October 2022 arXiv papers — page 36

Tae-hyeon Shin, Benedikt Diemer

The density profiles of dark matter haloes contain rich information about their growth history and physical properties. One particularly interesting region is the splashback radius, $R_{\rm sp}$, which marks the transition between particles orbiting in the halo and particles undergoing first infall. While the dependence of $R_{\rm sp}$ on the recent accretio

Michael B. S. Yust, Brady R. Cox, Joseph P. Vantassel, Peter G. Hubbard

Distributed acoustic sensing (DAS) is a relatively new technology for recording stress wave propagation, with promising applications in both engineering and geophysics. DAS's ability to simultaneously collect high spatial resolution data over long arrays suggests that it is especially well suited for near-surface imaging applications such as 2D MASW (multi-c

Wenchuan Mu, Kwan Hui Lim

The automatic scoring of summaries is important as it guides the development of summarizers. Scoring is also complex, as it involves multiple aspects such as fluency, grammar, and even textual entailment with the source text. However, summary scoring has not been considered a machine learning task to study its accuracy and robustness. In this study, we place

Chung-Kuan Cheng, Chia-Tung Ho, Chester Holtz

Packaging has become a crucial process due to the paradigm shift of More than Moore. Addressing manufacturing and yield issues is a significant challenge for modern layout algorithms. We propose to use printed circuit board (PCB) placement as a benchmark for the packaging problem. A maximum-margin formulation is devised to improve the separation between nets

Kara Merfeld

Magnetars are neutron stars with exceptionally strong dipole magnetic fields which are observed to display a range of x-ray flaring behavior, but the flaring mechanism is not well understood. The third observing run of Advanced LIGO and Virgo extended from April 1, 2019 to March 27, 2020, and contained x-ray flares from known magnetar SGR 1935+2154, as well

Wenchuan Mu, Kwan Hui Lim

Academic writing should be concise as concise sentences better keep the readers' attention and convey meaning clearly. Writing concisely is challenging, for writers often struggle to revise their drafts. We introduce and formulate revising for concision as a natural language processing task at the sentence level. Revising for concision requires algorithms to

Prayag Chatha, Yixin Wang, Zhenke Wu, Jeffrey Regier

In medicine, researchers often seek to infer the effects of a given treatment on patients' outcomes. However, the standard methods for causal survival analysis make simplistic assumptions about the data-generating process and cannot capture complex interactions among patient covariates. We introduce the Dynamic Survival Transformer (DynST), a deep survival m

Zhehao Ge, Sergey Slizovskiy, Peter Polizogopoulos, Toyanath Joshi

Massless Dirac fermions have been observed in various materials such as graphene and topological insulators in recent years, thus offering a solid-state platform to study relativistic quantum phenomena. Single quantum dots (QDs) and coupled QDs formed with massless Dirac fermions can be viewed as artificial relativistic atoms and molecules, respectively. Suc

Lokrshi Prawar Dadhichi, Klaus Kroy

Graham has shown in Z. Physik B 26, 397-405 (1977) that a fluctuation-dissipation relation can be imposed on a class of non-equilibrium Markovian Langevin equations that admit a stationary solution of the corresponding Fokker-Planck equation. The resulting equilibrium form of the Langevin equation is associated with a nonequilibrium Hamiltonian. Here we prov

Zhuohao Chen, Nikolaos Flemotomos, Zac E. Imel, David C. Atkins

In psychotherapy interactions, the quality of a session is assessed by codifying the communicative behaviors of participants during the conversation through manual observation and annotation. Developing computational approaches for automated behavioral coding can reduce the burden on human coders and facilitate the objective evaluation of the intervention. I

Bartosz Grabowski, Przemysław Głomb, Wojciech Masarczyk, Paweł Pławiak

Interpretation of electrocardiography (ECG) signals is required for diagnosing cardiac arrhythmia. Recently, machine learning techniques have been applied for automated computer-aided diagnosis. Machine learning tasks can be divided into regression and classification. Regression can be used for noise and artifacts removal as well as resolve issues of missing

Dawei Liang, Hang Su, Tarun Singh, Jay Mahadeokar

Interactive voice assistants have been widely used as input interfaces in various scenarios, e.g. on smart homes devices, wearables and on AR devices. Detecting the end of a speech query, i.e. speech end-pointing, is an important task for voice assistants to interact with users. Traditionally, speech end-pointing is based on pure classification methods along

