September 2021 arXiv papers

Jack Jeffries, Luis Núñez-Betancourt, Eamon Quinlan-Gallego

The Bernstein-Sato polynomial is an important invariant of an element or an ideal in a polynomial ring or power series ring of characteristic zero, with interesting connections to various algebraic and topological aspects of the singularities of the vanishing locus. Work of Mustaţă, later extended by Bitoun and the third author, provides an analogous Bernste

Amanda Adkins, Taijing Chen, Joydeep Biswas

Robots deployed in settings such as warehouses and parking lots must cope with frequent and substantial changes when localizing in their environments. While many previous localization and mapping algorithms have explored methods of identifying and focusing on long-term features to handle change in such environments, we propose a different approach -- can a r

Yoshinori Sueno, Shunsuke Honda, Hiroki Kutsuma, Satoru Mima

A microwave kinetic inductance detector (MKID) is a cutting-edge superconducting detector. It comprises a resonator circuit constructed with a superconducting film on a dielectric substrate. To expand its field of application, it is important to establish a method to suppress the two-level system (TLS) noise that is caused by the electric fluctuations betwee

L. V. El'nikova, A. T. Ponomarenko, V. G. Shevchenko

We propose the theoretical description for the temperature and concentration phase transformations in composite lithium grease doped with the mesogenic additives of the copper(II) carboxylates family, copper(II) valerate and isovalerate, in the concentration range 1, 5, 10, 20 wt. percents. The changes in character of specific electric conductivity of these

Nathaniel Selub, Frederick Wehlen, Craig Hogan, Stephan S. Meyer

We examine all-sky cosmic microwave background (CMB) temperature maps on large angular scales to compare their consistency with two scenarios: the standard inflationary quantum picture, and a distribution constrained to have a universal variance of primordial curvature perturbations on great circles. The latter symmetry is not a property of standard quantum

Jae Shin Yoon, Zhixuan Yu, Jaesik Park, Hyun Soo Park

This paper presents a new large multiview dataset called HUMBI for human body expressions with natural clothing. The goal of HUMBI is to facilitate modeling view-specific appearance and geometry of five primary body signals including gaze, face, hand, body, and garment from assorted people. 107 synchronized HD cameras are used to capture 772 distinctive subj

Jacqueline Comer, Sam Work, Kory W Mathewson, Lana Cuthbertson

The United Nations identified gender equality as a Sustainable Development Goal in 2015, recognizing the underrepresentation of women in politics as a specific barrier to achieving gender equality. Political systems around the world experience gender inequality across all levels of elected government as fewer women run for office than men. This is due in par

Yo Joong Choe, Aaditya Ramdas

Consider two forecasters, each making a single prediction for a sequence of events over time. We ask a relatively basic question: how might we compare these forecasters, either online or post-hoc, while avoiding unverifiable assumptions on how the forecasts and outcomes were generated? In this paper, we present a rigorous answer to this question by designing

D. A. Kann, A. Rossi, S. R. Oates, S. Klose

The supernovae (SNe) associated with gamma-ray bursts (GRBs) are generally seen as a homogenous population, but at least one exception exists, both in terms of luminosity as well as Spectral Energy Distribution (SED). However, this event, SN 2011kl, was associated with an ultra-long GRB 111209A. Do such outliers also exist for more typical GRBs? Within the c

Tara Abrishami, Maria Chudnovsky, Cemil Dibek, Kristina Vušković

We give a combinatorial polynomial-time algorithm to find a maximum weight independent set in perfect graphs of bounded degree that do not contain a prism or a hole of length four as an induced subgraph. An even pair in a graph is a pair of vertices all induced paths between which are even. An even set is a set of vertices every two of which are an even pair

Yongxin Zeng, Allan H. MacDonald

The optical properties of weakly-doped two-dimensional materials are dominated by strong exciton and trion absorption and luminescence features. In this article we examine the influence of moiré patterns in semiconductor heterobilayers on exciton and trion states in the limit of strong moiré modulation potentials, commenting on similarities and differences c

Nariman Torkzaban, Mohammad A. Amir Khojastepour

Millimeter-wave (mmWave) communications is considered as a key enabler towards the realization of next-generation wireless networks, due to the abundance of available spectrum at mmWave frequencies. However, mmWave suffers from high free-space path-loss and poor scattering resulting in mostly line-of-sight (LoS) channels which result in a lack of coverage. R

Davide Macera, Sasha Sodin

In 1990, Klein, Lacroix, and Speis proved (spectral) Anderson localisation for the Anderson model on the strip of width $W \geqslant 1$, allowing for singular distribution of the potential. Their proof employs multi-scale analysis, in addition to arguments from the theory of random matrix products (the case of regular distributions was handled earlier in the

