July 2023 arXiv papers — page 102

Zikun Lin, Roberto Soria, Douglas A. Swartz

We present the results of our study of the luminous (L_{X} ~ 10^{39} erg/s) X-ray binary CXOU J121538.2+361921 in NGC 4214, the high mass X-ray binary with the shortest known orbital period. Using Chandra data, we confirm the ~13,000 s (3.6 hr) eclipse period, and an eclipse duration of ~2000 s. From this, we estimate a mass ratio M_2/M_1 >~ 3 and a stellar

Xiaoying Pang, Yifan Wang, Shih-Yun Tang, Yicheng Rui

Using membership of 85 open clusters from previous studies (Pang et al. 2021a,b, 2022b; Li et al. 2021) based on Gaia DR3 data, we identify binary candidates in the color-magnitude diagram, for systems with mass ratio q > 0.4. The binary fraction is corrected for incompleteness at different distances due to the Gaia angular resolution limit. We find a decrea

J. A. Aguilar-Saavedra

Top pairs produced at the Large Hadron Collider exhibit quantum entanglement of their spins near threshold and for boosted, central $t \bar t$ pairs. The entanglement is maintained between the decay products, in particular between the top quark and the $W^-$ boson from the anti-quark (or vice-versa, between $\bar t$ and $W^+$) in certain kinematical regions.

Mesut Çalışkan, Neha Anil Kumar, Lingyuan Ji, Jose M. Ezquiaga

The Laser Interferometer Space Antenna (LISA) will detect gravitational waves (GWs) emitted by massive black hole binaries (MBHBs) in the low-frequency ($\sim$mHz) band. Low-mass lenses, such as low-mass dark matter halos or subhalos, have sizes comparable to the wavelength of these GWs. Encounters with these lenses produce wave-optics (WO) effects that alte

Marios Galanis, Ken Van Tilburg, Masha Baryakhtar, Neal Weiner

We develop in detail a recently proposed optical-path modification of astronomical intensity interferometers. Extended-Path Intensity Correlation (EPIC) introduces a tunable path extension, enabling differential astrometry of multiple compact sources such as stars and quasars at separations of up to a few arcseconds. Combined with other recent technological

Paul A. Draghis, Jon M. Miller, McKinley C. Brumback, Andrew C. Fabian

The black hole candidate XTE J2012+381 underwent an outburst at the end of 2022. We analyzed 105 NICER observations and 2 NuSTAR observations of the source during the outburst. The NuSTAR observations of the $M \sim10M_\odot$ black hole indicate clear signs of relativistic disk reflection, which we modeled to measure a BH spin of $a=0.988^{+0.008}_{-0.030}$

Nataniel Ruiz, Yuanzhen Li, Varun Jampani, Wei Wei

Personalization has emerged as a prominent aspect within the field of generative AI, enabling the synthesis of individuals in diverse contexts and styles, while retaining high-fidelity to their identities. However, the process of personalization presents inherent challenges in terms of time and memory requirements. Fine-tuning each personalized model needs c

Muhammad Uzair Khattak, Syed Talal Wasim, Muzammal Naseer, Salman Khan

Prompt learning has emerged as an efficient alternative for fine-tuning foundational models, such as CLIP, for various downstream tasks. Conventionally trained using the task-specific objective, i.e., cross-entropy loss, prompts tend to overfit downstream data distributions and find it challenging to capture task-agnostic general features from the frozen CLI

Syed Talal Wasim, Muhammad Uzair Khattak, Muzammal Naseer, Salman Khan

Recent video recognition models utilize Transformer models for long-range spatio-temporal context modeling. Video transformer designs are based on self-attention that can model global context at a high computational cost. In comparison, convolutional designs for videos offer an efficient alternative but lack long-range dependency modeling. Towards achieving

David Roberts, Aashish A. Clerk

The dissipative variant of the Ising model in a transverse field is one of the most important models in the analysis of open quantum many-body systems, due to its paradigmatic character for understanding driven-dissipative quantum phase transitions, as well as its relevance in modelling diverse experimental platforms in atomic physics and quantum simulation.

