April 2024 arXiv papers — page 46

Hamid Zakernezhad, Ali Soleimani, Milad Mohabbati

This article evaluates the types of typical renewable energy technologies separately. Switching from fossil-fuel-based technology to green energies is time-consuming and requires a high investment cost. In addition, the production of energy by new technology may cause the deactivation of some power plants, which will result in unemployment and negative econo

Chihiro Taguchi, Jefferson Saransig, Dayana Velásquez, David Chiang

This paper presents Killkan, the first dataset for automatic speech recognition (ASR) in the Kichwa language, an indigenous language of Ecuador. Kichwa is an extremely low-resource endangered language, and there have been no resources before Killkan for Kichwa to be incorporated in applications of natural language processing. The dataset contains approximate

Simranjit Singh, Michael Fore, Dimitrios Stamoulis

Geospatial Copilots unlock unprecedented potential for performing Earth Observation (EO) applications through natural language instructions. However, existing agents rely on overly simplified single tasks and template-based prompts, creating a disconnect with real-world scenarios. In this work, we present GeoLLM-Engine, an environment for tool-augmented agen

Riccardo Bolzonella, Jerome Alexandre Alozy, Rafael Ballabriga, Martin van Beuzekom

The timing performance of the Timepix4 application-specific integrated circuit (ASIC) bump-bonded to a $100\;\mu\textrm{m}$ thick n-on-p silicon sensor is presented. A picosecond pulsed infrared laser was used to generate electron-hole pairs in the silicon bulk in a repeatable fashion, controlling the amount, position and time of the stimulated charge signal

Mingyuan Xiang, Xuhan Xie, Pedro Savarese, Xin Yuan

Resistive random-access memory (RRAM) is widely recognized as a promising emerging hardware platform for deep neural networks (DNNs). Yet, due to manufacturing limitations, current RRAM devices are highly susceptible to hardware defects, which poses a significant challenge to their practical applicability. In this paper, we present a machine learning techniq

Phu N. Tran, Sattvic Ray, Linnea Lemma, Yunrui Li

Deep learning-based optical flow (DLOF) extracts features in adjacent video frames with deep convolutional neural networks. It uses those features to estimate the inter-frame motions of objects at the pixel level. In this article, we evaluate the ability of optical flow to quantify the spontaneous flows of MT-based active nematics under different labeling co

Rémi Morvan

We introduce "synchronous algebras", an algebraic structure tailored to recognize automatic relations (aka. synchronous relations, or regular relations). They are the equivalent of monoids for regular languages, however they conceptually differ in two points: first, they are typed and second, they are equipped with a dependency relation expressing constraint

Marcin Wątorek, Paweł Szydło, Jarosław Kwapień, Stanisław Drożdż

The non-fungible token (NFT) market emerges as a recent trading innovation leveraging blockchain technology, mirroring the dynamics of the cryptocurrency market. The current study is based on the capitalization changes and transaction volumes across a large number of token collections on the Ethereum platform. In order to deepen the understanding of the mark

Tommaso Rossi

This paper contains some results about the topology of $\M_{0,n+1}/\Sigma_n$, where $\M_{0,n+1}$ is the moduli space of genus zero Riemann surfaces with marked points. We show that $\M_{0,n+1}/\Sigma_n$ is not a topological manifold for $n\geq 4$, and it is simply connected for any $n\in\N$. We also present some homology computations: for example we show tha

Sergey Pastukhov

This paper introduces a novel algorithm for two-player deterministic games with perfect information, which we call PROBS (Predict Results of Beam Search). Unlike existing methods that predominantly rely on Monte Carlo Tree Search (MCTS) for decision processes, our approach leverages a simpler beam search algorithm. We evaluate the performance of our algorith

Zhongyuan Liu, Ruotian Gong, Benchen Huang, Yu Jin

The negatively charged boron-vacancy center ($\mathrm{V}_{\mathrm{B}}^-$) in hexagonal boron nitride (hBN) has recently emerged as a highly promising quantum sensor. Compared to the nitrogen-vacancy (NV) center in diamond, the change with temperature of the spin transition energy of $\mathrm{V}_{\mathrm{B}}^-$ is more than an order of magnitude larger, makin

Ioannis Kavouras, Ioannis Rallis, Emmanuel Sardis, Eftychios Protopapadakis

The scarcity of green spaces, in urban environments, consists a critical challenge. There are multiple adverse effects, impacting the health and well-being of the citizens. Small scale interventions, e.g. pocket parks, is a viable solution, but comes with multiple constraints, involving the design and implementation over a specific area. In this study, we ha