Richard A. P. Birkett

The dynamics of a rational surface map $f : X \dashrightarrow X$ are easier to analyse when $f$ is `algebraically stable'. Here we investigate when and how this condition can be achieved by conjugating $f$ with a birational change of coordinates. We show that if this can be done with a birational morphism, then there is a minimal such conjugacy. For bira

Simon Streicher, Johan du Preez

Probabilistic graphical models (PGMs) are powerful tools for solving systems of complex relationships over a variety of probability distributions. However, while tree-structured PGMs always result in efficient and exact solutions, inference on graph (or loopy) structured PGMs is not guaranteed to discover the optimal solutions. It is in principle possible to

Xiangyi Fan, Grani A. Hanasusanto

We study two-stage stochastic optimization problems with random recourse, where the adaptive decisions are multiplied with the uncertain parameters in both the objective function and the constraints. To mitigate the computational intractability of infinite-dimensional optimization, we propose a scalable approximation scheme via piecewise linear and piecewise

Jingwei Li

Statistic modeling and data-driven learning are the two vital fields that attract many attentions. Statistic models intend to capture and interpret the relationships among variables, while data-based learning attempt to extract information directly from the data without pre-processing through complex models. Given the extensive studies in both fields, a subt

Nikaya Snell, Chang Zhang, Gengyang Mu, Alexandre Bouchard

Silicon nitride (SiN) drumhead resonators offer a promising platform for thermal sensing due to their high mechanical quality factor and the high temperature sensitivity of their resonance frequency. As such, gaining an understanding of heat transport in SiN resonators as well as their sensing noise limitations is of interest, both of which are goals of the

Matteo Nerini, Shanpu Shen, Bruno Clerckx

Reconfigurable intelligent surfaces (RISs) allow controlling the propagation environment in wireless networks through reconfigurable elements. Recently, beyond diagonal RISs (BD-RISs) have been proposed as novel RIS architectures whose scattering matrix is not limited to being diagonal. However, BDRISs have been studied assuming continuous-value scattering m

Xiang Dai, Shiqi Xu, Xi Yang, Kevin C. Zhou

This paper presents a microscopic imaging technique that uses variable-angle illumination to recover the complex polarimetric properties of a specimen at high resolution and over a large field-of-view. The approach extends Fourier ptychography, which is a synthetic aperture-based imaging approach to improve resolution with phaseless measurements, to addition

Arjun D Desai, Batu M Ozturkler, Christopher M Sandino, Robert Boutin

Deep learning (DL) has shown promise for faster, high quality accelerated MRI reconstruction. However, supervised DL methods depend on extensive amounts of fully-sampled (labeled) data and are sensitive to out-of-distribution (OOD) shifts, particularly low signal-to-noise ratio (SNR) acquisitions. To alleviate this challenge, we propose Noise2Recon, a model-

Rong Duan, Joseph N. Mastron, Yin Song, Kevin J. Kubarych

Strong coupling between vibrational transitions in molecules within a resonant optical microcavity leads to the formation of collective, delocalized vibrational polaritons. There are many potential applications of "polaritonic chemistry," ranging from modified chemical reactivity to quantum in-formation processing. One challenge in obtaining the pola

Lisette Espín-Noboa, Claudia Wagner, Markus Strohmaier, Fariba Karimi

Though algorithms promise many benefits including efficiency, objectivity and accuracy, they may also introduce or amplify biases. Here we study two well-known algorithms, namely PageRank and Who-to-Follow (WTF), and show to what extent their ranks produce inequality and inequity when applied to directed social networks. To this end, we propose a directed ne

Futoon M. Abushaqra, Hao Xue, Yongli Ren, Flora D. Salim

Heterogeneity and irregularity of multi-source data sets present a significant challenge to time-series analysis. In the literature, the fusion of multi-source time-series has been achieved either by using ensemble learning models which ignore temporal patterns and correlation within features or by defining a fixed-size window to select specific parts of the

Cagri Toraman, Furkan Şahinuç, Eyup Halit Yilmaz

After George Floyd's death in May 2020, the volume of discussion in social media increased dramatically. A series of protests followed this tragic event, called as the 2020 BlackLivesMatter movement. Eventually, many user accounts are deleted by their owners or suspended due to violating the rules of social media platforms. In this study, we analyze what

Weize Zhang, Peyman Yadmellat, Zhiwei Gao

Motion planning is one of the key modules in autonomous driving systems to generate trajectories for self-driving vehicles to follow. A common motion planning approach is to generate trajectories within semantic safe corridors. The trajectories are generated by optimizing parametric curves (e.g. Bezier curves) according to an objective function. To guarantee

