July 2022 arXiv papers — page 83

Hongbin Yang, Andrea Konečná, Xianghan Xu, Sang-Wook Cheong

Doping inhomogeneities in solids are not uncommon, but their microscopic observation and understanding are limited due to the lack of bulk-sensitive experimental techniques with high-enough spatial and spectral resolution. Here, we demonstrate nanoscale imaging of both dopants and free charge carriers in La-doped BaSnO3 (BLSO) using high-resolution electron

Teng Hu, Vikram Khaire, Joseph F. Hennawi, Michael Walther

We present a new approach to measure the power-law temperature density relationship $T=T_0 (\rho / \bar{\rho})^{\gamma -1}$ and the UV background photoionization rate $\Gamma_{\rm HI}$ of the IGM based on the Voigt profile decomposition of the Ly$\alpha$ forest into a set of discrete absorption lines with Doppler parameter $b$ and the neutral hydrogen column

Tianjun Zhang, Tongzheng Ren, Mengjiao Yang, Joseph E. Gonzalez

It is common to address the curse of dimensionality in Markov decision processes (MDPs) by exploiting low-rank representations. This motivates much of the recent theoretical study on linear MDPs. However, most approaches require a given representation under unrealistic assumptions about the normalization of the decomposition or introduce unresolved computati

Madonna Mayez, Khaled Nagaty, Abeer Hamdy

Bug triage is an essential task in software maintenance phase. It assigns developers (fixers) to bug reports to fix them. This process is performed manually by a triager, who analyzes developers profiles and submitted bug reports to make suitable assignments. Bug triaging process is time consuming thus automating this process is essential to improve the qual

Avval Amil, Shashank Gupta

Random numbers are critical for any cryptographic application. However, the data that is flowing through the internet is not secure because of entropy deprived pseudo random number generators and unencrypted IoTs. In this work, we address the issue of lesser entropy of several data formats. Specifically, we use the large information space associated with the

Duo Zeng

In this paper we generalize a shift theorem, which plays a key role in studying representations of FI$^m$, the product category of the category of finite sets and injections, and classify finitely generated injective FI$^m$-modules over a field of characteristic 0.

Yossef Zenati, Qinan Wang, Alexey Bobrick, Lindsay DeMarchi

We present multi-band ATLAS photometry for SN 2019tsf, a stripped-envelope Type Ib supernova (SESN). The SN shows a triple-peaked light curve and a late (re-)brightening, making it unique among stripped-envelope systems. The re-brightening observations represent the latest photometric measurements of a multi-peaked Type Ib SN to date. As late-time photometry

Xin Zheng, Jonathan Dolde, Matthew C. Cambria, Hong Ming Lim

Einstein's theory of general relativity predicts that a clock at a higher gravitational potential will tick faster than an otherwise identical clock at a lower potential, an effect known as the gravitational redshift. Here we perform a laboratory-based, blinded test of the gravitational redshift using differential clock comparisons within an evenly spaced ar

Matthäus Schulik, Richard Booth

We present a new 1-D multi-physics simulation code with use cases intended for, but not limited to, hydrodynamic escapeproblems of planetary atmospheres and planetary accretion models. Our formulation treats an arbitrary number of species asseparated hydrodynamic fields, couples them via friction laws, allows for a multi-band flux-limited radiation transport

Delia Kesner, Loïc Peyrot, Daniel Ventura

We define and study a term calculus implementing higher-order node replication. It is used to specify two different (weak) evaluation strategies: call-by-name and fully lazy call-by-need, that are shown to be observationally equivalent by using type theoretical technical tools.

Shouvik Roy Choudhury, Steen Hannestad, Thomas Tram

Certain inflationary models like Natural inflation (NI) and Coleman-Weinberg inflation (CWI) are disfavoured by cosmological data in the standard $\Lambda\textrm{CDM}+r$ model (where $r$ is the scalar-to-tensor ratio), as these inflationary models predict the regions in the $n_s-r$ parameter space that are excluded by the cosmological data at more than 2$\si

Carlota Andres, Fabio Dominguez, Andrey V. Sadofyev, Carlos A. Salgado

In this work, we obtain the leading corrections to the jet momentum broadening distribution in a QCD medium arising from the transverse flow of the matter. We first derive the single-particle propagator of a highly energetic parton resumming its multiple interactions with the homogeneous flowing matter, explicitly keeping the leading subeikonal flow terms. T

E. Laos, J. P. Wisniewski, M. J. Kuchner, S. M. Silverberg

We present Chandra X-ray observations of 6 previously-identified Peter Pan objects, rare 40 Myr systems with evidence of primordial disk retention. We observe X-ray luminosities (0.8-3.0 keV) ranging from log Lx 27.7-29.1. We find that our Peter Pan sample exhibits X-ray properties similar to that of weak-lined T-Tauri stars and do not exhibit evidence of st

