November 2022 arXiv papers — page 153

Nishtha Madaan, Adithya Manjunatha, Hrithik Nambiar, Aviral Kumar Goel

Machine learning and deep learning-based decision making has become part of today's software. The goal of this work is to ensure that machine learning and deep learning-based systems are as trusted as traditional software. Traditional software is made dependable by following rigorous practice like static analysis, testing, debugging, verifying, and repairing

Amir Siraj, Abraham Loeb, Amaya Moro-Martin, Mark Elowitz

In this paper, we review some of the extant literature on the study of interstellar objects (ISOs). With the forthcoming Vera C. Rubin Telescope and Legacy Survey of Space and Time (LSST), we find that $0.38 - 84$ `Oumuamua-like interstellar objects are expected to be detected in the next 10 years, with 95\% confidence. The feasibility of a rendezvous trajec

Mais Alheraki, Rawan Al-Matham, Hend Al-Khalifa

Automatic Arabic handwritten recognition is one of the recently studied problems in the field of Machine Learning. Unlike Latin languages, Arabic is a Semitic language that forms a harder challenge, especially with variability of patterns caused by factors such as writer age. Most of the studies focused on adults, with only one recent study on children. More

N. Balakrishnan, E. Castilla

In this paper we present robust estimators for one-shot device test data under lognormal lifetimes. Based on these estimators, confidence intervals and Wald-type tests are also developed. Their robustness feature is illustrated through a simulation study and two numerical examples.

Jay Armas, Erik van Heumen, Akash Jain, Ruben Lier

We construct a new hydrodynamic framework describing plastic deformations in electronic crystals. The framework accounts for pinning, phase, and momentum relaxation effects due to translational disorder, diffusion due to the presence of interstitials and vacancies, and strain relaxation due to plasticity and dislocations. We obtain the hydrodynamic mode spec

Eric Huang, Arthur Pesah, Christopher T. Chubb, Michael Vasmer

Tailored topological stabilizer codes in two dimensions have been shown to exhibit high storage threshold error rates and improved subthreshold performance under biased Pauli noise. Three-dimensional (3D) topological codes can allow for several advantages including a transversal implementation of non-Clifford logical gates, single-shot decoding strategies, p

Shawn M. Jones, Diane Oyen

Much computer vision research has focused on natural images, but technical documents typically consist of abstract images, such as charts, drawings, diagrams, and schematics. How well do general web search engines discover abstract images? Recent advancements in computer vision and machine learning have led to the rise of reverse image search engines. Where

Josimar J. R. Aguirre, Abílio Lemos, Victor G. L. Neumann, Sávio Ribas

Let $\mathbb{F}_{q^n}$ be a finite field with $q^n$ elements. For a positive divisor $r$ of $q^n-1$, the element $\alpha \in \mathbb{F}_{q^n}^*$ is called \textit{$r$-primitive} if its multiplicative order is $(q^n-1)/r$. Also, for a non-negative integer $k$, the element $\alpha \in \mathbb{F}_{q^n}$ is \textit{$k$-normal} over $\mathbb{F}_q$ if $\gcd(\alpha

Jordan Almeter

A graph associahedron is a polytope dual to a simplicial complex whose elements are induced connected subgraphs called tubes. Graph associahedra generalize permutahedra, associahedra, and cyclohedra, and therefore are of great interest to those who study Coxeter combinatorics. This thesis characterizes nested complexes of simplicial complexes, which we call

Daniel E. Maison, Leonid V. Skripnikov, Gleb Penyazkov, Matt Grau

The LuOH$^+$ cation is a promising system to search for manifestations of time reversal and spatial parity violation effects. Such effects in LuOH$^+$ induced by the electron electric dipole moment $e$EDM and the scalar-pseudoscalar interaction of the nucleus with electrons, characterized by $k_s$ constant, in LuOH$^+$ are studied. The enhancement factors, p

Joshua Bruton, Hairong Wang

The effective receptive field of a fully convolutional neural network is an important consideration when designing an architecture, as it defines the portion of the input visible to each convolutional kernel. We propose a neural network module, extending traditional skip connections, called the translated skip connection. Translated skip connections geometri

Thomas L. Dearing, John Hauser, Christopher Petersen, Marco M. Nicotra

In this work, we develop a numerically tractable trajectory optimization problem for rest-to-rest attitude transfers with CMG-driven spacecraft. First, we adapt a specialized dynamical model which avoids many of the numerical challenges (singularities) introduced by common dynamical approximations. To formulate and solve our specialized trajectory optimizati