Hakan Guler

We study the bar-and-joint frameworks in $\mathbb{R}^2$ such that some vertices are constrained to lie on some lines. The generic rigidity of such frameworks is characterised by Streinu and Theran (2010). Katoh and Tanigawa (2013) remarked that the corresponding matroid and its rank function can be characterised by using a submodular function. In this paper,

Moncef Gabbouj, Serkan Kiranyaz, Junaid Malik, Muhammad Uzair Zahid

Although numerous R-peak detectors have been proposed in the literature, their robustness and performance levels may significantly deteriorate in low-quality and noisy signals acquired from mobile electrocardiogram (ECG) sensors, such as Holter monitors. Recently, this issue has been addressed by deep 1-D convolutional neural networks (CNNs) that have achiev

Brandon Smock, Rohith Pesala, Robin Abraham

Recently, significant progress has been made applying machine learning to the problem of table structure inference and extraction from unstructured documents. However, one of the greatest challenges remains the creation of datasets with complete, unambiguous ground truth at scale. To address this, we develop a new, more comprehensive dataset for table extrac

Xi Jiang, Noah Apthorpe

Consumer Internet of things research often involves collecting network traffic sent or received by IoT devices. These data are typically collected via crowdsourcing or while researchers manually interact with IoT devices in a laboratory setting. However, manual interactions and crowdsourcing are often tedious, expensive, inaccurate, or do not provide compreh

Mahnaz Asghari, Ahmad Sheykhi

Taking into account a fractal structure for the black hole horizon, Barrow argued that the area law of entropy is modified due to quantum-gravitational effects (Barrow in Phys Lett B 808:135643, https://doi.org/10.1016/j.physletb.2020.135643, 2020). Accordingly, the corrected entropy takes the form $S \sim A^{1+\mathrmΔ/2}$, where $0\leq\mathrmΔ\leq1$, indic

Erik D. Demaine, Maarten Löffler, Christiane Schmidt

Spiral Galaxies is a pencil-and-paper puzzle played on a grid of unit squares: given a set of points called centers, the goal is to partition the grid into polyominoes such that each polyomino contains exactly one center and is 180° rotationally symmetric about its center. We show that this puzzle is NP-complete, ASP-complete, and #P-complete even if (a) all

Stephan Baier, Esrafil Ali Molla, with an appendix by Arijit Ganguly

In the thirties of the last century, I. M. Vinogradov established uniform distribution modulo 1 of the sequence $pα$ when $α$ is a fixed irrational real number and $p$ runs over the primes. In particular, he showed that the inequality $||pα||\le p^{-1/5+\varepsilon}$ has infinitely prime solutions $p$, where $||.||$ denotes the distance to the nearest intege

Yan Luo, Yongkang Wong, Mohan S. Kankanhalli, Qi Zhao

Understanding the trustworthiness of a prediction yielded by a classifier is critical for the safe and effective use of AI models. Prior efforts have been proven to be reliable on small-scale datasets. In this work, we study the problem of predicting trustworthiness on real-world large-scale datasets, where the task is more challenging due to high-dimensiona

Giuseppe Calajo, Darrick E. Chang

Solitons are known to occur in the context of atom-light interaction via the well-known semi-classical phenomenon of self-induced transparency (SIT). Separately, in the regime where both light and atoms are fully treated quantum mechanically, quantum few-photon bound states are known to be a ubiquitous phenomenon that arises in different systems such as atom

João Azevedo, Pavel Shumyatsky

If $K$ is a closed subgroup of a compact group $G$, the probability that randomly chosen pair of elements from $K$ and $G$ commute is denoted by $Pr(K,G)$. Say that a subgroup $K\leq G$ is $ε$-central in $G$ if $Pr(\langle g \rangle,G)\geq ε$ for any $g$ in $K$. Here $\langle g \rangle$ denotes the monothetic subgroup generated by $g\in G$. Our main result i

Oskar Grocholski, Bernard Pire, Paweł Sznajder, Lech Szymanowski

We calculate in the framework of collinear factorization the amplitude for the photoproduction of a near forward large mass diphoton at leading twist and next to leading order (NLO) in $α_s$. We demonstrate the validity of factorization at this order, which was never achieved for such a reaction where the coefficient function describes a $2 \to 3$ hard proce

Arjit Jain, Pranay Reddy Samala, Deepak Mittal, Preethi Jyoti

Time masking has become a de facto augmentation technique for speech and audio tasks, including automatic speech recognition (ASR) and audio classification, most notably as a part of SpecAugment. In this work, we propose SpliceOut, a simple modification to time masking which makes it computationally more efficient. SpliceOut performs comparably to (and somet

