Tootfinder

Gyroscope measurements of the precession and nutation of Earth’s axis: #gyroscope detects Earth’s rotation with the highest precision yet: https://physicsworld.com/a/optical-gyroscope-detects-earths-rotation-with-the-highest-precision-yet/

FineServe: Precision-Aware KV Slab and Two-Level Scheduling for Heterogeneous Precision LLM Serving
Kyungmin Bin, Seungbeom Choi, Jimyoung Son, Jieun Choi, Daseul Bae, Daehyeon Baek, Kihyo Moon, Minsung Jang, Hyojung Lee
https://arxiv.org/abs/2509.06261

FineServe: Precision-Aware KV Slab and Two-Level Scheduling for Heterogeneous Precision LLM Serving
Recent advances in Post-Training Quantization (PTQ) techniques have significantly increased demand for serving quantized large language models (LLMs), enabling higher throughput and substantially reduced memory usage with minimal accuracy loss. Quantized models address memory constraints in LLMs and enhance GPU resource utilization through efficient GPU sharing. However, quantized models have smaller KV block sizes than non-quantized models, causing limited memory efficiency due to memory fragm…

Breaking Precision Time: OS Vulnerability Exploits Against IEEE 1588
Muhammad Abdullah Soomro, Fatima Muhammad Anwar
https://arxiv.org/abs/2510.06421 https://

Breaking Precision Time: OS Vulnerability Exploits Against IEEE 1588
The Precision Time Protocol (PTP), standardized as IEEE 1588, provides sub-microsecond synchronization across distributed systems and underpins critical infrastructure in telecommunications, finance, power systems, and industrial automation. While prior work has extensively analyzed PTP's vulnerability to network-based attacks, prompting the development of cryptographic protections and anomaly detectors, these defenses presume an uncompromised host. In this paper, we identify and exploit a crit…

🧬 Study finds viruses rely on diverse RNA traits to pack their genomes with precision
#virus

Study finds viruses rely on diverse RNA traits to pack their genomes with precision
Researchers at San Diego State University and Michigan State University are shedding new light on how viruses meticulously pack their genetic material — a breakthrough that could help researchers engineer antivirals and gene therapies.

Distributed Detection and Bandwidth Allocation with Hybrid Quantized and Full-Precision Observations over Multiplicative Fading Channels
Linlin Mao, Zeping Sui, Michail Matthaiou, Hongbin Li
https://arxiv.org/abs/2510.06429

Distributed Detection and Bandwidth Allocation with Hybrid Quantized and Full-Precision Observations over Multiplicative Fading Channels
A hybrid detector that fuses both quantized and full-precision observations is proposed for weak signal detection under additive and multiplicative Gaussian noise. We first derive a locally most powerful test (LMPT)--based hybrid detector from the composite probability distribution of the compound observations received by the fusion center, and then analyze its asymptotic detection performance. Subsequently, we optimize the sensor-wise quantization thresholds to achieve near-optimal asymptotic …

Sharpness-Aware Data Generation for Zero-shot Quantization
Dung Hoang-Anh, Cuong Pham Trung Le, Jianfei Cai, Thanh-Toan Do
https://arxiv.org/abs/2510.07018 https://

Sharpness-Aware Data Generation for Zero-shot Quantization
Zero-shot quantization aims to learn a quantized model from a pre-trained full-precision model with no access to original real training data. The common idea in zero-shot quantization approaches is to generate synthetic data for quantizing the full-precision model. While it is well-known that deep neural networks with low sharpness have better generalization ability, none of the previous zero-shot quantization works considers the sharpness of the quantized model as a criterion for generating tr…

RUSSIAN SOLDERING PLANT DESTROYED! ⚡ UAF Strikes with Precision! #shorts: https://benborges.xyz/2025/10/09/russian-soldering-plant-destroyed-uaf.html

TIGeR: Tool-Integrated Geometric Reasoning in Vision-Language Models for Robotics
Yi Han, Cheng Chi, Enshen Zhou, Shanyu Rong, Jingkun An, Pengwei Wang, Zhongyuan Wang, Lu Sheng, Shanghang Zhang
https://arxiv.org/abs/2510.07181

TIGeR: Tool-Integrated Geometric Reasoning in Vision-Language Models for Robotics
Vision-Language Models (VLMs) have shown remarkable capabilities in spatial reasoning, yet they remain fundamentally limited to qualitative precision and lack the computational precision required for real-world robotics. Current approaches fail to leverage metric cues from depth sensors and camera calibration, instead reducing geometric problems to pattern recognition tasks that cannot deliver the centimeter-level accuracy essential for robotic manipulation. We present TIGeR (Tool-Integrated Ge…

Multiparameter quantum metrology at Heisenberg scaling for an arbitrary two-channel linear interferometer with squeezed light
Atmadev Rai, Danilo Triggiani, Paolo Facchi, Vincenzo Tamma
https://arxiv.org/abs/2509.07574

Multiparameter quantum metrology at Heisenberg scaling for an arbitrary two-channel linear interferometer with squeezed light
We present a framework for simultaneously estimating all four real parameters of a general two-channel unitary U(2) with Heisenberg-scaling precision. We derive analytical expressions for the quantum Fisher information matrix and show that all parameters attain the 1/N scaling in the precision by using experimentally feasible Gaussian probes such as two-mode squeezed states or two single-mode squeezed states. Our results extend multiparameter metrology to its most general two-mode setting and e…

Extending the low-$Z$ "border'' of the $A=100$ region of deformation with precision mass spectrometry of $^{96-98}$Kr
D. Lunney, V. Manea, M. Mougeot, L. Nies, N. A. Althubiti, D. Atanasov, K. Blaum, A. Herlert, W. -J. Huang, J. Karthein, I. Kulikov, Yu. A. Litvinov, D. Neidherr, T. R. Rodr\'iguez, M. Rosenbusch, L. Schweikhard, T. Steinsberger, A. Welker, F. Wienholtz, R. N. Wolf

Extending the low-$Z$ "border'' of the $A=100$ region of deformation with precision mass spectrometry of $^{96-98}$Kr
The onset of collective nuclear behavior in the ${N=60}$, ${A\sim100}$, region is examined through high-precision mass measurements of $^{96-98}$Kr, performed with the ISOLTRAP mass spectrometer at ISOLDE, CERN. Our results for $^{96-97}$Kr agree with previous measurements, with our new $^{97}$Kr Penning-trap mass value three times more precise. The mass value of $^{98}$Kr is measured for the first time. The new mass surface, together with comparisons to beyond-mean-field theoretical prediction…

Hardware-Efficient CNNs: Interleaved Approximate FP32 Multipliers for Kernel Computation
Bindu G Gowda (International Institute of Information Technology Bangalore), Yogesh Goyal (International Institute of Information Technology Bangalore), Yash Gupta (International Institute of Information Technology Bangalore), Madhav Rao (International Institute of Information Technology Bangalore)

Hardware-Efficient CNNs: Interleaved Approximate FP32 Multipliers for Kernel Computation
Single-precision floating point (FP32) data format, defined by the IEEE 754 standard, is widely employed in scientific computing, signal processing, and deep learning training, where precision is critical. However, FP32 multiplication is computationally expensive and requires complex hardware, especially for precisely handling mantissa multiplication. In practical applications like neural network inference, perfect accuracy is not always necessary, minor multiplication errors often have little …

Added 'a few' math tests to picolibc today. These create reference values using nickle with its arbitrary precision floating point arithmetic. The result is a list of functions which need work to improve their accuracy. Most are "close", with known errors of 1 or 2 ulp, but tgamma is in rough shape with errors of 56 ulp for binary64 and 97ulp for binary128. The complex functions are almost all in very rough shape with errors of thousands of ulps.

test-math: Add a few math tests by keith-packard · Pull Request #1095 · picolibc/picolibc
Generate test vectors for math functions using nickle scripts with separate values for 32, 64, 80 and 128 bit formats.

