May 2023 arXiv papers — page 183

Fatemeh Kayanikhoo, Mateusz Kapusta, Miljenko Čemeljić

We study the structure and total energy of a strange quark star (SQS) endowed with a strong magnetic field with different rotational frequencies. The MIT bag model is used, with the density-dependent bag constant for the equation of state (EOS). The EOS is computed considering the Landau quantization effect regarding the strong magnetic fields (up to $5\time

Tatsuya Akiba, Ann-Marie Madigan

Gravitational wave recoil kicks from merging supermassive black hole binaries can have a profound effect on the surrounding stellar population. In this work, we study the dynamic and kinematic properties of nuclear star clusters following a recoil kick. We show that these post-kick structures present unique signatures that can provide key insight to observat

Kai Klede, Leo Schwinn, Dario Zanca, Björn Eskofier

Clustering is at the very core of machine learning, and its applications proliferate with the increasing availability of data. However, as datasets grow, comparing clusterings with an adjustment for chance becomes computationally difficult, preventing unbiased ground-truth comparisons and solution selection. We propose FastAMI, a Monte Carlo-based method to

Erlin Pan, Zhao Kang

Graph neural networks (GNNs) based methods have achieved impressive performance on node clustering task. However, they are designed on the homophilic assumption of graph and clustering on heterophilic graph is overlooked. Due to the lack of labels, it is impossible to first identify a graph as homophilic or heterophilic before a suitable GNN model can be fou

Robin Willems, Koen L. P. M. Janssens, Peter H. M. Bovendeerd, Clemens V. Verhoosel

The finite element method (FEM) is commonly used in computational cardiac simulations. For this method, a mesh is constructed to represent the geometry and, subsequently, to approximate the solution. To accurately capture curved geometrical features many elements may be required, possibly leading to unnecessarily large computation costs. Without loss of accu

Anay Mehrotra, Nisheeth K. Vishnoi

Subset selection tasks, arise in recommendation systems and search engines and ask to select a subset of items that maximize the value for the user. The values of subsets often display diminishing returns, and hence, submodular functions have been used to model them. If the inputs defining the submodular function are known, then existing algorithms can be us

Jiyuan Pei, Hao Tong, Jialin Liu, Yi Mei

For solving combinatorial optimisation problems with metaheuristics, different search operators are applied for sampling new solutions in the neighbourhood of a given solution. It is important to understand the relationship between operators for various purposes, e.g., adaptively deciding when to use which operator to find optimal solutions efficiently. Howe

Heewoo Jun, Alex Nichol

We present Shap-E, a conditional generative model for 3D assets. Unlike recent work on 3D generative models which produce a single output representation, Shap-E directly generates the parameters of implicit functions that can be rendered as both textured meshes and neural radiance fields. We train Shap-E in two stages: first, we train an encoder that determi

Zhanghao Sun, Sunil Pai, Carson Valdez, Maziyar Milanizadeh

Optical phase measurement is critical for many applications and traditional approaches often suffer from mechanical instability, temporal latency, and computational complexity. In this paper, we describe compact phase sensor arrays based on integrated photonics, which enable accurate and scalable reference-free phase sensing in a few measurement steps. This

Yuehaw Khoo, Michael Lindsey, Hongli Zhao

Fueled by the expressive power of deep neural networks, normalizing flows have achieved spectacular success in generative modeling, or learning to draw new samples from a distribution given a finite dataset of training samples. Normalizing flows have also been applied successfully to variational inference, wherein one attempts to learn a sampler based on an

Marianne Akian, Stéphane Gaubert, Ulysse Naepels, Basile Terver

We analyse an algorithm solving stochastic mean-payoff games, combining the ideas of relative value iteration and of Krasnoselskii-Mann damping. We derive parameterized complexity bounds for several classes of games satisfying irreducibility conditions. We show in particular that an $ε$-approximation of the value of an irreducible concurrent stochastic game

Benjamin Shade, Eduardo G. Altmann

Quantifying the dissimilarity of two texts is an important aspect of a number of natural language processing tasks, including semantic information retrieval, topic classification, and document clustering. In this paper, we compared the properties and performance of different dissimilarity measures $D$ using three different representations of texts -- vocabul

Alejandro Ayala, Wolfgang Bietenholz, Eleazar Cuautle, Rodrigo García Formentí

In heavy-ion reactions, statistical models predict a rapid change in the baryon-to-meson ratio as a function of the collision energy. This change occurs when the hadronic medium transits from a baryon- to a meson-dominated gas. The transition is expected to take place at a temperature around 140 MeV and a baryon chemical potential around 420 MeV, correspondi

