Tootfinder

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new/
[6/6]:
TooBadRL: Trigger Optimization to Boost Effectiveness of Backdoor Attacks on Deep Reinforcement L...

Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new/
[1/1]:
Distortion-Aware Brushing for Reliable Cluster Analysis in Multidimensional Projections

Replaced article(s) found for cs.DC. https://arxiv.org/list/cs.DC/new/
[1/1]:
Fully Energy-Efficient Randomized Backoff: Slow Feedback Loops Yield Fast Contention Resolution

[2025-05-15 Thu (UTC), no new articles found for q-fin.TR Trading and Market Microstructure]
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Replaced article(s) found for gr-qc. https://arxiv.org/list/gr-qc/new/
[1/1]:
Mode stability for the Teukolsky equations on Kerr-anti-de Sitter spacetimes

My Saturday morning: remove 18 words - 16 of them adjectives - from the last 1 page I wrote. Done. What was I thinking!

[2025-05-14 Wed (UTC), 1 new article found for cs.OH Other Computer Science]
#toXiv_bot_toot

Replaced article(s) found for q-bio.NC. https://arxiv.org/list/q-bio.NC/new/
[1/1]:
On Broken Symmetry in Cognition
https://

Replaced article(s) found for math.RT. https://arxiv.org/list/math.RT/new/
[1/1]:
Diagrammatics for real supergroups
https://

Replaced article(s) found for astro-ph.IM. https://arxiv.org/list/astro-ph.IM/new/
[1/1]:
Energy Reconstruction of Non-fiducial Electron-Positron Events in the DAMPE Experiment Using Conv...

Replaced article(s) found for math.LO. https://arxiv.org/list/math.LO/new/
[1/1]:
The initial segment condition for $\kappa^ $-supercompactness
ht…

[2025-04-15 Tue (UTC), no new articles found for cs.GL General Literature]

How Well Can Reasoning Models Identify and Recover from Unhelpful Thoughts?
Sohee Yang, Sang-Woo Lee, Nora Kassner, Daniela Gottesman, Sebastian Riedel, Mor Geva
https://arxiv.org/abs/2506.10979

How Well Can Reasoning Models Identify and Recover from Unhelpful Thoughts?
Recent reasoning models show the ability to reflect, backtrack, and self-validate their reasoning, which is crucial in spotting mistakes and arriving at accurate solutions. A natural question that arises is how effectively models can perform such self-reevaluation. We tackle this question by investigating how well reasoning models identify and recover from four types of unhelpful thoughts: uninformative rambling thoughts, thoughts irrelevant to the question, thoughts misdirecting the question a…

Replaced article(s) found for econ.GN. https://arxiv.org/list/econ.GN/new/
[1/1]:
Paired Completion: Flexible Quantification of Issue-framing at Scale with LLMs

This https://arxiv.org/abs/2403.16971 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csOS_…

AIOS: LLM Agent Operating System
LLM-based intelligent agents face significant deployment challenges, particularly related to resource management. Allowing unrestricted access to LLM or tool resources can lead to inefficient or even potentially harmful resource allocation and utilization for agents. Furthermore, the absence of proper scheduling and resource management mechanisms in current agent designs hinders concurrent processing and limits overall system efficiency. As the diversity and complexity of agents continue to gro…

Prompt Variability Effects On LLM Code Generation
Andrei Paleyes, Radzim Sendyka, Diana Robinson, Christian Cabrera, Neil D. Lawrence
https://arxiv.org/abs/2506.10204

Prompt Variability Effects On LLM Code Generation
Code generation is one of the most active areas of application of Large Language Models (LLMs). While LLMs lower barriers to writing code and accelerate development process, the overall quality of generated programs depends on the quality of given prompts. Specifically, functionality and quality of generated code can be sensitive to user's background and familiarity with software development. It is therefore important to quantify LLM's sensitivity to variations in the input. To this end we prop…

Replaced article(s) found for eess.AS. https://arxiv.org/list/eess.AS/new/
[1/1]:
Optimal Scalogram for Computational Complexity Reduction in Acoustic Recognition Using Deep Learning

[2025-05-14 Wed (UTC), no new articles found for q-fin.TR Trading and Market Microstructure]
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Replaced article(s) found for math.AG. https://arxiv.org/list/math.AG/new/
[1/1]:
Liftings of ideals in positive characteristic to those in characteristic zero : Low dimension

The Iris File Extension
Ryan Erik Landvater, Michael David Olp, Mustafa Yousif, Ulysses Balis
https://arxiv.org/abs/2506.10009 https://

The Iris File Extension
A modern digital pathology vendor-agnostic binary slide format specifically targeting the unmet need of efficient real-time transfer and display has not yet been established. Growing adoption of digital pathology only intensifies the need for an intermediary digital slide format with an emphasis on performance for use between slide servers and image management software or for inter-institutional transmission of cases. Although the DICOM standard is a well-established format widely used for long…

Replaced article(s) found for cs.DB. https://arxiv.org/list/cs.DB/new/
[1/1]:
GenJoin: Conditional Generative Plan-to-Plan Query Optimizer that Learns from Subplan Hints

This https://arxiv.org/abs/2505.18675 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

Can MLLMs Guide Me Home? A Benchmark Study on Fine-Grained Visual Reasoning from Transit Maps
Multimodal large language models (MLLMs) have recently achieved significant progress in visual tasks, including semantic scene understanding and text-image alignment, with reasoning variants enhancing performance on complex tasks involving mathematics and logic. However, their capacity for reasoning tasks involving fine-grained visual understanding remains insufficiently evaluated. To address this gap, we introduce ReasonMap, a benchmark designed to assess the fine-grained visual understanding …

[2025-05-15 Thu (UTC), 1 new article found for q-bio.OT Other Quantitative Biology]
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[2025-06-13 Fri (UTC), 11 new articles found for eess.SP Signal Processing]
toXiv_bot_toot

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new/
[5/5]:
AnnaAgent: Dynamic Evolution Agent System with Multi-Session Memory for Realistic Seeker Simulation

Replaced article(s) found for cond-mat.mtrl-sci. https://arxiv.org/list/cond-mat.mtrl-sci/new/
[1/1]:
Ab Initio bulk free energy surface of proper ferroelectrics

A Combined Parallel-in-time Direct Inverse (ParaDIn)-Parareal Method for Nonlinear Differential Equations
Subhash Paudel, Nail K. Yamaleev
https://arxiv.org/abs/2506.10820

