July 2022 arXiv papers — page 113

Neil Perry, Bruce Spang, Saba Eskandarian, Dan Boneh

Messaging systems built on mesh networks consisting of smartphones communicating over Bluetooth have been used by protesters around the world after governments have disrupted Internet connectivity. Unfortunately, existing systems have been shown to be insecure; most concerningly by not adequately hiding metadata. This is further complicated by the fact that

Juan Ramirez, Jose Gallego-Posada

Advances in Implicit Neural Representations (INR) have motivated research on domain-agnostic compression techniques. These methods train a neural network to approximate an object, and then store the weights of the trained model. For example, given an image, a network is trained to learn the mapping from pixel locations to RGB values. In this paper, we propos

Yigit Efe Erginbas, Soham Phade, Kannan Ramchandran

Recommendation systems when employed in markets play a dual role: they assist users in selecting their most desired items from a large pool and they help in allocating a limited number of items to the users who desire them the most. Despite the prevalence of capacity constraints on allocations in many real-world recommendation settings, a principled way of i

W. Klein, Harvey Gould, Sakib Matin

Many systems in nature are conjectured to exist at a critical point, including the brain and earthquake faults. The primary reason for this conjecture is that the distribution of clusters (avalanches of firing neurons in the brain or regions of slip in earthquake faults) can be described by a power law. Because there are other mechanisms such as $1/f$ noise

Dingwen Qian, Monica Olvera de la Cruz

We study size- and charge-asymmetric oppositely charged colloids driven by an external electric field. The large particles are connected by harmonic springs, forming a hexagonal-lattice network while the small particles are free of bonds and exhibit fluid-like motion. We show that this model exhibits a cluster formation pattern when the external driving forc

Michele Martelli, Antonio Virdis, Alberto Gotta, Pietro CassarÀ

In the shipping digitalisation process, the peak will be reached with the advent of a wholly autonomous and at the same time safe and reliable ship. Full autonomy could be obtained by two linked Artificial-Intelligence systems representing the ship navigator and the ship engineer that possess sensing and analysis skills, situational awareness, planning, and

Samuel Grushevsky, Tomoyoshi Ibukiyama, Gabriele Mondello, Riccardo Salvati Manni

We study the cone of moving divisors on the moduli space ${\mathcal A}_g$ of principally polarized abelian varieties. Partly motivated by the generalized Rankin-Cohen bracket, we construct a non-linear holomorphic differential operator that sends Siegel modular forms to Siegel modular forms, and we apply it to produce new modular forms. Our construction reco

Steven Rendon Restrepo, Pierre Barge

Theoretical and numerical studies have shown that large-scale vortices in Protoplanetary discs can result from various hydrodynamical instabilities. Once produced, such vortices can survive nearly unchanged over a large number of rotation periods, slowly migrating towards the star. In the outer disc, self-gravity may affect the vortex evolution and must be i

Asli M. Abdullahi, Jaime Hoefken Zink, Matheus Hostert, Daniele Massaro

We introduce DarkNews, a lightweight Python-based Monte-Carlo generator for beyond-the-Standard-Model neutrino-nucleus scattering. The generator handles the production and decay of heavy neutral leptons via additional vector or scalar mediators, as well as through transition magnetic moments. DarkNews samples pre-computed neutrino-nucleus upscattering cross

Jorge A. Mendez, Marcel Hussing, Meghna Gummadi, Eric Eaton

We present CompoSuite, an open-source simulated robotic manipulation benchmark for compositional multi-task reinforcement learning (RL). Each CompoSuite task requires a particular robot arm to manipulate one individual object to achieve a task objective while avoiding an obstacle. This compositional definition of the tasks endows CompoSuite with two remarkab

W. Zimmermann

A treatment is given of the precession of a Foucault pendulum by means of two successive rotational transformations of coordinate system. The simplicity and accuracy of this approach is emphasized.

Paul R. Genssler, Hamza E. Barkam, Karthik Pandaram, Mohsen Imani

The pivotal issue of reliability is one of colossal concern for circuit designers. The driving force is transistor aging, dependent on operating voltage and workload. At the design time, it is difficult to estimate close-to-the-edge guardbands that keep aging effects during the lifetime at bay. This is because the foundry does not share its calibrated physic

Kevin Zelaya, Vit Jakubský

This work reports the three-band structure associated with a Lieb lattice with arbitrary nearest and next-nearest neighbors hopping interactions. For specific configurations, the system admits a flat band located between two dispersion bands. Three inequivalent Dirac valleys are identified so that the quasi-particles are effectively described by the spin-1 D