Sudhanshu Arya, Ying Wang

We present a novel and first-of-its-kind information-theoretic framework for the key design consideration and implementation of a ground-to-UAV (G2U) communication network to minimize end-to-end transmission delay in the presence of interference. The proposed framework is useful as it describes the minimum transmission latency for an uplink ground-to-UAV com

Vishal Sawant, Debraj Chakraborty, Debasattam Pal

In this paper, the communication effort required in a multi-agent system (MAS) is minimized via an explicit optimization formulation. The paper considers a MAS of single-integrator agents with bounded inputs and a time-invariant communication graph. A new model of discrete asynchronous communication and a distributed consensus protocol based on it, are propo

Marcus Olofsson, Anton Grafström, Niklas L. P. Lundström

The local pivotal method (LPM) is a successful sampling method for taking well-spread samples from discrete populations. We show how the LPM can be utilized to sample from arbitrary continuous distributions and thereby give powerful variance reduction in general cases. The method creates an ``automatic stratification" on any continuous distribution, of a

Deepak Narayanan, Keshav Santhanam, Peter Henderson, Rishi Bommasani

Large language models (LLMs) power many state-of-the-art systems in natural language processing. However, these models are extremely computationally expensive, even at inference time, raising the natural question: when is the extra cost of deploying a larger model worth the anticipated boost in capabilities? Better understanding this tradeoff fundamentally c

D. K. Vysokikh, A. P. Bazakutsa, A. V. Dorofeenko, O. V. Butov

A model of an Er$^{3+}$/Yb$^{3+}$ co-doped glass gain medium is considered. The system of rate equations taking into account a minimum set of processes required to describe experimental data is built. As a result, a moderate number of fitting parameters is used, thereby increasing the model reliability. For the populations of the energy levels of Er$^{3+}$ a

Panagiotis Mougkogiannis, Andrew Adamatzky

This paper examines the modulation of proteinoid spiking frequency in response to light. Proteinoids are proteins formed through thermal condensation of amino acids and have been found to exhibit spiking behaviour in response to various stimuli. It has been demonstrated that their properties can be modulated by light, with the frequency of spikes changing in

Radek Suchánek

We describe a necessary condition for the local solvability of the strong inverse variational problem in the context of Monge-Ampère partial differential equations and first-order Lagrangians. This condition is based on comparing effective differential forms on the first jet bundle. To illustrate and apply our approach, we study the linear Klein-Gordon equat

C. R. Argüelles, K. Boshkayev, A. Krut, G. Nurbakhyt

Observations support the idea that supermassive black holes (SMBHs) power the emission at the center of active galaxies. However, contrary to stellar-mass BHs, there is a poor understanding of their origin and physical formation channel. In this article, we propose a new process of SMBH formation in the early Universe that is not associated with baryonic mat

Ali Mehrban, Pegah Ahadian

This paper discusses the impact of the Internet on modern trading and the importance of data generated from these transactions for organizations to improve their marketing efforts. The paper uses the example of Divar, an online marketplace for buying and selling products and services in Iran, and presents a competition to predict the percentage of a car sale

Lichang Chen, Minhao Cheng, Heng Huang

Backdoor learning has become an emerging research area towards building a trustworthy machine learning system. While a lot of works have studied the hidden danger of backdoor attacks in image or text classification, there is a limited understanding of the model's robustness on backdoor attacks when the output space is infinite and discrete. In this paper

Lichang Chen, Heng Huang, Minhao Cheng

Recent studies show that prompt tuning can better leverage the power of large language models than fine-tuning on downstream natural language understanding tasks. However, the existing prompt tuning methods have training instability issues, as the variance of scores under different random seeds is quite large. To address this critical problem, we first inves

Tobias Holck Colding, William P. Minicozzi

We prove sharp lower bounds for eigenvalues of the drift Laplacian for a modified Ricci flow. The modified Ricci flow is a system of coupled equations for a metric and weighted volume that plays an important role in Ricci flow. We will also show that there is a splitting theorem in the case of equality.

