August 2022 arXiv papers — page 46

Ting-Kuo Chen, Cheng-Wei Chiang, Cheng-Tse Huang, Bo-Qiang Lu

With theoretical constraints such as perturbative unitarity and vacuum stability conditions and updated experimental data of Higgs measurements and direct searches for exotic scalars at the LHC, we perform an updated scan of the allowed parameter space of the Georgi-Machacek (GM) model. With the refined global fit, we examine the allowed parameter space for

Thai Thanh Nguyen

Let $n \ge 2$ be an integer and consider the defining ideal of the Fermat configuration of points in $\mathbb{P}^2$: $I_n=(x(y^n-z^n),y(z^n-x^n),z(x^n-y^n)) \subset R=\mathbb{C}[x,y,z]$. In this paper, we compute explicitly the least degree of generators of its symbolic powers in all unknown cases. As direct applications, we easily verify Chudnovsky's Co

Kunaal Verma, Mansi Girdhar, Azeem Hafeez, Selim S. Awad

Intrusion detection for Controller Area Network (CAN) protocol requires modern methods in order to compete with other electrical architectures. Fingerprint Intrusion Detection Systems (IDS) provide a promising new approach to solve this problem. By characterizing network traffic from known ECUs, hazardous messages can be discriminated. In this article, a mod

Yuan Deng, Jieming Mao, Vahab Mirrokni, Hanrui Zhang

We study the price of anarchy of the first-price auction in the autobidding world, where bidders can be either utility maximizers (i.e., traditional bidders) or value maximizers (i.e., autobidders). We show that with autobidders only, the price of anarchy of the first-price auction is $1/2$, and with both kinds of bidders, the price of anarchy degrades to ab

Jucelino F. Sousa, Carlos H. S. Vieira, Jonas F. G. Santos, Irismar G. da Paz

We study the effect of the intermode coupling in the generation of coherence when two bosonic modes are bilinearly coupled. We consider the case for which the two modes are weakly coupled and the rotating-wave approximation (RWA) applies and the case for which they are strongly coupled and the (RWA) does not apply. Then, in the regime of validity of (RWA), t

Kunle Adegoke

We evaluate the nested sum $\sum_{a_{n - 1} = c}^{a_n } {\sum_{a_{n - 2} = c}^{a_{n - 1} } { \cdots \sum_{a_0 = c}^{a_1 } {x^{a_0 } } } }$ where $a_n$ and $c$ are any integers and $x$ is a real or complex variable. Consequently, we evaluate multiple sums involving the terms of a general second order sequence, the Horadam sequence $(W_j(a,b;p,q))$, defined fo

R. Thimmappa, L. Stawarz, J. Neilsen, M. Ostrowski

Hotspots observed at the edges of extended radio lobes in high-power radio galaxies and quasars mark the position of mildly-relativistic termination shock, where the jet bulk kinetic energy is converted to the internal energy of the jet particles. These are the only astrophysical systems where mildly-relativistic shocks can be directly resolved at various wa

Hanae Inami, Jason Surace, Lee Armus, Aaron S. Evans

We have used the Mid-InfraRed Instrument (MIRI) on the James Webb Space Telescope (JWST) to obtain the first spatially resolved, mid-infrared (mid-IR) images of IIZw096, a merging luminous infrared galaxy (LIRG) at $z = 0.036$. Previous observations with the Spitzer Space Telescope suggested that the vast majority of the total IR luminosity (LIR) of the syst

Justin J. Page, Laura K. Treers, Steven Jens Jorgensen, Ronald S. Fearing

Reduced traction limits the ability of mobile robotic systems to resist or apply large external loads, such as tugging a massive payload. One simple and versatile solution is to wrap a tether around naturally occurring objects to leverage the capstan effect and create exponentially-amplified holding forces. Experiments show that an idealized capstan model ex

Jingyuan Wang, Camron Farhang, Di Yue, Xiaofeng Jin

Recent experiments have pointed to a chiral p-wave-like superconductivity in epitaxial Bi/Ni bilayers that are spontaneously time-reversal symmetry breaking (TRSB), making it a promising platform for exploring physics useful for topologically protected quantum computing. Quite intriguingly, evidence has emerged that in non-epitaxial Bi/Ni bilayers, supercond

Mansi Girdhar, Junho Hong, Yongsik Yoo, Tai-Jin Song

Safe and reliable electric vehicle charging stations (EVCSs) have become imperative in an intelligent transportation infrastructure. Over the years, there has been a rapid increase in the deployment of EVCSs to address the upsurging charging demands. However, advances in information and communication technologies (ICT) have rendered this cyber-physical syste