Filip Huško, Cedric G. Lacey, Carlton M. Baugh

We use the GALFORM semi-analytical model of galaxy formation and the Planck-Millennium simulation to investigate the origins of stellar mass in galaxies and their spheroids. We compare the importance of mergers and disc instabilities, as well as the starbursts that they trigger. We find that the fraction of galaxy stellar mass formed \textit{ex situ} ($f_\ma

Joydeep Chakravarty, Ashoke Sen

We compute the normalization of the D-instanton amplitudes in type 0B string theory in two dimensions and find perfect agreement with the dual matrix model result.

Lu Shen, Brian C. Lemaux, Lori M. Lubin, Guilin Liu

We present the radio properties of 66 spectroscopically-confirmed normal star-forming galaxies (SFGs) at $4.4<z<5.9$ in the COSMOS field that were [C II] detected in the Atacama Large Millimeter Array (ALMA) Large Program to INvestigate [C II] at Early times (ALPINE). We separate these galaxies ("CII-detected-all") into lower redshift ("CII-detected-lz", $\l

Brian D. Metzger

We present a toy model for the thermal optical/UV/X-ray emission from tidal disruption events (TDE). Motivated by recent hydrodynamical simulations, we assume the debris streams promptly and rapidly circularize (on the orbital period of the most tightly bound debris), generating a hot quasi-spherical pressure-supported envelope of radius R_v ~ 1e14 cm (photo

Fabrizio Del Monte, Pietro Longhi

We show that TBA equations defined by the BPS spectrum of $5d$ $\mathcal{N}=1$ $SU(2)$ Yang-Mills on $S^1\times \mathbb{R}^4$ encode the q-Painlev\'e III$_3$ equation. We find a fine-tuned stratum in the physical moduli space of the theory where solutions to TBA equations can be obtained exactly, and verify that they agree with the algebraic solutions to q-P

Oscar J. C. Dias, Prahar Mitra, Jorge E. Santos

We do a systematic search of supergravity solutions that, via the AdS$_5$/CFT$_4$ correspondence, are dual to thermal states in $\mathcal{N}=4$ SYM at finite chemical potential. These solutions dominate the microcanonical ensemble and are required to ultimately reproduce the microscopic entropy of AdS black holes. Using a mix of analytical and numerical meth

Gaopei Pan, Hongyu Lu, Heqiu Li, Xu Zhang

While the ground state phase diagram of the correlated flat-band systems have been intensively investigated, the dynamic and thermodynamic properties of such lattice models are less explored, but it is the latter which is most relevant to the experimental probes (transport, quantum capacitance and spectroscopy) of the quantum moir\'e materials such as twiste

Alexandre Serantes, Benjamin Withers

Given a set of sources and one-point function data for a Lorentzian holographic QFT, does the Fefferman-Graham expansion converge? If it does, what sets the radius of convergence, and how much of the interior of the spacetime can be reconstructed using this expansion? As a step towards answering these questions we consider real analytic CFT data, where in th

Ahana Chakraborty, Michele Pini, Martina S. Zündel, Francesco Piazza

How are two-body scattering and the resulting collective phenomena affected by preparing the mediator of interactions in different quantum states? This question has recently become experimentally relevant in a specific non-relativistic version of QED implemented within materials, where standard techniques of quantum optics are available for the preparation o

Rostom Mbarek, Damiano Caprioli, Kohta Murase

We present a bottom-up calculation of the flux of ultra-high energy cosmic rays (UHECRs) and high-energy neutrinos produced by powerful jets of active galactic nuclei (AGNs). By propagating test particles in 3D relativistic magnetohydrodynamic jet simulations, including a Monte Carlo treatment of sub-grid pitch-angle scattering and attenuation losses due to

Pieter van Dokkum, Zili Shen, Aaron J. Romanowsky, Roberto Abraham

It was recently proposed that the dark matter-deficient ultra-diffuse galaxies DF2 and DF4 in the NGC1052 group could be the products of a "bullet dwarf" collision between two gas-rich progenitor galaxies. In this model DF2 and DF4 formed at the same time in the immediate aftermath of the collision, and a strong prediction is that their globular clusters sho

Seth Musser, T. Senthil

We study theoretically the quantum phase transition from a metal to a Wigner-Mott insulator at fractional commensurate filling on a two-leg ladder. We show that a continuous transition out of a symmetry-preserving Luttinger liquid metal is possible where the onset of insulating behavior is accompanied by the breaking of the lattice translation symmetry. At f

