Tootfinder

A website developed for the UK Home Office's 2022 "flop" anti-encryption campaign has seemingly been hijacked to push a payday loan scheme.
https://www.theregister.com/2025/06/25/home_office_antiencryption_campaign_website/?m…

UK govt dept website that campaigns against encryption hijacked to advertise ... payday loans
: Company at center of findings blamed SEO on outsourcer

A Two-armed Bandit Framework for A/B Testing
Jinjuan Wang, Qianglin Wen, Yu Zhang, Xiaodong Yan, Chengchun Shi
https://arxiv.org/abs/2507.18118 https://arx…

A Two-armed Bandit Framework for A/B Testing
A/B testing is widely used in modern technology companies for policy evaluation and product deployment, with the goal of comparing the outcomes under a newly-developed policy against a standard control. Various causal inference and reinforcement learning methods developed in the literature are applicable to A/B testing. This paper introduces a two-armed bandit framework designed to improve the power of existing approaches. The proposed procedure consists of three main steps: (i) employing doubl…

»Humans can be tracked with unique 'fingerprint' based on how their bodies block Wi-Fi signals:
Wi-Fi spy with my little eye that same guy I saw at another hotspot. Researchers in Italy have developed a way to create a biometric identifier for people based on the way the human body interferes with Wi-Fi signal propagation.«
If this is not also used for manipulating advertising of all kinds of interests?
🛜

Humans can be tracked with unique 'fingerprint' based on how their bodies block Wi-Fi signals
: Wi-Fi spy with my little eye that same guy I saw at another hotspot

Distinguishing Predictive and Generative AI in Regulation
Jennifer Wang, Andrew Selbst, Solon Barocas, Suresh Venkatasubramanian
https://arxiv.org/abs/2506.17347

Distinguishing Predictive and Generative AI in Regulation
Over the past decade, policymakers have developed a set of regulatory tools to ensure AI development aligns with key societal goals. Many of these tools were initially developed in response to concerns with predictive AI and therefore encode certain assumptions about the nature of AI systems and the utility of certain regulatory approaches. With the advent of generative AI, however, some of these assumptions no longer hold, even as policymakers attempt to maintain a single regulatory target tha…

Conceptual Modelling for Life Sciences Based on Systemist Foundations
R. Lukyanenko, O. Pastor, V. C. Storey
https://arxiv.org/abs/2506.18742 https://

Conceptual Modelling for Life Sciences Based on Systemist Foundations
All aspects of our society, including the life sciences, need a mechanism for people working within them to represent the concepts they employ to carry out their research. For the information systems being designed and developed to support researchers and scientists in conducting their work, conceptual models of the relevant domains are usually designed as both blueprints for a system being developed and as a means of communication between the designer and developer. Most conceptual modelling c…

What are you standing on? Check out the #geology under your feet using the Rockd app on your phone!
Developed by the University of #Wisconsin Macrostrat lab.
Funding from NSF (US National Science Foundation) and U Wisconsin Dept of Geoscience.

Computer Vision for Real-Time Monkeypox Diagnosis on Embedded Systems
Jacob M. Delgado-L\'opez, Ricardo A. Morell-Rodriguez, Sebasti\'an O. Espinosa-Del Rosario, Wilfredo E. Lugo-Beauchamp
https://arxiv.org/abs/2507.17123

Computer Vision for Real-Time Monkeypox Diagnosis on Embedded Systems
The rapid diagnosis of infectious diseases, such as monkeypox, is crucial for effective containment and treatment, particularly in resource-constrained environments. This study presents an AI-driven diagnostic tool developed for deployment on the NVIDIA Jetson Orin Nano, leveraging the pre-trained MobileNetV2 architecture for binary classification. The model was trained on the open-source Monkeypox Skin Lesion Dataset, achieving a 93.07% F1-Score, which reflects a well-balanced performance in p…

Orbital Collision: An Indigenously Developed Web-based Space Situational Awareness Platform
Partha Chowdhury, Harsha M, Ayush Gupta, Sanat K Biswas
https://arxiv.org/abs/2506.16892

Orbital Collision: An Indigenously Developed Web-based Space Situational Awareness Platform
This work presents an indigenous web based platform Orbital Collision (OrCo), created by the Space Systems Laboratory at IIIT Delhi, to enhance Space Situational Awareness (SSA) by predicting collision probabilities of space objects using Two Line Elements (TLE) data. The work highlights the growing challenges of congestion in the Earth's orbital environment, mainly due to space debris and defunct satellites, which increase collision risks. It employs several methods for propagating orbital unc…

ARCH-COMP25 Category Report: Stochastic Models
Alessandro Abate, Omid Akbarzadeh, Henk A. P. Blom, Sofie Haesaert, Sina Hassani, Abolfazl Lavaei, Frederik Baymler Mathiesen, Rahul Misra, Amy Nejati, Mathis Niehage, Fie {\O}rum, Anne Remke, Behrad Samari, Ruohan Wang, Rafal Wisniewski, Ben Wooding, Mahdieh Zaker
https://arxiv.org…

ARCH-COMP25 Category Report: Stochastic Models
This report is concerned with a friendly competition for formal verification and policy synthesis of stochastic models. The main goal of the report is to introduce new benchmarks and their properties within this category and recommend next steps toward next year's edition of the competition. In particular, this report introduces three recently developed software tools, a new water distribution network benchmark, and a collection of simplified benchmarks intended to facilitate further comparison…

Enhancing Security in LLM Applications: A Performance Evaluation of Early Detection Systems
Valerii Gakh, Hayretdin Bahsi
https://arxiv.org/abs/2506.19109 …

Enhancing Security in LLM Applications: A Performance Evaluation of Early Detection Systems
Prompt injection threatens novel applications that emerge from adapting LLMs for various user tasks. The newly developed LLM-based software applications become more ubiquitous and diverse. However, the threat of prompt injection attacks undermines the security of these systems as the mitigation and defenses against them, proposed so far, are insufficient. We investigated the capabilities of early prompt injection detection systems, focusing specifically on the detection performance of technique…

An Empirical Study of GenAI Adoption in Open-Source Game Development: Tools, Tasks, and Developer Challenges
Xiang Echo Chen, Wenhan Zhu, Guoshuai Albert Shi, Michael W. Godfrey
https://arxiv.org/abs/2507.18029

An Empirical Study of GenAI Adoption in Open-Source Game Development: Tools, Tasks, and Developer Challenges
The growing capabilities of generative AI (GenAI) have begun to reshape how games are designed and developed, offering new tools for content creation, gameplay simulation, and design ideation. While prior research has explored traditional uses of AI in games, such as controlling agents or generating procedural content. There is limited empirical understanding of how GenAI is adopted by developers in real-world contexts, especially within the open-source community. This study aims to explore how…

Geometric Measures of Complexity for Open and Closed Quantum Systems
Alberto Acevedo, Antonio Falco
https://arxiv.org/abs/2507.18440 https://arxiv.org/pdf/…

Geometric Measures of Complexity for Open and Closed Quantum Systems
The unitary dynamics of quantum systems can be modeled as a trajectory on a Riemannian manifold. This theoretical framework naturally yields a purely geometric interpretation of computational complexity for quantum algorithms, a notion originally developed by Michael Nielsen (Circa, 2007). However, for nonunitary dynamics, it is unclear how one can recover a completely geometric characterization of Nielsen-like geometric complexity. The main obstacle to overcome is that nonunitary dynamics cann…

A look at Decart, which has developed video-to-video AI model Mirage that manipulates live video in real time and can potentially shake up livestreaming (Will Knight/Wired)
https://www.wired.com/story/decart-artificial-intelligence-model-live-stream/

This AI Warps Live Video in Real Time
A startup called Decart has developed an AI model that can transform live footage. The results are mind-bending—and poised to take over streaming.

The spaces of rational curves on del Pezzo surfaces via conic bundles
Sho Tanimoto
https://arxiv.org/abs/2506.18239 https://arxiv.org…

The spaces of rational curves on del Pezzo surfaces via conic bundles
Using the homological sieve method developed by Das--Lehmann--Tosteson and the author, we prove Peyre's all height approach to Manin's conjecture for split quintic del Pezzo surfaces defined over $\mathbb F_q(t)$ assuming $q$ is sufficiently large. We also establish lower bounds of correct magnitude for the counting function of rational curves on split low degree del Pezzo surfaces defined over $\mathbb F_q$ assuming $q$ is large.

Differential operators on Hermitian modular forms on $\mathrm{u}(n, n)$
Nobuki Takeda
https://arxiv.org/abs/2506.18236 https://arxiv.…

Differential operators on Hermitian modular forms on $\mathrm{u}(n, n)$
We construct explicit differential operators on hermitian modular forms, extending methods developed for Siegel modular forms. These differential operators are closely related to the two-variable spherical pluriharmonic polynomials. We construct explicit bases for the space of such polynomials and use them to build concrete operators. As an application, we derive an exact pullback formula for hermitian Eisenstein series.