A Combined Parallel-in-time Direct Inverse (ParaDIn)-Parareal Method for Nonlinear Differential Equations
As has been shown in our previous work, the parallel-in-time direct inverse (ParaDIn) method introduced by Yamaleev and Paudel in (arXiv: 2406.00878v1, 2024) imposes some constraint on the maximum number of time levels, $N_t$, that can be integrated in parallel. To circumvent this problem and further increase the speedup, we combine the ParaDIn method with the Parareal algorithm to efficiently parallelize the first-order time derivative term in nonlinear partial differential equations discretiz…

This https://arxiv.org/abs/2502.09180 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

A Machine Learning Approach to Sensor Substitution from Tactile Sensing to Visual Perception for Non-Prehensile Manipulation
Mobile manipulators are increasingly deployed in complex environments, requiring diverse sensors to perceive and interact with their surroundings. However, equipping every robot with every possible sensor is often impractical due to cost and physical constraints. A critical challenge arises when robots with differing sensor capabilities need to collaborate or perform similar tasks. For example, consider a scenario where a mobile manipulator equipped with high-resolution tactile skin is skilled …

Accidental coincidences in camera-based high-dimensional entanglement certification
Rapha\"el Guitter (Institut des NanoSciences de Paris), Baptiste Courme (Institut des NanoSciences de Paris, Laboratoire Kastler Brossel), Chlo\'e Verni\`ere (Institut des NanoSciences de Paris), Peter Svihra (Faculty of Nuclear Sciences and Physical Engineering Czech Technical University), Andrei Nomerotski (Faculty of Nuclear Sciences and Physical Engineering Czech Technical University), Hugo…

Accidental coincidences in camera-based high-dimensional entanglement certification
High-dimensional entangled states, such as spatially-entangled photon pairs produced by Spontaneous Parametric Down-Conversion (SPDC), are a key resource for quantum technologies. In recent years, camera-based coincidence counting approaches have considerably improved the ability to characterize them in terms of speed and dimensionality. However, these methods have limitations, including in most of them the necessity to subtract accidental coincidences. Here, we study the role of these accident…

[2025-04-14 Mon (UTC), no new articles found for cs.GL General Literature]

Instance-Based Transfer Learning with Similarity-Aware Subject Selection for Cross-Subject SSVEP-Based BCIs
Ziwen Wang, Yue Zhang, Zhiqiang Zhang, Sheng Quan Xie, Alexander Lanzon, William P. Heath, Zhenhong Li
https://arxiv.org/abs/2506.10933

Instance-Based Transfer Learning with Similarity-Aware Subject Selection for Cross-Subject SSVEP-Based BCIs
Steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) can achieve high recognition accuracy with sufficient training data. Transfer learning presents a promising solution to alleviate data requirements for the target subject by leveraging data from source subjects; however, effectively addressing individual variability among both target and source subjects remains a challenge. This paper proposes a novel transfer learning framework, termed instance-based task-relat…

Reward Models Enable Scalable Code Verification by Trading Accuracy for Throughput
Gabriel Orlanski, Nicholas Roberts, Aws Albarghouthi, Frederic Sala
https://arxiv.org/abs/2506.10056

Reward Models Enable Scalable Code Verification by Trading Accuracy for Throughput
The standard paradigm for solving coding tasks via large language models (LLMs) is to generate-then-rank programs, where the latter step uses a verifier in the ranking process. The growing consensus is that a comprehensive verifier (e.g., a full test suite) should be prioritized over an outcome reward model (ORM) whenever possible, with little consideration given to the trade-offs involved. We aim to challenge this assumption by systematically exploring the tradeoff between speed and accuracy. …

Adaptive Job Scheduling in Quantum Clouds Using Reinforcement Learning
Waylon Luo (Kent State University), Jiapeng Zhao (Cisco), Tong Zhan (Meta), Qiang Guan (Kent State University)
https://arxiv.org/abs/2506.10889

Adaptive Job Scheduling in Quantum Clouds Using Reinforcement Learning
Present-day quantum systems face critical bottlenecks, including limited qubit counts, brief coherence intervals, and high susceptibility to errors-all of which obstruct the execution of large and complex circuits. The advancement of quantum algorithms has outpaced the capabilities of existing quantum hardware, making it difficult to scale computations effectively. Additionally, inconsistencies in hardware performance and pervasive quantum noise undermine system stability and computational accu…

[2025-06-12 Thu (UTC), 6 new articles found for math.AG Algebraic Geometry]
toXiv_bot_toot

This https://arxiv.org/abs/2505.18668 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

ChartGalaxy: A Dataset for Infographic Chart Understanding and Generation
Infographic charts are a powerful medium for communicating abstract data by combining visual elements (e.g., charts, images) with textual information. However, their visual and structural richness poses challenges for large vision-language models (LVLMs), which are typically trained on plain charts. To bridge this gap, we introduce ChartGalaxy, a million-scale dataset designed to advance the understanding and generation of infographic charts. The dataset is constructed through an inductive proc…

[2025-05-14 Wed (UTC), no new articles found for q-bio.OT Other Quantitative Biology]
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MOORL: A Framework for Integrating Offline-Online Reinforcement Learning
Gaurav Chaudhary, Wassim Uddin Mondal, Laxmidhar Behera
https://arxiv.org/abs/2506.09574

MOORL: A Framework for Integrating Offline-Online Reinforcement Learning
Sample efficiency and exploration remain critical challenges in Deep Reinforcement Learning (DRL), particularly in complex domains. Offline RL, which enables agents to learn optimal policies from static, pre-collected datasets, has emerged as a promising alternative. However, offline RL is constrained by issues such as out-of-distribution (OOD) actions that limit policy performance and generalization. To overcome these limitations, we propose Meta Offline-Online Reinforcement Learning (MOORL), …

Quantum gravitational corrections at third-order curvature, acoustic analog black holes and their quasinormal modes
R. Casadio, C. Noberto Souza, R. da Rocha
https://arxiv.org/abs/2506.10847

Quantum gravitational corrections at third-order curvature, acoustic analog black holes and their quasinormal modes
Quasinormal modes for bosonic (scalar, electromagnetic, and axial gravitational) and fermionic field perturbations, radiated from black holes that carry quantum gravitational corrections at third order in the curvature to the Schwarzschild solution, are scrutinized from the propagation of analog transonic sound waves across a de Laval nozzle. The thermodynamic variables, the nozzle geometry, the Mach number, and the thrust coefficient are computed as functions of the parameter driving the effec…