Kartiek Agarwal

Materials hosting topologically protected non-Abelian zero modes offer the exciting possibility of storing and manipulating quantum information in a manner that is protected from decoherence at the hardware level. In this work, we study the possibility of realizing such excitations along line defects in certain fractional quantum Hall states in multi-valley

Graciela B. Gelmini, Anna Simpson, Edoardo Vitagliano

Axion-like particles (ALPs), a compelling candidate for dark matter (DM), are the pseudo Nambu-Goldstone bosons of a spontaneously and explicitly broken global $U(1)$ symmetry. When the symmetry breaking happens after inflation, the ALP cosmology predicts the formation of a string-wall network which must annihilate early enough, producing gravitational waves

Vasily Kokorev, Gabriel Brammer, Seiji Fujimoto, Kotaro Kohno

We present a set of multi-wavelength mosaics and photometric catalogs in the ALMA lensing cluster survey (ALCS) fields. The catalogs were built by reprocessing of archival data from the CHArGE compilation, taken by the $\textit{Hubble Space Telescope}$ ($\textit{HST}$) in the RELICS, CLASH and Hubble Frontier Fields. Additionally we have reconstructed the $\

Xiaoyi Dong, Jianmin Bao, Ting Zhang, Dongdong Chen

We propose bootstrapped masked autoencoders (BootMAE), a new approach for vision BERT pretraining. BootMAE improves the original masked autoencoders (MAE) with two core designs: 1) momentum encoder that provides online feature as extra BERT prediction targets; 2) target-aware decoder that tries to reduce the pressure on the encoder to memorize target-specifi

Ho Kei Cheng, Alexander G. Schwing

We present XMem, a video object segmentation architecture for long videos with unified feature memory stores inspired by the Atkinson-Shiffrin memory model. Prior work on video object segmentation typically only uses one type of feature memory. For videos longer than a minute, a single feature memory model tightly links memory consumption and accuracy. In co

Asaf Miron

"Local resetting" was recently introduced to describe stochastic resetting in interacting systems where particles independently try to reset to a common "origin". Our understanding of such systems, where the resetting process is itself affected by interactions, is still very limited. One ubiquitous constraint that is often imposed on the dynamics of interact

Roman Marcarelli, Nicholas Miesch, Ethan T. Neil

We revisit standard arguments for hyperscaling of the spectrum when a non-zero fermion mass is introduced to a gauge-fermion theory which is conformal in the infrared limit. With some general assumptions, we argue that the induced confinement scale will be significantly enhanced near the edge of the conformal to confining transition. This enhancement can all

Anthony W. Schlimgen, Kade Head-Marsden, LeeAnn M. Sager-Smith, Prineha Narang

Electronic structure and transport in realistically-sized systems often require an open quantum system (OQS) treatment, where the system is defined in the context of an environment. As OQS evolution is non-unitary, implementation on quantum computers -- limited to unitary operations -- is challenging. We present a general framework for OQSs where the system'

Cristian Moreno-Pulido, Joan Sola Peracaula

Recent studies of quantum field theory in FLRW spacetime suggest that the cause of the speeding up of the universe is the running vacuum (RV). Appropriate renormalization of the energy-momentum tensor shows that the vacuum energy density is a smooth function of the Hubble rate and its derivatives: $\rho_{\rm vac}=\rho_{\rm vac}(H, \dot{H},\ddot{H},...)$. Thi

Ruizhao Zhu, Pengkai Zhu, Samarth Mishra, Venkatesh Saligrama

We propose a new method for fine-grained few-shot recognition via deep object parsing. In our framework, an object is made up of K distinct parts and for each part, we learn a dictionary of templates, which is shared across all instances and categories. An object is parsed by estimating the locations of these K parts and a set of active templates that can re

Maxim Goncharov

In the paper we describe structures of quasitriangular Lie bialgebra on $gl_2(\mathbb C)$ using the classification of Rota-Baxter operators of nonzero weight on $gl_2(\mathbb C)$.

Samuele Anni, Alexandru Ghitza, Anna Medvedovsky

We prove that mod-$p$ congruences between polynomials in $\mathbb{Z}_p[X]$ are equivalent to deeper $p$-power congruences between power-sum functions of their roots. This result generalizes to torsion-free $\mathbb{Z}_{(p)}$-algebras modulo divided-power ideals. Our approach is combinatorial: we introduce a $p$-equivalence relation on partitions, and use it

Leo Abbrescia, Jared Speck

We study the Cauchy problem for the $3D$ compressible Euler equations under an arbitrary equation of state with positive speed of sound, aside from that of a Chaplygin gas. For open sets of smooth initial data with non-trivial vorticity and entropy, our main results yield a constructive proof of the formation, structure, and stability of the singular boundar