Athanasios Fotopoulos, Vasileios G. Karageorgopoulos, Vassilis S. Geroyannis

We study models of uniformly and differentially rotating neutron stars in the framework of post-Newtonian approximation in general relativity as established by Chandrasechar. In particular, we adopt the polytropic equation of state in order to derive the appropriate hydrodynamic equations and a rotation law based on the generalized Clement's model. To co

Iraj Eshghi, Alexandra Zidovska, Alexander Y. Grosberg

We solve a hydrodynamic model of active chromatin dynamics, within a confined geometry simulating the cell nucleus. Using both analytical and numerical methods, we describe the behavior of the chromatin polymer driven by the activity of motors having polar symmetry, both in the linear response regime as well as in the long-term, fully nonlinear regime of the

Maciej Buze, Manh Hong Duong

We develop a mathematical theory of entropic regularisation of unbalanced optimal transport problems. Focusing on static formulation and relying on the formalism developed for the unregularised case, we show that unbalanced optimal transport problems can be regularised in two qualitatively distinct ways - either on the original space or on the extended space

Narsireddy Anugu, Jacques Kluska, Tyler Gardner, John D. Monnier

Some evolved binaries, namely post-asymptotic giant branch binaries, are surrounded by stable and massive circumbinary disks similar to protoplanetary disks found around young stars. Around 10% of these disks are transition disks: they have a large inner cavity in the dust. Previous interferometric measurements and modeling have ruled out the cavity being fo

Alan Lew

The $k$-th token graph of a graph $G=(V,E)$ is the graph $F_k(G)$ whose vertices are the $k$-subsets of $V$ and whose edges are all pairs of $k$-subsets $A,B$ such that the symmetric difference of $A$ and $B$ forms an edge in $G$. Let $L(G)$ be the Laplacian matrix of $G$, and $L_k(G)$ be the Laplacian matrix of $F_k(G)$. It was shown by Dalfó et al. that fo

Karl N. Blodgett, David Peana, Saumitra Phatak, Lane M. Terry

We have imaged lithium-6 thousands of times in an optical tweezer using $Λ$-enhanced gray molasses cooling light. Despite being the lightest alkali, with a recoil temperature of 3.5 $μ$K, we achieve an imaging survival of 0.99950(2), which sets the new benchmark for low-loss imaging of neutral atoms in optical tweezers. Lithium is loaded directly from a MOT

M. O. Williams, Y. M. Psarellis, D. Pozharskiy, C. Chong

This chapter discusses the development and implementation of algorithms based on Equation-Free/Dynamic Data Driven Applications Systems (EF/DDDAS) protocols for the computer-assisted study of the bifurcation structure of complex dynamical systems, such as those that arise in biology (neuronal networks, cell populations), multiscale systems in physics, chemis

B. D. Appelbe, W. T. Taitano, A. J. Crilly, O. M. Mannion

The energy spectra of unscattered neutrons produced by deuterium-deuterium and deuterium-tritium fusion reactions are an important diagnostic in High Energy Density Physics experiments as the spectra are sensitive to the velocities of reacting ions. Methods exist for calculating these spectra in radiation-hydrodynamic ("hydro") and Particle-in-Cell (

Ryan Abbott, Michael S. Albergo, Aleksandar Botev, Denis Boyda

Applications of normalizing flows to the sampling of field configurations in lattice gauge theory have so far been explored almost exclusively in two space-time dimensions. We report new algorithmic developments of gauge-equivariant flow architectures facilitating the generalization to higher-dimensional lattice geometries. Specifically, we discuss masked au

Sai Chowdary Gullapally, Yibo Zhang, Nitin Kumar Mittal, Deeksha Kartik

Machine learning algorithms have the potential to improve patient outcomes in digital pathology. However, generalization of these tools is currently limited by sensitivity to variations in tissue preparation, staining procedures and scanning equipment that lead to domain shift in digitized slides. To overcome this limitation and improve model generalization,

Aleksandar Bukva, Koenraad Schalm, Jan Zaanen

We consider $Z_2$ gauge field theory coupled to "Higgs" matter fields invoking several copies of such matter, interacting entirely through the gauge fields, the $Z_2 \times Z_2 \times Z_2\cdots / Z_2$ and the $O(N) \times O(N) \times O(N) \cdots / Z_2$ families of theories. We discover that the Higgs phase of such theories is characterized by a hithe

Mohammed Benharrat, Flank D. M. Bezerra

In this paper we explore the theory of fractional powers of maximal accretive operators to obtain results of existence, regularity and behavior asymptotic of solutions for linear abstract evolution equations of third order in time.