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new/
[4/5]:
Evolutionary Policy Optimization
https://arxiv.o…

This https://arxiv.org/abs/2506.04907 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

Verbose ListOps (VLO): Beyond Long Context -- Unmasking LLM's Reasoning Blind Spots
Large Language Models (LLMs), whilst great at extracting facts from text, struggle with nested narrative reasoning. Existing long context and multi-hop QA benchmarks inadequately test this, lacking realistic distractors or failing to decouple context length from reasoning complexity, masking a fundamental LLM limitation. We introduce Verbose ListOps, a novel benchmark that programmatically transposes ListOps computations into lengthy, coherent stories. This uniquely forces internal computation …

[2025-05-13 Tue (UTC), no new articles found for cs.OH Other Computer Science]
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[2025-06-13 Fri (UTC), no new articles found for q-bio.NC Neurons and Cognition]
toXiv_bot_toot

This https://arxiv.org/abs/2504.20349 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qfi…

Multi-Qubit Parity Gates for Rydberg Atoms in Various Configurations
Javad Kazemi, Michael Schuler, Christian Ertler, Wolfgang Lechner
https://arxiv.org/abs/2506.09686

Multi-Qubit Parity Gates for Rydberg Atoms in Various Configurations
We present a native approach for realizing multi-qubit parity phase gates in neutral atom systems through global phase modulation of a Rydberg excitation laser. By shaping the temporal profile of the laser's phase, we enable high fidelity, time efficient entangling operations between multiple qubits without requiring individual qubit addressing. To mitigate intrinsic noise sources including spontaneous decay and motional effects, we develop a noise-aware optimal control framework that reduces g…

Fluoroscopic Shape and Pose Tracking of Catheters with Custom Radiopaque Markers
Jared Lawson, Rohan Chitale, Nabil Simaan
https://arxiv.org/abs/2506.09934

Fluoroscopic Shape and Pose Tracking of Catheters with Custom Radiopaque Markers
Safe navigation of steerable and robotic catheters in the cerebral vasculature requires awareness of the catheters shape and pose. Currently, a significant perception burden is placed on interventionalists to mentally reconstruct and predict catheter motions from biplane fluoroscopy images. Efforts to track these catheters are limited to planar segmentation or bulky sensing instrumentation, which are incompatible with microcatheters used in neurointervention. In this work, a catheter is equippe…

Video-Mediated Emotion Disclosure: A Study of Mental Health Vlogging by People with Schizophrenia on YouTube
Jiaying Lizzy Liu, Yan Zhang
https://arxiv.org/abs/2506.10932

Video-Mediated Emotion Disclosure: A Study of Mental Health Vlogging by People with Schizophrenia on YouTube
Individuals with schizophrenia frequently experience intense emotions and often turn to vlogging as a medium for emotional expression. While previous research has predominantly focused on text based disclosure, little is known about how individuals construct narratives around emotions and emotional experiences in video blogs. Our study addresses this gap by analyzing 200 YouTube videos created by individuals with schizophrenia. Drawing on media research and self presentation theories, we develo…

The Impact of Partial Computations on the Red-Blue Pebble Game
P\'al Andr\'as Papp, Aleksandros Sobczyk, A. N. Yzelman
https://arxiv.org/abs/2506.10854

The Impact of Partial Computations on the Red-Blue Pebble Game
We study an extension of the well-known red-blue pebble game (RBP) with partial computation steps, inspired by the recent work of Sobczyk. While the original RBP assumes that we need to have all the inputs of an operation in fast memory at the same time, in many concrete computations, the inputs can be aggregated one by one into the final output value. These partial computation steps can enable pebbling strategies with much smaller I/O cost, and in settings where such a step-by-step aggregation…

STOAT: Spatial-Temporal Probabilistic Causal Inference Network
Yang Yang, Du Yin, Hao Xue, Flora Salim
https://arxiv.org/abs/2506.09544 https://

STOAT: Spatial-Temporal Probabilistic Causal Inference Network
Spatial-temporal causal time series (STC-TS) involve region-specific temporal observations driven by causally relevant covariates and interconnected across geographic or network-based spaces. Existing methods often model spatial and temporal dynamics independently and overlook causality-driven probabilistic forecasting, limiting their predictive power. To address this, we propose STOAT (Spatial-Temporal Probabilistic Causal Inference Network), a novel framework for probabilistic forecasting in …

Quasi-normal modes and echoes of generalized black hole bounces and their correspondence with shadows
Albert Duran-Cabac\'es, Diego Rubiera-Garcia, Diego S\'aez-Chill\'on G\'omez
https://arxiv.org/abs/2506.10814

Quasi-normal modes and echoes of generalized black hole bounces and their correspondence with shadows
We study the quasi-normal modes (QNMs) of a family of generalized black bounces interpolating between regular black holes and traversable wormhole solutions according to a single extra parameter $a$. Firstly, working with a generic spherically symmetric space-time with arbitrary radial function and an anisotropic fluid matter source, the general equations for the gravitational waves are obtained. Then, we focus on such particular space-time metric and use the time-domain method to find the evol…

This https://arxiv.org/abs/2506.04047 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

On Support Samples of Next Word Prediction
Language models excel in various tasks by making complex decisions, yet understanding the rationale behind these decisions remains a challenge. This paper investigates \emph{data-centric interpretability} in language models, focusing on the next-word prediction task. Using representer theorem, we identify two types of \emph{support samples}-those that either promote or deter specific predictions. Our findings reveal that being a support sample is an intrinsic property, predictable even before t…

The Role of Generative AI in Facilitating Social Interactions: A Scoping Review
T. T. J. E. Arets, G. Perugia, M. Houben, W. A. IJsselsteijn
https://arxiv.org/abs/2506.10927

The Role of Generative AI in Facilitating Social Interactions: A Scoping Review
Reduced social connectedness increasingly poses a threat to mental health, life expectancy, and general well-being. Generative AI (GAI) technologies, such as large language models (LLMs) and image generation tools, are increasingly integrated into applications aimed at enhancing human social experiences. Despite their growing presence, little is known about how these technologies influence social interactions. This scoping review investigates how GAI-based applications are currently designed to…

Towards Sustainable Computing: Exploring Energy Consumption Efficiency of Alternative Configurations and Workloads in an Open Source Messaging System
Maria Voreakou, George Kousiouris, Mara Nikolaidou
https://arxiv.org/abs/2506.10693

