Tootfinder

PE firm Advent International agrees to acquire U-blox, a SIX Swiss Exchange-listed wireless and positioning chipmaker, for about $1.3B via public tender offer (Andrea Figueras/Wall Street Journal)
https://www.wsj.com/business/de…

With the advent of Blacksky and Northsky, I was seriously considering creating a bsky account and checking things out over there. Turns out I don't need to after all!
https://mastodon.murkworks.net/@moira/115402352112431443

Beam Squint Assisted Joint Angle-Distance Localization for Near-Field Communications
Aibiao Zhang, Weizheng Zhang, Chiya Zhang
https://arxiv.org/abs/2509.14850 https://

Beam Squint Assisted Joint Angle-Distance Localization for Near-Field Communications
With the advent of extremely large-scale MIMO (XL-MIMO), mmWave/THz bands and ultra-wideband transmission, future 6G systems demand real-time positioning with centimeter or even millimeter level accuracy. This paper addresses the pronounced near-field beam squint problem caused by phase shifter based beamforming in wideband near-field scenarios and proposes a beam squint assisted joint angle-distance localization scheme. The key idea is to employ true-time-delay (TTD) units together with phase …

See, Think, Act: Teaching Multimodal Agents to Effectively Interact with GUI by Identifying Toggles
Zongru Wu, Rui Mao, Zhiyuan Tian, Pengzhou Cheng, Tianjie Ju, Zheng Wu, Lingzhong Dong, Haiyue Sheng, Zhuosheng Zhang, Gongshen Liu
https://arxiv.org/abs/2509.13615

See, Think, Act: Teaching Multimodal Agents to Effectively Interact with GUI by Identifying Toggles
The advent of multimodal agents facilitates effective interaction within graphical user interface (GUI), especially in ubiquitous GUI control. However, their inability to reliably execute toggle control instructions remains a key bottleneck. To investigate this, we construct a state control benchmark with binary toggle instructions from public datasets. Evaluations of existing agents demonstrate their unreliability, particularly when the current toggle state already matches the desired state. T…

TRACY: Benchmarking Execution Efficiency of LLM-Based Code Translation
Zhihao Gong, Zeyu Sun, Dong Huang, Qingyuan Liang, Jie M. Zhang, Dan Hao
https://arxiv.org/abs/2508.11468 …

TRACY: Benchmarking Execution Efficiency of LLM-Based Code Translation
Automatic code translation is a fundamental task in modern software development. While the advent of Large Language Models (LLMs) has significantly improved the correctness of code translation, the critical dimension of execution efficiency remains overlooked. To address this gap, we introduce TRACY, the first comprehensive benchmark designed to evaluate the execution efficiency of LLM-translated code. TRACY is constructed through an LLM-driven two-stage pipeline: an initial stage generates a s…

Open Letter to Deezer on the Advent of Track Removals #musicianresources #musiciantips https://

Open Letter to Deezer on the Advent of Track Removals
Stan Stewart - @muz4now

The Economics of Information Pollution in the Age of AI: A General Equilibrium Approach to Welfare, Measurement, and Policy
Yukun Zhang, Tianyang Zhang
https://arxiv.org/abs/2509.13729

The Economics of Information Pollution in the Age of AI: A General Equilibrium Approach to Welfare, Measurement, and Policy
The advent of Large Language Models (LLMs) represents a fundamental shock to the economics of information production. By asymmetrically collapsing the marginal cost of generating low-quality, synthetic content while leaving high-quality production costly, AI systematically incentivizes information pollution. This paper develops a general equilibrium framework to analyze this challenge. We model the strategic interactions among a monopolistic platform, profit-maximizing producers, and utility-ma…

tiktok is heading toward being full maga.
If your business or life is centered on that app, take steps now to change that.
I am happy to help however I can.
https://www.independent.co.uk/news/world/americas/us-p…

Barron Trump tipped for top job at TikTok after dad tells users they ‘owe’ him for saving platform
The president has previously claimed that users ‘owe’ Barron Trump for saving the social media platform in a video from the Oval Office

OpenCXD: An Open Real-Device-Guided Hybrid Evaluation Framework for CXL-SSDs
Hyunsun Chung, Junhyeok Park, Taewan Noh, Seonghoon Ahn, Kihwan Kim, Ming Zhao, Youngjae Kim
https://arxiv.org/abs/2508.11477

OpenCXD: An Open Real-Device-Guided Hybrid Evaluation Framework for CXL-SSDs
The advent of Compute Express Link (CXL) enables SSDs to participate in the memory hierarchy as large-capacity, byte-addressable memory devices. These CXL-enabled SSDs (CXL-SSDs) offer a promising new tier between DRAM and traditional storage, combining NAND flash density with memory-like access semantics. However, evaluating the performance of CXL-SSDs remains difficult due to the lack of hardware that natively supports the CXL.mem protocol on SSDs. As a result, most prior work relies on hybri…

Advent International agrees to acquire and take private Nasdaq-listed Sapiens International, an Israel-based insurance software company, for $2.5B in cash (Reuters)
https://www.reuters.com/world/middle-east/insurance-softwa…

TL;DR: what if instead of denying the harms of fascism, we denied its suppressive threats of punishment
Many of us have really sharpened our denial skills since the advent of the ongoing pandemic (perhaps you even hesitated at the word "ongoing" there and thought "maybe I won't read this one, it seems like it'll be tiresome"). I don't say this as a preface to a fiery condemnation or a plea to "sanity" or a bunch of evidence of how bad things are, because I too have honed my denial skills in these recent years, and I feel like talking about that development.
Denial comes in many forms, including strategic information avoidance ("I don't have time to look that up right now", "I keep forgetting to look into that", "well this author made a tiny mistake, so I'll click away and read something else", "I'm so tired of hearing about this, let me scroll farther", etc.) strategic dismissal ("look, there's a bit of uncertainty here, I should ignore this", "this doesn't line up perfectly with my anecdotal experience, it must be completely wrong", etc.) and strategic forgetting ("I don't remember what that one study said exactly; it was painful to think about", "I forgot exactly what my friend was saying when we got into that argument", etc.). It's in fact a kind of skill that you can get better at, along with the complementary skill of compartmentalization. It can of course be incredibly harmful, and a huge genre of fables exists precisely to highlight its harms, but it also has some short-term psychological benefits, chiefly in the form of muting anxiety. This is not an endorsement of denial (the harms can be catastrophic), but I want to acknowledge that there *are* short-term benefits. Via compartmentalization, it's even possible to be honest with ourselves about some of our own denials without giving them up immediately.
But as I said earlier, I'm not here to talk you out of your denials. Instead, given that we are so good at denial now, I'm here to ask you to be strategic about it. In particular, we live in a world awash with propaganda/advertising that serves both political and commercial ends. Why not use some of our denial skills to counteract that?
For example, I know quite a few people in complete denial of our current political situation, but those who aren't (including myself) often express consternation about just how many people in the country are supporting literal fascism. Of course, logically that appearance of widespread support is going to be partly a lie, given how much our public media is beholden to the fascists or outright in their side. Finding better facts on the true level of support is hard, but in the meantime, why not be in denial about the "fact" that Trump has widespread popular support?
To give another example: advertisers constantly barrage us with messages about our bodies and weight, trying to keep us insecure (and thus in the mood to spend money to "fix" the problem). For sure cutting through that bullshit by reading about body positivity etc. is a better solution, but in the meantime, why not be in denial about there being anything wrong with your body?
This kind of intentional denial certainly has its own risks (our bodies do actually need regular maintenance, for example, so complete denial on that front is risky) but there's definitely a whole lot of misinformation out there that it would be better to ignore. To the extent such denial expands to a more general denial of underlying problems, this idea of intentional denial is probably just bad. But I sure wish that in a world where people (including myself) routinely deny significant widespread dangers like COVID-19's long-term risks or the ongoing harms of escalating fascism, they'd at least also deny some of the propaganda keeping them unhappy and passive. Instead of being in denial about US-run concentration camps, why not be in denial that the state will be able to punish you for resisting them?

MVP4D: Multi-View Portrait Video Diffusion for Animatable 4D Avatars
Felix Taubner, Ruihang Zhang, Mathieu Tuli, Sherwin Bahmani, David B. Lindell
https://arxiv.org/abs/2510.12785

MVP4D: Multi-View Portrait Video Diffusion for Animatable 4D Avatars
Digital human avatars aim to simulate the dynamic appearance of humans in virtual environments, enabling immersive experiences across gaming, film, virtual reality, and more. However, the conventional process for creating and animating photorealistic human avatars is expensive and time-consuming, requiring large camera capture rigs and significant manual effort from professional 3D artists. With the advent of capable image and video generation models, recent methods enable automatic rendering o…

"The relationship between national identity and how people feel Scotland should be governed is, if anything, even bigger now than it was in 2015. In our latest survey, support for #ScottishIndependence is 60 points higher among those who say they are ‘Scottish, not British’ than it is among those who indicate they are wholly or mostly British"

Scottish Social Attitudes | 25 years of devolution in Scotland | National Centre for Social Research
This briefing charts some of the key developments in Scottish public opinion since the advent of devolution.