Multi-Condition Conformal Selection
Qingyang Hao, Wenbo Liao, Bingyi Jing, Hongxin Wei
https://arxiv.org/abs/2510.08075 https://arxiv.org/pdf/2510.08075

Multi-Condition Conformal Selection
Selecting high-quality candidates from large-scale datasets is critically important in resource-constrained applications such as drug discovery, precision medicine, and the alignment of large language models. While conformal selection methods offer a rigorous solution with False Discovery Rate (FDR) control, their applicability is confined to single-threshold scenarios (i.e., y > c) and overlooks practical needs for multi-condition selection, such as conjunctive or disjunctive conditions. In th…

Type, Ability, and Effect Systems: Perspectives on Purity, Semantics, and Expressiveness
Yuyan Bao, Tiark Rompf
https://arxiv.org/abs/2510.07582 https://ar…

Type, Ability, and Effect Systems: Perspectives on Purity, Semantics, and Expressiveness
Programming benefits from a clear separation between pure, mathematical computation and impure, effectful interaction with the world. Existing approaches to enforce this separation include monads, type-and-effect systems, and capability systems. All share a tension between precision and usability, and each one has non-obvious strengths and weaknesses. This paper aims to raise the bar in assessing such systems. First, we propose a semantic definition of purity, inspired by contextual equivalen…

MIT Scientists Unlock a New Level of Precision in Gene Editing
https://scitechdaily.com/mit-scientists-unlock-a-new-level-of-precision-in-gene-editing/

In the Air - Outside of the Window ✈️ ☁️
在空中 - 窗外 ✈️ ☁️
📷 Nikon FE
🎞️FOMAPAN Action 400
buy me ☕️ ?/请我喝杯☕️？
#filmphotography

Reliable Evaluation Protocol for Low-Precision Retrieval
Kisu Yang, Yoonna Jang, Hwanseok Jang, Kenneth Choi, Isabelle Augenstein, Heuiseok Lim
https://arxiv.org/abs/2508.03306 …

Reliable Evaluation Protocol for Low-Precision Retrieval
Lowering the numerical precision of model parameters and computations is widely adopted to improve the efficiency of retrieval systems. However, when computing relevance scores between the query and documents in low-precision, we observe spurious ties due to the reduced granularity. This introduces high variability in the results based on tie resolution, making the evaluation less reliable. To address this, we propose a more robust retrieval evaluation protocol designed to reduce score variatio…

@… Duncan Jones just posted this woodworking video over on BlueSty. Wow, some guys sure have amazing tools in their worksheds. I feel inspired by the precision of this guy's work and methodology! https://

Binary Neutron Stars from the Moon: Early Warnings and Precision Science for the Artemis Era
Anjali B. Yelikar, Karan Jani
https://arxiv.org/abs/2510.05400 https://

Binary Neutron Stars from the Moon: Early Warnings and Precision Science for the Artemis Era
Binary neutron star mergers are unique probes of matter at extreme density and standard candles of cosmic expansion. The only such event observed in both gravitational waves and electromagnetic radiation, GW170817, revealed the origin of heavy elements, constrained the neutron star equation of state, and provided an independent measurement of the Hubble constant. Current detectors such as LIGO, Virgo, and KAGRA capture only the final minutes of inspiral, offering limited advance warning and coa…

Two Precision-controlled Numerical Algorithms for the CDF of Doubly Non-central Beta Distribution Based on the Segmentation of the Infinite Double Series Matrix
Han Li, Fangfang Ma, Junjie Wang, Yinhua Tian, Baoli Dai, Tianyan Dong
https://arxiv.org/abs/2509.05045

Two Precision-controlled Numerical Algorithms for the CDF of Doubly Non-central Beta Distribution Based on the Segmentation of the Infinite Double Series Matrix
The cumulative distribution function (CDF) of the doubly non-central beta distribution can be expressed as an infinite double series. By truncating the sum of this series, one can obtain an approximate value of the CDF. Although numerous methods exist for calculating the non-central beta distribution, which allow for the control of the truncation range and estimation of the computational error, no such methods have been developed for the doubly non-central beta distribution. In this paper, we p…

Towards an Automated Framework to Audit Youth Safety on TikTok
Linda Xue, Francesco Corso, Nicolo' Fontana, Geng Liu, Stefano Ceri, Francesco Pierri
https://arxiv.org/abs/2509.05838

Towards an Automated Framework to Audit Youth Safety on TikTok
This paper investigates the effectiveness of TikTok's enforcement mechanisms for limiting the exposure of harmful content to youth accounts. We collect over 7000 videos, classify them as harmful vs not-harmful, and then simulate interactions using age-specific sockpuppet accounts through both passive and active engagement strategies. We also evaluate the performance of large language (LLMs) and vision-language models (VLMs) in detecting harmful content, identifying key challenges in precision a…

Bootstrapping Yang-Mills matrix integrals
Wenliang Li, Xinran Su
https://arxiv.org/abs/2510.06704 https://arxiv.org/pdf/2510.06704

Bootstrapping Yang-Mills matrix integrals
We revisit the large $N$ limit of bosonic $D$-matrix Yang-Mills integrals using two complementary bootstrap methods. In the positivity bootstrap, we obtain bounds for $\langle \text{tr}\, XX \rangle$ and $\langle \text{tr}\, XXXX \rangle$ at various length cutoff $L_{\max}$. For $D=3$, we do not find an isolated region until $L_{\max}=12$. For larger $D$, the allowed regions become islands at $L_{\max}=8$ and shrink rapidly as $L_{\max}$ increases. The precision of some $L_{\max}=12$ islands is…

An updated catalog of HIRES/Keck radial velocity measurements. Including Ca II H&K measurements
Jerusalem T. Teklu, Volker Perdelwitz, R. Paul Butler, Trifon Trifonov, Steven S. Vogt, Deepa Mukhija, Lev Tal-Or
https://arxiv.org/abs/2509.06072

An updated catalog of HIRES/Keck radial velocity measurements. Including Ca II H&K measurements
The first HIRES/Keck precision radial velocity (RV) catalog was released in 2017; it was followed by a second release in 2019, which incorporated corrections for small but significant systematic errors. The manifestation of stellar activity accompanied by systematic errors could affect the detection of exoplanets via the RV method. We expanded the HIRES catalog to March 2023 using publicly available spectra. Furthermore, we included the chromospheric emission line Ca II H&K indicator ($R_{\math…

Atomic Observables Induced by Cosmic Fields
Sebastian Lahs, Daniel Comparat, Fiona Kirk, Benjamin Roberts
https://arxiv.org/abs/2510.08007 https://arxiv.or…

Atomic Observables Induced by Cosmic Fields
The existence of cosmic fields made from yet unknown light bosons is predicted in many extensions to the Standard Model. They are especially of interest as possible constituents of dark matter. To detect such light and weakly interacting fields, atomic precision measurements offer one of the most sensitive platforms. In this work, we derive which atomic observables are sensitive to what kind of cosmic field couplings. For this we consider fields that couple either through scalar, pseudoscalar, …

Algorithmic Information Bounds for Distances and Orthogonal Projections
Peter Cholak, Marianna Cs\"ornyei, Neil Lutz, Patrick Lutz, Elvira Mayordomo, D. M. Stull
https://arxiv.org/abs/2509.05211

Algorithmic Information Bounds for Distances and Orthogonal Projections
We develop quantitative algorithmic information bounds for orthogonal projections and distances in the plane. Under mild independence conditions, the distance $|x-y|$ and a projection coordinate $p_e x$ each retain at least half the algorithmic information content of $x$ in the sense of finite-precision Kolmogorov complexity, up to lower-order terms. Our bounds support conditioning on coarser approximations, enabling case analyses across precision scales. The proofs introduce a surrog…

Quantifying spike train synchrony and directionality: Measures and Applications
Thomas Kreuz
https://arxiv.org/abs/2510.07140 https://arxiv.org/pdf/2510.07…

Quantifying spike train synchrony and directionality: Measures and Applications
By introducing the twin concepts of reliability and precision along with the corresponding measures, Mainen and Sejnowski's seminal 1995 paper "Reliability of spike timing in neocortical neurons" (Mainen and Sejnowski, 1995) paved the way for a new kind of quantitative spike train analysis. In subsequent years a host of new methods was introduced that measured both the synchrony among neuronal spike trains and the directional component, e.g. how activity propogates between neurons. This develop…

Dark Energy Survey Year 6 Results: improved mitigation of spatially varying observational systematics with masking
M. Rodr\'iguez-Monroy, N. Weaverdyck, J. Elvin-Poole, I. Sevilla-Noarbe, A. Carnero Rosell, A. Drlica-Wagner, S. Avila, M. R. Becker, K. Bechtol, M. Crocce, M. Gatti, J. Mena-Fern\'andez, A. Porredon, D. Sanchez Cid, M. Yamamoto, M. Aguena, S. S. Allam, O. Alves, F. Andrade-Oliveira, D. Bacon, J. Blazek, S. Bocquet, D. Brooks, R. Camilleri, J. Carretero, R. Cawthon…

Dark Energy Survey Year 6 Results: improved mitigation of spatially varying observational systematics with masking
As photometric surveys reach unprecedented statistical precision, systematic uncertainties increasingly dominate large-scale structure probes relying on galaxy number density. Defining the final survey footprint is critical, as it excludes regions affected by artefacts or suboptimal observing conditions. For galaxy clustering, spatially varying observational systematics, such as seeing, are a leading source of bias. Template maps of contaminants are used to derive spatially dependent correction…