Kyle R. Williams, Rachel Schlossman, Daniel Whitten, Joe Ingram

This paper presents a technique for trajectory planning based on continuously parameterized high-level actions (motion primitives) of variable duration. This technique leverages deep reinforcement learning (Deep RL) to formulate a policy which is suitable for real-time implementation. There is no separation of motion primitive generation and trajectory plann

Yuta Kurose

This study presents contemporaneous modeling of asset return and price range within the framework of stochastic volatility with leverage. A new representation of the probability density function for the price range is provided, and its accurate sampling algorithm is developed. A Bayesian estimation using Markov chain Monte Carlo (MCMC) method is provided for

Sayantan Khan

We provide evidence both for and against a conjectural analogy between geometrically finite infinite covolume Fuchsian groups and the mapping class group of compact non-orientable surfaces. In the positive direction, we show the complement of the limit set is open and dense. Moreover, we show that the limit set of the mapping class group contains the set of

Christian Bingane, Charles Audet

A small polygon is a polygon of unit diameter. The maximal width of an equilateral small polygon with $n=2^s$ vertices is not known when $s \ge 3$. This paper solves the first open case and finds the optimal equilateral small octagon. Its width is approximately $3.24\%$ larger than the width of the regular octagon: $\cos(π/8)$. In addition, the paper propose

Turgay Pamuklu, Shahram Mollahasani, Melike Erol-Kantarci

The radio access network (RAN) part of the next-generation wireless networks will require efficient solutions for satisfying low latency and high-throughput services. The open RAN (O-RAN) is one of the candidates to achieve this goal, in addition to increasing vendor diversity and promoting openness. In the O-RAN architecture, network functions are executed

Connor Hayden-Pawson, Mirko Curti, Roberto Maiolino, Michele Cirasuolo

We present a comparison of the nitrogen-to-oxygen ratio (N/O) in 37 high-redshift galaxies at $z\sim$2 taken from the KMOS Lensed Emission Lines and VElocity Review (KLEVER) Survey with a comparison sample of local galaxies, taken from the Sloan Digital Sky Survey (SDSS). The KLEVER sample shows only a mild enrichment in N/O of $+$0.1 dex when compared to lo

Mayank Sethi, Ambika Sadhu, Khushbu Pahwa, Sargun Nagpal

The severity of the coronavirus pandemic necessitates the need of effective administrative decisions. Over 4 lakh people in India succumbed to COVID-19, with over 3 crore confirmed cases, and still counting. The threat of a plausible third wave continues to haunt millions. In this ever changing dynamic of the virus, predictive modeling methods can serve as a

Nick Choksi, Eugene Chiang

Gaps imaged in protoplanetary discs are suspected to be opened by planets. We compute the present-day mass accretion rates $\dot{M}_{\rm p}$ of seven hypothesized gap-embedded planets, plus the two confirmed planets in the PDS 70 disc. The accretion rates are based on disc gas surface densities $Σ_{\rm gas}$ from C$^{18}$O observations, and planet masses $M_

Paz Beniamini, Pawan Kumar, Ramesh Narayan

We describe how the observed polarization properties of an astronomical object are related to its intrinsic polarization properties and the finite temporal and spectral resolutions of the observing device. Moreover, we discuss the effect that a scattering screen, with non-zero magnetic field, between the source and observer has on the observed polarization p

Guillermo Lara, Sebastian H. Völkel, Enrico Barausse

The observation of the shadow of the supermassive black hole M87$^{*}$ by the Event Horizon Telescope (EHT) is sensitive to the spacetime geometry near the circular photon orbit and beyond, and it thus has the potential to test general relativity in the strong field regime. Obstacles to this program, however, include degeneracies between putative deviations

Diptimoy Ghosh, Atanu Guha, Divya Sachdeva

We derive new constraints on combination of dark matter - electron cross-section ($σ_{χe}$) and dark matter - neutrino cross-section ($σ_{χν}$) utilising the gain in kinetic energy of the dark matter (DM) particles due to scattering with the cosmic ray electrons and the diffuse supernova neutrino background (DSNB). Since the flux of the DSNB neutrinos is com

Adrian S. Hamers, Hila Glanz, Patrick Neunteufel

In compact stellar triple systems, an evolved tertiary star can overflow its Roche lobe around the inner binary. Subsequently, the tertiary star can transfer mass to the inner binary in a stable manner, or Roche lobe overflow (RLOF) can be unstable and lead to common-envelope (CE) evolution. In the latter case, the inner binary enters the extended envelope o