Hannah Halin Kim, Shuzhi Yu, Shuai Yuan, Carlo Tomasi

We propose TAIN (Transformers and Attention for video INterpolation), a residual neural network for video interpolation, which aims to interpolate an intermediate frame given two consecutive image frames around it. We first present a novel vision transformer module, named Cross Similarity (CS), to globally aggregate input image features with similar appearan

Nawaf Nazir, Mads Almassalkhi, Ian Hiskens

A wind farm can provide reactive power at sub-transmission and transmission buses in order to support and improve voltage profiles. It is common for the reactive power capability of a wind farm to be evaluated as the sum of the individual turbine ratings. However, such an assessment does not take into account losses over the collector network, nor the voltag

Mathieu Leclercq, Martin Styner, Juan Carlos Prieto

We present our method for gestational age at birth prediction for the SLCN (surface learning for clinical neuroimaging) challenge. Our method is based on a multi-view shape analysis technique that captures 2D renderings of a 3D object from different viewpoints. We render the brain features on the surface of the sphere and then the 2D images are analyzed via

Raphael Olivier, Bhiksha Raj

Robustness to adversarial attacks is typically evaluated with adversarial accuracy. While essential, this metric does not capture all aspects of robustness and in particular leaves out the question of how many perturbations can be found for each point. In this work, we introduce an alternative approach, adversarial sparsity, which quantifies how difficult it

Zaid Jangda, Hannah Menke, Andreas Busch, Sebastian Geiger

The global commitment to achieve net-zero has led to increasing investment towards the production and usage of green hydrogen (H2).However, the massive quantity needed to match future demand will require new storage facilities. Underground storage of H2 is a potentially viable solution, but poses unique challenges due to the distinctive physical and chemical

Robert Zimmerman, Radu V. Craiu, Vianey Leos-Barajas

We propose a copula-based extension of the hidden Markov model (HMM) which applies when the observations recorded at each time in the sample are multivariate. The joint model produced by the copula extension allows decoding of the hidden states based on information from multiple observations. However, unlike the case of independent marginals, the copula depe

K. Khelifa-Kerfa, Y. Delenda, N. Ziani

We present analytical calculations of the distribution of non-global jet shapes in Higgs/vector boson + jet production at hadron colliders. Within the eikonal-limit framework and implementing various jet algorithms, we compute the full distribution of the particular jet mass shape observable at 2-loops, including the large single-logarithms known as non-glob

Rushil Anirudh, Jayaraman J. Thiagarajan

Our goal in this paper is to exploit heteroscedastic temperature scaling as a calibration strategy for out of distribution (OOD) detection. Heteroscedasticity here refers to the fact that the optimal temperature parameter for each sample can be different, as opposed to conventional approaches that use the same value for the entire distribution. To enable thi

Dimpi Thakuria, Abhay Srivastav, Brij Mohan, Asmita Kumari

The quantum speed limit describes how quickly a quantum system can evolve in time from an initial state to a final state under a given dynamics. Here, we derive a generalised quantum speed limit (GQSL) for arbitrary time-continuous evolution using the geometrical approach of quantum mechanics. The GQSL is applicable for quantum systems undergoing unitary, no

Ronan Legin, Connor Stone, Yashar Hezaveh, Laurence Perreault-Levasseur

A new generation of sky surveys is poised to provide unprecedented volumes of data containing hundreds of thousands of new strong lensing systems in the coming years. Convolutional neural networks are currently the only state-of-the-art method that can handle the onslaught of data to discover and infer the parameters of individual systems. However, many impo

Runhui Wang, Yuliang Li, Jin Wang

Machine learning (ML) is playing an increasingly important role in data management tasks, particularly in Data Integration and Preparation (DI&P). The success of ML-based approaches, however, heavily relies on the availability of large-scale, high-quality labeled datasets for different tasks. Moreover, the wide variety of DI&P tasks and pipelines oftentimes

Olga Lukyanova, Oleg Nikitin, Alex Kunin

In this article, we propose the approach to structural optimization of neural networks, based on the braid theory. The paper describes the basics of braid theory as applied to the description of graph structures of neural networks. It is shown how networks of various topologies can be built using braid structures between layers of neural networks. The operat

Juan Pablo Maldonado

Frieze patterns are combinatorial objects that are deeply related to cluster theory. Determinants of frieze patterns arise from triangular regions of the frieze, and they have been considered in previous works by Broline-Crowe-Isaacs, and by Baur-Marsh. In this article, we introduce a new type of matrix for any infinite frieze pattern. This approach allows u

