March 2023 arXiv papers — page 129

Thomas Pierrot, Arthur Flajolet

Quality Diversity (QD) has emerged as a powerful alternative optimization paradigm that aims at generating large and diverse collections of solutions, notably with its flagship algorithm MAP-ELITES (ME) which evolves solutions through mutations and crossovers. While very effective for some unstructured problems, early ME implementations relied exclusively on

Alexander Pattison, Cassio C. S. Pedroso, Bruce E. Cohen, Justin C. Ondry

Scanning transmission electron microscopy is a common tool used to study the atomic structure of materials. It is an inherently multimodal tool allowing for the simultaneous acquisition of multiple information channels. Despite its versatility, however, experimental workflows currently rely heavily on experienced human operators and can only acquire data fro

Marta Dujella, Anne-Maria Ernvall-Hytönen, Linda Frey, Bidisha Roy

For a given transcendental number $\xi$ and for any polynomial $P(X)=: \lambda_0+\cdots+\lambda_k X^k \in \mathbb{Z}[X]$, we know that $ P(\xi) \neq 0.$ Let $k \geq 1$ and $\omega (k, H)$ be the infimum of the numbers $r > 0$ satisfying the estimate $$ \left|\lambda_0+\lambda_1 \xi+\lambda_2 \xi^{2}+ \ldots +\lambda_k\xi^{k}\right| > \frac{1}{H^r}, $$ for al

Tommy Nyberg, Peter Bager, Ingrid Bech Svalgaard, Dritan Bejko

Several SARS-CoV-2 variants that evolved during the COVID-19 pandemic have appeared to differ in severity, based on analyses of single-country datasets. With decreased SARS-CoV-2 testing and sequencing, international collaborative studies will become increasingly important for timely assessment of the severity of newly emerged variants. The Joint WHO Regiona

Weizhen Jia, Marc S. Klinger, Robert G. Leigh

In this paper we demonstrate that the exterior algebra of an Atiyah Lie algebroid generalizes the familiar notions of the physicist's BRST complex. To reach this conclusion, we develop a general picture of Lie algebroid isomorphisms as commutative diagrams between algebroids preserving the geometric structure encoded in their brackets. We illustrate that a n

Chrisantus Eze, Christopher Crick

As the use of Augmented Reality (AR) to enhance interactions between human agents and robotic systems in a work environment continues to grow, robots must communicate their intents in informative yet straightforward ways. This improves the human agent's feeling of trust and safety in the work environment while also reducing task completion time. To this end,

Dmitry Galakhov

In this note we review a construction of a BPS Hilbert space in an effective supersymmetric quiver theory with 4 supercharges. We argue abstractly that this space contains elements of an equivariant generalized cohomology theory $E_G^{*}(-)$ of the quiver representation moduli space giving concretely Dolbeault cohomology, K-theory or elliptic cohomology depe

Giovanni Aricò, Raul E. Angulo, Matteo Zennaro, Sergio Contreras

We present the first analysis of cosmic shear measured in DES Y3 that employs the entire range of angular scales in the data. To achieve this, we build upon recent advances in the theoretical modelling of weak lensing provided by a combination of $N$-body simulations, physical models of baryonic processes, and neural networks. Specifically, we use BACCOemu t

Guglielmo Lami, Mario Collura

We introduce a novel breakthrough approach to evaluate the nonstabilizerness of an $N$-qubits Matrix Product State (MPS) with bond dimension $\chi$. In particular, we consider the recently introduced Stabilizer R\'enyi Entropies (SREs). We show that the exponentially hard evaluation of the SREs can be achieved by means of a simple perfect sampling of the man

Julius Wons, Emanuela Dimastrogiovanni, Matteo Fasiello, Jan Hamann

We forecast the ability of bispectrum estimators to constrain primordial non-Gaussianity using future photometric galaxy redshift surveys. A full-sky survey with photometric redshift resolution of $\sigma_z/(1+z)=0.05$ in the redshift range $0.2<z<2$ can provide constraints $\sigma(f^\mathrm{local}_\mathrm{NL})=3.4$, $\sigma(f^\mathrm{equil}_\mathrm{NL})=15$

P. Romano, A. Lähteenmäki, S. Vercellone, L. Foschini

We report on the first multi-wavelength Swift monitoring campaign performed on SDSS J164100.10+345452.7, a nearby narrow-line Seyfert 1 galaxy formerly known as radio quiet which was recently detected both in the radio (at 37 GHz) and in the $\gamma$-rays, which hints at the presence of a relativistic jet. During our 20-month Swift campaign, while pursuing t

Yuta Kikuchi, Conor Mc Keever, Luuk Coopmans, Michael Lubasch

Quantum signal processing (QSP) is a powerful toolbox for the design of quantum algorithms and can lead to asymptotically optimal computational costs. Its realization on noisy quantum computers without fault tolerance, however, is challenging because it requires a deep quantum circuit in general. We propose a strategy to run an entire QSP protocol on noisy q

