arXiv papers from November 2021

Paramanand Chandramouli, Hendrik Sommerhoff, Andreas Kolb

Inspired by the recent advances in implicitly representing signals with trained neural networks, we aim to learn a continuous representation for narrow-baseline 4D light fields. We propose an implicit representation model for 4D light fields which is conditioned on a sparse set of input views. Our model is trained to output the light field values for a conti

Muhammad Asaduzzaman, Simon Catterall, Jay Hubisz, Roice Nelson

Motivated by the AdS/CFT correspondence, we use Monte Carlo simulation to investigate the Ising model formulated on tessellations of the two-dimensional hyperbolic disk. We focus in particular on the behavior of boundary-boundary correlators, which exhibit power-law scaling both below and above the bulk critical temperature indicating scale invariance of the

Tiago P. Peixoto

Community detection is one of the most important methodological fields of network science, and one which has attracted a significant amount of attention over the past decades. This area deals with the automated division of a network into fundamental building blocks, with the objective of providing a summary of its large-scale structure. Despite its importanc

Qiushi Bai, Sadeem Alsudais, Chen Li, Shuang Zhao

We consider data-visualization systems where a middleware layer translates a frontend request to a SQL query to a backend database to compute visual results. We study the problem of answering a visualization request within a limited time constraint due to the responsiveness requirement. We explore the optimization options of rewriting an original query by ad

B. Pahlevanzadeh, P. Sahebsara, D. Sénéchal

We study the possibility of charge order at quarter filling and antiferromagnetism at half-filling in a tight-binding model of magic angle twisted bilayer graphene. We build on the model proposed by Kang and Vafek [Physical Review X 8(3), 031088 (2018)], relevant to a twist angle of $1.30^\circ$, and add on-site and extended density-density interactions. App

Jing Shi, Ning Xu, Haitian Zheng, Alex Smith

Recently, large pretrained models (e.g., BERT, StyleGAN, CLIP) have shown great knowledge transfer and generalization capability on various downstream tasks within their domains. Inspired by these efforts, in this paper we propose a unified model for open-domain image editing focusing on color and tone adjustment of open-domain images while keeping their ori

Fabian Falck, Yuyin Zhou, Emma Rocheteau, Liyue Shen

A collection of the accepted abstracts for the Machine Learning for Health (ML4H) symposium 2021. This index is not complete, as some accepted abstracts chose to opt-out of inclusion.

Michael te Vrugt

A long and intense debate in philosophy is concerned with the question whether there can be haecceistic differences between possible worlds, that is, nonqualitative differences that only arise from different de re representations. According to haecceitism, it can give rise to a different situation if the positions of two qualitatively identical particles are

Chavez-Caliz, Ana C

Motivated by a question from V. Arnold about self-dual curves in projective spaces, we study {\cal M}_{m,n,k}: the moduli space of m-self-dual n-gons in {\mathbb P}^k. This paper lays out an explicit construction of self-dual polygons, and for specific cases of n and m, provides the dimension of {\cal M}_{m,n,k}. We include a conjecture about the Pentagram m

Iván León, Diego Pazó

The emergence of collective synchrony from an incoherent state is a phenomenon essentially described by the Kuramoto model. This canonical model was derived perturbatively, by applying phase reduction to an ensemble of heterogeneous, globally coupled Stuart-Landau oscillators. This derivation neglects nonlinearities in the coupling constant. We show here tha

Katrin Gelfert, Maria Jose Pacifico, Diego Sanhueza

We derive sufficient conditions for a dynamical systems to have a set of irregular points with full topological entropy. Such conditions are verified for some nonuniformly hyperbolic systems such as positive entropy surface diffeomorphisms and rational functions on the Riemann sphere.

Julius Kunze, James Townsend, David Barber

We propose a new, more general approach to the design of stochastic gradient-based optimization methods for machine learning. In this new framework, optimizers assume access to a batch of gradient estimates per iteration, rather than a single estimate. This better reflects the information that is actually available in typical machine learning setups. To demo

Hiroyuki Tako Ishikawa, Wako Aoki, Teruyuki Hirano, Takayuki Kotani

Detailed chemical analyses of M dwarfs are scarce but necessary to constrain the formation environment and internal structure of planets being found around them. We present elemental abundances of 13 M dwarfs (2900 < Teff < 3500 K) observed in the Subaru/IRD planet search project. They are mid-to-late M dwarfs whose abundance of individual elements has not b