J. A. Pearcy, M. J. Rosenberg, T. M. Johnson, G. D. Sutcliffe

Magnetic reconnection is a ubiquitous and fundamental process in plasmas by which magnetic fields change their topology and release magnetic energy. Despite decades of research, the physics governing the reconnection process in many parameter regimes remains controversial. Contemporary reconnection theories predict that long, narrow current sheets are suscep

Laetitia Teodorescu, Eric Yuan, Marc-Alexandre Côté, Pierre-Yves Oudeyer

In this extended abstract we discuss the opportunities and challenges of studying intrinsically-motivated agents for exploration in textual environments. We argue that there is important synergy between text environments and autonomous agents. We identify key properties of text worlds that make them suitable for exploration by autonmous agents, namely, depth

Nathaniel Hamilton, Kyle Dunlap, Taylor T Johnson, Kerianne L Hobbs

Reinforcement Learning (RL) has become an increasingly important research area as the success of machine learning algorithms and methods grows. To combat the safety concerns surrounding the freedom given to RL agents while training, there has been an increase in work concerning Safe Reinforcement Learning (SRL). However, these new and safe methods have been

A. Gallenne, C. Desgrange, J. Milli, J. Sanchez-Bermudez

AU Mic is a young and nearby M-dwarf star harbouring a circumstellar debris disk and one recently discovered planet on an 8d orbit. Large-scale structures within the disk were also discovered and are moving outward at high velocity. We aim at studying this system with the highest spatial resolution in order to probe the innermost regions and to search for ad

Han Jiang, Shang-En Huang, Thatchaphol Saranurak, Tian Zhang

Recently, Chalermsook et al. [SODA'21(arXiv:2007.07862)] introduces a notion of vertex sparsifiers for $c$-edge connectivity, which has found applications in parameterized algorithms for network design and also led to exciting dynamic algorithms for $c$-edge st-connectivity [Jin and Sun FOCS'21(arXiv:2004.07650)]. We study a natural extension called vertex s

David B. Leep, Rachel L. Petrik

We study lower bound estimates for the number of solutions of systems of equations over finite fields. Heath-Brown improved the lower bounds given by the classical \emph{Chevalley-Warning Theorems} by excluding systems of equations whose solutions form an affine space. We improve each of Heath-Brown's results and demonstrate sharpness in several cases.

Avinash Achar, Soumen Pachal

Deep learning (DL) in general and Recurrent neural networks (RNNs) in particular have seen high success levels in sequence based applications. This paper pertains to RNNs for time series modelling and forecasting. We propose a novel RNN architecture capturing (stochastic) seasonal correlations intelligently while capable of accurate multi-step forecasting. I

Paweł Raźny

We introduce a new spectral sequence for the study of $\mathcal{K}$-manifolds which arises by restricting the spectral sequence of a Riemannian foliation to forms invariant under the flows of $\{\xi_1,...,\xi_s\}$. We use this sequence to generalize a number of theorems from $K$-contact geometry to $\mathcal{K}$-manifolds. Most importantly we compute the coh

Erbil Gügercinoğlu, Elif Köksal, Tolga Güver

The long-term rotational evolution of the old, isolated pulsar, PSR B0950+08 is intriguing in that its spin-down rate displays sinusoidal-like oscillations due to alternating variations, both in magnitude and sign, of the second time derivative of the pulse frequency. We show that the large internal temperature to pinning energy ratio towards the base of the

Kohei Hattori, Akifumi Okuno, Ian U. Roederer

$R$-process enhanced stars with [Eu/Fe]$\geq+0.7$ (so-called $r$-II stars) are believed to have formed in an extremely neutron-rich environment in which a rare astrophysical event (e.g., a neutron star merger) occurred. This scenario is supported by the existence of an ultra-faint dwarf galaxy, Reticulum~II, where most of the stars are highly enhanced in $r$

Yaofeng Desmond Zhong, Jiequn Han, Georgia Olympia Brikis

In recent years, an increasing amount of work has focused on differentiable physics simulation and has produced a set of open source projects such as Tiny Differentiable Simulator, Nimble Physics, diffTaichi, Brax, Warp, Dojo and DiffCoSim. By making physics simulations end-to-end differentiable, we can perform gradient-based optimization and learning tasks.