Javid Naikoo, Ravindra W. Chhajlany, Jan Kolodynski

Describing the evolution of quantum systems by means of non-Hermitian generators opens a new avenue to explore the dynamical properties naturally emerging in such a picture, e.g. operation at the so-called exceptional points, preservation of parity-time symmetry, or capitalising on the singular behaviour of the dynamics. In this work, we focus on the possibi

Vivienne Langen, Sebastiano Cantalupo, Charles C. Steidel, Yuguang Chen

The discovery of giant quasar Ly$\alpha$ nebulae at $z>2$ has opened up the possibility to directly study in emission the Circumgalactic and Intergalactic Medium (CGM/IGM). However, the resonant nature of the Ly$\alpha$ line and its different emission mechanisms hamper the ability to constrain both the kinematics and physical properties of the CGM/IGM. Here,

Thomas W. Baumgarte, Carsten Gundlach, David Hilditch

We report on numerical simulations of critical phenomena near the threshold of black hole formation in the collapse of axisymmetric gravitational waves in vacuum. We discuss several new features of our numerical treatment, and then compare results obtained from families of quadrupolar and hexadecapolar initial data. Specifically, we construct (nonlinear) ini

Umut Gürsoy, Juan F. Pedraza, Guim Planella Planas

The Ryu-Takayanagi prescription can be cast in terms of a set of microscopic threads that help visualize holographic entanglement in terms of distillation of EPR pairs. While this framework has been exploited for regions with a high degree of symmetry, we take the first steps towards understanding general entangling regions, focusing on AdS$_4$. Inspired by

Vedran Brdar, Julia Gehrlein, Joachim Kopp

A series of experiments studying neutrinos from intense radioactive sources have reported a deficit in the measured event rate which, in combination, has reached a statistical significance of $\sim 5\sigma$. In this paper, we explore avenues for explaining this anomaly, both within the Standard Model and beyond. First, we discuss possible biases in the predi

Megan Barry, Andrew Wetzel, Sierra Chapman, Jenna Samuel

A variety of observational campaigns seek to test dark-matter models by measuring dark-matter subhaloes at low masses. Despite their predicted lack of stars, these subhaloes may be detectable through gravitational lensing or via their gravitational perturbations on stellar streams. To set measurable expectations for subhalo populations within LambdaCDM, we e

Jakub Cehula, Ondřej Pejcha

Calculation of the mass transfer (MT) rate $\dot{M}_\text{d}$ of a Roche lobe overflowing star is a fundamental task in binary star evolution theory. Most of the existing MT prescriptions are based on a common set of assumptions that combine optically-thick and optically-thin regimes with different flow geometries. In this work, we develop a new model of MT

Jason T. Hinkle, Benjamin J. Shappee, Thomas W. -S. Holoien

Some galaxies show little to no sign of active galactic nucleus (AGN) activity, yet exhibit strong coronal emission lines (CLs) relative to common narrow emission lines. Many of these CLs have ionization potentials of $\geq 100$ eV, thus requiring strong extreme UV and/or soft X-ray flux. It has long been thought that such events are powered by tidal disrupt

Patryk Lipka-Bartosik, Christopher T. Chubb, Joseph M. Renes, Marco Tomamichel

We address the problem of exact and approximate transformation of quantum dichotomies in the asymptotic regime, i.e., the existence of a quantum channel $\mathcal E$ mapping $\rho_1^{\otimes n}$ into $\rho_2^{\otimes R_nn}$ with an error $\epsilon_n$ (measured by trace distance) and $\sigma_1^{\otimes n}$ into $\sigma_2^{\otimes R_n n}$ exactly, for a large

Eric Stringer, Thomas Kupfer, Matti Dorsch

We present follow-up studies of three ultracompact hot subdwarf binaries. Using data from the Zwicky Transient Facility, we find orbital periods of 33.6, 37.3, and 36.9 minutes for ZTF 1946+3203, ZTF 0640+1738, and ZTF 0643+0318 respectively. The light curves show ellipsoidal variability of the hot subdwarf star with potential eclipses of an accretion disc.