Kelly Van Lancker, Oliver Dukes, Stijn Vansteelandt

The problem of how to best select variables for confounding adjustment forms one of the key challenges in the evaluation of exposure effects in observational studies, and has been the subject of vigorous recent activity in causal inference. A major drawback of routine procedures is that there is no finite sample size at which they are guaranteed to deliver e

Ruisi Zhang, Youwei Liang, Sai Ashish Somayajula, Pengtao Xie

In differentiable neural architecture search (NAS) algorithms like DARTS, the training set used to update model weight and the validation set used to update model architectures are sampled from the same data distribution. Thus, the uncommon features in the dataset fail to receive enough attention during training. In this paper, instead of introducing more co

Alexander Montgomerie-Corcoran, Zhewen Yu, Christos-Savvas Bouganis

Significant effort has been placed on the development of toolflows that map Convolutional Neural Network (CNN) models to Field Programmable Gate Arrays (FPGAs) with the aim of automating the production of high performing designs for a diverse set of applications. However, within these toolflows, the problem of finding an optimal mapping is often overlooked,

Fangzhou Mu, Jian Wang, Yicheng Wu, Yin Li

Visual content creation has spurred a soaring interest given its applications in mobile photography and AR / VR. Style transfer and single-image 3D photography as two representative tasks have so far evolved independently. In this paper, we make a connection between the two, and address the challenging task of 3D photo stylization - generating stylized novel

David Harry Richman

In analogy with the Manin-Mumford conjecture for algebraic curves, one may ask how a metric graph under the Abel-Jacobi embedding intersects torsion points of its Jacobian. We show that the number of torsion points is finite for metric graphs of genus $g\geq 2$ which are biconnected and have edge lengths which are "sufficiently irrational" in a precise sense

Lei Sun, Christos Sakaridis, Jingyun Liang, Qi Jiang

Traditional frame-based cameras inevitably suffer from motion blur due to long exposure times. As a kind of bio-inspired camera, the event camera records the intensity changes in an asynchronous way with high temporal resolution, providing valid image degradation information within the exposure time. In this paper, we rethink the eventbased image deblurring

Suraj Kothawade, Saikat Ghosh, Sumit Shekhar, Yu Xiang

Deep neural networks based object detectors have shown great success in a variety of domains like autonomous vehicles, biomedical imaging, etc. It is known that their success depends on a large amount of data from the domain of interest. While deep models often perform well in terms of overall accuracy, they often struggle in performance on rare yet critical

Enrica Rossi, Marco Tognon, Luca Ballotta, Ruggero Carli

In this paper, we propose an inverse-kinematics controller for a class of multi-robot systems in the scenario of sampled communication. The goal is to make a group of robots perform trajectory tracking in a coordinated way when the sampling time of communications is much larger than the sampling time of low-level controllers, disrupting theoretical convergen

Nivedan Vishwanath, Aditya Karthik Saravanakumar, Kush Dwivedi, K. Ram Chandra Murthy

Tall buildings are often subjected to steady and unsteady forces due to external wind flows. Measurement and mitigation of these forces becomes critical to structural design in engineering applications. Over the last few decades, many approaches such as modification of the external geometry of structures have been investigated to mitigate wind-induced load.

Qianxia Wang, Uwe Titt, Radhe Mohan, Fada Guan

Methods: A phase space file in a plane at 202 mm downstream of the beam exit window is generated through tuning parameters to match FDC results with measured or MCNPX Monte Carlo-simulated integrated depth-dose distribution (IDD) and lateral dose profiles. To spread out the Bragg peak, widen the beam and reduce the penumbra, a ridge filter (RF), a high-Z mat

Edward D. White, Richard L. Warr

Students taking statistical courses orientated for business or economics often find the standard presentation of Bayes' Rule challenging. This key concept involves understanding multiple conditional probabilities and how they constitute an unconditional sample space. Many textbooks try to aid the comprehension of Bayes' Rule by illustrating these probabiliti

Sean Groathouse, Christopher Janjigian, Firas Rassoul-Agha

We show non-existence of non-trivial bi-infinite geodesics in the solvable last-passage percolation model with i.i.d. geometric weights. This gives the first example of a model with discrete weights where non-existence of non-trivial bi-infinite geodesics has been proven. Our proofs rely on the structure of the increment-stationary versions of the model, fol

Michael Färber, Anna Steyer

Argument search aims at identifying arguments in natural language texts. In the past, this task has been addressed by a combination of keyword search and argument identification on the sentence- or document-level. However, existing frameworks often address only specific components of argument search and do not address the following aspects: (1) argument-quer