Emilio Cano Renteria, Jacob A. Schwartz, Jesse D. Jenkins

Advanced nuclear fission, which encompasses various innovative nuclear reactor designs, could contribute to the decarbonization of the United States electricity sector. However, little is known about how cost-competitive these reactors would be compared to other technologies, or about which aspects of their designs offer the most value to a decarbonized powe

David Adame-Carrillo, Delara Behzad, Kalle Kytölä

To connect conformal field theories (CFT) to probabilistic lattice models, recent works [HKV22, Ada23] have introduced a novel definition of local fields of the lattice models. Local fields in this picture are probabilistically concrete: they are built from random variables in the model. The key insight is that discrete complex analysis ideas allow to equip

Matthew Willetts, Christian Harrington

Maximal Extractable Value (MEV) in Constant Function Market Making is fairly well understood. Does having dynamic weights, as found in liquidity boostrap pools (LBPs), Temporal-function market makers (TFMMs), and Replicating market makers (RMMs), introduce new attack vectors? In this paper we explore how inter-block weight changes can be analogous to trades,

Jean-Philippe Corbeil

In natural language processing applied to the clinical domain, utilizing large language models has emerged as a promising avenue for error detection and correction on clinical notes, a knowledge-intensive task for which annotated data is scarce. This paper presents MedReAct'N'MedReFlex, which leverages a suite of four LLM-based medical agents. The MedReAct a

Aritra Banik, Sayani Das, Anil Maheshwari, Bubai Manna

In the Minimum Consistent Subset (MCS) problem, we are presented with a connected simple undirected graph $G=(V,E)$, consisting of a vertex set $V$ of size $n$ and an edge set $E$. Each vertex in $V$ is assigned a color from the set $\{1,2,\ldots, c\}$. The objective is to determine a subset $V' \subseteq V$ with minimum possible cardinality, such that for e

Furui Cheng, Vilém Zouhar, Robin Shing Moon Chan, Daniel Fürst

Understanding the behavior of large language models (LLMs) is crucial for ensuring their safe and reliable use. However, existing explainable AI (XAI) methods for LLMs primarily rely on word-level explanations, which are often computationally inefficient and misaligned with human reasoning processes. Moreover, these methods often treat explanation as a one-t

Peter Myung-Won Pak, Francis Ogoke, Andrew Polonsky, Anthony Garland

We present a deep learning approach for quantifying and localizing ex-situ porosity within Laser Powder Bed Fusion fabricated samples utilizing in-situ thermal image monitoring data. Our goal is to build the real time porosity map of parts based on thermal images acquired during the build. The quantification task builds upon the established Convolutional Neu

Gianpaolo Piscitelli

In this paper, we study the optimal constant in the nonlocal nonlinear Poincar\'e-Wirtinger inequality in $(a,b)\subset\mathbb R$: \begin{equation*} \lambda_\alpha(p,q,r){\left(\int_{a}^{b}|u|^{q}dx\right)^\frac pq}\le{\int_{a}^{b}|u'|^{p}dx+\alpha\left|\int_{a}^{b}|u|^{r-2}u\, dx\right|^{\frac p{r-1}}}, \end{equation*}where $\alpha\in\mathbb R$, $p,q,r >1$

Het Patel, Umair Rehman, Farkhund Iqbal

Phishing, a prevalent cybercrime tactic for decades, remains a significant threat in today's digital world. By leveraging clever social engineering elements and modern technology, cybercrime targets many individuals, businesses, and organizations to exploit trust and security. These cyber-attackers are often disguised in many trustworthy forms to appear as l

Marcello Basili, Luca Pratelli

In Basili and Pratelli (2024), a novel and coherent concept of interval probability measures has been introduced, providing a method for representing imprecise probabilities and uncertainty. Within the framework of set algebra, we introduced the concepts of weak complementation and interval probability measures associated with a family of random variables, w

Stefan Kiefer, Richard Mayr, Mahsa Shirmohammadi, Patrick Totzke

We study 2-player zero-sum concurrent (i.e., simultaneous move) stochastic B\"uchi games and Transience games on countable graphs. Two players, Max and Min, seek respectively to maximize and minimize the probability of satisfying the game objective. The B\"uchi objective is to visit a given set of target states infinitely often. This can be seen as a special

Abhner P. De Almeida, Gary A. Mamon, Avishai Dekel, Gastão B. Lima Neto

Nearby dwarf galaxies display a variety of effective radii (sizes) at a given stellar mass, suggesting different evolution scenarios according to their final "stellar" size. The TNG hydrodynamical simulations present a bimodality in the z = 0 size - mass relation (SMRz0) of dwarf galaxies, at $r_{1/2,\star}$ ~ 450 pc. Using the TNG50 simulation, we explored