Anthony Mezzacappa, Pedro Marronetti, Ryan E. Landfield, Eric J. Lentz

We present gravitational wave emission predictions based on three core collapse supernova simulations corresponding to three different progenitor masses. The masses span a large range, between 9.6 and 25 Solar masses, are all initially non-rotating, and are of two metallicities: zero and Solar. We compute both the temporal evolution of the gravitational wave

Mohammad Khairul Bashar, Zongli Lin, Nikhil Shukla

Dynamical systems can offer a novel non-Boolean approach to computing. Specifically, the natural minimization of energy in the system is a valuable property for minimizing the objective functions of combinatorial optimization problems, many of which are still challenging to solve using conventional digital solvers. In this work, we formulate two oscillator-i

Zeyu Fu, Jianbo Jiao, Robail Yasrab, Lior Drukker

Self-supervised contrastive representation learning offers the advantage of learning meaningful visual representations from unlabeled medical datasets for transfer learning. However, applying current contrastive learning approaches to medical data without considering its domain-specific anatomical characteristics may lead to visual representations that are i

Won Joon Yun, Jihong Park, Joongheon Kim

Although quantum supremacy is yet to come, there has recently been an increasing interest in identifying the potential of quantum machine learning (QML) in the looming era of practical quantum computing. Motivated by this, in this article we re-design multi-agent reinforcement learning (MARL) based on the unique characteristics of quantum neural networks (QN

Yuxuan Tian

The spread of fake news has long been a social issue and the necessity of identifying it has become evident since its dangers are well recognized. In addition to causing uneasiness among the public, it has even more devastating consequences. For instance, it might lead to death during pandemics due to unverified medical instructions. This study aims to build

Sri Tata

In the limit of the lattice spacing going to zero, we consider the dimer model on isoradial graphs in the presence of singular $SL(N,\mathbb{C})$ gauge fields flat away from a set of punctures. We consider the cluster expansion of this twisted dimer partition function show it matches an analogous cluster expansion of the 2D Dirac partition function in the pr

Haoyang Yang, Pratham Darrpan Mehta, Jonathan Leo, Zhiyan Zhou

Advanced surgical procedures for congenital heart diseases (CHDs) require precise planning before the surgeries. The conventional approach utilizes 3D-printing and cutting physical heart models, which is a time and resource intensive process. While rapid advances in augmented reality (AR) technologies have the potential to streamline surgical planning, there

Govind Saraswat, Blake Lundstrom, Murti V Salapaka

Residential buildings with the ability to monitor and control their net-load (sum of load and generation) can provide valuable flexibility to power grid operators. We present a novel multiclass nonintrusive load monitoring (NILM) approach that enables effective net-load monitoring capabilities at high-frequency with minimal additional equipment and cost. The

Sina Abbasi, Ebrahim Bedeer

Faster-than-Nyquist (FTN) signaling can improve the spectral efficiency (SE); however, at the expense of high computational complexity to remove the introduced intersymbol interference (ISI). Motivated by the recent success of ML in physical layer (PHY) problems, in this paper we investigate the use of ML in reducing the detection complexity of FTN signaling

Mulham Hijazi

We present a mathematical framework to produce a numerical estimation to the distribution of the lifetime of bubbles emerging from first order cosmological phase transitions. In a precedent work, we have implemented the Sound Shell model to predict the power spectra of gravitational waves arising from the decay of scalar fields. The model depends on the life

Benjamin Jourdain, William Margheriti, Gudmund Pammer

Wasserstein projections in the convex order were first considered in the framework of weak optimal transport, and found application in various problems such as concentration inequalities and martingale optimal transport. In dimension one, it is well-known that the set of probability measures with a given mean is a lattice w.r.t. the convex order. Our main re

Scott C. Chapman, Anthony I. Huber, Adrian K. Sinclair, Jordan D. Wheeler

The Fred Young Submillimeter Telescope (FYST) at the Cerro-Chajnantor Atacama Telescope prime (CCAT- prime) Facility will host Prime-Cam as a powerful, first generation camera with imaging polarimeters working at several wavelengths and spectroscopic instruments aimed at intensity mapping during the Epoch of Reionization. Here we introduce the 850 GHz (350 m

Ruben La

The generalised Springer correspondence for $G = \mathrm{SO}(N,\mathbb{C})$ attaches to a pair $(C,\mathcal{E})$, where $C$ is a unipotent class of $G$ and $\mathcal{E}$ is an irreducible $G$-equivariant local system on $C$, an irreducible representation $\rho(C,\mathcal{E})$ of a relative Weyl group of $G$. We call $C$ the Springer support of $\rho(C,\mathc