Jacopo Borga

We recently introduced a new universal family of permutons, depending on two parameters, called skew Brownian permuton. For some specific choices of the parameters, the skew Brownian permuton coincides with some previously studied permutons: the biased Brownian separable permuton and the Baxter permuton. The latter two permutons are degenerate cases of the s

Sundararajan Srinivasan, Zhaocheng Huang, Katrin Kirchhoff

Generic pre-trained speech and text representations promise to reduce the need for large labeled datasets on specific speech and language tasks. However, it is not clear how to effectively adapt these representations for speech emotion recognition. Recent public benchmarks show the efficacy of several popular self-supervised speech representations for emotio

Yogesh S. S. Patil, Judith Höller, Parker A. Henry, Chitres Guria

Any system of coupled oscillators may be characterized by its spectrum of resonance frequencies (or eigenfrequencies), which can be tuned by varying the system's parameters. The relationship between control parameters and the eigenfrequency spectrum is central to a range of applications. However, fundamental aspects of this relationship remain poorly underst

Jacopo Borga

We construct a new family of random permutons, called skew Brownian permuton, which describes the limits of several models of random constrained permutations. This family is parametrized by two real parameters. For a specific choice of the parameters, the skew Brownian permuton coincides with the Baxter permuton, i.e., the permuton limit of Baxter permutatio

Philipp Kopp, Victor Calo, Ernst Rank, Stefan Kollmannsberger

The direct numerical simulation of metal additive manufacturing processes such as laser powder bed fusion is challenging due to the vast differences in spatial and temporal scales. Classical approaches based on locally refined finite elements combined with time-stepping schemes can only address the spatial multi-scale nature and provide only limited scaling

Santiago Guzmán-Pro, Pavol Hell, César Hernández-Cruz

Each hereditary property can be characterized by its set of minimal obstructions; these sets are often unknown, or known but infinite. By allowing extra structure it is sometimes possible to describe such properties by a finite set of forbidden objects. This has been studied most intensely when the extra structure is a linear ordering of the vertex set. For

Norman Christ, Xu Feng, Joseph Karpie, Tuan Nguyen

The relationship between finite volume multi-hadron energy levels and matrix elements and two particle scattering phase shifts and decays is well known, but the inclusion of long range interactions such as QED is non-trivial. Inclusion of QED is an important systematic error correction to $K\to\pi\pi$ decays. In this talk, we present a method of including a

Danny Nam, Allan Sly, Youngtak Sohn

Continuing our earlier work in \cite{nss20a}, we study the random regular k-NAE-SAT model in the condensation regime. In \cite{nss20a}, the 1RSB properties of the model were established with positive probability. In this paper, we improve the result to probability arbitrarily close to one. To do so, we introduce a new framework which is the synthesis of two

Yafeng Chen, Fei Meng, Zhihao Lan, Baohua Jia

Second-order photonic topological insulators that host highly localized corner states resilient to defects, are opening new routes towards developing fascinating photonic devices. However, the existing works on second-order photonic topological insulators have mainly focused on either transverse magnetic or transverse electric modes. In this paper, we propos

Yusuke Namekawa, Yuhma Asano, Yuta Ito, Takashi Kaneko

We discuss the flavor number dependence of QCD at low temperature and high density by the complex Langevin method. In our previous work, the complex Langevin method is confirmed to satisfy the criterion for correct convergence in certain regions, such as $\mu_{\rm q} / T = 5.2-7.2$ on $8^3 \times 16$ and $\mu_{\rm q} / T = 1.6-9.6$ on $16^3 \times 32$ using

Nathann T. Rodrigues, Jürgen F. Stilck, Tiago J. Oliveira

Although hard rigid rods ($k$-mers) defined on the square lattice have been widely studied in the literature, their entropy per site, $s(k)$, in the full-packing limit is only known exactly for dimers ($k=2$) and numerically for trimers ($k=3$). Here, we investigate this entropy for rods with $k \le 7$, by defining and solving them on Husimi lattices built w

Yafeng Chen, Zhihao Lan, Jensen Li, Jie Zhu

Topology-driven nonlinear light-matter effects open up new paradigms for both topological photonics and nonlinear optics. Here, we propose to achieve high-efficiency second-harmonic generation in a second-order photonic topological insulator. Such system hosts highly localized topological corner states with large quality factors for both fundamental and seco

Ali Esmaeily, Katina Kralevska, Toktam Mahmoodi

One of the most challenging services fifth-generation (5G) mobile network is designed to support, is the critical services in-need of very low latency, and/or high reliability. It is now clear that such critical services will also be at the core of beyond 5G (B5G) networks. While 5G radio design accommodates such supports by introducing more flexibility in t