Yuanhan Zhang, Zhenfei Yin, Jing Shao, Ziwei Liu

Though impressive performance has been achieved in specific visual realms (e.g. faces, dogs, and places), an omni-vision representation generalizing to many natural visual domains is highly desirable. But, existing benchmarks are biased and inefficient to evaluate the omni-vision representation -- these benchmarks either only include several specific realms,

Tatjana Chavdarova, Ya-Ping Hsieh, Michael I. Jordan

Algorithms that solve zero-sum games, multi-objective agent objectives, or, more generally, variational inequality (VI) problems are notoriously unstable on general problems. Owing to the increasing need for solving such problems in machine learning, this instability has been highlighted in recent years as a significant research challenge. In this paper, we

Zhaoxi Chen, Ziwei Liu

Human relighting is a highly desirable yet challenging task. Existing works either require expensive one-light-at-a-time (OLAT) captured data using light stage or cannot freely change the viewpoints of the rendered body. In this work, we propose a principled framework, Relighting4D, that enables free-viewpoints relighting from only human videos under unknown

Zhuquan Zhang, Frank Y. Gao, Yu-Che Chien, Zi-Jie Liu

Tailored light excitation and nonlinear control of lattice vibrations have emerged as powerful strategies to manipulate the properties of quantum materials out of equilibrium. Generalizing the use of coherent phonon-phonon interactions to nonlinear couplings among other types of collective modes would open unprecedented opportunities in the design of novel d

Massimo Pascale, Brenda L. Frye, Jose Diego, Lukas J. Furtak

The first deep field images from the James Webb Space Telescope (JWST) of the galaxy cluster SMACS~J0723.3-7327 reveal a wealth of new lensed images at uncharted infrared wavelengths, with unprecedented depth and resolution. Here we securely identify 14 new sets of multiply imaged galaxies totalling 42 images, adding to the five sets of bright and multiply-i

Guillaume Mahler, Mathilde Jauzac, Johan Richard, Benjamin Beauchesne

Exploiting the fundamentally achromatic nature of gravitational lensing, we present a lens model for the massive galaxy cluster SMACSJ0723.3-7323 (SMACSJ0723, z=0.388) that significantly improves upon earlier work. Building on strong-lensing constraints identified in prior Hubble Space Telescope (HST) observations, the mass model utilizes 21 multiple-image s

John Orlowski-Scherer, Saianeesh K. Haridas, Luca Di Mascolo, Karen Perez Sarmiento

Mechanical feedback from active galactic nuclei (AGN) is thought to be the dominant feedback mechanism quenching cooling flows and star formation in galaxy cluster cores. However, the mechanisms by which AGN couple to the intracluster medium (ICM) are not well understood. The nature of pressure supporting the cavities is not known. Using the MUSTANG-2 instru

Alexander Dukhovny

The concept of Relative Divergence of one Grading Function from another is extended from totally ordered chains to power sets of finite event spaces. Shannon Entropy concept is extended to normalized grading functions on such power sets. Maximum Relative Divergence Principle is introduced as a generalization of the Maximum Entropy Principle as a tool for det

Dingfeng Shi, Yujie Zhong, Qiong Cao, Jing Zhang

This work aims at advancing temporal action detection (TAD) using an encoder-decoder framework with action queries, similar to DETR, which has shown great success in object detection. However, the framework suffers from several problems if directly applied to TAD: the insufficient exploration of inter-query relation in the decoder, the inadequate classificat

Adithya Sriram, Tibor Rakovszky, Vedika Khemani, Matteo Ippoliti

We consider a paradigmatic solvable model of topological order in two dimensions, Kitaev's honeycomb Hamiltonian, and turn it into a measurement-only dynamics consisting of stochastic measurements of two-qubit bond operators. We find an entanglement phase diagram that resembles that of the Hamiltonian problem in some ways, while being qualitatively different

Felicia Lucke, Daniël Paulusma, Bernard Ries

The NP-complete problem Matching Cut is to decide if a graph has a matching that is also an edge cut of the graph. We prove new complexity results for Matching Cut restricted to $H$-free graphs, that is, graphs that do not contain some fixed graph $H$ as an induced subgraph. We also prove new complexity results for two recently studied variants of Matching C

Purbesh Mitra, Sennur Ulukus

We consider a fully-connected wireless gossip network which consists of a source and $n$ receiver nodes. The source updates itself with a Poisson process and also sends updates to the nodes as Poisson arrivals. Upon receiving the updates, the nodes update their knowledge about the source. The nodes gossip the data among themselves in the form of Poisson arri

