Tootfinder

📏 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.

A robust and compliant robotic assembly control strategy for batch precision assembly task with uncertain fit types and fit amounts
Bin Wang, Jiwen Zhang, Song Wang, Dan Wu
https://arxiv.org/abs/2508.12296

A robust and compliant robotic assembly control strategy for batch precision assembly task with uncertain fit types and fit amounts
In some high-precision industrial applications, robots are deployed to perform precision assembly tasks on mass batches of manufactured pegs and holes. If the peg and hole are designed with transition fit, machining errors may lead to either a clearance or an interference fit for a specific pair of components, with uncertain fit amounts. This paper focuses on the robotic batch precision assembly task involving components with uncertain fit types and fit amounts, and proposes an efficient method…

Phase-Driven Precision Boost in Quantum Compression for Postselected Metrology
Aiham M. Rostom, Saeed Haddadi, Vladimir A. Tomilin
https://arxiv.org/abs/2508.13934 https://

Phase-Driven Precision Boost in Quantum Compression for Postselected Metrology
We unveil the noncyclic Pancharatnam phase as a fundamental geometric criterion governing the optimal operation of quantum compression channels in postselected metrology. Harnessing this phase enables precise control over the interplay between orthogonal parameter sensitivity and parallel evolution in the meter state, thereby maximizing the quantum Fisher information per trial. Strikingly, fine-tuning the postselection parameter just below this optimal phase incurs substantial information loss,…

Precise Action-to-Video Generation Through Visual Action Prompts
Yuang Wang, Chao Wen, Haoyu Guo, Sida Peng, Minghan Qin, Hujun Bao, Xiaowei Zhou, Ruizhen Hu
https://arxiv.org/abs/2508.13104

Precise Action-to-Video Generation Through Visual Action Prompts
We present visual action prompts, a unified action representation for action-to-video generation of complex high-DoF interactions while maintaining transferable visual dynamics across domains. Action-driven video generation faces a precision-generality trade-off: existing methods using text, primitive actions, or coarse masks offer generality but lack precision, while agent-centric action signals provide precision at the cost of cross-domain transferability. To balance action precision and dyna…

Deep Precision Strike https://www.german-foreign-policy.com/news/detail/10068

Complementarity between gravitational wave signatures and Higgs precision measurements of a classically conformal hidden U(1) extended Standard Model
Victor Baules, Nobuchika Okada
https://arxiv.org/abs/2508.13527

Complementarity between gravitational wave signatures and Higgs precision measurements of a classically conformal hidden U(1) extended Standard Model
We consider a classically conformal extension of the Standard Model (SM) with a hidden $U(1)$ gauge symmetry, where the $U(1)$ symmetry is radiatively broken via the Coleman-Weinberg mechanism. This radiative breaking then induces electroweak (EW) symmetry breaking through a negative mixed quartic coupling between the hidden sector Higgs field and the SM Higgs doublet. Due to the mixed quartic coupling, the original two Higgs fields mix with a small angle $θ$ to form two mass eigenstates, $h_1…

Iterative Youla-Kucera Loop Shaping For Precision Motion Control
Xiaohai Hu, Jason Laks, Guoxiao Guo, Xu Chen
https://arxiv.org/abs/2508.14309 https://arxi…

Iterative Youla-Kucera Loop Shaping For Precision Motion Control
This paper presents a numerically robust approach to multi-band disturbance rejection using an iterative Youla-Kucera parameterization technique. The proposed method offers precise control over shaping the frequency response of a feedback loop while maintaining numerical stability through a systematic design process. By implementing an iterative approach, we overcome a critical numerical issue in rejecting vibrations with multiple frequency bands. Meanwhile, our proposed modification of the all…

XR-NPE: High-Throughput Mixed-precision SIMD Neural Processing Engine for Extended Reality Perception Workloads
Tejas Chaudhari, Akarsh J., Tanushree Dewangan, Mukul Lokhande, Santosh Kumar Vishvakarma
https://arxiv.org/abs/2508.13049

XR-NPE: High-Throughput Mixed-precision SIMD Neural Processing Engine for Extended Reality Perception Workloads
This work proposes XR-NPE, a high-throughput Mixed-precision SIMD Neural Processing Engine, designed for extended reality (XR) perception workloads like visual inertial odometry (VIO), object classification, and eye gaze extraction. XR-NPE is first to support FP4, Posit (4,1), Posit (8,0), and Posit (16,1) formats, with layer adaptive hybrid-algorithmic implementation supporting ultra-low bit precision to significantly reduce memory bandwidth requirements, and accompanied by quantization-aware …

A Bayesian Dirichlet Auto-Regressive Conditional Heteroskedasticity Model for Compositional Time Series
Harrison Katz, Robert E. Weiss
https://arxiv.org/abs/2507.14132

