Tootfinder

Near-Heisenberg-limited parallel amplitude estimation with logarithmic depth circuit
Kohei Oshio, Kaito Wada, Naoki Yamamoto
https://arxiv.org/abs/2508.06121 https://

Near-Heisenberg-limited parallel amplitude estimation with logarithmic depth circuit
Quantum amplitude estimation is one of the core subroutines in quantum algorithms. This paper gives a parallelized amplitude estimation (PAE) algorithm, that simultaneously achieves near-Heisenberg scaling in the total number of queries and sub-linear scaling in the circuit depth, with respect to the estimation precision. The algorithm is composed of a global GHZ state followed by separated low-depth Grover circuits; the number of qubits in the GHZ state and the depth of each circuit is tunable…

Resilient Global Practical Fixed-Time Cooperative Output Regulation of Uncertain Nonlinear Multi-Agent Systems Subject to Denial-of-Service Attacks
Wenji Cao, Lu Liu, Zehua Ye, Dan Zhang, Gang Feng
https://arxiv.org/abs/2509.08324

Resilient Global Practical Fixed-Time Cooperative Output Regulation of Uncertain Nonlinear Multi-Agent Systems Subject to Denial-of-Service Attacks
This paper investigates the problem of resilient global practical fixed-time cooperative output regulation of uncertain nonlinear multi-agent systems subject to denial-of-service attacks. A novel distributed resilient adaptive fixed-time control strategy is proposed, which consists of a novel distributed resilient fixed-time observer with a chain of nonlinear filters and a novel distributed resilient adaptive fixed-time controller. It is shown that the problem of resilient global practical fixe…

Low-energy theory of jet processes and PDF factorization
Thomas Becher, Patrick Hager, Sebastian Jaskiewicz, Matthias Neubert, Dominik Schwienbacher
https://arxiv.org/abs/2509.07082

Low-energy theory of jet processes and PDF factorization
The consistency of collinear factorization violation with PDF factorization has been an outstanding challenge and subject of considerable debate. In this work we demonstrate their compatibility using a factorization theorem for non-global jet observables. Our analysis relies on consistency relations derived from renormalization conditions in effective field theory. We verify these relations through an explicit computation at three-loop order and show that the double-logarithmic evolution sourci…

Scaling Truth: The Confidence Paradox in AI Fact-Checking
Ihsan A. Qazi, Zohaib Khan, Abdullah Ghani, Agha A. Raza, Zafar A. Qazi, Wassay Sajjad, Ayesha Ali, Asher Javaid, Muhammad Abdullah Sohail, Abdul H. Azeemi
https://arxiv.org/abs/2509.08803

Scaling Truth: The Confidence Paradox in AI Fact-Checking
The rise of misinformation underscores the need for scalable and reliable fact-checking solutions. Large language models (LLMs) hold promise in automating fact verification, yet their effectiveness across global contexts remains uncertain. We systematically evaluate nine established LLMs across multiple categories (open/closed-source, multiple sizes, diverse architectures, reasoning-based) using 5,000 claims previously assessed by 174 professional fact-checking organizations across 47 languages…

Science at Risk: The Urgent Need for Institutional Support of Long-Term Ecological and Evolutionary Research in an Era of Data Manipulation and Disinformation
Vincent A. Viblanc (UMR ISEM), Elise Huchard (UMR ISEM), Gilles Pinay (CEFE), Elena Orme\~no (CEFE), C\'eline Teplitsky (CEFE), Fran\c{c}ois Criscuolo (IGE), Dominique Joly (IGE), David Renault (IGE), C\'ecile Callou (IGE), Fran\c{c}oise Gourmelon (IGE), Sandrine Anquetin (IGE), B\'en\'edicte Augeard (OFB), Fabien…