Bondi Takes Revenge on Family of Man Who Created ICEBlock App
https://www.yahoo.com/news/bondi-takes-revenge-family-man-180841002.html

Bondi Takes Revenge on Family of Man Who Created Anti-ICE App
Pam Bondi’s Justice Department has fired the wife of the man who developed a controversial “anti-ICE” warning system after far-right influencer Laura Loomer ...

Quantitative Benchmarking of Anomaly Detection Methods in Digital Pathology
Can Cui, Xindong Zheng, Ruining Deng, Quan Liu, Tianyuan Yao, Keith T Wilson, Lori A Coburn, Bennett A Landman, Haichun Yang, Yaohong Wang, Yuankai Huo
https://arxiv.org/abs/2506.19234

Quantitative Benchmarking of Anomaly Detection Methods in Digital Pathology
Anomaly detection has been widely studied in the context of industrial defect inspection, with numerous methods developed to tackle a range of challenges. In digital pathology, anomaly detection holds significant potential for applications such as rare disease identification, artifact detection, and biomarker discovery. However, the unique characteristics of pathology images, such as their large size, multi-scale structures, stain variability, and repetitive patterns, introduce new challenges t…

General theory of perturbation of infinite resistor networks
J\'ozsef Cserti, Gyula D\'avid
https://arxiv.org/abs/2506.18654 https://

General theory of perturbation of infinite resistor networks
The effective resistance between any two nodes in a perturbed resistor network is determined by removing multiple bonds from an infinite resistor lattice. We have developed an efficient method for calculating the Green operator of the Laplacian for such perturbed networks, which is directly related to the two-point resistance. Unlike the recursive techniques that remove bonds one at a time, our approach handles all bond modifications simultaneously. To demonstrate the versatility of our m…

New tools in hierarchical hyperbolicity: A survey
Alessandro Sisto
https://arxiv.org/abs/2507.17546 https://arxiv.org/pdf/2507.17546

New tools in hierarchical hyperbolicity: A survey
The aim of this short survey is to advertise various tools that have been developed to study hierarchically hyperbolic spaces (HHSs) in recent years, with particular emphasis on those that require little to no knowledge of the HHS machinery to be used.

The Economist aiming for #Vietnam and the general secretary.
"If Mr Lam fails, Vietnam will muddle on as a low-value-added production centre. But if he succeeds, a second doi moi would propel 100m Vietnamese into the developed world, creating another Asian growth engine."

Variational Quantum Latent Encoding for Topology Optimization
Alireza Tabarraei
https://arxiv.org/abs/2506.17487 https://arxiv.org/pd…

Variational Quantum Latent Encoding for Topology Optimization
A variational framework for structural topology optimization is developed, integrating quantum and classical latent encoding strategies within a coordinate-based neural decoding architecture. In this approach, a low-dimensional latent vector, generated either by a variational quantum circuit or sampled from a Gaussian distribution, is mapped to a higher-dimensional latent space via a learnable projection layer. This enriched representation is then decoded into a high-resolution material distrib…

A primer on the closure of algebraic complexity classes under factoring
C. S. Bhargav, Prateek Dwivedi, Nitin Saxena
https://arxiv.org/abs/2506.19604 https…

A primer on the closure of algebraic complexity classes under factoring
Polynomial factorization is a fundamental problem in computational algebra. Over the past half century, a variety of algorithmic techniques have been developed to tackle different variants of this problem. In parallel, algebraic complexity theory classifies polynomials into complexity classes based on their perceived `hardness'. This raises a natural question: Do these classes afford efficient factorization? In this survey, we revisit two pivotal techniques in polynomial factorization: Hensel…

On circumcentered direct methods for monotone variational inequality problems
Roger Behling, Yunier Bello-Cruz, Alfredo Iusem, Di Liu, Luiz-Rafael Santos
https://arxiv.org/abs/2506.17814

On circumcentered direct methods for monotone variational inequality problems
The variational inequality problem (VIP) plays a central role in the theory and applications in continuous optimization. In particular, minimization problems and KKT systems can be regard as VIPs. In this work, we present the first methods using circumcenter iterations for solving VIPs. The circumcentered-reflection method (CRM) is a tool based on projections developed with the aim of finding a point in the intersection of finitely many closed convex sets. CRM has gone through enhancements and …

Observation of Astrophysical Sources with SST-1M Telescopes -- First Results
Jakub Jury\v{s}ek (for the SST-1M Collaboration), Thomas Tavernier (for the SST-1M Collaboration), Vladim\'ir Novotn\'y (for the SST-1M Collaboration)
https://arxiv.org/abs/2507.17451

Observation of Astrophysical Sources with SST-1M Telescopes -- First Results
The Single-Mirror Small Size Cherenkov Telescope (SST-1M) was developed by a consortium of institutes in Switzerland, Poland, and the Czech Republic. The SST-1M design is based on the Davies-Cotton concept, featuring a 4-meter mirror and an innovative SiPM-based camera. It is most sensitive to gamma rays in the TeV and multi-TeV energy bands. Since 2022, two SST-1M prototypes have been commissioned at the Ondrejov Observatory in the Czech Republic, where their performance in both mono and stere…

Selecting N-lowest scores for training MOS prediction models
Yuto Kondo, Hirokazu Kameoka, Kou Tanaka, Takuhiro Kaneko
https://arxiv.org/abs/2506.18326 htt…

Selecting N-lowest scores for training MOS prediction models
The automatic speech quality assessment (SQA) has been extensively studied to predict the speech quality without time-consuming questionnaires. Recently, neural-based SQA models have been actively developed for speech samples produced by text-to-speech or voice conversion, with a primary focus on training mean opinion score (MOS) prediction models. The quality of each speech sample may not be consistent across the entire duration, and it remains unclear which segments of the speech receive the …

Quaternion-Domain Super MDS for Robust 3D Localization
Alessio Lukaj, Keigo Masuoka, Takumi Takahashi, Giuseppe Thadeu Freitas de Abreu, Hideki Ochiai
https://arxiv.org/abs/2507.17645

Quaternion-Domain Super MDS for Robust 3D Localization
This paper proposes a novel low-complexity three-dimensional (3D) localization algorithm for wireless sensor networks, termed quanternion-domain super multi-dimensional scaling (QD-SMDS). The algorithm is based on a reformulation of the SMDS, originally developed in the real domain, using quaternion algebra. By representing 3D coordinates as quaternions, the method constructs a rank-1 Gram edge kernel (GEK) matrix that integrates both relative distance and angular information between nodes, whi…

Unfolding the Past: A Comprehensive Deep Learning Approach to Analyzing Incunabula Pages
Klaudia Ropel, Krzysztof Kutt, Luiz do Valle Miranda, Grzegorz J. Nalepa
https://arxiv.org/abs/2506.18069

Unfolding the Past: A Comprehensive Deep Learning Approach to Analyzing Incunabula Pages
We developed a proof-of-concept method for the automatic analysis of the structure and content of incunabula pages. A custom dataset comprising 500 annotated pages from five different incunabula was created using resources from the Jagiellonian Digital Library. Each page was manually labeled with five predefined classes: Text, Title, Picture, Table, and Handwriting. Additionally, the publicly available DocLayNet dataset was utilized as supplementary training data. To perform object detection, Y…

Estimating Treatment Effects with Independent Component Analysis
Patrik Reizinger, Lester Mackey, Wieland Brendel, Rahul Krishnan
https://arxiv.org/abs/2507.16467

Estimating Treatment Effects with Independent Component Analysis
The field of causal inference has developed a variety of methods to accurately estimate treatment effects in the presence of nuisance. Meanwhile, the field of identifiability theory has developed methods like Independent Component Analysis (ICA) to identify latent sources and mixing weights from data. While these two research communities have developed largely independently, they aim to achieve similar goals: the accurate and sample-efficient estimation of model parameters. In the partially lin…

SIP-IFVM: An observation-based magnetohydrodynamic model of coronal mass ejection
Haopeng Wang, Jinhan Guo, Stefaan Poedts, Andrea Lani, Luis Linan, Tinatin Baratashvili, Liping Yang, Hyun-Jin Jeong, Wenwen Wei, Caixia Li, Yun Yang, Yucong Li, Hao Wu, Yang Guo, Brigitte Schmieder
https://arxiv.org/abs/2506.19711

SIP-IFVM: An observation-based magnetohydrodynamic model of coronal mass ejection
Currently, achieving a balance between computational efficiency, accuracy, and numerical stability in CME simulations, particularly in the sub-Alfv{'e}nic coronal region, remains a significant challenge. This paper aims to address the challenge by integrating observational data and developing advanced numerical algorithms, focusing on reproducing large-scale CME evolutions that are consistent with observations in the coronal region. Based on the recently developed fully implicit thermodynamic M…

🪩 HUSH: Holistic panoramic 3D scene understanding using spherical harmonics
#ai

HUSH: Holistic panoramic 3D scene understanding using spherical harmonics
An advanced artificial intelligence (AI) technology has been developed that can extract three-dimensional (3D) spatial structure and object information within indoor environments using just a single 360-degree panoramic photograph. This breakthrough is expected to significantly impact fields requiring precise spatial understanding, including augmented reality (AR), mixed reality (MR), and digital twin applications.