Cathrin Elich, Iro Armeni, Martin R. Oswald, Marc Pollefeys

Intelligent robots require object-level scene understanding to reason about possible tasks and interactions with the environment. Moreover, many perception tasks such as scene reconstruction, image retrieval, or place recognition can benefit from reasoning on the level of objects. While keypoint-based matching can yield strong results for finding corresponde

Tristan Ballard, Matthew Cooper, Chris Lowrie, Gopal Erinjippurath

Carbon offset programs are critical in the fight against climate change. One emerging threat to the long-term stability and viability of forest carbon offset projects is wildfires, which can release large amounts of carbon and limit the efficacy of associated offsetting credits. However, analysis of wildfire risk to forest carbon projects is challenging beca

Daniel P. Keane, Colby J. Constantine, Matthew D. Mellor, Ryan Poling-Skutvik

Soft materials possessing tunable rheological properties are desirable in applications ranging from 3D printing to biological scaffolds. Here, we use a telechelic, triblock copolymer polystyrene-b-poly(ethylene oxide)-b-polystyrene (SEOS) to form elastic networks of polymer-linked droplets in cyclohexane-in-water emulsions. The SEOS endblocks partition into

Zhimeng Ouyang, Luis Silvestre

We consider weak solutions of the inhomogeneous non-cutoff Boltzmann equation in a bounded domain with any of the usual physical boundary conditions: in-flow, bounce-back, specular-reflection and diffuse-reflection. When the mass, energy and entropy densities are bounded above, and the mass density is bounded away from vacuum, we obtain an estimate of the $L

Sipra Mohapatra, Hema Teherpuria, Sapta Sindhu Paul Chowdhury, Suleman Jalilahmad Ansari

Using all-atom molecular dynamics simulations, we report the structure and ion transport characteristics of a new class of solid polymer electrolytes that contain biodegradable and mechanically stable biopolymer pectin. We simulate a highly conducting ethylene carbonate (EC) as a solvent for lithium-trifluoromethanesulfonimide (LiTFSI) salt containing differ

Xinghui Li, Kai Han, Xingchen Wan, Victor Adrian Prisacariu

We propose SimSC, a remarkably simple framework, to address the problem of semantic matching only based on the feature backbone. We discover that when fine-tuning ImageNet pre-trained backbone on the semantic matching task, L2 normalization of the feature map, a standard procedure in feature matching, produces an overly smooth matching distribution and signi

Guilherme Vicentin de Toledo, Yoni Zohar, Clark Barrett

We make two contributions to the study of theory combination in satisfiability modulo theories. The first is a table of examples for the combinations of the most common model-theoretic properties in theory combination, namely stable infiniteness, smoothness, convexity, finite witnessability, and strong finite witnessability (and therefore politeness and stro

Vasudha Kowtha, Miquel Espi Marques, Jonathan Huang, Yichi Zhang

This work investigates pretrained audio representations for few shot Sound Event Detection. We specifically address the task of few shot detection of novel acoustic sequences, or sound events with semantically meaningful temporal structure, without assuming access to non-target audio. We develop procedures for pretraining suitable representations, and method

Suryansh Upadhyay, Swaroop Ghosh

As the quantum computing ecosystem grows in popularity and utility it is important to identify and address the security and privacy vulnerabilities before they can be widely exploited. One major concern is the involvement of third party tools and hardware. Usage of untrusted hardware could present the risk of intellectual property (IP) theft. For example the

Talley Amir, James Aspnes

The population protocol model introduced by Angluin et al. in 2006 offers a theoretical framework for designing and analyzing distributed algorithms among limited-resource mobile agents. While the original population protocol model considers the concept of anonymity, the issue of privacy is not investigated thoroughly. However, there is a need for time- and

Seyed Vahid Moravvej, Seyed Jalaleddin Mousavirad, Diego Oliva, Fardin Mohammadi

Detecting plagiarism involves finding similar items in two different sources. In this article, we propose a novel method for detecting plagiarism that is based on attention mechanism-based long short-term memory (LSTM) and bidirectional encoder representations from transformers (BERT) word embedding, enhanced with optimized differential evolution (DE) method

Shenbo Xu, Bang Zheng, Bowen Su, Stan Finkelstein

In empirical studies with time-to-event outcomes, investigators often leverage observational data to conduct causal inference on the effect of exposure when randomized controlled trial data is unavailable. Model misspecification and lack of overlap are common issues in observational studies, and they often lead to inconsistent and inefficient estimators of t

Juan Gomez, Haily Martinez, Mrinal K. Roychowdhury, Alexis Salazar

The quantization scheme in probability theory deals with finding a best approximation of a given probability distribution by a probability distribution that is supported on finitely many points. In this paper, first we state and prove a theorem, and then give a conjecture. We verify the conjecture by a few examples. Assuming that the conjecture is true, for

