April 2024 arXiv papers — page 48

Mikkel Odgaard, Kiril Vadimovic Klein, Sanne Møller Thysen, Espen Jimenez-Solem

The widespread adoption of Electronic Health Records (EHR) has significantly increased the amount of available healthcare data. This has allowed models inspired by Natural Language Processing (NLP) and Computer Vision, which scale exceptionally well, to be used in EHR research. Particularly, BERT-based models have surged in popularity following the release o

John B. Little

In this note, we show how certain everywhere-regular real rational function solutions of the KP1 equation ("multi-lumps") can be constructed via the polynomial analogs of theta functions from singular rational curves with cusps. We use two methods, one direct and the other producing a degeneration of the well-understood soliton solutions from nodal singular

Haozhe Tian, Homayoun Hamedmoghadam, Robert Shorten, Pietro Ferraro

Reinforcement Learning (RL) is a powerful method for controlling dynamic systems, but its learning mechanism can lead to unpredictable actions that undermine the safety of critical systems. Here, we propose RL with Adaptive Regularization (RL-AR), an algorithm that enables safe RL exploration by combining the RL policy with a policy regularizer that hard-cod

Yurii Paniv, Dmytro Chaplynskyi, Nikita Trynus, Volodymyr Kyrylov

To build large language models for Ukrainian we need to expand our corpora with large amounts of new algorithmic tasks expressed in natural language. Examples of task performance expressed in English are abundant, so with a high-quality translation system our community will be enabled to curate datasets faster. To aid this goal, we introduce a recipe to buil

Joseph R. Masiero, Yuna G. Kwon, Dar W. Dahlen, Frank J. Masci

Asteroids with low orbital perihelion distances experience extreme heating from the Sun that can modify their surfaces and trigger non-typical activity mechanisms. These objects are generally difficult to observe from ground-based telescopes due to their frequent proximity to the Sun. The Near Earth Object Surveyor mission, however, will regularly survey dow

Michal Nazarczuk, Jan Kristof Behrens, Karla Stepanova, Matej Hoffmann

Embodied reasoning systems integrate robotic hardware and cognitive processes to perform complex tasks, typically in response to a natural language query about a specific physical environment. This usually involves changing the belief about the scene or physically interacting and changing the scene (e.g. sort the objects from lightest to heaviest). In order

S. Myroshnychenko, K. Tatarko, V. Yaskin

We construct a convex body $K$ in $\mathbb{R}^n$, $n \geq 5$, with the property that there is exactly one hyperplane $H$ passing through $c(K)$, the centroid of $K$, such that the centroid of $K\cap H$ coincides with $c(K)$. This provides answers to questions of Gr\"unbaum and Loewner for $n\geq 5$. The proof is based on the existence of non-intersection bod

Richard F. Lebed, Steven R. Martinez

Using the diabatic formalism, which generalizes the adiabatic approximation in the Born-Oppenheimer formalism, we apply well-known Hamiltonian methods to calculate the effect of open di-meson thresholds that lie well below the mass of elementary $c\bar c q\bar q^\prime$, $c\bar c s\bar s$, and $c \bar c q \bar s$ tetraquark bound states. We compute the resul

Jeevan Chandra, Thomas Hartman, Viraj Meruliya

Black holes and wormholes in the gravitational path integral can be used to calculate the statistics of heavy operators. An explicit example in higher dimensions is provided by thin shells of matter. We study these solutions in 3D gravity, and reproduce the behavior of black holes and wormholes from the dual CFT using the large-$c$ conformal bootstrap. The C

Josefina Catoni, Domonkos Martos, Ferenc Csikor, Enzo Ferrante

Optimal computations under uncertainty require an adequate probabilistic representation about beliefs. Deep generative models, and specifically Variational Autoencoders (VAEs), have the potential to meet this demand by building latent representations that learn to associate uncertainties with inferences while avoiding their characteristic intractable computa

Sergio Y. Hayashi, Nina S. T. Hirata

Deep neural networks are largely used for complex prediction tasks. There is plenty of empirical evidence of their successful end-to-end training for a diversity of tasks. Success is often measured based solely on the final performance of the trained network, and explanations on when, why and how they work are less emphasized. In this paper we study encoder-

Shu-Min Wu, Xiao-Wei Teng, Jin-Xuan Li, Hao-Sheng Zeng

In this paper, we use the concepts of quantum entanglement and coherence to analyze the Unruh and anti-Unruh effects based on the model of Unruh-DeWitt detector. For the first time, we find that (i) the Unruh effect reduces quantum entanglement but enhances quantum coherence; (ii) the anti-Unruh effect enhances quantum entanglement but reduces quantum cohere