Tao Ge, Jing Hu, Lei Wang, Xun Wang

We propose the In-context Autoencoder (ICAE), leveraging the power of a large language model (LLM) to compress a long context into short compact memory slots that can be directly conditioned on by the LLM for various purposes. ICAE is first pretrained using both autoencoding and language modeling objectives on massive text data, enabling it to generate memor

Rafael von Kanel, Arno Kret

We continue our study of integral points on moduli schemes by combining the method of Faltings (Arakelov, Parsin, Szpiro) with modularity results and Masser-W\"ustholz isogeny estimates. In this work we explicitly bound the height and the number of integral points on coarse Hilbert moduli schemes outside the branch locus. In the first part we define and stud

Yi Wang, Yinan He, Yizhuo Li, Kunchang Li

This paper introduces InternVid, a large-scale video-centric multimodal dataset that enables learning powerful and transferable video-text representations for multimodal understanding and generation. The InternVid dataset contains over 7 million videos lasting nearly 760K hours, yielding 234M video clips accompanied by detailed descriptions of total 4.1B wor

Emanuele Albini, Shubham Sharma, Saumitra Mishra, Danial Dervovic

Explainable Artificial Intelligence (XAI) has received widespread interest in recent years, and two of the most popular types of explanations are feature attributions, and counterfactual explanations. These classes of approaches have been largely studied independently and the few attempts at reconciling them have been primarily empirical. This work establish

Yingqing He, Menghan Xia, Haoxin Chen, Xiaodong Cun

Generating videos for visual storytelling can be a tedious and complex process that typically requires either live-action filming or graphics animation rendering. To bypass these challenges, our key idea is to utilize the abundance of existing video clips and synthesize a coherent storytelling video by customizing their appearances. We achieve this by develo

G. L. van de Stolpe, D. P. Kwiatkowski, C. E. Bradley, J. Randall

Spins associated to optically accessible solid-state defects have emerged as a versatile platform for exploring quantum simulation, quantum sensing and quantum communication. Pioneering experiments have shown the sensing, imaging, and control of multiple nuclear spins surrounding a single electron-spin defect. However, the accessible size of these spin netwo

João G. L. Condé, Pablo L. Saldanha

We discuss a fundamental question regarding the Abraham-Minkowski debate about the momentum of light in a medium: If an atom in a gas absorbs a photon, what is the momentum transferred to it? We consider a classical model for the internal degrees of freedom of the absorbing atom, computing the absorbed energy and momentum using the Lorentz force law due to t

Seongwook Shin, Yong Siah Teo, Hyunseok Jeong

Ascertaining whether a classical model can efficiently replace a given quantum model -- dequantization -- is crucial in assessing the true potential of quantum algorithms. In this work, we introduced the dequantizability of the function class of variational quantum-machine-learning~(VQML) models by employing the tensor network formalism, effectively identify

Aaron W. Young, Shawn Geller, William J. Eckner, Nathan Schine

A boson sampler implements a restricted model of quantum computing. It is defined by the ability to sample from the distribution resulting from the interference of identical bosons propagating according to programmable, non-interacting dynamics. Here, we demonstrate a new combination of tools for implementing boson sampling using ultracold atoms in a two-dim

Zhong-Bo Kang, Kyle Lee, Ding Yu Shao, Fanyi Zhao

We generalize the conventional Energy-Energy Correlator (EEC) to include the azimuthal angle dependence, so to define azimuthal angle dependent EEC observables. We study this new EEC observable in $e^+e^-$ and semi-inclusive deep inelastic scattering (SIDIS). In the back-to-back region, we find that the azimuthal angle dependent EEC is sensitive to both the

Soham Chanda, Amanda Hirschi, Luya Wang

Vianna constructed infinitely many exotic Lagrangian tori in the complex projective plane. We lift these tori to higher-dimensional projective spaces and show that they remain non-symplectomorphic. Our proof is elementary except for an application of the wall-crossing formula by Pascaleff-Tonkonog.

Samudra Dasgupta, Travis S. Humble

Noisy intermediate-scale quantum (NISQ) devices are valuable platforms for testing the tenets of quantum computing, but these devices are susceptible to errors arising from de-coherence, leakage, cross-talk and other sources of noise. This raises concerns regarding the stability of results when using NISQ devices since strategies for mitigating errors genera

Konstantinos Fysarakis, Alexios Lekidis, Vasileios Mavroeidis, Konstantinos Lampropoulos

As digital technologies become more pervasive in society and the economy, cybersecurity incidents become more frequent and impactful. According to the NIS and NIS2 Directives, EU Member States and their Operators of Essential Services must establish a minimum baseline set of cybersecurity capabilities and engage in cross-border coordination and cooperation.

Jacob Honeycutt, Vyron Vellis, Scott Zimmerman

We generalize a bi-Lipschitz extension result of David and Semmes from Euclidean spaces to complete metric measure spaces with controlled geometry (Ahlfors regularity and supporting a Poincar\'e inequality). In particular, we find sharp conditions on metric measure spaces $X$ so that any bi-Lipschitz embedding of a subset of the real line into $X$ extends to

Gregor Geigle, Abhay Jain, Radu Timofte, Goran Glavaš

Modular vision-language models (Vision-LLMs) align pretrained image encoders with (frozen) large language models (LLMs) and post-hoc condition LLMs to `understand' the image input. With the abundance of readily available high-quality English image-text data as well as strong monolingual English LLMs, the research focus has been on English-only Vision-LLMs. M