Information-thermodynamic bounds on precision in interacting quantum systems
Ryotaro Honma, Tan Van Vu
https://arxiv.org/abs/2510.04866 https://arxiv.org/p…

Information-thermodynamic bounds on precision in interacting quantum systems
The thermodynamic uncertainty relation quantifies a trade-off between the relative fluctuations of trajectory currents and the thermodynamic cost, indicating that the current precision is fundamentally constrained by entropy production. In classical bipartite systems, it has been shown that information flow between subsystems can enhance the current precision alongside thermodynamic dissipation. In this study, we investigate how information flow, local dissipation, and quantum effects jointly c…

A Deep Look into the Intermediate-Age Open Cluster NGC 2506: What Binary Systems Reveal About Cluster Distance and Age
K. Yakut, B. Kalomeni, S. Rappaport, Veselin Kostov
https://arxiv.org/abs/2510.06320

A Deep Look into the Intermediate-Age Open Cluster NGC 2506: What Binary Systems Reveal About Cluster Distance and Age
Using high-precision observations from the space-based \textit{Gaia} and \textit{TESS} missions, complemented by ground-based spectroscopic data and multi-band photometric surveys, we perform a detailed investigation of the Galactic open cluster NGC~2506. We present a new analysis of the intermediate-age open cluster NGC~2506, using joint fits to the radial velocities (RVs) and spectral energy distributions (SEDs) of five double-lined binary systems, including two eclipsing binaries. The analys…

Dynamic Control Aware Semantic Communication Enabled Image Transmission for Lunar Landing
Fangzhou Zhao, Yao Sun, Jianglin Lan, Muhammad Ali Imran
https://arxiv.org/abs/2510.06916

Dynamic Control Aware Semantic Communication Enabled Image Transmission for Lunar Landing
The primary challenge in autonomous lunar landing missions lies in the unreliable local control system, which has limited capacity to handle high-dynamic conditions, severely affecting landing precision and safety. Recent advancements in lunar satellite communication make it possible to establish a wireless link between lunar orbit satellites and the lunar lander. This enables satellites to run high-performance autonomous landing algorithms, improving landing accuracy while reducing the lander'…

Full Integer Arithmetic Online Training for Spiking Neural Networks
Ismael Gomez, Guangzhi Tang
https://arxiv.org/abs/2509.06636 https://arxiv.org/pdf/2509…

Full Integer Arithmetic Online Training for Spiking Neural Networks
Spiking Neural Networks (SNNs) are promising for neuromorphic computing due to their biological plausibility and energy efficiency. However, training methods like Backpropagation Through Time (BPTT) and Real Time Recurrent Learning (RTRL) remain computationally intensive. This work introduces an integer-only, online training algorithm using a mixed-precision approach to improve efficiency and reduce memory usage by over 60%. The method replaces floating-point operations with integer arithmetic …

TIGER: A Topology-Agnostic, Hierarchical Graph Network for Event Reconstruction
Nathalie Soybelman, Francesco A. Di Bello, Nilotpal Kakati, Eilam Gross
https://arxiv.org/abs/2510.08162

TIGER: A Topology-Agnostic, Hierarchical Graph Network for Event Reconstruction
Event reconstruction at the LHC, the task of assigning observed physics objects to their true origins, is a central challenge for precision measurements and searches. Many existing machine learning approaches address this problem but rely on a single event topology, restricting their applicability to realistic analyses where multiple signal and background processes with different structures are present. To overcome this, we present TIGER, a novel hierarchical graph network that is fundamentally…

All-optical polarization control in time-varying low-index films via plasma symmetry breaking
Wallace Jaffray, Sven Stengel, Alexandra Boltasseva, Vladimir M. Shalaev, Maria Antonietta Vincenti, Domenico De Ceglia, Michael Scalora, Carlo Rizza, Marcello Ferrera
https://arxiv.org/abs/2510.06985

All-optical polarization control in time-varying low-index films via plasma symmetry breaking
Controlling the polarization state of light with sub-picosecond speed and subwavelength precision remains a key challenge for next-generation nanophotonic devices. Conventional methods such as birefringent crystals, liquid crystals, or electro-optic Pockels cells are limited in speed, compactness, and energy efficiency. While structured materials and two-dimensional heterostructures offer potential for on-chip ultrafast performance, achieving all-optical control remains an open problem. Here we…

Mixed-precision ab initio tensor network state methods adapted for NVIDIA Blackwell technology via emulated FP64 arithmetic
Cole Brower, Samuel Rodriguez Bernabeu, Jeff Hammond, John Gunnels, Sotiris S. Xanthea, Martin Ganahl, Andor Menczer, \"Ors Legeza
https://arxiv.org/abs/2510.04795

Mixed-precision ab initio tensor network state methods adapted for NVIDIA Blackwell technology via emulated FP64 arithmetic
We report cutting-edge performance results via mixed-precision spin adapted ab initio Density Matrix Renormalization Group (DMRG) electronic structure calculations utilizing the Ozaki scheme for emulating FP64 arithmetic through the use of fixed-point compute resources. By approximating the underlying matrix and tensor algebra with operations on a modest number of fixed-point representatives (``slices''), we demonstrate on smaller benchmark systems and for the active compounds of the FeMoco and…

Precision measurement of the $^{176}\mathrm{Lu}^ $ $^3D_1$ microwave clock transitions
M. D. K. Lee, Qi Zhao, Qin Qichen, Zhao Zhang, N. Jayjong, K. J. Arnold, M. D. Barrett
https://arxiv.org/abs/2510.06814

Statistical inference using debiased group graphical lasso for multiple sparse precision matrices
Sayan Ranjan Bhowal, Debashis Paul, Gopal K Basak, Samarjit Das
https://arxiv.org/abs/2510.04683

Statistical inference using debiased group graphical lasso for multiple sparse precision matrices
Debiasing group graphical lasso estimates enables statistical inference when multiple Gaussian graphical models share a common sparsity pattern. We analyze the estimation properties of group graphical lasso, establishing convergence rates and model selection consistency under irrepresentability conditions. Based on these results, we construct debiased estimators that are asymptotically Gaussian, allowing hypothesis testing for linear combinations of precision matrix entries across populations. …

Nanobot Algorithms for Treatment of Diffuse Cancer
Noble Harasha, Nancy Lynch
https://arxiv.org/abs/2509.06893 https://arxiv.org/pdf/2509.06893

Nanobot Algorithms for Treatment of Diffuse Cancer
Motile nanosized particles, or "nanobots", promise more effective and less toxic targeted drug delivery because of their unique scale and precision. We consider the case in which the cancer is "diffuse", dispersed such that there are multiple distinct cancer sites. We investigate the problem of a swarm of nanobots locating these sites and treating them by dropping drug payloads at the sites. To improve the success of the treatment, the drug payloads must be allocated between sites according to …

Unified microscopic theory of equilibrium thermodynamics and ion association in aqueous and non-aqueous electrolytes with explicit hard-core size
Sahin Buyukdagli
https://arxiv.org/abs/2510.07619

Unified microscopic theory of equilibrium thermodynamics and ion association in aqueous and non-aqueous electrolytes with explicit hard-core size
Within the framework of a functional integral formalism incorporating ionic charge and hard-core (HC) interactions on an equal footing, we formulate a unified theory of equilibrium thermodynamics and ion association in charged solutions. Via comparison with recent Monte-Carlo (MC) simulation results (J. Forsman et al., PCCP 26, 19921 (2024)), it is shown that our approach is able to predict with quantitative precision the pair distributions of monovalent ions with the typical hydrated sizes d =…

ZeroFalse: Improving Precision in Static Analysis with LLMs
Mohsen Iranmanesh (Simon Fraser University), Sina Moradi Sabet (Amirkabir University of Technology), Sina Marefat (K. N. Toosi University of Technology), Ali Javidi Ghasr (Ferdowsi University of Mashhad), Allison Wilson (Cyber Risk Solutions), Iman Sharafaldin (Forward Security), Mohammad A. Tayebi (Simon Fraser University)

ZeroFalse: Improving Precision in Static Analysis with LLMs
Static Application Security Testing (SAST) tools are integral to modern software development, yet their adoption is undermined by excessive false positives that weaken developer trust and demand costly manual triage. We present ZeroFalse, a framework that integrates static analysis with large language models (LLMs) to reduce false positives while preserving coverage. ZeroFalse treats static analyzer outputs as structured contracts, enriching them with flow-sensitive traces, contextual evidence,…