MATH-Beyond: A Benchmark for RL to Expand Beyond the Base Model
Prasanna Mayilvahanan, Ricardo Dominguez-Olmedo, Thadd\"aus Wiedemer, Wieland Brendel
https://arxiv.org/abs/2510.11653

MATH-Beyond: A Benchmark for RL to Expand Beyond the Base Model
With the advent of DeepSeek-R1, a new wave of reinforcement learning (RL) methods has emerged that seem to unlock stronger mathematical reasoning. However, a closer look at the open-source ecosystem reveals a critical limitation: with sufficiently many draws (e.g., $\texttt{pass@1024}$), many existing base models already solve nearly all questions on widely used math benchmarks such as MATH-500 and AIME 2024. This suggests that the RL fine-tuning methods prevalent in the LLM reasoning literatur…

Robust ML-based Detection of Conventional, LLM-Generated, and Adversarial Phishing Emails Using Advanced Text Preprocessing
Deeksha Hareesha Kulal, Chidozie Princewill Arannonu, Afsah Anwar, Nidhi Rastogi, Quamar Niyaz
https://arxiv.org/abs/2510.11915

Robust ML-based Detection of Conventional, LLM-Generated, and Adversarial Phishing Emails Using Advanced Text Preprocessing
Phishing remains a critical cybersecurity threat, especially with the advent of large language models (LLMs) capable of generating highly convincing malicious content. Unlike earlier phishing attempts which are identifiable by grammatical errors, misspellings, incorrect phrasing, and inconsistent formatting, LLM generated emails are grammatically sound, contextually relevant, and linguistically natural. These advancements make phishing emails increasingly difficult to distinguish from legitimat…

Why Report Failed Interactions With Robots?! Towards Vignette-based Interaction Quality
Agnes Axelsson, Merle Reimann, Ronald Cumbal, Hannah Pelikan, Divesh Lala
https://arxiv.org/abs/2508.10603

Why Report Failed Interactions With Robots?! Towards Vignette-based Interaction Quality
Although the quality of human-robot interactions has improved with the advent of LLMs, there are still various factors that cause systems to be sub-optimal when compared to human-human interactions. The nature and criticality of failures are often dependent on the context of the interaction and so cannot be generalized across the wide range of scenarios and experiments which have been implemented in HRI research. In this work we propose the use of a technique overlooked in the field of HRI, eth…

Interference between non-overlapping waves
Alan C. Santos, Celso J. Villas-Boas
https://arxiv.org/abs/2508.10622 https://arxiv.org/pdf/2508.10622

Interference between non-overlapping waves
In classical mechanics and electromagnetism, interference occurs when two or more waves overlap at the same point in spacetime. However, the advent of quantum electrodynamics (QED) and its remarkable success in describing light-matter interactions at the microscopic level invites us to reconsider whether interference-like effects could arise even when the waves do not physically overlap. In this work, we extend the notion of wave interference to a novel and unconventional regime. Building upon …

SABR: A Stable Adaptive Bitrate Framework Using Behavior Cloning Pretraining and Reinforcement Learning Fine-Tuning
Pengcheng Luo, Yunyang Zhao, Bowen Zhang, Genke Yang, Boon-Hee Soong, Chau Yuen
https://arxiv.org/abs/2509.10486

SABR: A Stable Adaptive Bitrate Framework Using Behavior Cloning Pretraining and Reinforcement Learning Fine-Tuning
With the advent of 5G, the internet has entered a new video-centric era. From short-video platforms like TikTok to long-video platforms like Bilibili, online video services are reshaping user consumption habits. Adaptive Bitrate (ABR) control is widely recognized as a critical factor influencing Quality of Experience (QoE). Recent learning-based ABR methods have attracted increasing attention. However, most of them rely on limited network trace sets during training and overlook the wide-distrib…

Fe XVIII-XXIV K beta Inner-shell Absorption Lines in the X-ray Spectra of Neutron Star and Black Hole Binaries with XRISM
Masahiro Tsujimoto, Daiki Miura, Hiroya Yamaguchi, Ehud Behar, Chris Done, Maria Diaz Trigo, Chamani M. Gunasekera, Peter A. M. van Hoof, Stefano Bianchi, Maryam Dehghanian, Gary J. Ferland
https://arxiv.org/abs/2510.12…

Fe XVIII-XXIV K beta Inner-shell Absorption Lines in the X-ray Spectra of Neutron Star and Black Hole Binaries with XRISM
The advent of the X-ray microcalorimeter spectrometer Resolve onboard the XRISM space telescope opened a new era for high-resolution X-ray spectroscopy of astrophysical plasmas. Many spectral features were newly detected, including the K alpha and K beta inner-shell transition lines of mildly ionized (F- to Li-like) Fe at 6-8 keV in the spectra of X-ray binaries and active galactic nuclei. The widely used atomic databases contain information on the K alpha but not K beta lines of these ions. We…

Hierarchical summaries for primordial non-Gaussianities
M. S. Cagliari, A. Bairagi, B. Wandelt
https://arxiv.org/abs/2510.12715 https://arxiv.org/pdf/2510.…

Hierarchical summaries for primordial non-Gaussianities
The advent of Stage IV galaxy redshift surveys such as DESI and Euclid marks the beginning of an era of precision cosmology, with one key objective being the detection of primordial non-Gaussianities (PNG), potential signatures of inflationary physics. In particular, constraining the amplitude of local-type PNG, parameterised by $f_{\rm NL}$, with $σ_{f_{\rm NL}} \sim 1$, would provide a critical test of single versus multi-field inflation scenarios. While current large-scale structure and cos…

Characterizing Web Search in The Age of Generative AI
Elisabeth Kirsten, Jost Grosse Perdekamp, Mihir Upadhyay, Krishna P. Gummadi, Muhammad Bilal Zafar
https://arxiv.org/abs/2510.11560

Characterizing Web Search in The Age of Generative AI
The advent of LLMs has given rise to a new type of web search: Generative search, where LLMs retrieve web pages related to a query and generate a single, coherent text as a response. This output modality stands in stark contrast to traditional web search, where results are returned as a ranked list of independent web pages. In this paper, we ask: Along what dimensions do generative search outputs differ from traditional web search? We compare Google, a traditional web search engine, with four g…

Ultrafast cooperative electronic, structural, and magnetic switching in an altermagnet
Tiangao Lu, Ao Wu, Junxiang Li, Meng Zeng, Di Cheng, Chang Liu, Jiangbin Gong, Xinwei Li
https://arxiv.org/abs/2509.11722

Ultrafast cooperative electronic, structural, and magnetic switching in an altermagnet
Femtosecond laser control of antiferromagnetic order is a cornerstone for future memory and logic devices operating at terahertz clock rates. The advent of altermagnets -- antiferromagnets with unconventional spin-group symmetries -- creates new opportunities in this evolving field. Here, we demonstrate ultrafast laser-induced switching in altermagnetic $α$-MnTe that orchestrates the concerted dynamics of charge, lattice, and spin degrees of freedom. Time-resolved reflectivity and birefringenc…

Spin-polarization and diode effect in thermoelectric current through altermagnet-based superconductor heterostructures
Debika Debnath, Arijit Saha, Paramita Dutta
https://arxiv.org/abs/2509.12198

Spin-polarization and diode effect in thermoelectric current through altermagnet-based superconductor heterostructures
The recent advent of a new class of magnetic material named as altermagnet (AM), characterized by a combination of momentum-dependent spin-splitting with zero net magnetization, has opened up promising prospects for spintronic applications. We theoretically explore how the altermagnetic spin-splitting affects the thermoelectric quasiparticle current in AM-based superconducting heterostructures. Our setup comprises of a bilayer system where a $d$-wave AM is proximity coupled to an ordinary $s$-w…

Cluster Models for Next-Generation, Machine-Learning-Based Energy Functions for Molecular Simulations
JingChun Wang, Meenu Upadhyay, Eric D. Boittier, Kham Lek Chaton, Valerii Andreichev, Mike Devereux, Shimoni Patel, Sena Aydin, Kai T\"opfer, Markus Meuwly
https://arxiv.org/abs/2509.11639

Cluster Models for Next-Generation, Machine-Learning-Based Energy Functions for Molecular Simulations
Energy functions for pure and heterogenous systems are one of the backbones for molecular simulation of condensed phase systems. With the advent of machine learned potential energy surfaces (ML-PESs) a new era has started. Statistical models allow the representation of reference data from electronic structure calculations for chemical systems of almost arbitrary complexity at unprecedented detail and accuracy. Here, kernel- and neural network-based approaches for intramolecular degrees of freed…

Decentralized Relaxed Smooth Optimization with Gradient Descent Methods
Zhanhong Jiang, Aditya Balu, Soumik Sarkar
https://arxiv.org/abs/2508.08413 https://

Decentralized Relaxed Smooth Optimization with Gradient Descent Methods
$L_0$-smoothness, which has been pivotal to advancing decentralized optimization theory, is often fairly restrictive for modern tasks like deep learning. The recent advent of relaxed $(L_0,L_1)$-smoothness condition enables improved convergence rates for gradient methods. Despite centralized advances, its decentralized extension remains unexplored and challenging. In this work, we propose the first general framework for decentralized gradient descent (DGD) under $(L_0,L_1)$-smoothness by introd…

Noncontact friction in ultracoherent nanomechanical resonators near dielectric materials
Amirali Arabmoheghi, Alessio Zicoschi, Guillermo Arregui, Mohammad J. Bereyhi, Yi Xia, Nils J. Engelsen, Tobias J. Kippenberg
https://arxiv.org/abs/2509.10237

Noncontact friction in ultracoherent nanomechanical resonators near dielectric materials
Micro- and nanomechanical resonators are emerging as promising platforms for quantum technologies, precision sensors and fundamental science experiments. To utilize these devices for force sensing or quantum optomechanics, they must be brought in close proximity with other systems for functionalization or efficient readout. Improved understanding of the loss mechanisms in nanomechanical resonators, specifically the advent of dissipation dilution, has led to the development of resonators with un…

"However, by 2015, support for independence stood at 52% among those on the left, compared with just 24% among those on the right – a difference of 28 points... In our most recent survey in 2024, those on the left were 34 points more likely than those on the right to say that Scotland should become an independent country"
#ScottishIndependence

Scottish Social Attitudes | 25 years of devolution in Scotland | National Centre for Social Research
This briefing charts some of the key developments in Scottish public opinion since the advent of devolution.