Bernard Deconinck, Sergey A. Dyachenko, Anastassiya Semenova

We consider steady surface waves in an infinitely deep two--dimensional ideal fluid with potential flow, focusing on high-amplitude waves near the steepest wave with a 120 degree corner at the crest. The stability of these solutions with respect to coperiodic and subharmonic perturbations is studied, using new matrix-free numerical methods. We provide eviden

Anatoly Kuklov, Lode Pollet, Nikolay Prokof'ev, Boris Svistunov

Even when ideal solids are insulating, their states with crystallographic defects may have superfluid properties. It became clear recently that edge dislocations in $^4$He featuring a combination of microscopic quantum roughness and superfluidity of their cores may represent a new paradigmatic class of quasi-one-dimensional superfluids. The new state of matt

Ashot Minasyan, Motiejus Valiunas

We investigate criteria ensuring that a one-relator group $G$ contains a right-angled Artin subgroup $A(\Gamma)$, corresponding to a finite graph $\Gamma$. In particular, we prove that if $\Gamma$ is a forest with at least one edge and the positive submonoid $T(\Gamma)$, of $A(\Gamma)$, embeds into $G$ then so does all of $A(\Gamma)$. As by-products of our m

Zhaowei Liu, Mingchao Liu, K. Jimmy Hsia, Xiaonan Huang

Soft robots utilizing inflatable dielectric membranes can realize intricate functionalities through the application of non-mechanical fields. However, given the current limitations in simulations, including low computational efficiency and difficulty in dealing with complex external interactions, the design and control of such soft robots often require trial

Alexander Barzykin, Philippe Bergault, Olivier Guéant

The primary challenge of market making in spot precious metals is navigating the liquidity that is mainly provided by futures contracts. The Exchange for Physical (EFP) spread, which is the price difference between futures and spot, plays a pivotal role and exhibits multiple modes of relaxation corresponding to the diverse trading horizons of market particip

Peiyu Duan, Nicha C. Dvornek, Jiyao Wang, Jeffrey Eilbott

Children with Autism Spectrum Disorder (ASD) frequently exhibit comorbid anxiety, which contributes to impairment and requires treatment. Therefore, it is critical to investigate co-occurring autism and anxiety with functional imaging tools to understand the brain mechanisms of this comorbidity. Multidimensional Anxiety Scale for Children, 2nd edition (MASC-

Jahanfar Abouie, Daryoosh Vashaee

This study investigates the entanglement properties of quantum dots (QDs) under a universal Hamiltonian where the Coulomb interaction between particles (electrons or holes) decouples into a charging energy and an exchange coupling term. While this formalism typically decouples the charge and spin components, the confinement-induced energy splitting can induc

Van Cyr, Bryna Kra, Scott Schmieding

Motivated by Furstenberg's Theorem on sets in the circle invariant under multiplication by a non-lacunary semigroup, we define a general class of dynamical systems possessing similar topological dynamical properties. We call such systems chaotic almost minimal, reflecting that these systems are chaotic, but in some sense are close to minimal. We study proper

Robert L. Grossman

Cloud-based data commons, data meshes, data hubs, and other data platforms are important ways to manage, analyze and share data to accelerate research and to support reproducible research. This is an annotated glossary of some of the more common terms used in articles and discussions about these platforms.

M. Ryleigh Davis, Michael E. Brown

We examine high spatial resolution Galileo/NIMS observations of the young (~1 My - 20 My) impact features, Pwyll and Manann\'{a}n craters, on Europa's trailing hemisphere in an effort to constrain irradiation timescales. We characterize their composition using a linear spectral modeling analysis and find that both craters and their ejecta are depleted in hyd

Pedro P. da Silva, Carlos H. S. Vieira, Jonas F. G. Santos, Lucas S. Marinho

We explore the effects of Markovian bath coupling and initial position-momentum correlations on the coherence and purity of Gaussian quantum states. Our analysis focuses on the roles these factors play in the dynamics of quantum coherence, coherence lengths, and state purity. Our results reveal that initial position-momentum correlations have a remarkable im

Suresh Kumaar Jayaraman, Reid Simmons, Aaron Steinfeld, Henny Admoni

In this work, we aim to improve transparency and efficacy in human-robot collaboration by developing machine teaching algorithms suitable for groups with varied learning capabilities. While previous approaches focused on tailored approaches for teaching individuals, our method teaches teams with various compositions of diverse learners using team belief repr