A Bayesian Dirichlet Auto-Regressive Conditional Heteroskedasticity Model for Compositional Time Series
We analyze daily Airbnb service-fee shares across eleven settlement currencies, a compositional series that shows bursts of volatility after shocks such as the COVID-19 pandemic. Standard Dirichlet time series models assume constant precision and therefore miss these episodes. We introduce B-DARMA-DARCH, a Bayesian Dirichlet autoregressive moving average model with a Dirichlet ARCH component, which lets the precision parameter follow an ARMA recursion. The specification preserves the Dirichlet …

Controlling the Flow of Information in Optical Metrology
Maximilian Weimar, Huanli Zhou, Luca Neubacher, Thomas A. Grant, Jakob H\"upfl, Kevin F. MacDonald, Stefan Rotter, Nikolay I. Zheludev
https://arxiv.org/abs/2508.13640

Controlling the Flow of Information in Optical Metrology
Optical metrology has progressed beyond the Abbe-Rayleigh limit, unlocking (sub)atomic precision by leveraging nonlinear phenomena, statistical accumulation, and AI-estimators trained on measurand variations. Here, we reveal that Fisher information, which defines the fundamental precision limit, can be viewed as a physical entity that propagates through space, and we derive the wave equation for sensitivity fields defining the flow of Fisher information, which can resonate, diffract, and interf…

Approximate Bayesian Inference via Bitstring Representations
Aleksanteri Sladek, Martin Trapp, Arno Solin
https://arxiv.org/abs/2508.13598 https://arxiv.or…

Approximate Bayesian Inference via Bitstring Representations
The machine learning community has recently put effort into quantized or low-precision arithmetics to scale large models. This paper proposes performing probabilistic inference in the quantized, discrete parameter space created by these representations, effectively enabling us to learn a continuous distribution using discrete parameters. We consider both 2D densities and quantized neural networks, where we introduce a tractable learning approach using probabilistic circuits. This method offers …

Dynamics-independent bounds on state transformations and precision in open quantum systems
Yoshihiko Hasegawa
https://arxiv.org/abs/2508.13884 https://arxi…

Dynamics-independent bounds on state transformations and precision in open quantum systems
We derive dynamics-independent upper bounds on achievable quantum state transformations. Modeling the evolution as a joint unitary on the system and its environment, we show that the Rényi divergence between the initial system state and any state reachable via the dynamics is bounded from above by a quantity determined solely by the eigenvalues of the initial system and environment density operators. As a consequence, we establish dynamics-independent lower bounds on the relative variance for …

Iteratively Learning Muscle Memory for Legged Robots to Master Adaptive and High Precision Locomotion
Jing Cheng, Yasser G. Alqaham, Zhenyu Gan, Amit K. Sanyal
https://arxiv.org/abs/2507.13662

Iteratively Learning Muscle Memory for Legged Robots to Master Adaptive and High Precision Locomotion
This paper presents a scalable and adaptive control framework for legged robots that integrates Iterative Learning Control (ILC) with a biologically inspired torque library (TL), analogous to muscle memory. The proposed method addresses key challenges in robotic locomotion, including accurate trajectory tracking under unmodeled dynamics and external disturbances. By leveraging the repetitive nature of periodic gaits and extending ILC to nonperiodic tasks, the framework enhances accuracy and gen…

Random Variate Generation with Formal Guarantees
Feras A. Saad, Wonyeol Lee
https://arxiv.org/abs/2507.13494 https://arxiv.org/pdf/25…

Random Variate Generation with Formal Guarantees
This article introduces a new approach to principled and practical random variate generation with formal guarantees. The key idea is to first specify the desired probability distribution in terms of a finite-precision numerical program that defines its cumulative distribution function (CDF), and then generate exact random variates according to this CDF. We present a universal and fully automated method to synthesize exact random variate generators given any numerical CDF implemented in any bina…

CPC-CMS: Cognitive Pairwise Comparison Classification Model Selection Framework for Document-level Sentiment Analysis
Jianfei Li, Kevin Kam Fung Yuen
https://arxiv.org/abs/2507.14022

CPC-CMS: Cognitive Pairwise Comparison Classification Model Selection Framework for Document-level Sentiment Analysis
This study proposes the Cognitive Pairwise Comparison Classification Model Selection (CPC-CMS) framework for document-level sentiment analysis. The CPC, based on expert knowledge judgment, is used to calculate the weights of evaluation criteria, including accuracy, precision, recall, F1-score, specificity, Matthews Correlation Coefficient (MCC), Cohen's Kappa (Kappa), and efficiency. Naive Bayes, Linear Support Vector Classification (LSVC), Random Forest, Logistic Regression, Extreme Gradient B…

Controlling Context: Generative AI at Work in Integrated Circuit Design and Other High-Precision Domains
Emanuel Moss, Elizabeth Watkins, Christopher Persaud, Passant Karunaratne, Dawn Nafus
https://arxiv.org/abs/2506.14567