Operator Splitting Methods: Numerical Solutions of Ordinary Differential Equations via Separation of Variables
A. Banjara, I. AlJabea, T. Papamarkou, F. Neubrander
https://arxiv.org/abs/2506.17524

Operator Splitting Methods: Numerical Solutions of Ordinary Differential Equations via Separation of Variables
This paper applies the concept of linear semigroups induced by nonlinear flows, originally developed by Dorroh and Neuberger in the 1990s, to the approximation of uniquely solvable initial value problems for nonlinear ordinary differential equations. Building on a framework rooted in the earlier works of Lie, Kowalewski, and Groebner, we analyze nonlinear systems through the lens of the Koopman-Lie semigroup exp(tK), where K is the linear Lie generator associated with the flow induced by the no…

Practitioner forecasts of technological progress in biostasis
Andrew T. McKenzie, Michael Cerullo, Navid Farahani, Jordan S. Sparks, Taurus Londo\~no, Aschwin de Wolf, Suzan Dziennis, Borys Wr\'obel, Alexander German, Emil F. Kendziorra, Jo\~ao Pedro de Magalh\~aes, Wonjin Cho, R. Michael Perry, Max More
https://arxiv.org/abs/2507.1727…

Practitioner forecasts of technological progress in biostasis
Biostasis has the potential to extend human lives by offering a bridge to powerful life extension technologies that may be developed in the future. However, key questions in the field remain unresolved, including which biomarkers reliably indicate successful preservation, what technical obstacles pose the greatest barriers, and whether different proposed revival methods are theoretically feasible. To address these gaps, we conducted a collaborative forecasting exercise with 22 practitioners in …

If you're in or around Galway tomorrow, check this out!
From the game director of award-winning Monument Valley 3.
Join Game Director and Designer Jennifer Estaris in an interactive session developed as part of the Citizens Assemble Game Jam.
https://w…

Join Andrew Musselman and Trevor Grant as they present the latest developments in Mahout's new quantum compute layer, Qumat. They will provide an overview of the project, explain why Qumat was developed, and demonstrate its current capabilities. They will also present a demo of Qumat in action and conclude with calls to action for researchers and engineers who are interested in using and contributing to the project.
Learn more:

A 3D model simulation of hydrogen chloride photochemistry on Mars: Comparison with satellite data
Benjamin Benne (The University of Edinburgh, School of GeoSciences, UK, Centre for Exoplanet Science, University of Edinburgh, UK), Paul I. Palmer (The University of Edinburgh, School of GeoSciences, UK, Centre for Exoplanet Science, University of Edinburgh, UK), Benjamin M. Taysum (DLR, Germany), Kevin S. Olsen (Department of Physics, University of Oxford, UK, School of Physical Sciences,…

A 3D model simulation of hydrogen chloride photochemistry on Mars: Comparison with satellite data
HCl was detected in the Martian atmosphere by the NOMAD and ACS spectrometers aboard the ExoMars TGO. Photochemical models show that using gas-phase chemistry alone is insufficient to reproduce these data. Recent work has developed a heterogeneous chemical network within a 1D photochemistry model, guided by the seasonal variability in HCl. The aim of this work is to show that incorporating heterogeneous chlorine chemistry into a global 3D model of Martian photochemistry with conventional gas-ph…

'Mic drop': on estimating the size of sub-mm droplets using a simple condenser microphone
Avshalom Offner
https://arxiv.org/abs/2506.19782 https://…

'Mic drop': on estimating the size of sub-mm droplets using a simple condenser microphone
The size distribution of aerosol droplets is a key parameter in a myriad of processes, and it is typically measured with optical aids (e.g., lasers or cameras) that require sophisticated calibration, thus making the measurement cost intensive. We developed a new method to indirectly measure the size of small droplets using off-the-shelf <\$1 electret microphones. In this method we exploit the natural oscillations that small droplets undergo after impacting a flat surface: by allowing droplets t…

Rigidity control of general origami structures
Rongxuan Li, Gary P. T. Choi
https://arxiv.org/abs/2507.16934 https://arxiv.org/pdf/2507.16934

Rigidity control of general origami structures
Origami, the traditional paper-folding art, has inspired the modern design of numerous flexible structures in science and engineering. In particular, origami structures with different physical properties have been studied and utilized for various applications. More recently, several deterministic and stochastic approaches have been developed for controlling the rigidity or softness of the Miura-ori structures. However, the rigidity control of other origami structures is much less understood. In…

Impact of the ambipolar diffusion in the structuration of the magnetic Rayleigh Taylor instability with oblique magnetic field
E. Callies, V. Guillet, A. Marcowith, Z. Meliani, P. Lesaffre
https://arxiv.org/abs/2506.19672

Impact of the ambipolar diffusion in the structuration of the magnetic Rayleigh Taylor instability with oblique magnetic field
Aims. We investigate the impact of ambipolar diffusion on the development of the Rayleigh-Taylor instability (RTI) with an oblique magnetic field in the incompressible limit. Methods. We developed a general bi-fluid framework comprising charges and neutrals with the specific feature of differing gravity between charges and neutrals. We derived the perturbed magnetohydrodynamic (MHD) equations and obtained an analytic dispersion relation for an oblique magnetic field. The growth rate was then ev…

End-to-end reconstruction of ultra-high energy particle observables from radio detection of extensive air showers
Kewen Zhang, Duan Kaikai, Ramesh Koirala, Mat\'ias Tueros, Chao Zhang, Yi Zhang
https://arxiv.org/abs/2507.17266

End-to-end reconstruction of ultra-high energy particle observables from radio detection of extensive air showers
The radio detection of very inclined air showers offers a promising avenue for studying ultra-high-energy cosmic rays (UHECRs) and neutrinos. Accurate reconstruction methods are essential for investigating the properties of primary particles. Recently, we developed an analytical least-squares method to reconstruct the electric field using three polarization components. The reconstruction yields no bias, with a 68\% confidence interval of [-0.02, 0.02], and a standard deviation of 0.04. Using th…

MATE: LLM-Powered Multi-Agent Translation Environment for Accessibility Applications
Aleksandr Algazinov, Matt Laing, Paul Laban
https://arxiv.org/abs/2506.19502

MATE: LLM-Powered Multi-Agent Translation Environment for Accessibility Applications
Accessibility remains a critical concern in today's society, as many technologies are not developed to support the full range of user needs. Existing multi-agent systems (MAS) often cannot provide comprehensive assistance for users in need due to the lack of customization stemming from closed-source designs. Consequently, individuals with disabilities frequently encounter significant barriers when attempting to interact with digital environments. We introduce MATE, a multimodal accessibility MA…

Flux-driven turbulent transport using penalisation in the Hasegawa-Wakatani system
Pierre L. Guillon, \"Ozg\"ur D. G\"urcan, Guilhem Dif-Pradalier, Yanick Sarazin, Nicolas Fedorczak
https://arxiv.org/abs/2506.18705

Flux-driven turbulent transport using penalisation in the Hasegawa-Wakatani system
First numerical results from the newly-developed pseudo-spectral code P-FLARE (Penalised FLux-driven Algorithm for REduced models) are presented. This flux-driven turbulence/transport code uses a pseudo-spectral formulation with the penalisation method in order to impose radial boundary conditions. Its concise, flexible structure allows implementing various two dimensional reduced fluid models in flux-driven formulation. Here, results from simulations of the modified Hasegawa-Wakatani system ar…

Continuous-wave laser source at the 148 nm nuclear transition of Th-229
Vishal Lal, Maksim V. Okhapkin, Johannes Tiedau, Niels Irwin, Valentin Petrov, Ekkehard Peik
https://arxiv.org/abs/2507.17719

Continuous-wave laser source at the 148 nm nuclear transition of Th-229
A continuous-wave laser source at 148.4 nm based on second-harmonic generation in randomly quasi-phase matched strontium tetraborate, SrB4O7, is demonstrated. It provides (1.3-0.6+0.7) nW of VUV power in a single pass for an incident UV laser power of 325 mW. The laser system is developed for the resonant laser excitation of the 229Th nucleus to its low-energy isomeric state. For a frequency-stabilized laser system we expect to reach similar VUV power spectral densities as in previous pulsed la…

Normal modes and shockwaves in cold atoms
Francisco Raposo, Hugo Ter\c{c}as
https://arxiv.org/abs/2506.17404 https://arxiv.org/pdf/25…