Lisa Randolph, Mohammadreza Banjafar, Toshinori Yabuuchi, Carsten Baehtz

Femtosecond high-intensity laser pulses at intensities surpassing $10^{14} \,\text{W}/\text{cm}^2$ can generate a diverse range of functional surface nanostructures. Achieving precise control over the production of these functional structures necessitates a thorough understanding of the surface morphology dynamics with nanometer-scale spatial resolution and

Carla E. Brodley, McKenna Quam, Mark A. Weiss

For at least 40 years, there has been debate and disagreement as to the role of mathematics in the computer science curriculum. This paper presents the results of an analysis of the math requirements of 199 Computer Science BS/BA degrees from 158 U.S. universities, looking not only at which math courses are required, but how they are used as prerequisites (a

David Doukhan, Simon Devauchelle, Lucile Girard-Monneron, Mía Chávez Ruz

This paper presents a software allowing to describe voices using a continuous Voice Femininity Percentage (VFP). This system is intended for transgender speakers during their voice transition and for voice therapists supporting them in this process. A corpus of 41 French cis- and transgender speakers was recorded. A perceptual evaluation allowed 57 participa

Salvador A. Ochoa-Oregon, David F. Rentería-Estrada, Roger J. Hernández-Pinto, German F. R. Sborlini

Parton distribution functions play a pivotal role in hadron collider phenomenology. They are non-perturbative quantities extracted from fits to available data, and their scale dependence is dictated by the DGLAP evolution equations. In this article, we discuss machine-assisted strategies to efficiently compute PDFs directly incorporating the scale evolution

Yu-Jie Liang, Zihan Cao, Liang-Jian Deng, Xiao Wu

Recently, implicit neural representations (INR) have made significant strides in various vision-related domains, providing a novel solution for Multispectral and Hyperspectral Image Fusion (MHIF) tasks. However, INR is prone to losing high-frequency information and is confined to the lack of global perceptual capabilities. To address these issues, this paper

Ze Wang

Human brain is a massive information generation and processing machine. Studying the information flow may provide unique insight into brain function and brain diseases. We present here a tool for mapping the regional information flow in the entire brain using fMRI. Using the tool, we can estimate the information flow from a single region to the rest of the b

Anne Dattilo, Natalie M. Batalha

The Kepler mission enabled us to look at the intrinsic population of exoplanets within our galaxy. In period-radius space, the distribution of the intrinsic population of planets contains structure that can trace planet formation and evolution history. The most distinctive feature in period-radius space is the radius cliff, a steep drop-off in occurrence bet

C. Baheeja, S. Sahayanathan, F. M. Rieger, C. D. Ravikumar

The curvature in blazar spectrum has the potential to understand the particle dynamics in jets. We performed a detailed analysis of simultaneous Swift-XRT (0.3-10 keV) and NuSTAR (3-79 keV)} observations of Mkn 421. Our analysis of NuSTAR observations alone reveals that, during periods of low flux, the hard X-ray spectra are best represented by a steep power

Divyanshu Pandey, Alexis Decurninge, Harry Leib

This work considers the notion of random tensors and reviews some fundamental concepts in statistics when applied to a tensor based data or signal. In several engineering fields such as Communications, Signal Processing, Machine learning, and Control systems, the concepts of linear algebra combined with random variables have been indispensable tools. With th

E. R. Filimoshina, D. S. Shirokov

This paper investigates centralizers and twisted centralizers in degenerate and non-degenerate Clifford (geometric) algebras. We provide an explicit form of the centralizers and twisted centralizers of the subspaces of fixed grades, subspaces determined by the grade involution and the reversion, and their direct sums. The results can be useful for applicatio

Sooyeong Kim, Neal Madras

Let $G$ be a graph on $n$ vertices, with complement $\overline{G}$. The spectral gap of the transition probability matrix of a random walk on $G$ is used to estimate how fast the random walk becomes stationary. We prove that the larger spectral gap of $G$ and $\overline{G}$ is $\Omega(1/n)$. Moreover, if all degrees are $\Omega(n)$ and $n-\Omega(n)$, then th

M. Yassine Naghmouchi, Joseph Vovrosh, Wesley da Silva Coelho, Alexandre Dauphin

This paper introduces weighted-BMP, a variant of the Bandwidth Minimization Problem (BMP), with a significant application in optimizing quantum emulation. Weighted-BMP optimizes particles ordering to reduce the emulation costs, by designing a particle interaction matrix where strong interactions are placed as close as possible to the diagonal. We formulate t

