Tootfinder

Robust Competitive Ratio for Deterministic Monopoly Pricing
Tim S. G. van Eck, Pieter Kleer, Johan S. H. van Leeuwaarden
https://arxiv.org/abs/2509.06619 https://

Robust Competitive Ratio for Deterministic Monopoly Pricing
We study deterministic monopoly pricing under partial knowledge of the market, where the seller has access only to summary statistics of the valuation distribution, such as the mean, dispersion, and maximum value. Using tools from distributionally robust optimization and max-min analysis, we evaluate pricing strategies based on their competitive ratio (CR). We characterize the worst-case market scenario consistent with the available information and provide a complete solution for minimizing the…

Type-III Seesaw in Non-Holomorphic Modular Symmetry and Leptogenesis
Priya, Labh Singh, B. C. Chauhan, Surender Verma
https://arxiv.org/abs/2508.05047 https://

Type-III Seesaw in Non-Holomorphic Modular Symmetry and Leptogenesis
Recently, Qu and Ding, have proposed a formalism where modular invariance is extended to non-supersymmetric scenario considering Yukawa couplings as non-holomorphic functions of modules field $τ$. Adopting this formalism in this work, we propose a Type-III seesaw model as a unified framework to explain lepton masses and mixing and baryogenesis via leptogenesis. $χ^2$ analysis is performed to fit the neutrino oscillation data from NuFIT~6.0 leading to a normal hierarchical pattern of neutrino …

Analysis of untrusted-node quantum key distribution from a geostationary satellite
Thomas Liege, Perrine Lognone, Matteo Schiavon, Caroline B. Lim, Jean-Marc Conan, Eleni Diamanti, Daniele Dequal
https://arxiv.org/abs/2507.23466

Analysis of untrusted-node quantum key distribution from a geostationary satellite
In pursuit of a global quantum key distribution (QKD) network, a service based on untrusted nodes on geostationary satellites could offer wide coverage, continuous operation, and enhanced security compared to the trusted node alternative. Although this scenario has been studied for entanglement-based protocols, such an approach would require large-area telescopes both on the ground and in space. In this work, we analyze the performance of two QKD protocols well adapted to this scenario, namely …

If You Had to Pitch Your Ideal Software -- Evaluating Large Language Models to Support User Scenario Writing for User Experience Experts and Laypersons
Patrick Stadler, Christopher Lazik, Christopher Katins, Thomas Kosch
https://arxiv.org/abs/2506.23694

If You Had to Pitch Your Ideal Software -- Evaluating Large Language Models to Support User Scenario Writing for User Experience Experts and Laypersons
The process of requirements analysis requires an understanding of the end users of a system. Thus, expert stakeholders, such as User Experience (UX) designers, usually create various descriptions containing information about the users and their possible needs. In our paper, we investigate to what extent UX novices are able to write such descriptions into user scenarios. We conducted a user study with 60 participants consisting of 30 UX experts and 30 novices who were asked to write a user scena…

Foundation Models in Autonomous Driving: A Survey on Scenario Generation and Scenario Analysis
Yuan Gao, Mattia Piccinini, Yuchen Zhang, Dingrui Wang, Korbinian Moller, Roberto Brusnicki, Baha Zarrouki, Alessio Gambi, Jan Frederik Totz, Kai Storms, Steven Peters, Andrea Stocco, Bassam Alrifaee, Marco Pavone, Johannes Betz
https://

Foundation Models in Autonomous Driving: A Survey on Scenario Generation and Scenario Analysis
For autonomous vehicles, safe navigation in complex environments depends on handling a broad range of diverse and rare driving scenarios. Simulation- and scenario-based testing have emerged as key approaches to development and validation of autonomous driving systems. Traditional scenario generation relies on rule-based systems, knowledge-driven models, and data-driven synthesis, often producing limited diversity and unrealistic safety-critical cases. With the emergence of foundation models, wh…

A Comparative Study of Optimal Control and Neural Networks in Asteroid Rendezvous Mission Analysis
Zhong Zhang, Niccol\`o Michelotti, Gon\c{c}alo Oliveira Pinho, Francesco Topputo
https://arxiv.org/abs/2508.02920