ODKE : Ontology-Guided Open-Domain Knowledge Extraction with LLMs
Samira Khorshidi, Azadeh Nikfarjam, Suprita Shankar, Yisi Sang, Yash Govind, Hyun Jang, Ali Kasgari, Alexis McClimans, Mohamed Soliman, Vishnu Konda, Ahmed Fakhry, Xiaoguang Qi
https://arxiv.org/abs/2509.04696

ODKE+: Ontology-Guided Open-Domain Knowledge Extraction with LLMs
Knowledge graphs (KGs) are foundational to many AI applications, but maintaining their freshness and completeness remains costly. We present ODKE+, a production-grade system that automatically extracts and ingests millions of open-domain facts from web sources with high precision. ODKE+ combines modular components into a scalable pipeline: (1) the Extraction Initiator detects missing or stale facts, (2) the Evidence Retriever collects supporting documents, (3) hybrid Knowledge Extractors apply …

China halts high-precision machine tool exports to Russia as trade ties cool: https://benborges.xyz/2025/10/08/china-halts-highprecision-machine-tool.html

A 10-bit SAR ADC with 1.5x Input Range
Yi Zhang
https://arxiv.org/abs/2509.05636 https://arxiv.org/pdf/2509.05636…

A 10-bit SAR ADC with 1.5x Input Range
This paper presents a differential 10-bit 2 MS/s successive approximation register (SAR) analog-to-digital converter (ADC) with a precision-improvement technique. The proposed method breaks the direct tradeoff between the capacitive digital-to-analog converter (CDAC) units and the resolution of SAR ADCs by extending the effective input range, thereby enhancing the effective number of bits (ENOB). Specifically, the technique is implemented by switching the potential of the MSB capacitors during …

Safe Robust Predictive Control-based Motion Planning of Automated Surface Vessels in Inland Waterways
Sajad Ahmadi, Hossein Nejatbakhsh Esfahani, Javad Mohammadpour Velni
https://arxiv.org/abs/2509.06687

Safe Robust Predictive Control-based Motion Planning of Automated Surface Vessels in Inland Waterways
Deploying self-navigating surface vessels in inland waterways offers a sustainable alternative to reduce road traffic congestion and emissions. However, navigating confined waterways presents unique challenges, including narrow channels, higher traffic density, and hydrodynamic disturbances. Existing methods for autonomous vessel navigation often lack the robustness or precision required for such environments. This paper presents a new motion planning approach for Automated Surface Vessels (ASV…

Non-Asymptotic Analysis of Data Augmentation for Precision Matrix Estimation
Lucas Morisset, Adrien Hardy, Alain Durmus
https://arxiv.org/abs/2510.02119 https://

Non-Asymptotic Analysis of Data Augmentation for Precision Matrix Estimation
This paper addresses the problem of inverse covariance (also known as precision matrix) estimation in high-dimensional settings. Specifically, we focus on two classes of estimators: linear shrinkage estimators with a target proportional to the identity matrix, and estimators derived from data augmentation (DA). Here, DA refers to the common practice of enriching a dataset with artificial samples--typically generated via a generative model or through random transformations of the original data--…

TPCpp-10M: Simulated proton-proton collisions in a Time Projection Chamber for AI Foundation Models
Shuhang Li, Yi Huang, David Park, Xihaier Luo, Haiwang Yu, Yeonju Go, Christopher Pinkenburg, Yuewei Lin, Shinjae Yoo, Joseph Osborn, Christof Roland, Jin Huang, Yihui Ren
https://arxiv.org/abs/2509.05792

TPCpp-10M: Simulated proton-proton collisions in a Time Projection Chamber for AI Foundation Models
Scientific foundation models hold great promise for advancing nuclear and particle physics by improving analysis precision and accelerating discovery. Yet, progress in this field is often limited by the lack of openly available large scale datasets, as well as standardized evaluation tasks and metrics. Furthermore, the specialized knowledge and software typically required to process particle physics data pose significant barriers to interdisciplinary collaboration with the broader machine learn…

High-Performance and Power-Efficient Emulation of Matrix Multiplication using INT8 Matrix Engines
Yuki Uchino, Katsuhisa Ozaki, Toshiyuki Imamura
https://arxiv.org/abs/2508.03984

High-Performance and Power-Efficient Emulation of Matrix Multiplication using INT8 Matrix Engines
Recent architectures integrate high-performance and power-efficient matrix engines. These engines demonstrate remarkable performance in low-precision matrix multiplication, which is crucial in deep learning. Several techniques have been proposed to emulate single- and double-precision general matrix-matrix multiplication (SGEMM and DGEMM, respectively) by leveraging such low-precision matrix engines. In this study, we present emulation methods that significantly outperforms conventional approac…

Optimising the MeerKAT Pulsar Timing Array and towards precision pulsar timing with SKA-mid
Pratyasha Gitika, Ryan M. Shannon, Matthew Bailes, Daniel J. Reardon, Matthew T. Miles, David J. Champion, Kathrin Grunthal
https://arxiv.org/abs/2510.03139

Optimising the MeerKAT Pulsar Timing Array and towards precision pulsar timing with SKA-mid
Pulsar timing arrays (PTAs) are Galactic-scale nanohertz-frequency gravitational wave (GW) detectors. Recently, several PTAs have found evidence for the presence of GWs in their datasets, but none of them have achieved a community-defined definitive (> 5$σ$) detection. Here, we identify limiting noise sources for PTAs and quantify their impact on sensitivity to GWs under different observing and noise modelling strategies. First, we search for intrinsic pulse jitter in a sample of 89 MSPs obser…

Federated Computation of ROC and PR Curves
Xuefeng Xu, Graham Cormode
https://arxiv.org/abs/2510.04979 https://arxiv.org/pdf/2510.04979

Federated Computation of ROC and PR Curves
Receiver Operating Characteristic (ROC) and Precision-Recall (PR) curves are fundamental tools for evaluating machine learning classifiers, offering detailed insights into the trade-offs between true positive rate vs. false positive rate (ROC) or precision vs. recall (PR). However, in Federated Learning (FL) scenarios, where data is distributed across multiple clients, computing these curves is challenging due to privacy and communication constraints. Specifically, the server cannot access raw …

Flow Matching for Conditional MRI-CT and CBCT-CT Image Synthesis
Arnela Hadzic, Simon Johannes Joham, Martin Urschler
https://arxiv.org/abs/2510.04823 https://

Flow Matching for Conditional MRI-CT and CBCT-CT Image Synthesis
Generating synthetic CT (sCT) from MRI or CBCT plays a crucial role in enabling MRI-only and CBCT-based adaptive radiotherapy, improving treatment precision while reducing patient radiation exposure. To address this task, we adopt a fully 3D Flow Matching (FM) framework, motivated by recent work demonstrating FM's efficiency in producing high-quality images. In our approach, a Gaussian noise volume is transformed into an sCT image by integrating a learned FM velocity field, conditioned on featu…

Simultaneous Rational Function Codes: Improved Analysis Beyond Half the Minimum Distance with Multiplicities and Poles
Matteo Abbondati, Eleonora Guerrini, Romain Lebreton
https://arxiv.org/abs/2508.05284

Simultaneous Rational Function Codes: Improved Analysis Beyond Half the Minimum Distance with Multiplicities and Poles
In this paper, we extend the work of Abbondati et al. (2024) on decoding simultaneous rational function codes by addressing two important scenarios: multiplicities and poles (zeros of denominators). First, we generalize previous results to rational codes with multiplicities by considering evaluations with multi-precision. Then, using the hybrid model from Guerrini et al. (2023), we extend our approach to vectors of rational functions that may present poles. Our contributions include: a rigorous…

Precision Dose-Finding Design for Phase I Oncology Trials by Integrating Pharmacology Data
Kyong Ju Lee, Yuan Ji
https://arxiv.org/abs/2509.05120 https://a…

Precision Dose-Finding Design for Phase I Oncology Trials by Integrating Pharmacology Data
Phase I oncology trials aim to identify a safe yet effective dose - often the maximum tolerated dose (MTD) - for subsequent studies. Conventional designs focus on population-level toxicity modeling, with recent attention on leveraging pharmacokinetic (PK) data to improve dose selection. We propose the Precision Dose-Finding (PDF) design, a novel Bayesian phase I framework that integrates individual patient PK profiles into the dose-finding process. By incorporating patient-specific PK parameter…

\texttt{simple-idealized-1d-nlse}: Pseudo-Spectral Solver for the 1D Nonlinear Schr\"odinger Equation
Sandy H. S. Herho, Iwan P. Anwar, Faruq Khadami, Rusmawan Suwarman, Dasapta E. Irawan
https://arxiv.org/abs/2509.05901