Eneko Aranguren, Raül Vera

The tidal problem is used to obtain the tidal deformability (or Love number) of stars. The semi-analytical study is usually treated in perturbation theory as a first order perturbation problem over a spherically symmetric background configuration consisting of a stellar interior region matched across a boundary to a vacuum exterior region that models the tid

Tianwei Zhou, Songbai Tan, Wei Zhou, Yu Luo

With the increasing maturity of the text-to-image and image-to-image generative models, AI-generated images (AGIs) have shown great application potential in advertisement, entertainment, education, social media, etc. Although remarkable advancements have been achieved in generative models, very few efforts have been paid to design relevant quality assessment

Merey Ramazanova, Alejandro Pardo, Bernard Ghanem, Motasem Alfarra

Understanding videos that contain multiple modalities is crucial, especially in egocentric videos, where combining various sensory inputs significantly improves tasks like action recognition and moment localization. However, real-world applications often face challenges with incomplete modalities due to privacy concerns, efficiency needs, or hardware issues.

Xiaoyu Cheng, Yonggyun Kim

We study the monotonicity of information costs: more informative experiments must be more costly. As criteria for informativeness, we consider the standard information orders introduced by Blackwell (1951, 1953) and Lehmann (1988). We provide simple necessary and sufficient conditions for a cost function to be monotone with respect to each order, grounded in

Shashank Sonkar, Naiming Liu, Richard G. Baraniuk

The pursuit of personalized education has led to the integration of Large Language Models (LLMs) in developing intelligent tutoring systems. To better understand and adapt to individual student needs, including their misconceptions, LLMs need to be trained on extensive datasets of student-tutor dialogues. Our research uncovers a fundamental challenge in this

Allen Weitsman

We prove that univalent harmonic mappings can be approximated by univalent Fourier series of step functions.

Y. Ivette Colón, Matthew Rouse, Matthew A. Lambon Ralph, Timothy T. Rogers

Our interaction with others largely hinges on how we semantically organize the social world. The organization of such conceptual information is not static -- as we age, our experiences and ever-changing anatomy alter how we represent and arrange semantic information. How does semantic distance between concepts affect this organization, particularly for those

Katerina Batziakoudi, Florent Cabric, Stéphanie Rey, Jean-Daniel Fekete

We explore the design of visualizations for values spanning multiple orders of magnitude; we call them Orders of Magnitude Values (OMVs). Visualization researchers have shown that separating OMVs into two components, the mantissa and the exponent, and encoding them separately overcomes limitations of linear and logarithmic scales. However, only a small numbe

Raphael Poulain, Hamed Fayyaz, Rahmatollah Beheshti

Large Language Models (LLMs) have emerged as powerful candidates to inform clinical decision-making processes. While these models play an increasingly prominent role in shaping the digital landscape, two growing concerns emerge in healthcare applications: 1) to what extent do LLMs exhibit social bias based on patients' protected attributes (like race), and 2

Ana Climent, Roberto Emparan, Robie A. Hennigar

We study systems in $2+1$ dimensions consisting of defects that source an electric charge, or a magnetic flux, of a $U(1)$ field, and we use holography to compute their effects on quantum conformal fields. We can also hide the defects inside the horizon of a black hole, where they continue to affect the quantum fields outside. By extending the solutions to b

Wei Lin, Weicheng Fu, Zhen Wang, Yong Zhang

In this letter, a multi-wave quasi-resonance framework is established to analyze energy diffusion in classical lattices, uncovering that it is fundamentally determined by the characteristics of eigenmodes. Namely, based on the presence and the absence of extended modes, lattices fall into two universality classes with qualitatively different thermalization b

Avi Schwarzschild, Zhili Feng, Pratyush Maini, Zachary C. Lipton

Large language models (LLMs) trained on web-scale datasets raise substantial concerns regarding permissible data usage. One major question is whether these models "memorize" all their training data or they integrate many data sources in some way more akin to how a human would learn and synthesize information. The answer hinges, to a large degree, on how we d

Hao Yu

Let $X=GD$ be a group, where $G$ is a nonabelian simple group and $D$ is a dihedral group. These groups $X$ are closely related to regular Cayley maps. The main theorems of this paper describes $X$.