Núria Miret-Roig

Free-floating planets (FFPs) are the lightest products of star formation and they carry important information on the initial conditions of the environment in which they were formed. They were first discovered in the 2000s but still few of them have been identified and confirmed due to observational challenges. This is a review of the last advances in the det

Wei Li

The quiver Yangians were originally defined for the quiver and superpotential from string theory on general toric Calabi-Yau threefolds, and serve as BPS algebras of these systems. Their characters reproduce the unrefined BPS indices, which correspond to classical Donaldson-Thomas (DT) invariants. We generalize this construction in two directions. First, we

Francesco D'Eugenio, Arjen van der Wel, Joanna M. Piotrowska, Rachel Bezanson

We present the first study of spatially integrated higher-order stellar kinematics over cosmic time. We use deep rest-frame optical spectroscopy of quiescent galaxies at redshifts z=0.05, 0.3 and 0.8 from the SAMI, MAGPI and LEGA-C surveys to measure the excess kurtosis $h_4$ of the stellar velocity distribution, the latter parametrised as a Gauss-Hermite se

Javier Moran-Fraile, Fabian R. N. Schneider, Friedrich K. Roepke, Sebastian T. Ohlmann

We are witnessing the dawn of gravitational wave (GW) astronomy. With currently available detectors, observations are restricted to GW frequencies in the range between ${\sim} 10\,\mathrm{Hz}$ and $10\,\mathrm{kHz}$, which covers the signals from mergers of compact objects. The launch of the space observatory LISA will open up a new frequency band for the de

Xuan Li, Yi-Ling Qiao, Peter Yichen Chen, Krishna Murthy Jatavallabhula

Existing approaches to system identification (estimating the physical parameters of an object) from videos assume known object geometries. This precludes their applicability in a vast majority of scenes where object geometries are complex or unknown. In this work, we aim to identify parameters characterizing a physical system from a set of multi-view videos

Minguk Kang, Jun-Yan Zhu, Richard Zhang, Jaesik Park

The recent success of text-to-image synthesis has taken the world by storm and captured the general public's imagination. From a technical standpoint, it also marked a drastic change in the favored architecture to design generative image models. GANs used to be the de facto choice, with techniques like StyleGAN. With DALL-E 2, auto-regressive and diffusion m

Shun Zhang, Zhenfang Chen, Yikang Shen, Mingyu Ding

Existing large language model-based code generation pipelines typically use beam search or sampling algorithms during the decoding process. Although the programs they generate achieve high token-matching-based scores, they often fail to compile or generate incorrect outputs. The main reason is that conventional Transformer decoding algorithms may not be the

Maxime Dupont, Bram Evert, Mark J. Hodson, Bhuvanesh Sundar

Combinatorial optimization is a broadly attractive area for potential quantum advantage, but no quantum algorithm has yet made the leap. Noise in quantum hardware remains a challenge, and more sophisticated quantum-classical algorithms are required to bolster their performance. Here, we introduce an iterative quantum heuristic optimization algorithm to solve

Yunchu Zhang, Liyiming Ke, Abhay Deshpande, Abhishek Gupta

Grasping small objects surrounded by unstable or non-rigid material plays a crucial role in applications such as surgery, harvesting, construction, disaster recovery, and assisted feeding. This task is especially difficult when fine manipulation is required in the presence of sensor noise and perception errors; errors inevitably trigger dynamic motion, which

Carl Johan Casselgren, Fikre B. Petros, Samuel A. Fufa

We consider the problem of extending partial edge colorings of cartesian products of graphs. More specifically, we suggest the following Evans-type conjecture: If $G$ is a graph where every precoloring of at most $k$ precolored edges can be extended to a proper $\chi'(G)$-edge coloring, then every precoloring of at most $k+1$ edges of $G \square K_2$ is exte

Alan Jeffares, Tennison Liu, Jonathan Crabbé, Fergus Imrie

Despite their success with unstructured data, deep neural networks are not yet a panacea for structured tabular data. In the tabular domain, their efficiency crucially relies on various forms of regularization to prevent overfitting and provide strong generalization performance. Existing regularization techniques include broad modelling decisions such as cho

Lawrence Hollom, Julien Portier, Leo Versteegen

An interval colouring of a graph $G=(V,E)$ is a proper colouring $c\colon E\to \mathbb{Z}$ such that the set of colours of edges incident to any given vertex forms an interval of $\mathbb{Z}$. The interval thickness $\theta(G)$ of a graph $G$ is the smallest integer $k$ such that $G$ can be edge-partitioned into $k$ interval colourable graphs, and $\theta(n)

Yuanfang Ren, Tyler J. Loftus, Ziyuan Guan, Rayon Uddin

In the United States, more than 5 million patients are admitted annually to ICUs, with ICU mortality of 10%-29% and costs over $82 billion. Acute brain dysfunction status, delirium, is often underdiagnosed or undervalued. This study's objective was to develop automated computable phenotypes for acute brain dysfunction states and describe transitions among br

Tarun Kalluri, Weiyao Wang, Heng Wang, Manmohan Chandraker

Many top-down architectures for instance segmentation achieve significant success when trained and tested on pre-defined closed-world taxonomy. However, when deployed in the open world, they exhibit notable bias towards seen classes and suffer from significant performance drop. In this work, we propose a novel approach for open world instance segmentation ca