Vladimir Igoshin, Mariia Tsimokha, Anastasia Nikitina, Mihail Petrov

Exceptional points (EPs) have been widely studied in quantum mechanics, condensed matter physics, optics and photonics. However, their potential in acoustics has only recently been recognized due to the rapid development of acoustic metamaterials. This paper proposes a method for achieving EP conditions in acoustic resonators by lowering their symmetry and e

Jaime Pizarroso, David Alfaya, José Portela, Antonio Muñoz

As Machine Learning models are considered for autonomous decisions with significant social impact, the need for understanding how these models work rises rapidly. Explainable Artificial Intelligence (XAI) aims to provide interpretations for predictions made by Machine Learning models, in order to make the model trustworthy and more transparent for the user.

K. Graham, J. O'Donnell, M. M. Silverstein, O. Eiger

We search for the presence of cool cores in optically-selected galaxy clusters from the Dark Energy Survey (DES) and investigate their prevalence as a function of redshift and cluster richness. Clusters were selected from the redMaPPer analysis of three years of DES observations that have archival Chandra X-ray observations, giving a sample of 99 clusters wi

Marius Lehmann, Min-Kai Lin

Protoplanetary discs (PPDs) can host a number of instabilities that may partake directly or indirectly in the process of planetesimal formation. These include the Vertical Shear Instability (VSI), Convective Overstability (COS), Streaming Instability (SI), and Dust Settling Instability (DSI), to name a few. Notably, the VSI and COS have mostly been studied i

Mengyun Shi, Claire Cardie, Serge Belongie

Consumers are exposed to advertisements across many different domains on the internet, such as fashion, beauty, car, food, and others. On the other hand, fashion represents second highest e-commerce shopping category. Does consumer digital record behavior on various fashion ad images reveal their fashion taste? Does ads from other domains infer their fashion

Irene Vanni, Stefania Salvadori, Ása Skúladóttir

Hydrodynamical cosmological simulations predict that the metal-free Population III (Pop III) stars were likely very massive and, therefore, short-lived. However, they left their chemical imprint on their descendants, which can also have masses $ < 0.8 \mathrm {M_{\odot}}$ and still be alive today. The Milky Way stellar halo is one of the oldest and most meta

Ren Zhang, Hui Zhai

In a quantum many-body system, autocorrelation functions can determine linear responses nearby equilibrium and quantum dynamics far from equilibrium. In this letter, we bring out the connection between the operator complexity and the autocorrelation function. In particular, we focus on a particular kind of operator complexity called the Krylov complexity. We

S. Andreon, C. Romero, H. Aussel, T. Bhandarkar

In this work we study the intracluster medium of a galaxy cluster at the cosmic noon: JKCS041 at z=1.803. A 28h long Sunyaev-Zel&#39;dovich (SZ) observation using MUSTANG-2 allows us to detect JKCS041, even if intrinsically extremely faint compared to other SZ-detected clusters. We found that the SZ peak is offset from the X-ray center by about 220 kpc in th

P. Aromal, R. Srianand, P. Petitjean

We study the time variability (over $\le$7.3 yrs) of ultra-fast outflows (UFOs) detected in a sample of 64 C IV broad absorption line (BAL) quasars (with 80 distinct BAL components) monitored using the Southern African Large Telescope. By comparing the properties of the quasar in our sample with those of a control sample of non-BAL quasars we show that the d

Adway Kumar Das, Anandamohan Ghosh, Ivan M. Khaymovich

Unlike the well-known Mott&#39;s argument that extended and localized states should not coexist at the same energy in a generic random potential, we provide an example of a nearest-neighbor tight-binding disordered model which carries both localized and extended states without forming the mobility edge (ME). Unexpectedly, this example appears to be given by

A. Saccardi, S. Salvadori, V. D&#39;Odorico, G. Cupani

The first stars were born from chemically pristine gas. They were likely massive, and thus they rapidly exploded as supernovae, enriching the surrounding gas with the first heavy elements. In the Local Group, the chemical signatures of the first stellar population were identified among low-mass, long-lived, very metal-poor ([Fe/H]<-2) stars, characterized by

Shiwu Zhang, Zheng Cai, Dandan Xu, Rhythm Shimakawa

Stars form in galaxies, from gas that has been accreted from the intergalactic medium. Simulations have shown that recycling of gas-the reaccretion of gas that was previously ejected from a galaxy-could sustain star formation in the early Universe. We observe the gas surrounding a massive galaxy at redshift 2.3 and detect emission lines from neutral hydrogen