Normal modes and shockwaves in cold atoms
Numerical methods are developed to simulate the dynamics of atoms in a Magneto-Optic Trap (MOT), based on the fluid description of ultracold gases under laser cooling and magnetic trapping forces. With this model, equilibrium hydrostatic profiles and normal modes are calculated, and numerical results are validated against theoretical predictions. As a test case, shock wave formation due to rapid gas expansion and contraction of the ultracold gas is simulated. The latter is caused by a sudden ch…

What You Think Is What You Get: Bridge User Intent and Transfer Function Design through Multimodal Large Language Models
Yiyao Wang, Bo Pan, Ke Wang, Han Liu, Jinyuan Mao, Yuxin Liu, Minfeng Zhu, Bo Zhang, Weifeng Chen, Xiuqi Huang, Wei Chen
https://arxiv.org/abs/2506.18407

What You Think Is What You Get: Bridge User Intent and Transfer Function Design through Multimodal Large Language Models
Direct volume rendering (DVR) is a fundamental technique for visualizing volumetric data, with transfer functions (TFs) playing a crucial role in extracting meaningful structures. However, designing effective TFs remains unintuitive due to the semantic gap between user intent and TF parameter space. Researchers have developed numerous TF optimization methods to bridge this gap. However, existing methods still face two challenges: large exploration space and weak generalizability. To address the…

A System Level Compiler for Massively-Parallel, Spatial, Dataflow Architectures
Dirk Van Essendelft, Patrick Wingo, Terry Jordan, Ryan Smith, Wissam Saidi
https://arxiv.org/abs/2506.15875

A System Level Compiler for Massively-Parallel, Spatial, Dataflow Architectures
We have developed a novel compiler called the Multiple-Architecture Compiler for Advanced Computing Hardware (MACH) designed specifically for massively-parallel, spatial, dataflow architectures like the Wafer Scale Engine. Additionally, MACH can execute code on traditional unified-memory devices. MACH addresses the complexities in compiling for spatial architectures through a conceptual Virtual Machine, a flexible domain-specific language, and a compiler that can lower high-level languages to m…

Complete left tail asymptotic for branching processes in random environments
Anton A Kutsenko
https://arxiv.org/abs/2506.18450 https://

Complete left tail asymptotic for branching processes in random environments
Recently, the complete left tail asymptotic for the density of the {\it martingale limit} of the classical Galton-Watson process has been derived. The derivation is based on the properties of a special function (whose inverse Fourier transform is the density) satisfying a Poincaré-type functional equation. However, the corresponding special function does not satisfy the Poincaré-type functional equation for the processes in random environments. This makes it impossible to apply the developed …

A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction
Shigan Liu, Guannan Geng, Yanfei Xiang, Hejun Hu, Xiaodong Liu, Xiaomeng Huang, Qiang Zhang
https://arxiv.org/abs/2506.18018

A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction
Air pollution remains a leading global health threat, with fine particulate matter (PM2.5) contributing to millions of premature deaths annually. Chemical transport models (CTMs) are essential tools for evaluating how emission controls improve air quality and save lives, but they are computationally intensive. Reduced form models accelerate simulations but sacrifice spatial-temporal granularity, accuracy, and flexibility. Here we present CleanAir, a deep-learning-based model developed as an eff…

BiLO: Bilevel Local Operator Learning for PDE Inverse Problems. Part II: Efficient Uncertainty Quantification with Low-Rank Adaptation
Ray Zirui Zhang, Christopher E. Miles, Xiaohui Xie, John S. Lowengrub
https://arxiv.org/abs/2507.17019

BiLO: Bilevel Local Operator Learning for PDE Inverse Problems. Part II: Efficient Uncertainty Quantification with Low-Rank Adaptation
Uncertainty quantification and inverse problems governed by partial differential equations (PDEs) are central to a wide range of scientific and engineering applications. In this second part of a two part series, we extend Bilevel Local Operator Learning (BiLO) for PDE-constrained optimization problems developed in Part 1 to the Bayesian inference framework. At the lower level, we train a network to approximate the local solution operator by minimizing the local operator loss with respect to the…

Resist the surface field: the H-bond network decides if water aligns at metal electrodes
Mohammed Bin Jassar, Wei-tao Liu, Simone Pezzotti
https://arxiv.org/abs/2506.18467

Resist the surface field: the H-bond network decides if water aligns at metal electrodes
At an electrode, water molecules align to the surface field upon voltage application. This initiates important electrochemical reactions, e.g., hydrogen and oxygen evolution reactions. Recently developed non-linear optical techniques challenge the traditional picture by quantifying a lack of water alignment at metal electrodes. We here provide theoretical and experimental evidences for the existence of a driving force that opposes water alignment to the surface field. Such driving force origina…

Homeownership as Life Cycle Goldmine: Evidence from Macrohistory
Yang Bai, Shize Li, Jialu Shen
https://arxiv.org/abs/2507.17624 https://arxiv.org/pdf/2507…

Homeownership as Life Cycle Goldmine: Evidence from Macrohistory
Should a household buy a home? Using data from 16 developed countries spanning 1870 to 2020, this study provides a resounding affirmative answer. Contrary to popular expert advice, homeownership enhances life cycle wealth by up to 9% and welfare by up to 23%, compared to all-equity investment strategy. Homeownership reduces wealth portfolio risk and improves wealth equality, though it comes at the cost of lower working-life wealth and curtailed financial asset holdings. Gains are heterogeneous:…

In the United States, the power to use military force, including ordering airstrikes, is not granted explicitly to the President in the U.S. Constitution. Rather, this authority comes from Congress's power to declare war and grant the President the authority to take military action under Article II, Section 2 of the Constitution. This authority is further developed through the War Powers Resolution of 1973, which places limits on the President's ability to deploy U.S. forces into hos…

"The Research Data Management Workbook: Building a Collection of Data Management Exercises to Bridge Data Information Literacy and Data Management Implementation" @ Journal of eScience Librarianship: https://doi.org/10.7191/jeslib.937

From Brownian dynamics to Poisson-Nernst-Planck equations: multi-resolution simulations of ions
Jinyuan Zhang, Radek Erban
https://arxiv.org/abs/2506.19738

From Brownian dynamics to Poisson-Nernst-Planck equations: multi-resolution simulations of ions
Starting with a microscopic (individual-based) Brownian dynamics model of charged particles (ions), its macroscopic description is derived as a system of partial differential equations that govern the evolution of ion concentrations in space and time. The macroscopic equations are obtained in the form of the Poisson-Nernst-Planck system. A multi-resolution method for simulating charged particles is then developed, combining the detailed Brownian dynamics model in a part of the computational dom…