A Comparative Study of Optimal Control and Neural Networks in Asteroid Rendezvous Mission Analysis
This paper presents a comparative study of the applicability and accuracy of optimal control methods and neural network-based estimators in the context of porkchop plots for preliminary asteroid rendezvous mission design. The scenario considered involves a deep-space CubeSat equipped with a low-thrust engine, departing from Earth and rendezvousing with a near-Earth asteroid within a three-year launch window. A low-thrust trajectory optimization model is formulated, incorporating variable specif…

Multi-agent Auditory Scene Analysis
Caleb Rascon, Luis Gato-Diaz, Eduardo Garc\'ia-Alarc\'on
https://arxiv.org/abs/2507.02755 https://

Multi-agent Auditory Scene Analysis
Auditory scene analysis (ASA) aims to retrieve information from the acoustic environment, by carrying out three main tasks: sound source location, separation, and classification. These tasks are traditionally executed with a linear data flow, where the sound sources are first located; then, using their location, each source is separated into its own audio stream; from each of which, information is extracted that is relevant to the application scenario (audio event detection, speaker identificat…

Do Students Rely on AI? Analysis of Student-ChatGPT Conversations from a Field Study
Jiayu Zheng, Lingxin Hao, Kelun Lu, Ashi Garg, Mike Reese, Melo-Jean Yap, I-Jeng Wang, Xingyun Wu, Wenrui Huang, Jenna Hoffman, Ariane Kelly, My Le, Ryan Zhang, Yanyu Lin, Muhammad Faayez, Anqi Liu
https://arxiv.org/abs/2508.20244

Do Students Rely on AI? Analysis of Student-ChatGPT Conversations from a Field Study
This study explores how college students interact with generative AI (ChatGPT-4) during educational quizzes, focusing on reliance and predictors of AI adoption. Conducted at the early stages of ChatGPT implementation, when students had limited familiarity with the tool, this field study analyzed 315 student-AI conversations during a brief, quiz-based scenario across various STEM courses. A novel four-stage reliance taxonomy was introduced to capture students' reliance patterns, distinguishing A…

A possible two-fold scenario for the disc-corona of the luminous AGN 1H 0419--577: a high-density disc or a warm corona
Delphine Porquet, James N. Reeves, Valentina Braito
https://arxiv.org/abs/2506.23920

A possible two-fold scenario for the disc-corona of the luminous AGN 1H 0419--577: a high-density disc or a warm corona
[abridged] 1H 0419-577 is a highly-accreting, luminous BLS1 AGN. This study aims to characterise its disc-corona system using, for the first time, simultaneous XMM-Newton and NuSTAR observations, performed in May and November 2018. We conducted high-resolution grating spectroscopy to identify potential soft X-ray absorption and emission features. To measure the hot corona temperatures from the spectral analysis above 3 keV, we also included data from a previous NuSTAR observation from June 2015…

Secure Integrated Sensing and Communication Networks: Stochastic Performance Analysis
Marziyeh Soltani, Mahtab Mirmohseni, Rahim Tafazolli
https://arxiv.org/abs/2507.23234 https…

Secure Integrated Sensing and Communication Networks: Stochastic Performance Analysis
This paper analyzes the stochastic security performance of a multiple-input multiple-output (MIMO) integrated sensing and communication (ISAC) system in a downlink scenario. A base station (BS) transmits a multi-functional signal to simultaneously communicate with a user, sense a target's angular location, and counteract eavesdropping threats. The attack model considers a passive single-antenna communication eavesdropper intercepting communication data, as well as a multi-antenna sensing eavesd…

Families of Transfers from circular low Earth orbit to Distant Prograde Orbit around the Moon
Shuyue Fu, Di Wu, Yihan Peng, Peng Shi, Shengping Gong
https://arxiv.org/abs/2508.01769

Families of Transfers from circular low Earth orbit to Distant Prograde Orbit around the Moon
Distant prograde orbits around the Moon exhibit remarkable potential for practical applications such as cislunar surveillance activities and low-energy transfers due to their instability. Previous works on transfers from circular low Earth orbit to distant prograde orbits mainly focused on construction methods based on dynamical structures, lacking a comprehensive analysis of the solution space of this transfer scenario. This paper investigates the solution space and identifies families of tran…

Renormalization group flows in area-metric gravity
Johanna Borissova, Bianca Dittrich, Astrid Eichhorn, Marc Schiffer
https://arxiv.org/abs/2507.02034 http…