\texttt{simple-idealized-1d-nlse}: Pseudo-Spectral Solver for the 1D Nonlinear Schrödinger Equation
We present an open-source Python implementation of an idealized high-order pseudo-spectral solver for the one-dimensional nonlinear Schrödinger equation (NLSE). The solver combines Fourier spectral spatial discretization with an adaptive eighth-order Dormand-Prince time integration scheme to achieve machine-precision conservation of mass and near-perfect preservation of momentum and energy for smooth solutions. The implementation accurately reproduces fundamental NLSE phenomena including solit…

Machine Learning for Radial Velocity Analysis I: Vision Transformers as a Robust Alternative for Detecting Planetary Candidates
Anoop Gavankar, Tanish Mittal, Joe Ninan, Shravan Hanasoge
https://arxiv.org/abs/2510.07034

Machine Learning for Radial Velocity Analysis I: Vision Transformers as a Robust Alternative for Detecting Planetary Candidates
Extreme precision radial velocity (EPRV) surveys usually require extensive observational baselines to confirm planetary candidates, making them resource-intensive. Traditionally, periodograms are used to identify promising candidate signals before further observational investment, but their effectiveness is often limited for low-amplitude signals due to stellar jitter. In this work, we develop a machine learning (ML) framework based on a Transformer architecture that aims to detect the presence…

Cluster Catalog Validation with Multiwavelength Data
Ethan K. Steelberg, Tesla E. Jeltema, Jackson H. O'Donnell, Rance Solomon, The LSST Dark Energy Science Collaboration
https://arxiv.org/abs/2509.07268

Cluster Catalog Validation with Multiwavelength Data
The Legacy Survey of Space and Time (LSST) will provide a ground-breaking data set for cosmology, but to achieve the precision needed, the data, data reduction, and algorithms measuring the cosmological data vectors must be thoroughly validated and calibrated. In this note, we focus on clusters of galaxies and present a set of validation tests for optical cluster finding algorithms through comparison to X-ray and Sunyaev-Zel'dovich effect cluster catalogs. As an example, we apply our pipeline t…

The giant, remote-controlled vehicle
— somewhere between a tractor trailer, a tank and a Zamboni in appearance
— slowly rolled across the dry, brittle grass growing between the tangle of freeways making up the 101 and 23 interchange in Thousand Oaks.
Inside the beast, fire churned.
And as it rolled over the land, that fire incinerated any brush it encountered,
leaving only a thin smoke cloud billowing from the top of the machine, some flashes of orange and red fr…

A 'Roomba for the forest' could be SoCal's next wildfire weapon
The BurnBot is a remote-controlled vehicular system that removes flammable brush alongside roads with unprecedented precision.

Error Bounds for Radial Network Topology Learning from Quantized Measurements
Samuel Talkington, Aditya Rangarajan, Pedro A. de Alc\^antara, Line Roald, Daniel K. Molzahn, Daniel R. Fuhrmann
https://arxiv.org/abs/2508.05620

Error Bounds for Radial Network Topology Learning from Quantized Measurements
We probabilistically bound the error of a solution to a radial network topology learning problem where both connectivity and line parameters are estimated. In our model, data errors are introduced by the precision of the sensors, i.e., quantization. This produces a nonlinear measurement model that embeds the operation of the sensor communication network into the learning problem, expanding beyond the additive noise models typically seen in power system estimation algorithms. We show that the er…

Can language models boost the power of randomized experiments without statistical bias?
Xinrui Ruan, Xinwei Ma, Yingfei Wang, Waverly Wei, Jingshen Wang
https://arxiv.org/abs/2510.05545

Can language models boost the power of randomized experiments without statistical bias?
Randomized experiments or randomized controlled trials (RCTs) are gold standards for causal inference, yet cost and sample-size constraints limit power. Meanwhile, modern RCTs routinely collect rich, unstructured data that are highly prognostic of outcomes but rarely used in causal analyses. We introduce CALM (Causal Analysis leveraging Language Models), a statistical framework that integrates large language models (LLMs) predictions with established causal estimators to increase precision whil…

Ramsey Interferometry with Qudits
Branislav Ilikj, Nikolay V. Vitanov
https://arxiv.org/abs/2509.06290 https://arxiv.org/pdf/2509.06290

Ramsey Interferometry with Qudits
Ramsey interferometry, a cornerstone technique in quantum spectroscopy, traditionally operates with qubits for high precision measurements. In this work we build on Ramsey interferometry, extending it to qudits in Wigner-Majorana (WM) systems where the internal degrees of freedom are used to achieve enhanced resolution. We also show that replacing the two $π/2$ pulses of standard Ramsey interferometry with the quantum Fourier transform provides no increase in resolution. Theoretical analysis f…

Automatically Generating High-Precision Simulated Road Networking in Traffic Scenario
Liang Xie, Wenke Huang
https://arxiv.org/abs/2509.02990 https://arxiv…

Automatically Generating High-Precision Simulated Road Networking in Traffic Scenario
Existing lane-level simulation road network generation is labor-intensive, resource-demanding, and costly due to the need for large-scale data collection and manual post-editing. To overcome these limitations, we propose automatically generating high-precision simulated road networks in traffic scenario, an efficient and fully automated solution. Initially, real-world road street view data is collected through open-source street view map platforms, and a large-scale street view lane line datase…

Mixed Reality Guidance of a Surgical Scalpel Using Magic Leap: Evaluation on a 3D-Printed Liver Phantom
Alice Yang, Michael Beasley, Catherine Taylor, Hu Guo
https://arxiv.org/abs/2510.03617

Mixed Reality Guidance of a Surgical Scalpel Using Magic Leap: Evaluation on a 3D-Printed Liver Phantom
Augmented and mixed reality (MR) systems have the potential to improve surgical precision by overlaying digital guidance directly onto the operative field. This paper presents a novel MR guidance system using the Magic Leap head-mounted display to assist surgeons in executing precise scalpel movements during liver surgery. The system projects holographic cues onto a patient-specific 3D-printed liver phantom, guiding resection along a predetermined path. We describe the system design, including …

DeepAP: Deep Learning-based Aperture Photometry Feasibility Assessment and Aperture Size Prediction
Zheng-Jun Du, Qing-Quan Li, Yi-Cheng Rui, Yu-Li Liu, Yu-Ting Wu, Dong Li, Bing-Feng Seng, Yi-Fan Xuan, Fa-Bo Feng
https://arxiv.org/abs/2508.03400

DeepAP: Deep Learning-based Aperture Photometry Feasibility Assessment and Aperture Size Prediction
Aperture photometry is a fundamental technique widely used to obtain high-precision light curves in optical survey projects like Tianyu. However, its effectiveness is limited in crowded fields, and the choice of aperture size critically impacts photometric precision. To address these challenges, we propose DeepAP, an efficient and accurate two-stage deep learning framework for aperture photometry. Specifically, for a given source, we first train a Vision Transformer (ViT) model to assess its fe…

Replaced article(s) found for hep-ex. https://arxiv.org/list/hep-ex/new
[1/1]:
- Precision Measurement of the Branching Fraction of $D^{ }\to \mu^{ }\nu_{\mu}$
BESIII Collaboration, et al.

A laser with instability reaching $4 \times 10^{-17}$ based on a 10-cm-long silicon cavity at sub-5-K temperatures
Zhi-Ang Chen, Hao-Ran Zeng, Wen-Wei Wang, Han Zhang, Run-Qi Lei, Jian-Zhang Li, Cai-Yin Pang, She-Song Huang, Xibo Zhang
https://arxiv.org/abs/2510.06636

A laser with instability reaching $4 \times 10^{-17}$ based on a 10-cm-long silicon cavity at sub-5-K temperatures
The realization of ultra-stable lasers with $10^{-17}$-level frequency stability has enabled a wide range of researches on precision metrology and fundamental science, where cryogenic single-crystalline cavities constitute the heart of such ultra-stable lasers. For further improvements in stability, increasing the cavity length at few-kelvin temperatures provides a promising alternative to utilizing relatively short cavities with novel coating, but has yet to be demonstrated with state-of-the-a…

Vi-TacMan: Articulated Object Manipulation via Vision and Touch
Leiyao Cui, Zihang Zhao, Sirui Xie, Wenhuan Zhang, Zhi Han, Yixin Zhu
https://arxiv.org/abs/2510.06339 https://…

Vi-TacMan: Articulated Object Manipulation via Vision and Touch
Autonomous manipulation of articulated objects remains a fundamental challenge for robots in human environments. Vision-based methods can infer hidden kinematics but can yield imprecise estimates on unfamiliar objects. Tactile approaches achieve robust control through contact feedback but require accurate initialization. This suggests a natural synergy: vision for global guidance, touch for local precision. Yet no framework systematically exploits this complementarity for generalized articulate…