Towards Sustainable Computing: Exploring Energy Consumption Efficiency of Alternative Configurations and Workloads in an Open Source Messaging System
Energy consumption in current large scale computing infrastructures is becoming a critical issue, especially with the growing demand for centralized systems such as cloud environments. With the advancement of microservice architectures and the Internet of Things, messaging systems have become an integral and mainstream part of modern computing infrastructures, carrying out significant workload in a majority of applications. In this paper, we describe an experimental process to explore energy-ba…

[2025-05-13 Tue (UTC), 2 new articles found for q-fin.TR Trading and Market Microstructure]
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Athena: Enhancing Multimodal Reasoning with Data-efficient Process Reward Models
Shuai Wang, Zhenhua Liu, Jiaheng Wei, Xuanwu Yin, Dong Li, Emad Barsoum
https://arxiv.org/abs/2506.09532

Athena: Enhancing Multimodal Reasoning with Data-efficient Process Reward Models
We present Athena-PRM, a multimodal process reward model (PRM) designed to evaluate the reward score for each step in solving complex reasoning problems. Developing high-performance PRMs typically demands significant time and financial investment, primarily due to the necessity for step-level annotations of reasoning steps. Conventional automated labeling methods, such as Monte Carlo estimation, often produce noisy labels and incur substantial computational costs. To efficiently generate high-q…

(De)composing Craft: An Elementary Grammar for Sharing Expertise in Craft Workflows
Ritik Batra, Lydia Kim, Ilan Mandel, Amritansh Kwatra, Jane L. E., Steven J. Jackson, Thijs Roumen
https://arxiv.org/abs/2506.10891

(De)composing Craft: An Elementary Grammar for Sharing Expertise in Craft Workflows
Craft practices rely on evolving archives of skill and knowledge, developed through generations of craftspeople experimenting with designs, materials, and techniques. Better documentation of these practices enables the sharing of knowledge and expertise between sites and generations. However, most documentation focuses solely on the linear steps leading to final artifacts, neglecting the tacit knowledge necessary to improvise, or adapt workflows to meet the unique demands of each craft project.…

Analogous supercritical crossovers in black holes and water
Shoucheng Wang, Xinyang Li, Yuliang Jin, Li Li
https://arxiv.org/abs/2506.10808 https://…

Analogous supercritical crossovers in black holes and water
We investigate the supercritical crossovers for black hole thermodynamics in the supercritical regime beyond the critical point, where small and large black holes are indistinguishable from the conventional viewpoint. We establish a refined supercritical phase diagram that comprehensively characterizes small, large, and indistinguishable black hole phases, whose boundaries are defined by two supercritical crossover lines. The universal scaling laws of the two crossover lines are fully verified …

Deployment of Containerized Simulations in an API-Driven Distributed Infrastructure
Tim Kraus, Axel Sauer, Ingo Feldner
https://arxiv.org/abs/2506.10642 ht…

Deployment of Containerized Simulations in an API-Driven Distributed Infrastructure
The increasingly dynamic market for embedded systems makes virtual prototypes an indispensable tool for hardware/software codesign. The broad acceptance of the methodology has led to a diverse range of solutions: from open-source, pure console-based simulators to highly capable commercial simulation tools. In this work we present SUNRISE, an infrastructure to provide users a unified approach to utilizing virtual prototyping solutions, facilitate access to various simulation technologies and boo…

Grasp Prediction based on Local Finger Motion Dynamics
Dimitar Valkov, Pascal Kockwelp, Florian Daiber, Antonio Kr\"uger
https://arxiv.org/abs/2506.10818

Grasp Prediction based on Local Finger Motion Dynamics
The ability to predict the object the user intends to grasp offers essential contextual information and may help to leverage the effects of point-to-point latency in interactive environments. This paper explores the feasibility and accuracy of real-time recognition of uninstrumented objects based on hand kinematics during reach-to-grasp actions. In a data collection study, we recorded the hand motions of 16 participants while reaching out to grasp and then moving real and synthetic objects. Our…

SoK: Machine Unlearning for Large Language Models
Jie Ren, Yue Xing, Yingqian Cui, Charu C. Aggarwal, Hui Liu
https://arxiv.org/abs/2506.09227 https://

SoK: Machine Unlearning for Large Language Models
Large language model (LLM) unlearning has become a critical topic in machine learning, aiming to eliminate the influence of specific training data or knowledge without retraining the model from scratch. A variety of techniques have been proposed, including Gradient Ascent, model editing, and re-steering hidden representations. While existing surveys often organize these methods by their technical characteristics, such classifications tend to overlook a more fundamental dimension: the underlying…

Gauges for quadratic gravity: the extended transverse gauge and the energy-momentum tensor of the massive spin-2 field
Matheus F. S. Alves, L. G. Medeiros, Davi C. Rodrigues
https://arxiv.org/abs/2506.10793

Gauges for quadratic gravity: the extended transverse gauge and the energy-momentum tensor of the massive spin-2 field
We study the 4D Einstein-Hilbert action extension based on the square of the curvature tensors. Analyses of gauge and perturbation modes are often done considering the Teyssandier gauge condition. Although this approach can be useful for other higher-order extensions of quadratic gravity, a generalized transverse (or Lorentz) gauge is clear and sufficient for the present case, as explained here. We provide a detailed analysis of the generalized transverse gauge condition, its residual gauge sym…

Graph-based Gossiping for Communication Efficiency in Decentralized Federated Learning
Huong Nguyen, Hong-Tri Nguyen, Praveen Kumar Donta, Susanna Pirttikangas, Lauri Lov\'en
https://arxiv.org/abs/2506.10607

Graph-based Gossiping for Communication Efficiency in Decentralized Federated Learning
Federated learning has emerged as a privacy-preserving technique for collaborative model training across heterogeneously distributed silos. Yet, its reliance on a single central server introduces potential bottlenecks and risks of single-point failure. Decentralizing the server, often referred to as decentralized learning, addresses this problem by distributing the server role across nodes within the network. One drawback regarding this pure decentralization is it introduces communication ineff…

Revisiting the Excess Volatility Puzzle Through the Lens of the Chiarella Model
Jutta G. Kurth, Adam A. Majewski, Jean-Philippe Bouchaud
https://arxiv.org/abs/2505.07820