Controlling Context: Generative AI at Work in Integrated Circuit Design and Other High-Precision Domains
Generative AI tools have become more prevalent in engineering workflows, particularly through chatbots and code assistants. As the perceived accuracy of these tools improves, questions arise about whether and how those who work in high-precision domains might maintain vigilance for errors, and what other aspects of using such tools might trouble their work. This paper analyzes interviews with hardware and software engineers, and their collaborators, who work in integrated circuit design to iden…

from my link log —
Precision Clock Mk IV.
https://mitxela.com/projects/precision_clock_mk_iv
saved 2025-05-31 https://…

Precision and cost of feedback cooling
Andreas Dechant, Jakob H\"upfl, Shuta Kobayashi, Sosuke Ito, Stefan Rotter
https://arxiv.org/abs/2508.12875 https://

Precision and cost of feedback cooling
We investigate the consequences of information exchange between a system and a measurement-feedback apparatus that cools the system below the environmental temperature. A quantitative relationship between entropy pumping and information acquired about the system is derived, showing that, independent of the concrete realization of the feedback, the latter exceeds the former by a positive amount of excess information flow. This excess information flow satisfies a trade-off relation with the preci…

Koalas on the brink: Precision DNA test offers a lifeline to Australia’s icons #Australia

Koalas on the brink: Precision DNA test offers a lifeline to Australia’s icons
A University of Queensland-led project has developed a tool to standardise genetic testing of koala populations, providing a significant boost to conservation and recovery efforts.

Scaling the memory wall using mixed-precision -- HPG-MxP on an exascale machine
Aditya Kashi, Nicholson Koukpaizan, Hao Lu, Michael Matheson, Sarp Oral, Feiyi Wang
https://arxiv.org/abs/2507.11512

Scaling the memory wall using mixed-precision -- HPG-MxP on an exascale machine
Mixed-precision algorithms have been proposed as a way for scientific computing to benefit from some of the gains seen for artificial intelligence (AI) on recent high performance computing (HPC) platforms. A few applications dominated by dense matrix operations have seen substantial speedups by utilizing low precision formats such as FP16. However, a majority of scientific simulation applications are memory bandwidth limited. Beyond preliminary studies, the practical gain from using mixed-preci…

Hilbert geometry of the symmetric positive-definite bicone: Application to the geometry of the extended Gaussian family
Jacek Karwowski, Frank Nielsen
https://arxiv.org/abs/2508.14369

Hilbert geometry of the symmetric positive-definite bicone: Application to the geometry of the extended Gaussian family
The extended Gaussian family is the closure of the Gaussian family obtained by completing the Gaussian family with the counterpart elements induced by degenerate covariance or degenerate precision matrices, or a mix of both degeneracies. The parameter space of the extended Gaussian family forms a symmetric positive semi-definite matrix bicone, i.e. two partial symmetric positive semi-definite matrix cones joined at their bases. In this paper, we study the Hilbert geometry of such an open bounde…

Precision and rare ElectroWeak processes
Francesco Giuli
https://arxiv.org/abs/2506.14465 https://arxiv.org/pdf/2506.14465

Precision and rare ElectroWeak processes
This proceeding summarizes recent measurements of electroweak boson and diboson production. The results, based on data from LHC Run 2 and Run 3 at $\sqrt{s}=13$ and $13.6\,\mathrm{TeV}$, probe the Standard Model with unprecedented precision. These include inclusive and differential cross-section measurements of $W$, $Z$, $WZ$, $WW$, and $ZZ$ final states, constraints on Parton Distribution Functions, and interpretations within Effective Field Theories. A consistent picture with theory predictio…

Towards sub-milliarcsecond astrometric precision using seeing-limited imaging
Noam Segev, Eran O. Ofek, Yossi Shvartzvald, Krzysztof A. Rybicki, Chung-Uk Lee, Dong-Jin Kim, Jennifer C. Yee, Michael D. Albrow, Sun-Ju Chung, Andrew Gould, Cheongho Han, Kyu-Ha Hwang, Youn Kil Jung, In-Gu Shin, Hongjing Yang, Weicheng Zang, Sang-Mok Cha, Hyoun-Woo Kim, Seung-Lee Kim, Yoon-Hyun Ryu, Dong-Joo Lee, Yongseok Lee, Byeong-Gon Park, Richard W. Pogge

Towards sub-milliarcsecond astrometric precision using seeing-limited imaging
The Earth's atmospheric turbulence degrades the precision of ground-based astrometry. Here we discuss these limitations and propose that, with proper treatment of systematics and by leveraging the many epochs available from the Korean Microlensing Telescope Network (KMTNet), seeing-limited observations can reach sub-milliarcsecond precision. Such observations may be instrumental for the detection of Galactic black holes via microlensing. We present our methodology and pipeline for precise astro…