George Stein, Jacqueline Blaum, Peter Harrington, Tomislav Medan

We employ self-supervised representation learning to distill information from 76 million galaxy images from the Dark Energy Spectroscopic Instrument Legacy Imaging Surveys' Data Release 9. Targeting the identification of new strong gravitational lens candidates, we first create a rapid similarity search tool to discover new strong lenses given only a sin

Ciro Pappalardo, George J. Bendo, Mederic Boquien, Maarten Baes

In recent years, significant growth in the amount of data available to astronomers has opened up the possibility to uncover fundamental correlations, linking the dust component of a galaxy to its star formation rate (SFR). In this paper, we re-examine these correlations, investigating the origin of the observed scatter, and the ability of the James Webb Spac

Debasish Borah, Manoranjan Dutta, Satyabrata Mahapatra, Narendra Sahu

We propose a self-interacting dark matter (DM) scenario with right handed neutrino (RHN) portal to the standard model (SM). The dark sector consists of a particle DM, assumed to be a Dirac fermion, and a light mediator in terms of a dark Abelian vector boson to give rise to the required velocity dependent self-interactions in agreement with astrophysical obs

Lilia Correa Magnus, Eugene Vasiliev

The ongoing interaction between the Milky Way (MW) and its largest satellite - the Large Magellanic Cloud (LMC) - creates a significant perturbation in the distribution and kinematics of distant halo stars, globular clusters and satellite galaxies, and leads to biases in MW mass estimates from these tracer populations. We present a method for compensating th

Ramanjit Sohal, Laimei Nie, Xiao-Qi Sun, Eduardo Fradkin

We investigate the thermalization of Sachdev-Ye-Kitaev (SYK) models coupled via random interactions following quenches from the perspective of entanglement. Previous studies have shown that when a system of two SYK models coupled by random two-body terms is quenched from the thermofield double state with sufficiently low effective temperature, the Rényi entr

Guido D'Amico, Leonardo Senatore, Pierre Zhang, Takahiro Nishimichi

Former analyses of the BOSS data using the Effective Field Theory of Large-Scale Structure (EFTofLSS) have measured that the largest counterterms are the redshift-space distortion ones. This allows us to adjust the power-counting rules of the theory, and to explicitly identify that the leading next-order terms have a specific dependence on the cosine of the

Azadeh Moradinezhad Dizgah, Garrett K. Keating, Kirit S. Karkare, Abigail Crites

Line intensity mapping (LIM) is emerging as a powerful technique to map the cosmic large-scale structure and to probe cosmology over a wide range of redshifts and spatial scales. We perform Fisher forecasts to determine the optimal design of wide-field ground-based mm-wavelength LIM surveys for constraining properties of neutrinos and light relics. We consid

Benjamin R. Roulston, Paul J. Green, Rodolfo Montez, Joseph Filippazzo

As main-sequence stars with C$>$O, dwarf carbon (dC) stars are never born alone but inherit carbon-enriched material from a former asymptotic giant branch (AGB) companion. In contrast to M dwarfs in post-mass transfer binaries, C$_2$ and/or CN molecular bands allow dCs to be identified with modest-resolution optical spectroscopy, even after the AGB remnant h

Daniel J. Whalen, Mar Mezcua, Samuel J. Patrick, Avery Meiksin

Direct-collapse black holes (DCBHs) forming at $z \sim$ 20 are currently the leading candidates for the seeds of the first quasars, over 200 of which have now been found at $z >$ 6. Recent studies suggest that DCBHs could be detected in the near infrared by the James Webb Space Telescope, Euclid, and the Roman Space Telescope. However, new radio telescopes w

Mirjam Cvetic, Ling Lin, Andrew P. Turner

We argue for the quantum-gravitational inconsistency of certain 6d $\mathcal{N}=(1,0)$ supergravity theories, whose anomaly-free gauge algebra $\mathfrak{g}$ and hypermultiplet spectrum $M$ were observed in arxiv:2012.01437 to be realizable only as part of a larger gauge sector $(\mathfrak{g}' \supset \mathfrak{g}, M' \supset M)$ in F-theory. To deta

Mikhail M. Ivanov, Oliver H. E. Philcox, Marko Simonović, Matias Zaldarriaga

Non-linear redshift-space distortions ("fingers of God") are challenging to model analytically, a fact that limits the applicability of perturbation theory in redshift space as compared to real space. We show how this problem can be mitigated using a new observable, $Q_0$, which can be easily estimated from the redshift space clustering data and is a

Michael J. Baker, Moritz Breitbach, Joachim Kopp, Lukas Mittnacht

Primordial black holes could potentially form during a first-order cosmological phase transition due to a build-up of particles which are predominantly reflected from the advancing bubble walls. After discussing the general mechanism, we examine the criteria that need to be satisfied for a black hole to form. We then set out the Boltzmann equation that descr