Jose E. Tabarez, Arthur K. Barnes, Adam Mate, Russell W. Bent

With the proliferation of distributed generation into distribution networks, the need to consider fault currents in the dispatch problem becomes increasingly relevant. This paper introduces a method for adding fault current constraints into optimal power flow in order to reduce fault currents while minimizing generation cost. The optimal power flow problem i

Anh V. Vu, Daniel R. Thomas, Ben Collier, Alice Hutchings

There has been substantial commentary on the role of cyberattacks carried out by low-level cybercrime actors in the Russia-Ukraine conflict. We analyse 358k website defacement attacks, 1.7M UDP amplification DDoS attacks, 1764 posts made by 372 users on Hack Forums mentioning the two countries, and 441 Telegram announcements (with 58k replies) of a volunteer

Aarat P. Kalra, Alfy Benny, Sophie M. Travis, Eric A. Zizzi

The repeating arrangement of tubulin dimers confers great mechanical strength to microtubules, which are used as scaffolds for intracellular macromolecular transport in cells and exploited in biohybrid devices. The crystalline order in a microtubule, with lattice constants short enough to allow energy transfer between amino acid chromophores, is similar to s

Tsuyoshi Idé, Keerthiram Murugesan, Djallel Bouneffouf, Naoki Abe

This paper is concerned with online targeted advertising on social networks. The main technical task we address is to estimate the activation probability for user pairs, which quantifies the influence one user may have on another towards purchasing decisions. This is a challenging task because one marketing episode typically involves a multitude of marketing

Iason Efraimidis, Alejandro Mas, Dragan Vukotić

Recently, Kayumov \cite{K} obtained a sharp estimate for the $n$-th truncated area functional for normalized functions in the Bloch space for $n\le 5$ and then, together with Wirths \cite{KW1}, extended the result for $n=6$. We prove that for the functions with non-negative Taylor coefficients, the same sharp estimate is valid for all $n$. For arbitrary func

Eyal Weiss, Ariel Felner, Gal A. Kaminka

The shortest path problem in graphs is a cornerstone of AI theory and applications. Existing algorithms generally ignore edge weight computation time. We present a generalized framework for weighted directed graphs, where edge weight can be computed (estimated) multiple times, at increasing accuracy and run-time expense. This raises several generalized varia

Tai Le Quy, Thi Huyen Nguyen, Gunnar Friege, Eirini Ntoutsi

Predicting students' academic performance is one of the key tasks of educational data mining (EDM). Traditionally, the high forecasting quality of such models was deemed critical. More recently, the issues of fairness and discrimination w.r.t. protected attributes, such as gender or race, have gained attention. Although there are several fairness-aware learn

Florian Ellinger, Muhammad Shafiq, Iftikhar Ahmad, Michele Reticcioli

The cubic perovsike strontium titanate SrTiO$_3$ (STO) is one of the most studied, polarizable transition metal oxides. When excess charge is introduced to this material, e.g., through doping or atomic defects, STO tends to host polarons: Quasi-particles formed by excess charge carriers coupling with the crystal phonon field. Their presence alters the materi

Mojtaba Lashgari, Nishant Ravikumar, Irvin Teh, Jing-Rebecca Li

In silico tissue models enable evaluating quantitative models of magnetic resonance imaging. This includes validating and sensitivity analysis of imaging biomarkers and tissue microstructure parameters. We propose a novel method to generate a realistic numerical phantom of myocardial microstructure. We extend previous studies accounting for the cardiomyocyte

Gavin Ball, Jesse Madnick

Every compact 3-Sasakian 7-manifold $M$ admits a canonical 2-parameter family of co-closed $\text{G}_2$-structures $\varphi_{a,b}$ for $a,b > 0$, as well as a foliation by $\varphi_{a,b}$-associative 3-folds whose leaf space $X$ is a positive quaternion-K\"{a}hler 4-orbifold. We prove that associative 3-folds in $(M,\varphi_{a,b})$ that are ruled by a certai

Zehua Chen, Geert Brocks, Shuxia Tao, Peter A. Bobbert

Mixed iodine-bromine perovskites used in solar cells undergo below a critical temperature an intrinsic demixing into phases with different iodine-bromine compositions. In addition, under illumination they show nucleation of an iodine-rich phase. We predict from thermodynamic considerations that in mixed iodine-bromine perovskites like MAPb(I$_{1-x}$Br$_x$)$_

Alan A. Kaptanoglu, Rory Conlin, Matt Landreman

A number of scientific fields rely on placing permanent magnets in order to produce a desired magnetic field. We have shown in recent work that the placement process can be formulated as sparse regression. However, binary, grid-aligned solutions are desired for realistic engineering designs. We now show that the binary permanent magnet problem can be formula