Renormalization group flows in area-metric gravity
We put forward the first analysis of renormalization group flows in an area-metric theory, motivated by spin-foam quantum gravity. Area-metric gravity contains the well-known length-metric degrees of freedom of standard gravity as well as additional shape-mismatching degrees of freedom. To be phenomenologically viable, the shape-mismatching degrees of freedom have to decouple under the renormalization group flow towards lower scales. We test this scenario by calculating the renormalization grou…

Interference Analysis and Successive Interference Cancellation for Multistatic OFDM-based ISAC Systems
Taewon Jeong, Lucas Giroto, Umut Utku Erdem, Christian Karle, Jiyeon Choi, Thomas Zwick, Benjamin Nuss
https://arxiv.org/abs/2507.20942

Interference Analysis and Successive Interference Cancellation for Multistatic OFDM-based ISAC Systems
Multistatic integrated sensing and communications (ISAC) systems, which use distributed transmitters and receivers, offer enhanced spatial coverage and sensing accuracy compared to stand-alone ISAC configurations. However, these systems face challenges due to interference between co-existing ISAC nodes, especially during simultaneous operation. In this paper, we analyze the impact of this mutual interference arising from the co-existence in a multistatic ISAC scenario, where a mono- and a bista…

Your Token Becomes Worthless: Unveiling Rug Pull Schemes in Crypto Token via Code-and-Transaction Fusion Analysis
Hao Wu, Haijun Wang, Shangwang Li, Yin Wu, Ming Fan, Wuxia Jin, Yitao Zhao, Ting Liu
https://arxiv.org/abs/2506.18398

Your Token Becomes Worthless: Unveiling Rug Pull Schemes in Crypto Token via Code-and-Transaction Fusion Analysis
Rug pull scams have emerged as a persistent threat to cryptocurrency, causing significant financial losses. A typical scenario involves scammers deploying honeypot contracts to attract investments, restricting token sales, and draining the funds, which leaves investors with worthless tokens. Current methods either rely on predefined patterns to detect code risks or utilize statistical transaction data to train detection models. However, real-world Rug Pull schemes often involve a complex interp…

M3HG: Multimodal, Multi-scale, and Multi-type Node Heterogeneous Graph for Emotion Cause Triplet Extraction in Conversations
Qiao Liang, Ying Shen, Tiantian Chen, Lin Zhang
https://arxiv.org/abs/2508.18740

M3HG: Multimodal, Multi-scale, and Multi-type Node Heterogeneous Graph for Emotion Cause Triplet Extraction in Conversations
Emotion Cause Triplet Extraction in Multimodal Conversations (MECTEC) has recently gained significant attention in social media analysis, aiming to extract emotion utterances, cause utterances, and emotion categories simultaneously. However, the scarcity of related datasets, with only one published dataset featuring highly uniform dialogue scenarios, hinders model development in this field. To address this, we introduce MECAD, the first multimodal, multi-scenario MECTEC dataset, comprising 989 …

Cosmography with DESI DR2 and SN data
Gabriel Rodrigues, Rayff de Souza, Jailson Alcaniz
https://arxiv.org/abs/2506.22373 https://arx…

Cosmography with DESI DR2 and SN data
In this paper, we present a kinematic analysis of the Universe's expansion history using cosmography, with a particular emphasis on the jerk parameter $j_0$, which is equal to one in the standard $Λ$CDM scenario. We use distance measurements from DESI DR2, both independently and in combination with current Type Ia supernova (SN) samples, to constrain the cosmographic parameters up to the fourth order without relying on a specific cosmological model. Our results show that for the DESI DR2 data …

Timelike entanglement and central charge for quantum BTZ black holes
Dibakar Roychowdhury
https://arxiv.org/abs/2507.19813 https://arxiv.org/pdf/2507.19813…

Timelike entanglement and central charge for quantum BTZ black holes
We compute holographic timelike entanglement entropy for quantum BTZ black holes in a Karch-Randall braneworld scenario. These black holes are exact solutions of massive 3d gravity on the brane and are conjectured to be dual to thermal states in 2d defect CFTs, living at the interface of the brane and the boundary of the bulk $AdS_4$. Our analysis reveals an interesting relation between the tEE and the central charge pertaining to the dual CFT, which receives nontrivial corrections due to quant…

Techno-economic analysis of decarbonized backup power systems using scenario-based stochastic optimization
Jonas Schweiger, Ruaridh Macdonald
https://arxiv.org/abs/2507.06736