Shuaifeng Li, Xiaoming Mao

Recent advances unveiled physical neural networks as promising machine learning platforms, offering faster and more energy-efficient information processing. Compared with extensively-studied optical neural networks, the development of mechanical neural networks (MNNs) remains nascent and faces significant challenges, including heavy computational demands and

O. Yesiltas, B. B. Oner

The supersymmetric analysis of spinning cosmic string spacetime, involving an electron in magnetic fields, has been conducted. We examined the Dirac system within extended special functions known as exceptional orthogonal polynomials. Corresponding Dirac system is transformed to a relativistic system with a nonlinear isotonic oscillator. Furthermore, new pot

Wang Liu, Cunhua Pan, Hong Ren, Cheng-Xiang Wang

Combining millimetre-wave (mmWave) communications with an extremely large-scale antenna array (ELAA) presents a promising avenue for meeting the spectral efficiency demands of the future sixth generation (6G) mobile communications. However, beam training for mmWave ELAA systems is challenged by excessive pilot overheads as well as insufficient accuracy, as t

Vinicius Branco, Paula R. T. Coelho, Ariane Lançon, Lucimara P. Martins

Most Galactic Globular Clusters (GCs) harbour multiple populations of stars (MPs), composed of at least two generations: the first characterized by a "standard" $\alpha$-enhanced metal mixture, as observed in field halo stars of the Milky Way, and the second displaying anti-correlated CN--ONa chemical abundance pattern in combination with an enhanced helium

Chandeepa Dissanayake, Chanuka Algama

In this work, we present an extensive analysis of clock synchronization algorithms, with a specific focus on message complexity. We begin by introducing fundamental concepts in clock synchronization, such as the Byzantine generals problem and specific concepts like clock accuracy, precision, skew, offset, timestamping, and clock drift estimation. Describing

Tuoyi Zhao, Wen-xin Zhou, Lan Wang

The data-driven newsvendor problem with features has recently emerged as a significant area of research, driven by the proliferation of data across various sectors such as retail, supply chains, e-commerce, and healthcare. Given the sensitive nature of customer or organizational data often used in feature-based analysis, it is crucial to ensure individual pr

Khalid Zobaid Adnan, Mahesh R. Neupane, Tianli Feng

Thermal boundary conductance (TBC) across metal diamond interfaces plays a critical role in the thermal management of future diamond based ultrawide bandgap semiconductor devices. Molecular dynamics is a sophisticated method to predict TBC but is limited by the lack of reliable potential describing metal diamond interfaces. In this work, we report the develo

Anastasio Fratangelo, Philipp Heil, Christine Klauser, Gjon Markaj

The novel technique of frequency-offset separated oscillatory fields (FOSOF) has been originally proposed as a modification to Ramsey's method of separated oscillatory fields. It has recently been employed in precision measurements with atomic beams since it allows for an alternative approach to determine absolute resonance frequencies. We present results fr

Viacheslav Meshcherinov, Viktor Kazakov, Maxim Spiridonov, Gennady Suvorov

Enhancement of methane emission measurement techniques is necessary to address the need for greenhouse gas emissions monitoring. Here we introduce a gas analyzer designed for remote sensing of atmospheric methane aboard unmanned aerial vehicles. This device employs the wavelength modulation spectroscopy approach and quadrature detection of laser radiation sc

Anshul S. Tomar, Shaede Perzanowski, Ricardo Mejia-Alvarez, Ranjan Mukherjee

Bernoulli pads generate locally large wall shear stresses on workpieces, which can be used for cleaning, but may also damage delicate surfaces. This work presents direct measurements of the wall shear stress using constant temperature anemometry for the first time. A hot-film sensor was calibrated in the laminar and turbulent flow regimes using a purpose-bui

Haiyang Hu, Wenzheng Lu, Rodrigo Berte, Stefan A Maier

In the rapidly evolving field of nanophotonics, achieving precise spectral and temporal light manipulation at the nanoscale remains a critical challenge. While photonic bound states in the continuum (BICs) have emerged as a powerful means of controlling light, their common reliance on geometrical symmetry breaking for obtaining tailored resonances makes them

Nino Guallart

This paper belongs to the field of probabilistic modal logic, focusing on a comparative analysis of two distinct semantics: one rooted in Kripke semantics and the other in neighbourhood semantics. The primary distinction lies in the following: The latter allows us to adequately express belief functions (lower probabilities) over propositions, whereas the for