Kira Riedl, Elena Gati, Roser Valenti

The families of organic charge-transfer salts $\kappa$-(BEDT-TTF)$_2X$ and $\kappa$-(BETS)$_2X$ have proven to serve as a powerful playground for the investigation of the physics of frustrated Mott insulators. These materials have been ascribed model character, since dimerization of the organic molecules allows to map these materials onto a single band Hubba

Katherine Thai, Marzena Karpinska, Kalpesh Krishna, Bill Ray

Literary translation is a culturally significant task, but it is bottlenecked by the small number of qualified literary translators relative to the many untranslated works published around the world. Machine translation (MT) holds potential to complement the work of human translators by improving both training procedures and their overall efficiency. Literar

Syeda Lammim Ahad, Yannick M. Bahé, Henk Hoekstra

The diffuse light within galaxy groups and clusters provides valuable insight into the growth of massive cosmic structures. Groups are particularly interesting in this context, because they represent the link between galactic haloes and massive clusters. However, low surface brightness makes their diffuse light extremely challenging to detect individually. S

Francisco Albergaria, G. C. Branco, José Filipe Bastos, J. I. Silva-Marcos

We propose a minimal set of weak-basis invariants in an extension of the SM where one up-type isosinglet vector-like quark is introduced, which allows us to obtain all the physical content of the CKM matrix. We present CP-odd invariants of lower order in mass than the one in the SM, which may have important consequences for Baryogenesis. We study the extreme

Joscha Diehl, Leonard Schmitz

Quasisymmetric functions have recently been used in time series analysis as polynomial features that are invariant under, so-called, dynamic time warping. We extend this notion to data indexed by two parameters and thus provide warping invariants for images. We show that two-parameter quasisymmetric functions are complete in a certain sense, and provide a tw

Prabhat Kumar, Andrew Nonaka, Revathi Jambunathan, Girish Pahwa

We present a massively parallel, 3D phase-field simulation framework for modeling ferro-electric materials based scalable logic devices. We self-consistently solve the time-dependent Ginzburg Landau (TDGL) equation for ferroelectric polarization, Poisson equation for electric potential, and charge equation for carrier densities in semiconductor regions. The

Simone Blasi, Alberto Mariotti, Aäron Rase, Alexander Sevrin

We study the early Universe evolution of axion-like particle (ALP) domain walls taking into account the effect of friction from particles in the surrounding plasma, including the case of particles in thermal equilibrium and frozen out species. We characterize the friction force from interactions within the ALP effective theory, providing new results for the

Claudius Krause, Ian Pang, David Shih

CaloFlow is a new and promising approach to fast calorimeter simulation based on normalizing flows. Applying CaloFlow to the photon and charged pion Geant4 showers of Dataset 1 of the Fast Calorimeter Simulation Challenge 2022, we show how it can produce high-fidelity samples with a sampling time that is several orders of magnitude faster than Geant4. We dem

Soumavo Ghosh, Francesca Fragkoudi, Paola Di Matteo, Kanak Saha

The Milky Way as well as a majority of external galaxies possess a thick disc. However, the dynamical role of the (geometrically) thick disc on the bar formation and evolution is not fully understood. Here, we investigate the effect of thick discs in bar formation and evolution by means of a suite of N-body models of (kinematically cold) thin-(kinematically

Nestor Mirabal

The origin of ultra-high-energy cosmic rays (UHECRs) remains elusive. Gamma-ray bursts (GRBs) are among the best candidates able to meet the stringent energy requirements needed for particle acceleration to such high energies. If UHECRs were accelerated by the central engine of GRB 221009A, it might be possible to detect secondary photons and neutrinos as th

Zack Weinstein, Shane P. Kelly, Jamir Marino, Ehud Altman

We study quantum information scrambling in a random unitary circuit that exchanges qubits with an environment at a rate $p$. As a result, initially localized quantum information not only spreads within the system, but also spills into the environment. Using the out-of-time-order correlator (OTOC) to characterize scrambling, we find a nonequilibrium phase tra

Carlos R. Mafra, Oliver Schlotterer

We give a comprehensive review of recent developments on using the pure spinor formalism to compute massless superstring scattering amplitudes at tree level. The main results of the pure spinor computations are placed into the context of related topics including the color-kinematics duality in field theory and the mathematical structure of $\alpha'$-correcti

Damiano Anselmi

We formulate a new quantization principle for perturbative quantum field theory, based on a minimally non time-ordered product, and show that it gives the theories of physical particles and purely virtual particles. Given a classical Lagrangian, the quantization proceeds as usual, guided by the time-ordered product, up to the common scattering matrix $S$, wh