S. Mironov, M. Valencia-Villegas

Generic models in Galileons or Horndeski theory do not have cosmological solutions that are free of instabilities and singularities in the entire time of evolution. We extend this No-Go theorem to a spacetime with torsion. On this more general geometry the No-Go argument now holds provided the additional hypothesis that the graviton is also subluminal throug

Steven Ramsay, Charlie Walpole

We introduce two-sided type systems, which are sequent calculi for typing formulas. Two-sided type systems allow for hypothetical reasoning over the typing of compound program expressions, and the refutation of typing formulas. By incorporating a type of all values, these type systems support more refined notions of well-typing and ill-typing, guaranteeing b

Chockalingam Senthilnathan, Tal Cohen

There is significant interest in modelling the mechanics and physics of growth of soft biological systems such as tumors and bacterial biofilms. Solid tumors account for more than 85% of cancer mortality and bacterial biofilms account for a significant part of all human microbial infections.These growing biological systems are a mixture of fluid and solid co

Jean-Baptiste Fest, Audrey Repetti, Emilie Chouzenoux

Stochastic gradient optimization methods are broadly used to minimize non-convex smooth objective functions, for instance when training deep neural networks. However, theoretical guarantees on the asymptotic behaviour of these methods remain scarce. Especially, ensuring almost-sure convergence of the iterates to a stationary point is quite challenging. In th

Ashok Singh, Srimanta Pakhira

The development of high-activity and low-price cathodic catalysts to facilitate the electrochemical sluggish O$_2$ reduction reaction (ORR) is very important to achieve the commercial application of fuel cells. Here, we have investigated the electrocatalytic activity of two-dimensional single-layer Nb-doped zirconium diselenide (2D Nb-ZrSe$_2$) towards ORR b

Moab Arar, Rinon Gal, Yuval Atzmon, Gal Chechik

Text-to-image (T2I) personalization allows users to guide the creative image generation process by combining their own visual concepts in natural language prompts. Recently, encoder-based techniques have emerged as a new effective approach for T2I personalization, reducing the need for multiple images and long training times. However, most existing encoders

Shuijing Liu, Aamir Hasan, Kaiwen Hong, Runxuan Wang

Persons with visual impairments (PwVI) have difficulties understanding and navigating spaces around them. Current wayfinding technologies either focus solely on navigation or provide limited communication about the environment. Motivated by recent advances in visual-language grounding and semantic navigation, we propose DRAGON, a guiding robot powered by a d

Eva A. Gallardo-Gutierrez, Jonathan R. Partington, William T. Ross

This paper explores various classes of invariant subspaces of the classical Ces\`{a}ro operator $C$ on the Hardy space $H^2$. We provide a new characterization of the finite co-dimensional $C$-invariant subspaces, based on earlier work of the first two authors, and determine exactly which model spaces are $C$-invariant subspaces. We also describe the $C$-inv

Adam G. Emerson, Allison Sullivan

Alloy is a declarative modeling language that is well suited for verifying system designs. Alloy models are automatically analyzed using the Analyzer, a toolset that helps the user understand their system by displaying the consequences of their properties, helping identify any missing or incorrect properties, and exploring the impact of modifications to thos

Nils Lommen, Jürgen Giesl

We present a new procedure to infer size bounds for integer programs automatically. Size bounds are important for the deduction of bounds on the runtime complexity or in general, for the resource analysis of programs. We show that our technique is complete (i.e., it always computes finite size bounds) for a subclass of loops, possibly with non-linear arithme

Maxim Eingorn, Ezgi Yilmaz, A. Emrah Yükselci, Alexander Zhuk

One of the main objectives of modern cosmology is to explain the origin and evolution of cosmic structures at different scales. The principal force responsible for the formation of such structures is gravity. In a general relativistic framework, we have shown that matter density contrasts do not grow over time at scales exceeding the cosmic screening length,

Artur Philipp, Axel Küpper

Federated and decentralized networks supporting frequently changing system participants are a requirement for future Internet of Things (IoT) use cases. IoT devices and networks often lack adequate authentication and authorization mechanisms, resulting in insufficient privacy for entities in such systems. In this work we address both issues by designing a pr

S. Dalal, R. D. Haywood, A. Mortier, W. J. Chaplin

To detect Earth-mass planets using the Doppler method, a major obstacle is to differentiate the planetary signal from intrinsic stellar variability (e.g., pulsations, granulation, spots and plages). Convective blueshift, which results from small-scale convection at the surface of Sun-like stars, is relevant for Earth-twin detections as it exhibits Doppler no

Mahender Kumar

Elliptic curve cryptography (ECC) is a remarkable mathematical tool that offers the same level of security as traditional public-key cryptography (PKC) with a significantly smaller key size and lower computational requirements. The use of pairing on elliptic curves has emerged as a vibrant field of research that provides enhanced security measures for the ne