R. A. Dumer, M. Godoy

Meta-stable states are identified in the Ising model with competition between the Glauber and Kawasaki dynamics. The model of interaction between magnetic moments was implemented on a network where the degree distribution follows a power-law of the form, $P(k)\sim k^{-\alpha}$. The evolution towards the stationary state occurred through the competition betwe

Sahana Balasubramanya, Georgia Burkhalter, Rachel Niebler, Roberta Shapiro

A group has Property $\mathrm{(NL)}$ if it does not admit a loxodromic element in any hyperbolic action. In other words, a group with this property is inaccessible for study from the perspective of hyperbolic actions. This property was introduced by Balasubramanya, Fournier-Facio and Genevois, who initiated the study of this property. We expand on this resea

Joseph Tu, Hilda Hadan, Derrick M. Wang, Sabrina A Sgandurra

This workshop paper presents a critical examination of the integration of Generative AI (Gen AI) into the academic writing process, focusing on the use of AI as a collaborative tool. It contrasts the performance and interaction of two AI models, Gemini and ChatGPT, through a collaborative inquiry approach where researchers engage in facilitated sessions to d

Darui Lu, Yang Deng, Jordan M. Malof, Willie J. Padilla

Large language models (LLMs) such as ChatGPT, Gemini, LlaMa, and Claude are trained on massive quantities of text parsed from the internet and have shown a remarkable ability to respond to complex prompts in a manner often indistinguishable from humans. For all-dielectric metamaterials consisting of unit cells with four elliptical resonators, we present a LL

Aminur Rahman

Experiments violating Bell's inequality appear to indicate deterministic models do not correspond to a realistic theory of quantum mechanics. The theory of pilot waves seemingly overcomes this hurdle via nonlocality and statistical dependence, however it necessitates the existence of "ghost waves". This manuscript develops a deterministic dynamical system wi

David Wallace

Phenomena in gauge theory are often described in the physics literature via a specific choice of gauge. In foundational and philosophical discussions this is often criticized as introducing gauge dependence, and contrasted against (often aspirational) "gauge-invariant" descriptions of the physics. I argue, largely in the context of scalar electrodynamics, th

Meng-Zhi Wu, Marko Toroš, Sougato Bose, Anupam Mazumdar

Matter-wave interferometry is susceptible to non-inertial noise sources, which can induce dephasing and a resulting loss of interferometric visibility. Here, we focus on inertial torsion noise (ITN), which arises from the rotational motion of the experimental apparatus suspended by a thin wire and subject to random external torques. We provide analytical exp

Jason Blocklove, Siddharth Garg, Ramesh Karri, Hammond Pearce

Large Language Models (LLMs) have demonstrated capabilities for producing code in Hardware Description Languages (HDLs). However, most of the focus remains on their abilities to write functional code, not test code. The hardware design process consists of both design and test, and so eschewing validation and verification leaves considerable potential benefit

Yanjun Han, Tianze Jiang, Yihong Wu

Consider the problem of predicting the next symbol given a sample path of length n, whose joint distribution belongs to a distribution class that may have long-term memory. The goal is to compete with the conditional predictor that knows the true model. For both hidden Markov models (HMMs) and renewal processes, we determine the optimal prediction risk in Ku

Daniele Grandi, Yash Patawari Jain, Allin Groom, Brandon Cramer

Material selection is a crucial step in conceptual design due to its significant impact on the functionality, aesthetics, manufacturability, and sustainability impact of the final product. This study investigates the use of Large Language Models (LLMs) for material selection in the product design process and compares the performance of LLMs against expert ch

Zheng Sun

The Runge--Kutta (RK) discontinuous Galerkin (DG) method is a mainstream numerical algorithm for solving hyperbolic equations. In this paper, we use the linear advection equation in one and two dimensions as a model problem to prove the following results: For an arbitrarily high-order RKDG scheme in Butcher form, as long as we use the $P^k$ approximation in

Anushree Datta, Daniele Guerci, Mark O. Goerbig, Christophe Mora

Helical trilayer graphene (hTG) exhibits a supermoir\'e pattern with large domains centered around stacking points ABA and BAB, where two well-separated low-energy bands appear with different total Chern numbers at each valley, forming a Chern mosaic pattern. In the chiral limit, the low-energy bands become exactly flat at zero energy for magic-angle twists.