Science at Risk: The Urgent Need for Institutional Support of Long-Term Ecological and Evolutionary Research in an Era of Data Manipulation and Disinformation
Planet Earth and the biodiversity it supports are in crisis. Human impact on terrestrial, marine and freshwater ecosystems and the hundreds of thousands of organisms that inhabit them is global. To what extent can we push ecosystems before they collapse? Will species adapt to these changes and at what rate? What are the consequences, for the environment and humankind? These are some of the most pressing issues to date. Clear answers can only be addressed through long-term research programs that…

Quantum Relative Entropy Decay Composition Yields Shallow, Unstructured k-Designs
Nicholas Laracuente
https://arxiv.org/abs/2510.08537 https://arxiv.org/pd…

Quantum Relative Entropy Decay Composition Yields Shallow, Unstructured k-Designs
A major line of questions in quantum information and computing asks how quickly locally random circuits converge to resemble global randomness. In particular, approximate k-designs are random unitary ensembles that resemble random circuits up to their first k moments. It was recently shown that on n qudits, random circuits with slightly structured architectures converge to k-designs in depth O(log n), even on one-dimensional connectivity. It has however remained open whether the same shallow de…

Global-to-Local or Local-to-Global? Enhancing Image Retrieval with Efficient Local Search and Effective Global Re-ranking
Dror Aiger, Bingyi Cao, Kaifeng Chen, Andre Araujo
https://arxiv.org/abs/2509.04351

Global-to-Local or Local-to-Global? Enhancing Image Retrieval with Efficient Local Search and Effective Global Re-ranking
The dominant paradigm in image retrieval systems today is to search large databases using global image features, and re-rank those initial results with local image feature matching techniques. This design, dubbed global-to-local, stems from the computational cost of local matching approaches, which can only be afforded for a small number of retrieved images. However, emerging efficient local feature search approaches have opened up new possibilities, in particular enabling detailed retrieval at…

Machine learning magnetism from simple global descriptors
Ahmed E. Fahmy
https://arxiv.org/abs/2509.05909 https://arxiv.org/pdf/2509.05909

Machine learning magnetism from simple global descriptors
The reliable identification of magnetic ground states remains a major challenge in high-throughput materials databases, where density functional theory (DFT) workflows often converge to ferromagnetic (FM) solutions. Here, we partially address this challenge by developing machine learning classifiers trained on experimentally validated MAGNDATA magnetic materials leveraging a limited number of simple compositional, structural, and electronic descriptors sourced from the Materials Project databas…

Stereovision Image Processing for Planetary Navigation Maps with Semi-Global Matching and Superpixel Segmentation
Yan-Shan Lu, Miguel Arana-Catania, Saurabh Upadhyay, Leonard Felicetti
https://arxiv.org/abs/2509.05645

Stereovision Image Processing for Planetary Navigation Maps with Semi-Global Matching and Superpixel Segmentation
Mars exploration requires precise and reliable terrain models to ensure safe rover navigation across its unpredictable and often hazardous landscapes. Stereoscopic vision serves a critical role in the rover's perception, allowing scene reconstruction by generating precise depth maps through stereo matching. State-of-the-art Martian planetary exploration uses traditional local block-matching, aggregates cost over square windows, and refines disparities via smoothness constraints. However, this m…

OKVIS2-X: Open Keyframe-based Visual-Inertial SLAM Configurable with Dense Depth or LiDAR, and GNSS
Simon Boche, Jaehyung Jung, Sebasti\'an Barbas Laina, Stefan Leutenegger
https://arxiv.org/abs/2510.04612

OKVIS2-X: Open Keyframe-based Visual-Inertial SLAM Configurable with Dense Depth or LiDAR, and GNSS
To empower mobile robots with usable maps as well as highest state estimation accuracy and robustness, we present OKVIS2-X: a state-of-the-art multi-sensor Simultaneous Localization and Mapping (SLAM) system building dense volumetric occupancy maps, while scalable to large environments and operating in realtime. Our unified SLAM framework seamlessly integrates different sensor modalities: visual, inertial, measured or learned depth, LiDAR and Global Navigation Satellite System (GNSS) measuremen…