Joseph DeRose, Shi-Fan Chen, Nickolas Kokron, Martin White

Numerical simulations in cosmology require trade-offs between volume, resolution and run-time that limit the volume of the Universe that can be simulated, leading to sample variance in predictions of ensemble-average quantities such as the power spectrum or correlation function(s). Sample variance is particularly acute at large scales, which is also where an

Max Wiesner

We consider 4d N=1 theories arising from F-theory compactifications on elliptically-fibered Calabi-Yau four-folds and investigate the non-perturbative structure of their scalar field space beyond the large volume/large complex structure regime. We focus on regimes where the F-theory field space effectively reduces to the deformation space of the worldsheet t

Jenny E. Greene, Shany Danieli, Scott Carlsten, Rachael Beaton

Isolated dwarf galaxies usually exhibit robust star formation but satellite dwarf galaxies are often devoid of young stars, even in Milky Way-mass groups. Dwarf galaxies thus offer an important laboratory of the environmental processes that cease star formation. We explore the balance of quiescent and star-forming galaxies (quenched fractions) for a sample o

J. Sous, C. Zhang, M. Berciu, D. R. Reichman

Employing unbiased sign-problem-free quantum Monte Carlo, we investigate the effects of long-range Coulomb forces on BEC of bipolarons using a model of bond phonon-modulated electron hopping. In absence of long-range repulsion, this model was recently shown to give rise to small-size, light-mass bipolarons that undergo a superfluid transition at high values

Jee-Ho Kim, Sirio Belli, Rainer Weinberger

We analyze the stellar abundances of massive galaxies ($\log M_\ast/M_\odot>10.5$) at $z=2$ in the IllustrisTNG simulation with the goal of guiding the interpretation of current and future observations, particularly from the James Webb Space Telescope. We find that the effective size, $R_e$, of galaxies strongly affects the abundance measurements: both [Mg/H

Alex J. Cameron, Harley Katz, Martin P. Rey

Deriving oxygen abundances from the electron temperature (hereafter the $T_e$-method) is the gold-standard for extragalactic metallicity studies. However, unresolved temperature fluctuations within individual HII regions and across different HII regions throughout a galaxy can bias metallicity estimates low, with a magnitude that depends on the underlying an

Shany Danieli, Jenny E. Greene, Scott Carlsten, Fangzhou Jiang

Quantifying the connection between galaxies and their host dark matter halos has been key for testing cosmological models on various scales. Below $M_\star \sim 10^9\,M_\odot$, such studies have primarily relied on the satellite galaxy population orbiting the Milky Way. Here we present new constraints on the connection between satellite galaxies and their ho

Iryna S. Butsky, Shreya Nakum, Sam B. Ponnada, Cameron B. Hummels

Recent theoretical studies predict that the circumgalactic medium (CGM) around low-redshift, $\sim L_*$ galaxies could have substantial nonthermal pressure support in the form of cosmic rays. However, these predictions are sensitive to the specific model of cosmic-ray transport employed, which is theoretically and observationally underconstrained. In this wo

Riccardo J. Valencia-Tortora, Shane P. Kelly, Tobias Donner, Giovanna Morigi

Many-body cavity QED experiments are established platforms to tailor and control the collective responses of ensembles of atoms, interacting through one or more common photonic modes. The rich diversity of dynamical phases they can host, calls for a unified framework. Here we commence this program by showing that a cavity QED simulator assembled from $N$-lev

Thomas K. Langin, David DeMille

Recent experiments have demonstrated direct cooling and trapping of diatomic and triatomic molecules in magneto-optical traps (MOTs). However, even the best molecular MOTs to date still have density $10^{-5}$ times smaller than in typical atomic MOTs. The main limiting factors are: (i) inefficiencies in slowing molecules to velocities low enough to be captur

Katrin Renz, Kashyap Chitta, Otniel-Bogdan Mercea, A. Sophia Koepke

Planning an optimal route in a complex environment requires efficient reasoning about the surrounding scene. While human drivers prioritize important objects and ignore details not relevant to the decision, learning-based planners typically extract features from dense, high-dimensional grid representations containing all vehicle and road context information.