Yaşar Hiçyılmaz, Levent Selbuz, Cem Salih Ün

We explore the Higgs boson implications of a class of supersymmetric models, which extends the MSSM gauge group by a $U(1)^{\prime}$ symmetry, which is broken at low energy scales by VEVs of four MSSM singlet fields. These singlets also form a secluded sector, and one of them is allowed to interact with the MSSM Higgs fields directly. After the $U(1)^{\prime

Jiayuan Mao, Tomás Lozano-Pérez, Joshua B. Tenenbaum, Leslie Pack Kaelbling

This paper studies a model learning and online planning approach towards building flexible and general robots. Specifically, we investigate how to exploit the locality and sparsity structures in the underlying environmental transition model to improve model generalization, data-efficiency, and runtime-efficiency. We present a new domain definition language,

Alex Mei, Michael Saxon, Shiyu Chang, Zachary C. Lipton

Despite widespread calls for transparent artificial intelligence systems, the term is too overburdened with disparate meanings to express precise policy aims or to orient concrete lines of research. Consequently, stakeholders often talk past each other, with policymakers expressing vague demands and practitioners devising solutions that may not address the u

Shilong Liu, Zhaoyang Zeng, Tianhe Ren, Feng Li

In this paper, we present an open-set object detector, called Grounding DINO, by marrying Transformer-based detector DINO with grounded pre-training, which can detect arbitrary objects with human inputs such as category names or referring expressions. The key solution of open-set object detection is introducing language to a closed-set detector for open-set

Kirill Bykov, Klaus-Robert Müller, Marina M. -C. Höhne

The utilization of pre-trained networks, especially those trained on ImageNet, has become a common practice in Computer Vision. However, prior research has indicated that a significant number of images in the ImageNet dataset contain watermarks, making pre-trained networks susceptible to learning artifacts such as watermark patterns within their latent space

Ludvig Bergenstråhle, Jens Lagergren, Joakim Lundeberg

We introduce a new optimization algorithm, termed contrastive adjustment, for learning Markov transition kernels whose stationary distribution matches the data distribution. Contrastive adjustment is not restricted to a particular family of transition distributions and can be used to model data in both continuous and discrete state spaces. Inspired by recent

Guangxuan Xiao, Leslie Pack Kaelbling, Jiajun Wu, Jiayuan Mao

Reasoning about the relationships between entities from input facts (e.g., whether Ari is a grandparent of Charlie) generally requires explicit consideration of other entities that are not mentioned in the query (e.g., the parents of Charlie). In this paper, we present an approach for learning to solve problems of this kind in large, real-world domains, usin

Falk Herwig, Paul R. Woodward, Huaqing Mao, William R. Thompson

We performed 3D hydrodynamic simulations of the inner $\approx 50\%$ radial extent of a $25\ \mathrm{M_\odot}$ star in the early phase of the main sequence and investigate core convection and internal gravity waves in the core-envelope boundary region. Simulations for different grid resolutions and driving luminosities establish scaling relations to constrai

Joshua Lackman

Based on work done by Bonechi, Cattaneo, Felder and Zabzine on Poisson sigma models, we formally show that Kontsevich's star product can be obtained from the twisted convolution algebra of the geometric quantization of a Lie 2-groupoid, one which integrates the Poisson structure. We show that there is an analogue of the Poisson sigma model which is valued in

Michele Pernice

This paper is the third in a series of four papers aiming to describe the (almost integral) Chow ring of $\overline{\mathcal{M}}_3$, the moduli stack of stable curves of genus $3$. In this paper, we compute the Chow ring of $\widetilde{\mathcal{M}}_3^7$ with $\mathbb{Z}[1/6]$-coefficients.

Naoya Kitajima, Fuminobu Takahashi

Dark photons could be produced resonantly by the oscillating axion field in the early universe. This resonant production mechanism has been used in various contexts, including dark photon dark matter and primordial magnetic field production. However, for this resonant production to work in an expanding universe, a large axion-dark photon coupling is required

Andrea Lattuada, Travis Hance, Chanhee Cho, Matthias Brun

The Rust programming language provides a powerful type system that checks linearity and borrowing, allowing code to safely manipulate memory without garbage collection and making Rust ideal for developing low-level, high-assurance systems. For such systems, formal verification can be useful to prove functional correctness properties beyond type safety. This

Zhezheng Luo, Jiayuan Mao, Joshua B. Tenenbaum, Leslie Pack Kaelbling

This extended abstract describes a framework for analyzing the expressiveness, learning, and (structural) generalization of hypergraph neural networks (HyperGNNs). Specifically, we focus on how HyperGNNs can learn from finite datasets and generalize structurally to graph reasoning problems of arbitrary input sizes. Our first contribution is a fine-grained an