Hongyi Cai, Mohammad Mahdinur Rahman, Wenzhen Dong, Jingyu Wu

Feature pyramids have been widely adopted in convolutional neural networks and transformers for tasks in medical image segmentation. However, existing models generally focus on the Encoder-side Transformer for feature extraction. We further explore the potential in improving the feature decoder with a well-designed architecture. We propose Cross Feature Pyra

Pisin Chen, Kuan-Nan Lin, Wei-Chen Lin, Dong-han Yeom

We investigate the cosmological observables using the Euclidean path integral approach. Specifically, we study both the no-boundary compact instantons scenario and the Euclidean wormholes scenario that can induce the creation of two universes from nothing. It is known that perturbations associated with the no-boundary scenario can only be consistent with the

Weifeng Chen, Jiacheng Zhang, Jie Wu, Hefeng Wu

The rapid development of diffusion models has triggered diverse applications. Identity-preserving text-to-image generation (ID-T2I) particularly has received significant attention due to its wide range of application scenarios like AI portrait and advertising. While existing ID-T2I methods have demonstrated impressive results, several key challenges remain:

Serhii Favorov

We study properties of temperate non-negative purely atomic measures in the Euclidean space such that the distributional Fourier transform of these measures are pure point ones. A connection between these measures and almost periodicity is shown, several forms of the uniqueness theorem are proved. We also obtain necessary and sufficient conditions for a meas

Moyuru Yamada

Diffusion models have demonstrated their capability to synthesize high-quality and diverse images from textual prompts. However, simultaneous control over both global contexts (e.g., object layouts and interactions) and local details (e.g., colors and emotions) still remains a significant challenge. The models often fail to understand complex descriptions in

Jason Blocklove, Md Raz, Prithwish Basu Roy, Hammond Pearce

Cybersecurity threats in Additive Manufacturing (AM) are an increasing concern as AM adoption continues to grow. AM is now being used for parts in the aerospace, transportation, and medical domains. Threat vectors which allow for part compromise are particularly concerning, as any failure in these domains would have life-threatening consequences. A major cha

Saeid Abbassi, Kamaledin Ghiasi-Shirazi, Ahad Harati

Capsule networks are a type of neural network that identify image parts and form the instantiation parameters of a whole hierarchically. The goal behind the network is to perform an inverse computer graphics task, and the network parameters are the mapping weights that transform parts into a whole. The trainability of capsule networks in complex data with hi

Yaqiao Li, Mahtab Masoori, Lata Narayanan, Denis Pankratov

We study the Renting Servers in the Cloud problem (RSiC) in multiple dimensions. In this problem, a sequence of multi-parameter jobs must be scheduled on servers that can be rented on-demand. Each job has an arrival time, a finishing time, and a multi-dimensional size vector that specifies its resource demands. Each server has a multi-dimensional capacity an

Wijnand van Woerkom, Benno van den Berg

If a locally cartesian closed category carries a weak factorisation system, then the left maps are stable under pullback along right maps if and only if the right maps are closed under pushforward along right maps. We refer to this statement as the Frobenius equivalence and in this paper we state and prove an analogical statement for algebraic weak factorisa

Dmitriy N. Kim, Or Hen, Gerald A. Miller, E. Piasetzky

The relationship between medium modifications of nucleon electromagnetic form factors and nucleon structure functions is examined using a model motivated by Light-Front Holographic QCD (LFHQCD). These modifications are closely connected with the influence of short-ranged correlations. The size of the modifications to nucleon form factors is shown to be about

D. A. Coulter, C. D. Kilpatrick, D. O. Jones, R. J. Foley

We present an ultraviolet-to-infrared search for the electromagnetic (EM) counterpart to GW190425, the second-ever binary neutron star (BNS) merger discovered by the LIGO-Virgo-KAGRA Collaboration (LVK). GW190425 was more distant and had a larger localization area than GW170817, therefore we use a new tool teglon to redistribute the GW190425 localization pro

Jiahe Ling, Corey B. Jackson

This study delves into the pivotal role played by non-experts in knowledge production on open collaboration platforms, with a particular focus on the intricate process of tag development that culminates in the proposal of new glitch classes. Leveraging the power of Association Rule Mining (ARM), this research endeavors to unravel the underlying dynamics of c

Khalid Zobaid Adnan, Tianli Feng

At the nanoscale, the thermal boundary conductance (TBC) and thermal conductivity are not intrinsic properties of interfaces or materials but depend on the nearby environment. However, most studies focused on single interfaces or superlattices, and the thermal transport across heterostructures formed by multiple different materials is still mysterious. In th

Herbert Egger, Idoia Cortes Garcia, Vsevolod Shashkov, Michael Wiesheu

A novel strategy is proposed for the coupling of field and circuit equations when modeling power devices in the low-frequency regime. The resulting systems of differential-algebraic equations have a particular geometric structure which explicitly encodes the energy storage, dissipation, and transfer mechanisms. This implies a power balance on the continuous