Jinchao Zhao, Peizhi Mai, Barry Bradlyn, Philip Phillips

We show exactly that standard `invariants&#39; advocated to define topology for non-interacting systems deviate strongly from the Hall conductance whenever the excitation spectrum contains zeros of the single-particle Green function, $G$, as in general strongly correlated systems. Namely, we show that if the chemical potential sits atop the valence band, the

Emma Jane Weller, Fabio Pacucci, Priyamvada Natarajan, Tiziana Di Matteo

Recent dynamical measurements indicate the presence of a central SMBH with mass $\sim 3\times 10^6 \, \rm M_\odot$ in the dwarf galaxy Leo I, placing the system $\sim50$ times above the standard, local $M_{BH} - M_\star$ relation. While a few over-massive central SMBHs are reported in nearby isolated galaxies, this is the first detected in a Milky Way satell

Ian Banta, Tianji Cai, Nathaniel Craig, Zhengkang Zhang

We develop a diagrammatic approach to effective field theories (EFTs) corresponding to deep neural networks at initialization, which dramatically simplifies computations of finite-width corrections to neuron statistics. The structures of EFT calculations make it transparent that a single condition governs criticality of all connected correlators of neuron pr

L. Nemes

The apolar fullerenes C60 and C70 are not accessible for radio astronomy. Upon ionization static Jahn-Teller effects occur in C70+ that distort the D5h neutral symmetry to Cs. This point group is polar thus ionization induces a permanent electric dipole moment in C70. The goal of the present calculations is to compute the equilibrium geometry and dipole mome

Andrew Granville

We compare the values associated with (traditional) community based proof verification to those associated with computer proof verification. We propose ways that computer proofs might incorporate successful strategies from human experiences.

Zihao Zhang, Bradley Cantrell

This paper investigates the idea of cultivated wildness at the intersection of landscape design and artificial intelligence. The paper posits that contemporary landscape practices should overcome the potentially single understanding on wilderness, and instead explore landscape strategies to cultivate new forms of wild places via ideas and concerns in contemp

Zihao Zhang, Ben Bowes

There have been theory-based endeavours that directly engage with AI and ML in the landscape discipline. By presenting a case that uses machine learning techniques to predict variables in a coastal environment, this paper provides empirical evidence of the forthcoming cybernetic environment, in which designers are conceptualized not as authors but as choreog

Zihao Zhang

Taking on a historical lens, this paper traces the development of cybernetics and systems thinking back to the 1950s, when a group of interdisciplinary scholars converged to create a new theoretical model based on machines and systems for understanding matters of meaning, information, consciousness, and life. By presenting a genealogy of research in the land

Ufuk Asil, Efendi Nasibov

Culling newly hatched male chicks in industrial hatcheries poses a serious ethical problem. Both laying and broiler breeders need males, but it is a problem because they are produced more than needed. Being able to determine the sex of chicks in the egg at the beginning or early stage of incubation can eliminate ethical problems as well as many additional co

Arian Askari, Mohammad Aliannejadi, Evangelos Kanoulas, Suzan Verberne

We investigate the usefulness of generative Large Language Models (LLMs) in generating training data for cross-encoder re-rankers in a novel direction: generating synthetic documents instead of synthetic queries. We introduce a new dataset, ChatGPT-RetrievalQA, and compare the effectiveness of models fine-tuned on LLM-generated and human-generated data. Data

Vasil Kolev, Yavor Chapanov

The oscillations of climatic parameters of North Atlantic Ocean play important role in various events in North America and Europe. Several climatic indices are associated with these oscillations. The long term Atlantic temperature anomalies are described by the Atlantic Multidecadal Oscillation (AMO). The Atlantic Multidecadal Oscillation also known as Atlan

T. T. Hansen, J. D. Simon, T. S. Li, A. Frebel

Context: Carbon Enhanced Metal-Poor (CEMP) stars ($\mathrm{[C/Fe]} > 0.7$) are known to exist in large numbers at low metallicity in the Milky Way halo and are important tracers of early Galactic chemical evolution. However, very few such stars have been identified in the classical dwarf spheroidal (dSph) galaxies, and detailed abundances, including neutron-

E. Ponizovskaya Devine, Ahasan Ahamad, Ahmed Mayet, Amita Rawat

We study the nano- and micro-structures that increase the optical efficiency of the CMOS image pixels in visible and infrared. We consider the difference between the micro-holes at the pixels&#39; bottom and the top and the holes that are composed of smaller holes. Those solutions can facilitate the fabrication. We study the crosstalk and the optical efficie