Nicolò Zava

In this paper, we study the stability of the q-hyperconvex hull of a quasi-metric space, adapting known results for the hyperconvex hull of a metric space. To pursue this goal, we extend well-known metric notions, such as Gromov-Hausdorff distance and rough isometries, to the realm of quasi-metric spaces. In particular, we prove that two q-hyperconvex hulls

Ranvir Rana, Dimitris Karakostas, Sreeram Kannan, Aggelos Kiayias

Proof of Work (PoW) blockchains are susceptible to adversarial majority mining attacks in the early stages due to incipient participation and corresponding low net hash power. Bootstrapping ensures safety and liveness during the transient stage by protecting against a majority mining attack, allowing a PoW chain to grow the participation base and correspondi

Yassine El Gantouh

In this paper, we investigate the well-posedness and positivity property of infinite-dimensional linear system with unbounded input and output operators. In particular, we characterize the internal and external positivity for this class of systems. This latter effort is motivated in part by a complete description of well-posed positive control/observation sy

Nataša Krklec Jerinkić, Tijana Ostojić

We consider convex optimization problems with a possibly nonsmooth objective function in the form of a mathematical expectation. The proposed framework (AN-SPS) employs Sample Average Approximations (SAA) to approximate the objective function, which is either unavailable or too costly to compute. The sample size is chosen in an adaptive manner, which eventua

M. R. Hardman, F. I. Parra, B. S. Patel, C. M. Roach

In magnetic confinement fusion devices, the ratio of the plasma pressure to the magnetic field energy, $\beta$, can become sufficiently large that electromagnetic microinstabilities become unstable, driving turbulence that distorts or reconnects the equilibrium magnetic field. In this paper, a theory is proposed for electromagnetic, electron-driven linear in

François Lamarche, Helmut Ruhland

The article shows how two choices are possible whenever computing the geometric mean, and the repetition of this process can in general yield 2-to-the power N different values when the choices are compounded in the first N steps of evaluation of the arithmetic-geometric mean. This happens not only in the simple AGM involved in the computation of the complete

Joona Halkola, Markku Suomalainen, Basak Sakcak, Katherine J. Mimnaugh

In this paper, we present an implementation of a leaning-based control of a differential drive telepresence robot and a user study in simulation, with the goal of bringing the same functionality to a real telepresence robot. The participants used a balance board to control the robot and viewed the virtual environment through a head-mounted display. The main

Di Qi, John Harlim

We propose a statistical-stochastic surrogate modeling approach to predict the response of the mean and variance statistics under various initial conditions and external forcing perturbations. The proposed modeling framework extends the purely statistical modeling approach that is practically limited to the homogeneous statistical regime for high-dimensional

Meiyi Li, Soheil Kolouri, Javad Mohammadi

Constrained optimization problems appear in a wide variety of challenging real-world problems, where constraints often capture the physics of the underlying system. Classic methods for solving these problems rely on iterative algorithms that explore the feasible domain in the search for the best solution. These iterative methods are often the computational b

Matthew C. H. Leung, Shaojie Chen, Colby Jurgenson

Grating-based spectrographs suffer from smile and keystone distortion, which are problematic for hyperspectral data applications. Due to this, spectral lines will appear curved and roughly parabola-shaped. Smile and keystone need to be measured and corrected for accurate spectral and spatial calibration. In this paper, we present a novel method to accurately

Han Xuanyuan, Pietro Barbiero, Dobrik Georgiev, Lucie Charlotte Magister

Graph neural networks (GNNs) are highly effective on a variety of graph-related tasks; however, they lack interpretability and transparency. Current explainability approaches are typically local and treat GNNs as black-boxes. They do not look inside the model, inhibiting human trust in the model and explanations. Motivated by the ability of neurons to detect

Huy Phan, Cong Shi, Yi Xie, Tianfang Zhang

Recently backdoor attack has become an emerging threat to the security of deep neural network (DNN) models. To date, most of the existing studies focus on backdoor attack against the uncompressed model; while the vulnerability of compressed DNNs, which are widely used in the practical applications, is little exploited yet. In this paper, we propose to study

Jonathan Ventura, Camille Pawlak, Milo Honsberger, Cameron Gonsalves

We introduce a novel deep learning method for detection of individual trees in urban environments using high-resolution multispectral aerial imagery. We use a convolutional neural network to regress a confidence map indicating the locations of individual trees, which are localized using a peak finding algorithm. Our method provides complete spatial coverage