Millimeter-Wave Position Sensing Using Reconfigurable Intelligent Surfaces: Positioning Error Bound and Phase Shift Configuration
Xin Cheng, Guangjie Han, Menglu Li, Ruoguang Li, Feng Shu
https://arxiv.org/abs/2508.06958

Millimeter-Wave Position Sensing Using Reconfigurable Intelligent Surfaces: Positioning Error Bound and Phase Shift Configuration
Millimeter-wave (mmWave) positioning has emerged as a promising technology for next-generation intelligent systems. The advent of reconfigurable intelligent surfaces (RISs) has revolutionized high-precision mmWave localization by enabling dynamic manipulation of wireless propagation environments. This paper investigates a three-dimensional (3D) multi-input single-output (MISO) mmWave positioning system assisted by multiple RISs. We introduce a measurement framework incorporating sequential RIS …

Cardiotensor: A Python Library for Orientation Analysis and Tractography in 3D Cardiac Imaging
Joseph Brunet, Lisa Chestnutt, Matthieu Chourrout, Hector Dejea, Vaishnavi Sabarigirivasan, Peter D. Lee, Andrew C. Cook
https://arxiv.org/abs/2508.07476

Cardiotensor: A Python Library for Orientation Analysis and Tractography in 3D Cardiac Imaging
Understanding the architecture of the human heart requires analysis of its microstructural organization across scales. With the advent of high-resolution imaging techniques such as synchrotron-based tomography, it has become possible to visualize entire hearts at micron-scale resolution. However, translating these large, complex volumetric datasets into interpretable, quantitative descriptors of cardiac organization remains a major challenge. Here we present cardiotensor, an open-source Python …

A neural network model for quickly solving multiple-band light curves of contact binaries
Kai Li, Li-Heng Wang, Xiang Gao
https://arxiv.org/abs/2509.08189 https://

A neural network model for quickly solving multiple-band light curves of contact binaries
The advent of large-scale photometric surveys has led to the discovery of over a million contact binary systems. Conventional light curve analysis methods are no longer adequate for handling such massive datasets. To address this challenge, we developed a neural network-based model capable of rapid analysis of multiple-band light curves of contact binaries. Our model can determine the fundamental physical parameters, including temperature and mass ratios, orbital inclination, potential, fillout…

Direct Nuclear-Level Qubits using Trapped Th-229 Ions: A Platform for Entanglement and Universal Quantum Information Processing
Jingbo Wang, Haixing Miao, Shiqian Ding, Dong E. Liu
https://arxiv.org/abs/2508.10626

Direct Nuclear-Level Qubits using Trapped Th-229 Ions: A Platform for Entanglement and Universal Quantum Information Processing
The low-energy isomeric transition in Thorium-229 offers a unique interface between nuclear and atomic physics, presenting a resource for quantum technologies that is notably resilient to environmental decoherence. While early experiments focused on nuclei in solid-state crystals, the recent advent of a continuous-wave vacuum ultraviolet laser at 148.4~nm now enables direct coherent control of individual trapped Th-229 ions. Building on this breakthrough, we present a theoretical framework for …

Exploring Palette based Color Guidance in Diffusion Models
Qianru Qiu, Jiafeng Mao, Xueting Wang
https://arxiv.org/abs/2508.08754 https://arxiv.org/pdf/250…

Exploring Palette based Color Guidance in Diffusion Models
With the advent of diffusion models, Text-to-Image (T2I) generation has seen substantial advancements. Current T2I models allow users to specify object colors using linguistic color names, and some methods aim to personalize color-object association through prompt learning. However, existing models struggle to provide comprehensive control over the color schemes of an entire image, especially for background elements and less prominent objects not explicitly mentioned in prompts. This paper prop…

TURA: Tool-Augmented Unified Retrieval Agent for AI Search
Zhejun Zhao, Yuehu Dong, Alley Liu, Lixue Zheng, Pingsheng Liu, Dongdong Shen, Long Xia, Jiashu Zhao, Dawei Yin
https://arxiv.org/abs/2508.04604

TURA: Tool-Augmented Unified Retrieval Agent for AI Search
The advent of Large Language Models (LLMs) is transforming search engines into conversational AI search products, primarily using Retrieval-Augmented Generation (RAG) on web corpora. However, this paradigm has significant industrial limitations. Traditional RAG approaches struggle with real-time needs and structured queries that require accessing dynamically generated content like ticket availability or inventory. Limited to indexing static pages, search engines cannot perform the interactive q…

When Competition Helps: Achieving Optimal Traffic Flow with Multiple Autonomous Planners
Ivan Geffner, Erez Karpas, Moshe Tennenholtz
https://arxiv.org/abs/2508.07145 https://…

When Competition Helps: Achieving Optimal Traffic Flow with Multiple Autonomous Planners
The inefficiency of selfish routing in congested networks is a classical problem in algorithmic game theory, often captured by the Price of Anarchy (i.e., the ratio between the social cost of decentralized decisions and that of a centrally optimized solution.) With the advent of autonomous vehicles, capable of receiving and executing centrally assigned routes, it is natural to ask whether their deployment can eliminate this inefficiency. At first glance, a central authority could simply compute…

Faint southern spectrophotometric standard stars
N. P. Gentile Fusillo, S. Moehler, N. Przybilla, A. K. Elms, P. -E. Tremblay, W. Kausch, F. Kerber
https://arxiv.org/abs/2508.05758

Faint southern spectrophotometric standard stars
Context. The advent of the Extremely Large Telescope (ELT) will increase the collecting area by more than an order of magnitude compared to the individual Unit Telescopes of the Very Large Telescope (VLT). Fainter spectrophotometric standard stars than those currently available in the V = 11 to 13 mag (K = 12 to 14 mag) range are required for spectroscopic observations with instruments such as the Multi-AO Imaging Camera for Deep Observations (MICADO) on the ELT, notably in the near-infrared wa…

Assessing the Impact of Post-Quantum Digital Signature Algorithms on Blockchains
Alison Gon\c{c}alves Schemitt (PUCRS), Henrique Fan da Silva (UNIPAMPA), Roben Castagna Lunardi (PUCRS, IFRS), Diego Kreutz (UNIPAMPA), Rodrigo Brand\~ao Mansilha (UNIPAMPA), Avelino Francisco Zorzo (PUCRS)
https://arxiv.org/abs/2510.09271

Assessing the Impact of Post-Quantum Digital Signature Algorithms on Blockchains
The advent of quantum computing threatens the security of traditional encryption algorithms, motivating the development of post-quantum cryptography (PQC). In 2024, the National Institute of Standards and Technology (NIST) standardized several PQC algorithms, marking an important milestone in the transition toward quantum-resistant security. Blockchain systems fundamentally rely on cryptographic primitives to guarantee data integrity and transaction authenticity. However, widely used algorithms…

Hybrid-Locked Kerr Microcombs for Flexible On-Chip Optical Clock Division
Andrei Diakonov, Konstantin Khrizman, Liron Stern
https://arxiv.org/abs/2508.07258 https://

Hybrid-Locked Kerr Microcombs for Flexible On-Chip Optical Clock Division
Optical atomic clocks deliver unrivaled precision, yet their size and complexity still confine them to specialized laboratories. Frequency combs provide the crucial optical-to-microwave division needed for clock readout, but conventional fiber- or bulk-laser combs are far too large for portable use. The advent of chip-integrated microcombs, frequency combs generated in micron-scale resonators, has revolutionized this landscape, enabling fully miniaturized, low-power clocks that bridge optical a…

32 Millionen Schulden - Stadt muss heuer sogar den Advent „einsparen“ #News #Nachrichten

Feedback That Clicks: Introductory Physics Students' Valued Features in AI Feedback Generated From Self-Crafted and Engineered Prompts
Amogh Sirnoorkar, N. Sanjay Rebello
https://arxiv.org/abs/2509.08516

Feedback That Clicks: Introductory Physics Students' Valued Features in AI Feedback Generated From Self-Crafted and Engineered Prompts
Since the advent of GPT-3.5 in 2022, Generative Artificial Intelligence (AI) has shown tremendous potential in STEM education, particularly in providing real-time, customized feedback to students in large-enrollment courses. A crucial skill that mediates effective use of AI is the systematic structuring of natural language instructions to AI models, commonly referred to as prompt engineering. This study has three objectives: (i) to investigate the sophistication of student-generated prompts whe…