Katherine B. Follette, Laird M. Close, Jared R. Males, Kimberly Ward-Duong

Accreting protoplanets represent a window into planet formation processes. We report H{\alpha} differential imaging results from the deepest and most comprehensive accreting protoplanet survey to date, acquired with the Magellan Adaptive Optics (MagAO) system's VisAO camera. The fourteen transitional disks targeted are ideal candidates for protoplanet discov

Yuhao Nie, Quentin Paletta, Andea Scott, Luis Martin Pomares

Solar forecasting from ground-based sky images has shown great promise in reducing the uncertainty in solar power generation. With more and more sky image datasets open sourced in recent years, the development of accurate and reliable deep learning-based solar forecasting methods has seen a huge growth in potential. In this study, we explore three different

Nodari Vakhania

In contrast to the fixed parameter analysis (FPA), in the variable parameter analysis (VPA) the value of the target problem parameter is not fixed, it rather depends on the structure of a given problem instance and tends to have a favorable asymptotic behavior when the size of the input increases. While applying the VPA to an intractable optimization problem

Andrew K Kan

In this work, we explore combining automatic hyperparameter tuning and optimization for federated learning (FL) in an online, one-shot procedure. We apply a principled approach on a method for adaptive client learning rate, number of local steps, and batch size. In our federated learning applications, our primary motivations are minimizing communication budg

Johannes Müller, Guido Montúfar

We study the convergence of several natural policy gradient (NPG) methods in infinite-horizon discounted Markov decision processes with regular policy parametrizations. For a variety of NPGs and reward functions we show that the trajectories in state-action space are solutions of gradient flows with respect to Hessian geometries, based on which we obtain glo

Ajinkya H Kokandakar, Yuzhou Lin, Steven Jin, Jordan Weiss

We will study the impact of adolescent sports participation on early-adulthood health using longitudinal data from the National Study of Youth and Religion. We focus on two primary outcomes measured at ages 23--28 -- self-rated health and total score on the PHQ9 Patient Depression Questionnaire -- and control for several potential confounders related to demo

Benjamin D. G. Chandran, Alexander A. Schekochihin

We solve the linearized gyrokinetic equation, quasineutrality condition, and Ampere's law to obtain the dispersion relation of microtearing modes (MTMs) in collisionless low-beta toroidal plasmas. Consistent with past studies, we find that MTMs are driven unstable by the electron temperature gradient and that this instability drive is mediated by magnetic dr

Hamed Pezeshki, Fabio Valerio Massoli, Arash Behboodi, Taesang Yoo

Analog beamforming is the predominant approach for millimeter wave (mmWave) communication given its favorable characteristics for limited-resource devices. In this work, we aim at reducing the spectral efficiency gap between analog and digital beamforming methods. We propose a method for refined beam selection based on the estimated raw channel. The channel

L. Vergara, M. Arai, R. Woracek, M. Olsson

Accurate conversion of neutron time-of-flight (TOF) to wavelength, and its uncertainty, is of fundamental importance to neutron scattering measurements. Especially in cases where instruments are highly configurable, the determination of the absolute wavelength after any change must always be performed. Inspired by the manner with which neutron spectrometers

Bogdan Mazoure, Benjamin Eysenbach, Ofir Nachum, Jonathan Tompson

Model-based reinforcement learning (RL) methods are appealing in the offline setting because they allow an agent to reason about the consequences of actions without interacting with the environment. Prior methods learn a 1-step dynamics model, which predicts the next state given the current state and action. These models do not immediately tell the agent whi

Ben Webster

We continue our study of noncommutative resolutions of Coulomb branches in the case of quiver gauge theories. These include the Slodowy slices in type A and symmetric powers in $\mathbb{C}^2$ as special cases. These resolutions are based on vortex line defects in quantum field theory, but have a precise mathematical description, which in the quiver case is a

Yucen Han, Baoming Shi, Lei Zhang, Apala Majumdar

We model nematic liquid crystal configurations inside three-dimensional prisms, with a polygonal cross-section and Dirichlet boundary conditions on all prism surfaces. We work in a reduced Landau-de Gennes framework, and the Dirichlet conditions on the top and bottom surfaces are special in the sense, that they are critical points of the reduced Landau-de Ge

Mandar Sharma, Nikhil Muralidhar, Naren Ramakrishnan

Through their transfer learning abilities, highly-parameterized large pre-trained language models have dominated the NLP landscape for a multitude of downstream language tasks. Though linguistically proficient, the inability of these models to incorporate the learning of non-linguistic entities (numerals and arithmetic reasoning) limits their usage for tasks

Guilherme Pumi, Taiane Schaedler Prass, Cleiton Guollo Taufemback

In this work we introduce the class of unit-Weibull Autoregressive Moving Average models for continuous random variables taking values in $(0,1)$. The proposed model is an observation driven one, for which, conditionally on a set of covariates and the process' history, the random component is assumed to follow a unit-Weibull distribution parameterized throug

Javier Pliego

We examine a family of three-dimensional exponential sums with monomials and provide estimates which are in some instances sharper than those stemming from approaches entailing the use of existing bounds pertaining to analogous sums.