Why AI can't possibly make you more productive; long
#AI and "productivity", some thoughts:
Edit: fixed some typos.
Productivity is a concept that isn't entirely meaningless outside the context of capitalism, but it's a concept that is heavily inflected in a capitalist context. In many uses today it effectively means "how much you can satisfy and/or exceed your boss' expectations." This is not really what it should mean: even in an anarchist utopia, people would care about things like how many shirts they can produce in a week, although in an "I'd like to voluntarily help more people" way rather than an "I need to meet this quota to earn my survival" way. But let's roll with this definition for a second, because it's almost certainly what your boss means when they say "productivity", and understanding that word in a different (even if truer) sense is therefore inherently dangerous.
Accepting "productivity" to mean "satisfying your boss' expectations," I will now claim: the use of generative AI cannot increase your productivity.
Before I dive in, it's imperative to note that the big generative models which most people think of as constituting "AI" today are evil. They are 1: pouring fuel on our burning planet, 2: psychologically strip-mining a class of data laborers who are exploited for their precarity, 3: enclosing, exploiting, and polluting the digital commons, and 4: stealing labor from broad classes of people many of whom are otherwise glad to give that labor away for free provided they get a simple acknowledgement in return. Any of these four "ethical issues" should be enough *alone* to cause everyone to simply not use the technology. These ethical issues are the reason that I do not use generative AI right now, except for in extremely extenuating circumstances. These issues are also convincing for a wide range of people I talk to, from experts to those with no computer science background. So before I launch into a critique of the effectiveness of generative AI, I want to emphasize that such a critique should be entirely unnecessary.
But back to my thesis: generative AI cannot increase your productivity, where "productivity" has been defined as "how much you can satisfy and/or exceed your boss' expectations."
Why? In fact, what the fuck? Every AI booster I've met has claimed the opposite. They've given me personal examples of time saved by using generative AI. Some of them even truly believe this. Sometimes I even believe they saved time without horribly compromising on quality (and often, your boss doesn't care about quality anyways if the lack of quality is hard to measure of doesn't seem likely to impact short-term sales/feedback/revenue). So if generative AI genuinely lets you write more emails in a shorter period of time, or close more tickets, or something else along these lines, how can I say it isn't increasing your ability to meet your boss' expectations?
The problem is simple: your boss' expectations are not a fixed target. Never have been. In virtue of being someone who oversees and pays wages to others under capitalism, your boss' game has always been: pay you less than the worth of your labor, so that they can accumulate profit and thus more capital to remain in charge instead of being forced into working for a wage themselves. Sure, there are layers of management caught in between who aren't fully in this mode, but they are irrelevant to this analysis. It matters not how much you please your manager if your CEO thinks your work is not worth the wages you are being paid. And using AI actively lowers the value of your work relative to your wages.
Why do I say that? It's actually true in several ways. The most obvious: using generative AI lowers the quality of your work, because the work it produces is shot through with errors, and when your job is reduced to proofreading slop, you are bound to tire a bit, relax your diligence, and let some mistakes through. More than you would have if you are actually doing and taking pride in the work. Examples are innumerable and frequent, from journalists to lawyers to programmers, and we laugh at them "haha how stupid to not check whether the books the AI reviewed for you actually existed!" but on a deeper level if we're honest we know we'd eventually make the same mistake ourselves (bonus game: spot the swipe-typing typos I missed in this post; I'm sure there will be some).
But using generative AI also lowers the value of your work in another much more frightening way: in this era of hype, it demonstrates to your boss that you could be replaced by AI. The more you use it, and no matter how much you can see that your human skills are really necessary to correct its mistakes, the more it appears to your boss that they should hire the AI instead of you. Or perhaps retain 10% of the people in roles like yours to manage the AI doing the other 90% of the work. Paradoxically, the *more* you get done in terms of raw output using generative AI, the more it looks to your boss as if there's an opportunity to get enough work done with even fewer expensive humans. Of course, the decision to fire you and lean more heavily into AI isn't really a good one for long-term profits and success, but the modern boss did not get where they are by considering long-term profits. By using AI, you are merely demonstrating your redundancy, and the more you get done with it, the more redundant you seem.
In fact, there's even a third dimension to this: by using generative AI, you're also providing its purveyors with invaluable training data that allows them to make it better at replacing you. It's generally quite shitty right now, but the more use it gets by competent & clever people, the better it can become at the tasks those specific people use it for. Using the currently-popular algorithm family, there are limits to this; I'm not saying it will eventually transcend the mediocrity it's entwined with. But it can absolutely go from underwhelmingly mediocre to almost-reasonably mediocre with the right training data, and data from prompting sessions is both rarer and more useful than the base datasets it's built on.
For all of these reasons, using generative AI in your job is a mistake that will likely lead to your future unemployment. To reiterate, you should already not be using it because it is evil and causes specific and inexcusable harms, but in case like so many you just don't care about those harms, I've just explained to you why for entirely selfish reasons you should not use it.
If you're in a position where your boss is forcing you to use it, my condolences. I suggest leaning into its failures instead of trying to get the most out of it, and as much as possible, showing your boss very clearly how it wastes your time and makes things slower. Also, point out the dangers of legal liability for its mistakes, and make sure your boss is aware of the degree to which any of your AI-eager coworkers are producing low-quality work that harms organizational goals.
Also, if you've read this far and aren't yet of an anarchist mindset, I encourage you to think about the implications of firing 75% of (at least the white-collar) workforce in order to make more profit while fueling the climate crisis and in most cases also propping up dictatorial figureheads in government. When *either* the AI bubble bursts *or* if the techbros get to live out the beginnings of their worker-replacement fantasies, there are going to be an unimaginable number of economically desperate people living in increasingly expensive times. I'm the kind of optimist who thinks that the resulting social crucible, though perhaps through terrible violence, will lead to deep social changes that effectively unseat from power the ultra-rich that continue to drag us all down this destructive path, and I think its worth some thinking now about what you might want the succeeding stable social configuration to look like so you can advocate towards that during points of malleability.
As others have said more eloquently, generative AI *should* be a technology that makes human lives on average easier, and it would be were it developed & controlled by humanists. The only reason that it's not, is that it's developed and controlled by terrible greedy people who use their unfairly hoarded wealth to immiserate the rest of us in order to maintain their dominance. In the long run, for our very survival, we need to depose them, and I look forward to what the term "generative AI" will mean after that finally happens.

Formal Verification of the Safegcd Implementation
Russell O'Connor, Andrew Poelstra
https://arxiv.org/abs/2507.17956 https://arxiv.org/pdf/2507.17956…

Formal Verification of the Safegcd Implementation
The modular inverse is an essential piece of computation required for elliptic curve operations used for digital signatures in Bitcoin and other applications. A novel approach to the extended Euclidean algorithm has been developed by Bernstein and Yang within the last few years and incorporated into the libsecp256k1 cryptographic library used by Bitcoin. However, novel algorithms introduce new risks of errors. To address this we have completed a computer verified proof of the correctness of (on…

In the spring, I gave the participants of the fine arts pedagogy course at INN a glimpse into what I’ll be researching this fall. While the connections have developed since then, I still like the map and refer to it regularly.
A brief overview – fredsnotes https://filmschoolteacher.info…

Universal framework with exponential speedup for the quantum simulation of quantum field theories including QCD
Jad C. Halimeh, Masanori Hanada, Shunji Matsuura
https://arxiv.org/abs/2506.18966

Universal framework with exponential speedup for the quantum simulation of quantum field theories including QCD
We present a quantum simulation framework universally applicable to a wide class of quantum systems, including quantum field theories such as quantum chromodynamics (QCD). Specifically, we generalize an efficient quantum simulation protocol developed for bosonic theories in [Halimeh et al., arXiv:2411.13161] which, when applied to Yang-Mills theory, demonstrated an exponential resource advantage with respect to the truncation level of the bosonic modes, to systems with both bosons and fermions …

Lost in Translation? Converting RegExes for Log Parsing into Dynatrace Pattern Language
Julian Fragner, Christian Macho, Bernhard Dieber, Martin Pinzger
https://arxiv.org/abs/2506.19539

Lost in Translation? Converting RegExes for Log Parsing into Dynatrace Pattern Language
Log files provide valuable information for detecting and diagnosing problems in enterprise software applications and data centers. Several log analytics tools and platforms were developed to help filter and extract information from logs, typically using regular expressions (RegExes). Recent commercial log analytics platforms provide domain-specific languages specifically designed for log parsing, such as Grok or the Dynatrace Pattern Language (DPL). However, users who want to migrate to these p…

A supercharged HIV vaccine could offer strong protection with just one injection, a study in mice has indicated.
Developed by researchers from the Massachusetts Institute of Technology (MIT) and the Scripps Research Center, the vaccine includes two "adjuvants"
—materials that help stimulate the immune system response.
In the experiments, the dual-adjuvant vaccine was found to produce a wider diversity of antibodies to protect against an HIV protein than with either s…

HIV: Supercharged Vaccine Could Protect Well With Just One Dose
The approach employed by the research team could be used against other diseases—including COVID-19 and influenza.

UT-GraphCast Hindcast Dataset: A Global AI Forecast Archive from UT Austin for Weather and Climate Applications
Naveen Sudharsan, Manmeet Singh, Harsh Kamath, Hassan Dashtian, Clint Dawson, Zong-Liang Yang, Dev Niyogi
https://arxiv.org/abs/2506.17453

UT-GraphCast Hindcast Dataset: A Global AI Forecast Archive from UT Austin for Weather and Climate Applications
The UT GraphCast Hindcast Dataset from 1979 to 2024 is a comprehensive global weather forecast archive generated using the Google DeepMind GraphCast Operational model. Developed by researchers at The University of Texas at Austin under the WCRP umbrella, this dataset provides daily 15 day deterministic forecasts at 00UTC on an approximately 25 km global grid for a 45 year period. GraphCast is a physics informed graph neural network that was trained on ECMWF ERA5 reanalysis. It predicts more tha…

Diagnostic Imaging for Damage Detection in Plates Based on Topological Acoustic (TA) Sensing Technique
Bo Hu, Tribikram Kundu, Pierre A. Deymier, Keith Runge
https://arxiv.org/abs/2506.19203

Diagnostic Imaging for Damage Detection in Plates Based on Topological Acoustic (TA) Sensing Technique
Traditional structural damage detection methods in aerospace applications face challenges in accuracy and sensitivity, often necessitating multiple sensors to evaluate various measurement paths between the reference and defective states. However, the recently developed topological acoustic (TA) sensing technique can capture shifts in the geometric phase of an acoustic field, enabling the detection of even minor perturbations in the supporting medium. In this study, a diagnostic imaging method f…

Sources: Reddit is exploring Tools for Humanity's World ID identity system to allow users to verify that they are unique individuals while remaining anonymous (Reed Albergotti/Semafor)
https://www.semafor.com/article/06/20/2025

Reddit in talks to embrace Sam Altman’s iris-scanning Orb to verify users
Reddit, racing to preserve “humanness and authenticity,” has discussed using Sam Altman’s World ID, sources say.