Everton S. Medeiros, Oleh Omel'chenko, Ulrike Feudel

Nonlinear systems possessing nonattracting chaotic sets, such as chaotic saddles, embedded in their state space may oscillate chaotically for a transient time before eventually transitioning into some stable attractor. We show that these systems, when networked with nonlocal coupling in a ring, are capable of forming chimera states, in which one subset of th

Lars-Peter Meyer, Claus Stadler, Johannes Frey, Norman Radtke

Knowledge Graphs (KG) provide us with a structured, flexible, transparent, cross-system, and collaborative way of organizing our knowledge and data across various domains in society and industrial as well as scientific disciplines. KGs surpass any other form of representation in terms of effectiveness. However, Knowledge Graph Engineering (KGE) requires in-d

William Good, Zhouyou Fan, Huey-Wen Lin

We present the key results from the first study of the $x$-dependent nucleon gluon distribution from lattice QCD extrapolated to the physical-continuum limit. We use ensembles with $2+1+1$ flavors of highly improved staggered quarks (HISQ) generated by the MILC Collaboration with clover fermions for the valence action on three different lattice spacings and

Ziyang Wei, Wanrong Zhu, Wei Biao Wu

Stochastic Gradient Descent (SGD) is one of the most popular algorithms in statistical and machine learning due to its computational and memory efficiency. Various averaging schemes have been proposed to accelerate the convergence of SGD in different settings. In this paper, we explore a general averaging scheme for SGD. Specifically, we establish the asympt

L. Siddharth, Jianxi Luo

Aiming to support Retrieval Augmented Generation (RAG) in the design process, we present a method to identify explicit, engineering design facts - {head entity :: relationship :: tail entity} from patented artefact descriptions. Given a sentence with a pair of entities (based on noun phrases) marked in a unique manner, our method extracts the relationship th

Mingyang Deng, Jonathan Tidor, Yufei Zhao

Ruzsa asked whether there exist Fourier-uniform subsets of $\mathbb Z/N\mathbb Z$ with density $\alpha$ and 4-term arithmetic progression (4-AP) density at most $\alpha^C$, for arbitrarily large $C$. Gowers constructed Fourier uniform sets with density $\alpha$ and 4-AP density at most $\alpha^{4+c}$ for some small constant $c>0$. We show that an affirmative

Mara Graziani, Laura O' Mahony, An-Phi Nguyen, Henning Müller

Interpreting the inner workings of deep learning models is crucial for establishing trust and ensuring model safety. Concept-based explanations have emerged as a superior approach that is more interpretable than feature attribution estimates such as pixel saliency. However, defining the concepts for the interpretability analysis biases the explanations by th

Ulrich Dah-Achinanon, Emir Khaled Belhaddad, Guillaume Ricard, Giovanni Beltrame

Swarm robotics is an emerging field of research which is increasingly attracting attention thanks to the advances in robotics and its potential applications. However, despite the enthusiasm surrounding this area of research, software development for swarm robotics is still a tedious task. That fact is partly due to the lack of dedicated solutions, in particu

Xiaosheng Zhao, Shifan Zuo, Yi Mao

The Square Kilometre Array (SKA) will have the sensitivity to take the 3D light-cones of the 21 cm signal from the epoch of reionization. This signal, however, is highly non-Gaussian and can not be fully interpreted by the traditional statistic using power spectrum. In this work, we introduce the 3D ScatterNet that combines the normalizing flows with solid h

Thais Lemos, Rodrigo S. Gonçalves, Joel C. Carvalho, Jailson S. Alcaniz

Fast Radio Bursts (FRBs) are millisecond transient radio events with a high energy. By identifying the origin of the \textbf{burst}, it is possible to measure the redshift of the host galaxy, which can be used to constrain cosmological and astrophysical parameters and test aspects of fundamental physics when combined with the dispersion measure ($DM$). Howev

Tom Benhamou, Jing Zhang

We demonstrate that the technology of Radin forcing can be used to transfer compactness properties at a weakly inaccessible but not strong limit cardinal to a strongly inaccessible cardinal. As an application, relative to the existence of large cardinals, we construct a model of set theory in which there is a cardinal $\kappa$ that is $n$-$d$-stationary for

Ervin Győri, Alan Li, Runtian Zhou

The planar Tur\'an number, $ex_\mathcal{P}(n,H)$, is the maximum number of edges in an $n$-vertex planar graph which does not contain $H$ as a subgraph. The topic of extremal planar graphs was initiated by Dowden (2016). He obtained sharp upper bound for both $ex_\mathcal{P}(n,C_4)$ and $ex_\mathcal{P}(n,C_5)$. Later on, D. Ghosh et al. obtained sharp upper