Aliakbar Daemi, Kenji Fukaya

This is the third paper in a series of papers studying intersection Floer theory of Lagrangians in the complement of a smooth divisor. We complete the construction of Floer homology for such Lagrangians.

Yu-Heng Lin, Claudia Scarlata, Vihang Mehta, Evan Skillman

We present a new selection of 358 blue compact dwarf galaxies (BCDs) from 5,000 square degrees in the Dark Energy Survey (DES), and the spectroscopic follow-up of a subsample of 68 objects. For the subsample of 34 objects with deep spectra, we measure the metallicity via the direct T$_e$ method using the auroral [\oiii]$\lambda$ 4363 emission line. These BCD

Helen Zhou, Sivaraman Balakrishnan, Zachary C. Lipton

Rates of missing data often depend on record-keeping policies and thus may change across times and locations, even when the underlying features are comparatively stable. In this paper, we introduce the problem of Domain Adaptation under Missingness Shift (DAMS). Here, (labeled) source data and (unlabeled) target data would be exchangeable but for different m

Pei-Hung Lin, Chunhua Liao, Winson Chen, Tristan Vanderbruggen

The FAIR Guiding Principles aim to improve the findability, accessibility, interoperability, and reusability of digital content by making them both human and machine actionable. However, these principles have not yet been broadly adopted in the domain of machine learning-based program analyses and optimizations for High-Performance Computing (HPC). In this p

Bhaskar Ray Chaudhury, Linyi Li, Mintong Kang, Bo Li

Federated learning provides an effective paradigm to jointly optimize a model benefited from rich distributed data while protecting data privacy. Nonetheless, the heterogeneity nature of distributed data makes it challenging to define and ensure fairness among local agents. For instance, it is intuitively "unfair" for agents with data of high quality to sacr

J. A. Oller, Z. -H. Guo

Several methods for studying the nature of a resonance are applied to resonances recently discovered in the bottonomium and charmonium sectors. We employ the effective-range expansion, the saturation of the width and compositeness of a resonance, as well as direct fits to data. The latter stem from generic $S$-matrix parameterization that account for relevan

Gianluca Georg Alois Volkmer, Nabil Alsabah

In this paper, we elaborate on the design and discuss the results of a multi-agent simulation that we have developed using the PSI cognitive architecture. We demonstrate that imbuing agents with intrinsic needs for group affiliation, certainty and competence will lead to the emergence of social behavior among agents. This behavior expresses itself in altruis

Erik Christian Hansen, Yonathan Stone, Jesse Wolfson

This is an English translation of Ostrowski's article "\"Uber Dirichletsche Reihen und algebraische Differentialgleichungen" published German in Math. Zeit. vol. 8, 1920, pp. 241-298. In this article, Ostrowski proves a conjecture of Hilbert that the two variable function $\zeta(x,s)=\sum_{n\ge 1} \frac{x^n}{n^s}$ cannot be written as a composition of analyt

Spencer Hamblen, Rafe Jones

Given a field $K$, a rational function $\phi \in K(x)$, and a point $b \in \mathbb{P}^1(K)$, we study the extension $K(\phi^{-\infty}(b))$ generated by the union over $n$ of all solutions to $\phi^n(x) = b$, where $\phi^n$ is the $n$th iterate of $\phi$. We ask when a finite extension of $K(\phi^{-\infty}(b))$ can contain all $m$-power roots of unity for som

Jeongwan Haah

We introduce invertible subalgebras of local operator algebras on lattices. An invertible subalgebra is defined to be one such that every local operator can be locally expressed by elements of the inveritible subalgebra and those of the commutant. On a two-dimensional lattice, an invertible subalgebra hosts a chiral anyon theory by a commuting Hamiltonian, w

Roy Meshulam

Let $G$ be a finite group of order $n$ and for $1 \leq i \leq k+1$ let $V_i=\{i\} \times G$. Viewing each $V_i$ as a $0$-dimensional complex, let $Y_{G,k}$ denote the simplicial join $V_1*\cdots*V_{k+1}$. For $A \subset G$ let $Y_{A,k}$ be the subcomplex of $Y_{G,k}$ that contains the $(k-1)$-skeleton of $Y_{G,k}$ and whose $k$-simplices are all $\{(1,x_1),\

J. A. Oller

We study graviton-graviton scattering in partial-wave amplitudes after unitarizing their Born terms. In order to apply $S$-matrix techniques, based on unitarity and analyticity, we introduce an $S$-matrix associated to this resummation that is free of infrared divergences. This is achieved by removing the diverging phase factor calculated by Weinberg that mu