Gagandeep Singh, Dionysios Diamantopoulos, Juan Gómez-Luna, Sander Stuijk

Machine learning has recently gained traction as a way to overcome the slow accelerator generation and implementation process on an FPGA. It can be used to build performance and resource usage models that enable fast early-stage design space exploration. First, training requires large amounts of data (features extracted from design synthesis and implementati

Azqa Nadeem, Daniël Vos, Clinton Cao, Luca Pajola

Explainable Artificial Intelligence (XAI) aims to improve the transparency of machine learning (ML) pipelines. We systematize the increasingly growing (but fragmented) microcosm of studies that develop and utilize XAI methods for defensive and offensive cybersecurity tasks. We identify 3 cybersecurity stakeholders, i.e., model users, designers, and adversari

Atticus Stonestrom

Recall that a subset $X$ of a group $G$ is 'product-free' if $X^2\cap X=\varnothing$, ie if $xy\notin X$ for all $x,y\in X$. Let $G$ be a group definable in a distal structure. We prove there are constants $c>0$ and $\delta\in(0,1)$ such that every finite subset $X\subseteq G$ distinct from $\{1\}$ contains a product-free subset of size at least $\delta|X|^{

Wai Tong, Zhutian Chen, Meng Xia, Leo Yu-Ho Lo

This paper presents a design space of interaction techniques to engage with visualizations that are printed on paper and augmented through Augmented Reality. Paper sheets are widely used to deploy visualizations and provide a rich set of tangible affordances for interactions, such as touch, folding, tilting, or stacking. At the same time, augmented reality c

Pablo M. Oliveira, Mateus B. Vieira, Isaac C. Ferreira, João P. R. R. Leite

This paper presents a novel Active Blacklist (ABL) based on a modification of the Simple Mail Transfer Protocol (SMTP). ABL was implemented in the Mail Transfer Agent (MTA) Postfix of the e-mail server Zimbra and assessed exhaustively in a series of experiments. The modified server Zimbra showed computational performance and costs similar to those of the ori

Eli Sennesh, Jordan Theriault, Jan-Willem van de Meent, Lisa Feldman Barrett

Active inference offers a principled account of behavior as minimizing average sensory surprise over time. Applications of active inference to control problems have heretofore tended to focus on finite-horizon or discounted-surprise problems, despite deriving from the infinite-horizon, average-surprise imperative of the free-energy principle. Here we derive

M. Shifman

I describe the inception and development of nonperturbative OPE-based methods in hadronic physics, such as the SVZ sum rules, inverse heavy quark mass expansion (IHQME) and so on and related topics.

Vladlen Galetsky, Soham Ghosh, Christian Deppe, Roberto Ferrara

Physical unclonable functions (PUFs) are hardware structures in a physical system (e.g. semiconductor, crystals etc.) that are used to enable unique identification of the semiconductor or to secure keys for cryptographic processes. A PUF thus generates a noisy secret reproducible at runtime. This secret can either be used to authenticate the chip, or it is a

Lanqin Yuan, Marian-Andrei Rizoiu

Automatic identification of hateful and abusive content is vital in combating the spread of harmful online content and its damaging effects. Most existing works evaluate models by examining the generalization error on train-test splits on hate speech datasets. These datasets often differ in their definitions and labeling criteria, leading to poor generalizat

Saeid Alavi Naeini, Leif Simmatis, Yana Yunusova, Babak Taati

The analysis of speech measures in individuals with amyotrophic lateral sclerosis (ALS) can provide essential information for early diagnosis and tracking disease progression. However, current methods for extracting speech and pause features are manual or semi-automatic, which makes them time-consuming and labour-intensive. The advent of speech-text alignmen

Badal Mondal, Ralf Tonner-Zech

The modification of the nature and size of bandgaps for III-V semiconductors is of strong interest for optoelectronic applications. Strain can be used to systematically tune the bandgap over a wide range of values and induce indirect-to-direct (IDT), direct-to-indirect (DIT), and other changes in bandgap nature. Here, we establish a predictive ab initio appr

Kristin DeVleming, David Stapleton

For prime degree hypersurfaces of dimension at least 3, Mori asked if every smooth proper limit is still a hypersurface. Interestingly in dimensions 1 and 2, this is not the case. For example, Griffin constructed explicit families of quintic curves that give counterexamples in dimension 1 (Horikawa constructed similar examples for quintics in dimension 2). I

Sasindu Wijeratne, Akhilesh Jaiswal, Ajey P. Jacob, Bingyi Zhang

Electrical static random memory (E-SRAM) is the current standard for internal static memory in Field Programmable Gate Array (FPGA). Despite the dramatic improvement in E-SRAM technology over the past decade, the goal of ultra-fast, energy-efficient static random memory has yet to be achieved with E-SRAM technology. However, preliminary research into optical