Accretion onto Reissner-Nordstr\"{o}m naked singularities
Tomasz Krajewski, W{\l}odek Klu\'zniak
https://arxiv.org/abs/2510.10043 https://arxiv.or…

Accretion onto Reissner-Nordström naked singularities
Nearly every galactic core contains a supermassive compact object, hypothesized to be a Kerr black hole. It was only with the advent of Event Horizon Telescope observations that the predictions of this hypothesis could be observationally tested for our own Galaxy, and the nearby elliptical M87, on spatial scales comparable to the gravitational radius. At the same time it became possible to test whether alternatives such as naked singularities in general relativity, or similar objects in alterna…

Visible Light Communication for Vehicular Networks: A Tutorial
Pedro E. G\'oria Silva, Eduardo S. Lima, Jules M. Moualeu, Mohamed Korium, Pedro H. J. Nardelli
https://arxiv.org/abs/2510.11123

Visible Light Communication for Vehicular Networks: A Tutorial
The advent of the fifth-generation technology promises to bring about more vertical applications and emerging services that include vehicular networks and intelligent transportation systems (ITSs). To achieve their vision of real-time and safetyapplications, vehicular networks rely on short-range to medium-range communications. One emerging technology that aims to provide reliability and high-data rate in short-range communications is the visible light communications (VLC). Due to its remarkabl…

Resolving Tangling in Multi-Conformer Refinement via Iterative Projections
Avinash Mandaiya, Veit Elser
https://arxiv.org/abs/2509.05189 https://arxiv.org/…

Resolving Tangling in Multi-Conformer Refinement via Iterative Projections
The advent of advanced crystallographic techniques has shifted structural biology from static, single-conformer models toward probing protein dynamics. Extracting cooperative motions from temporally and spatially averaged electron density maps requires both high-resolution data and refinement algorithms capable of handling conformational heterogeneity. However, current refinement protocols often fail due to the tangling phenomenon, in which conformational states become improperly intertwined du…

Eat your own KR: a KR-based approach to index Semantic Web Endpoints and Knowledge Graphs
Pierre Maillot (WIMMICS), Catherine Faron (UniCA, I3S, WIMMICS), Fabien Gandon (WIMMICS), Franck Michel (Laboratoire I3S - SPARKS, WIMMICS), Pierre Monnin (WIMMICS)
https://arxiv.org/abs/2508.08713

Eat your own KR: a KR-based approach to index Semantic Web Endpoints and Knowledge Graphs
Over the last decade, knowledge graphs have multiplied, grown, and evolved on the World Wide Web, and the advent of new standards, vocabularies, and application domains has accelerated this trend. IndeGx is a framework leveraging an extensible base of rules to index the content of KGs and the capacities of their SPARQL endpoints. In this article, we show how knowledge representation (KR) and reasoning methods and techniques can be used in a reflexive manner to index and characterize existing kn…

Hydrogen-Alpha as a Tracer of Star Formation in the SPHINX Cosmological Simulations
I. G. Kramarenko, J. Rosdahl, J. Blaizot, J. Matthee, H. Katz, C. Di Cesare
https://arxiv.org/abs/2509.05403

Hydrogen-Alpha as a Tracer of Star Formation in the SPHINX Cosmological Simulations
The Hydrogen-alpha (Ha) emission line in galaxies is a powerful tracer of their recent star formation activity. With the advent of JWST, we are now able to routinely observe Ha in galaxies at high redshifts (z > 3) and thus measure their star-formation rates (SFRs). However, using "classical" SFR(Ha) calibrations to derive the SFRs leads to biased results because high-redshift galaxies are commonly characterized by low metallicities and bursty star-formation histories, affecting the conversion …

MultiCNKG: Integrating Cognitive Neuroscience, Gene, and Disease Knowledge Graphs Using Large Language Models
Ali Sarabadani, Kheirolah Rahsepar Fard
https://arxiv.org/abs/2510.06742

MultiCNKG: Integrating Cognitive Neuroscience, Gene, and Disease Knowledge Graphs Using Large Language Models
The advent of large language models (LLMs) has revolutionized the integration of knowledge graphs (KGs) in biomedical and cognitive sciences, overcoming limitations in traditional machine learning methods for capturing intricate semantic links among genes, diseases, and cognitive processes. We introduce MultiCNKG, an innovative framework that merges three key knowledge sources: the Cognitive Neuroscience Knowledge Graph (CNKG) with 2.9K nodes and 4.3K edges across 9 node types and 20 edge types…

Metamaterials and Fluid Flows
Francesco Avallone, Federico Bosia, Yi Chen, Giada Colombo, Richard Craster, Jacopo Maria De Ponti, Nicol\`o Fabbiane, Michael R. Haberman, Mahmoud I. Hussein, Wontae Hwang, Umberto Iemma, Abigail Juhl, Muamer Kadic, Marios Kotsonis, Vincent Laude, Olivier Marquet, Fabien Mery, Theodoros Michelis, Mostafa Nouh, Daniele Ragni, Marie Touboul, Martin Wegener, Anastasiia O. Krushynska

Metamaterials and Fluid Flows
Understanding and controlling the dynamic interactions between fluid flows and solid materials and structures-a field known as fluid-structure interaction -is central not only to established disciplines such as aerospace and naval engineering but also to emerging technologies such as energy harvesting, soft robotics, and biomedical devices. In recent years, the advent of metamaterials-rationally designed composites with properties beyond their constituents, often not found in conventional mater…

Controllable Audio-Visual Viewpoint Generation from 360{\deg} Spatial Information
Christian Marinoni, Riccardo Fosco Gramaccioni, Eleonora Grassucci, Danilo Comminiello
https://arxiv.org/abs/2510.06060

Controllable Audio-Visual Viewpoint Generation from 360° Spatial Information
The generation of sounding videos has seen significant advancements with the advent of diffusion models. However, existing methods often lack the fine-grained control needed to generate viewpoint-specific content from larger, immersive 360-degree environments. This limitation restricts the creation of audio-visual experiences that are aware of off-camera events. To the best of our knowledge, this is the first work to introduce a framework for controllable audio-visual generation, addressing thi…

A comparison between geostatistical and machine learning models for spatio-temporal prediction of PM2.5 data
Zeinab Mohamed, Wenlong Gong
https://arxiv.org/abs/2509.12051 https:…

A comparison between geostatistical and machine learning models for spatio-temporal prediction of PM2.5 data
Ambient air pollution poses significant health and environmental challenges. Exposure to high concentrations of PM$_{2.5}$ have been linked to increased respiratory and cardiovascular hospital admissions, more emergency department visits and deaths. Traditional air quality monitoring systems such as EPA-certified stations provide limited spatial and temporal data. The advent of low-cost sensors has dramatically improved the granularity of air quality data, enabling real-time, high-resolution mo…

The Memory Wars: AI Memory, Network Effects, and the Geopolitics of Cognitive Sovereignty
Mario Brcic
https://arxiv.org/abs/2508.05867 https://arxiv.org/pd…

The Memory Wars: AI Memory, Network Effects, and the Geopolitics of Cognitive Sovereignty
The advent of continuously learning Artificial Intelligence (AI) assistants marks a paradigm shift from episodic interactions to persistent, memory-driven relationships. This paper introduces the concept of "Cognitive Sovereignty", the ability of individuals, groups, and nations to maintain autonomous thought and preserve identity in the age of powerful AI systems, especially those that hold their deep personal memory. It argues that the primary risk of these technologies transcends traditional…

Detectors and Shieldings: Past and Future at LUNA
Chemseddine Ananna, Lucia Barbieri, Axel Boeltzig, Matteo Campostrini, Fausto Casaburo, Alessandro Compagnucci, Laszlo Csedreki, Riccardo Maria Gesue, Jordan Marsh, Daniela Mercogliano, Denise Piatti, Duncan Robb, Ragandeep Singh Sidhu, Jakub Skowronski
https://arxiv.org/abs/2510.06269

Detectors and Shieldings: Past and Future at LUNA
Nuclear reactions are responsible for the chemical evolution of stars, galaxies and the Universe. Unfortunately, at temperatures of interest for nuclear astrophysics, the cross-sections of the thermonuclear reactions are in the pico-femto-barn range and thus measuring them in the laboratory is extremely challenging. In this framework, major steps forward were made with the advent of underground nuclear astrophysics, pioneered by the Laboratory for Underground Nuclear Astrophysics (LUNA). The co…

Non-Verbal Vocalisations and their Challenges: Emotion, Privacy, Sparseness, and Real Life
Anton Batliner, Shahin Amiriparian, Bj\"orn W. Schuller
https://arxiv.org/abs/2508.01960

Non-Verbal Vocalisations and their Challenges: Emotion, Privacy, Sparseness, and Real Life
Non-Verbal Vocalisations (NVVs) are short `non-word' utterances without proper linguistic (semantic) meaning but conveying connotations -- be this emotions/affects or other paralinguistic information. We start this contribution with a historic sketch: how they were addressed in psychology and linguistics in the last two centuries, how they were neglected later on, and how they came to the fore with the advent of emotion research. We then give an overview of types of NVVs (formal aspects) and fu…