Xuefei Wu, Gautam Bordia, Robert Streubel, Jaffar Hasnain

Spontaneous emulsification, resulting from the assembly and accumulation of surfactants at liquid-liquid interfaces, is an interfacial instability where microdroplets are generated and diffusively spread from the interface until complete emulsification. Here, we show that an external magnetic field can modulate the assembly of paramagnetic nanoparticle surfa

Yifei Jin, Marios Daoutis, Sarunas Girdzijauskas, Aristides Gionis

Accurate routing network status estimation is a key component in Software Defined Networking. However, existing deep-learning-based methods for modeling network routing are not able to extrapolate towards unseen feature distributions. Nor are they able to handle scaled and drifted network attributes in test sets that include open-world inputs. To deal with t

Tom Ayoola, Shubhi Tyagi, Joseph Fisher, Christos Christodoulopoulos

We introduce ReFinED, an efficient end-to-end entity linking model which uses fine-grained entity types and entity descriptions to perform linking. The model performs mention detection, fine-grained entity typing, and entity disambiguation for all mentions within a document in a single forward pass, making it more than 60 times faster than competitive existi

Tolga Guver, Funda Bostanci, Tugba Boztepe, Ersin Gogus

We present the detection of 51 thermonuclear X-ray bursts observed from 4U 1636-536 by the Neutron Star Interior Composition Explorer (NICER) over the course of a three year monitoring campaign. We performed time resolved spectroscopy for 40 of these bursts and showed the existence of a strong soft excess in all the burst spectra. The excess emission can be

Tom Ayoola, Joseph Fisher, Andrea Pierleoni

Recent work in entity disambiguation (ED) has typically neglected structured knowledge base (KB) facts, and instead relied on a limited subset of KB information, such as entity descriptions or types. This limits the range of contexts in which entities can be disambiguated. To allow the use of all KB facts, as well as descriptions and types, we introduce an E

Harper R. Grimsley, Nicholas J. Mayhall

The recent quantum information boom has effected a resurgence of interest in unitary coupled cluster (UCC) theory. Our group's interest in local energy landscapes of unitary ans\"atze prompted us to investigate the classical approach of truncating the Taylor series expansion (instead of a perturbative expansion) of UCCSD energy at second-order. This amounts

Cédric Beaulac, Sidi Wu, Erin Gibson, Michelle F. Miranda

A major issue in the association of genes to neuroimaging phenotypes is the high dimension of both genetic data and neuroimaging data. In this article, we tackle the latter problem with an eye toward developing solutions that are relevant for disease prediction. Supported by a vast literature on the predictive power of neural networks, our proposed solution

Gregory Plumb, Nari Johnson, Ángel Alexander Cabrera, Ameet Talwalkar

A growing body of work studies Blindspot Discovery Methods ("BDM"s): methods that use an image embedding to find semantically meaningful (i.e., united by a human-understandable concept) subsets of the data where an image classifier performs significantly worse. Motivated by observed gaps in prior work, we introduce a new framework for evaluating BDMs, SpotCh

Dominik Lewy, Jacek Mańdziuk, Maria Ganzha, Marcin Paprzycki

Availability of large amount of annotated data is one of the pillars of deep learning success. Although numerous big datasets have been made available for research, this is often not the case in real life applications (e.g. companies are not able to share data due to GDPR or concerns related to intellectual property rights protection). Federated learning (FL

Yunus Can Gültekin, Kaiquan Wu, Alex Alvarado

We study the effective SNR behavior of various enumerative amplitude shaping algorithms. We show that their relative behavior can be explained via the temporal autocorrelation function or via the energy dispersion index.

Akbar Ali, Abeer M. Albalahi, Abdulaziz M. Alanazi, Akhlaq A. Bhatti

Let $G$ be a graph with edge set $E(G)$. Denote by $d_w$ the degree of a vertex $w$ of $G$. The sigma index of $G$ is defined as $\sum_{uv\in E(G)}(d_u-d_v)^2$. A connected graph of order $n$ and size $n+k-1$ is known as a connected $k$-cyclic graph. Abdo, Dimitrov, and Gutman [Discrete Appl. Math. 250 (2018) 57-64] characterized the graphs having the greate

Alexander Barzykin, Philippe Bergault, Olivier Guéant

In FX cash markets, market makers provide liquidity to clients for a wide variety of currency pairs. Because of flow uncertainty and market volatility, they face inventory risk. To mitigate this risk, they typically skew their prices to attract or divert the flow and trade with their peers on the dealer-to-dealer segment of the market for hedging purposes. T

Víctor A. González-Domínguez, Juan A Reyes-Nava, Pavel Castro-Villarreal

It is supposed the existence of a curved graphene sheet with the geometry of a Bour surface $B_{n}$, such as the catenoid (or helicoid), $B_{0}$, and the classical Enneper surface, $B_{2}$, among others. In particular, in this work, the propagation of the electronic degrees of freedom on these surfaces is studied based on the Dirac equation. As a consequence