On $\tau$ Spin Use with KKMCee
J. M. John, Ananya Tapadar, Zbigniew Was
https://arxiv.org/abs/2509.04400 https://arxiv.org/pdf/2509.04400

On $τ$ Spin Use with KKMCee
Spin of $τ$ represents an interesting phenomenology data point in both its production from $e^+ e^-$ collision and its subsequent decay. In precision applications such as Belle-II or FCC, where precision tagging is comparable or better than $0.1 \%$ Monte Carlo applications are usually necessary. \texttt{KKMCee}, the precision Monte Carlo program, is assuring such high precision in a broad energy range. But so far, spin effects were not easy to grasp. We introduce into \texttt{KKMCee}, \texttt…

A Mixed Precision Eigensolver Based on the Jacobi Algorithm
Zhengbo Zhou
https://arxiv.org/abs/2509.00495 https://arxiv.org/pdf/2509.00495

A Mixed Precision Eigensolver Based on the Jacobi Algorithm
The classic method for computing the spectral decomposition of a real symmetric matrix, the Jacobi algorithm, can be accelerated by using mixed precision arithmetic. The Jacobi algorithm is aiming to reduce the off-diagonal entries iteratively using Givens rotations. We investigate how to use the low precision to speed up this algorithm based on the approximate spectral decomposition in low precision. We first study two different index choosing techniques, classical and cyclic-by-row, for the…

Toward Axion Signal Extraction in Semiconductor Spin Qubits Via Spectral Engineering
Xiangjun Tan, Zhanning Wang
https://arxiv.org/abs/2509.06791 https://a…

Toward Axion Signal Extraction in Semiconductor Spin Qubits Via Spectral Engineering
Recent advances in quantum sensing and computational technologies indicate the possibility of improving the precision of measurements aimed at detecting cosmological particles and weakly interacting massive particles using various qubit platforms. While recent progress has been made, mitigating environmental noise remains a challenge in extracting particle parameters with high fidelity. Addressing these challenges requires efforts on two levels. At the device level, the qubit and its array acti…

Bayesian Analysis of the $^{86}$Sr$(\alpha, \alpha)$ Reaction to Constrain the $^{86}$Sr$(\alpha, n)$ Cross Section at Astrophysical Energies
Caleb Marshall, Taliah Lansing, David Gribble, Richard Longland, Athanasios Psaltis, Kiana Setoodehnia
https://arxiv.org/abs/2509.05461

Bayesian Analysis of the $^{86}$Sr$(α, α)$ Reaction to Constrain the $^{86}$Sr$(α, n)$ Cross Section at Astrophysical Energies
The Alpha Optical Model Potential (\aomp \!) is a phenomenological approach used to describe elastic scattering where multiple reaction channels are open. It is one of the most critical inputs for the calculation of thermonuclear reaction rates in explosive stellar environments, but uncertainties within the $α$-OMP lead to imprecise predictions hindering comparisons between calculations and observations. In order to improve the precision of the $α$-OMP, additional nuclear physics data are req…

CURLING -- II. Improvement on the $H_{0}$ Inference from Pixelized Cluster Strong Lens Modeling
Yushan Xie, Huanyuan Shan, Yiping Shu, Nan Li, Ji Yao, Ran Li, Xiaoyue Cao, Zizhao He, Yin Li, Eric Jullo, Jean-Paul Kneib, Guoliang Li
https://arxiv.org/abs/2510.07131

CURLING - II. Improvement on the $H_{0}$ Inference from Pixelized Cluster Strong Lens Modeling
Strongly lensed supernovae (glSNe) provide a powerful, independent method to measure the Hubble constant, $H_{0}$, through time delays between their multiple images. The accuracy of this measurement depends critically on both the precision of time delay estimation and the robustness of lens modeling. In many current cluster-scale modeling algorithms, all multiple images used for modeling are simplified as point sources to reduce computational costs. In the first paper of the CURLING program, we…

CHORD: Customizing Hybrid-precision On-device Model for Sequential Recommendation with Device-cloud Collaboration
Tianqi Liu, Kairui Fu, Shengyu Zhang, Wenyan Fan, Zhaocheng Du, Jieming Zhu, Fan Wu, Fei Wu
https://arxiv.org/abs/2510.03038

CHORD: Customizing Hybrid-precision On-device Model for Sequential Recommendation with Device-cloud Collaboration
With the advancement of mobile device capabilities, deploying reranking models directly on devices has become feasible, enabling real-time contextual recommendations. When migrating models from cloud to devices, resource heterogeneity inevitably necessitates model compression. Recent quantization methods show promise for efficient deployment, yet they overlook device-specific user interests, resulting in compromised recommendation accuracy. While on-device finetuning captures personalized user …

Direct Detection of Known Exoplanets in Reflected Light: Predicting Sky Position with Literature Orbit Solutions
Logan A. Pearce, Jared R. Males, Mary Anne Limbach
https://arxiv.org/abs/2509.06747

Direct Detection of Known Exoplanets in Reflected Light: Predicting Sky Position with Literature Orbit Solutions
The next generation of ground- and space-based observatories will enable direct imaging and characterization of cold, mature planets through thermal emission and, for the first time, reflected light detection. Known RV and astrometrically detected planets provide a known population for detection and characterization observations. However, many of the most promising targets lack orbital parameters of sufficient precision to confidently predict their location on relative to the star for a direct …

🧲 Ultra-high-resolution MRI maps brain fibers and cells with near-micron precision
#brain

Ultra-high-resolution MRI maps brain fibers and cells with near-micron precision
A scientific team supported in part by the National Institutes of Health (NIH) has developed a new, ultra-high-resolution brain imaging system that can reconstruct microscopic brain structures that are disrupted in neurological and neuropsychiatric brain disorders. The new system is a significant advance over conventional magnetic resonance imaging (MRI) scanners that cannot visualize these tiny but clinically important structures.

Fundamental Bounds for Off-Axis Illumination in Interferometric and Rotating Coherent Scattering Microscopy
Felix Hitzelhammer, Jonathan Dong, Ulrich Hohenester, Thomas Juffmann
https://arxiv.org/abs/2510.03034

Fundamental Bounds for Off-Axis Illumination in Interferometric and Rotating Coherent Scattering Microscopy
Coherent localization microscopy enables three-dimensional localization with nanoscale precision. Previous studies have characterized the fundamental precision limits for on-axis illumination geometries. In this paper, we theoretically analyze 3D particle localization precision under oblique illumination in interferometric scattering microscopy (iSCAT). We show that (quantum) Cramer-Rao bounds reveal an information gain in the off-axis case, potentially enabling enhanced localization precision.…

High-Sensitivity Optical Detection of Electron-Nuclear Spin Clusters in Diamond
Louis Chambard, Alrik Durand, Julien Voisin, Maxime Perdriat, Vincent Jacques, Gabriel H\'etet
https://arxiv.org/abs/2510.08474

High-Sensitivity Optical Detection of Electron-Nuclear Spin Clusters in Diamond
We perform sensitive nuclear magnetic resonance (NMR) with spin ensembles which are polarized by nitrogen vacancy centers (NV centers) in diamond at room-temperature. With a near shot-noise-limited photoluminescence detection and a highly uniform magnetic field, we resolve sharp NMR features arising from multiple spin clusters. In particular, we investigate the coupling between nuclear spins and NV centers in the neutral and negatively charged states. Further, we perform high precision NMR and …

A Framework of Arithmetic-Level Variable Precision Computing for In-Memory Architecture: Case Study in MIMO Signal Processing
Kaixuan Bao, Wei Xu, Xiaohu You, Derrick Wing Kwan Ng
https://arxiv.org/abs/2508.21079

A Framework of Arithmetic-Level Variable Precision Computing for In-Memory Architecture: Case Study in MIMO Signal Processing
Computational complexity poses a significant challenge in wireless communication. Most existing attempts aim to reduce it through algorithm-specific approaches. However, the precision of computing, which directly relates to both computing performance and computational complexity, is a dimension that is fundamental but rarely explored in the literature. With the emerging architecture of in-memory computing, variable precision computing (VPC) is enabled, allowing each arithmetic operation to be p…

OSINTtechnical (@Osinttechnical): "Major Ukrainian precision strike targeting the Russian city of Belgorod tonight, reportedly knocking out power and water to large portions of the city. Russian channels report that Ukrainian rockets hit the Luch thermal power plant and additional infrastructure." | XCancel
https://xcancel.com/Osinttechnical/status/1974916740799922547?t=y9n_Qrq-boIvl3Qb-y6cpw&s=19