GSM: GPU Accelerated Rare Events Sampling with Machine Learning Potentials
Haoting Zhang, Jiuyang Shi, Qiuhan Jia, Junjie Wang, Jian Sun
https://arxiv.org/abs/2510.06873 https:/…

GSM: GPU Accelerated Rare Events Sampling with Machine Learning Potentials
Enhanced sampling has achieved considerable success in molecular dynamics (MD) simulations of rare events. Metadynamics (MetaD), owing to its excellent compatibility with MD engines, became one of the most popular enhanced sampling methods. With the boom of GPU computing and the advent of machine learning potentials (MLPs), high-accuracy, large-scale MD simulations have gradually become feasible. However, the corresponding GPU-based enhanced sampling tools have not yet been well adapted to this…

The Role of Logic and Automata in Understanding Transformers
Anthony W. Lin, Pablo Barcelo
https://arxiv.org/abs/2509.24024 https://arxiv.org/pdf/2509.2402…

The Role of Logic and Automata in Understanding Transformers
The advent of transformers has in recent years led to powerful and revolutionary Large Language Models (LLMs). Despite this, our understanding on the capability of transformers is still meager. In this invited contribution, we recount the rapid progress in the last few years to the question of what transformers can do. In particular, we will see the integral role of logic and automata (also with some help from circuit complexity) in answering this question. We also mention several open problems…

New on #Quansight PBC blog: Python Wheels: from Tags to Variants
#Python distributions are uniform across different Python versions and platforms. For these distributions, it is sufficient to publish a single wheel that can be installed everywhere. However, some packages are more complex than that; they include compiled Python extensions or binaries. In order to robustly deploy these software on different platforms, you need to publish multiple binary packages, and the installers need to select the one that fits the platform used best.
For a long time, Python wheels made do with a relatively simple mechanism to describe the needed variance: Platform compatibility tags. These tags identified different Python implementations and versions, operating systems, and CPU architectures. Over time, they were extended to facilitate new use cases. To list a couple: PEP 513 added manylinux tags to standardize the core library dependencies on GNU/Linux systems, and PEP 656 added musllinux tags to facilitate Linux systems with musl libc.
However, not all new use cases can be handled effectively within the framework of tags. To list a few:
• The advent of GPU-backed computing made distinguishing different acceleration frameworks such as NVIDIA CUDA or AMD ROCm important.
• As the compatibility with older CPUs became less desirable, many distributions have set baselines for their binary packages to x86-64-v2 microarchitecture level, and Python packages need to be able to express the same requirement.
• Numerical libraries support different BLAS/LAPACK, MPI, OpenMP providers, and wish to enable the users to choose the build matching their desired provider.
While tags could technically be bent to facilitate all these use cases, they would grow quite baroque, and, critically, every change to tags needs to be implemented in all installers and package-related tooling separately, making the adoption difficult.
Facing these limitations, software vendors have employed different solutions to work around the lack of an appropriate mechanism. Eventually, the #WheelNext initiative took up the challenge to design a more robust solution.
"""
#packaging

From Faraday and Maxwell to Quantum Physics. The later story of the Electromagnetic Vector Potential
Tuck Choy, Miguel Ortuno
https://arxiv.org/abs/2509.04486 https://

From Faraday and Maxwell to Quantum Physics. The later story of the Electromagnetic Vector Potential
With the advent of quantum mechanics by Heisenberg in 1925 exactly a century ago, the quantization of the electromagnetic field became an important goal for our founding fathers, whom we are here to celebrate. It was realized very soon that a consistent picture of quantum electrodynamics (QED) requires the quantization of not just the electromagnetic field ${\bf A}({\bf r},t)$, but the electron field ${\bf ψ}({\bf r},t)$ as well. The electron field is now a Dirac spinor field and it becomes a …

5G Core Fault Detection and Root Cause Analysis using Machine Learning and Generative AI
Joseph H. R. Isaac, Harish Saradagam, Nallamothu Pardhasaradhi
https://arxiv.org/abs/2508.09152

5G Core Fault Detection and Root Cause Analysis using Machine Learning and Generative AI
With the advent of 5G networks and technologies, ensuring the integrity and performance of packet core traffic is paramount. During network analysis, test files such as Packet Capture (PCAP) files and log files will contain errors if present in the system that must be resolved for better overall network performance, such as connectivity strength and handover quality. Current methods require numerous person-hours to sort out testing results and find the faults. This paper presents a novel AI/ML-…

A Comparative Study of Classical and Post-Quantum Cryptographic Algorithms in the Era of Quantum Computing
Arimondo Scrivano
https://arxiv.org/abs/2508.00832 https://

A Comparative Study of Classical and Post-Quantum Cryptographic Algorithms in the Era of Quantum Computing
The advent of quantum computing poses a significant threat to the foundational cryptographic algorithms that secure modern digital communications. Protocols such as HTTPS, digital certificates, and public key infrastructures (PKIs) heavily rely on cryptographic primitives like RSA, ECC, and Diffie-Hellman, which are vulnerable to quantum attacks -- most notably Shor's algorithm. This paper presents a comprehensive comparative analysis between classical cryptographic algorithms currently in wide…

A Pathway to Practical Quantum Advantage in Solving Navier-Stokes Equations
Xi-Ning Zhuang, Zhao-Yun Chen, Ming-Yang Tan, Jiaxuan Zhang, Chuang-Chao Ye, Tian-Hao Wei, Teng-Yang Ma, Cheng Xue, Huan-Yu Liu, Qing-Song Li, Tai-Ping Sun, Xiao-Fan Xu, Yun-Jie Wang, Yu-Chun Wu, Guo-Ping Guo
https://arxiv.org/abs/2509.08807

A Pathway to Practical Quantum Advantage in Solving Navier-Stokes Equations
The advent of fault-tolerant quantum computing (FTQC) promises to tackle classically intractable problems. A key milestone is solving the Navier-Stokes equations (NSE), which has remained formidable for quantum algorithms due to their high input-output overhead and nonlinearity. Here, we establish a full-stack framework that charts a practical pathway to a quantum advantage for large-scale NSE simulation. Our approach integrates a spectral-based input/output algorithm, an explicit and synthesiz…

Order Book Filtration and Directional Signal Extraction at High Frequency
Aditya Nittur Anantha, Shashi Jain, Prithwish Maiti
https://arxiv.org/abs/2507.22712 https://

Order Book Filtration and Directional Signal Extraction at High Frequency
With the advent of electronic capital markets and algorithmic trading agents, the number of events in tick-by-tick market data has exploded. A large fraction of these orders is transient. Their ephemeral character degrades the informativeness of directional alphas derived from the limit order book (LOB) state. We investigate whether directional signals such as order book imbalance (OBI) can be improved by structurally filtering high-frequency LOB data. Three real-time, observable filtration sch…

Can LLMs effectively provide game-theoretic-based scenarios for cybersecurity?
Daniele Proverbio, Alessio Buscemi, Alessandro Di Stefano, The Anh Han, German Castignani, Pietro Li\`o
https://arxiv.org/abs/2508.05670

Can LLMs effectively provide game-theoretic-based scenarios for cybersecurity?
Game theory has long served as a foundational tool in cybersecurity to test, predict, and design strategic interactions between attackers and defenders. The recent advent of Large Language Models (LLMs) offers new tools and challenges for the security of computer systems; In this work, we investigate whether classical game-theoretic frameworks can effectively capture the behaviours of LLM-driven actors and bots. Using a reproducible framework for game-theoretic LLM agents, we investigate two ca…

FreshBrew: A Benchmark for Evaluating AI Agents on Java Code Migration
Victor May, Diganta Misra, Yanqi Luo, Anjali Sridhar, Justine Gehring, Silvio Soares Ribeiro Junior
https://arxiv.org/abs/2510.04852

FreshBrew: A Benchmark for Evaluating AI Agents on Java Code Migration
AI coding assistants are rapidly becoming integral to modern software development. A key challenge in this space is the continual need to migrate and modernize codebases in response to evolving software ecosystems. Traditionally, such migrations have relied on rule-based systems and human intervention. With the advent of powerful large language models (LLMs), AI-driven agentic frameworks offer a promising alternative-but their effectiveness has not been systematically evaluated. In this paper, …

A Survey of LLM-based Deep Search Agents: Paradigm, Optimization, Evaluation, and Challenges
Yunjia Xi, Jianghao Lin, Yongzhao Xiao, Zheli Zhou, Rong Shan, Te Gao, Jiachen Zhu, Weiwen Liu, Yong Yu, Weinan Zhang
https://arxiv.org/abs/2508.05668

A Survey of LLM-based Deep Search Agents: Paradigm, Optimization, Evaluation, and Challenges
The advent of Large Language Models (LLMs) has significantly revolutionized web search. The emergence of LLM-based Search Agents marks a pivotal shift towards deeper, dynamic, autonomous information seeking. These agents can comprehend user intentions and environmental context and execute multi-turn retrieval with dynamic planning, extending search capabilities far beyond the web. Leading examples like OpenAI's Deep Research highlight their potential for deep information mining and real-world a…

Can World Models Benefit VLMs for World Dynamics?
Kevin Zhang, Kuangzhi Ge, Xiaowei Chi, Renrui Zhang, Shaojun Shi, Zhen Dong, Sirui Han, Shanghang Zhang
https://arxiv.org/abs/2510.00855