D. Gadkari, K. S. Shanks, H. Hu, H. T. Philipp

We characterize a new x-ray Mixed-Mode Pixel Array Detector (MM-PAD-2.1) Application Specific Integrated Circuit (ASIC). Using an integrating pixel front-end with dynamic charge removal architecture, the MM-PAD-2.1 ASIC extends the maximum measurable x-ray signal (in 20 keV photon units) to > 10$^{7}$ x-rays/pixel/frame while maintaining a low read noise acr

Peyton T. Johnson, Michael W. Coughlin, Ashlie Hamilton, María José Bustamante-Rosell

The upcoming Laser Interferometer Space Antenna (LISA) will detect a large gravitational-wave foreground of Galactic white dwarf binaries. These sources are exceptional for their probable detection at electromagnetic wavelengths, some long before LISA flies. Studies in both gravitational and electromagnetic waves will yield strong constraints on system param

Lezier Geoffrey, Koleják Pierre, Lampin Jean-François, Postava Kamil

THz polarization control upon generation is a crucially missing functionality. THz spintronic emitters based on the inverse spin Hall effect allow for this by the strict implicit orthogonality between their magnetization state and the emitted polarization. This control was up till now only demonstrated using cumbersome external magnetic field biasing to impo

Farimasadat Miri, Richard Pazzi

In recent years, the number of IoT devices has been growing fast which leads to a challenging task for managing, storing, analyzing, and making decisions about raw data from different IoT devices, especially for delay-sensitive applications. In a vehicular network (VANET) environment, the dynamic nature of vehicles makes the current open research issues even

Yixuan Liu, Chrysafis Vogiatzis, Ruriko Yoshida, Erich Morman

Uncrewed autonomous vehicles (UAVs) have made significant contributions to reconnaissance and surveillance missions in past US military campaigns. As the prevalence of UAVs increases, there has also been improvements in counter-UAV technology that makes it difficult for them to successfully obtain valuable intelligence within an area of interest. Hence, it h

William Bains, Oliver Shorttle, Sukrit Ranjan, Paul B. Rimmer

The initial reports of the presence of phosphine in the cloud decks of Venus has led to the suggestion that volcanism was the source of phosphine, through volcanic phosphides ejected into the clouds. Here we examine the idea that mantle plume volcanism, bringing material from the deep mantle to the surface, could generate observed amounts of phosphine throug

Ridha jarray, Abir Hadriche, Cokri ben Amar, Nawel Jmail

The Electro-Encephalo-Graphy (EEG) technique consists of estimating the cortical distribution of signals over time of electrical activity and also of locating the zones of primary sensory projection. Moreover, it is able to record respectively the variations of potential and field magnetic waves generated by electrical activity in the brain every millisecond

P. Amaro, A. Adamczak, M. Abdou Ahmed, L. Affolter

The CREMA collaboration is pursuing a measurement of the ground-state hyperfine splitting (HFS) in muonic hydrogen ($\mu$p) with 1 ppm accuracy by means of pulsed laser spectroscopy to determine the two-photon-exchange contribution with $2\times10^{-4}$ relative accuracy. In the proposed experiment, the $\mu$p atom undergoes a laser excitation from the singl

Linda M. Carpenter, Matthew J. Smylie, Jesus Manuel Caridad Ramirez, Cameron McDowell

We present a study of the sensitivity to models of new physics of proton collisions resulting in three electroweak bosons. As a benchmark, we analyze models in which an exotic scalar field $\phi$ is produced in association with a gauge boson ($V=\gamma$ or $Z$). The scalar then decays to a pair of bosons, giving the process $pp\rightarrow \phi V\rightarrow V

I. Alekseev, M. Danilov, V. Rusinov, E. Samigullin

Wavelength shifting fibers are widely used for light collection from scintillation counters, which allow connection of various scintillation planes to relatively small photocathodes of photodetectors and especially tiny photocathodes of silicon photo-multipliers. In October 2020 Kuraray announced production of a new branch of faster fibers. We performed a co

Sihao Cheng, Brice Ménard

Extracting information from stochastic fields or textures is a ubiquitous task in science, from exploratory data analysis to classification and parameter estimation. From physics to biology, it tends to be done either through a power spectrum analysis, which is often too limited, or the use of convolutional neural networks (CNNs), which require large trainin

Jaime Burgos-Garcia, Abimael Bengochea, Luis Franco-Perez

In this work, we perform a first study of basic invariant sets of the spatial Hill's four-body problem, where we have used both analytical and numerical approaches. This system depends on a mass parameter mu in such a way that the classical Hill's problem is recovered when mu = 0. Regarding the numerical work, we perform a numerical continuation, for the Jac

Robert Lin

In this article, I introduce a group-theoretical method to prove positivity of certain linear combinations (with coefficients generally lying in $\mathbb{C}$) of exponential functions under a set of semidefinite linear constraints. The basic group-theoretic fact we rely on is the positivity of the fusion coefficients for multiplication of group characters.