Matthew J. Penn, Daniel J. Laydon, Joseph Penn, Charles Whittaker

Uncertainty can be classified as either aleatoric (intrinsic randomness) or epistemic (imperfect knowledge of parameters). The majority of frameworks assessing infectious disease risk consider only epistemic uncertainty. We only ever observe a single epidemic, and therefore cannot empirically determine aleatoric uncertainty. Here, we characterise both episte

Kieran A. Murphy, Dani S. Bassett

A hallmark of chaotic dynamics is the loss of information with time. Although information loss is often expressed through a connection to Lyapunov exponents -- valid in the limit of high information about the system state -- this picture misses the rich spectrum of information decay across different levels of granularity. Here we show how machine learning pr

Pavol Harar, Dennis Elbrächter, Monika Dörfler, Kory D. Johnson

We present an algorithm and package, Redistributor, which forces a collection of scalar samples to follow a desired distribution. When given independent and identically distributed samples of some random variable $S$ and the continuous cumulative distribution function of some desired target $T$, it provably produces a consistent estimator of the transformati

Behzad Tahmasebzadeh, Ling Zhu, Juntai Shen, Ortwin Gerhard

Barred structures are important in understanding galaxy evolution, but they were not included explicitly in most dynamical models for nearby galaxies due to their complicated morphological and kinematic properties. We modify the triaxial orbit-superposition Schwarzschild implementation by Van den Bosch et al. (2008) to include barred structures explicitly. T

Jacobo Ayensa-Jiménez, Mohamed H. Doweidar, Manuel Doblaré, Eamonn A. Gaffney

As motivated by studies of cellular motility driven by spatiotemporal chemotactic gradients in microdevices, we develop a framework for constructing approximate analytical solutions for the location, speed and cellular densities for cell chemotaxis waves in heterogeneous fields of chemoattractant from the underlying partial differential equation models. In p

Zhaoran Hou, Samuel W. K. Wong

Sequential Monte Carlo (SMC) methods are widely used to draw samples from intractable target distributions. Particle degeneracy can hinder the use of SMC when the target distribution is highly constrained or multimodal. As a motivating application, we consider the problem of sampling protein structures from the Boltzmann distribution. This paper proposes a g

Michael Laskin, Luyu Wang, Junhyuk Oh, Emilio Parisotto

We propose Algorithm Distillation (AD), a method for distilling reinforcement learning (RL) algorithms into neural networks by modeling their training histories with a causal sequence model. Algorithm Distillation treats learning to reinforcement learn as an across-episode sequential prediction problem. A dataset of learning histories is generated by a sourc

V. N. Velizhanin

We present a simple algebraic method for the analytic continuation of harmonic sums with integer real or purely imaginary indices near negative and positive integers. We provide a MATHEMATICA code for exact expansion of harmonic sums in a small parameter near these integers. As an application, we consider the analytic continuation of the anomalous dimension

William Thompson, Christian Marois, Clarissa R. Do Ó, Quinn Konopacky

The HR 8799 system hosts four massive planets orbiting 15 and 80 AU. Studies of the system's orbital stability and its outer debris disk open the possibility of additional planets, both interior to and exterior to the known system. Reaching a sufficient sensitivity to search for interior planets is very challenging due to the combination of bright quasi stat

Gideon Lee, Alexander McDonald, Aashish Clerk

We show for generic quantum non-Hermitian tight-binding models that relaxation timescales of local observables are not controlled by the localization length $\xi_{\rm loc}$ associated with the non-Hermitian skin effect, contrary to popular belief. Instead, interference between eigenvectors effectively makes the extreme localization of modes largely irrelevan

Wei Xun, Xiao Yang, Qing-Song Jiang, Ming-Jun Wang

Efficient and selective CO2 electroreduction into value-added chemicals and fuels emerged as a significant approach for CO2 conversion, however, it relies on catalysts with controllable product selectivity and reaction paths. In this work, by means of first-principles calculations, we identify five catalysts (TM@MoSi2N4, TM = Sc, Ti, Fe, Co and Ni) comprisin

Sudharshan Suresh, Zilin Si, Stuart Anderson, Michael Kaess

We present MidasTouch, a tactile perception system for online global localization of a vision-based touch sensor sliding on an object surface. This framework takes in posed tactile images over time, and outputs an evolving distribution of sensor pose on the object's surface, without the need for visual priors. Our key insight is to estimate local surface geo

Pedro A. Sánchez, Alessio Caciagli, Sofia S. Kantorovich, Erika Eiser

We characterize the self-assembly of colloidal particles with surface mobile DNA linkers under kinetically limited valence conditions. For this, we put forward a computer simulation model that captures quantitatively the interplay between the main dynamic processes governing these systems and allows the simulation of the long time scales reached in experimen

Khasa Gillani, Jorge Martín Pérez, Milan Groshev, Antonio de la Oliva

Recent trends in robotic services propose offloading robot functionalities to the Edge to meet the strict latency requirements of networked robotics. However, the Edge is typically an expensive resource and sometimes the Cloud is also an option, thus, decreasing the cost. Following this idea, we propose Don't Let Me Down! (DLMD), an algorithm that promotes o