Dor Muhlgay, Ori Ram, Inbal Magar, Yoav Levine

Before deploying a language model (LM) within a given domain, it is important to measure its tendency to generate factually incorrect information in that domain. Existing methods for factuality evaluation of LLM generation focus on facts sampled from the LM itself, and thus do not control the set of evaluated facts and might under-represent domain specific o

Rafał Filipów, Krzysztof Kowitz, Adam Kwela

For many years, there have been conducting research (e.g. by Bergelson, Furstenberg, Kojman, Kubi\'{s}, Shelah, Szeptycki, Weiss) into sequentially compact spaces that are, in a sense, topological counterparts of some combinatorial theorems, for instance Ramsey's theorem for coloring graphs, Hindman's finite sums theorem and van der Waerden's arithmetical pr

Matthias Fischer, Carsten Proppe

With computational models becoming more expensive and complex, surrogate models have gained increasing attention in many scientific disciplines and are often necessary to conduct sensitivity studies, parameter optimization etc. In the scientific discipline of uncertainty quantification (UQ), model input quantities are often described by probability distribut

Ruben Queiros, Jose Ruela, Helder Fontes, Rui Campos

Despite the trend towards ubiquitous wireless connectivity, there are scenarios where the communications infrastructure is damaged and wireless coverage is insufficient or does not exist, such as in natural disasters and temporary crowded events. Flying networks, composed of Unmanned Aerial Vehicles (UAV), have emerged as a flexible and cost-effective soluti

Shubham Patel, Narayan Mohanta, Snehasish Nandy, Subhendra D. Mahanti

Employing a first-principles and model Hamiltonian approach, we work out the electronic properties of polar-polar LaVO$_3$/KTaO$_3$ (LVO/KTO, 001) heterostrctures, with up to six layers of KTO and five layers of LVO. Our analyses indicate the existence of multiple Lifshitz transitions (LTs) within the $t_{2g}$ bands, which can be fine-tuned by adjusting the

Fangyang Zhan, Zheng Qin, Dong-Hui Xu, Xiaoyuan Zhou

The existence of fractionally quantized topological corner states serves as a key indicator for two-dimensional second-order topological insulators (SOTIs), yet has not been experimentally observed in realistic materials. Here, based on effective model analysis and symmetry arguments, we propose a strategy for achieving SOTI phases with in-gap corner states

Florent Ferro, Filiberto Ares, Pasquale Calabrese

The entanglement asymmetry is a novel quantity that, using entanglement methods, measures how much a symmetry is broken in a part of an extended quantum system. So far it has only been used to characterise the breaking of continuous Abelian symmetries. In this paper, we extend the concept to cyclic $\mathbb{Z}_N$ groups. As an application, we consider the XY

Monika Mothsara, Leela Ganesh Chandra Lakkaraju, Srijon Ghosh, Aditi Sen De

The typical bound on parameter estimation, known as the standard quantum limit (SQL), can be surpassed by exploiting quantum resources such as entanglement. To estimate the magnetic probe field, we propose a quantum sensor based on a variable-range many-body quantum spin chain with a moderate transverse magnetic field. We report the threefold benefits of emp

Martin Spiecker, Andrei I. Pavlov, Alexander Shnirman, Ioan M. Pop

We measure and model the combined relaxation of a qubit coupled to a discrete two-level system~(TLS) environment, also known as the central spin model. If the TLSs are much longer-lived than the qubit, non-exponential relaxation and non-Poissonian quantum jumps can be observed. In the limit of large numbers of TLSs, the relaxation is likely to follow a power

Zachary W. Riedel, Zhihao Jiang, Maxim Avdeev, André Schleife

Exploring the uncharacterized magnetic phases of Co$^{2+}$ chain compounds is critical for finding new low-dimensional magnets hosting quantized excitations. We map the unexplored magnetic phases of the Co$^{2+}$ chain compound Li$_2$CoCl$_4$. Magnetometry reveals magnetic ordering below 7 K with a metamagnetic transition near 16.5 kOe and a gradual transiti

Marcus Krellner, The Anh Han

To achieve common goals, we often use joint commitments. Our commitment helps us to coordinate with our partners and assures them that their cooperative efforts will benefit themselves. However, if one of us can exploit the other's cooperation (as in the Prisoner's Dilemma), our commitment appears less useful. It cannot remove the temptation for our partners

Maurice Dekker, Johannes Kloibhofer, Johannes Marti, Yde Venema

Automata operating on infinite objects feature prominently in the theory of the modal $\mu$-calculus. One such application concerns the tableau games introduced by Niwi\'{n}ski & Walukiewicz, of which the winning condition for infinite plays can be naturally checked by a nondeterministic parity stream automaton. Inspired by work of Jungteerapanich and Stirli