Yichi Zhang, Zhiru Zhang, Lukasz Lew

Optimization of Top-1 ImageNet promotes enormous networks that may be impractical in inference settings. Binary neural networks (BNNs) have the potential to significantly lower the compute intensity but existing models suffer from low quality. To overcome this deficiency, we propose PokeConv, a binary convolution block which improves quality of BNNs by techn

Yuxin Chen, Benjamin Brock, Serban Porumbescu, Aydın Buluç

We present Atos, a task-parallel GPU dynamic scheduling framework that is especially suited to dynamic irregular applications. Compared to the dominant Bulk Synchronous Parallel (BSP) frameworks, Atos exposes additional concurrency by supporting task-parallel formulations of applications with relaxed dependencies, achieving higher GPU utilization, which is p

Mrinmoy Roy, Venkata Devesh Reddy Seethi, Rami Lake, Pratool Bharti

Worldwide 2019 million people have been infected and 4.5 million have lost their lives in the ongoing Covid-19 pandemic. Until vaccines became widely available, precautions and safety measures like wearing masks, physical distancing, avoiding face touching were some of the primary means to curb the spread of virus. Face touching is a compulsive human begavio

E. A. Kudryavtseva, A. A. Oshemkov

In this paper, we study singularities of the Lagrangian fibration given by a completely integrable system. We prove that a non-degenerate singular fibre satisfying the so-called connectedness condition is structurally stable under (small enough) real-analytic integrable perturbations of the system. In other words, the topology of the fibration in a neighbour

C. M. Baugh, C. G. Lacey, V. Gonzalez-Perez, G. Manzoni

We present a new model to compute the luminosity of emission lines in star forming galaxies and apply this in the semi-analytical galaxy formation code GALFORM. The model combines a pre-computed grid of HII region models with an empirical determination of how the properties of HII regions depend on the macroscopic properties of galaxies based on observations

Dalibor Djukanovic

The form factors of the nucleon provide key information on nucleon properties. When confronted with precisely measured observables from experiments, they serve as benchmark quantities for lattice calculations. On the other hand lattice determinations may serve as vital theory input for the interpretation of experiments, e.g. in neutrino-nucleus scattering. I

Dalibor Djukanovic, Georg von Hippel, Jonna Koponen, Harvey B. Meyer

We present the analysis of isovector axial vector nucleon form factors on a set of $N_f=2+1$ CLS ensembles with $\mathcal O(a)$-improved Wilson fermions and L\"uscher-Weisz gauge action. The set of ensembles covers a pion mass range of $130-353\,$MeV with lattice spacings between $0.05\,$fm and $0.09\,$fm. In particular, the set includes a $L/a=96$ ensemble

Petr Plechac, Gabriel Stoltz, Ting Wang

We introduce a new class of estimators for the linear response of steady states of stochastic dynamics. We generalize the likelihood ratio approach and formulate the linear response as a product of two martingales, hence the name "martingale product estimators". We present a systematic derivation of the martingale product estimator, and show how to construct

Gabriele Grillo, Giulia Meglioli, Fabio Punzo

It is well known from the work of [2] that the Fujita phenomenon for reaction-diffusion evolution equations with power nonlinearities does not occur on the hyperbolic space $\mathbb{H}^N$, thus marking a striking difference with the Euclidean situation. We show that, on classes of manifolds in which the bottom $\Lambda$ of the $L^2$ spectrum of $-\Delta$ is

Shamiul Alam, Md Mazharul Islam, Md Shafayat Hossain, Akhilesh Jaiswal

The scaling of the already-matured CMOS technology is steadily approaching its physical limit, motivating the quest for a suitable alternative. Cryogenic operation offers a promising pathway towards continued improvement in computing speed and energy efficiency without aggressive scaling. However, the memory wall bottleneck of the traditional von-Neumann arc

A. J. Bohn, M. Benisty, K. Perraut, N. van der Marel

For several transition disks (TDs), dark regions interpreted as shadows have been observed in scattered light imaging and are hypothesized to originate from misalignments between distinct disk regions. We aim to investigate the presence of misalignments in TDs. We study the inner disk geometries of 20 well-known transition disks with VLTI/GRAVITY observation