Juven Wang

Discrete spacetime symmetries of parity P or reflection R, and time-reversal T, act naively as $\mathbb{Z}_2$-involutions in the passive transformation on the spacetime coordinates; but together with a charge conjugation C, the total C-P-R-T symmetries have enriched active transformations on fields in representations of the spacetime-internal symmetry groups

Ryota Takaku, Qi Wen, Scott Cray, Mark Devlin

We fabricated a 302 mm diameter low-pass filter made of alumina that has an anti-reflection coating (ARC) made with laser-ablated sub-wavelength structures (SWS). The filter has been integrated into and is operating with the MUSTANG2 instrument, which is coupled to the Green Bank Telescope. The average transmittance of the filter in the MUSTANG2 operating ba

Yang-Ting Chien, Abhay Deshpande, Mriganka Mouli Mondal, George Sterman

We study nonperturbative flavor correlations between pairs of leading and next-to-leading charged hadrons within jets at the Electron-Ion Collider (EIC). We introduce a charge correlation ratio observable $r_c$ that distinguishes same- and opposite-sign charged pairs. Using Monte Carlo simulations with different event generators, $r_c$ is examined as a funct

Jay Patravali, Gaurav Mittal, Ye Yu, Fuxin Li

We present MetaUVFS as the first Unsupervised Meta-learning algorithm for Video Few-Shot action recognition. MetaUVFS leverages over 550K unlabeled videos to train a two-stream 2D and 3D CNN architecture via contrastive learning to capture the appearance-specific spatial and action-specific spatio-temporal video features respectively. MetaUVFS comprises a no

Azita Pourkabirian, Melika Habibian, Azadeh Pourkabirian

This study aims to examine the impact of electronic word-of-mouth (eWoM) marketing on branding attitudes in social networks. Specifically, we investigate the effects of eWoM activities on brand awareness, brand destruction, branding, brand image, and brand competition. To gather data, we conducted a survey among followers of the Vizland shoe page on the Inst

Stephen J. Naus, Jiong Qiu, C. Richard DeVore, Spiro K. Antiochos

We analyze the structure and evolution of ribbons from the M7.3 SOL2014-04-18T13 flare using ultraviolet (UV) images from IRIS and SDO/AIA, magnetic data from SDO/HMI, hard X-ray (HXR) images from RHESSI, and light curves from Fermi/GBM, in order to infer properties of coronal magnetic reconnection. As the event progresses, two flare ribbons spread away from

Alexandre de Faveri

Let $f \in S_k(Γ_1(N))$ be a primitive holomorphic form of arbitrary weight $k$ and level $N$. We show that the completed $L$-function of $f$ has $Ω\left(T^δ\right)$ simple zeros with imaginary part in $\left[-T, T\right]$, for any $δ< \frac{2}{27}$. This is the first power bound in this problem for $f$ of non-trivial level, where previously the best results

Benjamin Ayton, Masataro Asai

Width-based planning has shown promising results on Atari 2600 games using pixel input, while using substantially fewer environment interactions than reinforcement learning. Recent width-based approaches have computed feature vectors for each screen using a hand designed feature set or a variational autoencoder trained on game screens (VAE-IW), and prune scr

Joe A. Smith, Jorge Monroy-Ruz, Pisu Jiang, John G. Rarity

While grating couplers have become the de-facto standard for optical access to integrated silicon photonics platforms, their performance at visible wavelengths, in moderate index contrast platforms like silicon nitride, leaves significant room for improvement. In particular, the index contrast governs the diffraction efficiency per grating tooth and the resu

Michael Arcidiacono, David Ryan Koes

Recent advances in machine learning have enabled generative models for both optimization and de novo generation of drug candidates with desired properties. Previous generative models have focused on producing SMILES strings or 2D molecular graphs, while attempts at producing molecules in 3D have focused on reinforcement learning (RL), distance matrices, and

Shang-Qiang Ning, Yang Qi, Zheng-Cheng Gu, Chenjie Wang

It is well known that two-dimensional fermionic systems with a nonzero Chern number must break the time reversal symmetry, manifested by the appearance of chiral edge modes on an open boundary. Such an incompatibility between topology and symmetry can occur more generally. We will refer to this phenomenon as enforced symmetry breaking by topological orders.