Soyeun Kim, Yinchuan Lv, Xiao-Qi Sun, Chengxi Zhao

The lowest-lying fundamental excitation of an incommensurate charge density wave (CDW) material is widely believed to be a massless phason -- a collective modulation of the phase of the CDW order parameter. However, as first pointed out by Lee and Fukuyama, long-range Coulomb interactions should push the phason energy up to the plasma energy of the CDW conde

Jennifer Elder, Pamela E. Harris, Zoe Markman, Izah Tahir

A permutation of length $n$ is called a flattened partition if the leading terms of maximal chains of ascents (called runs) are in increasing order. We analogously define flattened parking functions: a subset of parking functions for which the leading terms of maximal chains of weak ascents (also called runs) are in weakly increasing order. For $n\leq 8$, wh

John So, Amber Xie, Sunggoo Jung, Jeffrey Edlund

Autonomous driving is complex, requiring sophisticated 3D scene understanding, localization, mapping, and control. Rather than explicitly modelling and fusing each of these components, we instead consider an end-to-end approach via reinforcement learning (RL). However, collecting exploration driving data in the real world is impractical and dangerous. While

Christian Brownlees, Vladislav Morozov

In this work we introduce a unit averaging procedure to efficiently recover unit-specific parameters in a heterogeneous panel model. The procedure consists in estimating the parameter of a given unit using a weighted average of all the unit-specific parameter estimators in the panel. The weights of the average are determined by minimizing an MSE criterion we

Brandon Foggo, Koji Yamashita, Nanpeng Yu

This paper introduces pmuGE (phasor measurement unit Generator of Events), one of the first data-driven generative model for power system event data. We have trained this model on thousands of actual events and created a dataset denoted pmuBAGE (the Benchmarking Assortment of Generated PMU Events). The dataset consists of almost 1000 instances of labeled eve

Frank Trujillo, Corinna Ulcigrai

We produce affine interval exchange transformations (AIETs) which are topologically conjugated to (standard) interval exchange maps (IETs) via a singular conjugacy, i.e. a diffeomorphism $h$ of $[0,1]$ which is $C^0$ but not $C^1$ and such that the pull-back of the Lebesgue measure is a singular invariant measure for the AIET. In particular, we show that for

Louise Alamichel, Daria Bystrova, Julyan Arbel, Guillaume Kon Kam King

Bayesian nonparametric mixture models are common for modeling complex data. While these models are well-suited for density estimation, recent results proved posterior inconsistency of the number of clusters when the true number of components is finite, for the Dirichlet process and Pitman--Yor process mixture models. We extend these results to additional Bay

J. van de Kraats, D. J. M. Ahmed-Braun, J. -L. Li, S. J. J. M. F. Kokkelmans

We analyse the change in the hyperradial Efimovian three-body potential as the two-body interaction is tuned from the broad to narrow Feshbach resonance regime. Here, it is known from both theory and experiment that the three-body dissociation scattering length $a_-$ shifts away from the universal value of $-9.7 \ r_{\mathrm{vdW}}$, with $r_{\mathrm{vdW}} =

Hong Liu, Sang Michael Xie, Zhiyuan Li, Tengyu Ma

Language modeling on large-scale datasets leads to impressive performance gains on various downstream language tasks. The validation pre-training loss (or perplexity in autoregressive language modeling) is often used as the evaluation metric when developing language models since the pre-training loss tends to be well-correlated with downstream performance (w

Jayant Rao, Shubhanshu Tiwari

We study the holographic duals of bosonic and fermionic fields and compute their Quasinormal Frequencies (QNF) by exploiting that they are massive charged fields in $\mathrm{AdS_2 \times \mathcal{K}}$. In particular, we assess the stability of the scalar and fermionic operators in Myers-Perry's black holes with equal angular momenta. We compute the central c

Julius Baldauf

This paper studies the Ricci flow on closed manifolds admitting harmonic spinors. It is shown that Perelman's Ricci flow entropy can be expressed in terms of the energy of harmonic spinors in all dimensions, and in four dimensions, in terms of the energy of Seiberg-Witten monopoles. Consequently, Ricci flow is the gradient flow of these energies. The proof r

Haoyu Hu, Lei Chen, Qimiao Si

An overarching question in strongly correlated electron systems is how the landscape of quantum phases emerges from electron correlations. The method of extended dynamical mean field theory (EDMFT) has been developed for clean lattice models of the correlated electrons. For such models, not only onsite Hubbard-like interactions are important, but so are inte