Techno-economic analysis of decarbonized backup power systems using scenario-based stochastic optimization
In the context of growing concerns about power disruptions, grid reliability and the need for decarbonization, this study evaluates a broad range of clean backup power systems (BPSs) to replace traditional emergency diesel generators. A scenario-based stochastic optimization framework using actual load profiles and outage probabilities is proposed to assess the most promising options from a pool of 27 technologies. This framework allows a comparison of cost-effectiveness and environmental impac…

EarthLink: Interpreting Climate Signals with Self-Evolving AI Agents
Zijie Guo, Jiong Wang, Xiaoyu Yue, Wangxu Wei, Zhe Jiang, Wanghan Xu, Ben Fei, Wenlong Zhang, Xinyu Gu, Lijing Cheng, Jing-Jia Luo, Chao Li, Yaqiang Wang, Tao Chen, Wanli Ouyang, Fenghua Ling, Lei Bai
https://arxiv.org/abs/2507.17311

EarthLink: Interpreting Climate Signals with Self-Evolving AI Agents
Modern Earth science is at an inflection point. The vast, fragmented, and complex nature of Earth system data, coupled with increasingly sophisticated analytical demands, creates a significant bottleneck for rapid scientific discovery. Here we introduce EarthLink, the first AI agent designed as an interactive copilot for Earth scientists. It automates the end-to-end research workflow, from planning and code generation to multi-scenario analysis. Unlike static diagnostic tools, EarthLink can lea…

Density Prediction of Income Distribution Based on Mixed Frequency Data
Yinzhi Wang, Yingqiu Zhu, Ben-Chang Shia, Lei Qin
https://arxiv.org/abs/2507.16150 …

Density Prediction of Income Distribution Based on Mixed Frequency Data
Modeling large dependent datasets in modern time series analysis is a crucial research area. One effective approach to handle such datasets is to transform the observations into density functions and apply statistical methods for further analysis. Income distribution forecasting, a common application scenario, benefits from predicting density functions as it accounts for uncertainty around point estimates, leading to more informed policy formulation. However, predictive modeling becomes challen…

Exploiting Movable Elements of Intelligent Reflecting Surface for Enhancement of Integrated Sensing and Communication
Xingyu Peng, Qin Tao, Yong Liang Guan, Xiaoming Chen
https://arxiv.org/abs/2507.23296

Exploiting Movable Elements of Intelligent Reflecting Surface for Enhancement of Integrated Sensing and Communication
In this paper, we propose to exploit movable elements of intelligent reflecting surface (IRS) to enhance the overall performance of integrated sensing and communication (ISAC) systems. Firstly, focusing on a single-user scenario, we reveal the function of movable elements by performance analysis, and then design a joint beamforming and element position optimization scheme. Further, we extend it to a general multi-user scenario, and also propose an element position optimization scheme according …

VisFinEval: A Scenario-Driven Chinese Multimodal Benchmark for Holistic Financial Understanding
Zhaowei Liu, Xin Guo, Haotian Xia, Lingfeng Zeng, Fangqi Lou, Jinyi Niu, Mengping Li, Qi Qi, Jiahuan Li, Wei Zhang, Yinglong Wang, Weige Cai, Weining Shen, Liwen Zhang
https://arxiv.org/abs/2508.09641

VisFinEval: A Scenario-Driven Chinese Multimodal Benchmark for Holistic Financial Understanding
Multimodal large language models (MLLMs) hold great promise for automating complex financial analysis. To comprehensively evaluate their capabilities, we introduce VisFinEval, the first large-scale Chinese benchmark that spans the full front-middle-back office lifecycle of financial tasks. VisFinEval comprises 15,848 annotated question-answer pairs drawn from eight common financial image modalities (e.g., K-line charts, financial statements, official seals), organized into three hierarchical sc…

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems
Erwin de Gelder, Maren Buermann, Olaf Op den Camp
https://arxiv.org/abs/2507.22429

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems
The development of safety validation methods is essential for the safe deployment and operation of Automated Driving Systems (ADSs). One of the goals of safety validation is to prospectively evaluate the risk of an ADS dealing with real-world traffic. Scenario-based assessment is a widely-used approach, where test cases are derived from real-world driving data. To allow for a quantitative analysis of the system performance, the exposure of the scenarios must be accurately estimated. The exposur…