J. A. Oller

In many physical applications, bound states and/or resonances are observed, which raises the question whether these states are elementary or composite. Here we elaborate on several methods for calculating the compositeness $X$ of bound states and resonances in Quantum Mechanics, and in Quantum Field Theory by introducing particle number operators. For resona

Derek Frydel

The present work investigates the effect of inertia on the entropy production rate $\Pi$ for all canonical models of active particles for different dimensions and the type of confinement. To calculate $\Pi$, the link between the entropy production and dissipation of heat rate is explored resulting in a simple and intuitive expression. By analyzing the Kramer

Mridula Prathapan, Peter Mueller, David Heim, Maria Vittoria Oropallo

In this paper, we provide a system level perspective on the design of control electronics for large scale quantum systems. Quantum computing systems with high-fidelity control and readout, coherent coupling, calibrated gates, and reconfigurable circuits with low error rates are expected to have superior quantum volumes. Cryogenic CMOS plays a crucial role in

Vitaly A. Kudryavtsev, Piotr Krawczun, Rayna Bocheva

Neutrons can induce background events in underground experiments looking for rare processes. Neutrons in a MeV range in deep underground laboratories are produced in spontaneous fission processes and ($\alpha,n$) reactions. A number of computer codes are available to calculate cross-sections of ($\alpha,n$) reactions, branching ratios to various states and n

S. Ya. Startsev

The autonomous Hietarinta equation is a well-known example of the quad-graph discrete equation which is consistent around the cube. In a recent work, it was conjectured that this equation is Darboux integrable (i.e., for each of two independent discrete variables there exist non-trivial functions that remain unchanged on solutions of the equation after the s

Leandro V. Mauri, Rade T. Živaljević, Denise de Mattos, Edivaldo L. dos Santos

We prove a relative of the Optimal (Type B)} Colored Tverberg theorem of \v{Z}ivaljevi\'{c} and Vre\'{c}ica which modifies this results in two different ways. (1) Our result is valid if the number of rainbow faces is $q= p^n-1$, where $p$ is a prime. (2) The size of rainbow simplices satisfies the condition $\vert C_i\vert \in \{2q-2, 2q+1\}$ while in the or

Aurora Polo-Rodriguez, Javier Medina-Quero

This work presents a computer model to discriminate sensor activation in multi-occupancy environments based on proximity interaction. Current proximity-based and indoor location methods allow the estimation of the positions or areas where inhabitants carry out their daily human activities. The spatial-temporal relation between location and sensor activations

Junru Wu, Yi Liang, Feng Han, Hassan Akbari

Self-supervised pre-training recently demonstrates success on large-scale multimodal data, and state-of-the-art contrastive learning methods often enforce the feature consistency from cross-modality inputs, such as video/audio or video/text pairs. Despite its convenience to formulate and leverage in practice, such cross-modality alignment (CMA) is only a wea

Maria Petropoulou, Filippos Psarras, Dimitrios Giannios

Blazars are a rare class of active galactic nuclei (AGN) with relativistic jets pointing towards the observer. Jets are thought to be launched as Poynting-flux dominated outflows that accelerate to relativistic speeds at the expense of the available magnetic energy. In this work, we consider electron-proton jets and assume that particles are energized via ma

Ran Gutin

We present two interactive visualisations of 2x2 real matrices, which we call v1 and v2. v1 is only valid for PSD matrices, and uses the spectral theorem in a trivial way -- we use it as a warm-up. By contrast, v2 is valid for *all* 2x2 real matrices, and is based on the lesser known theory of Lie Sphere Geometry. We show that the dynamics of iterative eigen

Joseph A. Wolf

Two homogeneous pseudo-riemannian manifolds $(G/H, ds^2)$ and $(G'/H', ds'^2)$ belong to the same {\it real form family} if their complexifications $(G_{\mathbb C}/H_{\mathbb C}, ds_{\mathbb C}^2)$ and $(G'_{\mathbb C}/H'_{\mathbb C}, ds'^2_{\mathbb C})$ are isometric. The point is that in many cases a particular space $(G/H, ds^2)$ has interesting propertie

Kazuki Ikeda, Adam Lowe

We devised a protocol that allows two parties, who may malfunction or intentionally convey incorrect information in communication through a quantum channel, to verify each other's measurements and agree on each other's results. This has particular relevance in a modified version of the quantum coin flipping game where the possibility of the players cheating

Arianna S. Long, Caitlin M. Casey, Claudia del P. Lagos, Erini L. Lambrides

Due to their extremely dust-obscured nature, much uncertainty still exists surrounding the stellar mass growth and content in dusty, star-forming galaxies (DSFGs) at $z>1$. In this work, we present a numerical model built using empirical data on DSFGs to estimate their stellar mass contributions across the first $\sim$10 Gyr of cosmic time. We generate a dus

