper we solve the isomorphism problem for all large-type Artin groups. Our strategy involves reconstructing the Coxeter groups associated with large-type Artin groups in a purely algebraic way. This answers several questions raised by Charney. We also study 2-dimensional Artin groups in general. By classifying all their dihedral Artin subgroups, we

Marbarisha M. Kharkongor, Dipendu Maity

A tiling (edge-to-edge) of the plane is a family of tiles that cover the plane without gaps or overlaps. Vertex figure of a vertex in a tiling to be the union of all edges incident to that vertex. A tiling is $k$-vertex-homogeneous if any two vertices with congruent vertex figures are symmetric with each other and the vertices form precisely $k$ transitivity

G. Grätzer

Let $L$ be a slim, planar, semimodular lattice (slim means that it does not contain ${\mathsf M}_3$-sublattices). We call the interval $I = [o, i]$ of $L$ \emph{rectangular}, if there are $u_l, u_r \in [o, i] - \{o,i\}$ such that $o = u_l \wedge u_r$ and $i = u_l \vee u_r$, where $u_l$ is to the left of $u_r$. We prove that a rectangular interval of a rectan

Subhroshekhar Ghosh, Soumendu Sundar Mukherjee

Group or cluster structure on explanatory variables in machine learning problems is a very general phenomenon, which has attracted broad interest from practitioners and theoreticians alike. In this work we contribute an approach to learning under such group structure, that does not require prior information on the group identities. Our paradigm is motivated

Uzy Smilansky

The main purpose of the present paper is to introduce a scattering approach to the study of the Kronig-Penney model in a quadratic channel with $\delta$ interactions, which was discussed in full generality in the first paper of the present series. In particular, a secular equation whose zeros determine the spectrum will be written in terms of the scattering

W. Barreto, R. da Rocha

The gravitational instability of kinks is scrutinized in the context of information entropy, including the black hole formation near the scalar field critical collapse. The differential configurational entropy (DCE) is computed and examined for globally perturbed static kinks and the far-from-equilibrium kink solutions as well. In the case of the first kink,

E. Orozco-Acosta, A. Adin, M. D. Ugarte

Fitting spatio-temporal models for areal data is crucial in many fields such as cancer epidemiology. However, when data sets are very large, many issues arise. The main objective of this paper is to propose a general procedure to analyze high-dimensional spatio-temporal count data, with special emphasis on mortality/incidence relative risk estimation. We pre

Sisi Miao, Lukas Rapp, Laurent Schmalen

The decoding performance of product codes and staircase codes based on iterative bounded-distance decoding (iBDD) can be improved with the aid of a moderate amount of soft information, maintaining a low decoding complexity. One promising approach is error-and-erasure (EaE) decoding, whose performance can be reliably estimated with density evolution (DE). How

Taekyung Kim, Hojin Lee, Seongil Hong, Wonsuk Lee

Neural networks have been increasingly employed in Model Predictive Controller (MPC) to control nonlinear dynamic systems. However, MPC still poses a problem that an achievable update rate is insufficient to cope with model uncertainty and external disturbances. In this paper, we present a novel control scheme that can design an optimal tracking controller u

Max E. Lee, Tianhuan Lu, Zoltán Haiman, Jia Liu

Next-generation weak lensing (WL) surveys, such as by the Vera Rubin Observatory's LSST, the $\textit{Roman}$ Space Telescope, and the $\textit{Euclid}$ space mission, will supply vast amounts of data probing small, highly nonlinear scales. Extracting information from these scales requires higher-order statistics and the controlling of related systematics su

Matej Hoffmann, Matthew R. Longo

Neurocognitive models of higher-level somatosensory processing have emphasised the role of stored body representations in interpreting real-time sensory signals coming from the body (Longo, Azanon and Haggard, 2010; Tame, Azanon and Longo, 2019). The need for such stored representations arises from the fact that immediate sensory signals coming from the body

Anna Filighera, Sebastian Ochs, Tim Steuer, Thomas Tregel

Automatic grading models are valued for the time and effort saved during the instruction of large student bodies. Especially with the increasing digitization of education and interest in large-scale standardized testing, the popularity of automatic grading has risen to the point where commercial solutions are widely available and used. However, for short ans

Virendrasinh Kher, Raghav Chaturvedi, Nayneshkumar Devlani, A. K. Rai

The coulomb plus linear (Cornell) potential is used to investigate the mass spectrum of bottomonium. Gaussian wave function is used in position and momentum space to estimate values of potential and kinetic energies, respectively. Based on our calculations, we study newly observed ${{\mathit \Upsilon}{(10860)}}$ as an admixture of $4^{3}S_{1}$ with $4^{3}D_{

Thomas Staudt, Shayan Hundrieser, Axel Munk

Kantorovich potentials denote the dual solutions of the renowned optimal transportation problem. Uniqueness of these solutions is relevant from both a theoretical and an algorithmic point of view, and has recently emerged as a necessary condition for asymptotic results in the context of statistical and entropic optimal transport. In this work, we challenge t

Maxime Cauchois, Suyash Gupta, Alnur Ali, John Duchi

The expense of acquiring labels in large-scale statistical machine learning makes partially and weakly-labeled data attractive, though it is not always apparent how to leverage such data for model fitting or validation. We present a methodology to bridge the gap between partial supervision and validation, developing a conformal prediction framework to provid