Cooperative Face Liveness Detection from Optical Flow
Artem Sokolov, Mikhail Nikitin, Anton Konushin
https://arxiv.org/abs/2508.10786 https://arxiv.org/pdf…

Cooperative Face Liveness Detection from Optical Flow
In this work, we proposed a novel cooperative video-based face liveness detection method based on a new user interaction scenario where participants are instructed to slowly move their frontal-oriented face closer to the camera. This controlled approaching face protocol, combined with optical flow analysis, represents the core innovation of our approach. By designing a system where users follow this specific movement pattern, we enable robust extraction of facial volume information through neur…

Optimizing $pp\to A\to Z^{*}h\to \ell^ \ell^- b\bar b$ Searches at the LHC in the 2HDM Type-I with Inverted Hierarchy
S. Alanazi, S. Moretti, A. G. Akeroyd
https://arxiv.org/abs/2508.21385

Optimizing $pp\to A\to Z^{*}h\to \ell^+\ell^- b\bar b$ Searches at the LHC in the 2HDM Type-I with Inverted Hierarchy
In this study, we investigate the Large Hadron Collider (LHC) search for the signal process $pp\to A \to Z^{*}h \to \ell^{+} \ell^{-} b \bar{b}$ ($\ell=e,μ$) within the framework of the 2-Higgs-Doublet Model (2HDM) Type-I, considering an Inverted Hierarchy (IH) scenario wherein the Standard Model (SM)-like Higgs boson $H$ is heavier than $h$ (i.e., $m_h < m_H=125$ GeV). We reproduce the dominant background distributions from a CMS analysis of $pp\to H \to Z A \to \ell^{+} \ell^{-} b \bar{b}$ (…

Improved lower bound for the worst case Pretty Good Measurement
Austin Pechan, Sergio Escobar
https://arxiv.org/abs/2508.19085 https://arxiv.org/pdf/2508.1…

Improved lower bound for the worst case Pretty Good Measurement
We derive a new lower bound on the success probability of the Pretty Good Measurement (PGM) for worst-case quantum state discrimination among $m$ pure states. Our bound is strictly tighter than the previously known Gram-matrix-based bound for $m\geq 4$. The proof adapts techniques from Barnum and Knill's analysis of the average-case PGM, applied here to the worst-case scenario. By comparing the PGM to the sequential measurement algorithm, we obtain a guarantee showing that, in the low-fidelity …

How Holographic is the Dark Energy? A Spline Nodal reconstruction approach
Miguel A. Zapata, Gabriela Garcia-Arroyo, Shahnawaz A. Adil, J. Alberto Vazquez
https://arxiv.org/abs/2507.22292

How Holographic is the Dark Energy? A Spline Nodal reconstruction approach
In this work, we explore the generalized holographic dark energy (HDE) scenario. We relate the HDE density to the future-horizon scale via a function $f(a)$, which we reconstruct via spline-based nodal interpolation. We perform a Bayesian analysis to assess model's consistency with current observations, including baryon acoustic oscillations (BAO) from the Dark Energy Spectroscopic Instrument (DESI) DR1, Type Ia supernovae (SNe Ia) from the Union3 and Pantheon+ compilations, and local measureme…

Impact of model uncertainty on SPARC operating scenario predictions with empirical modeling
A. Saltzman, P. Rodriguez-Fernandez, T. Body, A. Ho, N. T. Howard
https://arxiv.org/abs/2506.09879

Impact of model uncertainty on SPARC operating scenario predictions with empirical modeling
Understanding and accounting for uncertainty helps to ensure next-step tokamaks such as SPARC will robustly achieve their goals. While traditional Plasma OPerating CONtour (POPCON) analyses guide design, they often overlook the significant impact of uncertainties in scaling laws, plasma profiles, and impurity concentrations on performance predictions. This work confronts these challenges by introducing statistical POPCONs, which leverage Monte Carlo analysis to quantify the sensitivity of SPARC…

Periodic equatorial orbits in a black bounce scenario
Anderson Bragado, Gonzalo J. Olmo
https://arxiv.org/abs/2506.15600 https://arxi…