Zi Hong Liu, Bernhard Frank, Lukas Janssen, Matthias Vojta

We consider a two-dimensional quantum spin system described by a Heisenberg model that is embedded in a three-dimensional metal. The two systems couple via an antiferromagnetic Kondo interaction. In such a setup, the ground state generically remains metallic down to the lowest temperatures and allows us to study magnetic quantum phase transitions in metallic

Alexey S. Koshelev, Alexei A. Starobinsky, Anna Tokareva

Gravity can be embedded into a renormalizable theory by means of adding quadratic in curvature terms. However, this at first leads to the presence of the Weyl ghost. It is possible to get rid of this ghost if the locality assumption is weakened and the propagator of the graviton is represented by an entire function of the d'Alembertian operator without new p

Avia Efrat, Or Honovich, Omer Levy

As the performance of large language models rapidly improves, benchmarks are getting larger and more complex as well. We present LMentry, a benchmark that avoids this "arms race" by focusing on a compact set of tasks that are trivial to humans, e.g. writing a sentence containing a specific word, identifying which words in a list belong to a specific category

Sihan Yuan, Boryana Hadzhiyska, Tom Abel

Novel summary statistics beyond the standard 2-point correlation function (2PCF) are necessary to capture the full astrophysical and cosmological information from the small-scale (r < 30Mpc/h) galaxy clustering. However, the analysis of beyond-2PCF statistics on small scales is challenging because we lack the appropriate treatment of observational systematic

D. Blas

Rotational superradiance generates the amplification of incoming waves of sufficiently low frequency when scattered with a rotating absorbing body. This may be used to discover new \emph{bosonic} particles of mass $m_b$ if the rotating body has a sufficiently strong gravitational field, that may confine the massive particle and turn amplification into expone

Claire E. Williams, Smadar Naoz, William Lake, Yeou S. Chiou

A supersonic relative velocity between dark matter (DM) and baryons (the stream velocity) at the time of recombination induces the formation of low mass objects with anomalous properties in the early Universe. We widen the scope of the `Supersonic Project' paper series to include objects we term Dark Matter + Gas Halos Offset by Streaming (DM GHOSts)--diffus

Alberto Rolandi, Martí Perarnau-Llobet

Landauer's principle gives a fundamental limit to the thermodynamic cost of erasing information. Its saturation requires a reversible isothermal process, and hence infinite time. We develop a finite-time version of Landauer's principle for a bit encoded in the occupation of a single fermionic mode, which can be strongly coupled to a reservoir. By solving the

Johanna Erdmenger, Bastian Heß, Ioannis Matthaiakakis, René Meyer

Motivated by establishing holographic renormalization for gravitational theories with non-metricity and torsion, we present a new and efficient general method for calculating Gibbons-Hawking-York (GHY) terms. Our method consists of linearizing any nonlinearity in curvature, torsion or non-metricity by introducing suitable Lagrange multipliers. Moreover, we u

Bronwyn Reichardt Chu, Deanne B. Fisher, Alberto D. Bolatto, John Chisholm

We compare 500~pc scale, resolved observations of ionised and molecular gas for the $z\sim0.02$ starbursting disk galaxy IRAS08339+6517, using measurements from KCWI and NOEMA. We explore the relationship of the star formation driven ionised gas outflows with colocated galaxy properties. We find a roughly linear relationship between the outflow mass flux ($\

Michelle Lochner, Lawrence Rudnick, Ian Heywood, Kenda Knowles

We report the discovery of a unique object in the MeerKAT Galaxy Cluster Legacy Survey (MGCLS) using the machine learning anomaly detection framework Astronomaly. This strange, ring-like source is 30' from the MGCLS field centred on Abell 209, and is not readily explained by simple physical models. With an assumed host galaxy at redshift 0.55, the luminosity

C. E. Martínez-Vázquez, R. Salinas, A. K. Vivas, M. Catelan

The period-luminosity relations (PLR) of Milky Way $\delta$ Scuti ($\delta$ Sct) stars have been described to the present day by a linear relation. However, when studying extragalactic systems such as the Magellanic Clouds and several dwarf galaxies, we notice for the first time a non-linear behaviour in the PLR of $\delta$ Sct stars. Using the largest sampl

G. Ponti, J. S. Sanders, N. Locatelli, X. Zheng

Recent studies have demonstrated that the emission from the circumgalactic medium of the Milky Way displays a relatively high degree of patchiness on angular scales of $\sim10^\circ$. Taking advantage of the Spectrum Roentgen Gamma eROSITA Final Equatorial Depth Survey (eFEDS), we aim to constrain any variation in the soft X-ray surface brightness on scales