Enna Sachdeva, Chiho Choi

Effective understanding of dynamically evolving multiagent interactions is crucial to capturing the underlying behavior of agents in social systems. It is usually challenging to observe these interactions directly, and therefore modeling the latent interactions is essential for realizing the complex behaviors. Recent work on Dynamic Neural Relational Inferen

Saeid Alavi Naeini, Leif Simmatis, Deniz Jafari, Diego L. Guarin

Computer vision techniques can help automate or partially automate clinical examination of orofacial impairments to provide accurate and objective assessments. Towards the development of such automated systems, we evaluated two approaches to detect and temporally segment (parse) repetitions in orofacial assessment videos. Recorded videos of participants with

Caden Gobat, Hui Yang, Oleg Kargaltsev, Jeremy Hare

We present a catalog of X-ray Detected Be Stars (XDBS) with 161 Be stars from the Be Star Spectra (BeSS) database having X-ray counterparts in the Chandra Source Catalog v2.0, XMM-Newton 4XMM-DR11 Catalog, or Swift 2SXPS Catalog. The multi-wavelength catalog includes accurate optical positions, X-ray properties (fluxes, photon indices and hardness ratios), o

Zhengwei Bai, Guoyuan Wu, Matthew J. Barth, Yongkang Liu

Perceiving the environment is one of the most fundamental keys to enabling Cooperative Driving Automation (CDA), which is regarded as the revolutionary solution to addressing the safety, mobility, and sustainability issues of contemporary transportation systems. Although an unprecedented evolution is now happening in the area of computer vision for object pe

Federico Dalmao

In this note we prove that the asymptotic variance of the nodal length of complex-valued monochromatic random waves restricted to an increasing domain in $\R^3$ is linear in the volume of the domain. Put together with previous results this shows that a Central Limit Theorem holds true for $3$-dimensional monochromatic random waves. We compare with the varian

Aslanbek Naziev

We study the (in)dependence of additivity and homogeneity conditions in the definition of linear mappings between vector spaces over the same scalar field. Unlike other works on the subject, dealing with particular fields like real or complex numbers, or with particular mappings like continuous or measurable, we consider the general case. This enables us to

Alon Amar, Tirza Routtenberg

In this paper, we consider the problem of recovering random graph signals with complex values. For general Bayesian estimation of complex-valued vectors, it is known that the widely-linear minimum mean-squared-error (WLMMSE) estimator can achieve a lower mean-squared-error (MSE) than that of the linear minimum MSE (LMMSE) estimator. Inspired by the WLMMSE es

Kayla Orlinsky

The semisimple bismash product Hopf algebra $J_n=k^{S_{n-1}}\#kC_n$ for an algebraically closed field $k$ is constructed using the matched pair actions of $C_n$ and $S_{n-1}$ on each other. In this work, we reinterpret these actions and use an understanding of the involutions of $S_{n-1}$ to derive a new Froebnius-Schur indicator formula for irreps of $J_n$

Andrew W. Jackura

Two methodologies have been presented in the literature which connect relativistic three-particle scattering amplitudes with lattice QCD spectra -- the ``relativistic effective field theory'' approach and the ``finite-volume unitarity'' method. While both methods have been shown to be equivalent in various works, it has not been shown how to arrive at the re

Xiang Peng, Huixia Judy Wang

Quantiles and expected shortfalls are commonly used risk measures in financial risk management. The two measurements are correlated while have distinguished features. In this project, our primary goal is to develop stable and practical inference method for conditional expected shortfall. To facilitate the statistical inference procedure, we consider the join

S. Mossman, G. C. Katsimiga, S. I. Mistakidis, A. Romero-Ros

Solitons are nonlinear solitary waves which maintain their shape over time and through collisions, occurring in a variety of nonlinear media from plasmas to optics. We present an experimental and theoretical study of hydrodynamic phenomena in a two-component atomic Bose-Einstein condensate where a soliton array emerges from the imprinting of a periodic spin

William Huntington, Jeremy Glick, Michael Borysow, Daniel J. Heinzen

We demonstrate an intense, continuous cold atom beam generated via post nozzle seeding of a supersonic helium jet with $^7$Li atoms. The nozzle is cooled to about 4.4 K to reduce the forward velocity of the atoms. The atomic beam is brought to a focus 175 cm from the nozzle by a 10 cm bore diameter magnetic hexapole lens. Absorption and fluorescence imaging