Chaohan Cui, Liang Zhang, Linran Fan

Kerr nonlinearity in nanophotonic cavities provides a versatile platform to explore fundamental physical sciences and develop novel photonic technologies. This is driven by the precise dispersion control and significant field enhancement with nanoscale structures. Beyond dispersion and pump engineering, the direct control of Kerr nonlinearity can release the

Connor L. Box, Wojciech G. Stark, Reinhard J. Maurer

Molecular motion at metallic surfaces is affected by nonadiabatic effects and electron-phonon coupling. The ensuing energy dissipation and dynamical steering effects are not captured by classical molecular dynamics simulations, but can be described with the molecular dynamics with electronic friction method and linear response calculations based on density f

Gabriel Acosta, Francisco Bersetche, Julio Rossi

We introduce two different ways of coupling local and nonlocal equations with Neumann boundary conditions in such a way that the resulting model is naturally associated with an energy functional. For these two models we prove that there is a minimizer of the resulting energy that is unique modulo adding a constant.

Ulises Pereira-Obilinovic, Johnatan Aljadeff, Nicolas Brunel

Attractor networks are an influential theory for memory storage in brain systems. This theory has recently been challenged by the observation of strong temporal variability in neuronal recordings during memory tasks. In this work, we study a sparsely connected attractor network where memories are learned according to a Hebbian synaptic plasticity rule. After

Othmane Bouhali, Kerstin Hoepfner, Francesco Ivone, Teruki Kamon

The Gas Electron Multiplier (GEM) foil is an amplification stage that has been introduced to overcome the problem of discharges observed in gaseous detectors. There are two major production techniques of GEM foils: double-mask and single-mask etching. Despite being an effective method, an asymmetry is observed between the top and bottom diameters of GEM hole

Gian Singh, Ankit Wagle, Sarma Vrudhula, Sunil Khatri

Numerous applications such as graph processing, cryptography, databases, bioinformatics, etc., involve the repeated evaluation of Boolean functions on large bit vectors. In-memory architectures which perform processing in memory (PIM) are tailored for such applications. This paper describes a different architecture for in-memory computation called CIDAN, tha

Natarajan Arul Murugan, Artur Podobas, Davide Gadioli, Emanuele Vitali

Drug discovery is the most expensive, time demanding and challenging project in biopharmaceutical companies which aims at the identification and optimization of lead compounds from large-sized chemical libraries. The lead compounds should have high affinity binding and specificity for a target associated with a disease and in addition they should have favora

Thomas Nakken Larsen, Amalie Heiberg, Eivind Meyer, Adil Rasheeda

Autonomous systems are becoming ubiquitous and gaining momentum within the marine sector. Since the electrification of transport is happening simultaneously, autonomous marine vessels can reduce environmental impact, lower costs, and increase efficiency. Although close monitoring is still required to ensure safety, the ultimate goal is full autonomy. One maj

Maxwell Nye, Anders Johan Andreassen, Guy Gur-Ari, Henryk Michalewski

Large pre-trained language models perform remarkably well on tasks that can be done "in one pass", such as generating realistic text or synthesizing computer programs. However, they struggle with tasks that require unbounded multi-step computation, such as adding integers or executing programs. Surprisingly, we find that these same models are able to perform

Shubhaankar Gupta, Thomas P. O'Connell, Bernhard Egger

Pre-training on large-scale databases consisting of natural images and then fine-tuning them to fit the application at hand, or transfer-learning, is a popular strategy in computer vision. However, Kataoka et al., 2020 introduced a technique to eliminate the need for natural images in supervised deep learning by proposing a novel synthetic, formula-based met

Atakan Topcu, Asli Alpman, Mustafa Utkur, Emine Ulku Saritas

In Magnetic Particle Imaging (MPI), the distribution of magnetic nanoparticles (MNPs) is imaged by moving a field free point (FFP) in space. All MNPs in close vicinity of the FFP contribute to the signal induced on the receive coil. The relaxation behavior of these MNPs are subject to a DC field due to the selection field (SF). In this work, we investigate t

Zhi-Qiu Huang, John Kirk, Gwenael Giacinti, Brian Reville

Motivated by the detection of very high energy gamma-rays deep in the afterglow emission of a gamma-ray burst, we revisit predictions of the maximum energy to which electrons can be accelerated at a relativistic blast wave. Acceleration at the weakly-magnetized forward shock of a blast-wave can be limited either by the rapid damping of turbulence generated b