Can World Models Benefit VLMs for World Dynamics?
Trained on internet-scale video data, generative world models are increasingly recognized as powerful world simulators that can generate consistent and plausible dynamics over structure, motion, and physics. This raises a natural question: with the advent of strong video foundational models, might they supplant conventional vision encoder paradigms for general-purpose multimodal understanding? While recent studies have begun to explore the potential of world models on common vision tasks, these…

Beyond the Hook: Predicting Billboard Hot 100 Chart Inclusion with Machine Learning from Streaming, Audio Signals, and Perceptual Features
Christos Mountzouris
https://arxiv.org/abs/2509.24856

Beyond the Hook: Predicting Billboard Hot 100 Chart Inclusion with Machine Learning from Streaming, Audio Signals, and Perceptual Features
The advent of digital streaming platforms have recently revolutionized the landscape of music industry, with the ensuing digitalization providing structured data collections that open new research avenues for investigating popularity dynamics and mainstream success. The present work explored which determinants hold the strongest predictive influence for a track's inclusion in the Billboard Hot 100 charts, including streaming popularity, measurable audio signal attributes, and probabilistic indi…

Role of Plaquette Term in Genuine $2 1$D String Dynamics on Quantum Simulators
Yizhuo Tian, N. S. Srivatsa, Kaidi Xu, Jesse J. Osborne, Umberto Borla, Jad C. Halimeh
https://arxiv.org/abs/2508.05736

Role of Plaquette Term in Genuine $2+1$D String Dynamics on Quantum Simulators
With the advent of quantum simulators of $2+1$D lattice gauge theories (LGTs), a fundamental open question is under what circumstances the observed physics is genuinely $2+1$D rather than effectively $1+1$D. Here, we address this question in the ongoing strong effort to quantum-simulate string dynamics in $2+1$D LGTs on state-of-the-art quantum hardware. Through tensor network simulations and analytic derivations, we show that the plaquette term, which represents a magnetic field and only emerg…

Near-Field Communication with Massive Movable Antennas: A Functional Perspective
Shicong Liu, Xianghao Yu, Jie Xu, Rui Zhang
https://arxiv.org/abs/2508.01201 https://

Near-Field Communication with Massive Movable Antennas: A Functional Perspective
The advent of massive multiple-input multiple-output (MIMO) technology has provided new opportunities for capacity improvement via strategic antenna deployment, especially when the near-field effect is pronounced due to antenna proliferation. In this paper, we investigate the optimal antenna placement for maximizing the achievable rate of a point-to-point near-field channel, where the transmitter is deployed with massive movable antennas. First, we propose a novel design framework to explore th…

Knowledge Extraction on Semi-Structured Content: Does It Remain Relevant for Question Answering in the Era of LLMs?
Kai Sun, Yin Huang, Srishti Mehra, Mohammad Kachuee, Xilun Chen, Renjie Tao, Zhaojiang Lin, Andrea Jessee, Nirav Shah, Alex Betty, Yue Liu, Anuj Kumar, Wen-tau Yih, Xin Luna Dong
https://arxiv.org/abs/2509.25107

Knowledge Extraction on Semi-Structured Content: Does It Remain Relevant for Question Answering in the Era of LLMs?
The advent of Large Language Models (LLMs) has significantly advanced web-based Question Answering (QA) systems over semi-structured content, raising questions about the continued utility of knowledge extraction for question answering. This paper investigates the value of triple extraction in this new paradigm by extending an existing benchmark with knowledge extraction annotations and evaluating commercial and open-source LLMs of varying sizes. Our results show that web-scale knowledge extract…

A Systematic Search for Main-Sequence Dipper Stars Using the Zwicky Transient Facility
Anastasios Tzanidakis, James R. A. Davenport, Neven Caplar, Eric C. Bellm, Wilson Beebe, Doug Branton, Sandro Campos, Andrew J. Connolly, Melissa DeLucchi, Konstantin Malanchev, Sean McGuire
https://arxiv.org/abs/2508.03964…

A Systematic Search for Main-Sequence Dipper Stars Using the Zwicky Transient Facility
Main-sequence dipper stars, characterized by irregular and often aperiodic luminosity dimming events, offer a unique opportunity to explore the variability of circumstellar material and its potential links to planet formation, debris disks, and broadly star-planet interactions. The advent of all-sky time-domain surveys has enabled the rapid discovery of these unique systems. We present the results of a large systematic search for main-sequence dipper stars, conducted across a sample of 63 milli…

Pioneering Scalable Prototyping for Mid-Band XL-MIMO Systems: Design and Implementation
Jiachen Tian, Yu Han, Zhengtao Jin, Xi Yang, Jie Yang, Wankai Tang, Xiao Li, Wenjin Wang, Shi Jin
https://arxiv.org/abs/2510.02793

Pioneering Scalable Prototyping for Mid-Band XL-MIMO Systems: Design and Implementation
The mid-band frequency range, combined with extra large-scale multiple-input multiple-output (XL-MIMO), is emerging as a key enabler for future communication systems. Thanks to the advent of new spectrum resources and degrees of freedom brought by the near-field propagation, the mid-band XL-MIMO system is expected to significantly enhance throughput and inherently support advanced functionalities such as integrated sensing and communication. Although theoretical studies have highlighted the ben…

Safety Evaluation of Motion Plans Using Trajectory Predictors as Forward Reachable Set Estimators
Kaustav Chakraborty, Zeyuan Feng, Sushant Veer, Apoorva Sharma, Wenhao Ding, Sever Topan, Boris Ivanovic, Marco Pavone, Somil Bansal
https://arxiv.org/abs/2507.22389

Safety Evaluation of Motion Plans Using Trajectory Predictors as Forward Reachable Set Estimators
The advent of end-to-end autonomy stacks - often lacking interpretable intermediate modules - has placed an increased burden on ensuring that the final output, i.e., the motion plan, is safe in order to validate the safety of the entire stack. This requires a safety monitor that is both complete (able to detect all unsafe plans) and sound (does not flag safe plans). In this work, we propose a principled safety monitor that leverages modern multi-modal trajectory predictors to approximate forwar…

Green's Function Methods for Computing Supercurrents in Josephson Junctions
Eduardo R. Mucciolo, Jouko Nieminen, Xiao Xiao, Wei-Chi Chiu, Michael N. Leuenberger, Arun Bansil
https://arxiv.org/abs/2509.07165

Green's Function Methods for Computing Supercurrents in Josephson Junctions
Interest in Josephson junctions (JJs) has increased rapidly in recent years not only because of their use in qubits and other quantum devices but also due to the unique physics supported by the JJs. The advent of various novel quantum materials for both the barrier region and the superconducting leads has led to the possibility of adding new functionalities to the JJs. Thus, there is a growing need for accurate modeling of the JJs and related systems to enable their predictive control and atomi…

A Secure Authentication-Driven Protected Data Collection Protocol in Internet of Things
Maryam Ataei Nezhad, Hamid Barati, Ali Barati
https://arxiv.org/abs/2510.07462 https://…

A Secure Authentication-Driven Protected Data Collection Protocol in Internet of Things
Internet of Things means connecting different devices through the Internet. The Internet of things enables humans to remotely manage and control the objects they use with the Internet infrastructure. After the advent of the Internet of Things in homes, organizations, and private companies, privacy and information security are the biggest concern. This issue has challenged the spread of the Internet of things as news of the users theft of information by hackers intensified. The proposed method i…

Assessing Universal Relations for Rapidly Rotating Neutron Stars: Insights from an Interpretable Deep Learning Perspective
Grigorios Papigkiotis, Georgios Vardakas, Nikolaos Stergioulas
https://arxiv.org/abs/2508.05850

Assessing Universal Relations for Rapidly Rotating Neutron Stars: Insights from an Interpretable Deep Learning Perspective
Relations between stellar properties independent of the nuclear equation of state offer profound insights into neutron star physics and have practical applications in data analysis. Commonly, these relations are derived from utilizing various realistic nuclear cold hadronic, hyperonic, and hybrid EoS models, each of which should obey the current constraints and cover a wide range of stiffnesses. Concurrently, the field of multimessenger astronomy has been significantly enhanced by the advent of…

Design and analysis of a set of discrete variable protocols for secure quantum communication
Arindam Dutta
https://arxiv.org/abs/2508.06380 https://arxiv.o…

Design and analysis of a set of discrete variable protocols for secure quantum communication
The advent of quantum key distribution (QKD) has revolutionized secure communication by providing unconditional security, unlike classical cryptographic methods. However, its effectiveness relies on robust identity authentication, as vulnerabilities in the authentication process can cause a compromise with the security of the entire communication system. Over the past three decades, numerous quantum identity authentication (QIA) protocols have been proposed. This thesis first presents a chronol…

Toward quantum-safe scalable networks: an open, standards-aware key management framework
Ane Sanz, Asier Atutxa, David Franco, Jasone Astorga, Eduardo Jacob, Diego L\'opez
https://arxiv.org/abs/2509.09453

Toward quantum-safe scalable networks: an open, standards-aware key management framework
With the advent of quantum computing, the increasing threats to security poses a great challenge to communication networks. Recent innovations in this field resulted in promising technologies such as Quantum Key Distribution (QKD), which enables the generation of unconditionally secure keys, establishing secure communications between remote nodes. Additionally, QKD networks enable the interconnection of multinode architectures, extending the point-to-point nature of QKD. However, due to the lim…