Jeanne Bourgeois, Gianmichele Blasi, Shishir Khandelwal, Géraldine Haack

Entanglement engines are autonomous quantum thermal machines designed to generate entanglement from the presence of a particle current flowing through the device. In this work, we investigate the functioning of a two-qubit entanglement engine beyond the steady-state regime. Within a master equation approach, we derive the time-dependent state, the particle c

Seth Layton, Thiago De Andrade, Daniel Olszewski, Kevin Warren

Deepfake speech represents a real and growing threat to systems and society. Many detectors have been created to aid in defense against speech deepfakes. While these detectors implement myriad methodologies, many rely on low-level fragments of the speech generation process. We hypothesize that breath, a higher-level part of speech, is a key component of natu

Tommy Murphy, David Weed

We characterize the Archimedean solids among the convex uniform polyhedra via face embeddings into a regular Tetrahedron. This result has been listed without proof in the literature.

Mingbao Lin, Zhihang Lin, Wengyi Zhan, Liujuan Cao

Transforming large pre-trained low-resolution diffusion models to cater to higher-resolution demands, i.e., diffusion extrapolation, significantly improves diffusion adaptability. We propose tuning-free CutDiffusion, aimed at simplifying and accelerating the diffusion extrapolation process, making it more affordable and improving performance. CutDiffusion ab

Suraj Maurya, Sashideep Gutti, Rahul Nigam

In Schwarzschild spacetime, Reinhart (1973) has shown the hypersurface $r_R = 3M/2$ (the subscript stands for "Reinhart") to be a maximal hypersurface. This Reinhart radius $r_R$ plays a crucial role in evaluating the interior volume of a black hole. In this article, we find such a maximal hypersurface for the Kerr and Kerr-Newaman black holes. We obtain the

Gilles G. de Castro, Daniel Gonçalves, Benjamin Steinberg

We prove the Effros-Hahn conjecture for groupoid algebras with coefficients in a sheaf, obtaining as a consequence a description of the ideals in skew inverse semigroup rings. We also use the description of the ideals to characterize when the groupoid algebras with coefficients in a sheaf are von Neumann regular, primitive, semiprimitive, or simple. We apply

Bhagyarathi Sahoo, Captain R. Singh, Raghunath Sahoo

The global and local spin polarization measurements of $\Lambda$ ($\bar{\Lambda}$) hyperons by STAR and ALICE Collaborations open up an immense interest in investigating the spin polarization dynamics in heavy-ion collisions. Recent studies suggest the transverse component of the vorticity field is responsible for the global spin polarization. In contrast, t

Yu Wu, Rishi Veerapaneni, Jiaoyang Li, Maxim Likhachev

The majority of multi-agent path finding (MAPF) methods compute collision-free space-time paths which require agents to be at a specific location at a specific discretized timestep. However, executing these space-time paths directly on robotic systems is infeasible due to real-time execution differences (e.g. delays) which can lead to collisions. To combat t

Hong-Fang Gong, Qi Lu, Zhen-Yan Lu, Lu-Meng Liu

We study the QCD topology and axion properties at finite temperature and chemical potential in the framework of the two-flavor Nambu$-$Jona-Lasinio model. We find that the behaviors of the two lowest cumulants of the QCD topological charge distribution and axion properties are highly sensitive to the critical behavior of the chiral phase transition. In parti

Jakki O. Bailey, Xinyue, You

People leverage avatars to communicate nonverbal behaviors in immersive virtual reality (VR), like interpersonal distance [2, 6] and virtual touch [5]. However, violations of appropriate physical distancing and unsolicited intimate touching behavior in social virtual worlds represent potential social and psychological virtual harm to older adolescent users [

Rohit Premlal, B. Sundar Rajan

Function-correcting codes were introduced in the work "Function-Correcting Codes" (FCC) by Lenz et al. 2023, which provides a graphical representation for the problem of constructing function-correcting codes. We use this function dependent graph to get a lower bound on the redundancy required for function correction codes. By considering the function to be

Libor Vojáček, Joaquín Medina Dueñas, Jing Li, Fatima Ibrahim

We report a very large spin-orbit torque (SOT) capability of chromium-based transition metal dichalcogenides (TMD) in their Janus forms CrXTe, with X=S,Se. The structural inversion symmetry breaking, inherent to Janus structures is responsible for a large SOT response generated by giant Rashba splitting, equivalent to that obtained by applying a transverse e

Chaoyi Lu, Nial Friel

There is increasing interest to develop Bayesian inferential algorithms for point process models with intractable likelihoods. A purpose of this paper is to illustrate the utility of using simulation based strategies, including Approximate Bayesian Computation (ABC) and Markov Chain Monte Carlo (MCMC) methods for this task. Shirota and Gelfand (2017) propose