Eqab. M. Rabei, Ahmed Al-Jamel, Mohamed. Al-Masaeed

In this paper, the conformable Laguerre and associated Laguerre differential equations are solved using the Laplace transform. The solution is found to be in exact agreement with that obtained using the power series. In addition some of properties of the Laguerre polynomial is discussed and the conformable Rodriguez's Formula and generating function are prop

John C. Baez

The Gauss-Lucas theorem says that for any complex polynomial $P$, the roots of the derivative $P'$ lie in the convex hull of the roots of $P$. In other words, the roots of $P'$ lie inside the smallest convex subset of the complex plane containing all the roots of $P$. This theorem is not hard to prove, but is there an intuitive explanation? In fact there is,

Radouane Gannouji, Yolbeiker Rodríguez Baez

We study the stability of static black holes in generalized Einstein-Maxwell-scalar theories. We derive the master equations for the odd and even parity perturbations. The sufficient and necessary conditions for the stability of black holes under odd-parity perturbations are derived. We show that these conditions are usually not similar to energy conditions

Yuanqi Mao, Behcet Acikmese

In this paper, we extend our previous results and formally propose the SCvx-fast algorithm, a new addition to the Successive Convexification algorithmic framework. The said algorithm solves non-convex optimal control problems with specific types of state constraints (i.e. union of convex keep-out zones) and is faster to converge than SCvx, its predecessor. I

Christine Geeng, Alexis Hiniker

We conducted semi-structured interviews with members of the LGBTQ community about their privacy practices and concerns on social networking sites. Participants used different social media sites for different needs and adapted to not being completely out on each site. We would value the opportunity to discuss the unique privacy and security needs of this popu

Yue Cui, Solomon W. Harrar

Quality of Life (QOL) outcomes are important in the management of chronic illnesses. In studies of efficacies of treatments or intervention modalities, QOL scales multi-dimensional constructs are routinely used as primary endpoints. The standard data analysis strategy computes composite (average) overall and domain scores, and conducts a mixed-model analysis

Eduardo Esteves, Renan Santos, Eduardo Vital

We give a local characterization for when certain quiver representations in semisimple Abelian categories are semisimple, among them those arising from degenerations of linear series. This paper is the first of two, aimed to describe all the schematic limits of families of divisors associated to a given family of linear series on a one-dimensional family of

Guram Mikaberidze, Raissa M. D'Souza

Cascading failures abound in complex systems and the BTW sandpile model provides a theoretical underpinning for their analysis. Yet, it does not account for the possibility of nodes having oscillatory dynamics such as in power grids and brain networks. Here we consider a network of Kuramoto oscillators upon which the BTW model is unfolding, enabling us to st

Lars Winther Christensen, Luigi Ferraro, Peder Thompson

Let p be a prime ideal in a commutative noetherian ring R and denote by k(p) the residue field of the local ring R_p. We prove that if an R-module M satisfies Ext_R^n(k(p),M) = 0 for some n >= dim R, then Ext_R^i(k(p),M) = 0 holds for all i >= n. This improves a result of Christensen, Iyengar, and Marley by lowering the bound on n. We also improve existing r

Stan Zachary

Future ``net-zero'' electricity systems in which all or most generation is renewable may require very high volumes of storage, provided jointly by a number of heterogeneous technologies, in order to manage the associated variability in the generation-demand balance. We consider the problems of scheduling and dimensioning such storage. We develop a value-func

Tananun Songdechakraiwut, Bryan M. Krause, Matthew I. Banks, Kirill V. Nourski

The topological patterns exhibited by many real-world networks motivate the development of topology-based methods for assessing the similarity of networks. However, extracting topological structure is difficult, especially for large and dense networks whose node degrees range over multiple orders of magnitude. In this paper, we propose a novel and computatio

Savannah Norem, Ashley E Rice, Samantha Erwin, Robert A Bridges

Security operation centers (SOCs) all over the world are tasked with reacting to cybersecurity alerts ranging in severity. Security Orchestration, Automation, and Response (SOAR) tools streamline cybersecurity alert responses by SOC operators. SOAR tool adoption is expensive both in effort and finances. Hence, it is crucial to limit adoption to those most wo

Ramin Faal, Hamid Reza Ebrahimi Vishki

By using the Principle of Local Reflexivity (PLR), we prove that for every two Banach spaces $E$ and $X$ there exists a suitable ultrafilter $\mathcal{U}$ such that $ \mathcal{F}(E,X)^*,$ the dual space of the finite rank operators, can be isomorphically identified with certain quotient of the ultrapower space $(E\widehat{\otimes} X^*)_\mathcal{U}$, of the p