⚛️ 3D printing reshapes construction for nuclear energy
#energy

3D printing reshapes construction for nuclear energy
In a bold step toward transforming how nuclear infrastructure is built, the Department of Energy's Manufacturing Demonstration Facility, or MDF, at Oak Ridge National Laboratory, in partnership with Kairos Power and Barnard Construction, has successfully developed and validated large-scale, 3D-printed polymer composite forms for casting complex, high-precision concrete structures that would be technically challenging and costly to produce using conventional methods. The concrete forms are being…

A 3D segmented Water-based Liquid Scintillator for high-precision detection of neutrinos in water
Botao Li, Daria Borodulina, Davide Sgalaberna, Tim Weber, Minfang Yeh, Umut Kose, Matthew Franks, Andr\'e Rubbia, Johannes W\"uthrich, Claudio Giganti, Tatsuya Kikawa
https://arxiv.org/abs/2508.11355

A 3D segmented Water-based Liquid Scintillator for high-precision detection of neutrinos in water
Precision detection of neutrino-nucleus interactions in water with the complete detection of the final state, including leptons and hadrons, is challenging due to water being a non-scintillating medium. This can be a limitation for the next-generation long-baseline neutrino oscillation experiments, such as Hyper-Kamiokande, where the neutrino-nucleus interaction models must reach a few percent-level accuracy. Water-based liquid scintillator can be a game changer for the future near detectors. I…

Reconstructing galactic feedback history via the Lyman-$\alpha$ forest with Habitable Worlds Observatory
Megan T. Tillman, Joseph N. Burchett, Blakesley Burkhart, Vikram Khaire, Sanchayeeta Borthakur
https://arxiv.org/abs/2507.13442

Reconstructing galactic feedback history via the Lyman-$α$ forest with Habitable Worlds Observatory
Recent studies have focused on the low-$z$ Ly$α$ forest as a potential constraint on galactic feedback, as different AGN and stellar feedback models in hydrodynamic simulations produce varying intergalactic medium (IGM) statistics. However, existing low-$z$ Ly$α$ forest data provide insufficient observational constraints for simulations due to their low precision and the lack of observations from $z \sim 0.4$ to $1.8$. The Habitable Worlds Observatory, equipped with an ultraviolet (FUV / NUV)…

Towards high-precision inspiral gravitational waveforms from binary neutron star mergers in numerical relativity
Kenta Kiuchi
https://arxiv.org/abs/2508.10981 https://

Towards high-precision inspiral gravitational waveforms from binary neutron star mergers in numerical relativity
We report the performance of a newly implemented fourth-order accurate finite-volume HLLC Riemann solver in the adaptive-mesh-refinement numerical relativity code {\tt SACRA-MPI}. First, we validate our implementation in one-dimensional special relativistic hydrodynamics tests, i.e., a simple wave and shock tube test, which have analytic solutions. We demonstrate that the fourth-order convergence is achieved for the smooth flow, which cannot be achieved in our original second-order accurate fin…

OPTIC-ER: A Reinforcement Learning Framework for Real-Time Emergency Response and Equitable Resource Allocation in Underserved African Communities
Mary Tonwe
https://arxiv.org/abs/2508.12943

OPTIC-ER: A Reinforcement Learning Framework for Real-Time Emergency Response and Equitable Resource Allocation in Underserved African Communities
Public service systems in many African regions suffer from delayed emergency response and spatial inequity, causing avoidable suffering. This paper introduces OPTIC-ER, a reinforcement learning (RL) framework for real-time, adaptive, and equitable emergency response. OPTIC-ER uses an attention-guided actor-critic architecture to manage the complexity of dispatch environments. Its key innovations are a Context-Rich State Vector, encoding action sub-optimality, and a Precision Reward Function, wh…

Phenomenological characterization of the isomerization transition state of carbonyl sulfide
Amine Rafik, Jamil Khalouf-Rivera, F. P\'erez-Bernal, Khadija Marakchi, Miguel Carvajal
https://arxiv.org/abs/2507.14027

Phenomenological characterization of the isomerization transition state of carbonyl sulfide
Signatures of excited-state quantum phase transitions in the bending degree of freedom of triatomic systems that undergo an isomerization reaction have been recently evinced. In this work, we study the carbonyl sulfide bending motion using an effective Hamiltonian within the two-dimensional limit of the vibron model framework, which has been shown to accurately describe critical phenomena in molecular bending spectra within experimental precision. To estimate the transition state energy barrier…

Resources for bosonic metrology: quantum-enhanced precision from a superselection rule perspective
Astghik Saharyan, Eloi Descamps, Arne Keller, P\'erola Milman
https://arxiv.org/abs/2507.13245