Thomas G. Mertens, Joan Simón, Gabriel Wong

Recent progress in AdS/CFT has provided a good understanding of how the bulk spacetime is encoded in the entanglement structure of the boundary CFT. However, little is known about how spacetime emerges directly from the bulk quantum theory. We address this question in an effective 3d quantum theory of pure gravity, which describes the high temperature regime

Giuseppe Morello, Achrène Dyrek, Quentin Changeat

We explore how finite integration time or temporal binning can affect the analysis of exoplanet phase-curves. We provide analytical formulae to account for this effect or, if neglected, to estimate the potential biases in the retrieved parameters. As expected, due to their smoother variations over longer time-scales, phase curves can be binned more heavily t

Marek Miller, Manfredi Scalici, Marco Fellous Asiani, Alexander Streltsov

Entanglement distillation allows to convert noisy quantum states into singlets, which can in turn be used for various quantum technological tasks, such as quantum teleportation and quantum key distribution. Entanglement dilution is the inverse process: singlets are converted into quantum states with less entanglement. While the usefulness of distillation is

Aditya Nandy, Shuwen Yue, Changhwan Oh, Chenru Duan

High-throughput screening of large hypothetical databases of metal-organic frameworks (MOFs) can uncover new materials, but their stability in real-world applications is often unknown. We leverage community knowledge and machine learning (ML) models to identify MOFs that are thermally stable and stable upon activation. We separate these MOFs into their build

Hossein Rajaby Faghihi, Bashar Alhafni, Ke Zhang, Shihao Ran

Social media has increasingly played a key role in emergency response: first responders can use public posts to better react to ongoing crisis events and deploy the necessary resources where they are most needed. Timeline extraction and abstractive summarization are critical technical tasks to leverage large numbers of social media posts about events. Unfort

Dimitrios Panteleimon Giakatos, Sofia Kostoglou, Pavlos Sermpezis, Athena Vakali

The Internet is composed of networks, called Autonomous Systems (or, ASes), interconnected to each other, thus forming a large graph. While both the AS-graph is known and there is a multitude of data available for the ASes (i.e., node attributes), the research on applying graph machine learning (ML) methods on Internet data has not attracted a lot of attenti

Zhonglin Cao, Rishikesh Magar, Yuyang Wang, Amir Barati Farimani

Metal-Organic Frameworks (MOFs) are materials with a high degree of porosity that can be used for applications in energy storage, water desalination, gas storage, and gas separation. However, the chemical space of MOFs is close to an infinite size due to the large variety of possible combinations of building blocks and topology. Discovering the optimal MOFs

Aida Behmard, Melissa Ness, Emily C. Cunningham, Megan Bedell

The elemental abundances of planet host stars can shed light on the conditions of planet forming environments. We test if individual abundances of 130 known/candidate planet hosts in APOGEE are statistically different from those of a reference doppelganger sample. The reference set comprises objects selected with the same Teff, logg, [Fe/H], and [Mg/H] as ea

Minho Kwon, Aaron Holman, Quan Gan, Chun-Wei Liu

We report on the design and characterization of a cold atom source for strontium (Sr) based on a two-dimensional magneto-optical trap (MOT) that is directly loaded from the atom jet of a dispenser. We characterize the atom flux of the source by measuring the loading rate of a three-dimensional MOT. We find loading rates of up to $10^{8}$ atoms per second. Th

Remy Dou, Eric Brewe, Geoff Potvin, Justyna P. Zwolak

Modeling Instruction (MI), an active-learning introductory physics curriculum, has been shown to improve student academic success. Peer-to-peer interactions play a salient role in the MI classroom. Their impact on student interest and self-efficacy -- preeminent constructs of various career theories -- has not been thoroughly explored. Our examination of thr

Tian-Yi Zhou, Xiaoming Huo

It is frequently observed that overparameterized neural networks generalize well. Regarding such phenomena, existing theoretical work mainly devotes to linear settings or fully-connected neural networks. This paper studies the learning ability of an important family of deep neural networks, deep convolutional neural networks (DCNNs), under both underparamete

Haoyu Hu, Lei Chen, Qimiao Si

Strange metals develop near quantum critical points in a variety of strongly correlated systems. Some of the issues that are central to the field include how the quantum-critical state loses quasiparticles, how it drives superconductivity, and to what extent the strange-metal physics in different classes of correlated systems are interconnected. In this Revi