Daniel Fry, Amol Deshmukh, Samuel Yen-Chi Chen, Vladimir Rastunkov

Quantum reservoir computing is strongly emerging for sequential and time series data prediction in quantum machine learning. We make advancements to the quantum noise-induced reservoir, in which reservoir noise is used as a resource to generate expressive, nonlinear signals that are efficiently learned with a single linear output layer. We address the need f

Zhezheng Luo, Jiayuan Mao, Jiajun Wu, Tomás Lozano-Pérez

We present a framework for learning useful subgoals that support efficient long-term planning to achieve novel goals. At the core of our framework is a collection of rational subgoals (RSGs), which are essentially binary classifiers over the environmental states. RSGs can be learned from weakly-annotated data, in the form of unsegmented demonstration traject

Yuntao Ma, Farbod Farshidian, Marco Hutter

Adaptive falling and recovery skills greatly extend the applicability of robot deployments. In the case of legged mobile manipulators, the robot arm could adaptively stop the fall and assist the recovery. Prior works on falling and recovery strategies for legged mobile manipulators usually rely on assumptions such as inelastic collisions and falling in defin

Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Sihan Liu

We give the first polynomial-time algorithm for the testable learning of halfspaces in the presence of adversarial label noise under the Gaussian distribution. In the recently introduced testable learning model, one is required to produce a tester-learner such that if the data passes the tester, then one can trust the output of the robust learner on the data

Jill Lundell, Brennan Bean, Juergen Symanzik

Improved understanding of characteristics related to weather forecast accuracy in the United States may help meteorologists develop more accurate predictions and may help Americans better interpret their daily weather forecasts. This article examines how spatio-temporal characteristics across the United States relate to forecast accuracy. We cluster the Unit

Y. Alexanian, E. Lhotel, R. Ballou, C. V. Colin

Geometrical frustration, as in pyrochlore lattices made of corner-sharing tetrahedra, precludes the onset of conventional magnetic ordering, enabling the stabilization of fluctuating spin states at low temperature. Disorder is a subtle ingredient that can modify the nature of these exotic non-ordered phases. Here, we study the interplay between disorder and

Hiroki Ohata

Monte Carlo study of the Schwinger model (quantum electrodynamics in one spatial dimension) with a topological $\theta$ term is very difficult due to the sign problem in the conventional lattice formulation. In this paper, we point out that this problem can be circumvented by utilizing the lattice formulation of the bosonized Schwinger model, initially inven

Alison Crosby, Eric C. Orenstein, Susan E. Poulton, Katherine L. C. Bell

Ocean scientists studying diverse organisms and phenomena increasingly rely on imaging devices for their research. These scientists have many tools to collect their data, but few resources for automated analysis. In this paper, we report on discussions with diverse stakeholders to identify community needs and develop a set of functional requirements for the

Mitsuhiko Nakamoto, Yuexiang Zhai, Anikait Singh, Max Sobol Mark

A compelling use case of offline reinforcement learning (RL) is to obtain a policy initialization from existing datasets followed by fast online fine-tuning with limited interaction. However, existing offline RL methods tend to behave poorly during fine-tuning. In this paper, we devise an approach for learning an effective initialization from offline data th

Yen Q. Do, Nhan D. V. Nguyen

We compute the precise leading asymptotics of the variance of the number of real roots for a large class of random polynomials, where the random coefficients have polynomial growth. Our results apply to many classical ensembles, including the Kac polynomials, hyperbolic polynomials, their derivatives, and any linear combinations of these polynomials. Prior t

Adrián González Casanova, Imanol Nuñez, J. -L. Pérez

Birkner et al. obtained necessary and sufficient conditions for the frequency between two independent and identically distributed continuous-state branching processes time-changed by a functional of the total mass process to be a Markov process. Foucart et al. extended this result to continuous-state branching processes with immigration. We generalize these

Laura Cobden, Jingyi Zhuang, Wenjie Lei, Renata Wentzcovitch

Joint interpretation of bulk and shear wave speeds constrains the chemistry of the deep mantle. At all depths, the diversity of wave speeds cannot be explained by an isochemical mantle. Between 1000 and 2500 km depth, hypothetical mantle models containing an electronic spin crossover in (Mg,Fe)O provide a significantly better fit to the wave-speed distributi

Peng Gao, Renrui Zhang, Rongyao Fang, Ziyi Lin

Masked Autoencoders (MAE) have been popular paradigms for large-scale vision representation pre-training. However, MAE solely reconstructs the low-level RGB signals after the decoder and lacks supervision upon high-level semantics for the encoder, thus suffering from sub-optimal learned representations and long pre-training epochs. To alleviate this, previou