Pei Zeng, Jinzhao Sun, Xiao Yuan

Quantum cooling, a deterministic process that drives any state to the lowest eigenstate, has been widely used from studying ground state properties of chemistry and condensed matter quantum physics, to general optimization problems. However, the cooling procedure is generally non-unitary, hence its realization on a quantum computer either requires deep circu

F. C. E. Lima, A. Yu. Petrov, C. A. S. Almeida

In this work, a possible description for quantum dynamics of the cuscuton within the sigma-model approach is presented. Lower order perturbative corrections and the structure of divergences are found. Motivated by the results generated by the perturbative approach, we investigate the existence of topological structures in the cuscuton-like model. The structu

Yu-Chen Liu, Xu-Guang Huang

We derive a Cooper-Frye type spin polarization formula for Dirac fermions at local thermal equilibrium described by a grand canonical ensemble specified by temperature, fluid velocity, chemical potential, and spin potential. We discuss the physical meaning of different contributions to spin polarization and compare them with previous works. The present formu

Binbin Xu, Lingni Ma, Yuting Ye, Tanner Schmidt

Neural shape models can represent complex 3D shapes with a compact latent space. When applied to dynamically deforming shapes such as the human hands, however, they would need to preserve temporal coherence of the deformation as well as the intrinsic identity of the subject. These properties are difficult to regularize with manually designed loss functions.

Daniel Massatt, Stephen Carr, Mitchell Luskin

Momentum space transformations for incommensurate 2D electronic structure calculations are fundamental for reducing computational cost and for representing the data in a more physically motivating format, as exemplified in the Bistritzer-MacDonald model. However, these transformations can be difficult to implement in more complex systems such as when mechani

Benjamin Bisping, David N. Jansen, Uwe Nestmann

We introduce a generalization of the bisimulation game that finds distinguishing Hennessy-Milner logic formulas from every finitary, subformula-closed language in van Glabbeek&#39;s linear-time--branching-time spectrum between two finite-state processes. We identify the relevant dimensions that measure expressive power to yield formulas belonging to the coar

Udit Khanna, Moshe Goldstein, Yuval Gefen

Chiral gapless boundary modes are characteristic of quantum Hall (QH) states. For hole-conjugate fractional QH phases counterpropagating edge modes (upstream and downstream) are expected. In the presence of electrostatic interactions and disorder these modes may renormalize into charge and upstream neutral modes. Orthodox models of Laughlin phases anticipate

Borna Bešić, Nikhil Gosala, Daniele Cattaneo, Abhinav Valada

Scene understanding is a pivotal task for autonomous vehicles to safely navigate in the environment. Recent advances in deep learning enable accurate semantic reconstruction of the surroundings from LiDAR data. However, these models encounter a large domain gap while deploying them on vehicles equipped with different LiDAR setups which drastically decreases

Zhen Qin, Le Yan, Yi Tay, Honglei Zhuang

We explore a novel perspective of knowledge distillation (KD) for learning to rank (LTR), and introduce Self-Distilled neural Rankers (SDR), where student rankers are parameterized identically to their teachers. Unlike the existing ranking distillation work which pursues a good trade-off between performance and efficiency, SDR is able to significantly improv

Pablo Candela, Diego González-Sánchez, Balázs Szegedy

In this paper, the nilspace approach to higher-order Fourier analysis is developed in the setting of vector spaces over a prime field $\mathbb{F}_p$, with applications mainly in ergodic theory. A key requisite for this development is to identify a class of nilspaces adequate for this setting. We introduce such a class, whose members we call $p$-homogeneous n

Shi-Zhong Du

In this paper, we study the planar Lp-Minkowski problem for all p, which was introduced by Lutwak [23]. A detailed exploration on solvability and uniqueness will be presented.

Thomas Dick, Stephan Schmidt, Nicolas R. Gauger

On the one hand, Sobolev gradient smoothing can considerably improve the performance of aerodynamic shape optimization and prevent issues with regularity. On the other hand, Sobolev smoothing can also be interpreted as an approximation for the shape Hessian. This paper demonstrates, how Sobolev smoothing, interpreted as a shape Hessian approximation, offers

Wenqi Ke, Pietro Slavich

The prediction for the quartic coupling of the SM-like Higgs boson constrains the parameter space of SUSY models, even in scenarios where all of the new-particle masses are above the scale probed so far by the LHC. We study the implications of the Higgs-mass prediction on a recently-proposed SUSY model that features two pairs of Higgs doublets, and provides

Megan Cowie, Rikke Plougmann, Zeno Schumacher, Peter Grütter

In this work, we experimentally demonstrate two-state fluctuations in a metal-insulator-semiconductor (MIS) device formed out of a metallic atomic force microscopy tip, vacuum gap, and multilayer MoSe$_2$ sample. We show that noise in this device is intrinsically bias-dependent due to the bias-dependent surface potential, and does not require that the freque

Jungang Zou, Fan Lin, Siyu Gao, Gaoshan Deng

Dynamic community detection is the hotspot and basic problem of complex network and artificial intelligence research in recent years. It is necessary to maximize the accuracy of clustering as the network structure changes, but also to minimize the two consecutive clustering differences between the two results. There is a trade-off relationship between these