R. Sett, F. Hassani, D. Phan, S. Barzanjeh

The photon blockade breakdown in a continuously driven cavity QED system has been proposed as a prime example for a first-order driven-dissipative quantum phase transition. But the predicted scaling from a microscopic system - dominated by quantum fluctuations - to a macroscopic one - characterized by stable phases - and the associated exponents and phase di

Jerson Caro, Hector Pasten

For a non-constant elliptic surface over $\mathbb{P}^1$ defined over $\mathbb{Q}$, it is a result of Silverman that the Mordell--Weil rank of the fibres is at least the rank of the group of sections, up to finitely many fibres. If the elliptic surface is non-isotrivial one expects that this bound is an equality for infinitely many fibres, although no example

Charles F. Dunkl

The two-dimensional quantum harmonic oscillator is modified with reflection terms associated with the action of the Coxeter group $B_2$, which is the symmetry group of the square. The angular momentum operator is also modified with reflections. The wavefunctions are known to be built up from Jacobi and Laguerre polynomials. This paper introduces a fourth-ord

Chunqiu Steven Xia, Yuxiang Wei, Lingming Zhang

Automated Program Repair (APR) aims to help developers automatically patch software bugs. However, current state-of-the-art traditional and learning-based APR techniques face the problem of limited patch variety, failing to fix complicated bugs. This is mainly due to the reliance on bug-fixing datasets to craft fix templates or directly predict potential pat

Kingman Cheung

Recently, several telescopes, including Swift-BAT, GBM, and LHAASO, have observed the ever highest-energy and long-duration gamma-rays from a gamma-ray burst named as GRB221009A (located at a red-shift of $z=0.151$) on October 9, 2022. Conventional understanding tells us that very high-energy photons produced at such a far distance suffer severe attenuation

Sarthak Jain, Varun Manjunatha, Byron C. Wallace, Ani Nenkova

Many language tasks (e.g., Named Entity Recognition, Part-of-Speech tagging, and Semantic Role Labeling) are naturally framed as sequence tagging problems. However, there has been comparatively little work on interpretability methods for sequence tagging models. In this paper, we extend influence functions - which aim to trace predictions back to the trainin

Anish Ghoshal, Dibyendu Nanda, Abhijit Kumar Saha

We study the imprints of high scale non-thermal leptogenesis on cosmic microwave background (CMB) from the measurements of inflationary spectral index ($n_s$) and tensor-to-scalar ratio ($r$), which otherwise is inaccessible to the conventional laboratory experiments. We argue that non-thermal production of baryon (lepton) asymmetry from subsequent decays of

Débora Lopes, Tito Alexandro Medina Tejeda, Maria Aparecida Soares Ruas, Igor Chagas Santos

This paper is a first step in order to extend Kummer's theory for line congruences to the case $\lbrace x, \xi \rbrace $, where $x: U \rightarrow \mathbb{R}^3$ is a smooth map and $\xi: U \rightarrow \mathbb{R}^3$ is a proper frontal. We show that if $\lbrace x, \xi \rbrace$ is a normal congruence, the equation of the principal surfaces is a multiple of the

Ben Schaper, Christopher Lohse, Marcell Streile, Andrea Giovannini

Despite extensive recent advances in summary generation models, evaluation of auto-generated summaries still widely relies on single-score systems insufficient for transparent assessment and in-depth qualitative analysis. Towards bridging this gap, we propose the multifaceted interpretable summary evaluation method (MISEM), which is based on allocation of a

Yanlong Hao, Xiugui Liu, Qianwen Sun

In this paper, we describe the homotopy type of the homotopy fixed point sets of $S^3$-actions on rational spheres and complex projective spaces, and provide some properties of $S^1$-actions on a general rational complex.

Qianwen Sun

For an amalgam of two free groups and a particular kind of automorphism, we show that the Dehn function of the corresponding mapping torus is quadratic.

Valerio De Luca, Gabriele Franciolini, Antonio Riotto

We show that heavy primordial black holes may originate from much lighter ones if the latter are strongly clustered at the time of their formation. While this population is subject to the usual constraints from late-time universe observations, its relation to the initial conditions is different from the standard scenario and provides a new mechanism to gener

Junren Chen, Michael K. Ng

The main aim of this paper is to study quaternion phase retrieval (QPR), i.e., the recovery of quaternion signal from the magnitude of quaternion linear measurements. We show that all $d$-dimensional quaternion signals can be reconstructed up to a global right quaternion phase factor from $O(d)$ phaseless measurements. We also develop the scalable algorithm