Yergali Kurmanov, Kuantay Boshkayev, Talgar Konysbayev, Orlando Luongo

We investigate a family of spherically symmetric, static, charged regular black hole solutions derived within the framework of Einstein-nonlinear electrodynamics. Our study focuses on examining the characteristics of accretion disks in the spacetimes described by the Dymnikova and Fan-Wang solutions. We explore circular geodesics of test particles and calcul

Alina Pleli, Simon Baeuerle, Michel Janus, Jonas Barth

Unsupervised clustering of wafer map defect patterns is challenging because the appearance of certain defect patterns varies significantly. This includes changing shape, location, density, and rotation of the defect area on the wafer. We present a harvesting approach, which can cluster even challenging defect patterns of wafer maps well. Our approach makes u

Enkelejda Kasneci, Hong Gao, Suleyman Ozdel, Virmarie Maquiling

Eye-tracking technology is widely used in various application areas such as psychology, neuroscience, marketing, and human-computer interaction, as it is a valuable tool for understanding how people process information and interact with their environment. This tutorial provides a comprehensive introduction to eye tracking, from the basics of eye anatomy and

Xiaolong Han, Pouria Salekani

We continue our investigation of the fractal uncertainty principle (FUP) for random fractal sets. In the prequel (arXiv:2107.08276), we considered the Cantor sets in the discrete setting with alphabets randomly chosen from a base of digits so the dimension d is in (0,2/3). We proved that, with overwhelming probability, the FUP with an exponent >=1/2-3d/4- ho

Bradford J. Foley

Nearly 30 years after the discovery of the first exoplanet around a main sequence star, thousands of planets have now been confirmed. These discoveries have completely revolutionized our understanding of planetary systems, revealing types of planets that do not exist in our solar system but are common in extrasolar systems, and a wide range of system archite

Eva E. Stüeken, Stephanie L. Olson, Eli Moore, Bradford J. Foley

Planet Earth has evolved from an entirely anoxic planet with possibly a different tectonic regime to the oxygenated world with horizontal plate tectonics that we know today. For most of this time, Earth has been inhabited by a purely microbial biosphere albeit with seemingly increasing complexity over time. A rich record of this geobiological evolution over

Edward W. Schwieterman, Michaela Leung

This chapter reviews proposed exoplanet biosignatures, including their biological origins, observable features, atmospheric sinks, and potentially confounding abiotic sources. Emphasis is placed on material published since past comprehensive reviews while providing a foundational understanding of each named biosignature. Topics include possible gaseous biosi

Eliza M. -R. Kempton, Heather A. Knutson

The field of exoplanet atmospheric characterization has recently made considerable advances with the advent of high-resolution spectroscopy from large ground-based telescopes and the commissioning of the James Webb Space Telescope (JWST). We have entered an era in which atmospheric compositions, aerosol properties, thermal structures, mass loss, and three-di

David A. Brain, Melodie M. Kao, Joseph G. O'Rourke

Planetary magnetic fields are important indicators of planetary processes and evolution, from a planet's outer core to its surface (if it possesses one) to its atmosphere and near-space environment. Magnetic fields are most directly measured in situ, and determining whether distant planetary objects possess magnetic fields can be challenging. At present we h

Keith D. Putirka

We'll examine plate tectonics on Earth -- its features and forces -- and examine some concepts that may allow astronomers to ask useful questions regarding numeric models that putatively predict tectonic activity. But exo-planetologists should be aware that geologists are still attempting to understand: why does Earth operates as it does, and so much differe

Claire Marie Guimond, Haiyang Wang, Fabian Seidler, Paolo Sossi

This review is focused on describing the logic by which we make predictions of exoplanetary compositions and mineralogies, and how these processes could lead to compositional diversity among rocky exoplanets. We use these predictions to determine the sensitivity of present-day and future observations to detecting compositional differences between rocky exopl

Keith D. Putirka

This chapter begins with some basic concepts regarding the structure and mineralogy of rocky planets, how to read and construct ternary diagrams, and why partial melting occurs when plate tectonics is operative. Partial melting is a key concept in that it governs crust and core formation, which in turn control mineralogy. These sections are for astronomers,

Siyi Xu, Laura K. Rogers, Simon Blouin

White dwarf planetary systems provide a unique way to measure the bulk composition of exoplanetary material. Extrasolar asteroids/comets/moons which have survived the evolution of their host star can end up in the atmosphere of the white dwarf. Asteroids and boulders appear to be the most common pollutants, where we use the term "asteroids" to refer to the p