Periodic equatorial orbits in a black bounce scenario
We study equatorial closed orbits in a popular black bounce model to see if the internal structure of these objects could lead to peculiar observable features. Paralleling the analysis of the Schwarzschild and Kerr metrics, we show that in the black bounce case each orbit can also be associated with a triplet of integers which can then be used to construct a rational number characterizing each periodic orbit. When the black bounce solution represents a traversable wormhole, we show that the pre…

TableCopilot: A Table Assistant Empowered by Natural Language Conditional Table Discovery
Lingxi Cui, Guanyu Jiang, Huan Li, Ke Chen, Lidan Shou, Gang Chen
https://arxiv.org/abs/2507.08283

TableCopilot: A Table Assistant Empowered by Natural Language Conditional Table Discovery
The rise of LLM has enabled natural language-based table assistants, but existing systems assume users already have a well-formed table, neglecting the challenge of table discovery in large-scale table pools. To address this, we introduce TableCopilot, an LLM-powered assistant for interactive, precise, and personalized table discovery and analysis. We define a novel scenario, nlcTD, where users provide both a natural language condition and a query table, enabling intuitive and flexible table di…

Local graph estimation: Interpretable network discovery for complex data
Omar Melikechi, David B. Dunson, Noureddine Melikechi, Jeffrey W. Miller
https://arxiv.org/abs/2507.17172

Local graph estimation: Interpretable network discovery for complex data
Large, complex datasets often include a small set of variables of primary interest, such as clinical outcomes or known biomarkers, whose relation to the broader system is the main focus of analysis. In these situations, exhaustively estimating the entire network may obscure insights into the scientific question at hand. To address this common scenario, we introduce local graph estimation, a statistical framework that focuses on inferring substructures around target variables rather than recover…

Indirect stabilization of nonlinear coupled wave equations in the presence of time delay or indefinite damping
Alhabib Moumni, Cristina Pignotti, Jawad Salhi, Mouhcine Tilioua
https://arxiv.org/abs/2507.07311

Indirect stabilization of nonlinear coupled wave equations in the presence of time delay or indefinite damping
This paper explores the exponential stability of two nonlinear wave equations coupled through their velocities. The analysis is divided into two main cases. First, we consider a system where one equation is damped, while the other experiences a discrete time delay. By reformulating the problem in an abstract framework, we use semigroup theory and energy methods to establish well-posedness and derive conditions that guarantee exponential energy decay. In the second case, we examine a scenario wh…

A workflow for generating synthetic LiDAR datasets in simulation environments
Abhishek Phadke, Shakib Mahmud Dipto, Pratip Rana
https://arxiv.org/abs/2506.17378

A workflow for generating synthetic LiDAR datasets in simulation environments
This paper presents a simulation workflow for generating synthetic LiDAR datasets to support autonomous vehicle perception, robotics research, and sensor security analysis. Leveraging the CoppeliaSim simulation environment and its Python API, we integrate time-of-flight LiDAR, image sensors, and two dimensional scanners onto a simulated vehicle platform operating within an urban scenario. The workflow automates data capture, storage, and annotation across multiple formats (PCD, PLY, CSV), produ…

Extended datasamples under the lens of Brane World Theory
Kyra Jacobo, Dorian Araya
https://arxiv.org/abs/2506.15002 https://arxiv.or…

Extended datasamples under the lens of Brane World Theory
This work revises the Brane World Theory known as Randall-Sundrum with the modification of an exponential, redshift-dependent brane tension. This model is studied in a scenario assuming no dark energy, with the aim of determining whether it can reproduce the universe's acceleration on its own, without the addition of a dark energy fluid. Bayesian statistical analysis is performed in order to constrain the free parameters of each scenario using SLS, SNIa, OHD, and BAO data samples, the last two …

Propagation features of Lorentz-violating electrodynamics
E. Goulart, J. E. Ottoni, J. C. C. Felipe
https://arxiv.org/abs/2507.08263 https://

Propagation features of Lorentz-violating electrodynamics
This paper explores some propagation features of electrodynamics in a Lorentz-violating scenario, focusing on a specific CPT-even term within the photon sector of the Standard Model Extension (SME). The study derives a covariant dispersion relation for light propagation in the presence of a Lorentz-violating symmetric tensor field \(C_{ab}(x)\), which reveals a modified light cone structure described by a quartic polynomial. The analysis includes a simplified model where the tensor field assume…

PAPR of DFT-s-OTFS with Pulse Shaping
Jialiang Zhu, Sanoopkumar P. S., Arman Farhang
https://arxiv.org/abs/2507.12210 https://arxiv.o…