Maximillian Chen, Alexandros Papangelis, Chenyang Tao, Andy Rosenbaum

Dialogue understanding tasks often necessitate abundant annotated data to achieve good performance and that presents challenges in low-resource settings. To alleviate this barrier, we explore few-shot data augmentation for dialogue understanding by prompting large pre-trained language models and present a novel approach that iterates on augmentation quality

Yanlong Hao, Xiugui Liu

Let $\rm{Aut}(p)$ denote the space of all self-fibre homotopy equivalences of a principal $G$-bundle $p: E\rightarrow X$ of simply connected CW complexes with $E$ finite. When $G$ is a compact connected topological group, we show that there exists an inequality $$n-{\rm N}(p)\leq {\rm Hnil}_{\mathbb{Q}}({\rm{Aut}}(p)_0)\leq n$$ for any space $X$, where $n$ i

Daniel Alpay, Fabrizio Colombo, Kamal Diki, Irene Sabadini

We use methods from the Fock space and Segal-Bargmann theories to prove several results on the Gaussian RBF kernel in complex analysis. The latter is one of the most used kernels in modern machine learning kernel methods, and in support vector machines (SVMs) classification algorithms. Complex analysis techniques allow us to consider several notions linked t

N. Bukharskii, Ph. Korneev

Irradiation of a thin metallic wire with an intense femtosecond laser pulse creates a strong discharge wave that travels as a narrow pulse along the wire surface. The travelling discharge efficiently emits secondary radiation with spectral characteristics mostly defined by the wire geometry. Several exemplary designs are considered in the context of generati

Max Alteg, Baptiste Chevalier, Octave Mestoudjian, Johan-Luca Rossi

In order to answer the problem of Quantum Phase Estimation Algorithm been not suitable for NISQ devices, and allows one to outperform classical computers, Variational Quantum Algorithms (VQAs) were designed. Our subject of interest is the so-called Variational Quantum Eigensolver (VQE) algorithm and was originally designed to simulate electronic structures a

Kimara Naicker, Ilya Sinayskiy, Francesco Petruccione

One of the approaches used to solve for the dynamics of open quantum systems is the hierarchical equations of motion (HEOM). Although it is numerically exact, this method requires immense computational resources to solve. The objective here is to demonstrate whether models such as SARIMA, CatBoost, Prophet, convolutional and recurrent neural networks are abl

William Giarè, Matteo Forconi, Eleonora Di Valentino, Alessandro Melchiorri

Inflationary gravitational waves, behaving as additional radiation in the Early Universe, can increase the effective number of relativistic species ($N_{\rm eff}$) by a further correction that depends on the integrated energy-density in gravitational waves over all scales. This effect is typically used to constrain (blue-tilted) models of inflation in light

Yanlong Hao, Xiugui Liu, Qianwen Sun

In this note, we give some new families of two-stage spaces for which the torus rank conjecture is affirmed.

SNO+ Collaboration, :, A. Allega, M. R. Anderson

The SNO+ Collaboration reports the first evidence of reactor antineutrinos in a Cherenkov detector. The nearest nuclear reactors are located 240~km away in Ontario, Canada. This analysis uses events with energies lower than in any previous analysis with a large water Cherenkov detector. Two analytical methods are used to distinguish reactor antineutrinos fro

Achintya Low, Susanta Ghosh, Susmita Changdar, Sayan Routh

Magnetic topological materials, in which strong correlations between magnetic and electronic properties of matter, give rise to various exotic phenomena such as anomalous Hall effect (AHE), topological Hall effect (THE), and skyrmion lattice. Here, we report on the electronic, magnetic, and topological properties of Mn$_{3-\it{x}}$Fe$_{\it{x}}$Sn single crys

Oluwatosin Samuel Falebita

The reliability and success of any organization such as academic institution rely on its ability to provide secure, accurate and timely data about its operations. Erstwhile managing student information in academic institution was done through paper-based information system, where academic records are documented in several files that are kept in shelves. Seve

Shubhodip Mondal, Emanuel Reinecke

We show that the hypercomplete $\infty$-topos associated with any replete topos is Postnikov complete, positively answering a question of Bhatt and Scholze; this will be deduced from the Milnor sequences for sheaves of spaces on replete topoi that we construct. As a corollary, we generalize a result of To\"en on affine stacks.

Narayanan Rengaswamy, Nithin Raveendran, Ankur Raina, Bane Vasić

Recent constructions of quantum low-density parity-check (QLDPC) codes provide optimal scaling of the number of logical qubits and the minimum distance in terms of the code length, thereby opening the door to fault-tolerant quantum systems with minimal resource overhead. However, the hardware path from nearest-neighbor-connection-based topological codes to l