Goutam Das, Daigo Shishika

In this paper we consider a Target-guarding differential game where the Defender must protect a linearly moving line segment by intercepting the Attacker who tries to reach it. In contrast to common Target-guarding problems, we assume that the Defender is attached to the Target and moves along with it. This assumption affects the Defender's maximum speed dep

Giovanni Acquaviva, Alfredo Iorio, Pablo Pais, Luca Smaldone

Analogs of fundamental physical phenomena can be used in two ways. One way consists in reproducing specific aspects of classical or quantum gravity, of quantum fields in curved space or of other high-energy scenarios, on lower-energy corresponding systems. The ``reverse way'' consists in building fundamental physical theories, for instance, quantum gravity m

Yunus Can Gültekin, Olga Vassilieva, Inwoong Kim, Paparao Palacharla

We show that a 0.9 dB SNR improvement can be obtained via short-blocklength enumerative sphere shaping for single-span transmission at 56 GBd. This gain vanishes for higher symbol rates and a larger number of spans.

Hanseul Jun, Husam Shaik, Dyan DeVeaux, Michael Lewek

The present research investigates the effectiveness of using a telepresence system compared to a video conferencing system and the effectiveness of using two cameras compared to one camera for remote physical therapy. We used Telegie as our telepresence system, which allowed users to see an environment captured with RGBD cameras in 3D through a VR headset. S

Shu-Ichiro Suzuki, Satoshi Ikegaya, Alexander A. Golubov

The fragility of the chiral surface current of ($d_{zx}+id_{yz}$)-wave superconductor, a potential candidate for Sr$_2$RuO$_4$, against surface roughness is demonstrated utilizing the quasiclassical Eilenberger theory. Comparing the chiral surface currents of ($d_{zx}+id_{yz}$)-wave and ($p_{x}+ip_{y}$)-wave pairings, we conclude the chiral current for ($d_{

Colin J. Burke, Yue Shen, Xin Liu, Priyamvada Natarajan

We present a phenomenological forward Monte Carlo model for forecasting the population of active galactic nuclei (AGNs) in dwarf galaxies observable via their optical variability. Our model accounts for expected changes in the spectral energy distribution of AGNs in the intermediate-mass black hole (IMBH) mass range and uses observational constraints on opti

Francisco Arana-Herrera

We prove an effective estimate with a power saving error term for the number of square-tiled surfaces in a connected component of a stratum of quadratic differentials whose vertical and horizontal foliations belong to prescribed mapping class group orbits and which have at most $L$ squares. This result strengthens asymptotic counting formulas in work of Dele

Zhengang Li, Sheng Lin, Shan Liu, Songnan Li

Recently, high-quality video conferencing with fewer transmission bits has become a very hot and challenging problem. We propose FAIVConf, a specially designed video compression framework for video conferencing, based on the effective neural human face generation techniques. FAIVConf brings together several designs to improve the system robustness in real vi

Edouard Yvinec, Arnaud Dapogny, Matthieu Cord, Kevin Bailly

The leap in performance in state-of-the-art computer vision methods is attributed to the development of deep neural networks. However it often comes at a computational price which may hinder their deployment. To alleviate this limitation, structured pruning is a well known technique which consists in removing channels, neurons or filters, and is commonly app

Spencer Stahl, Chitrarth Prasad, Hemanth Goparaju, Datta Gaitonde

The correlation and extraction of coherent structures from a turbulent flow is a principle objective of data-driven modal decomposition techniques. The Conditional space-time Proper Orthogonal Decomposition (CPOD) offers insight into transient dynamics, revealing the causation of specific flow phenomenon - or events, in a customizable manner. This work explo

Christof Beierle

Let $p>3$ be a prime. We show that, for each integer $d$ with $p \leq d \leq 2(p-1)$, there exists a generalized almost perfect nonlinear (GAPN) binomial or trinomial over $\mathbb{F}_{p^2}$ of algebraic degree $d$. We start by deriving sufficient conditions for the function $G \colon \mathbb{F}_{p^2} \rightarrow \mathbb{F}_{p^2}, X \mapsto X^{d_1} + u X^{d_

Travis Dore, Jamie M. Karthein, Isaac Long, Debora Mroczek

In this work, we study the lensing effect of the QCD critical point on hydrodynamic trajectories, and its consequences on the net-proton kurtosis $\kappa_4$. Including critical behavior by means of the BEST Collaboration equation of state (EoS), we first consider a scenario in equilibrium, then compare with hydrodynamic 0+1D simulations with Bjorken expansio