Bo Ying Su, Yuchen Wu, Chengtao Wen, Changliu Liu

Tactile and textile skin technologies have become increasingly important for enhancing human-robot interaction and allowing robots to adapt to different environments. Despite notable advancements, there are ongoing challenges in skin signal processing, particularly in achieving both accuracy and speed in dynamic touch sensing. This paper introduces a new fra

Fan Fei, Yulu Mao, Wuzhang Fang, Wenhao Liu

Spin-mechanical coupling is vital in diverse fields including spintronics, sensing and quantum transduction. Two-dimensional (2D) magnetic materials provide a unique platform for investigating spin-mechanical coupling, attributed to their mechanical flexibility and novel spin orderings. However, studying spin-mechanical coupling in 2D magnets presents challe

Sara Dadjouy, Hedieh Sajedi

Medical image analysis is a significant application of artificial intelligence for disease diagnosis. A crucial step in this process is the identification of regions of interest within the images. This task can be automated using object detection algorithms. YOLO and Faster R-CNN are renowned for such algorithms, each with its own strengths and weaknesses. T

Dario Baratella, Omar Abou El Kheir, Marco Bernasconi

A machine-learned interatomic potential for Ge-rich Ge$_x$Te alloys has been developed aiming at uncovering the kinetics of phase separation and crystallization in these materials. The results are of interest for the operation of embedded phase change memories which exploits Ge-enrichment of GeSbTe alloys to raise the crystallization temperature. The potenti

Sunan He, Yuxiang Nie, Hongmei Wang, Shu Yang

Generalist foundation models (GFMs) are renowned for their exceptional capability and flexibility in effectively generalizing across diverse tasks and modalities. In the field of medicine, while GFMs exhibit superior generalizability based on their extensive intrinsic knowledge as well as proficiency in instruction following and in-context learning, speciali

The Nguyen

The Cayley distance between two permutations $\pi, \sigma \in S_n$ is the minimum number of \textit{transpositions} required to obtain the permutation $\sigma$ from $\pi$. When we only allow adjacent transpositions, the minimum number of such transpositions to obtain $\sigma$ from $\pi$ is referred to the Kendall $\tau$-distance. A set $C$ of permutation wor

Zhenxing Di, Liping Li, Li Liang

In this paper we consider representations of certain combinatorial categories, including the poset $\D$ of positive integers and division, the Young lattice $\mathscr{Y}$ of partitions of finite sets, the opposite category of the orbit category $\mathscr{Z}$ of $(\mathbb{Z}, +)$ with respect to nontrivial subgroups, and the category $\mathscr{CI}$ of finite

Peter Gracar, Arne Grauer

We study the phenomenon of information propagation on mobile geometric scale-free random graphs, where vertices instantaneously pass on information to all other vertices in the same connected component. The graphs we consider are constructed on a Poisson point process of intensity $\lambda>0$, and the vertices move over time as simple Brownian motions on eit

Petrus W. N. van Diepen, Martijn C. van Beurden, Roeland J. Dilz

An implicit causal space-time Galerkin scheme applied to the contrast current density volume integral equation gives rise to a marching-on-in-time scheme known as the MOT-JVIE, which is accelerated and stabilized via a fully embedded FIR filter to compute the electromagnetic scattering from high permittivity dielectric objects discretized with over a million

Didier Barret, Vincent Albouys, Jürgen Knödlseder, Xavier Loizillon

The X-ray Integral Field Unit (X-IFU) is the high-resolution X-ray spectrometer to fly on board the Athena Space Observatory of the European Space Agency (ESA). It is being developed by an international Consortium led by France, involving twelve ESA member states, plus the United States. It is a cryogenic instrument, involving state of the art technology, su

Rui Chen, Mingyi Shi, Shaoli Huang, Ping Tan

We present a novel character control framework that effectively utilizes motion diffusion probabilistic models to generate high-quality and diverse character animations, responding in real-time to a variety of dynamic user-supplied control signals. At the heart of our method lies a transformer-based Conditional Autoregressive Motion Diffusion Model (CAMDM),

Garima Gupta, Kenji Watanabe, Takashi Taniguchi, Kausik Majumdar

Motional narrowing implies narrowing induced by motion, for example, in nuclear resonance, the thermally induced random motion of the nuclei in an inhomogeneous environment leads to counter-intuitive narrowing of the resonance line. Similarly, the excitons in monolayer semiconductors experience magnetic inhomogeneity: the electron-hole spin-exchange interact