Revisiting the Excess Volatility Puzzle Through the Lens of the Chiarella Model
We amend and extend the Chiarella model of financial markets to deal with arbitrary long-term value drifts in a consistent way. This allows us to improve upon existing calibration schemes, opening the possibility of calibrating individual monthly time series instead of classes of time series. The technique is employed on spot prices of four asset classes from ca. 1800 onward (stock indices, bonds, commodities, currencies). The so-called fundamental value is a direct output of the calibration, w…

Integrating Large Language Models into Text Animation: An Intelligent Editing System with Inline and Chat Interaction
Bao Zhang, Zihan Li, Zhenglei Liu, Huanchen Wang, Yuxin Ma
https://arxiv.org/abs/2506.10762

Integrating Large Language Models into Text Animation: An Intelligent Editing System with Inline and Chat Interaction
Text animation, a foundational element in video creation, enables efficient and cost-effective communication, thriving in advertisements, journalism, and social media. However, traditional animation workflows present significant usability barriers for non-professionals, with intricate operational procedures severely hindering creative productivity. To address this, we propose a Large Language Model (LLM)-aided text animation editing system that enables real-time intent tracking and flexible edi…

6G Infrastructures for Edge AI: An Analytical Perspective
Kurt Horvath, Shpresa Tuda, Blerta Idrizi, Stojan Kitanov, Fisnik Doko, Dragi Kimovski
https://arxiv.org/abs/2506.10570

6G Infrastructures for Edge AI: An Analytical Perspective
The convergence of Artificial Intelligence (AI) and the Internet of Things has accelerated the development of distributed, network-sensitive applications, necessitating ultra-low latency, high throughput, and real-time processing capabilities. While 5G networks represent a significant technological milestone, their ability to support AI-driven edge applications remains constrained by performance gaps observed in real-world deployments. This paper addresses these limitations and highlights criti…

Detectability of massive binary black holes with sub-mHz gravitational wave missions
Renjie Wang, Yumeng Xu, Gang Wang, Bin Hu, Rong-Gen Cai
https://arxiv.org/abs/2506.10768

Detectability of massive binary black holes with sub-mHz gravitational wave missions
Beyond LISA, proposed space-based gravitational wave (GW) missions aim to explore the sub-millihertz to microhertz frequency band, with one key objective being the detection of massive binary black hole (MBBH) mergers across cosmic distances. In this work, we investigate the detection and localization capabilities of future sub-mHz GW observatories for MBBH coalescences. Including the full galactic foreground noise, we find that signal-to-noise ratios (SNRs) can reach several thousand across a …

Can LLM-based Financial Investing Strategies Outperform the Market in Long Run?
Weixian Waylon Li, Hyeonjun Kim, Mihai Cucuringu, Tiejun Ma
https://arxiv.org/abs/2505.07078

Can LLM-based Financial Investing Strategies Outperform the Market in Long Run?
Large Language Models (LLMs) have recently been leveraged for asset pricing tasks and stock trading applications, enabling AI agents to generate investment decisions from unstructured financial data. However, most evaluations of LLM timing-based investing strategies are conducted on narrow timeframes and limited stock universes, overstating effectiveness due to survivorship and data-snooping biases. We critically assess their generalizability and robustness by proposing FINSABER, a backtesting …

Accessible Design in Integrated Development Environments: A Think Aloud Study Exploring the Experiences of Students with ADHD
Luke Halpin, Phillip Benachour, Tracy Hall, Ann-Marie Houghton, Emily Winter
https://arxiv.org/abs/2506.10598

Accessible Design in Integrated Development Environments: A Think Aloud Study Exploring the Experiences of Students with ADHD
Coding forms a key part of computer science education in universities. As part of this education, Integrated Development Environments (IDEs) are essential tools for coding. However, it is currently unknown how the design of an IDE's interface impacts on students with Attention Deficit Hyperactivity Disorder (ADHD). In this study we investigated the use of IDEs by students with ADHD. We conducted a think aloud study with nine university computing students, followed by qualitative observational…

GPU-Accelerated Distributed QAOA on Large-scale HPC Ecosystems
Zhihao Xu, Srikar Chundury, Seongmin Kim, Amir Shehata, Xinyi Li, Ang Li, Tengfei Luo, Frank Mueller, In-Saeng Suh
https://arxiv.org/abs/2506.10531

GPU-Accelerated Distributed QAOA on Large-scale HPC Ecosystems
Quantum computing holds great potential to accelerate the process of solving complex combinatorial optimization problems. The Distributed Quantum Approximate Optimization Algorithm (DQAOA) addresses high-dimensional, dense problems using current quantum computing techniques and high-performance computing (HPC) systems. In this work, we improve the scalability and efficiency of DQAOA through advanced problem decomposition and parallel execution using message passing on the Frontier CPU/GPU super…

Entanglement and entropy uncertainty in black hole quantum atmosphere
Shuai Zhang, Li-Juan Li, Xue-Ke Song, Liu Ye, Dong Wang
https://arxiv.org/abs/2506.10631

Entanglement and entropy uncertainty in black hole quantum atmosphere
In this work, we investigate the properties of Hawking radiation induced by the quantum atmosphere beyond the event horizon, by considering two detectors in Schwarzschild spacetime with the parameterized Hartle-Hawking temperature. \textcolor{black}{We explicitly study the dynamics of quantum entanglement and found that its characteristics are closely correlated with Hawking quantum radiation beyond the event horizon. Namely, its minimal value corresponds to the peak of Hawking radiation.} By v…

IDEA: Augmenting Design Intelligence through Design Space Exploration
Chuer Chen, Xiaoke Yan, Xiaoyu Qi, Nan Cao
https://arxiv.org/abs/2506.10587 https://

IDEA: Augmenting Design Intelligence through Design Space Exploration
Design spaces serve as a conceptual framework that enables designers to explore feasible solutions through the selection and combination of design elements. However, effective decision-making remains heavily dependent on the designer's experience, and the absence of mathematical formalization prevents computational support for automated design processes. To bridge this gap, we introduce a structured representation that models design spaces with orthogonal dimensions and discrete selectable elem…

HP2C-DT: High-Precision High-Performance Computer-enabled Digital Twin
E. Iraola (Barcelona Supercomputing Center), M. Garc\'ia-Lorenzo (Barcelona Supercomputing Center), F. Lordan-Gomis (Barcelona Supercomputing Center), F. Rossi (CITCEA, Universitat Polit\`ecnica de Catalunya), E. Prieto-Araujo (CITCEA, Universitat Polit\`ecnica de Catalunya), R. M. Badia (Barcelona Supercomputing Center)