Stephen Serjeant

The European Open Science Cloud aims to make all data Findable, Accessible, Interoperable and Reusable. By far the largest community of users of the European Open Science Cloud is the science-inclined public. These users need a more curated experience of open science than subject specialists, but nevertheless make very substantial research contributions in o

Zheng Sun, Ting Li, Hui Tian, Yinjun Hou

Partial filament eruptions have often been observed, however, the physical mechanisms that lead to filament splitting are not yet fully understood. In this study, we present a unique event of a partial filament eruption that undergoes two distinct splitting processes. The first process involves vertical splitting and is accompanied by brightenings inside the

Daoce Wang, Jesus Pulido, Pascal Grosset, Jiannan Tian

As supercomputers advance towards exascale capabilities, computational intensity increases significantly, and the volume of data requiring storage and transmission experiences exponential growth. Adaptive Mesh Refinement (AMR) has emerged as an effective solution to address these two challenges. Concurrently, error-bounded lossy compression is recognized as

Mohammad A. Alhejji, Emanuel Knill

Consider minimizing the entropy of a mixture of states by choosing each state subject to constraints. If the spectrum of each state is fixed, we expect that in order to reduce the entropy of the mixture, we should make the states less distinguishable in some sense. Here, we study a class of optimization problems that are inspired by this situation and shed l

Kelen C. T. Vivaldini, Jorge P. M. Galdames, Thales B. Pasqual, Rafael M. Sobral

Automation of logistic processes is essential to improve productivity and reduce costs. In this context, intelligent warehouses are becoming a key to logistic systems thanks to their ability of optimizing transportation tasks and, consequently, reducing costs. This paper initially presents briefly routing systems applied on intelligent warehouses. Then, we p

Sayantan Ghosh, Shahebaj Shaikh, Probit J Kalita, Pinku Routaray

Neutron stars (NSs) have traditionally been viewed as cold, zero-temperature entities. However, recent progress in computational methods and theoretical modelling has opened up the exploration of finite temperature effects, marking a novel research frontier. This study examines Proto-Neutron Stars (PNSs) using the BigApple parameter set to investigate their

Victor Nikolaevich Mitryakhin, Alexander Steinhoff, Jens-Christian Drawer, Hangyong Shan

Emitter dephasing is one of the key issues in the performance of solid-state single photon sources. Among the various sources of dephasing, acoustic phonons play a central role in adding decoherence to the single photon emission. Here, we demonstrate, that it is possible to tune and engineer the coherence of photons emitted from a single WSe$_2$ monolayer qu

Christian Bender, Steffen Meyer

We introduce and analyze a family of linear least-squares Monte Carlo schemes for backward SDEs, which interpolate between the one-step dynamic programming scheme of Lemor, Warin, and Gobet (Bernoulli, 2006) and the multi-step dynamic programming scheme of Gobet and Turkedjiev (Mathematics of Computation, 2016). Our algorithm approximates conditional expecta

Shiju Li, Xin Huang, Chul-Ho Lee, Do Young Eun

In this paper, we study the problem of minimizing the spread of a viral epidemic when immunization takes a non-negligible amount of time to take into effect. Specifically, our problem is to determine which set of nodes to be vaccinated when vaccines take a random amount of time in order to maximize the total reward, which is the expected number of saved node

A. Sud, K. Yamamoto, K. Z. Suzuki, S. Mizukami

Magnetic multilayers with interlayer exchange coupling have been widely studied for both static and dynamic regimes. Their dynamical responses depend on the exchange coupling strength and magnetic properties of individual layers. Magnetic resonance spectra in such systems are conveniently discussed in terms of coupling of acoustic and optical modes. At a cer

Liam Collins, Hamed Hassani, Mahdi Soltanolkotabi, Aryan Mokhtari

An increasingly popular machine learning paradigm is to pretrain a neural network (NN) on many tasks offline, then adapt it to downstream tasks, often by re-training only the last linear layer of the network. This approach yields strong downstream performance in a variety of contexts, demonstrating that multitask pretraining leads to effective feature learni

Arman Adibi, Aritra Mitra, Hamed Hassani

Delays and asynchrony are inevitable in large-scale machine-learning problems where communication plays a key role. As such, several works have extensively analyzed stochastic optimization with delayed gradients. However, as far as we are aware, no analogous theory is available for min-max optimization, a topic that has gained recent popularity due to applic

Giovanni Bellettini, Riccardo Scala, Giuseppe Scianna

Given a bounded open connected Lipschitz set $\Omega \subset \mathbb R^2$, we show that the relaxed Cartesian area functional $\overline{\mathcal A}(u,\Omega)$ of a map $u\in W^{1,1}(\Omega;\mathbb S^1)$ is finite, and provide a useful upper bound for its value. Using this estimate, we prove a modified version of a De Giorgi conjecture [17] adapted to $W^{1,