Shi-Mei Ma, Toufik Mansour, Jean Yeh, Yeong-Nan Yeh

We introduce the theory of normal ordered grammars, which gives a natural generalization of the normal ordering problem. To illustrate the main idea, we explore normal ordered grammars associated with the Eulerian polynomials and the second-order Eulerian polynomials. In particular, we present a normal ordered grammatical interpretation for the (cdes,cyc) (p

Rodrigo Carmo Terin, Zochil González Arenas, Roberto Santana

The use of machine learning algorithms to investigate phase transitions in physical systems is a valuable way to better understand the characteristics of these systems. Neural networks have been used to extract information of phases and phase transitions directly from many-body configurations. However, one limitation of neural networks is that they require t

Kerry S. Klemmer, Michael F. Howland

To achieve decarbonization targets, wind turbines are growing in hub height, rotor diameter, and are being deployed in new locations with diverse atmospheric conditions not previously seen, such as offshore. Physics-based analytical wake models commonly used for design and control of wind farms simplify atmospheric boundary layer (ABL) and wake physics to ac

Ian Balitsky

I calculate ${1\over Q^2}$ power corrections to unpolarized Drell-Yan hadronic tensor for electromagnetic (EM) current at large $N_c$ and demonstrate the EM gauge invariance at this level.

Ettore Settanni

Principal Component Analysis and biplots are so well-established and readily implemented that it is just too tempting to give for granted their internal workings. In this note I get back to basics in comparing how PCA and biplots are implemented in base-R and contributed R packages, leveraging an implementation-agnostic understanding of the computational str

Jochen Glück, Jonathan Mui

We study heat equations $\partial_t u - \operatorname{div}(A\nabla u) = 0$ on bounded Lipschitz domains $\Omega$, where $-\operatorname{div}(A\nabla\,\cdot\,)$ is a second-order uniformly elliptic operator with generalised Robin boundary conditions. These boundary conditions are formally given by $\nu\cdot A\nabla u + Bu=0$, where $B\in\mathcal{L}(L^2(\parti

Giuseppe Degrassi, Ramona Gröber, Marco Vitti

We present the virtual corrections due to the top-quark loops for the process $gg \to ZZ$ at next-to-leading order in QCD. The associated two-loop box diagrams are computed using a small-transverse-momentum expansion. Our results are then merged with those available in the complementary energy region, obtained via a high-energy expansion, in order to provide

Luca Buonocore, Luca Rottoli, Paolo Torrielli

We consider neutral- and charged-current Drell Yan lepton-pair production at hadron colliders, and include dominant classes of electroweak and mixed QCD-electroweak corrections to all orders in perturbation theory. The accurate description of these physical effects is vital for a precise determination of fundamental Standard Model parameters, such as the $W$

Qin-Geng Chen, Ming-Yue Liu, Xian-Xian Huang, Jiaojiao Chen

Cavity optomechanics, providing an inherently nonlinear interaction between photons and phonons, have shown enomerous potential in generating macroscopic quantum entanglement. Here we propose to realize diverse bipartite and tripartite entanglement in cavity-magnon optomechanics. By introducing magnons to standard cavity optomechanics, not only tunable optom

Sergii Parchenko, Matthias Riepp, Simon Marotzke, Agne Åberg Larsson

We explore the impact of optical excitation using two interfering ultrashort optical pulses on ultrafast magnetization dynamics. Our investigation focuses on Pt/Co/Pt multilayers and TbCo alloy samples, employing a dual pump approach. We observe significant variations in the dynamics of magnetization suppression and subsequent recovery when triggered with tw

Anson Lei, Frederik Nolte, Bernhard Schölkopf, Ingmar Posner

We present COmpetitive Mechanisms for Efficient Transfer (COMET), a modular world model which leverages reusable, independent mechanisms across different environments. COMET is trained on multiple environments with varying dynamics via a two-step process: competition and composition. This enables the model to recognise and learn transferable mechanisms. Spec

Heather Snyder Quinn, Jessa Dickinson

Mariah is an augmented reality (AR) mobile application that exposes power structures (e.g., capitalism, patriarchy, white supremacy) through storytelling and celebrates acts of resistance against them. People can use Mariah to "legally trespass" the metaverse as a form of protest. Mariah provides historical context to the user's physical surroundings by supe