HP2C-DT: High-Precision High-Performance Computer-enabled Digital Twin
Digital twins are transforming the way we monitor, analyze, and control physical systems, but designing architectures that balance real-time responsiveness with heavy computational demands remains a challenge. Cloud-based solutions often struggle with latency and resource constraints, while edge-based approaches lack the processing power for complex simulations and data-driven optimizations. To address this problem, we propose the High-Precision High-Performance Computer-enabled Digital Twin …

Beyond Compliance: A User-Autonomy Framework for Inclusive and Customizable Web Accessibility
Lalitha A R
https://arxiv.org/abs/2506.10324 https://

Beyond Compliance: A User-Autonomy Framework for Inclusive and Customizable Web Accessibility
This paper proposes a shift from compliance-centered web accessibility to a care-driven model that prioritizes user autonomy, using neurodivergent users as a catalyst case for broader personalization needs. While accessibility standards offer a flexible framework, they are often interpreted and implemented as static compliance checklists, our approach reframes it as a flexible, user-centered process. We introduce a customizable Comfort Mode framework that allows users to adapt interface setting…

HBAR entropy of Infalling Atoms into a GUP-corrected Schwarzschild Black Hole and equivalence principle
Ali \"Ovg\"un, Reggie C. Pantig
https://arxiv.org/abs/2506.10621 …

HBAR entropy of Infalling Atoms into a GUP-corrected Schwarzschild Black Hole and equivalence principle
In this work, we have investigated the phenomenon of acceleration radiation exhibited by a two-level atom freely falling into a Generalized Uncertainty Principle (GUP)-corrected Schwarzschild black hole. We derive analytic expressions for the atom's excitation probability with simultaneous emission of a scalar quantum and observe that it satisfies the Einstein equivalence principle when compared to the excitation probability induced by a uniformly accelerating mirror, motivated by studies [10.1…

Trading Under Uncertainty: A Distribution-Based Strategy for Futures Markets Using FutureQuant Transformer
Wenhao Guo, Yuda Wang, Zeqiao Huang, Changjiang Zhang, Shumin ma
https://arxiv.org/abs/2505.05595

Trading Under Uncertainty: A Distribution-Based Strategy for Futures Markets Using FutureQuant Transformer
In the complex landscape of traditional futures trading, where vast data and variables like real-time Limit Order Books (LOB) complicate price predictions, we introduce the FutureQuant Transformer model, leveraging attention mechanisms to navigate these challenges. Unlike conventional models focused on point predictions, the FutureQuant model excels in forecasting the range and volatility of future prices, thus offering richer insights for trading strategies. Its ability to parse and learn from…

TD-Pipe: Temporally-Disaggregated Pipeline Parallelism Architecture for High-Throughput LLM Inference
Hongbin Zhang, Taosheng Wei, Zhenyi Zheng, Jiangsu Du, Zhiguang Chen, Yutong Lu
https://arxiv.org/abs/2506.10470

TD-Pipe: Temporally-Disaggregated Pipeline Parallelism Architecture for High-Throughput LLM Inference
As the model size continuously increases, pipeline parallelism shows great promise in throughput-oriented LLM inference due to its low demand on communications. However, imbalanced pipeline workloads and complex data dependencies in the prefill and decode phases result in massive pipeline bubbles and further severe performance reduction. To better exploit the pipeline parallelism for high-throughput LLM inference, we propose TD-Pipe, with the key idea lies in the temporally-disaggregated pipeli…

Extended Creativity: A Conceptual Framework for Understanding Human-AI Creative Relations
Andrea Gaggioli, Sabrina Bartolotta, Andrea Ubaldi, Katusha Gerardini, Eleonora Diletta Sarcinella, Alice Chirico
https://arxiv.org/abs/2506.10249

Extended Creativity: A Conceptual Framework for Understanding Human-AI Creative Relations
Artificial Intelligence holds significant potential to enhance human creativity. However, achieving this vision requires a clearer understanding of how such enhancement can be effectively realized. Adopting the perspective of distributed creativity, we identify three primary modes through which AI can contribute to creative processes: Support, where AI acts as a tool; Synergy, where AI and humans collaborate in complementary ways; and Symbiosis, where human and AI cognition become so integrated…

Enhancing Taiji's Parameter Estimation under Non-Stationarity: a Time-Frequency Domain Framework for Galactic Binaries and Instrumental Noises
Minghui Du, Ziren Luo, Peng Xu
https://arxiv.org/abs/2506.10599

Enhancing Taiji's Parameter Estimation under Non-Stationarity: a Time-Frequency Domain Framework for Galactic Binaries and Instrumental Noises
The data analysis of space-based gravitational wave detectors like Taiji faces significant challenges from non-stationary noise, which compromises the efficacy of traditional frequency-domain analysis. This work proposes a unified framework based on short-time Fourier transform (STFT) to enhance parameter estimation of Galactic binary and characterization of instrumental noise under non-stationarity. Segmenting data into locally stationary intervals, we derive STFT-based models for signals and …

Automating Multi-Tenancy Performance Evaluation on Edge Compute Nodes
Joanna Georgiou, Moysis Symeonides, George Pallis, Marios D. Dikaiakos
https://arxiv.org/abs/2506.10461

Automating Multi-Tenancy Performance Evaluation on Edge Compute Nodes
Edge Computing emerges as a promising alternative of Cloud Computing, with scalable compute resources and services deployed in the path between IoT devices and Cloud. Since virtualization techniques can be applied on Edge compute nodes, administrators can share their Edge infrastructures among multiple users, providing the so-called multi-tenancy. Even though multi-tenancy is unavoidable, it raises concerns about security and performance degradation due to resource contention in Edge Computing.…

Speculative Design in Spiraling Time: Methods and Indigenous HCI
James Eschrich, Cole McMullen, Sarah Sterman
https://arxiv.org/abs/2506.10229 https://

Speculative Design in Spiraling Time: Methods and Indigenous HCI
In this position paper, we first discuss the uptake of speculative design as a method for Indigenous HCI. Then, we outline how a key assumption about temporality threatens to undermine the usefulness of speculative design in this context. Finally, we briefly sketch out a possible alternative understanding of speculative design, based on the concept of "spiraling time," which could be better suited for Indigenous HCI.