Iván Pacheco, Pablo Roig

We first study the hadronic lepton flavor violating tau decays within the littlest Higgs model with T-parity (including one or two pseudoscalars, or a vector resonance). We consider the case where only T-odd particles and partner fermions contribute, and also its extension including Majorana neutrinos coming from an inverse seesaw. In both cases our mean val

Shashank Subramanian, Robert M. Kirby, Michael W. Mahoney, Amir Gholami

Physics-informed neural networks (PINNs) incorporate physical knowledge from the problem domain as a soft constraint on the loss function, but recent work has shown that this can lead to optimization difficulties. Here, we study the impact of the location of the collocation points on the trainability of these models. We find that the vanilla PINN performance

Sylvain Sardy, Xiaoyu Ma

In multivariate regression, when covariates are numerous, it is often reasonable to assume that only a small number of them has predictive information. In some medical applications for instance, it is believed that only a few genes out of thousands are responsible for cancers. In that case, the aim is not only to propose a good fit, but also to select the re

Guillaume Allaire Pouliot

We produce methodology for regression analysis when the geographic locations of the independent and dependent variables do not coincide, in which case we speak of misaligned data. We develop and investigate two complementary methods for regression analysis with misaligned data that circumvent the need to estimate or specify the covariance of the regression e

Long Chen, Yixiong Meng, Venkatesh Ravichandran, Andreas Stolcke

Speaker identification (SID) in the household scenario (e.g., for smart speakers) is an important but challenging problem due to limited number of labeled (enrollment) utterances, confusable voices, and demographic imbalances. Conventional speaker recognition systems generalize from a large random sample of speakers, causing the recognition to underperform f

Benjamin D. M. Jones, Roope Uola, Thomas Cope, Marie Ioannou

The effect of quantum steering arises from the judicious combination of an entangled state with a set of incompatible measurements. Recently, it was shown that this form of quantum correlations can be quantified in terms of a dimension, leading to the notion of genuine high-dimensional steering. While this naturally connects to the dimensionality of entangle

Chen-Chih Lai, Michael I. Weinstein

We consider the dynamics of a gas bubble immersed in an incompressible fluid of fixed temperature, and focus on the relaxation of an expanding and contracting spherically symmetric bubble due to thermal effects. We study two models, both systems of PDEs with an evolving free boundary: the full mathematical model as well as an approximate model, arising for e

Tsao-Hsien Chen, Mark Macerato, David Nadler, John O'Brien

We establish a derived geometric Satake equivalence for the quaternionic general linear group GL_n(H). By applying the real-symmetric correspondence for affine Grassmannians, we obtain a derived geometric Satake equivalence for the symmetric variety GL_2n/Sp_2n. We explain how these equivalences fit into the general framework of a geometric Langlands corresp

R. Vilela Mendes

The technique of stochastic solutions, previously used for deterministic equations, is here proposed as a solution method for partial differential equations driven by distribution-valued noises.

Mohsen Fathi, Marco Olivares, J. R. Villanueva

In this paper, we calculate the analytical solutions for the radii of planar and polar spherical photon orbits around a rotating black hole that is associated with quintessential field and cloud of strings. This includes a full analytical treatment of a quintic that describes orbits on the equatorial plane. Furthermore, The radial profile of the impact param

Sara Fridovich-Keil, Brian R. Bartoldson, James Diffenderfer, Bhavya Kailkhura

Improving the accuracy of deep neural networks (DNNs) on out-of-distribution (OOD) data is critical to an acceptance of deep learning (DL) in real world applications. It has been observed that accuracies on in-distribution (ID) versus OOD data follow a linear trend and models that outperform this baseline are exceptionally rare (and referred to as "effective

Yining Xian, Bo-Qiang Ma

This work studies the experiments of two-photon processes at BESIII from a theoretical viewpoint in light-cone quantum field theory. We adopt the momentum space wave function of the pion in the light-cone formalism by two forms of the Brodsky-Huang-Lepage~(BHL) prescription and the light-cone holographic QCD. We find that the wave function got by the light-c

David Hansen, Lucas Mann

We establish several new properties of the $p$-adic Jacquet-Langlands functor defined by Scholze in terms of the cohomology of the Lubin-Tate tower. In particular, we reprove Scholze's basic finiteness theorems, prove a duality theorem, and show a kind of partial K\"unneth formula. Using these results, we deduce bounds on Gelfand-Kirillov dimension, together

Richard H. Benavides, D. V. Forero, Luis Muñoz, Jose M. Muñoz

In this work, we have assumed special structures for the charged and neutral mass matrices in the lepton sector, inspired by structures for the up and down quark mass matrices that result by assuming a certain number of symmetrical zeros in their entries named texture zeros. A prediction of the lepton mixing matrix results from the rotation matrices that dia