Feras A. Saad, Brian J. Patton, Matthew D. Hoffman, Rif A. Saurous

This paper presents a new approach to automatically discovering accurate models of complex time series data. Working within a Bayesian nonparametric prior over a symbolic space of Gaussian process time series models, we present a novel structure learning algorithm that integrates sequential Monte Carlo (SMC) and involutive MCMC for highly effective posterior

Luis F. Alday, Vasco Gonçalves, Maria Nocchi, Xinan Zhou

We present a powerful new approach to compute tree-level higher-point holographic correlators. Our method only exploits the flat-space limit, where we point out a novel and important simplification, and factorization of amplitudes in AdS. In particular, it makes minimal use of supersymmetry, crucial in all previous bootstrap methods. We demonstrate our metho

Chuyu Zhong, Kun Liao, Tianxiang Dai, Maoliang Wei

Optical neural networks (ONNs) herald a new era in information and communication technologies and have implemented various intelligent applications. In an ONN, the activation function (AF) is a crucial component determining the network performances and on-chip AF devices are still in development. Here, we first demonstrate on-chip reconfigurable AF devices w

Rafał Filipów, Krzysztof Kowitz, Adam Kwela

A family I of subsets of a set X is an ideal on X if it is closed under taking subsets and finite unions of its elements. An ideal I on X is below an ideal J on Y in the Katetov order if there is a function $f:Y\to X$ such that $f^{-1}[A]\in J$ for every $A\in I$. We show that the Hindman ideal, the Ramsey ideal and the summable ideal are pairwise incomparab

Edyvalberty Alenquer Cordeiro, Anselmo Ramalho Pitombeira-Neto

The dynamic vehicle dispatching problem corresponds to deciding which vehicles to assign to requests that arise stochastically over time and space. It emerges in diverse areas, such as in the assignment of trucks to loads to be transported; in emergency systems; and in ride-hailing services. In this paper, we model the problem as a semi-Markov decision proce

Megan Delamer, Shubham Kanodia, Caleb I. Cañas, Simon Müller

We confirm TOI-4201 b as a transiting Jovian mass planet orbiting an early M dwarf discovered by the Transiting Exoplanet Survey Satellite. Using ground based photometry and precise radial velocities from NEID and the Planet Finder Spectrograph, we measure a planet mass of 2.59$^{+0.07}_{-0.06}$ M$_{J}$, making this one of the most massive planets transiting

Joshua F. Belot, Valentin Taufour, Stefano Sanvito, Gus L. W. Hart

Technologies that function at room temperature often require magnets with a high Curie temperature, $T_\mathrm{C}$, and can be improved with better materials. Discovering magnetic materials with a substantial $T_\mathrm{C}$ is challenging because of the large number of candidates and the cost of fabricating and testing them. Using the two largest known data

Filippo Camilloni, Troels Harmark, Marta Orselli, Maria J. Rodriguez

General relativity (GR) will be imminently challenged by upcoming experiments in the strong gravity regime, including those testing the energy extraction mechanisms for black holes. Motivated by this, we explore magnetospheric models and black hole jet emissions in MOdified Gravity (MOG) scenarios. Specifically, we construct new power emitting magnetospheres

Christos Papadimitriou, Binghui Peng

The problem of continual learning in the domain of reinforcement learning, often called non-stationary reinforcement learning, has been identified as an important challenge to the application of reinforcement learning. We prove a worst-case complexity result, which we believe captures this challenge: Modifying the probabilities or the reward of a single stat

Xiaosheng Zhao, Yuan-Sen Ting, Kangning Diao, Yi Mao

Generative adversarial networks (GANs) are frequently utilized in astronomy to construct an emulator of numerical simulations. Nevertheless, training GANs can prove to be a precarious task, as they are prone to instability and often lead to mode collapse problems. Conversely, the diffusion model also has the ability to generate high-quality data without adve

Sakthi Priya Amirtharaj, Zhiyuan Xie, Josephine Si Yu See, Gabriele Rolleri

Electrically connected and plasmonically enhanced molecular junctions combine the optical functionalities of high field confinement and enhancement (cavity function), and of high radiative efficiency (antenna function) with the electrical functionalities of molecular transport. Such combined optical and electrical probes have proven useful for the fundamenta

H. M. Maridi, N. Keeley, K. Rusek

Simultaneous analyses are performed for cross section data of elastic scattering, fusion, Coulomb breakup, and other direct yields for the $^{6}$He+$^{209}$Bi system at near-Coulomb-barrier energies. The bare and dynamical polarization potentials are constructed microscopically from the structure of the colliding nuclei and they reproduce all the data well w