Sarah Frei, Lena Ji, Soumya Sankar, Bianca Viray

We undertake a study of conic bundle threefolds $\pi\colon X\to W$ over geometrically rational surfaces whose associated discriminant covers $\tilde{\Delta}\to\Delta\subset W$ are smooth and geometrically irreducible. First, we determine the structure of the group $\mathrm{CH}^2 X_{\overline{k}}$ of rational equivalence classes of curves. Precisely, we const

Marco Cotogni, Claudio Cusano

Nowadays, image-to-image translation methods, are the state of the art for the enhancement of natural images. Even if they usually show high performance in terms of accuracy, they often suffer from several limitations such as the generation of artifacts and the scalability to high resolutions. Moreover, their main drawback is the completely black-box approac

Fotios Drakopoulos, Sarah Verhulst

Sound processing in the human auditory system is complex and highly non-linear, whereas hearing aids (HAs) still rely on simplified descriptions of auditory processing or hearing loss to restore hearing. Even though standard HA amplification strategies succeed in restoring audibility of faint sounds, they still fall short of providing targeted treatments for

Victor Ilisie

In this work we study the high-energy Higgs boson phenomenology associated to the non-metricity scale $\Lambda_Q$ at the LHC. Non-metricity is present in more generic non-Riemannian geometries describing gravity beyond General Relativity and exhibits nice features in astronomy and cosmology, and it can be analysed perturbatively. Using effective field theory

Mehmet Yamaç, Mert Duman, İlke Adalıoğlu, Serkan Kiranyaz

This paper proposes a low-cost and highly accurate ECG-monitoring system intended for personalized early arrhythmia detection for wearable mobile sensors. Earlier supervised approaches for personalized ECG monitoring require both abnormal and normal heartbeats for the training of the dedicated classifier. However, in a real-world scenario where the personali

Mehmet Ozkan, Yao Ma

Human drivers have limited and time-varying cognitive resources when making decisions in real-world traffic scenarios, which often leads to unique and stochastic behaviors that can not be explained by perfect rationality assumption, a widely accepted premise in modeling driving behaviors that presume drivers rationally make decisions to maximize their own re

Weng Lam Tam, Xiao Liu, Kaixuan Ji, Lilong Xue

Prompt tuning attempts to update few task-specific parameters in pre-trained models. It has achieved comparable performance to fine-tuning of the full parameter set on both language understanding and generation tasks. In this work, we study the problem of prompt tuning for neural text retrievers. We introduce parameter-efficient prompt tuning for text retrie

T. H. Tennahewa, S. Hosseinzadeh, S. I. Atwood, H. Popli

We report measurements of room-temperature spin-relaxation times $T_1$ and $T_2$ of charge-carrier spins in a $\pi$-conjugated polymer thin film under bipolar injection and low ($1\mbox{ mT}\lesssim B_0\lesssim 10\mbox{ mT}$) static magnetic fields, using electrically detected magnetic resonant Hahn-echo and inversion-recovery pulse sequences. The experiment

Yu Li, P. G. LaBarre, D. M. Pajerowski, A. P. Ramirez

The anisotropic spin glass transition, in which spin freezing is observed only along the c-axis in pseudobrookite Fe$_2$TiO$_5$, has long been perplexing because the Fe$^{3+}$ moments (d$^5$) are expected to be isotropic. Recently, neutron diffraction demonstrated that surfboard-shaped antiferromagnetic nanoregions coalesce above the glass transition tempera

Deepa Antony, Rupam Barman

Let $(x_n)_{n\geq0}$ be a linear recurrence of order $k\geq2$ satisfying $$x_n=a_1x_{n-1}+a_2x_{n-2}+\dots+a_kx_{n-k}$$ for all integers $n\geq k$, where $a_1,\dots,a_k,x_0,\dots, x_{k-1}\in \mathbb{Z},$ with $a_k\neq0$. In [`The quotient set of $k$-generalised Fibonacci numbers is dense in $\mathbb{Q}_p$', \emph{Bull. Aust. Math. Soc.} \textbf{96} (2017), 2

Vladimir Salnikov, Antoine Falaize, Daria Loziienko

In this article we study the possibilities of recovering the structure of port-Hamiltonian systems starting from ``unlabelled'' ordinary differential equations describing mechanical systems. The algorithm we suggest solves the problem in two phases. It starts by constructing the connectivity structure of the system using machine learning methods -- producing

Alexei Kotov, Vladimir Salnikov

In this paper we address several algebraic constructions in the context of groupoids, algebroids and $\mathbb Z$-graded manifolds. We generalize the results of integration of $\mathbb N$-graded Lie algebras to the honest $\mathbb Z$-graded case and provide some examples of application of the technique based on Harish-Chandra pairs. We extend the construction