Y. Ageeva, P. Petrov, V. Rubakov

We construct a concrete model of Horndeski bounce with strong gravity in the past. Within this model we show that the correct spectra of cosmological perturbations may be generated at early contracting epoch, with mild fine-tuning ensuring that the scalar spectral tilt $n_S$ and tensor-to-scalar ratio $r$ are consistent with observations. The smallness of $r

Amy Etherington, James W. Nightingale, Richard Massey, Andrew Robertson

Observations suggest that the dark matter and stars in early-type galaxies `conspire' to produce a surprisingly simple distribution of total mass, $\rho(r)\propto\rho^{-\gamma}$, with $\gamma\approx2$. We measure the distribution of mass in 48 early-type galaxies that gravitationally lens a resolved background source. By fitting the source light in every pix

Marco Benini, Giorgio Musante, Alexander Schenkel

We develop a homological generalization of Green hyperbolic operators, called Green hyperbolic complexes, which cover many examples of derived critical loci for gauge-theoretic quadratic action functionals in Lorentzian signature. We define Green hyperbolic complexes through a generalization of retarded and advanced Green's operators, called retarded and adv

Sarah Appleby, Romeel Davé, Daniele Sorini, Weiguang Cui

We study the nature of the low-redshift CGM in the Simba cosmological simulations as traced by ultraviolet absorption lines around galaxies in bins of stellar mass ($M_\star>10^{10}M_\odot$) for star-forming, green valley and quenched galaxies at impact parameters $r_\perp\leq 1.25r_{200}$. We generate synthetic spectra for HI, MgII, CII, SiIII, CIV, and OVI

R. A. J. Eyles-Ferris, R. L. C. Starling, P. T. O'Brien, P. A. Evans

The Second Swift-XRT Point Source catalogue offers a combination of sky coverage and sensitivity and presents an invaluable opportunity for transient discovery. We search the catalogue at the positions of inactive and active galaxies, and identify transient candidates by comparison with XMM-Newton and ROSAT. We recover 167 previously known transients and fin

Sergi Navarro Albalat, Aaron Zimmerman, Matthew Giesler, Mark A. Scheel

Recent studies have shown the surprising effectiveness of the small mass-ratio approximation (SMR) in modeling the relativistic two-body problem even at comparable masses. Up to now this effectiveness has been demonstrated only during inspiral, before the binary transitions into plunge and merger. Here we examine the binding energy of nonspinning binary blac

Janosz W. Dewberry, Christopher R. Mankovich, Jim Fuller

The excitation of density and bending waves in Saturn's C ring by planetary oscillation modes presents a unique opportunity to learn about gas giant interiors and rotation. However, theoretical complications related to Saturn's rapid and differential rotation pose a barrier to the full utilization of ring wave detections. We calculate oscillation modes using

David Izquierdo-Villalba, Alberto Sesana, Monica Colpi

Parsec-scale massive black hole binaries (MBHBs) are expected to form in hierarchical models of structure formation. Even though different observational strategies have been designed to detect these systems, a theoretical study is a further guide for their search and identification. In this work, we investigate the hosts properties and the electromagnetic si

Jenny K. Calahan, Edwin A. Bergin, Arthur D. Bosman

An understanding of the abundance and distribution of water vapor in the innermost region of protoplanetary disks is key to understanding the origin of habitable worlds and planetary systems. Past observations have shown H2O to be abundant and a major carrier of elemental oxygen in disk surface layers that lie within the inner few au of the disk. The combina

Petter Taule, Miguel Escudero, Mathias Garny

Neutrinos are expected to freestream (i.e. not interact with anything) since they decouple in the early Universe at a temperature $T\sim 2~{\rm MeV}$. However, there are many relevant particle physics scenarios that can make neutrinos interact at $T< 2~{\rm MeV}$. In this work, we take a global perspective and aim to identify the temperature range in which n

Arpit Das, Chethan N. Gowdigere, Sunil Mukhi

In recent years it has been understood that new rational CFTs can be discovered by applying the coset construction to meromorphic CFTs. Here we turn this approach around and show that the coset construction, together with the classification of meromorphic CFT with $c\leq 24$, can be used to predict the existence of new meromorphic CFTs with $c\geq 32$ whose