Zheng Ning, Zheng Zhang, Jerrick Ban, Kaiwen Jiang

Spatial audio offers more immersive video consumption experiences to viewers; however, creating and editing spatial audio often expensive and requires specialized equipment and skills, posing a high barrier for amateur video creators. We present MIMOSA, a human-AI co-creation tool that enables amateur users to computationally generate and manipulate spatial

Asaf Szulc, Ido Regev

The origin of the transition from asymptotically reversible to asymptotically irreversible response in amorphous solids subject to oscillatory shear is still unknown. It is known that the plastic events that result from shearing always involve localized particle rearrangements, but it is unclear why some are reversible while others are not. Here we show, usi

Satadru Bag, Simon Huber, Sherry H. Suyu, Nikki Arendse

Strongly gravitationally lensed supernovae (LSNe) are promising probes for providing absolute distance measurements using gravitational-lens time delays. Spatially unresolved LSNe offer an opportunity to enhance the sample size for precision cosmology. We predict that there will be approximately three times as many unresolved as resolved LSNe Ia in the Legac

Carsten Gundlach, David Hilditch, Thomas W. Baumgarte

We present a code for numerical simulations of the collapse of regular initial data to a black hole in null coordinates. We restrict to twist-free axisymmetry with scalar field matter. Our coordinates are $(u,x,y,\varphi)$, where the retarded time $u$ labels outgoing null cones emerging from a regular central worldline, the angles $(\theta,\varphi)$ label th

Kevin Stowe, Benny Longwill, Alyssa Francis, Tatsuya Aoyama

Natural language generation tools are powerful and effective for generating content. However, language models are known to display bias and fairness issues, making them impractical to deploy for many use cases. We here focus on how fairness issues impact automatically generated test content, which can have stringent requirements to ensure the test measures o

Kuicai Dong, Derrick Goh Xin Deik, Yi Quan Lee, Hao Zhang

Long document question answering (DocQA) aims to answer questions from long documents over 10k words. They usually contain content structures such as sections, sub-sections, and paragraph demarcations. However, the indexing methods of long documents remain under-explored, while existing systems generally employ fixed-length chunking. As they do not consider

Beñat Martinez de Aguirre Jokisch, Benjamin Falkenberg Gøtzsche, Philip Trøst Kristensen, Martijn Wubs

Optical trapping enables precise control of individual particles of different sizes, such as atoms, molecules, or nanospheres. Optical tweezers provide free-space omnidirectional optical trapping of objects in laboratories around the world. As an alternative to standard macroscopic setups based on lenses, which are inherently bound by the diffraction limit,

Mengjie Zu, Carl Goodrich

The ability to control forces between sub-micron-scale building blocks offers considerable potential for designing new materials through self-assembly. A typical paradigm is to first identify a particular (crystal) structure that has some desired property, and then design building-block interactions so that this structure assembles spontaneously. While signi

Xun Wu, Shaohan Huang, Furu Wei

Recent studies have demonstrated the exceptional potentials of leveraging human preference datasets to refine text-to-image generative models, enhancing the alignment between generated images and textual prompts. Despite these advances, current human preference datasets are either prohibitively expensive to construct or suffer from a lack of diversity in pre

Yunsong Gui, Tian Hong Loh

The inherent long decay power delay profile (PDP) in the reverberation chamber (RC) is a major challenge for accurate channel emulation of 3GPP channel model, which is widely used in performance test of the physical layer. To tackle this challenge, we propose in this paper a novel two-step "closed-loop" approach consisting of (i) a channel measuring step and

Farzan Kaviani, Ivan Markovsky, Hamid R. Ossareh

We revisit the problem of predicting the output of an LTI system directly using offline input-output data (and without the use of a parametric model) in the behavioral setting. Existing works calculate the output predictions by projecting the recent samples of the input and output signals onto the column span of a Hankel matrix consisting of the offline inpu

Myrto Falalaki, Vasiliki Pavlidou

Cosmic ray (CR) knees (spectral steepenings) encode information on CR accelerator populations. We seek population features that imprint onto knee observables in a manner that is robust enough to be discernible even in the presence of significant systematics in CR data. In particular, we explore how diversity among population members could imprint on the knee

Neil Guan, Shangqun Yu, Shifan Zhu, Donghyun Kim

Replicating the remarkable athleticism seen in animals has long been a challenge in robotics control. Although Reinforcement Learning (RL) has demonstrated significant progress in dynamic legged locomotion control, the substantial sim-to-real gap often hinders the real-world demonstration of truly dynamic movements. We propose a new framework to mitigate thi