Rhian H. Jones

Meteorites are a remarkable resource. They capture the imagination of people worldwide with their spectacular entry through Earth's atmosphere as fireballs, and their exotic character of being pieces of other worlds. Scientifically, they are critical to interpreting the early stages of formation of the Solar System, as well as the geological evolution of ast

Ke Zhang

Planets are formed inside disks around young stars. The gas, dust, and ice in these natal disks are the building materials of planets, and therefore their compositions fundamentally shape the final chemical compositions of planets. In this review, we summarize current observations of molecular lines in protoplanetary disks, from near-infrared to millimeter w

Natalie R. Hinkel, Allison Youngblood, Melinda Soares-Furtado

It has become a common practice within the exoplanet field to say that "to know the star is to know the planet." The properties of the host star have a strong, direct influence on the interior and surface conditions of the orbiting planet and oftentimes measurements of planetary properties are made relative to the star's properties. Not only are observationa

Jesse Comer

A famous result due to Lov\'{a}sz states that two finite relational structures $M$ and $N$ are isomorphic if, and only if, for all finite relational structures $T$, the number of homomorphisms from $T$ to $M$ is equal to the number of homomorphisms from $T$ to $N$. Since first-order logic (FOL) can describe finite structures up to isomorphism, this can be in

João Monteiro, Étienne Marcotte, Pierre-André Noël, Valentina Zantedeschi

In-context learning (ICL) approaches typically leverage prompting to condition decoder-only language model generation on reference information. Just-in-time processing of a context is inefficient due to the quadratic cost of self-attention operations, and caching is desirable. However, caching transformer states can easily require almost as much space as the

Kinya Toride, Matthew Newman, Andrew Hoell, Antonietta Capotondi

We introduce an interpretable-by-design method, optimized model-analog, that integrates deep learning with model-analog forecasting which generates forecasts from similar initial climate states in a repository of model simulations. This hybrid framework employs a convolutional neural network to estimate state-dependent weights to identify initial analog stat

Karen Roberts-Licklider, Theodore Trafalis

The aim of this study is to look at predicting whether a person will complete a drug and alcohol rehabilitation program and the number of times a person attends. The study is based on demographic data obtained from Substance Abuse and Mental Health Services Administration (SAMHSA) from both admissions and discharge data from drug and alcohol rehabilitation c

Zakaria Mhammedi, Dylan J. Foster, Alexander Rakhlin

Simulators are a pervasive tool in reinforcement learning, but most existing algorithms cannot efficiently exploit simulator access -- particularly in high-dimensional domains that require general function approximation. We explore the power of simulators through online reinforcement learning with {local simulator access} (or, local planning), an RL protocol

Santiago Agui Salcedo, Thomas Colas, Enrico Pajer

In our quest to understand the generation of cosmological perturbations, we face two serious obstacles: we do not have direct information about the environment experienced by primordial perturbations during inflation, and our observables are practically limited to correlators of massless fields, heavier fields and derivatives decaying exponentially in the nu

Salvador Centelles Chuliá, Antonio Herrero-Brocal, Avelino Vicente

We provide a comprehensive analysis of the Type-I Seesaw family of neutrino mass models, including the conventional type-I seesaw and its low-scale variants, namely the linear and inverse seesaws. We establish that all these models essentially correspond to a particular form of the type-I seesaw in the context of explicit lepton number violation. We then foc

Naomi Gendler, Cumrun Vafa

The dark dimension scenario, which is motivated from Swampland principles and predicts a single micron scale extra dimension, suggests a consistent framework for the dark sector of the universe. We consider the implications of this scenario for the QCD axion. We find that in the scenario in which the axion is localized on the standard model brane (which we w

Feige Wang, Jinyi Yang, Xiaohui Fan, Bram Venemans

The [CII] 158 $\mu$m emission line and the underlying far-infrared (FIR) dust continuum are important tracers for studying star formation and kinematic properties of early galaxies. We present a survey of the [CII] emission lines and FIR continua of 31 luminous quasars at $z>6.5$ using the Atacama Large Millimeter Array (ALMA) and the NOrthern Extended Milli

Yannik Schuler

A two-component Looijenga pair is a rational smooth projective surface with an anticanonical divisor consisting of two transversally intersecting curves. We establish an all-genus correspondence between the logarithmic Gromov-Witten theory of a two-component Looijenga pair and open Gromov-Witten theory of a toric Calabi-Yau threefold geometrically engineered