Automatic Large Language Models Creation of Interactive Learning Lessons
Jionghao Lin, Jiarui Rao, Yiyang Zhao, Yuting Wang, Ashish Gurung, Amanda Barany, Jaclyn Ocumpaugh, Ryan S. Baker, Kenneth R. Koedinger
https://arxiv.org/abs/2506.17356

Automatic Large Language Models Creation of Interactive Learning Lessons
We explore the automatic generation of interactive, scenario-based lessons designed to train novice human tutors who teach middle school mathematics online. Employing prompt engineering through a Retrieval-Augmented Generation approach with GPT-4o, we developed a system capable of creating structured tutor training lessons. Our study generated lessons in English for three key topics: Encouraging Students' Independence, Encouraging Help-Seeking Behavior, and Turning on Cameras, using a task deco…

Quadratic Corrections to the Higher-Spin Equations by the Differential Homotopy Approach
P. T. Kirakosiants, D. A. Valerev, M. A. Vasiliev
https://arxiv.org/abs/2506.16634

Quadratic Corrections to the Higher-Spin Equations by the Differential Homotopy Approach
The recently proposed differential homotopy approach to the analysis of nonlinear higher spin theory is developed. The Ansatz is extended to the form applicable in the second order of the perturbation theory and general star-multiplication formulae are derived. The relation of the shifted homotopy and differential homotopy formalisms is worked out. Projectively-compact spin-local quadratic (anti)holomorphic vertices in the one-form sector of higher-spin equations are obtained within the differe…

Characteristic equations of linearized $\lambda R$ gravity
J. Aldair Pantoja-Gonzalez (Puebla U., Inst. Fis.), D. Vanessa Castro-Luna (Puebla U., Inst. Fis.), Alberto Escalante (Puebla U., Inst. Fis.)
https://arxiv.org/abs/2506.16603

Characteristic equations of linearized $λR$ gravity
A detailed Hamilton-Jacobi analysis for linearized $λR$ gravity is developed. The model is constructed by rewriting linearized gravity in terms of a parameter $λ$ and new variables. The set of all hamiltonians is identified successfully, and the fundamental differential is established. The non-involutive hamiltonians are eliminated, and the Hamilton-Jacobi generalized brackets are calculated. Such brackets are used to report the characteristic equations, and the counting of the number of degr…

Time to Split: Exploring Data Splitting Strategies for Offline Evaluation of Sequential Recommenders
Danil Gusak, Anna Volodkevich, Anton Klenitskiy, Alexey Vasilev, Evgeny Frolov
https://arxiv.org/abs/2507.16289

Time to Split: Exploring Data Splitting Strategies for Offline Evaluation of Sequential Recommenders
Modern sequential recommender systems, ranging from lightweight transformer-based variants to large language models, have become increasingly prominent in academia and industry due to their strong performance in the next-item prediction task. Yet common evaluation protocols for sequential recommendations remain insufficiently developed: they often fail to reflect the corresponding recommendation task accurately, or are not aligned with real-world scenarios. Although the widely used leave-one-…

Talk about poisoned pen! https://www.theguardian.com/books/2025/jun/06/tool-to-identify-poisonous-books-developed-by-university-of-st-andrews

CultureMERT: Continual Pre-Training for Cross-Cultural Music Representation Learning
Angelos-Nikolaos Kanatas, Charilaos Papaioannou, Alexandros Potamianos
https://arxiv.org/abs/2506.17818

CultureMERT: Continual Pre-Training for Cross-Cultural Music Representation Learning
Recent advances in music foundation models have improved audio representation learning, yet their effectiveness across diverse musical traditions remains limited. We introduce CultureMERT-95M, a multi-culturally adapted foundation model developed to enhance cross-cultural music representation learning and understanding. To achieve this, we propose a two-stage continual pre-training strategy that integrates learning rate re-warming and re-decaying, enabling stable adaptation even with limited co…

Learning from the Storm: A Multivariate Machine Learning Approach to Predicting Hurricane-Induced Economic Losses
Bolin Shen, Eren Erman Ozguven, Yue Zhao, Guang Wang, Yiqun Xie, Yushun Dong
https://arxiv.org/abs/2506.17964

Learning from the Storm: A Multivariate Machine Learning Approach to Predicting Hurricane-Induced Economic Losses
Florida is particularly vulnerable to hurricanes, which frequently cause substantial economic losses. While prior studies have explored specific contributors to hurricane-induced damage, few have developed a unified framework capable of integrating a broader range of influencing factors to comprehensively assess the sources of economic loss. In this study, we propose a comprehensive modeling framework that categorizes contributing factors into three key components: (1) hurricane characteristics…

Nuclear $\beta$-decay half-lives within the subtracted second random-phase approximation
Danilo Gambacurta, Marcella Grasso
https://arxiv.org/abs/2506.18849

Nuclear $β$-decay half-lives within the subtracted second random-phase approximation
We employ, within the framework of Skyrme energy-density functional theory, the subtracted second random-phase approximation, recently developed for charge-exchange excitations, to compute $β$-decay half-lives in four nuclei, $^{24}$O, $^{34}$Si, $^{78}$Ni, and $^{132}$Sn. Following our recent results on the description of the Gamow-Teller strength, we proceed coherently in the present work by computing $β$-decay half-lives using the bare value of the axial-vector coupling constant $g_A$. Hal…

Dynamic Activation and Assignment of SDN Controllers in LEO Satellite Constellations
Wafa Hasanain, Pablo G. Madoery, Halim Yanikomeroglu, Gunes Karabulut Kurt, Sameera Siddiqui, Stephane Martel, Khaled Ahmed, Colin Bellinger
https://arxiv.org/abs/2507.16774

Dynamic Activation and Assignment of SDN Controllers in LEO Satellite Constellations
Software-defined networking (SDN) has emerged as a promising approach for managing traditional satellite communication. This enhances opportunities for future services, including integrating satellite and terrestrial networks. In this paper, we have developed an SDN-enabled framework for Low Earth Orbit (LEO) satellite networks, incorporating the OpenFlow protocol, all within an OMNeT++ simulation environment. Dynamic controller assignment is one of the most significant challenges for large LEO…

Coupled Entropy: A Goldilocks Generalization?
Kenric P. Nelson
https://arxiv.org/abs/2506.17229 https://arxiv.org/pdf/2506.17229

Coupled Entropy: A Goldilocks Generalization?
Nonextensive Statistical Mechanics (NSM) has developed into a powerful toolset for modeling and analyzing complex systems. Despite its many successes, a puzzle arose early in its development. The constraints on the Tsallis entropy are in the form of an escort distribution with elements proportional to $p_i^q$, but this same factor within the Tsallis entropy function is not normalized. This led to consideration of the Normalized Tsallis Entropy (NTE); however, the normalization proved to make th…

Early Identification of Optical Tidal Disruption Events: A science module for the Fink broker
Miguel Llamas Lanza, Sergey Karpov, Etienne Russeil, Erwan Quintin, Emille Ishida, Julien Peloton, Maria Pruzhinskaya, Anais M\"oller
https://arxiv.org/abs/2507.17499

Early Identification of Optical Tidal Disruption Events: A science module for the Fink broker
The detection of tidal disruption events (TDEs) is one of the key science goals of large optical time-domain surveys such as the Zwicky Transient Facility (ZTF) and the upcoming Vera C. Rubin Observatory Legacy Survey of Space and Time. However, identifying TDEs in the vast alert streams produced by these surveys requires automated and reliable classification pipelines that can select promising candidates in real time. We developed a module within the Fink alert broker to identify TDEs during t…

Explicit Monotone Stable Super-Time-Stepping Methods for Finite Time Singularities
Zheng Tan, Tariq D. Aslam, Andrea L. Bertozzi
https://arxiv.org/abs/2507.17062 https://…

Explicit Monotone Stable Super-Time-Stepping Methods for Finite Time Singularities
We explore a novel way to numerically resolve the scaling behavior of finite-time singularities in solutions of nonlinear parabolic PDEs. The Runge--Kutta--Legendre (RKL) and Runge--Kutta--Gegenbauer (RKG) super-time-stepping methods were originally developed for nonlinear complex physics problems with diffusion. These are multi-stage single step second-order, forward-in-time methods with no implicit solves. The advantage is that the timestep size for stability scales with stage number $s$ as $…

PolyGuard: Massive Multi-Domain Safety Policy-Grounded Guardrail Dataset
Mintong Kang, Zhaorun Chen, Chejian Xu, Jiawei Zhang, Chengquan Guo, Minzhou Pan, Ivan Revilla, Yu Sun, Bo Li
https://arxiv.org/abs/2506.19054

PolyGuard: Massive Multi-Domain Safety Policy-Grounded Guardrail Dataset
As LLMs become widespread across diverse applications, concerns about the security and safety of LLM interactions have intensified. Numerous guardrail models and benchmarks have been developed to ensure LLM content safety. However, existing guardrail benchmarks are often built upon ad hoc risk taxonomies that lack a principled grounding in standardized safety policies, limiting their alignment with real-world operational requirements. Moreover, they tend to overlook domain-specific risks, while…

Which Consciousness Can Be Artificialized? Local Percept-Perceiver Phenomenon for the Existence of Machine Consciousness
Shri Lal Raghudev Ram Singh
https://arxiv.org/abs/2506.18935

Which Consciousness Can Be Artificialized? Local Percept-Perceiver Phenomenon for the Existence of Machine Consciousness
This paper presents a novel paradigm of the local percept-perceiver phenomenon to formalize certain observations in neuroscientific theories of consciousness. Using this model, a set-theoretic formalism is developed for artificial systems, and the existence of machine consciousness is proved by invoking Zermelo-Fraenkel set theory. The article argues for the possibility of a reductionist form of epistemic consciousness within machines.