Nicusor Costea

In this paper we investigate the existence of solutions for a system consisting of two inequalities of variational type. Each inequality is formulated in terms of a nonlinear bifunction $\chi$ and $\psi$, respectively and a coupling functional $B$. We consider two sets of assumptions ${\bf (H_\chi^i)}$, ${\bf (H_\psi^j)}$ and ${\bf (H_B^k)}$, $i,j,k\in\{1,2\

Pedro Catuogno, André de Oliveira Gomes

This article concerns the large deviations regime and the consequent solution of the Kramers problem for a two-time scale stochastic system driven by a common jump noise signal perturbed in small intensity $\varepsilon>0$ and with accelerated jumps by intensity $\frac{1}{\varepsilon}$. We establish Freidlin-Wentzell estimates for the slow process of the mult

Valentino Vito, Lim Yohanes Stefanus

Contrastive learning is a representation learning method performed by contrasting a sample to other similar samples so that they are brought closely together, forming clusters in the feature space. The learning process is typically conducted using a two-stage training architecture, and it utilizes the contrastive loss (CL) for its feature learning. Contrasti

Simone Servadio, Roberto Armellin, Richard Linares

A high order optimal control strategy implemented in the Koopman operator framework is proposed in this work. The new technique exploits the Koopman representation of the solution of the equations of motion to develop an energy optimal inverse control methodology. The operator theory can reformulate a nonlinear dynamical system of finite dimension into a lin

Bin Yan, Yi Jiang, Peize Sun, Dong Wang

We present a unified method, termed Unicorn, that can simultaneously solve four tracking problems (SOT, MOT, VOS, MOTS) with a single network using the same model parameters. Due to the fragmented definitions of the object tracking problem itself, most existing trackers are developed to address a single or part of tasks and overspecialize on the characterist

Tien Do, Khiem Vuong, Hyun Soo Park

In this paper, we study a problem of egocentric scene understanding, i.e., predicting depths and surface normals from an egocentric image. Egocentric scene understanding poses unprecedented challenges: (1) due to large head movements, the images are taken from non-canonical viewpoints (i.e., tilted images) where existing models of geometry prediction do not

Yunru Bai, Nicusor Costea, Shengda Zeng

In this paper we investigate a system of coupled inequalities consisting of a variational-hemivariational inequality and a quasi-hemivariational inequality on Banach spaces. The approach is topological, and a wide variety of existence results is established for both bounded and unbounded constraint sets in real reflexive Banach spaces. The main point of inte

Shamindra Shrotriya, Matey Neykov

Classical univariate isotonic regression involves nonparametric estimation under a monotonicity constraint of the true signal. We consider a variation of this generating process, which we term adversarial sign-corrupted isotonic (\texttt{ASCI}) regression. Under this \texttt{ASCI} setting, the adversary has full access to the true isotonic responses, and is

Sandip Aryal, Joseph Frimpong, Zhen-Fei Liu

Quantum dot (QD) assemblies are nanostructured networks made from aggregates of QDs and feature improved charge and energy transfer efficiencies compared to discrete QDs. Using first-principles many-body perturbation theory, we systematically compare the electronic and optical properties of two types of CdS QD assemblies that have been experimentally investi

Sidi Yaya Arnaud Yarga, Jean Rouat, Sean U. N. Wood

Spiking Neural Networks (SNN) are known to be very effective for neuromorphic processor implementations, achieving orders of magnitude improvements in energy efficiency and computational latency over traditional deep learning approaches. Comparable algorithmic performance was recently made possible as well with the adaptation of supervised training algorithm

Guy Blanc, Caleb Koch, Jane Lange, Li-Yang Tan

We design an algorithm for finding counterfactuals with strong theoretical guarantees on its performance. For any monotone model $f : X^d \to \{0,1\}$ and instance $x^\star$, our algorithm makes \[ {S(f)^{O(\Delta_f(x^\star))}\cdot \log d}\] queries to $f$ and returns {an {\sl optimal}} counterfactual for $x^\star$: a nearest instance $x'$ to $x^\star$ for w

Jin Beniyama, Shigeyuki Sako, Ryou Ohsawa, Satoshi Takita

We report the results of video observations of tiny (diameter less than 100 m) near-Earth objects (NEOs) with Tomo-e Gozen on the Kiso 105 cm Schmidt telescope. A rotational period of a tiny asteroid reflects its dynamical history and physical properties since smaller objects are sensitive to the YORP effect. We carried out video observations of 60 tiny NEOs

Kyle McKee

The electrostatic force on a charge above a neutral conductor is generally attractive. Surprisingly, that force becomes repulsive in certain geometries (Levin & Johnson 2011), a result that follows from an energy theorem in electrostatics. Based on the analogous minimum energy theorem of Kelvin (1849), valid in the theory of ideal fluids, we show correspondi