New Radio Data on Sources of the Big Trio Program for Searching for Distant Radio Galaxies
Olga Zhelenkova, Adelina Temirova, Yurij Parijskij, Natalia Soboleva
https://arxiv.org/abs/2508.02225

New Radio Data on Sources of the Big Trio Program for Searching for Distant Radio Galaxies
A sample of objects with steep and ultra-steep spectra was prepared from radio sources of the Cold experiment surveys conducted on the RATAN-600 radio telescope. It formed the basis for the Big Trio program for searching for distant radio galaxies. With the advent of high-sensitivity, high-angular-resolution radio sky surveys, as well as deep optical and infrared surveys, it became possible to conduct additional studies of the sample. We refined the morphology and spectra of continuous radio em…

The radial variation of the silicate-to-carbon ratio in M31 probed by PRIMA
J\'er\'emy Chastenet, Ilse De Looze, Maarten Baes, Simone Bianchi, Viviana Casasola, Laure Ciesla, Stephen Eales, Jacopo Fritz, Fr\'ed\'eric Galliano, Suzanne C. Madden, Angelos Nersesian, Monica Rela\~no, Matthew W. L. Smith, Stefan van der Giessen, Emmanuel Xilouris
ht…

The radial variation of the silicate-to-carbon ratio in M31 probed by PRIMA
The properties of interstellar dust grains are being scrutinized more than ever before, with the advent of large facilities. Infrared emission from dust grains is a powerful asset than can help constrain their physical and chemical properties. Among these, the relative ratio of carbon-rich to silicate-rich grains remains one that has not yet been investigated thoroughly, due to the lack of dedicated instruments and modeling limitations. In this paper, we quantify the modeling degeneracies inher…

M&SCheck: Towards a Checklist to Support Software Engineering Newcomers to the Modeling and Simulation Area
Luiza Martins de Freitas Cintra, Philipp Zech, Mohamad Kassab, Eliomar Ara\'ujo Lima, Sofia Larissa da Costa Paiva, Valdemar Vicente Graciano Neto
https://arxiv.org/abs/2509.25625

M&SCheck: Towards a Checklist to Support Software Engineering Newcomers to the Modeling and Simulation Area
The advent of increasingly complex and dynamic ecosystems, such as digital twins (DT), smart cities and Industry 4.0 and 5.0, has made evident the need to include modeling and simulation (M&S) in the software development life cycle. Such disruptive systems include simulation models in their own architecture (such as DT) or require the use of simulation models to represent the high degree of movement and the multiplicity of interactions that occur between the involved systems. However, when soft…

Fast Learning of Non-Cooperative Spacecraft 3D Models through Primitive Initialization
Pol Francesch Huc, Emily Bates, Simone D'Amico
https://arxiv.org/abs/2507.19459 https:…

Fast Learning of Non-Cooperative Spacecraft 3D Models through Primitive Initialization
The advent of novel view synthesis techniques such as NeRF and 3D Gaussian Splatting (3DGS) has enabled learning precise 3D models only from posed monocular images. Although these methods are attractive, they hold two major limitations that prevent their use in space applications: they require poses during training, and have high computational cost at training and inference. To address these limitations, this work contributes: (1) a Convolutional Neural Network (CNN) based primitive initializer…

Enhancing Manufacturing Knowledge Access with LLMs and Context-aware Prompting
Sebastian Monka, Irlan Grangel-Gonz\'alez, Stefan Schmid, Lavdim Halilaj, Marc Rickart, Oliver Rudolph, Rui Dias
https://arxiv.org/abs/2507.22619

Enhancing Manufacturing Knowledge Access with LLMs and Context-aware Prompting
Knowledge graphs (KGs) have transformed data management within the manufacturing industry, offering effective means for integrating disparate data sources through shared and structured conceptual schemas. However, harnessing the power of KGs can be daunting for non-experts, as it often requires formulating complex SPARQL queries to retrieve specific information. With the advent of Large Language Models (LLMs), there is a growing potential to automatically translate natural language queries into…

Flare-Driven Plasma Dynamics and Elemental Abundance Redistribution
Biswajit Mondal, Amy R. Winebarger
https://arxiv.org/abs/2510.02102 https://arxiv.org/p…

Flare-Driven Plasma Dynamics and Elemental Abundance Redistribution
Since the advent of X-ray and EUV spectroscopy, the discovery of the First Ionization Potential (FIP) effect--where coronal elemental compositions diverge from their photospheric values based on the element's FIP--has remained a key puzzle in solar and stellar astrophysics. These deviations exhibit significant fluctuations during flares, yet their connection to plasma dynamics has remained unclear. Here, we report a clear correlation between temperature-sensitive flaring plasma emission and ele…

LLM-as-classifier: Semi-Supervised, Iterative Framework for Hierarchical Text Classification using Large Language Models
Doohee You, Andy Parisi, Zach Vander Velden, Lara Dantas Inojosa
https://arxiv.org/abs/2508.16478

LLM-as-classifier: Semi-Supervised, Iterative Framework for Hierarchical Text Classification using Large Language Models
The advent of Large Language Models (LLMs) has provided unprecedented capabilities for analyzing unstructured text data. However, deploying these models as reliable, robust, and scalable classifiers in production environments presents significant methodological challenges. Standard fine-tuning approaches can be resource-intensive and often struggle with the dynamic nature of real-world data distributions, which is common in the industry. In this paper, we propose a comprehensive, semi-supervise…

Artificial Authority: From Machine Minds to Political Alignments. An Experimental Analysis of Democratic and Autocratic Biases in Large-Language Models
Szymon {\L}ukasik, Natalia O\.zegalska-{\L}ukasik
https://arxiv.org/abs/2509.25286

Artificial Authority: From Machine Minds to Political Alignments. An Experimental Analysis of Democratic and Autocratic Biases in Large-Language Models
Political beliefs vary significantly across different countries, reflecting distinct historical, cultural, and institutional contexts. These ideologies, ranging from liberal democracies to rigid autocracies, influence human societies, as well as the digital systems that are constructed within those societies. The advent of generative artificial intelligence, particularly Large Language Models (LLMs), introduces new agents in the political space-agents trained on massive corpora that replicate a…

Shedding light on classical shadows: learning photonic quantum states
Hugo Thomas, Ulysse Chabaud, Pierre-Emmanuel Emeriau
https://arxiv.org/abs/2510.07240 https://

Shedding light on classical shadows: learning photonic quantum states
Efficient learning of quantum state properties is both a fundamental and practical problem in quantum information theory. Classical shadows have emerged as an efficient method for estimating properties of unknown quantum states, with rigorous statistical guarantees, by performing randomized measurement on a few number of copies. With the advent of photonic technologies, formulating efficient learning algorithms for such platforms comes out as a natural problem. Here, we introduce a classical sh…

Classification errors distort findings in automated speech processing: examples and solutions from child-development research
Lucas Gautheron, Evan Kidd, Anton Malko, Marvin Lavechin, Alejandrina Cristia
https://arxiv.org/abs/2508.15637

Classification errors distort findings in automated speech processing: examples and solutions from child-development research
With the advent of wearable recorders, scientists are increasingly turning to automated methods of analysis of audio and video data in order to measure children's experience, behavior, and outcomes, with a sizable literature employing long-form audio-recordings to study language acquisition. While numerous articles report on the accuracy and reliability of the most popular automated classifiers, less has been written on the downstream effects of classification errors on measurements and statist…

Sovereign AI for 6G: Towards the Future of AI-Native Networks
Swarna Bindu Chetty, David Grace, Simon Saunders, Paul Harris, Eirini Eleni Tsiropoulou, Tony Quek, Hamed Ahmadi
https://arxiv.org/abs/2509.06700

Sovereign AI for 6G: Towards the Future of AI-Native Networks
The advent of Generative Artificial Intelligence (GenAI), Large Language Models (LLMs), and Large Telecom Models (LTM) significantly reshapes mobile networks, especially as the telecom industry transitions from 5G's cloud-centric to AI-native 6G architectures. This transition unlocks unprecedented capabilities in real-time automation, semantic networking, and autonomous service orchestration. However, it introduces critical risks related to data sovereignty, security, explainability, and regula…

NoMod: A Non-modular Attack on Module Learning With Errors
Cristian Bassotto, Ermes Franch, Marina Kr\v{c}ek, Stjepan Picek
https://arxiv.org/abs/2510.02162 https://

NoMod: A Non-modular Attack on Module Learning With Errors
The advent of quantum computing threatens classical public-key cryptography, motivating NIST's adoption of post-quantum schemes such as those based on the Module Learning With Errors (Module-LWE) problem. We present NoMod ML-Attack, a hybrid white-box cryptanalytic method that circumvents the challenge of modeling modular reduction by treating wrap-arounds as statistical corruption and casting secret recovery as robust linear estimation. Our approach combines optimized lattice preprocessing--in…

Modular Embedding Recomposition for Incremental Learning
Aniello Panariello, Emanuele Frascaroli, Pietro Buzzega, Lorenzo Bonicelli, Angelo Porrello, Simone Calderara
https://arxiv.org/abs/2508.16463