Rebecca Diesing, Brian D. Metzger, Elias Aydi, Laura Chomiuk

In August of 2021, Fermi-LAT, H.E.S.S., and MAGIC detected GeV and TeV $\gamma$-ray emission from an outburst of recurrent nova RS Ophiuchi. This detection represents the first very high energy $\gamma$-rays observed from a nova, and opens a new window to study particle acceleration. Both H.E.S.S. and MAGIC described the observed $\gamma$-rays as arising fro

Raquel Gomez Ambrosio, Jaco ter Hoeve, Maeve Madigan, Juan Rojo

Theoretical interpretations of particle physics data, such as the determination of the Wilson coefficients of the Standard Model Effective Field Theory (SMEFT), often involve the inference of multiple parameters from a global dataset. Optimizing such interpretations requires the identification of observables that exhibit the highest possible sensitivity to t

Andrew Cheek, Jacek K. Osiński, Leszek Roszkowski, Sebastian Trojanowski

The Froggatt-Nielsen (FN) mechanism provides an attractive way of generating the determined fermion mass hierarchy and quark mixing matrix elements in the Standard Model (SM). Here we extend it by coupling the FN field, the flavon, to a dark sector containing one or more dark matter particles which are produced non-thermally sequentially through flavon produ

Vihang Mehta, Harry I. Teplitz, Claudia Scarlata, Xin Wang

The UltraViolet imaging of the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey Fields (UVCANDELS) program provides HST/UVIS F275W imaging for four CANDELS fields. We combine this UV imaging with existing HST/near-IR grism spectroscopy from 3D-HST$+$AGHAST to directly compare the resolved rest-frame UV and H$\alpha$ emission for a sample of 979

Erin Blauvelt, Laura Engelbrecht, Kurt Hinterbichler

Massive fields on anti-de Sitter (AdS) space enjoy galileon-like shift symmetries at particular values of their masses. We explore how these shift symmetries are realized through the boundary conformal field theory (CFT), at the level of the 2-point functions. In the alternate quantization scheme in which the dual conformal field gets the smaller $\Delta_-$

Tomasz P. Dutka, John Gargalionis

The gauge bosons of Pati-Salam do not mediate proton decay at the renormalisable level, and for this reason it is possible to construct scenarios in which $SU(4) \otimes SU(2)_{R}$ is broken at relatively low scales. In this Letter we show that such low-scale models generate dimension-5 operators that can give rise to nucleon decays at unacceptably large rat

Cornelius Rampf, Oliver Hahn

Cosmological perturbation theory is known to converge poorly for predicting the spherical collapse and void evolution of collisionless matter. Using the exact parametric solution as a testing ground, we develop two asymptotic methods in spherical symmetry that resolve the gravitational evolution to much higher accuracy than Lagrangian perturbation theory (LP

Muyang Li, Ji Lin, Chenlin Meng, Stefano Ermon

During image editing, existing deep generative models tend to re-synthesize the entire output from scratch, including the unedited regions. This leads to a significant waste of computation, especially for minor editing operations. In this work, we present Spatially Sparse Inference (SSI), a general-purpose technique that selectively performs computation for

Jordy Sehn, Yuchen Wu, Timothy D. Barfoot

Visual Teach and Repeat 3 (VT&R3), a generalization of stereo VT&R, achieves long-term autonomous path-following using topometric mapping and localization from a single rich sensor stream. In this paper, we improve the capabilities of a LiDAR implementation of VT&R3 to reliably detect and avoid obstacles in changing environments. Our architecture simplifies

Liyun Jiang, Ying Yuan

The traditional more-is-better dose selection paradigm, developed based on cytotoxic chemotherapeutics, is often problematic When applied to the development of novel molecularly targeted agents (e.g., kinase inhibitors, monoclonal antibodies, and antibody-drug conjugates). The US Food and Drug Administration (FDA) initiated Project Optimus to reform the dose

Jonas El Gammal, Nils Schöneberg, Jesús Torrado, Christian Fidler

We present the GPry algorithm for fast Bayesian inference of general (non-Gaussian) posteriors with a moderate number of parameters. GPry does not need any pre-training, special hardware such as GPUs, and is intended as a drop-in replacement for traditional Monte Carlo methods for Bayesian inference. Our algorithm is based on generating a Gaussian Process su

Sven Jäger, Guillaume Sagnol, Daniel Schmidt genannt Waldschmidt, Philipp Warode

We study kill-and-restart and preemptive strategies for the fundamental scheduling problem of minimizing the sum of weighted completion times on a single machine in the non-clairvoyant setting. First, we show a lower bound of~$3$ for any deterministic non-clairvoyant kill-and-restart strategy. Then, we give for any $b > 1$ a tight analysis for the natural $b