Mike Wa Nkongolo

This study discusses how insights retrieved from subscriber data can impact decision-making in telecommunications, focusing on predictive modeling using machine learning techniques such as the ARIMA model. The study explores time series forecasting to predict subscriber usage trends, evaluating the ARIMA model's performance using various metrics. It also com

Anna Zhitnitsky, Elad Benjamin, Ora Bitton, Dan Oron

We present super-resolved coherent anti-Stokes Raman scattering (CARS) microscopy by implementing phase-resolved image scanning microscopy (ISM), achieving up to two-fold resolution increase as compared with a conventional CARS microscope. Phase-sensitivity is required for the standard pixel-reassignment procedure since the scattered field is coherent, thus

Jefferson Seide Molléri

Population analysis is crucial for ensuring that empirical software engineering (ESE) research is representative and its findings are valid. Yet, there is a persistent gap between sampling processes and the holistic examination of populations, which this position paper addresses. We explore the challenges ranging from analysing populations of individual soft

Markus Kulossa, Joachim Wagner

We provide analytical expressions for the second virial coefficients of hard, convex, monoaxial solids of revolution in ${\mathbb{R}^{4}}$. The excluded volume per particle and thus the second virial coefficient is calculated using quermassintegrals and rotationally invariant mixed volumes based on the Brunn-Minkowski theorem. We derive analytical expression

Chukwuemeka Muonagor, Mounir Bensalem, Admela Jukan

Intent-Based Networking (IBN) is a known concept for enabling the autonomous configuration and self-adaptation of networks. One of the major issues in IBN is maintaining the applied intent due the effects of drifts over time, which is the gradual degradation in the fulfillment of the intents, before they fail. Despite its critical role to intent assurance an

David M. Markowitz

This paper evaluated the effectiveness of using generative AI to simplify science communication and enhance the public's understanding of science. By comparing lay summaries of journal articles from PNAS, yoked to those generated by AI, this work first assessed linguistic simplicity differences across such summaries and public perceptions in follow-up experi

Snigdha Dhar, Md. Shafiqul Islam

This paper is devoted to find the numerical solutions of one dimensional general nonlinear system of third-order boundary value problems (BVPs) for the pair of functions using Galerkin weighted residual method. We derive mathematical formulations in matrix form, in details, by exploiting Bernstein polynomials as basis functions. A reasonable accuracy is foun

Jerome Martin, Christophe Ringeval, Vincent Vennin

We show that the simplest, and currently favoured, theoretical realizations of cosmic inflation yield a sharp prediction for the running of the spectral index $\alpha_\mathrm{S}$. Using latest cosmological data, we compute its marginalized posterior probability distribution over the space of nearly 300 models of single-field slow-roll inflation. The most pro

Aodong Li, Bingcong Xu, Biye Xie

Disorder, traditionally believed to hinder the propagation of waves. has recently been shown to prompt the occurrence of topological phase transitions. For example, when disorder strength continuously increases and surpasses certain critical value, a phase transition from topologically trivial to nontrivial insulating phases occurs. However, in the parameter

Yue Hu, Bin Huang, Chunzi Zang

Protein circular permutations are crucial for understanding protein evolution and functionality. Traditional detection methods, sequence-based or structure-based, struggle with accuracy and computational efficiency, the latter also limited by treating proteins as rigid bodies. The plmCP method, utilizing a protein language model, not only speeds up the detec

Brian E. Wood, Graham M. Harper, Hans-Reinhard Mueller

We describe recent spectroscopic observations of red giant stars made by the Space Telescope Imaging Spectrograph (STIS) instrument on board the Hubble Space Telescope, which have provided spatially resolved observations of the warm chromospheric winds that predominate for early K to mid-M giants. The H I Lyman-alpha lines of a set of 11 red giants observed

Mikhail A. Ivanov, Jignesh N. Pandya, Pietro Santorelli, Nakul R. Soni

We study the rare semileptonic decays of $B_c$ mesons within the effective field theoretical framework of covariant confined quark model. The transition form factors corresponding to $B_c^+ \to D^{(*)+}$ and $B_c^+ \to D_s^{(*)+}$ are computed in the entire $q^2$ range. Using form factors, we compute the branching fractions and compare them with the availabl

Yuta Saito, Masahiro Nomura

There has been a growing interest in off-policy evaluation in the literature such as recommender systems and personalized medicine. We have so far seen significant progress in developing estimators aimed at accurately estimating the effectiveness of counterfactual policies based on biased logged data. However, there are many cases where those estimators are