Jonathan W. Berry, Cynthia A Phillips, Alexandra M. Porter

Motivated by the properties of unending real-world cybersecurity streams, we present a new graph streaming model: XStream. We maintain a streaming graph and its connected components at single-edge granularity. In cybersecurity graph applications, input streams typically consist of edge insertions; individual deletions are not explicit. Analysts maintain as m

Ethan L Addison

We begin by defining a type of K\"ahler metric near the zero section of a trivial holomorphic open disk bundle $N$ over a compact K\"ahler manifold $X$ by incorporating flows generated by holomorphic vector fields on $X$. These metrics are then shown to deviate exponentially from Poincar\'e-type metrics on $N\setminus X$ in terms of the log-polar distance fr

Faezeh Zarrinkhat, Joel Lamberg, Aleksi Tamminen, Mariangela Baggio

Coupling to longitudinal modes of thin spherical shells, under Gaussian-beam illumination, was explored with a theoretical method based on Fourier-optics analysis and vector spherical harmonics. The illumination frequency band was fixed between 100-600 GHz and the outer spherical shell radius of curvature and thickness are 7.5 mm and 0.5 mm, respectively. Th

Piotr T. Chruściel, Erwann Delay, Raphaela Wutte

We derive a formula for the energy of asymptotically locally hyperbolic (ALH) manifolds obtained by a gluing at infinity of two ALH manifolds. As an application we show that there exist three-dimensional conformally compact ALH manifolds either without boundary or with toroidal black hole boundary, with connected conformal infinity of higher genus, with cons

Chris McDonagh, Xi Chen

Designing models that produce accurate predictions is the fundamental objective of machine learning (ML). This work presents methods demonstrating that when the derivatives of target variables (outputs) with respect to inputs can be extracted from processes of interest, e.g., neural networks (NN) based surrogate models, they can be leveraged to further impro

Steve Mann, Cayden Pierce, Christopher Tong, Christina Mann

"Vironment" is a series of art pieces, social commentary, technology, etc., based on wearable health technologies of social-distancing, culminating in a social-distancing device that takes the familiar world of security and surveillance technologies that surround us and re-situates it on the body of the wearer (technologies that become part of us). This piec

Kamiokande Collaboration, S. Locke, A. Coffani, K. Abe

Radioactivity induced by cosmic muon spallation is a dominant source of backgrounds for $\mathcal{O}(10)~$MeV neutrino interactions in water Cherenkov detectors. In particular, it is crucial to reduce backgrounds to measure the solar neutrino spectrum and find neutrino interactions from distant supernovae. In this paper we introduce new techniques to locate

Alexander F. Jercher, Daniele Oriti, Andreas G. A. Pithis

We study the cosmological sector of the Lorentzian Barrett-Crane (BC) model coupled to a free massless scalar field in its Group Field Theory (GFT) formulation, corresponding to the mean-field hydrodynamics obtained from coherent condensate states. The relational evolution of the condensate with respect to the scalar field yields effective dynamics of homoge

Máté Matolcsi, Mihály Weiner

Suppose that for some unit vectors $b_1,\ldots b_n$ in $\mathbb C^d$ we have that for any $j\neq k$ $b_j$ is either orthogonal to $b_k$ or $|\langle b_j,b_k\rangle|^2 = 1/d$ (i.e. $b_j$ and $b_k$ are unbiased). We prove that if $n=d(d+1)$, then these vectors necessarily form a complete system of mutually unbiased bases, that is, they can be arranged into $d+

Florian Slanovc, Michael Ortner, Mohssen Moridi, Claas Abert

We present an analytical solution for the magnetic field of a homogeneously magnetized cylinder tile and by extension solutions for full cylinders, rings, cylinder sectors and ring segments. The derivation is done by direct integration in the magnetic surface charge picture. Results are closed-form expressions and elliptic integrals. All special cases are tr

Jay Gopalakrishnan, Lukas Kogler, Philip L. Lederer, Joachim Schöberl

We introduce two new lowest order methods, a mixed method, and a hybrid Discontinuous Galerkin (HDG) method, for the approximation of incompressible flows. Both methods use divergence-conforming linear Brezzi-Douglas-Marini space for approximating the velocity and the lowest order Raviart-Thomas space for approximating the vorticity. Our methods are based on

Prashant Singh

Heterogeneous diffusion with spatially changing diffusion coefficient arises in many experimental systems like protein dynamics in the cell cytoplasm, mobility of cajal bodies and confined hard-sphere fluids. Here, we showcase a simple model of heterogeneous diffusion where the diffusion coefficient $D(x)$ varies in power-law way, i.e. $D(x) \sim |x|^{-\alph