Tensor perturbations in higher derivative gravity theories in $D$ dimensions
Ercan Kilicarslan
https://arxiv.org/abs/2506.10563 https://

Tensor perturbations in higher derivative gravity theories in $D$ dimensions
We study tensor perturbations of the ghost-free generic non-local gravity theory constructed infinite series of higher derivative terms in $D$ dimensions. The infinite series of higher derivative terms are encoded by form factors, the forms of which can be restricted by requiring that the action remains perturbatively free of ghosts and tachyons around maximally symmetric backgrounds for transverse traceless fluctuations. To demonstrate this, we obtain field equations for AdS plane wave metric …

Federated Learning within Global Energy Budget over Heterogeneous Edge Accelerators
Roopkatha Banerjee, Tejus Chandrashekar, Ananth Eswar, Yogesh Simmhan
https://arxiv.org/abs/2506.10413

Federated Learning within Global Energy Budget over Heterogeneous Edge Accelerators
Federated Learning (FL) enables collaborative model training across distributed clients while preserving data privacy. However, optimizing both energy efficiency and model accuracy remains a challenge, given device and data heterogeneity. Further, sustainable AI through a global energy budget for FL has not been explored. We propose a novel optimization problem for client selection in FL that maximizes the model accuracy within an overall energy limit and reduces training time. We solve this wi…

Intergenerational AI Literacy in Korean Immigrant Families: Interpretive Gatekeeping Meets Convenient Critical Deferment
Jeongone Seo, Ryan Womack, Tawfiq Ammari
https://arxiv.org/abs/2506.10197

Intergenerational AI Literacy in Korean Immigrant Families: Interpretive Gatekeeping Meets Convenient Critical Deferment
As artificial intelligence (AI) becomes deeply integrated into family life, immigrant families must navigate unique intergenerational, linguistic, and cultural challenges. This study examines how Korean immigrant families in the United States negotiate the use of AI tools such as ChatGPT and smart assistants in their homes. Through 20 semi-structured interviews with parents and teens, we identify two key practices that shape their engagement: interpretive gatekeeping, where parents mediate thei…

On the use and interpretation of signal-model indistinguishability measures for gravitational-wave astronomy
Jonathan E. Thompson, Charlie Hoy, Edward Fauchon-Jones, Mark Hannam
https://arxiv.org/abs/2506.10530

On the use and interpretation of signal-model indistinguishability measures for gravitational-wave astronomy
The difference ("mismatch") between two gravitational-wave (GW) signals is often used to estimate the signal-to-noise ratio (SNR) at which they will be distinguishable in a measurement or, alternatively, when the errors in a signal model will lead to biased measurements. It is well known that the standard approach to calculate this "indistinguishability SNR" is too conservative: a model may fail the criterion at a given SNR, but not necessarily incur a biased measurement of any individual param…

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration
Jiaqi Lv, Xufeng He, Yanchen Liu, Xu Dai, Yang Hu, Shouyi Yin
https://arxiv.org/abs/2506.10401

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration
The rapid growth of deep learning has driven exponential increases in model parameters and computational demands. NVIDIA GPUs and their CUDA-based software ecosystem provide robust support for parallel computing, significantly alleviating computational bottlenecks. Meanwhile, due to the cultivation of user programming habits and the high performance of GPUs, the CUDA ecosystem has established a dominant position in the field of parallel software. This dominance requires other hardware platforms…

Mastery Learning Improves Performance on Complex Tasks on PCP Literacy Test
Chandana Srinivas, Elif E. Firat, Robert S. Laramee, Alark Joshi
https://arxiv.org/abs/2506.10164

Mastery Learning Improves Performance on Complex Tasks on PCP Literacy Test
Developing literacy with unfamiliar data visualization techniques such as Parallel Coordinate Plots (PCPs) can be a significant challenge for students. We adopted the Revised Bloom's taxonomy to instruct students on Parallel Coordinate Plots (PCPs) using Mastery Learning in the classroom. To evaluate Mastery Learning's impact, we conducted an intervention in a Data Visualization course to teach students about PCPs using the Revised Bloom's taxonomy with and without Mastery Learning. Based on ou…

Cybernetic Marionette: Channeling Collective Agency Through a Wearable Robot in a Live Dancer-Robot Duet
Anup Sathya, Jiasheng Li, Zeyu Yan, Adriane Fang, Bill Kules, Jonathan David Martin, Huaishu Peng
https://arxiv.org/abs/2506.10079

Cybernetic Marionette: Channeling Collective Agency Through a Wearable Robot in a Live Dancer-Robot Duet
We describe DANCE^2, an interactive dance performance in which audience members channel their collective agency into a dancer-robot duet by voting on the behavior of a wearable robot affixed to the dancer's body. At key moments during the performance, the audience is invited to either continue the choreography or override it, shaping the unfolding interaction through real-time collective input. While post-performance surveys revealed that participants felt their choices meaningfully influenced …

Is Sparse Matrix Reordering Effective for Sparse Matrix-Vector Multiplication?
Omid Asudeh, Sina Mahdipour Saravani, Gerald Sabin, Fabrice Rastello, P Sadayappan
https://arxiv.org/abs/2506.10356

Is Sparse Matrix Reordering Effective for Sparse Matrix-Vector Multiplication?
This work evaluates the impact of sparse matrix reordering on the performance of sparse matrix-vector multiplication across different multicore CPU platforms. Reordering can significantly enhance performance by optimizing the non-zero element patterns to reduce total data movement and improve the load-balancing. We examine how these gains vary over different CPUs for different reordering strategies, focusing on both sequential and parallel execution. We address multiple aspects, including appro…

Constraining quadrupole deformations with relativistic effects
Daniya Utepova, Kuantay Boshkayev, Serzhan Momynov, Anuar Idrissov, Gulzada Baimbetova, Hernando Quevedo, Ainur Urazalina
https://arxiv.org/abs/2506.10437

Constraining quadrupole deformations with relativistic effects
We investigate two general relativistic effects - namely, the Shirokov and Shapiro effects - within the framework of the Zipoy-Voorhees spacetime ($q$-metric), which generalizes the Schwarzschild solution by incorporating a quadrupole moment. By analyzing the geodesic deviation equations, we explore the oscillatory motion of test particles and demonstrate how the source's quadrupole parameter influences the Shirokov effect. Furthermore, we derive an expression for the Shapiro time delay in this…

[2025-06-13 Fri (UTC), 14 new articles found for cs.HC Human-Computer Interaction]
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Resilience through Automated Adaptive Configuration for Distribution and Replication
Scott D. Stoller, Balaji Jayasankar, Yanhong A. Liu
https://arxiv.org/abs/2506.10248