Eshwar S R, Shishir Kolathaya, Gugan Thoppe

Evolution Strategy (ES) is a powerful black-box optimization technique based on the idea of natural evolution. In each of its iterations, a key step entails ranking candidate solutions based on some fitness score. For an ES method in Reinforcement Learning (RL), this ranking step requires evaluating multiple policies. This is presently done via on-policy app

Carlos Hernandez-Suarez, Osval Montesinos Lopez

Epidemic models are a valuable tool in the decision making process. Once a mathematical model for an epidemics has been established, the very next step is calculating a mathematical expression for the basic reproductive number, $R_0$, which is the average number of infections caused by an individual that is introduced in a population of susceptibles. Finding

A. Ballow, P. Linton, D. J. Priour

In the case of media comprised of impermeable particles, fluid flows through voids around impenetrable grains. For sufficiently low concentrations of the latter, spaces around grains join to allow transport on macroscopic scales, whereas greater impenetrable inclusion densities disrupt void networks and block macroscopic fluid flow. A critical grain concentr

Abigail Wolf, Shannon Brooks-Lehnert, Keigo Hirakawa

We propose an Event-Based Snow Removal algorithm called EBSnoR. We developed a technique to measure the dwell time of snowflakes on a pixel using event-based camera data, which is used to carry out a Neyman-Pearson hypothesis test to partition event stream into snowflake and background events. The effectiveness of the proposed EBSnoR was verified on a new da

Jack Foster, Mazvydas Gudelis, Amir Ghalamzan Esfahani

To better optimise the global food supply chain, robotic solutions are needed to automate tasks currently completed by humans. Namely, phenotyping, quality analysis and harvesting are all open problems in the field of agricultural robotics. Robotic perception is a key challenge for autonomous solutions to such problems as scene understanding and object detec

Sturmius Tuschmann

Ren\'e Thom's remarkable and far-reaching concept of transversality has found numerous powerful applications. Most importantly, it allowed Thom to develop cobordism theory, which led to a piercing insight into the topology of smooth manifolds, when he generalized Lev Pontryagin's earlier concept of framed cobordism. For his profound findings, in 1958 he was

Seth Pettie, Dingyu Wang

\emph{Cardinality Estimation} (aka \emph{Distinct Elements}) is a classic problem in sketching with many industrial applications. Although sketching \emph{algorithms} are fairly simple, analyzing the cardinality \emph{estimators} is notoriously difficult, and even today the state-of-the-art sketches such as HyperLogLog and (compressed) \PCSA{} are not covere

Deng Wang

Recently, under the standard cosmological model, a new growth tension between the Planck-2018 observation and the combined observation of cosmic microwave background lensing and galaxy clustering at $z\sim4$ emerges over the $1\,\sigma$ confidence level. We demonstrate that dynamical dark energy can well solve this tension within the $1\,\sigma$ confidence l

Richard C. Gerum, Cassidy Pirlot, Alona Fyshe, Joel Zylberberg

Recent studies suggest that artificial neural networks (ANNs) that match the spectral properties of the mammalian visual cortex -- namely, the $\sim 1/n$ eigenspectrum of the covariance matrix of neural activities -- achieve higher object recognition performance and robustness to adversarial attacks than those that do not. To our knowledge, however, no previ

Andrew M. Oster

In this paper, we present a multi--layer, activity--dependent model for the joint development of ocular dominance (OD) columns and cytochrome oxidase (CO) blobs in primate primary visual cortex (V1). For simplicity, we focus on layers 4C and 2/3 with both layers receiving direct thalamic inputs and layer 4C sending vertical projections to layer 2/3. Both the

Christian de Ronde, César Massri

The distinction between pure states and mixed states is a kernel ingredient of what is considered to be the standard formulation of quantum mechanics and plays today a kernel role in foundational debates about the meaning of quantum probability, the separability of quantum systems, the definition and measure of entanglement, etc. In this work we attempt to e

Anina Gruica, Anna-Lena Horlemann, Alberto Ravagnani, Nadja Willenborg

We investigate the asymptotic density of error-correcting codes with good distance properties and prescribed linearity degree, including sublinear and nonlinear codes. We focus on the general setting of finite translation-invariant metric spaces, and then specialize our results to the Hamming metric, to the rank metric, and to the sum-rank metric. Our result

Tao Jiang, Sean Longbrake

In a ground-breaking paper solving a conjecture of Erd\H{o}s on the number of $n$-vertex graphs not containing a given even cycle, Morris and Saxton \cite{MS} made a broad conjecture on so-called balanced supersaturation property of a bipartite graph $H$. Ferber, McKinley, and Samotij \cite{FMS} established a weaker version of this conjecture and applied it

Fatna Abdedou, Bassam Fayad, Arezki Kessi

We give an example of a real analytic reparametrization of a minimal translation flow on $\mathbb{T}^{5}$ that has a Lebesgue spectrum with infinite multiplicity.