Ginny Ray Clevenger, Haley Havard, Patch Heard, Andrew Lott

For $A\subseteq \mathbb{R}$, let $A+A=\{a+b: a,b\in A\}$ and $AA=\{ab: a,b\in A\}$. For $k\in \mathbb{N}$, let $SP(k)$ denote the minimum value of $\max\{|A+A|, |AA|\}$ over all $A\subseteq \mathbb{N}$ with $|A|=k$. Here we establish $SP(k)=3k-3$ for $2\leq k \leq 7$, the $k=7$ case achieved for example by $\{1,2,3,4,6,8,12\}$, while $SP(k)=3k-2$ for $k=8,9$

Lijun Ding, Alex L. Wang

We study a sample complexity vs. conditioning tradeoff in modern signal recovery problems (including sparse recovery, low-rank matrix sensing, covariance estimation, and abstract phase retrieval), where convex optimization problems are built from sampled observations. We begin by introducing a set of condition numbers related to sharpness in $\ell_p$ or Scha

Rédoane Daoudi

Overcoming chemoresistance is a challenge for multiple chemotherapeutics agents like cisplatin. ABC transporters such as MDR1 or MRPs and PI3K/AKT pathway have been proposed as actors of chemoresistance in several cancers. In this review we describe two downstream targets of Akt: c-myc and p53 in the chemoresistance. We suggest a potential link between p53,

Lion Steger, Liming Kuang, Johannes Zirngibl, Georg Carle

Internet measurements are a crucial foundation of IPv6-related research. Due to the infeasibility of full address space scans for IPv6 however, those measurements rely on collections of reliably responsive, unbiased addresses, as provided e.g., by the IPv6 Hitlist service. Although used for various use cases, the hitlist provides an unfiltered list of respon

Eufrásio de A. Lima Neto, Jonathan Bailiss, Axel Finke, Jo Miller

Local authorities in England, such as Leicestershire County Council (LCC), provide Early Help services that can be offered at any point in a young person's life when they experience difficulties that cannot be supported by universal services alone, such as schools. This paper investigates the utilisation of machine learning (ML) to assist experts in identify

Jorge Mendez-Mendez, Leslie Pack Kaelbling, Tomás Lozano-Pérez

A robot deployed in a home over long stretches of time faces a true lifelong learning problem. As it seeks to provide assistance to its users, the robot should leverage any accumulated experience to improve its own knowledge and proficiency. We formalize this setting with a novel formulation of lifelong learning for task and motion planning (TAMP), which end

Pei Ke, Fei Huang, Fei Mi, Yasheng Wang

Existing evaluation metrics for natural language generation (NLG) tasks face the challenges on generalization ability and interpretability. Specifically, most of the well-performed metrics are required to train on evaluation datasets of specific NLG tasks and evaluation dimensions, which may cause over-fitting to task-specific datasets. Furthermore, existing

A. I. Stefanescu, V. Panin, L. Trache, T. Motobayashi

This work describes a silicon tracker system developed for experiments with proton-rich radioactive ion beams at the SAMURAI superconducting spectrometer of RIBF at RIKEN. The system is designed for accurate angular reconstruction and atomic number identification of relativistic heavy ions and protons which are simultaneously produced in reactions motivated

Yiming Zhang, Nicholas Carlini, Daphne Ippolito

The text generated by large language models is commonly controlled by prompting, where a prompt prepended to a user's query guides the model's output. The prompts used by companies to guide their models are often treated as secrets, to be hidden from the user making the query. They have even been treated as commodities to be bought and sold on marketplaces.

Michael W. Topping, Daniel P. Stark, Ryan Endsley, Lily Whitler

The power-law slope of the rest-UV continuum ($f_{\lambda}\propto\lambda^{\beta}$) is a key metric of early star forming galaxies, providing one of our only windows into the stellar populations and physical conditions of $z>10$ galaxies. Expanding upon previous studies with limited sample sizes, we leverage deep imaging from JADES to investigate the UV slope

Yichen Liu, Xiaomin Liu, Yihao Zhang, Meng Cai

To enable intelligent and self-driving optical networks, high-accuracy physical layer models are required. The dynamic wavelength-dependent gain effects of non-constant-pump erbium-doped fiber amplifiers (EDFAs) remain a crucial problem in terms of modeling, as it determines optical-to-signal noise ratio as well as the magnitude of fiber nonlinearities. Blac

R. Abileah, J. Gomez-Enri, A. Scozzari, S. Vignudelli

ESA's Envisat mission carried a RA-2 radar altimeter since its launch in 2002 to sense sea state and especially measure sea surface height (SSH). The onboard processing combined multiple echoes incoherently to reduce Speckle noise and benefit from data compression. In fact, according to past literature the amplitudes were generally expected to be independent