Kun Song, Junwei Han, Gong Cheng, Jiwen Lu

In this paper, we reveal that metric learning would suffer from serious inseparable problem if without informative sample mining. Since the inseparable samples are often mixed with hard samples, current informative sample mining strategies used to deal with inseparable problem may bring up some side-effects, such as instability of objective function, etc. To

Nuwan Yapa, Sebastian König

We develop an extension of eigenvector continuation (EC) that makes it possible to extrapolate simulations of quantum systems in finite periodic boxes across large ranges of box sizes. The formal justification for this approach, which we call finite-volume eigenvector continuation (FVEC), is provided by matching periodic functions at different box sizes. As

Andy Jarnevic

Given a finitely generated subgroup $H$ of a finitely generated group $G$ and a non-principal ultrafilter $\omega$, we consider a natural subspace, $Cone^{\omega}_{G}(H)$, of the asymptotic cone of $G$ corresponding to $H$. Informally, this subspace consists of the points of the asymptotic cone of $G$ represented by elements of the ultrapower $H^{\omega}$. W

Yue Sheng, Alnur Ali

Acceleration and momentum are the de facto standard in modern applications of machine learning and optimization, yet the bulk of the work on implicit regularization focuses instead on unaccelerated methods. In this paper, we study the statistical risk of the iterates generated by Nesterov's accelerated gradient method and Polyak's heavy ball method, when app

Moiz Rauf, Sebastian Padó, Michael Pradel

Source code summarization is the task of generating a high-level natural language description for a segment of programming language code. Current neural models for the task differ in their architecture and the aspects of code they consider. In this paper, we show that three SOTA models for code summarization work well on largely disjoint subsets of a large c

Omar Alfarisi, Hongtao Zhang, Djamel Ouzzane, Hongxia Li

Researchers have used NMR to measure multi-phase fluid saturation and distribution inside porous media of natural rock. However, the NMR signal amplitude suffers reduction with the increase of temperature. The main reason is the Transverse Overhauser Effect, where heating increases the freedom for ionic motion, affecting spinning behavior by having two spins

Lin Lin

This is a set of lecture notes used in a graduate topic class in applied mathematics called ``Quantum Algorithms for Scientific Computation'' at the Department of Mathematics, UC Berkeley during the fall semester of 2021. These lecture notes focus only on quantum algorithms closely related to scientific computation, and in particular, matrix computation. The

Wen Shang, Vasilis Friderikos

In this paper, to address backhaul capacity bottleneck and concurrently optimize energy consumption and delay, we formulate a novel weighted-sum multi-objective optimization problem where popular content caching placement and integrated access and backhaul (IAB) millimeter (mmWave) bandwidth partitioning are optimized jointly to provide Pareto efficient opti

Charul Paliwal, Pravesh Biyani, Ketan Rajawat

Missing data is a common problem in real-world sensor data collection. The performance of various approaches to impute data degrade rapidly in the extreme scenarios of low data sampling and noisy sampling, a case present in many real-world problems in the field of traffic sensing and environment monitoring, etc. However, jointly exploiting the spatiotemporal

Amirmohammad Farzaneh, Justin P. Coon

A novel Markovian network evolution model is introduced and analysed by means of information theory. It will be proved that the model, called Network Evolution Chain, is a stationary and ergodic stochastic process. Therefore, the Asymptotic Equipartition Property can be applied to it. The model's entropy rate and typical sequences are also explored. Extracti

Zipeng Wang, Thomas Helfer, Katy Clough, Emanuele Berti

Superradiance is a process by which massive bosonic particles can extract energy from spinning black holes, leading to the build up of a "cloud" if the particle has a Compton wavelength comparable to the black hole's Schwarzschild radius. One interesting possibility is that superradiance may occur for photons in a diffuse plasma, where they gain a small effe

Afroditi Papadaki, Natalia Martinez, Martin Bertran, Guillermo Sapiro

Federated learning is an increasingly popular paradigm that enables a large number of entities to collaboratively learn better models. In this work, we study minimax group fairness in federated learning scenarios where different participating entities may only have access to a subset of the population groups during the training phase. We formally analyze how

D. B. Blaschke, V. V. Dmitriev, N. T. Gevorgyan, B. Mahato

The effective mass approximation is analysed in a nonperturbative kinetic theory approach to strong field excitations in graphene [1,2]. This problem is highly actual for the investigation of quantum radiation from graphene [3], where the collision integrals in the photon kinetic equation are rather complicated functionals of the distribution functions of th

Chengyuan Han, Dirk Witthaut, Leonardo Rydin Gorjão, Philipp C. Böttcher

Sustainable energy systems require flexible elements to balance the variability of renewable energy sources. Demand response aims to adapt the demand to the variable generation, in particular by shifting the load in time. In this article, we provide a detailed statistic analysis of the collective operation of many demand response units. We establish and simu

Chenyu Sun, Hangwei Qian, Chunyan Miao

Psychological curiosity plays a significant role in human intelligence to enhance learning through exploration and information acquisition. In the Artificial Intelligence (AI) community, artificial curiosity provides a natural intrinsic motivation for efficient learning as inspired by human cognitive development; meanwhile, it can bridge the existing gap bet

A. S. Agrawal, B. Mishra, P. H. R. S. Moraes

Wormholes are outstanding solutions of Einstein's General Relativity. They were worked out in the late 1980's by Morris and Thorne, who have figured out a recipe that wormholes must obey in order to be traversable, that is, safely crossed by travelers. A remarkable feature is that General Relativity Theory wormholes must be filled by {\it exotic matter}, whi