Mixed-precision iterative refinement for low-rank Lyapunov equations
Peter Benner, Xiaobo Liu
https://arxiv.org/abs/2510.02126 https://arxiv.org/pdf/2510.0…

Mixed-precision iterative refinement for low-rank Lyapunov equations
We develop a mixed-precision iterative refinement framework for solving low-rank Lyapunov matrix equations $AX + XA^T + W =0$, where $W=LL^T$ or $W=LSL^T$. Via rounding error analysis of the algorithms we derive sufficient conditions for the attainable normwise residuals in different precision settings and show how the algorithmic parameters should be chosen. Using the sign function Newton iteration as the solver, we show that reduced precisions, such as the half precision, can be used as the s…

Covariate adjustment for linear models in estimating treatment effects in randomised clinical trials. Some useful theory to guide simulation
Stephen Senn, Franz K\"onig, Martin Posch
https://arxiv.org/abs/2508.05459

Covariate adjustment for linear models in estimating treatment effects in randomised clinical trials. Some useful theory to guide simulation
Building on key papers that were published in special issues of Biometrics in 1957 and 1982 we propose and develop a three-aspect system for evaluating the effect of fitting covariates in the analysis of designed experiments, in particular randomised clinical trials. The three aspects are: first the effect on residual mean square error, second the effect on the variance inflation factor (VIF) and third the effect on second order precision. We concentrate, in particular, on the VIF and highlight…

A Multi-Layer Electronic and Cyber Interference Model for AI-Driven Cruise Missiles: The Case of Khuzestan Province
Pouriya Alimoradi, Ali Barati, Hamid Barati
https://arxiv.org/abs/2510.03542

A Multi-Layer Electronic and Cyber Interference Model for AI-Driven Cruise Missiles: The Case of Khuzestan Province
The rapid advancement of Artificial Intelligence has enabled the development of cruise missiles endowed with high levels of autonomy, adaptability, and precision. These AI driven missiles integrating deep learning algorithms, real time data processing, and advanced guidance systems pose critical threats to strategic infrastructures, especially under complex geographic and climatic conditions such as those found in Irans Khuzestan Province. In this paper, we propose a multi layer interference mo…

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[1/4]:
- FC-PINO: High Precision Physics-Informed Neural Operators via Fourier Continuation
Ganeshram, Maust, Duruisseaux, Li, Wang, Leibovici, Bruno, Hou, Anandkumar

H2SGEMM: Emulating FP32 GEMM on Ascend NPUs using FP16 Units with Precision Recovery and Cache-Aware Optimization
Weicheng Xue, Baisong Xu, Kai Yang, Yongxiang Liu, Dengdeng Fan, Pengxiang Xu, Yonghong Tian
https://arxiv.org/abs/2507.23387

H2SGEMM: Emulating FP32 GEMM on Ascend NPUs using FP16 Units with Precision Recovery and Cache-Aware Optimization
Low-precision matrix engines, such as FP16 cube, offer high throughput but lack support for full-precision computation. In this work, we propose H2SGEMM, a high-performance algorithm for emulating FP32 general matrix-matrix multiplication (GEMM) using only FP16 computation units on a representative AI accelerator. The method decomposes each FP32 operand into two FP16 values and compensates for numerical errors through a tunable scaling strategy. A detailed analysis of numerical errors, includin…

Monte Carlo challenges for strong field quantum electrodynamics
Anthony Hartin
https://arxiv.org/abs/2509.05119 https://arxiv.org/pdf/2509.05119

Monte Carlo challenges for strong field quantum electrodynamics
The assisted Schwinger effect, which is predicted to display non-perturbative quantum tunnelling, is expected to be produced in precision lab experiments with electron beams and intense lasers. Indeed, many novel effects predicted by a theory which incorporates the laser field exactly, can be probed experimentally with the proper application of theory and simulation. Among predicted first order effects are a rest mass shift and harmonic Compton scattering. Higher order effects include resonant …

A multi-modal tactile fingertip design for robotic hands to enhance dexterous manipulation
Zhuowei Xu, Zilin Si, Kevin Zhang, Oliver Kroemer, Zeynep Temel
https://arxiv.org/abs/2510.05382

A multi-modal tactile fingertip design for robotic hands to enhance dexterous manipulation
Tactile sensing holds great promise for enhancing manipulation precision and versatility, but its adoption in robotic hands remains limited due to high sensor costs, manufacturing and integration challenges, and difficulties in extracting expressive and reliable information from signals. In this work, we present a low-cost, easy-to-make, adaptable, and compact fingertip design for robotic hands that integrates multi-modal tactile sensors. We use strain gauge sensors to capture static forces and…

Mixed Precision Photonic Computing with 3D Electronic-Photonic Integrated Circuits
Georgios Charalampous, Rui Chen, Mehmet Berkay On, Aslan Nasirov, Chun-Yi Cheng, Mahmoud AbdelGhany, Arka Majumdar, Ji Wang, Jennifer A. Black, Rajkumar Chinnakonda Kubendran, Caglar Oskay, Zhaojun Bai, Sam Palermo, Scott B. Papp, S. J. Ben Yoo
https://arxiv…

Mixed Precision Photonic Computing with 3D Electronic-Photonic Integrated Circuits
We propose advancing photonic in-memory computing through three-dimensional photonic-electronic integrated circuits using phase-change materials (PCM) and AlGaAs-CMOS technology. These circuits offer high precision (greater than 12 bits), scalability (greater than 1024 by 1024), and massive parallelism (greater than 1 million operations) across the wavelength, spatial, and temporal domains at ultra-low power (less than 1 watt per PetaOPS). Monolithically integrated hybrid PCM-AlGaAs memory reso…

📏 Optical frequency comb integration transforms absolute distance measurement precision
https://phys.org/news/2025-07-optical-frequency-absolute-distance-precision.html

Optical frequency comb integration transforms absolute distance measurement precision
The Korea Research Institute of Standards and Science has successfully developed a length measurement system that achieves a level of precision approaching the theoretical limit allowed by quantum physics.

Why Can't I See My Clusters? A Precision-Recall Approach to Dimensionality Reduction Validation
Diede P. M. van der Hoorn, Alessio Arleo, Fernando V. Paulovich
https://arxiv.org/abs/2509.04222

Why Can't I See My Clusters? A Precision-Recall Approach to Dimensionality Reduction Validation
Dimensionality Reduction (DR) is widely used for visualizing high-dimensional data, often with the goal of revealing expected cluster structure. However, such a structure may not always appear in the projections. Existing DR quality metrics assess projection reliability (to some extent) or cluster structure quality, but do not explain why expected structures are missing. Visual Analytics solutions can help, but are often time-consuming due to the large hyperparameter space. This paper addresses…

Verifier-free Test-Time Sampling for Vision Language Action Models
Suhyeok Jang, Dongyoung Kim, Changyeon Kim, Youngsuk Kim, Jinwoo Shin
https://arxiv.org/abs/2510.05681 https:/…

Verifier-free Test-Time Sampling for Vision Language Action Models
Vision-Language-Action models (VLAs) have demonstrated remarkable performance in robot control. However, they remain fundamentally limited in tasks that require high precision due to their single-inference paradigm. While test-time scaling approaches using external verifiers have shown promise, they require additional training and fail to generalize to unseen conditions. We propose Masking Distribution Guided Selection (MG-Select), a novel test-time scaling framework for VLAs that leverages the…

Granulation on a quiet K dwarf: HD 166620 I. Spectral signatures as a function of line-formation temperature
Ancy Anna John, Khaled Al Moulla, Niamh K. O Sullivan, Jay Fitzpatrick, Andrew Collier Cameron, Ben S. Lakeland, Michael Cretignier, Annelies Mortier, Tim Naylor, Joe Llama, Suzanne Aigrain, Christian Hartogh, Shweta Dalal, Heather M. Cegla, Christopher A. Watson, Xavier Dumusque, Aldo F. Martinez Fiorenzano

Granulation on a quiet K dwarf: HD 166620 I. Spectral signatures as a function of line-formation temperature
As Radial velocity (RV) spectrographs reach unprecedented precision and stability below 1 m/s, the challenge of granulation in the context of exoplanet detection has intensified. Despite promising advancements in post-processing tools, granulation remains a significant concern for the EPRV community. We present a pilot study to detect and characterise granulation using the High-Accuracy Radial-velocity Planet Searcher for the Northern hemisphere (HARPS-N) spectrograph. We observed HD166620, a K…

Reconstruction of the Dipole Amplitude in the Dipole Picture as a mathematical Inverse Problem
Henri H\"anninen, Antti Kykk\"anen, Hj{\o}rdis Schl\"uter
https://arxiv.org/abs/2509.05005 …