Resources for bosonic metrology: quantum-enhanced precision from a superselection rule perspective
Quantum optics and atomic systems are prominent platforms for exploiting quantum-enhanced precision in parameter estimation. However, not only are quantum optical and atomic systems often treated separately, but even within quantum optics, identifying optimal probes (quantum states) and evolutions (parameter-dependent dynamics) typically relies on case-by-case analyses. Mode, and sometimes only particle entanglement, can yield quantum enhancement of precision in continuous- and discrete-variabl…

Breaking the material-limited temperature coefficient of resistance via carrier feedback in a single transistor
Jiazhen Chen, Yihao Song, David Alexander Montealegre, Mingyang Cai, Minjoo Larry Lee, Fengnian Xia
https://arxiv.org/abs/2508.13987

Breaking the material-limited temperature coefficient of resistance via carrier feedback in a single transistor
The temperature coefficient of resistance (TCR) is one of the most fundamental properties of a material. Semiconductor materials exhibiting high TCR are promising candidates for applications in high-resolution thermal imaging for autonomous systems, high-precision temperature sensing, and neuromorphic computing. However, the TCR magnitude is typically below 5%/K near 300 K for thermal imaging materials, such as vanadium oxide and amorphous silicon. Inspired by the distinctive characteristic of …

Linearly Polarized Photon Fusion as a Precision Probe of the Tau Lepton Dipole Moments at Lepton Colliders
Ding Yu Shao, Hao Xiang, Fang Xu, Bin Yan, Cheng Zhang
https://arxiv.org/abs/2506.15245

Linearly Polarized Photon Fusion as a Precision Probe of the Tau Lepton Dipole Moments at Lepton Colliders
We present a comprehensive investigation into the anomalous magnetic dipole moment ($a_τ$) and electric dipole moment ($d_τ$) of the $τ$ lepton using the $γγ\to τ^+τ^-$ process at future lepton colliders, with the Super Tau-Charm Facility serving as a benchmark. By employing transverse-momentum-dependent factorization, we introduce novel observables derived from $\cos2ϕ$, $\sin2ϕ$, and $\cos4ϕ$ azimuthal asymmetries to precisely probe the $τ$ lepton's electromagnetic structure. Our a…

Improving Prostate Gland Segmenting Using Transformer based Architectures
Shatha Abudalou
https://arxiv.org/abs/2506.14844 https://ar…

Improving Prostate Gland Segmenting Using Transformer based Architectures
Inter reader variability and cross site domain shift challenge the automatic segmentation of prostate anatomy using T2 weighted MRI images. This study investigates whether transformer models can retain precision amid such heterogeneity. We compare the performance of UNETR and SwinUNETR in prostate gland segmentation against our previous 3D UNet model [1], based on 546 MRI (T2weighted) volumes annotated by two independent experts. Three training strategies were analyzed: single cohort dataset, 5…

Range-Angle Likelihood Maps for Indoor Positioning Using Deep Neural Networks
Muhammad Ammad, Paul Schwarzbach, Michael Schultz, Oliver Michler
https://arxiv.org/abs/2508.12746 …

Range-Angle Likelihood Maps for Indoor Positioning Using Deep Neural Networks
Accurate and high precision of the indoor positioning is as important as ensuring reliable navigation in outdoor environments. Using the state-of-the-art deep learning models provides better reliability and accuracy to navigate and monitor the accurate positions in the aircraft cabin environment. We utilize the simulated aircraft cabin environment measurements and propose a residual neural network (ResNet) model to predict the accurate positions inside the cabin. The measurements include the ra…

On #CNN, Major General Randy Menner (retired) just compared the precision of Israeli air strikes to “#HanSolo dropping the missile down the elevator shaft”. Yikes.

Half of North Korea's first missile shipment to Russia exploded in mid-air — now they strike Ukrainian targets with deadly precision - Euromaidan Press
https://euromaidanpress.com/2025/06/10/half-of-north-koreas-first-missile-shipment-to-russia-exploded-in-mid-air-now-they-strike-ukrainian-targets-with-deadly-precision/

White-Box Reasoning: Synergizing LLM Strategy and gm/Id Data for Automated Analog Circuit Design
Jianqiu Chen, Siqi Li, Xu He
https://arxiv.org/abs/2508.13172 https://

White-Box Reasoning: Synergizing LLM Strategy and gm/Id Data for Automated Analog Circuit Design
Analog IC design is a bottleneck due to its reliance on experience and inefficient simulations, as traditional formulas fail in advanced nodes. Applying Large Language Models (LLMs) directly to this problem risks mere "guessing" without engineering principles. We present a "synergistic reasoning" framework that integrates an LLM's strategic reasoning with the physical precision of the gm/Id methodology. By empowering the LLM with gm/Id lookup tables, it becomes a quantitative, data-driven desig…

Accurate Reduced Floating-Point Precision Implicit Monte Carlo
Simon Butson, Mathew Cleveland, Alex Long, Todd Palmer
https://arxiv.org/abs/2506.11962 http…