Pascal Maillard, Olivier Wintenberger

We consider random coefficient autoregressive models of infinite order (AR($\infty$)) under the assumption of non-negativity of the coefficients. We develop novel methods yielding sufficient or necessary conditions for finiteness of moments, based on combinatorial expressions of first and second moments. The methods based on first moments recover previous su

Max Hort, Zhenpeng Chen, Jie M. Zhang, Mark Harman

This paper provides a comprehensive survey of bias mitigation methods for achieving fairness in Machine Learning (ML) models. We collect a total of 341 publications concerning bias mitigation for ML classifiers. These methods can be distinguished based on their intervention procedure (i.e., pre-processing, in-processing, post-processing) and the technique th

Feras Al Taha, Tyrone Vincent, Eilyan Bitar

Plug-in electric vehicles (EVs) are widely recognized as being highly flexible electric loads that can be pooled and controlled via aggregators to provide low-cost energy and ancillary services to wholesale electricity markets. To participate in these markets, an aggregator must encode the aggregate flexibility of the population of EVs under their command as

Dominic M. Rouse, Adam Stokes, Ahsan Nazir

We derive an arbitrary-gauge criterion under which condensed matter within an electromagnetic field may transition to a photon condensed phase. Previous results are recovered by selecting the Coulomb-gauge wherein photon condensation can only occur for a spatially-varying field and can be interpreted as a magnetic instability. We demonstrate the gauge-invari

Weijian Deng, Stephen Gould, Liang Zheng

Generalization and invariance are two essential properties of any machine learning model. Generalization captures a model's ability to classify unseen data while invariance measures consistency of model predictions on transformations of the data. Existing research suggests a positive relationship: a model generalizing well should be invariant to certain visu

F. M. Hahne, P. Klimas

We study compact kinks and its interaction with compact oscillons in models with non-analytic potentials. Oscillon-like excitations are the main ingredients of the radiation field. We look at the problem of scattering which involves topological compact kinks and non-topological oscillons. We also look at the problem of propagation of small perturbation at th

A. G. Tatashev, O. V. Seleznjev, M. V. Yashina

In the paper we consider a multichannel loss preemptive priority system with a Poisson input and general service time distribution depending on the priority of job. Jobs of the same priority are preempted according with First Come First Displaced (FCFD) protocol. Approximate formulas are obtained for the loss probability of a prescribed priority job and some

Leonid Positselski

This is an overview on derived nonhomogeneous Koszul duality over a field, mostly based on the author's memoir arXiv:0905.2621. The paper is intended to serve as a pedagogical introduction and a summary of the covariant duality between DG-algebras and curved DG-coalgebras, as well as the triality between DG-modules, CDG-comodules, and CDG-contramodules. Some

Pralhad Lamichhane, Dilli Dhakal, Ishan N Jayalath, Ganga Raj Neupane

Polyaniline and graphene nanoplatelets (PANI-GNP) nanocomposites are synthesized by in situ oxidative polymerization of polyaniline using an oxidizing agent, ammonium peroxy disulphate (APS). The mass of GNP in the nanocomposites varied by 5, 10, and 15 wt% compared to PANI. The synthesized polyaniline coated graphene nanoplatelets (PANI-GNP) nanocomposites

Tal Schuster, Adam Fisch, Jai Gupta, Mostafa Dehghani

Recent advances in Transformer-based large language models (LLMs) have led to significant performance improvements across many tasks. These gains come with a drastic increase in the models' size, potentially leading to slow and costly use at inference time. In practice, however, the series of generations made by LLMs is composed of varying levels of difficul

Reza Saadati, Andrea Giusti, Valerio Faraoni, Fatimah Shojai

We generate new spherical and time-dependent solutions of viable Horndeski gravity by disforming a solution of the Einstein equations with scalar field source and positive cosmological constant. They describe dynamical objects embedded in asymptotically FLRW spacetimes and contain apparent horizons and a finite radius singularity that evolve in time in pecul

Sauradip Nag, Xiatian Zhu, Yi-Zhe Song, Tao Xiang

Existing temporal action detection (TAD) methods rely on a large number of training data with segment-level annotations. Collecting and annotating such a training set is thus highly expensive and unscalable. Semi-supervised TAD (SS-TAD) alleviates this problem by leveraging unlabeled videos freely available at scale. However, SS-TAD is also a much more chall

Charlotte K. Duda, Kate R. Ferguson, Rose L. Ahlefeldt, Morgan P. Hedges

We studied the recall efficiency as a function of optical depth of rephased amplified spontaneous emission (RASE), a protocol for generating entangled light. The experiments were performed on the $^{3}\! H_{4}$ $\rightarrow$ $^{1}\! D_{2}$ transition in the rare-earth doped crystal Pr$^{3+}$:Y$_{2}$SiO$_{5}$, using a four-level echo sequence between four hyp

Nikolaos Diamantis, Min Lee, Larry Rolen

We define an analogue of the Bol operator on spaces of weakly holomorphic modular forms of half-integral weight. We establish its main properties and relation with other objects.