Resilience through Automated Adaptive Configuration for Distribution and Replication
This paper presents a powerful automated framework for making complex systems resilient under failures, by optimized adaptive distribution and replication of interdependent software components across heterogeneous hardware components with widely varying capabilities. A configuration specifies how software is distributed and replicated: which software components to run on each computer, which software components to replicate, which replication protocols to use, etc. We present an algorithm that,…

Variation in the size of the Photon Sphere and Black Hole Shadow in the Modified Gravity
Kanav Ganguly, Ajay Kumar Sharma, Murli Manohar Verma
https://arxiv.org/abs/2506.10414

Variation in the size of the Photon Sphere and Black Hole Shadow in the Modified Gravity
Black hole shadows are a widespread topic in astrophysics. This paper searches for an optical view of the black hole and the relationship between black hole shadow and photon sphere with curvature. We were inspired by the observations of Sagittarius $A^*$ and supermassive black hole M87$*$ through the Event Horizon Telescope. We have found the signature of the modified theory of gravity on the photon sphere and shadow. We considered $f(R)$ modified theory of gravity and new scalar degree of fre…

[2025-06-13 Fri (UTC), 14 new articles found for cs.DC Distributed, Parallel, and Cluster Computing]
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Analytical solutions of CPT-odd Maxwell equations in Schwarzschild spacetime
Hao Wang, Zhi Xiao, Bing Sun
https://arxiv.org/abs/2506.10409 https://

Analytical solutions of CPT-odd Maxwell equations in Schwarzschild spacetime
In this work, we present the CPT-violating (CPTV) Maxwell equations in curved spacetime using the Newman-Penrose (NP) formalism. We obtain a semi-analytical solution to the Maxwell equations in Schwarzschild spacetime under the assumption that the CPT-odd $\left(k_{AF}\right)^μ$ term exhibits spherical symmetry in the Schwarzschild background. Retaining only terms up to linear order in the $\left(k_{AF}\right)^μ$ coefficient, we obtain perturbative solutions by treating the solutions of the L…

On the Earth's tidal perturbations. II. LARES 2 satellite
V. G. Gurzadyan, I. Ciufolini, H. G. Khachatryan, S. Mirzoyan, A. Paolozzi
https://arxiv.org/abs/2506.10310

On the Earth's tidal perturbations. II. LARES 2 satellite
Laser-ranging satellites have proved their efficiency in high precision testing of General Relativity and constraining modified gravity theories proposed to explain the dark sector and the cosmological tensions. The LARES 2 satellite launched in 2022, is currently providing improved information regarding the frame-dragging effect predicted by General Relativity, as well as the geodesy, thus essentially complementing the data of already existing laser-ranging satellites. The proper knowledge of …

Dynamical Horizon Segments and Spacetime Isometries
Abhay Ashtekar, Badri Krishnan
https://arxiv.org/abs/2506.10190 https://arxiv.org…

Dynamical Horizon Segments and Spacetime Isometries
Given a space-time $(\mathscr{M}, g_{ab})$ admitting a dynamical horizon segment (DHS) $\mathscr{H}$, we show that there are stringent constraints on the Killing fields $ξ^a$ that $g_{ab}$ can admit in a neighborhood of $\mathscr{H}$: Generically, $ξ^a$ can only be a rotational Killing field which, furthermore, leaves each marginally trapped 2-sphere cross-section $\mathcal{S}$ of $\mathscr{H}$ invariant. Finally, if $ξ^a$ happens to be hypersurface orthogonal near $\mathscr{H}$, then, not o…

Nethotrons: exploring the possibility of measuring relativistic spin precessions, from Earth's satellites to the Galactic Centre
Lorenzo Iorio
https://arxiv.org/abs/2506.10162

Nethotrons: exploring the possibility of measuring relativistic spin precessions, from Earth's satellites to the Galactic Centre
By ``nethotrons'', from the ancient Greek verb for to ``spin'', it is meant here a natural or artificial rotating object, like a pulsar or an artificial satellite, whose rotational axis is cumulatively displaced by the post-Newtonian static (gravitoelectric) and stationary (gravitomagnetic) components of the gravitational field of some massive body around which it freely moves. Until now, both relativistic effects have been measured only by the dedicated space-based mission Gravity Probe B in t…

Precision predictions of Starobinsky inflation with self-consistent Weyl-squared corrections
Eugenio Bianchi, Mauricio Gamonal
https://arxiv.org/abs/2506.10081

Precision predictions of Starobinsky inflation with self-consistent Weyl-squared corrections
Starobinsky's $R+αR^2$ inflation provides a compelling one-parameter inflationary model that is supported by current cosmological observations. However, at the same order in spacetime derivatives as the $R^2$ term, an effective theory of spacetime geometry must also include the Weyl-squared curvature invariant $W^2$. In this paper, we study the inflationary predictions of the gravitational theory with action of the form $R+αR^2 - βW^2$, where the coupling constant $α$ sets the scale of infl…

Cylindrical gravitational impulse wave
Jean Jules Defo, Victor Kamgang Kuetche
https://arxiv.org/abs/2506.10053 https://arxiv.org/pdf…

Cylindrical gravitational impulse wave
The description of gravitational waves as explosion and implosion waves as predicted by Weber and Wheeler [{\it Rev. Mod. Phys. {\bf 29} 509 (1957)}] in Einstein and Rosen spacetime, has recently been confirmed following observations by the LIGO-VIRGO scientific team [{\it Phys. Rev. Lett. {\bf 116 } 061102 (2016)}] resulting from the collision of two massive black holes. In this dynamics, we explore a new possibility in the construction of gravitational waves like explosion and implosion waves…

3-dimensional charged black holes in $f({Q})$ gravity
G. G. L. Nashed, Emmanuel N. Saridakis
https://arxiv.org/abs/2506.10046 https://

3-dimensional charged black holes in $f({Q})$ gravity
We present new exact charged black hole solutions in (2+1) dimensions within the framework of $f({Q})$ gravity, where ${Q}$ denotes the non-metricity scalar. By considering a cubic $f({Q})$ form we derive classes of charged and uncharged spherically symmetric solutions, and we identify conditions under which these reduce to the well-known Banados-Teitelboim-Zanelli (BTZ) black hole. Notably, our analysis reveals a novel charged solution that is asymptotically Anti-de Sitter (AdS) but cannot be …

[2025-06-13 Fri (UTC), 19 new articles found for gr-qc General Relativity and Quantum Cosmology]
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