Stefan C. Schonsheck, Scott Mahan, Timo Klock, Alexander Cloninger

Autoencoding is a popular method in representation learning. Conventional autoencoders employ symmetric encoding-decoding procedures and a simple Euclidean latent space to detect hidden low-dimensional structures in an unsupervised way. Some modern approaches to novel data generation such as generative adversarial networks askew this symmetry, but still empl

Tuochao Chen, Justin Chan, Shyamnath Gollakota

Since its inception, underwater digital acoustic communication has required custom hardware that neither has the economies of scale nor is pervasive. We present the first acoustic system that brings underwater messaging capabilities to existing mobile devices like smartphones and smart watches. Our software-only solution leverages audio sensors, i.e., microp

Mohamad Mohamad, Julian Neubert, Juan Segundo Argayo

Federated Learning is a recent approach to train statistical models on distributed datasets without violating privacy constraints. The data locality principle is preserved by sharing the model instead of the data between clients and the server. This brings many advantages but also poses new challenges. In this report, we explore this new research area and pe

Linda Hlophe, Konstantinos Kravvaris, Sofia Quaglioni

\noindent{\bf Background:} Deuteron-induced nuclear reactions are an essential tool for probing the structure of nuclei as well as astrophysical information such as $(n,\gamma)$ cross sections. The deuteron-nucleus system is typically described within a Faddeev three-body model consisting of a neutron ($n$), a proton ($p$), and the target nucleus ($A$) inter

Tony Gherghetta, Andrey Shkerin

We study how vacuum neutrino oscillations can be affected by a causal, nonlinear and state-dependent modification of quantum field theory that may be interpreted using the many-worlds formulation of quantum mechanics. The effect is induced by a Higgs-neutrino Yukawa interaction that causes a nonlinear interference between the neutrino mass eigenstates. This

M. S. Rumenskikh, A. A. Chibranov, M. A. Efimov, A. G. Berezutsky

The paper presents results of laboratory experiment modeling the interaction between Lunar magnetic anomalies and Solar wind. To model the LMA we use quadrupole magnetic field. The main dimentionless parameter of the problem, the ion inertia length relative to the mini-magnetosphere size, well corresponds between experiment and LMA conditions. The main resul

Jennifer Schultens

A Heegaard splitting of a $3$-manifold is flippable if there is an isotopy that interchanges the two sides of the Heegaard splitting. We explore which Heegaard splittings of Seifert fibered spaces are flippable.

Aidan Boyd, Jeremy Speth, Lucas Parzianello, Kevin Bowyer

Research in presentation attack detection (PAD) for iris recognition has largely moved beyond evaluation in "closed-set" scenarios, to emphasize ability to generalize to presentation attack types not present in the training data. This paper offers several contributions to understand and extend the state-of-the-art in open-set iris PAD. First, it describes th

Jonathan Lin, Michael Fitzgerald, Yinzi Xin, Olivier Guyon

The photonic lantern (PL) is a tapered waveguide that can efficiently couple light into multiple single-mode optical fibers. Such devices are currently being considered for a number of tasks, including the coupling of telescopes and high-resolution, fiber-fed spectrometers, coherent detection, nulling interferometry, and vortex-fiber nulling (VFN). In conjun

Geeth Ongole, Hongchao Zhang, Tao Zhu, Anzhong Wang

In this paper, we study a proposal put forward recently by Bodendorfer, Mele and M\"unch and Garc\'\i{}a-Quismondo and Marug\'an, in which the two polymerization parameters of spherically symmetric black hole spacetimes are the Dirac observables of the four-dimensional Ashtekar's variables. In this model, black and white hole horizons in general exist and na

Roie Dann, Ronnie Kosloff

Underlying the classical thermodynamic principles are analogous microscopic laws, arising from the fundamental axioms of quantum mechanics. These define quantum thermodynamic variables such as quantum work and heat and characterize the possible transformations of open quantum systems. The foremost quantum thermodynamic law is a simple statement concerning th

Yanlong Shi, Chen Heinrich, Olivier Doré

Relativistic and free-streaming particles like neutrinos leave imprints in large scale structures (LSS), providing probes of the effective number of neutrino species $N_{\rm eff}$. In this paper, we use the Fisher formalism to forecast $N_{\rm eff}$ constraints from the bispectrum (B) of LSS for current and future galaxy redshift surveys, specifically using