Accurate Reduced Floating-Point Precision Implicit Monte Carlo
This work describes methodologies to successfully implement the Implicit Monte Carlo (IMC) scheme for thermal radiative transfer in reduced-precision floating-point arithmetic. The methods used can be broadly categorized into scaling approaches and floating-point arithmetic manipulations. Scaling approaches entail re-scaling values to ensure computations stay within a representable range. Floating-point arithmetic manipulations involve changes to order of operations and alternative summation al…

Hard-Stop Synthesis for Multi-DOF Compliant Mechanisms
Dean Chen, Armin Pomeroy, Brandon T. Peterson, Will Flanagan, He Kai Lim, Alexandra Stavrakis, Nelson F. SooHoo, Jonathan B. Hopkins, Tyler R. Clites
https://arxiv.org/abs/2507.13455

Hard-Stop Synthesis for Multi-DOF Compliant Mechanisms
Compliant mechanisms have significant potential in precision applications due to their ability to guide motion without contact. However, an inherent vulnerability to fatigue and mechanical failure has hindered the translation of compliant mechanisms to real-world applications. This is particularly challenging in service environments where loading is complex and uncertain, and the cost of failure is high. In such cases, mechanical hard stops are critical to prevent yielding and buckling. Convent…

On regularizations of the integral representation of Dirac delta function -- elementary approach
Grzegorz M. Koczan, Piotr Stachura
https://arxiv.org/abs/2508.11639 https://

On regularizations of the integral representation of Dirac delta function -- elementary approach
The article presents, in an elementary way, but with mathematical precision and without harm to the intuition, the path from the integral representation to the Dirac delta, starting with Schwartz's functional approach. Next, the considered representation is presented in a more intuitive sequential approach, formulated by Mikusiński and Sikorski. Finally, we present the third regularization that can be related to Sato's approach to distributions.

Operando Electron Microscopy of Nanoscale Electronic Devices on Non-Conductive Substrates
Menglin Zhu, Michael Xu, Zishen Tian, Colin Gilgenbach, Daniel Drury, Bridget R. Denzer, Ching-Che Lin, Deokyoung Kang, Lane W. Martin, James M. LeBeau
https://arxiv.org/abs/2508.12503

Operando Electron Microscopy of Nanoscale Electronic Devices on Non-Conductive Substrates
Achieving operating conditions comparable to ``bulk'' electronic devices, such as thin film capacitors, during \textit{operando} electron microscopy remains challenging, particularly when devices are grown on non-conductive substrates. Limited precision of focused ion beam milling for sample preparation often necessitates the use of conductive substrates or artificially thick layers that differ from actual device architectures. These modifications can alter native strain, electrostatic boundary…

The JWST Rocky Worlds DDT Program reveals GJ 3929b to likely be a bare rock
Qiao Xue, Michael Zhang, Brandon P. Coy, Madison Brady, Xuan Ji, Jacob L. Bean, Michael Radica, Andreas Seifahrt, Julian Sturmer, Rafael Luque, Ritvik Basant, Nina Brown, Tanya Das, David Kasper, Caroline Piaulet-Ghorayeb, Eliza M. -R. Kempton, Edwin S. Kite
https://

The JWST Rocky Worlds DDT Program reveals GJ 3929b to likely be a bare rock
We report first results from the JWST Rocky Worlds Director's Discretionary Time program. Two secondary eclipses of the terrestrial exoplanet GJ 3929b were recently observed using MIRI photometric imaging at 15 um. We present a reduction of these data using the updated SPARTA pipeline. We also refine the planet mass, radius, and predicted time of secondary eclipse using a new sector of TESS data and new, high-precision radial velocities from the MAROON-X spectrograph. For the two JWST observati…

Ever wondered how Kubernetes runs on a tractor? At Berlin Buzzwords 2025, join Wieneke Keller & Sebastian Lenartowicz from Aurea Imaging to explore their innovative AgTech journey! Discover how they built an edge device with Python microservices and K3s for precision farming, tackling unique rural challenges. 
Learn more:

Precision farming powered by K3s and TensorRT
Aurea Imaging is an AgTech scaleup focusing on precision farming in orchards. By retrofitting our TreeScout sensor package to their tractors, farmers are able to collect data about their orchard down to the tree level as they perform other tasks. Using onboard stereo cameras, the tractor’s high-precision GPS, a machine-vision pipeline running in real time on the device, and cloud-based analytics, this data is turned into maps used by other agricultural machines that enable the grower to utili…

This https://arxiv.org/abs/2501.03742 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Computing accurate eigenvalues using a mixed-precision Jacobi algorithm
We provide a rounding error analysis of a mixed-precision preconditioned Jacobi algorithm, which uses low precision to compute the preconditioner, applies it at high precision (amounting to two matrix-matrix multiplications) and solves the eigenproblem using the Jacobi algorithm at working precision. Our analysis yields meaningfully smaller relative forward error bounds for the computed eigenvalues compared with those of the Jacobi algorithm. We further prove that, after preconditioning, if the…