Yutong Lin, Ze Liu, Zheng Zhang, Han Hu

Frozen pretrained models have become a viable alternative to the pretraining-then-finetuning paradigm for transfer learning. However, with frozen models there are relatively few parameters available for adapting to downstream tasks, which is problematic in computer vision where tasks vary significantly in input/output format and the type of information that

Adam Prada, Eszter S. Pós, Stuart C. Althorpe

Matsubara dynamics is the classical dynamics which results when imaginary-time path-integrals are smoothed; it conserves the quantum Boltzmann distribution and appears in drastically approximated form in path-integral dynamics methods such as (thermostatted) ring-polymer molecular dynamics (T)RPMD and centroid molecular dynamics (CMD). However, it has never

Abinash Kumar Shaw, Manoj Jagannath, Aishrila Mazumder, Arnab Chakraborty

The upcoming Square Kilometer Array (SKA) is expected to produce humongous amount of data for undertaking H{\sc i}~science. We have developed an MPI-based {\sc Python} pipeline to deal with the large data efficiently with the present computational resources. Our pipeline divides such large H{\sc i}~21-cm spectral cubes into several small cubelets, and then p

Anton Rask Lundborg, Ilmun Kim, Rajen D. Shah, Richard J. Samworth

Testing the significance of a variable or group of variables $X$ for predicting a response $Y$, given additional covariates $Z$, is a ubiquitous task in statistics. A simple but common approach is to specify a linear model, and then test whether the regression coefficient for $X$ is non-zero. However, when the model is misspecified, the test may have poor po

James A. A. Trussler, Christopher J. Conselice, Nathan J. Adams, Roberto Maiolino

We utilise theoretical models of Population III stellar+nebular spectra to investigate the prospects of observing and accurately identifying Population III galaxies with JWST using both deep imaging and spectroscopy. We investigate a series of different colour cuts, finding that a combination of NIRCam and MIRI photometry through the F444W-F560W, F560W-F770W

Julien Sorci

The Szegedy quantum walk is a discrete time quantum walk model which defines a quantum analogue of any Markov chain. The long-term behavior of the quantum walk can be encoded in a matrix called the average mixing matrix, whose columns give the limiting probability distribution of the walk given an initial state. We define a version of the average mixing matr

Peter Scherbak, Jim Fuller

Common envelope (CE) evolution, which is crucial in creating short period binaries and associated astrophysical events, can be constrained by reverse modeling of such binaries' formation histories. Through analysis of a sample of well-constrained white dwarf (WD) binaries with low-mass primaries (7 eclipsing double WDs, 2 non-eclipsing double WDs, 1 WD-brown

Chih-Wei Chang, Duncan Bohannon, Zhen Tian, Yinan Wang

Online adaptive proton therapy (APT) is an ideal solution theoretically, which however is challenging to proton clinics. Although multiple groups have been endeavoring to develop online APT technology, there is a concern in the radiotherapy community about the necessity of online APT because of its unknown impact on treatment outcomes. Hence, we have perform

Johannes Forkel, Isao Sauzedde

We prove that the convergence of the real and imaginary parts of the logarithm of the characteristic polynomial of unitary Brownian motion toward Gaussian free fields on the cylinder, as the matrix dimension goes to infinity, holds in certain suitable Sobolev spaces, which we believe to be optimal. This is the natural dynamical analogue of the result for a f

Deepankar Sri Gyan, Hyeon Jun Lee, Youngjun Ahn, Jerome Carnis

Above-bandgap femtosecond optical excitation of a ferroelectric/dielectric BaTiO3/CaTiO3 superlattice leads to structural responses that are a consequence of the screening of the strong electrostatic coupling between the component layers. Time-resolved x-ray free-electron laser diffraction shows that the structural response to optical excitation includes a n

Cédric Bernardin, Reda Chhaibi, Joseph Najnudel, Clément Pellegrini

We study the celebrated Shiryaev-Wonham filter (1964) in its historical setup where the hidden Markov jump process has two states. We are interested in the weak noise regime for the observation equation. Interestingly, this becomes a strong noise regime for the filtering equations. Earlier results of the authors show the appearance of spikes in the filtered

Hao-Xin Wang, Yi-Ming Wu, Yi-Fan Jiang, Hong Yao

Recent ARPES experiments on doped 1D cuprates revealed the importance of effective near-neighbor (NN) attractions in explaining certain features in spectral functions. Here we investigate spectral properties of the extended Hubbard model with the on-site repulsion $U$ and NN interaction $V$, by employing bosonization analysis and the high-precision time-depe