PAPR of DFT-s-OTFS with Pulse Shaping
Orthogonal Time Frequency Space (OTFS) suffers from high peak-to-average power ratio (PAPR) when the number of Doppler bins is large. To address this issue, a discrete Fourier transform spread OTFS (DFT-s-OTFS) scheme is employed by applying DFT spreading across the Doppler dimension. This paper presents a thorough PAPR analysis of DFT-s-OTFS in the uplink scenario using different pulse shaping filters and resource allocation strategies. Specifically, we derive a PAPR upper bound of DFT-s-OTFS …

Statistical post-processing of operational dual-resolution wind-speed ensemble forecasts
S\'andor Baran, M\'aria Lakatos
https://arxiv.org/abs/2506.15578

Statistical post-processing of operational dual-resolution wind-speed ensemble forecasts
Weather forecasting presents several challenges, including the chaotic nature of the atmosphere and the high computational demands of numerical weather prediction models. To achieve the most accurate predictions, the ideal scenario involves the lowest possible horizontal resolution and the largest ensemble size. This study provides a detailed comparative analysis of the forecast skill of the raw and post-processed medium- and extended-range wind-speed ensemble forecasts of the European Centre f…

Spirals, vortices, and helicity entanglements in dynamical Sauter-Schwinger pair creation
M. M. Majczak, K. Krajewska, A. Bechler, J. Z. Kami\'nski
https://arxiv.org/abs/2507.08720

Spirals, vortices, and helicity entanglements in dynamical Sauter-Schwinger pair creation
We study helicity correlations of electron-positron pairs created by a homogeneous time-dependent electric field in the Sauter-Schwinger scenario. Our analysis is based on solving the Dirac equation with the Feynman or anti-Feynman boundary conditions, which is equivalent to the scattering matrix approach widely used in high energy physics. Most importantly, both these methods allow to fully account for the helicity (or, more generally, spin) correlations of created particles. The influence of …

Exploring non-cold dark matter in a scenario of dynamical dark energy with DESI DR2 data
Tian-Nuo Li, Peng-Ju Wu, Guo-Hong Du, Yan-Hong Yao, Jing-Fei Zhang, Xin Zhang
https://arxiv.org/abs/2507.07798

Exploring non-cold dark matter in a scenario of dynamical dark energy with DESI DR2 data
Recent observations of DESI hint that dark matter (DM) may not be cold but have a non-zero equation of state (EoS) parameter, and that dark energy (DE) may not be a cosmological constant. In this work, we explore the possibility of a non-zero DM EoS parameter within the framework of dynamical DE. We perform analysis by using the latest baryon acoustic oscillation (BAO) data from DESI DR2, the cosmic microwave background (CMB) data from Planck, and the type Ia supernova (SN) data from DESY5 and …

Environment Reconstruction in Terahertz Monostatic Sensing: Joint Millimeter-level Geometry Mapping and Material Identification
Zitong Fang, Yejian Lyu, Ziming Yu, Chong Han
https://arxiv.org/abs/2508.10372

Environment Reconstruction in Terahertz Monostatic Sensing: Joint Millimeter-level Geometry Mapping and Material Identification
Terahertz (THz) integrated sensing and communication (ISAC) offers high-speed communication alongside precise environmental sensing. This paper presents a computationally efficient framework for THz-based environment reconstruction by integrating connected component analysis (CCA)-assisted multipath component (MPC) estimation with a sliding-window refinement strategy. To start with, a monostatic sensing experiment is conducted in an indoor scenario using a vector network analyzer (VNA)-based so…

Interaction of polytropic dark energy in cosmological model: Constraints from observational data
Elangbam Chingkheinganba Meetei, S. Surendra Singh
https://arxiv.org/abs/2508.15187

Interaction of polytropic dark energy in cosmological model: Constraints from observational data
We investigate an interacting polytropic dark energy (PDE) model characterised by the equation of state $p_{d} = αρ_{d}^{\,1+\frac{1}β}$, where the interaction between dark energy and pressureless matter is modelled via a linear coupling term $Q = 3ηHρ_{d}$. The background dynamics are formulated by deriving the Hubble parameter in the interacting scenario, and the model parameters are constrained through a Markov Chain Monte Carlo (MCMC) analysis using three joint observational data sets:…