Reconstruction of the Dipole Amplitude in the Dipole Picture as a mathematical Inverse Problem
We show that the inference problem of constraining the dipole amplitude with inclusive deep inelastic scattering data can be written into a discrete linear inverse problem, in an analogous manner as can be done for computed tomography. To this formulation of the problem, we apply standard inverse problems methods and algorithms to reconstruct known dipole amplitudes from simulated reduced cross section data with realistic precision. The main difference of this approach to previous works is that…

The resummation model in FLAMINGO: precisely predicting matter power suppression from observed halo baryon fractions
Marcel P. van Daalen, Ioannis Koutalios, Jeger C. Broxterman, Bart J. H. Wolfs, John C. Helly, Matthieu Schaller, Joop Schaye
https://arxiv.org/abs/2509.04552

The resummation model in FLAMINGO: precisely predicting matter power suppression from observed halo baryon fractions
In order to derive unbiased cosmological parameters from Stage-IV surveys, we need models that can predict the matter power spectrum for at least $k\,\lesssim\,10\,h\mathrm{\,Mpc^{-1}}$ with percent-level precision. The main challenge in this endeavour is that baryonic feedback significantly redistributes matter on large scales, but to an unknown degree. Here, we present an improved version of the "resummation" model, which maps observed halo baryon fractions of massive haloes ($M_{\mathrm{500c…

Efficient Mixed-Precision Large Language Model Inference with TurboMind
Li Zhang, Youhe Jiang, Guoliang He, Xin Chen, Han Lv, Qian Yao, Fangcheng Fu, Kai Chen
https://arxiv.org/abs/2508.15601

Efficient Mixed-Precision Large Language Model Inference with TurboMind
Mixed-precision inference techniques reduce the memory and computational demands of Large Language Models (LLMs) by applying hybrid precision formats to model weights, activations, and KV caches. This work introduces mixed-precision LLM inference techniques that encompass (i) systematic memory and compute optimization across hierarchical storage and tensor core architectures, and (ii) comprehensive end-to-end mixed-precision optimization across diverse precision formats and hardware configurati…

Nanometer-precision tracking of adipocyte dynamics via single lipid droplet whispering-gallery optical resonances
Rok Podlipec, Ana Kri\v{s}elj, Maja Garvas Zorc, Petra Matjan \v{S}tefin, Siegfried Usaar, Matja\v{z} Humar
https://arxiv.org/abs/2509.04201

Nanometer-precision tracking of adipocyte dynamics via single lipid droplet whispering-gallery optical resonances
Biophotonics-and more recently, biointegrated photonics-offer transformative tools for probing cellular processes with unprecedented precision. Among these, whispering gallery mode (WGM) resonators-optical microcavities formed in spherical structures-have emerged as powerful biosensors and intracellular barcodes. Lipid droplets (LDs), with their high refractive index and intrinsic spherical geometry, are ideal candidates for supporting intracellular lasing. Although lasing in LDs has been previ…

Universal Precision Limits in General Open Quantum Systems
Tan Van Vu, Ryotaro Honma, Keiji Saito
https://arxiv.org/abs/2508.21567 https://arxiv.org/pdf/25…

Universal Precision Limits in General Open Quantum Systems
The intuition that the precision of observables is constrained by thermodynamic costs has recently been formalized through thermodynamic and kinetic uncertainty relations. While such trade-offs have been extensively studied in Markovian systems, corresponding constraints in the non-Markovian regime remain largely unexplored. In this Letter, we derive universal bounds on the precision of generic observables in open quantum systems coupled to environments of arbitrary strength and subjected to tw…

Symbolic regression and precision LHC physics
Josh Bendavid, Daniel Conde, Manuel Morales-Alvarado, Veronica Sanz, Maria Ubiali
https://arxiv.org/abs/2508.00989 https://

Symbolic regression and precision LHC physics
We explore the use of symbolic regression to derive compact analytical expressions for angular observables relevant to electroweak boson production at the Large Hadron Collider (LHC). Focusing on the angular coefficients that govern the decay distributions of $W$ and $Z$ bosons, we investigate whether symbolic models can well approximate these quantities, typically computed via computationally costly numerical procedures, with high fidelity and interpretability. Using the PySR package, we first…

The impact of galaxy bias on cross-correlation tomography
Sara Maleubre, Matteo Zennaro, David Alonso, Ian McCarthy, Matthieu Schaller, Joop Schaye
https://arxiv.org/abs/2508.05319

The impact of galaxy bias on cross-correlation tomography
The cross-correlation of galaxies at different redshifts with other tracers of the large-scale structure can be used to reconstruct the cosmic mean of key physical quantities, and their evolution over billions of years, at high precision. However, a correct interpretation of these measurements must ensure that they are independent of the clustering properties of the galaxy sample used. In this paper we explore different prescriptions to extract tomographic reconstruction measurements and use th…

Implementation of multiparticle quantum speed limits on observables
Rui-Heng Miao, Zhao-Di Liu, Chen-Xi Ning, Yu-Cong Hu, Hao Zhang, Chuan-Feng Li, Guang-Can Guo
https://arxiv.org/abs/2510.05794

Implementation of multiparticle quantum speed limits on observables
The energy-time uncertainty relation limits the maximum speed of quantum system evolution and is crucial for determining whether quantum tasks can be accelerated. However, multiparticle quantum speed limits have not been experimentally explored. In this work, we experimentally verify that both multiparticles and entanglement can accelerate the quantum speed on observables in two-particle systems based on ultrahigh precision control of quantum evolution time. Furthermore, we experimentally prove…

Graphite: A GPU-Accelerated Mixed-Precision Graph Optimization Framework
Shishir Gopinath, Karthik Dantu, Steven Y. Ko
https://arxiv.org/abs/2509.26581 https://

Graphite: A GPU-Accelerated Mixed-Precision Graph Optimization Framework
We present Graphite, a GPU-accelerated nonlinear graph optimization framework. It provides a CUDA C++ interface to enable the sharing of code between a realtime application, such as a SLAM system, and its optimization tasks. The framework supports techniques to reduce memory usage, including in-place optimization, support for multiple floating point types and mixed-precision modes, and dynamically computed Jacobians. We evaluate Graphite on well-known bundle adjustment problems and find that it…

A New Quantum Linear System Algorithm Beyond the Condition Number and Its Application to Solving Multivariate Polynomial Systems
Jianqiang Li
https://arxiv.org/abs/2510.05588 ht…

A New Quantum Linear System Algorithm Beyond the Condition Number and Its Application to Solving Multivariate Polynomial Systems
Given a matrix $A$ of dimension $M \times N$ and a vector $\vec{b}$, the quantum linear system (QLS) problem asks for the preparation of a quantum state $|\vec{y}\rangle$ proportional to the solution of $A\vec{y} = \vec{b}$. Existing QLS algorithms have runtimes that scale linearly with the condition number $κ(A)$, the sparsity of $A$, and logarithmically with inverse precision, but often overlook structural properties of $\vec{b}$, whose alignment with $A$'s eigenspaces can greatly affec…

SCOUT: An in-vivo Methane Sensing System for Real-time Monitoring of Enteric Emissions in Cattle with ex-vivo Validation
Yuelin Deng, Hinayah Rojas de Oliveira, Richard M. Voyles, Upinder Kaur
https://arxiv.org/abs/2508.04056

SCOUT: An in-vivo Methane Sensing System for Real-time Monitoring of Enteric Emissions in Cattle with ex-vivo Validation
Accurate measurement of enteric methane emissions remains a critical bottleneck for advancing livestock sustainability through genetic selection and precision management. Existing ambient sampling approaches suffer from low data retention rates, environmental interference, and limited temporal resolution. We developed SCOUT (Smart Cannula-mounted Optical Unit for Trace-methane), the first robust in-vivo sensing system enabling continuous, high-resolution monitoring of ruminal methane concentrat…

ResMimic: From General Motion Tracking to Humanoid Whole-body Loco-Manipulation via Residual Learning
Siheng Zhao, Yanjie Ze, Yue Wang, C. Karen Liu, Pieter Abbeel, Guanya Shi, Rocky Duan
https://arxiv.org/abs/2510.05070

ResMimic: From General Motion Tracking to Humanoid Whole-body Loco-Manipulation via Residual Learning
Humanoid whole-body loco-manipulation promises transformative capabilities for daily service and warehouse tasks. While recent advances in general motion tracking (GMT) have enabled humanoids to reproduce diverse human motions, these policies lack the precision and object awareness required for loco-manipulation. To this end, we introduce ResMimic, a two-stage residual learning framework for precise and expressive humanoid control from human motion data. First, a GMT policy, trained on large-sc…