Zijian Dong, Xu Chen, Jinlong Yang, Michael J. Black

While progress in 2D generative models of human appearance has been rapid, many applications require 3D avatars that can be animated and rendered. Unfortunately, most existing methods for learning generative models of 3D humans with diverse shape and appearance require 3D training data, which is limited and expensive to acquire. The key to progress is hence

Daniel Lobser, Joshua Goldberg, Andrew J. Landahl, Peter Maunz

One of the many challenges of developing an open user testbed such as QSCOUT is providing an interface that maintains simplicity without compromising expressibility or control. This interface comprises two distinct elements: a quantum assembly language designed for specifying quantum circuits at the gate level, and a low-level counterpart used for describing

Alex Trevithick, Matthew Chan, Michael Stengel, Eric R. Chan

We present a one-shot method to infer and render a photorealistic 3D representation from a single unposed image (e.g., face portrait) in real-time. Given a single RGB input, our image encoder directly predicts a canonical triplane representation of a neural radiance field for 3D-aware novel view synthesis via volume rendering. Our method is fast (24 fps) on

Tobias Barthel, Natalia Castellana, Drew Heard, Niko Naumann

We investigate to what extent we can descend the classification of localizing, smashing and thick ideals in a presentably symmetric monoidal stable $\infty$-category $\mathscr{C}$ along a descendable commutative algebra $A$. We establish equalizer diagrams relating the lattices of localizing and smashing ideals of $\mathscr{C}$ to those of $\mathrm{Mod}_{A}(

Mengyun Shi, Serge Belongie, Claire Cardie

Existing fashion datasets do not consider the multi-facts that cause a consumer to like or dislike a fashion image. Even two consumers like a same fashion image, they could like this image for total different reasons. In this paper, we study the reason why a consumer like a certain fashion image. Towards this goal, we introduce an interpretability dataset, F

Liran Ron-George, Ariel Yadin

We show that an infinite finitely generated group G is virtually-Z if and only if every Cayley graph of G contains only finitely many Busemann points in its horofunction boundary. This complements a previous result of the second named author and M. Tointon.

Ayşe Elçiboğa Kuday, Ferhat Özok, Erdinç Ulaş Saka

We present an analysis of fermionic dark matter (DM) in the context of 6 dimensional Effective Field Theory (EFT). We also compared the result generated via the 6-dimensional EFT analysis with the current experimental results for dark matter searches. These experiments are methodically categorised as direct and indirect search and present some constraints on

Hao Cheng, Meng Zhang, Weixuan Wang, Liangyou Li

Length-controllable machine translation is a type of constrained translation. It aims to contain the original meaning as much as possible while controlling the length of the translation. We can use automatic summarization or machine translation evaluation metrics for length-controllable machine translation, but this is not necessarily suitable and accurate.

Chuhan Zhang, Antoine Miech, Jiajun Shen, Jean-Baptiste Alayrac

Large-scale visual language models are widely used as pre-trained models and then adapted for various downstream tasks. While humans are known to efficiently learn new tasks from a few examples, deep learning models struggle with adaptation from few examples. In this work, we look into task adaptation in the low-data regime, and provide a thorough study of t

Nikita Karaev, Ignacio Rocco, Benjamin Graham, Natalia Neverova

We consider the problem of reconstructing a dynamic scene observed from a stereo camera. Most existing methods for depth from stereo treat different stereo frames independently, leading to temporally inconsistent depth predictions. Temporal consistency is especially important for immersive AR or VR scenarios, where flickering greatly diminishes the user expe

Soheila Hatami, Majid Sadedel, Farideh Jamali

The issue of Automatic License Plate Recognition (ALPR) has been one of the most challenging issues in recent years. Weather conditions, camera angle of view, lighting conditions, different characters written on license plates, and many other factors are among the challenges for the issue of ALPR. Given the advances that have been made in recent years in the

Ming Jiang, Jennifer D&#39;Souza, Sören Auer, J. Stephen Downie

The rapid growth of research publications has placed great demands on digital libraries (DL) for advanced information management technologies. To cater to these demands, techniques relying on knowledge-graph structures are being advocated. In such graph-based pipelines, inferring semantic relations between related scientific concepts is a crucial step. Recen

Henrique de Carvalho Videira

A major drawback in deploying central bank digital currencies (CDBC) is the offline puzzle, which requires that a CBDC must keep the provision given by cash, and, simultaneously, avoid double-spending, counterfeiting, and other issues. The puzzle is solved by minting the coins in serials, which are stored on a local blockchain (e.g. smartphone). The local bl

Per Salberger

This is a retyped version of an unpublished manuscript from 1993. It contains proofs of two conjectures of Colliot-Thélène, Sansuc and Swinnerton-Dyer on the arithmetic of intersections of two quadrics in the case where the variety contains a conic.