Multivariate Statistical Analysis of Exoplanet Habitability: Detection Bias and Earth Analog Identification
Caleb Traxler, Samuel Townsend, Abby Mori, Grace Newman, Kaitlyn Morenzone
https://arxiv.org/abs/2506.18200

Multivariate Statistical Analysis of Exoplanet Habitability: Detection Bias and Earth Analog Identification
We present a comprehensive multivariate statistical analysis of 517 exoplanets from the NASA Exoplanet Archive to identify potentially habitable worlds and quantify detection bias in current surveys. Using eight key parameters (planetary radius, equilibrium temperature, insolation flux, density, and stellar effective temperature, radius, mass, metallicity), we developed a classification framework that successfully identifies Earth as an "Excellent Candidate" for habitability. Our analysis revea…

Relationship between unpredictability and intermittency in shell models of turbulence and experiments
Ewen Frog\'e (IMT Atlantique - MEE, ODYSSEY, Lab-STICC_OSE), Carlos Granero-Belinchon (ODYSSEY, IMT Atlantique - MEE, Lab-STICC_OSE), St\'ephane G. Roux (IMT Atlantique - MEE, Lab-STICC_MATRIX), Thierry Chonavel (IMT Atlantique - MEE, Lab-STICC_MATRIX), Nicolas B. Garnier

Relationship between unpredictability and intermittency in shell models of turbulence and experiments
We study the predictability of turbulent velocity signals using probabilistic analog-forecasting. Here, predictability is defined by the accuracy of forecasts and the associated uncertainties. We study the Gledzer-Ohkitani-Yamada (GOY) shell model of turbulence as well as experimental measurements from a fully developed turbulent flow. In both cases, we identify the extreme values of velocity at small scales as localized unpredictable events that lead to a loss of predictability: worse predicti…

SMECS: A Software Metadata Extraction and Curation Software
Stephan Ferenz, Aida Jafarbigloo, Oliver Werth, Astrid Nie{\ss}e
https://arxiv.org/abs/2507.18159 https://

SMECS: A Software Metadata Extraction and Curation Software
Metadata play a crucial role in adopting the FAIR principles for research software and enables findability and reusability. However, creating high-quality metadata can be resource-intensive for researchers and research software engineers. To address this challenge, we developed the Software Metadata Extraction and Curation Software (SMECS) which integrates the extraction of metadata from existing sources together with a user-friendly interface for metadata curation. SMECS extracts metadata from…

Plasma Position Constrained Free-Boundary MHD Equilibrium in Tokamaks using pyIPREQ
Udaya Maurya, Amit K. Singh, Suman Aich, Jagabandhu Kumar, Rohit Kumar, Daniel Raju
https://arxiv.org/abs/2507.18324 …

Plasma Position Constrained Free-Boundary MHD Equilibrium in Tokamaks using pyIPREQ
A free-boundary, axisymmetric magnetohydrodynamic (MHD) equilibrium code, pyIPREQ, has been developed for Tokamak plasmas using finite difference and Green's function approach. The code builds upon the foundational frameworks of the PEST and IPREQ codes, introducing several enhancements and new capabilities. Notably, pyIPREQ supports the specification of limiter boundaries and enables the computation of key physical quantities. The code has also been extended to compute equilibria constrained b…

Galactokinetics II: Spiral structure
Chris Hamilton, Shaunak Modak, Scott Tremaine
https://arxiv.org/abs/2507.16950 https://arxiv.org…

Galactokinetics II: Spiral structure
We present a unified theory of linear spiral structure in stellar disks. We begin by identifying the characteristic scales involved in the spiral structure problem and listing some quantitative requirements of a successful theory. We then write down the general linear response theory for thin disks, making clear the equivalence between different representations (e.g., Volterra, Landau, van Kampen) of the theory. Next, using the asymptotic expansions developed in our previous galactokinetics pap…

TasVisAn and InsPy -- Python Packages for Triple-Axis Spectrometer Data Visualization, Analysis, Instrument Resolution Calculation, and Convolution
Guochu Deng
https://arxiv.org/abs/2506.18216

TasVisAn and InsPy -- Python Packages for Triple-Axis Spectrometer Data Visualization, Analysis, Instrument Resolution Calculation, and Convolution
Experimental data collected from a triple-axis spectrometer (TAS) are typically analysed by considering the instrument resolution, as the resolution of a TAS instrument is often complex and significantly influences the measured results. Two Python packages, TasVisAn and InsPy, have been developed to visualize and analyse data from TAS instruments - particularly from the cold-neutron TAS Sika and the thermal-neutron TAS Taipan at the Australian Centre for Neutron Scattering. TasVisAn offers a ra…

Ultra-broadband spectral and polarisation entanglement using dispersion-engineered nanophotonic waveguides
Mahmoud Almassri, Mohammed F. Saleh
https://arxiv.org/abs/2506.17819

Ultra-broadband spectral and polarisation entanglement using dispersion-engineered nanophotonic waveguides
In this paper, we propose exploiting dispersion-engineered nanophotonic waveguides in generating unprecedented ultra-broadband spectral and polarisation entanglement using spontaneous four-wave mixing parametric processes. We developed a simplified theoretical quantum framework to investigate and analyse these interactions under pulse source excitations. Using aluminum gallium arsenide and thin-film lithium niobate waveguides, we anticipate to obtain photon pairs with high-dimensional frequency…

A Concept for Efficient Scalability of Automated Driving Allowing for Technical, Legal, Cultural, and Ethical Differences
Lars Ullrich, Michael Buchholz, Jonathan Petit, Klaus Dietmayer, Knut Graichen
https://arxiv.org/abs/2507.18326

A Concept for Efficient Scalability of Automated Driving Allowing for Technical, Legal, Cultural, and Ethical Differences
Efficient scalability of automated driving (AD) is key to reducing costs, enhancing safety, conserving resources, and maximizing impact. However, research focuses on specific vehicles and context, while broad deployment requires scalability across various configurations and environments. Differences in vehicle types, sensors, actuators, but also traffic regulations, legal requirements, cultural dynamics, or even ethical paradigms demand high flexibility of data-driven developed capabilities. In…

Collaborative governance of cyber violence: A two-phase, multi-scenario four-party evolutionary game and SBI1I2R public opinion dissemination
Xiaoting Yang, Wei Lv, Ting Yang, Bart Baesens
https://arxiv.org/abs/2506.19704

Collaborative governance of cyber violence: A two-phase, multi-scenario four-party evolutionary game and SBI1I2R public opinion dissemination
Cyber violence severely disrupts public order in both cyberspace and the real world. Existing studies have gradually advocated collaborative governance but rely on macro-level theoretical analyses. This study integrates micro- and macro-level perspectives to propose a two-stage, multi-scenario governance mechanism for cyber violence. In the first phase, a multi-scenario evolutionary game model with four parties involved in cyber violence was developed based on evolutionary game theory. Matlab s…

Stochastic dynamics simulation of the focused electron beam induced deposition process
Ilia A. Solov'yov, Alexey Prosvetov, Gennady Sushko, Andrey V. Solov'yov
https://arxiv.org/abs/2506.18163

Stochastic dynamics simulation of the focused electron beam induced deposition process
This work reports on the development of a new approach to the multiscale computational modelling of the focused electron beam-induced deposition (FEBID), realised using the advanced software packages: MBN Explorer and MBN Studio. Our approach is based on stochastic dynamics (SD), which describes the probabilistic evolution of complex systems. The parameters for the new SD-based FEBID model were determined using molecular dynamics (MD) simulations. A new methodology was developed for this purpos…

Lessons from a Big-Bang Integration: Challenges in Edge Computing and Machine Learning
Alessandro Aneggi, Andrea Janes
https://arxiv.org/abs/2507.17270 htt…

Lessons from a Big-Bang Integration: Challenges in Edge Computing and Machine Learning
This experience report analyses a one year project focused on building a distributed real-time analytics system using edge computing and machine learning. The project faced critical setbacks due to a big-bang integration approach, where all components developed by multiple geographically dispersed partners were merged at the final stage. The integration effort resulted in only six minutes of system functionality, far below the expected 40 minutes. Through root cause analysis, the study identifi…

Evaluating Social Acceptance of eXtended Reality (XR) Agent Technology: A User Study (Extended Version)
Megha Quamara, Viktor Schmuck, Cristina Iani, Axel Primavesi, Alexander Plaum, Luca Vigano
https://arxiv.org/abs/2507.16562