Precision Measurement of Large Shear Signals
Jiarui Sun, Jun Zhang, Li Cui, Alessandro Sonnenfeld, Xin Wang
https://arxiv.org/abs/2508.10319 https://arxiv.…

Precision Measurement of Large Shear Signals
So far, estimators of galaxy shape distortions are only carefully studied perturbatively in the case of small shear signals, mainly for weak lensing sciences. However, in the neighborhood of massive foreground clusters, a large number of background galaxies can be significantly distorted. The measurement of such large shear signals could be quite nontrivial under general observing conditions, i.e., in the presence of the point spread function (PSF) and noise. In this work, we propose a non-pert…

Observable Optimization for Precision Theory: Machine Learning Energy Correlators
Arindam Bhattacharya, Katherine Fraser, Matthew D. Schwartz
https://arxiv.org/abs/2508.10988 ht…

Observable Optimization for Precision Theory: Machine Learning Energy Correlators
The practice of collider physics typically involves the marginalization of multi-dimensional collider data to uni-dimensional observables relevant for some physics task. In any cases, such as classification or anomaly detection, the observable can be arbitrarily complicated, such as the output of a neural network. However, for precision measurements, the observable must correspond to something computable systematically beyond the level of current simulation tools. In this work, we demonstrate t…

XGraphRAG: Interactive Visual Analysis for Graph-based Retrieval-Augmented Generation
Ke Wang, Bo Pan, Yingchaojie Feng, Yuwei Wu, Jieyi Chen, Minfeng Zhu, Wei Chen
https://arxiv.org/abs/2506.13782

XGraphRAG: Interactive Visual Analysis for Graph-based Retrieval-Augmented Generation
Graph-based Retrieval-Augmented Generation (RAG) has shown great capability in enhancing Large Language Model (LLM)'s answer with an external knowledge base. Compared to traditional RAG, it introduces a graph as an intermediate representation to capture better structured relational knowledge in the corpus, elevating the precision and comprehensiveness of generation results. However, developers usually face challenges in analyzing the effectiveness of GraphRAG on their dataset due to GraphRAG's …

Quantum Phase Estimation Beyond the Gaussian Limit
Kimin Park, Tanjung Krisnanda, Yvonne Gao, Radim Filip
https://arxiv.org/abs/2508.13046 https://arxiv.or…

Quantum Phase Estimation Beyond the Gaussian Limit
Quantum metrology aims to enhance measurement precision beyond the standard quantum limit (SQL), the benchmark set by classical resources, enabling advances in sensing, imaging, and fundamental physics. A critical milestone beyond the SQL is surpassing the Gaussian bound -- the fundamental precision limit achievable with any Gaussian state, such as optimally squeezed states. Certain non-Gaussian states, specifically asymmetric superpositions of coherent states (SCS) and superpositions of a vacu…

Speech Emotion Recognition Using Fine-Tuned DWFormer:A Study on Track 1 of the IERPChallenge 2024
Honghong Wang, Xupeng Jia, Jing Deng, Rong Zheng
https://arxiv.org/abs/2508.11371

Speech Emotion Recognition Using Fine-Tuned DWFormer:A Study on Track 1 of the IERPChallenge 2024
The field of artificial intelligence has a strong interest in the topic of emotion recognition. The majority of extant emotion recognition models are oriented towards enhancing the precision of discrete emotion label prediction. Given the direct relationship between human personality and emotion, as well as the significant inter-individual differences in subjective emotional expression, the IERP Challenge 2024 incorporates personality traits into emotion recognition research. This paper present…

High-precision baryon number cumulants from lattice QCD in a finite box: cumulant ratios, Lee-Yang zeros and critical endpoint predictions
Alexander Adam, Szabolcs Bors\'anyi, Zoltan Fodor, Jana N. Guenther, Piyush Kumar, Paolo Parotto, Attila P\'asztor, Chik Him Wong
https://arxiv.org/abs/2507.13254

High-precision baryon number cumulants from lattice QCD in a finite box: cumulant ratios, Lee-Yang zeros and critical endpoint predictions
We have performed high-statistics lattice simulations using 4HEX improved staggered fermions on $16^3 \times 8$ lattices. We calculated the Taylor expansion coefficients of the pressure with respect to the baryochemical potential to the tenth order at zero, and fourth order at purely imaginary chemical potentials. We used this data to construct rational function approximations of the free energy. We use a rational ansatz that explicitly satisfies the charge conjugation symmetry and the Roberge-…

SoK: The Privacy Paradox of Large Language Models: Advancements, Privacy Risks, and Mitigation
Yashothara Shanmugarasa, Ming Ding, M. A. P Chamikara, Thierry Rakotoarivelo
https://arxiv.org/abs/2506.12699