Zhe Xu, Tao Yan, Simon X. Yang, S. Andrew Gadsden

This paper investigated the distributed leader follower formation control problem for multiple differentially driven mobile robots. A distributed estimator is first introduced and it only requires the state information from each follower itself and its neighbors. Then, we propose a bioinspired neural dynamic based backstepping and sliding mode control hybrid

Shuo Kong, Héctor G. Arce, John J. Tobin, Yichen Zhang

We report high-resolution ALMA observations toward a massive protostellar core C1-Sa ($\sim$30 M$_\odot$) in the Dragon Infrared Dark Cloud. At the resolution of 140 AU, the core fragments into two kernels (C1-Sa1 and C1-Sa2) with a projected separation of $\sim$1400 AU along the elongation of C1-Sa, consistent with a Jeans length scale of $\sim$1100 AU. Rad

Trevor O. Foote, Thomas Barclay, Christina L. Hedges, Nikole K. Lewis

Pandora is an upcoming NASA SmallSat mission that will observe transiting exoplanets to study their atmospheres and the variability of their host stars. Efficient mission planning is critical for maximizing the science achieved with the year-long primary mission. To this end, we have developed a scheduler based on a metaheuristic algorithm that is focused on

Sharief Saleh, Qamar Bader, Malek Karaim, Mohamed Elhabiby

Achieving the highest levels of autonomy within autonomous vehicles (AVs) requires a precise and dependable positioning solution that is not influenced by the environment. 5G mmWave signals have been extensively studied in the literature to provide such a positioning solution. Yet, it is evident that 5G alone will not be able to provide uninterrupted positio

Christelle Saliby, Agnes Fienga, Arthur Briaud, Anthony Memin

The tidal deformations of a planet are often considered as markers of its inner structure. In this work, we use the tide excitations induced by the Sun on Venus for deciphering the nature of its internal layers. In using a Monte Carlo Random Exploration of the space of parameters describing the thickness, density and viscosity of 4 or 5 layer profiles, we we

Sripan Mondal, A. K. Srivastava, Sudheer K. Mishra, K. Sangal

Multiwavelength observations of the propagating disturbances (PDs), discovered by Atmospheric Imaging Assembly (AIA) onboard Solar Dynamics Observatory (SDO), are analyzed to determine its driving mechanism and physical nature. Two magnetic strands in the localised corona are observed to approach and merge with each other followed by the generation of bright

Markus Holzmann, Francesco Calcavecchia, David M. Ceperley, Valerio Olevano

We discuss the methodology of quantum Monte Carlo calculations of the effective mass based on the static self energy, $Σ(k,0)$. We then use variational Monte Carlo calculations of $Σ(k,0)$ of the homogeneous electron gas at various densities to obtain results very close to perturbative $G_0 W_0$ calculations for values of the density parameter $1 \le r_s \le

C. do Rei Filho, S. Canevari

We prove that a minimal hypersurfaces $f\colon M^{3} \to \mathbb{Q}^4(c)$ with nonzero three distinct principal curvature cannot be isometrically immersed in $\mathbb{Q}^4(\tilde{c}), \ \tilde{c}\neq c$. In the other cases, we present a description of such hypersurfaces.

Jinlong Xue, Yayue Deng, Fengping Wang, Ya Li

Conversational text-to-speech (TTS) aims to synthesize speech with proper prosody of reply based on the historical conversation. However, it is still a challenge to comprehensively model the conversation, and a majority of conversational TTS systems only focus on extracting global information and omit local prosody features, which contain important fine-grai

J. R. Eskilt, D. J. Watts, R. Aurlien, A. Basyrov

Cosmic birefringence is a parity-violating effect that might have rotated the plane of linearly polarized light of the cosmic microwave background (CMB) by an angle $β$ since its emission. This has recently been measured to be non-zero at a statistical significance of $3.6σ$ in the official Planck PR4 and 9-year WMAP data. In this work, we constrain $β$ usin

David Reixach

In this work we present Low-rank Deconvolution, a powerful framework for low-level feature-map learning for efficient signal representation with application to signal recovery. Its formulation in multi-linear algebra inherits properties from convolutional sparse coding and low-rank approximation methods as in this setting signals are decomposed in a set of f