Bogdan Ganchev, Anthony Houppe, Nicholas P. Warner

We analyze the BPS equations in the ``superstratum sector'' of three-dimensional gauged supergravity. We obtain multi-parameter supersymmetric solutions that include elliptical deformations of the supertubes that underlie standard superstrata. We uplift the three-dimensional solutions to obtain the corresponding six-dimensional geometries. This yields new fa

Henning Bahl, Wen Han Chiu, Christina Gao, Lian-Tao Wang

A new precision measurement of the $W$ boson mass has been announced by the CDF collaboration, which strongly deviates from the Standard Model prediction. In this article, we study the implications of this measurement on the parameter space of the $SU(2)_L$ triplet extension (with hypercharge $Y=1$) of the Standard Model Higgs sector, focusing on a limit whe

Shashank Shalgar, Irene Tamborra

At high densities in compact astrophysical sources, the coherent forward scattering of neutrinos onto each other is responsible for making the flavor evolution non-linear. Under the assumption of spherical symmetry, we present the first simulations tracking flavor transformation in the presence of neutrino-neutrino forward scattering, neutral and charged cur

James Hung-Hsu Chan, Sergey Sibiryakov, Wei Xue

Axion-like particles, including the QCD axion, are well-motivated dark matter candidates. Numerical simulations have revealed coherent soliton configurations, also known as boson stars, in the centers of axion halos. We study evolution of axion solitons immersed into a gas of axion waves with Maxwellian velocity distribution. Combining analytical approach wi

Qihang Yu, Huiyu Wang, Siyuan Qiao, Maxwell Collins

The rise of transformers in vision tasks not only advances network backbone designs, but also starts a brand-new page to achieve end-to-end image recognition (e.g., object detection and panoptic segmentation). Originated from Natural Language Processing (NLP), transformer architectures, consisting of self-attention and cross-attention, effectively learn long

Mirac Suzgun, Luke Melas-Kyriazi, Suproteem K. Sarkar, Scott Duke Kominers

Innovation is a major driver of economic and social development, and information about many kinds of innovation is embedded in semi-structured data from patents and patent applications. Although the impact and novelty of innovations expressed in patent data are difficult to measure through traditional means, ML offers a promising set of techniques for evalua

Stephan Jackson, Grigor Sargsyan, John Steel

We obtain a partial result on the following conjecture. Conjecture. Let (P, {\Sigma}) be a projectum stable mouse pair, and let \kappa be a cardinal of V such that \kappa < o(M_\infty(P, {\Sigma})); then the following are equivalent: (1) \kappa is a Suslin cardinal, (2) \kappa is a cutpoint of M_\infty(P, {\Sigma}).

Eric Lescano, Nahuel Mirón-Granese

The scalar field-perfect fluid (sf-pf) correspondence shows that the energy-momentum tensor of a scalar field is in correspondence with the dynamics of a perfect fluid. In this work we generalize this concept to study the higher-derivative structure of Double Field Theory with statistical matter. Using the generalized Bergshoeff-de Roo identification we find

Yunus Can Gültekin, Frans M. J. Willems, Alex Alvarado

Recent years have seen renewed attention to arithmetic coding (AC). This is thanks to the use of AC for distribution matching (DM) to control the channel input distribution in probabilistic amplitude shaping. There are two main problems inherent to AC: (1) its required arithmetic precision grows linearly with the input length, and (2) high-precision multipli

Giovanni Verza, Carmelita Carbone, Alessandro Renzi

The bias of dark matter halos and galaxies is a crucial quantity in many cosmological analyses. In this work, using large cosmological simulations, we explore the halo mass function and halo bias within cosmic voids. For the first time to date, we show that they are scale-dependent along the void profile, and provide a predictive theoretical model of both th

Javier de Lucas, Xavier Rivas

We define and analyse the properties of contact Lie systems, namely systems of first-order differential equations describing the integral curves of a $t$-dependent vector field taking values in a finite-dimensional Lie algebra of Hamiltonian vector fields relative to a contact structure. As a particular example, we study families of conservative contact Lie

A. Spurio Mancini, M. M. Docherty, M. A. Price, J. D. McEwen

Comparison of appropriate models to describe observational data is a fundamental task of science. The Bayesian model evidence, or marginal likelihood, is a computationally challenging, yet crucial, quantity to estimate to perform Bayesian model comparison. We introduce a methodology to compute the Bayesian model evidence in simulation-based inference (SBI) s

Zhiyuan Li, Tianhao Wang, JasonD. Lee, Sanjeev Arora

As part of the effort to understand implicit bias of gradient descent in overparametrized models, several results have shown how the training trajectory on the overparametrized model can be understood as mirror descent on a different objective. The main result here is a characterization of this phenomenon under a notion termed commuting parametrization, whic