A. Gurgone, A. Papa, P. Schwendimann, A. Signer

The physics programme of the MEG II experiment can be extended with the search for new invisible particles produced in rare muon decays. The hunt for such elusive signals requires accurate simulations to characterise the detector response and estimate the experimental sensitivity. This work presents an improved simulation of muon decay in MEG II, based on Mc

Loukas Gouskos, Fabio Iemmi, Sascha Liechti, Benedikt Maier

We propose a novel strategy for disentangling proton collisions at hadron colliders such as the LHC that considerably improves over the current state of the art. Employing a metric inspired by optimal transport problems as the cost function of a graph neural network, our algorithm is able to compare two particle collections with different noise levels and le

Vedran Brdar, Ying-Ying Li

LHAASO collaboration detected photons with energy above 10 TeV from the most recent gamma-ray burst (GRB), GRB221009A. Given the redshift of this event, $z\sim 0.15$, photons of such energy are expected to interact with the diffuse extragalactic background light (EBL) well before reaching Earth. In this paper we provide a novel neutrino-related explanation o

R. Benbrik, M. Krab, B. Manaut, M. Ouchemhou

In this study, we investigate the light charged Higgs boson production via $pp \rightarrow H^\pm bj$ in the type-I configuration of the Two-Higgs Doublet Model (2HDM). In the viable parameter space, assuming either $h$ or $H$ is the SM-like Higgs boson observed at the Large Hadron Collider (LHC), we focus on the bosonic decays $H^\pm \rightarrow W^\pm A/h$ a

Dilhan Manawadu, Darren J. Valentine, William Barford

We present a dynamical simulation scheme to model the highly correlated excited state dynamics of linear polyenes. We apply it to investigate the internal conversion processes of carotenoids following their photoexcitation. We use the extended Hubbard-Peierls model, $\hat{H}_{\textrm{UVP}}$, to describe the $\pi$-electronic system coupled to nuclear degrees

Colin Defant, Noah Kravitz

If your socks come out of the laundry all mixed up, how should you sort them? We introduce and study a novel foot-sorting algorithm that uses feet to attempt to sort a sock ordering; one can view this algorithm as an analogue of Knuth's stack-sorting algorithm for set partitions. The sock orderings that can be sorted using a fixed number of feet are characte

Ajinkya H. Kokandakar, Hyunseung Kang, Sameer K. Deshpande

We demonstrate how Hahn et al.'s Bayesian Causal Forests model (BCF) can be used to estimate conditional average treatment effects for the longitudinal dataset in the 2022 American Causal Inference Conference Data Challenge. Unfortunately, existing implementations of BCF do not scale to the size of the challenge data. Therefore, we developed flexBCF -- a mor

B. Corci, O. Hooiveld, A. M. Dolga, C. Åberg

The physics of how molecules, organelles, and foreign objects move within living cells has been extensively studied in organisms ranging from bacteria to human cells. In mammalian cells, in particular, cellular vesicles move across the cell using motor proteins that carry the vesicle down the cytoskeleton to their destination. We have recently noted several

Yifan Wei, Jiwei Zhang, Chengchao Zhao, Yanmin Zhao

An adaptive implicit-explicit (IMEX) BDF2 scheme is investigated on generalized SAV approach for the Cahn-Hilliard equation by combining with Fourier spectral method in space. It is proved that the modified energy dissipation law is unconditionally preserved at discrete levels. Under a mild ratio restriction, i.e., \Ass{1}: $0<r_k:=\tau_k/\tau_{k-1}< r_{\max

Mridula Prathapan, Peter Mueller, Christian Menolfi, Matthias Braendli

Realization of qubit gate sequences require coherent microwave control pulses with programmable amplitude, duration, spacing and phase. We propose an SRAM based arbitrary waveform generator for cryogenic control of spin qubits. We demonstrate in this work, the cryogenic operation of a fully programmable radio frequency arbitrary waveform generator in 14 nm F

Jonathan N. Lee, George Tucker, Ofir Nachum, Bo Dai

In offline reinforcement learning (RL), a learner leverages prior logged data to learn a good policy without interacting with the environment. A major challenge in applying such methods in practice is the lack of both theoretically principled and practical tools for model selection and evaluation. To address this, we study the problem of model selection in o

Oliver Janzer, Benny Sudakov

In 1964, Erd\H{o}s proposed the problem of estimating the Tur\'an number of the $d$-dimensional hypercube $Q_d$. Since $Q_d$ is a bipartite graph with maximum degree $d$, it follows from results of F\"uredi and Alon, Krivelevich, Sudakov that $\mathrm{ex}(n,Q_d)=O_d(n^{2-1/d})$. A recent general result of Sudakov and Tomon implies the slightly stronger bound