Enes Suyabatmaz, Raphael F. Ribeiro

Chemical reactions and energy transport phenomena have been experimentally reported to be significantly affected by strong light-matter interactions and vibrational polariton formation. These quasiparticles exhibit nontrivial transport phenomena due to the long-range correlations induced by the photonic system and elastic and inelastic scattering processes d

Seginus Mowlavi

Many results about the geometry of the trianguline variety have been obtained by Breuil-Hellmann-Schraen. Among them, using geometric methods, they have computed a formula for the dimension of the tangent space of the trianguline variety at dominant crystalline generic points, which has a conjectural generalisation to companion (i.e. non-dominant) points. In

Antonio Bucciarelli, Antonino Salibra

Clones of operations of arity omega (referred to as omega-operations) have been employed by Neumann to represent varieties of infinitary algebras defined by operations of at most arity omega. More recently, clone algebras have been introduced to study clones of functions, including omega-operations, within the framework of one-sorted universal algebra. Addit

Aengus Lynch, Gbètondji J-S Dovonon, Jean Kaddour, Ricardo Silva

The problem of spurious correlations (SCs) arises when a classifier relies on non-predictive features that happen to be correlated with the labels in the training data. For example, a classifier may misclassify dog breeds based on the background of dog images. This happens when the backgrounds are correlated with other breeds in the training data, leading to

Jocienne N. Nelson, Anthony D. Rice, Rafal Kurleto, Amanda Shackelford

MX monopnictide compounds (M=Nb,Ta, X = As,P) are prototypical three-dimensional Weyl semimetals (WSMs) that have been shown in bulk single crystal form to have potential for a wide variety of novel devices due to topologically protected band structures and high mobilities. However, very little is known about thin film synthesis, which is essential to enable

Linghan Zhong, Ryan Lindeborg, Jesse Zhang, Joseph J. Lim

Program synthesis aims to automatically construct human-readable programs that satisfy given task specifications, such as input/output pairs or demonstrations. Recent works have demonstrated encouraging results in a variety of domains, such as string transformation, tensor manipulation, and describing behaviors of embodied agents. Most existing program synth

Rubén A. Hidalgo, Yerika Marín Montilla, Saúl Quispe

Conformal/anticonformal actions of the quasi-abelian group $QA_{n}$ of order $2^n$, for $n\geq 4$, on closed Riemann surfaces, pseudo-real Riemann surfaces and closed Klein surfaces are considered. We obtain several consequences, such as the solution of the minimum genus problem for the $QA_n$-actions, and for each of these actions, we study the topological

Giorgio Metafune, Luigi Negro, Chiara Spina

We study elliptic and parabolic problems governed by singular elliptic operators \begin{equation*} \mathcal L =\sum_{i,j=1}^{N+1}q_{ij}D_{ij}+\frac c y D_y \end{equation*} in the half-space $\mathbb{R}^{N+1}_+=\{(x,y): x \in \mathbb{R}^N, y>0\}$ under Neumann boundary conditions at $y=0$. More general operators and oblique derivative boundary conditions will

Michele Guerreri, Sean Epstein, Hojjat Azadbakht, Hui Zhang

Quantitative MRI (qMRI) aims to map tissue properties non-invasively via models that relate these unknown quantities to measured MRI signals. Estimating these unknowns, which has traditionally required model fitting - an often iterative procedure, can now be done with one-shot machine learning (ML) approaches. Such parameter estimation may be complicated by

Ghazal Alinezhad Noghre, Armin Danesh Pazho, Vinit Katariya, Hamed Tabkhi

Pose-based anomaly detection is a video-analysis technique for detecting anomalous events or behaviors by examining human pose extracted from the video frames. Utilizing pose data alleviates privacy and ethical issues. Also, computation-wise, the complexity of pose-based models is lower than pixel-based approaches. However, it introduces more challenges, suc

Ankur Kushwaha, Kiran M. Jayasurya, Vivek K. Agrawal, Anuj Nandi

We present a detailed spectro-polarimetric study of Black hole X-ray binary 4U $1630-47$ during its $2022$ outburst with IXPE and NICER observations. The source is observed in disk dominated thermal state (kT$_{in}\approx1.4$ keV) with clear detection of absorption features at $6.69\pm0.01$ keV and $6.97\pm0.01$ keV from both NICER as well as IXPE spectra, l

Ionut Moraru, Tsvetan Zhivkov, Shaun Coutts, Dom Li

Climate change, increase in world population and the war in Ukraine have led nations such as the UK to put a larger focus on food security, while simultaneously trying to halt declines in biodiversity and reduce risks to human health posed by chemically-reliant farming practices. Achieving these goals simultaneously will require novel approaches and accelera

Cyrill B. Muratov, Matteo Novaga, Philip Zaleski

This paper addresses the ill-posedness of the classical Rayleigh variational model of conducting charged liquid drops by incorporating the discreteness of the elementary charges. Introducing the model that describes two immiscible fluids with the same dielectric constant, with a drop of one fluid containing a fixed number of elementary charges together with