Xiaoxing Wang, Xiangxiang Chu, Junchi Yan, Xiaokang Yang

Neural architecture search (NAS) has been an active direction of automatic machine learning (Auto-ML), aiming to explore efficient network structures. The searched architecture is evaluated by training on datasets with fixed data augmentation policies. However, recent works on auto-augmentation show that the suited augmentation policies can vary over differe

Benjamin Attal, Eliot Laidlaw, Aaron Gokaslan, Changil Kim

Neural networks can represent and accurately reconstruct radiance fields for static 3D scenes (e.g., NeRF). Several works extend these to dynamic scenes captured with monocular video, with promising performance. However, the monocular setting is known to be an under-constrained problem, and so methods rely on data-driven priors for reconstructing dynamic con

Laura Eslava, Bas Lodewijks, Marcel Ortgiese

A weighted recursive tree is an evolving tree in which vertices are assigned random vertex-weights and new vertices connect to a predecessor with a probability proportional to its weight. Here, we study the maximum degree and near-maximum degrees in weighted recursive trees when the vertex-weights are almost surely bounded and their distribution function sat

Aarti Tiwari, Nitish Govindarajan, Hendrik H. Heenen, Anton Bjørnlund

Understanding CO electro-oxidation is crucial towards designing catalysts for electrochemically oxidizing complex organic molecules. Earth-abundant Copper (Cu) has recently been demonstrated to exhibit high alkaline CO electro-oxidation activity, rivaling the previously acclaimed Gold (Au). Herein, we combine single crystal rotating disc electrode (RDE) expe

Yung-Chung Chiu, Hsueh-I Lu

For vertices $u$ and $v$ of an $n$-vertex graph $G$, a $uv$-trail of $G$ is an induced $uv$-path of $G$ that is not a shortest $uv$-path of $G$. Berger, Seymour, and Spirkl [Discrete Mathematics 2021] gave the previously only known polynomial-time algorithm, running in $O(n^{18})$ time, to either output a $uv$-trail of $G$ or ensure that $G$ admits no $uv$-t

Raphael Trumpp, Harald Bayerlein, David Gesbert

Reliable pedestrian crash avoidance mitigation (PCAM) systems are crucial components of safe autonomous vehicles (AVs). The nature of the vehicle-pedestrian interaction where decisions of one agent directly affect the other agent&#39;s optimal behavior, and vice versa, is a challenging yet often neglected aspect of such systems. We address this issue by mode

Valérie Vallet, Jonathan Coles, Florent Réal, Céline Houriez

We investigated isolated sodium/chloride aqueous droplets at the microscopic level, which comprise from about 5k to 1M water molecules and whose salt concentrations are 0.2$m$ (brackish water) and 0.6$m$ (sea water), by means of molecular dynamics simulations based on an \emph{ab initio}-based polarizable force field. The size of our largest droplets is at t

Joan Verdera

We prove persistence of the regularity of the boundary of vortex patches for a large class of transport equations in the plane. The velocity field is given by convolution of the vorticity with an odd kernel, homogeneous of degree $-1$ and of class $C^2$ off the origin.

Kevin P. Josey, Priyanka deSouza, Xiao Wu, Danielle Braun

Numerous studies have examined the associations between long-term exposure to fine particulate matter (PM2.5) and adverse health outcomes. Recently, many of these studies have begun to employ high-resolution predicted PM2.5 concentrations, which are subject to measurement error. Previous approaches for exposure measurement error correction have either been a

Giovanni E. Comi, Daniel Spector, Giorgio Stefani

We continue the study of the fractional variation following the distributional approach developed in the previous works arXiv:1809.08575, arXiv:1910.13419 and arXiv:2011.03928. We provide a general analysis of the distributional space $BV^{α,p}(\mathbb{R}^n)$ of $L^p$ functions, with $p\in[1,+\infty]$, possessing finite fractional variation of order $α\in(0,

Alan J. Aw, Jeffrey P. Spence, Yun S. Song

In scientific studies involving analyses of multivariate data, basic but important questions often arise for the researcher: Is the sample exchangeable, meaning that the joint distribution of the sample is invariant to the ordering of the units? Are the features independent of one another, or perhaps the features can be grouped so that the groups are mutuall

Dingzhu Wen, Ki-Jun Jeon, Kaibin Huang

Federated learning (FL) is a popular framework for training an AI model using distributed mobile data in a wireless network. It features data parallelism by distributing the learning task to multiple edge devices while attempting to preserve their local-data privacy. One main challenge confronting practical FL is that resource constrained devices struggle wi