Modular Embedding Recomposition for Incremental Learning
The advent of pre-trained Vision-Language Models (VLMs) has significantly transformed Continual Learning (CL), mainly due to their zero-shot classification abilities. Such proficiency makes VLMs well-suited for real-world applications, enabling robust performance on novel unseen classes without requiring adaptation. However, fine-tuning remains essential when downstream tasks deviate significantly from the pre-training domain. Prior CL approaches primarily focus on preserving the zero-shot capa…

Plugging Leaks in Fault-Tolerant Quantum Computation and Verification
Theodoros Kapourniotis, Dominik Leichtle, Luka Music, Harold Ollivier
https://arxiv.org/abs/2510.03227 http…

Plugging Leaks in Fault-Tolerant Quantum Computation and Verification
With the advent of quantum cloud computing, the security of delegated quantum computation has become of utmost importance. While multiple statistically secure blind verification schemes in the prepare-and-send model have been proposed, none of them achieves full quantum fault-tolerance, a prerequisite for useful verification on scalable quantum computers. In this paper, we present the first fault-tolerant blind verification scheme for universal quantum computations able to handle secret-depende…

Agentic Program Repair from Test Failures at Scale: A Neuro-symbolic approach with static analysis and test execution feedback
Chandra Maddila, Adam Tait, Claire Chang, Daniel Cheng, Nauman Ahmad, Vijayaraghavan Murali, Marshall Roch, Arnaud Avondet, Aaron Meltzer, Victor Montalvao, Michael Hopko, Chris Waterson, Parth Thakkar, Renuka Fernandez, Kristian Kristensen, Sivan Barzily, Sherry Chen, Rui Abreu, Nachiappan Nagappan, Payam Shodjai, Killian Murphy, James Everingham, Aparna Raman…

Agentic Program Repair from Test Failures at Scale: A Neuro-symbolic approach with static analysis and test execution feedback
Aim: With the advent of LLMs, sophisticated agentic program repair has become viable at large organizations with large codebases. In this work, we develop an Engineering Agent that fixes the source code based on test failures at scale across diverse software offerings internally. Method: Using Llama as the base, we employ the ReAct harness to develop an agent. We start with a test failure that was triaged by a rule-based test failure bot. We then set up an agentic harness and allow the agent …

Addressing Selected Gamma-Ray Burst Science Topics with Future Space Instruments
Nicolas De Angelis
https://arxiv.org/abs/2510.00707 https://arxiv.org/pdf/…

Addressing Selected Gamma-Ray Burst Science Topics with Future Space Instruments
Gamma-ray bursts (GRBs) are among the most energetic events in the universe, offering insights into stellar collapse, extreme matter behavior, and cosmic evolution. The advent of multi-messenger astronomy, combining electromagnetic, gravitational wave, and neutrino observations, alongside advances in high-energy polarimetry, is revolutionizing GRB research, enabling deeper exploration of their physical mechanisms. This manuscript summarizes how upcoming and proposed space-based missions will …

Astrophotometric search for massive stars in the Milky way. Confronting Random Forest predictions with available spectroscopy
N. Monsalves, A. Bayo, M. Jaque Arancibia, J. Bodensteiner, A. G. Caneppa, P. S\'anchez-S\'aez, R. Angeloni
https://arxiv.org/abs/2508.21573

Astrophotometric search for massive stars in the Milky way. Confronting Random Forest predictions with available spectroscopy
Massive stars play a significant role in different branches of astronomy, from shaping the processes of star and planet formation to influencing the evolution and chemical enrichment of the distant universe. Despite their high astrophysical significance, these objects are rare and difficult to detect. With Gaia's advent, we now possess extensive kinematic and photometric data for a significant portion of the Galaxy that can unveil, among others, new populations of massive star candidates. In or…

Geopolitical Parallax: Beyond Walter Lippmann Just After Large Language Models
Mehmet Can Yavuz, Humza Gohar Kabir, Aylin \"Ozkan
https://arxiv.org/abs/2508.19492 https://

Geopolitical Parallax: Beyond Walter Lippmann Just After Large Language Models
Objectivity in journalism has long been contested, oscillating between ideals of neutral, fact-based reporting and the inevitability of subjective framing. With the advent of large language models (LLMs), these tensions are now mediated by algorithmic systems whose training data and design choices may themselves embed cultural or ideological biases. This study investigates geopolitical parallax-systematic divergence in news quality and subjectivity assessments-by comparing article-level embeddi…

Modular Embedding Recomposition for Incremental Learning
Aniello Panariello, Emanuele Frascaroli, Pietro Buzzega, Lorenzo Bonicelli, Angelo Porrello, Simone Calderara
https://arxiv.org/abs/2508.16463

Modular Embedding Recomposition for Incremental Learning
The advent of pre-trained Vision-Language Models (VLMs) has significantly transformed Continual Learning (CL), mainly due to their zero-shot classification abilities. Such proficiency makes VLMs well-suited for real-world applications, enabling robust performance on novel unseen classes without requiring adaptation. However, fine-tuning remains essential when downstream tasks deviate significantly from the pre-training domain. Prior CL approaches primarily focus on preserving the zero-shot capa…

From Bell Products to GHZ: Quantum Memories via Emergent Hamiltonians
Anubhab Sur, Qiujiang Guo, Rubem Mondaini
https://arxiv.org/abs/2510.01117 https://ar…

From Bell Products to GHZ: Quantum Memories via Emergent Hamiltonians
With the advent of exquisite quantum emulators, storing highly entangled many-body states becomes essential. While entanglement typically builds over time when evolving a quantum system initialized in a product state, freezing that information at any given instant requires quenching to a Hamiltonian with the time-evolved state as an eigenstate, a concept we realize via an Emergent Hamiltonian framework. While the Emergent Hamiltonian is generically non-local and may lack a closed form, we show …

Literature Review of the Effect of Quantum Computing on Cryptocurrencies using Blockchain Technology
Adi Mutha, Jitendra Sandu
https://arxiv.org/abs/2508.17296 https://

Literature Review of the Effect of Quantum Computing on Cryptocurrencies using Blockchain Technology
With the advent of quantum computing, cryptocurrencies that rely on blockchain technology face mounting cryptographic vulnerabilities. This paper presents a comprehensive literature review evaluating how quantum algorithms, specifically Shors and Grovers, could disrupt the foundational security mechanisms of cryptocurrencies. Shors algorithm poses a threat to public-key cryptographic schemes by enabling efficient factorization and discrete logarithm solving, thereby endangering digital signatur…

Quantum Optics and Quantum Electrodynamics of Strong Field Processes
Marcelo F. Ciappina, Misha Yu. Ivanov, Maciej Lewenstein, Javier Rivera-Dean, Philipp Stammer, Paraskevas Tzallas
https://arxiv.org/abs/2509.26602

Quantum Optics and Quantum Electrodynamics of Strong Field Processes
In its beginnings, the physics of intense laser-matter interactions was the physics of multiphoton processes. The theory was reduced then to high-order perturbation theory, while treating matter and light in a quantum manner. With the advent of chirped pulse amplification developed by D. Strickland and G. Mourou, which enabled generation of ultra-intense, ultra-short, coherent laser pulses, the need for a quantum electrodynamics description of electromagnetic (EM) fields practically ceased to e…

Analysis of Post-Quantum Cryptography in User Equipment in 5G and Beyond
Sanzida Hoque, Abdullah Aydeger, Engin Zeydan, Madhusanka Liyanage
https://arxiv.org/abs/2507.17074 http…

Analysis of Post-Quantum Cryptography in User Equipment in 5G and Beyond
The advent of quantum computing threatens the security of classical public-key cryptographic systems, prompting the transition to post-quantum cryptography (PQC). While PQC has been analyzed in theory, its performance in practical wireless communication environments remains underexplored. This paper presents a detailed implementation and performance evaluation of NIST-selected PQC algorithms in user equipment (UE) to UE communications over 5G networks. Using a full 5G emulation stack (Open5GS a…

SoK: Securing the Final Frontier for Cybersecurity in Space-Based Infrastructure
Nafisa Anjum, Tasnuva Farheen
https://arxiv.org/abs/2507.17064 https://arx…

SoK: Securing the Final Frontier for Cybersecurity in Space-Based Infrastructure
With the advent of modern technology, critical infrastructure, communications, and national security depend increasingly on space-based assets. These assets, along with associated assets like data relay systems and ground stations, are, therefore, in serious danger of cyberattacks. Strong security defenses are essential to ensure data integrity, maintain secure operations, and protect assets in space and on the ground against various threats. Previous research has found discrete vulnerabilities…

Learning measurement-induced phase transitions using attention
Hyejin Kim, Abhishek Kumar, Yiqing Zhou, Yichen Xu, Romain Vasseur, Eun-Ah Kim
https://arxiv.org/abs/2508.15895 ht…

Learning measurement-induced phase transitions using attention
Measurement-induced phase transitions (MIPTs) epitomize new intellectual pursuits inspired by the advent of quantum hardware and the emergence of discrete and programmable circuit dynamics. Nevertheless, experimentally observing this transition is challenging, often requiring non-scalable protocols, such as post-selecting measurement trajectories or relying on classical simulations. We introduce a scalable data-centric approach using Quantum Attention Networks (QuAN) to detect MIPTs without req…