Sandip Purnapatra, Conor Miller-Lynch, Stephen Miner, Yu Liu

Touch-based fingerprint biometrics is one of the most popular biometric modalities with applications in several fields. Problems associated with touch-based techniques such as the presence of latent fingerprints and hygiene issues due to many people touching the same surface motivated the community to look for non-contact-based solutions. For the last few ye

Zhengmao Zhu, Yuren Liu, Honglong Tian, Yang Yu

Playing an important role in Model-Based Reinforcement Learning (MBRL), environment models aim to predict future states based on the past. Existing works usually ignore instantaneous dependence in the state, that is, assuming that the future state variables are conditionally independent given the past states. However, instantaneous dependence is prevalent in

Dulanjana M. Perera, Dimuthu D. K. Arachchige, Sanjaya Mallikarachchi, Talal Ghafoor

Soft robotics holds tremendous potential for various applications, especially in unstructured environments such as search and rescue operations. However, the lack of autonomy and teleoperability, limited capabilities, absence of gait diversity and real-time control, and onboard sensors to sense the surroundings are some of the common issues with soft-limbed

Hannah Rose Kirk, Bertie Vidgen, Paul Röttger, Scott A. Hale

Large language models (LLMs) are used to generate content for a wide range of tasks, and are set to reach a growing audience in coming years due to integration in product interfaces like ChatGPT or search engines like Bing. This intensifies the need to ensure that models are aligned with human preferences and do not produce unsafe, inaccurate or toxic output

Vikram Soni

We consider a variational 'crystalline' equation of state (EOS) that follows from nucleons that are chiral solitons with deep relativistic quark bound states. In this model conventional quark matter does not occur till a high density threshold at which the quark bound states in the nucleons get compressed and merge with the continuum. Once the barrier at thi

Jian-Xiang Qiu, Christian Tzschaschel, Junyeong Ahn, Anyuan Gao

Using circularly-polarized light to control quantum matter is a highly intriguing topic in physics, chemistry and biology. Previous studies have demonstrated helicity-dependent optical control of spatial chirality and magnetization $M$. The former is central for asymmetric synthesis in chemistry and homochirality in bio-molecules, while the latter is of grea

Godfrin Ismail, Kenneth Chesoli, Golda Moni, Kinyua Gikunda

Autism Spectrum Disorder (ASD) is one neuro developmental disorder that is now widespread in the world. ASD persists throughout the life of an individual, impacting the way they behave and communicate, resulting to notable deficits consisting of social life retardation, repeated behavioural traits and a restriction in their interests. Early detection of the

Sören Christensen, Simon Fischer, Oskar Hallmann

Let $W$ be a standard Brownian motion with $W_0 = 0$ and let $b: \mathbb{R}_+ \to \mathbb{R}$ be a continuous function with $b(0) > 0$. The first passage time (from below) is then defined as \begin{align*} \tau := \inf \{ t \geq 0 \vert W_t \geq b(t) \}. \end{align*} It is well-known that the distribution $F$ of $\tau$ satisfies a set of Fredholm equations o

Vineet Rawat, M. R. Samal, D. L. Walker, A. Zavagno

Clouds more massive than about $10^5$ M$_\odot$ are potential sites of massive cluster formation. Studying the properties of such clouds in the early stages of their evolution offers an opportunity to test various cluster formation processes. We make use of CO, Herschel, and UKIDSS observations to study one such cloud, G148.24+00.41. Our results show the clo

Xiao Tang, Sicong Liu

Visible light communication (VLC) has been widely applied as a promising solution for modern short range communication. When it comes to the deployment of LED arrays in VLC networks, the emerging ultra-dense network (UDN) technology can be adopted to expand the VLC network's capacity. However, the problem of inter-cell interference (ICI) mitigation and effic

Ruzin Ağanoğlu, Beate Klösgen, Agnes Sandner, Iris Traulsen

In the early phase of the COVID-19 pandemic, the Working Group on Equal Opportunities of the German Physical Society conducted a nonrepresentative, international online survey, investigating the impact of the pandemic and its consequences on daily life and work. Special attention was paid to the situation of female physicists in academia and industry. The re

Aatiya Ali, Viacheslav Sadykov, Alexander Kosovichev, Irina N. Kitiashvili

Solar Energetic Particle (SEP) events and their major subclass, Solar Proton Events (SPEs), can have unfavorable consequences on numerous aspects of life and technology, making them one of the most harmful effects of solar activity. Garnering knowledge preceding such events by studying operational data flows is essential for their forecasting. Considering on