Tobias Neumann, John Campbell

Drell-Yan production is one of the precision cornerstones of the LHC, serving as calibration for measurements such as the $W$-boson mass. Its extreme precision at the level of 1% challenges theory predictions at the highest level. We present the first independent calculation of Drell-Yan production at order $\alpha_s^3$ in transverse-momentum ($q_T$) resumma

Ilias Chronopoulos, Katerina Chrysikou, George Kapetanios

In this paper we develop inference for high dimensional linear models, with serially correlated errors. We examine Lasso under the assumption of strong mixing in the covariates and error process, allowing for fatter tails in their distribution. While the Lasso estimator performs poorly under such circumstances, we estimate via GLS Lasso the parameters of int

R. Aafreen, R. Abhishek, B. Ajithkumar, Arunkumar M. Vaidyanathan

This paper presents the High-Performance computing efforts with FPGA for the accelerated pulsar/transient search for the SKA. Case studies are presented from within SKA and pathfinder telescopes highlighting future opportunities. It reviews the scenario that has shifted from offline processing of the radio telescope data to digitizing several hundreds/thousa

Arthur Azevedo de Amorim

Andrew Pitts' framework of relational properties of domains is a powerful method for defining predicates or relations on domains, with applications ranging from reasoning principles for program equivalence to proofs of adequacy connecting denotational and operational semantics. Its main appeal is handling recursive definitions that are not obviously well-fou

Anthony K. Cheetham, Ram Seshadri, Fred Wudl

Functional materials impact every area of our lives ranging from electronic and computing devices to transportation and health. In this Perspective, we examine the relationship between synthetic discoveries and the scientific breakthroughs that they have enabled. By tracing the development of some important examples, we explore how and why the materials were

Ishita Dasgupta, Andrew K. Lampinen, Stephanie C. Y. Chan, Hannah R. Sheahan

Reasoning is a key ability for an intelligent system. Large language models (LMs) achieve above-chance performance on abstract reasoning tasks, but exhibit many imperfections. However, human abstract reasoning is also imperfect. For example, human reasoning is affected by our real-world knowledge and beliefs, and shows notable "content effects"; humans reaso

Maria Bustamante Madrid, Jeroen Famaey, Filip Lemic

The 6th generation of wireless communication (6G) is envisioned to give rise to various technologies for improving the end-to-end communication performance, where the communication is envisioned to utilize wireless signals in the millimeter wave (mmWave) frequencies and above. Among others, these technologies comprise Intelligent Reflective Surfaces (IRSs) a

Manuel Navarro-García, Daniel Precioso, Kathryn Gavira-O'Neill, Alberto Torres-Barrán

Based on the data gathered by echo-sounder buoys attached to drifting Fish Aggregating Devices (dFADs) across tropical oceans, the current study applies a Machine Learning protocol to examine the temporal trends of tuna schools' association to drifting objects. Using a binary output, metrics typically used in the literature were adapted to account for the fa

Sayash Kapoor, Arvind Narayanan

The use of machine learning (ML) methods for prediction and forecasting has become widespread across the quantitative sciences. However, there are many known methodological pitfalls, including data leakage, in ML-based science. In this paper, we systematically investigate reproducibility issues in ML-based science. We show that data leakage is indeed a wides

Alessio Barbieri, Enzo Vitillaro

The aim of the paper is to study the problem $$u_{tt}+du_t-c^2\Delta u=0 \qquad \text{in $\mathbb{R}\times\Omega$,}$$ $$\mu v_{tt}- \text{div}_\Gamma (\sigma \nabla_\Gamma v)+\delta v_t+\kappa v+\rho u_t =0\qquad \text{on $\mathbb{R}\times \Gamma_1$,}$$ $$v_t =\partial_\nu u\qquad \text{on $\mathbb{R}\times \Gamma_1$,}$$ $$\partial_\nu u=0 \text{on $\mathbb{

Emilio J. González, Jesús González

We introduce an algorithm that constructs a discrete gradient field on any simplicial complex. We show that, in all situations, the gradient field is maximal possible and, in a number of cases, optimal. We make a thorough analysis of the resulting gradient field in the case of Munkres' discrete model for $\text{Conf}(K_m,2)$, the configuration space of order