Evaluating Social Acceptance of eXtended Reality (XR) Agent Technology: A User Study (Extended Version)
In this paper, we present the findings of a user study that evaluated the social acceptance of eXtended Reality (XR) agent technology, focusing on a remotely accessible, web-based XR training system developed for journalists. This system involves user interaction with a virtual avatar, enabled by a modular toolkit. The interactions are designed to provide tailored training for journalists in digital-remote settings, especially for sensitive or dangerous scenarios, without requiring specialized …

An elementary proof of Newman's eta-quotient theorem
David Savitt
https://arxiv.org/abs/2507.16225 https://arxiv.org/pdf/2507.162…

An elementary proof of Newman's eta-quotient theorem
Let eta(z) be the Dedekind eta function. Newman studied the modularity of eta-quotients, giving necessary and sufficient conditions for a function of the form \prod_{0 < m | N} eta(mz)^{r_m} to be a (weakly) holomorphic modular form of level N. We explain a proof of Newman's theorem, developed while teaching a class for talented high school students at Canada/USA Mathcamp. The key observation is that although Gamma_1(N) is not generated by its upper triangular and lower triangular subgroup…

On the Practicability of Ceramic-Tiled Walls for Sound Absorption by Tuning Cavities
Ozgur T. Tugut, Brahim Lemkalli, Qingxiang Ji, Mahmoud Addouche, Benjamin Vial, S\'ebastien Guenneau, Richard Craster, Claudio Bizzaglia, Bogdan Ungureanu, Muamer Kadic
https://arxiv.org/abs/2506.17699…

On the Practicability of Ceramic-Tiled Walls for Sound Absorption by Tuning Cavities
We present the practicality of structuring ceramic tiles for enhancing sound absorption on rigid walls. The cornerstone of our methodology is to structure walls with cavities so that walls effectively behave as heterogeneous absorbing surfaces over a large frequency bandwidth. Using this approach, ceramic tiled walls are developed by integrating tuned cavity structures based on Helmholtz resonators. Such a design leverages the empty joints between tiles to form resonator necks, while the space …

Sources: Anthropic has rehired Boris Cherny and Cat Wu, who developed Claude Code, just two weeks after they left for Cursor developer Anysphere (Natasha Mascarenhas/The Information)
https://www.theinformation.com/briefings/anthr…

Anthropic Hires Back Two Coding AI Leaders From Cursor Developer Anysphere 
In a surprising reversal, two leaders of Anthropic’s coding product who joined rival Anysphere two weeks ago have returned to Anthropic, according to people with direct knowledge of the move. In early July, Boris Cherny and Cat Wu left Anthropic, where they had developed a fast-growing artificial intelligence coding service, Claude Code, to join the maker of Cursor in more senior roles,

The Effect of Scale Consistency between Real and Virtual Spaces on Immersion in Exhibition Hybrid Spaces
Qiong Wu, Yan Dong, Zipeng Zhang, Ruochen Hu
https://arxiv.org/abs/2507.16542

The Effect of Scale Consistency between Real and Virtual Spaces on Immersion in Exhibition Hybrid Spaces
In exhibition hybrid spaces, scale consistency between real and virtual spaces is crucial for user immersion. However, there is currently a lack of systematic research to determine appropriate virtual-to-real mapping ratios. This study developed an immersive interaction system based on Intel 3D Athlete Tracking body mapping technology. Two experiments investigated the impact of virtual space and virtual avatar scale on immersion. Experiment 1 investigated 30 participants' preferences for virtua…

AutoWISP: Automated Processing of Wide-Field Color Images
Angel E. Romero, Kaloyan Penev, S. Javad Jafarzadeh, Zoltan Csubry, Joel D. Hartman, Gaspar A. Bakos
https://arxiv.org/abs/2507.15830

AutoWISP: Automated Processing of Wide-Field Color Images
We have developed a software pipeline, AutoWISP, for extracting high-precision photometry from citizen scientists' observations made with consumer-grade color digital cameras (digital single-lens reflex, or DSLR, cameras), based on our previously developed tool, AstroWISP. The new pipeline is designed to convert these observations, including color images, into high-precision light curves of stars. We outline the individual steps of the pipeline and present a case study using a Sony-alpha 7R II …

Modeling the position and velocity distribution of space objects by maximizing entropy with energy constraint
Partha Chowdhury, Sanat K Biswas
https://arxiv.org/abs/2506.16606

Modeling the position and velocity distribution of space objects by maximizing entropy with energy constraint
In this work, we have developed a 6-dimensional joint probability density function for the 3-dimensional position and 3-dimensional velocity vectors of space objects in the Low Earth Orbit (LEO) based on the Principle of Maximum Entropy (MaxEnt), adhering to the principle of energy conservation. For the problem under consideration, maximizing entropy subject to energy conservation ensures that the derived probability density function (PDF) is the best representation of the uncertainty of a spac…

PAC Off-Policy Prediction of Contextual Bandits
Yilong Wan, Yuqiang Li, Xianyi Wu
https://arxiv.org/abs/2507.16236 https://arxiv.org/…

PAC Off-Policy Prediction of Contextual Bandits
This paper investigates off-policy evaluation in contextual bandits, aiming to quantify the performance of a target policy using data collected under a different and potentially unknown behavior policy. Recently, methods based on conformal prediction have been developed to construct reliable prediction intervals that guarantee marginal coverage in finite samples, making them particularly suited for safety-critical applications. To further achieve coverage conditional on a given offline data set…

Semantic Scaffolding: Augmenting Textual Structures with Domain-Specific Groupings for Accessible Data Exploration
Jonathan Zong, Isabella Pedraza Pineros, Mengzhu Katie Chen, Daniel Hajas, Arvind Satyanarayan
https://arxiv.org/abs/2506.15883

Semantic Scaffolding: Augmenting Textual Structures with Domain-Specific Groupings for Accessible Data Exploration
Drawing connections between interesting groupings of data and their real-world meaning is an important, yet difficult, part of encountering a new dataset. A lay reader might see an interesting visual pattern in a chart but lack the domain expertise to explain its meaning. Or, a reader might be familiar with a real-world concept but struggle to express it in terms of a dataset's fields. In response, we developed semantic scaffolding, a technique for using domain-specific information from large l…

AI-Assisted Fixes to Code Review Comments at Scale
Chandra Maddila, Negar Ghorbani, James Saindon, Parth Thakkar, Vijayaraghavan Murali, Rui Abreu, Jingyue Shen, Brian Zhou, Nachiappan Nagappan, Peter C. Rigby
https://arxiv.org/abs/2507.13499

AI-Assisted Fixes to Code Review Comments at Scale
Aim. There are 10s of thousands of code review comments each week at Meta. We developed Metamate for Code Review (MetaMateCR) that provides AI-assisted fixes for reviewer comments in production at scale. Method. We developed an internal benchmark of 64k data points to fine-tune Llama models. Once our models achieve reasonable offline results, we roll them into production. To ensure that our AI-assisted fixes do not negatively impact the time it takes to do code reviews…

How an open-source approach helped DeepSeek and other Chinese AI companies; Hugging Face: Alibaba's Qwen is now the world's largest open-source AI ecosystem (South China Morning Post)
https://www.scmp.com/tech/big-tech/article

How open-source AI is helping China win hearts and market share
China’s free-for-all AI models, developed by firms like DeepSeek and Alibaba, present a viable alternative to US closed-source systems.

Exploring the Usage of Generative AI for Group Project-Based Offline Art Courses in Elementary Schools
Zhiqing Wang, Haoxiang Fan, Shiwei Wu, Qiaoyi Chen, Yongqi Liang, Zhenhui Peng
https://arxiv.org/abs/2506.16874

Exploring the Usage of Generative AI for Group Project-Based Offline Art Courses in Elementary Schools
The integration of Generative Artificial Intelligence (GenAI) in K-6 project-based art courses presents both opportunities and challenges for enhancing creativity, engagement, and group collaboration. This study introduces a four-phase field study, involving in total two experienced K-6 art teachers and 132 students in eight offline course sessions, to investigate the usage and impact of GenAI. Specifically, based on findings in Phases 1 and 2, we developed AskArt, an interactive interface that…

LOCOFY Large Design Models -- Design to code conversion solution
Sohaib Muhammad, Ashwati Vipin, Karan Shetti, Honey Mittal
https://arxiv.org/abs/2507.16208

LOCOFY Large Design Models -- Design to code conversion solution
Despite rapid advances in Large Language Models and Multimodal Large Language Models (LLMs), numerous challenges related to interpretability, scalability, resource requirements and repeatability remain, related to their application in the design-to-code space. To address this, we introduce the Large Design Models (LDMs) paradigm specifically trained on designs and webpages to enable seamless conversion from design-to-code. We have developed a training and inference pipeline by incorporating dat…