Junghyun Lee, Laura Schmid, Se-Young Yun

Multi-armed bandits are extensively used to model sequential decision-making, making them ubiquitous in many real-life applications such as online recommender systems and wireless networking. We consider a multi-agent setting where each agent solves their own bandit instance endowed with a different set of arms. Their goal is to minimize their group regret w

Ting-Chun Lin, John McGreevy

We derive an entropy formula satisfied by the ground states of 1+1D conformal field theories. The formula implies that the ground state is the critical point of an entropy function. We conjecture that this formula may serve as an information-theoretic criterion for conformal field theories, which differs from the conventional algebraic definition. In additio

Savita Pareek, Kalyan Das, Siuli Mukhopadhyay

This work proposes a statistical model for crossover trials with multiple skewed responses measured in each period. A 3 $\times$ 3 crossover trial data where different drug doses were administered to subjects with a history of seasonal asthma rhinitis to grass pollen is used for motivation. In each period, gene expression values for ten genes were measured f

Dorian Goldfeld, Eric Stade, Michael Woodbury

Fourier coefficients of Eisenstein series figure prominently in the study of automorphic L-functions via the Langlands-Shahidi method, and in various other aspects of the theory of automorphic forms and representations. In this paper, we define Langlands Eisenstein series for ${\rm SL}(n,\mathbb Z)$ in an elementary manner, and then determine the first Fouri

ATLAS Collaboration

A search for vector-like leptons in multilepton (two, three, or four-or-more electrons plus muons) final states with zero or more hadronic $\tau$-lepton decays is presented. The search is performed using a dataset corresponding to an integrated luminosity of 139 fb$^{-1}$ of proton$-$proton collisions at a centre-of-mass energy of 13 TeV recorded by the ATLA

Marco Padovani

A field with particularly exciting results over the past few years is the study of the interaction of cosmic rays with interstellar matter. For star formation to take place, gas and dust need to be sufficiently cold for gravity to overcome thermal pressure, and the ionisation fraction must be low enough to enable substantial decoupling between the gas and th

Fabian Mohn, Miriam Exner, Patryk Szwargulski, Martin Möddel

Objective. Magnetic Particle Imaging (MPI) is capable of high temporal resolution measurements of the spatial distribution of magnetic nanoparticles and therefore well suited for perfusion imaging, which is an important tool in medical diagnosis. Perfusion imaging in MPI usually requires a fresh bolus of tracer material to capture the key signal dynamics. He

Allah Ditta, Xia Tiecheng, Saadia Mumtaz, Farruh Atamurotov

This work mainly focuses to unveil the optical features of a black hole. For this objective, we utilize the metric-affine black hole geometry with the inclusion of dilation, spin, and shear charge. The Lagrangian coefficients $f_1$ and $d_1$ are the main parameters, where $f_1<0$, which differentiate the solutions by $d_1=8f_1,\;d_1=-8f_1,\;\&\;d_1=\pm8f_1$.

K. Ding, J. Liu, Y. Yang, K. Scholberg

There is a global trend to increase the light yield of CsI scintillators used in neutrino and dark matter detection by operating undoped crystals at cryogenic temperatures. However, high light yield alone is not sufficient to guarantee a low-energy threshold. The response of undoped crystals to nuclear recoils at cryogenic temperatures is equally important.

Vera Delfavero, Richard O'Shaughnessy, Krzysztof Belczynski, Paweł Drozda

Gravitational-wave observations have the capability to strongly differentiate between different assumptions for how binary compact objects form. In this work, we show how to carefully interpolate a marginal likelihood between choices of binary evolution model parameters. Using the StarTrack binary evolution code, we compare one- and four-dimensional binary e

Margalit Glasgow, Matthew Kwan, Ashwin Sah, Mehtaab Sawhney

Two landmark results in combinatorial random matrix theory, due to Koml\'os and Costello-Tao-Vu, show that discrete random matrices and symmetric discrete random matrices are typically nonsingular. In particular, in the language of graph theory, when $p$ is a fixed constant, the biadjacency matrix of a random Erd\H{o}s-R\'enyi bipartite graph $\mathbb{G}(n,n

Sacha Ikonicoff, Marcello Lanfranchi, Jean-Simon Pacaud Lemay

Tangent categories provide a categorical axiomatization of the tangent bundle. There are many interesting examples and applications of tangent categories in a variety of areas such as differential geometry, algebraic geometry, algebra, and even computer science. The purpose of this paper is to expand the theory of tangent categories in a new direction: the t

Diego Artacho, Marie-Amélie Lawn

Spinorial methods have proven to be a powerful tool to study geometric properties of spin manifolds. Our aim is to continue the spinorial study of manifolds that are not necessarily spin. We introduce and study the notion of $G$-invariance of spin$^r$ structures on a manifold $M$ equipped with an action of a Lie group $G$. For the case when $M$ is a homogene