SoK: The Privacy Paradox of Large Language Models: Advancements, Privacy Risks, and Mitigation
Large language models (LLMs) are sophisticated artificial intelligence systems that enable machines to generate human-like text with remarkable precision. While LLMs offer significant technological progress, their development using vast amounts of user data scraped from the web and collected from extensive user interactions poses risks of sensitive information leakage. Most existing surveys focus on the privacy implications of the training data but tend to overlook privacy risks from user inter…

Taming VR Teleoperation and Learning from Demonstration for Multi-Task Bimanual Table Service Manipulation
Weize Li, Zhengxiao Han, Lixin Xu, Xiangyu Chen, Harrison Bounds, Chenrui Zhang, Yifan Xu
https://arxiv.org/abs/2508.14542

Taming VR Teleoperation and Learning from Demonstration for Multi-Task Bimanual Table Service Manipulation
This technical report presents the champion solution of the Table Service Track in the ICRA 2025 What Bimanuals Can Do (WBCD) competition. We tackled a series of demanding tasks under strict requirements for speed, precision, and reliability: unfolding a tablecloth (deformable-object manipulation), placing a pizza onto the table (pick-and-place), and opening and closing a food container with the lid. Our solution combines VR-based teleoperation and Learning from Demonstrations (LfD) to balance …

It should surprise no one that AI watermarking is not going to work.
#ai

AI Watermark Remover Defeats Top Techniques
UnMarker targets AI image watermarks with precision. Find out how it scrambles security and what it means for the future of AI images.

SGD Convergence under Stepsize Shrinkage in Low-Precision Training
Vincent-Daniel Yun
https://arxiv.org/abs/2508.07142 https://arxiv.org/pdf/2508.07142

SGD Convergence under Stepsize Shrinkage in Low-Precision Training
Low-precision training has become essential for reducing the computational and memory costs of large-scale deep learning. However, quantization of gradients introduces both magnitude shrinkage and additive noise, which can alter the convergence behavior of stochastic gradient descent (SGD). In this work, we study the convergence of SGD under a gradient shrinkage model, where each stochastic gradient is scaled by a factor $q_k \in (0,1]$ and perturbed by zero-mean quantization noise. We show tha…

Precision Spatio-Temporal Feature Fusion for Robust Remote Sensing Change Detection
Buddhi Wijenayake, Athulya Ratnayake, Praveen Sumanasekara, Nichula Wasalathilaka, Mathivathanan Piratheepan, Roshan Godaliyadda, Mervyn Ekanayake, Vijitha Herath
https://arxiv.org/abs/2507.11523

Precision Spatio-Temporal Feature Fusion for Robust Remote Sensing Change Detection
Remote sensing change detection is vital for monitoring environmental and urban transformations but faces challenges like manual feature extraction and sensitivity to noise. Traditional methods and early deep learning models, such as convolutional neural networks (CNNs), struggle to capture long-range dependencies and global context essential for accurate change detection in complex scenes. While Transformer-based models mitigate these issues, their computational complexity limits their applica…

Non-Equilibrium Criticality-Enhanced Quantum Sensing with Superconducting Qubits
Hao Li, Yaoling Yang, Yun-Hao Shi, Zheng-An Wang, Ziting Wang, Jintao Li, Yipeng Zhang, Kui Zhao, Yue-Shan Xu, Cheng-Lin Deng, Yu Liu, Wei-Guo Ma, Tian-Ming Li, Jia-Chi Zhang, Cai-Ping Fang, Jia-Cheng Song, Hao-Tian Liu, Si-Yun Zhou, Zheng-He Liu, Bing-Jie Chen, Gui-Han Liang, Xiaohui Song, Zhongcheng Xiang, Kai Xu, Kaixuan Huang, Abolfazl Bayat, Heng Fan

Non-Equilibrium Criticality-Enhanced Quantum Sensing with Superconducting Qubits
Exploiting quantum features allows for estimating external parameters with precisions well beyond the capacity of classical sensors, a phenomenon known as quantum-enhanced precision. Quantum criticality has been identified as a resource for achieving such enhancements with respect to the probe size. However, they demand complex probe preparation and measurement and the achievable enhancement is ultimately restricted to narrow parameter regimes. On the other hand, non-equilibrium probes harness …

Precision measurement of the ${\it{\Xi}}_b^0$ baryon lifetime
LHCb collaboration, et al.
https://arxiv.org/abs/2507.12402 https://arx…

Precision measurement of the ${\itΞ}_b^0$ baryon lifetime
A sample of $pp$ collision data, corresponding to an integrated luminosity of 5.4 fb$^{-1}$ and collected by the LHCb experiment during LHC Run 2, is used to measure the ratio of the lifetime of the ${\itΞ}_b^0$ baryon to that of the ${\itΛ}_b^0$ baryon, $r_τ\equivτ_{{\itΞ}_b^0}/τ_{{\itΛ}_b^0}$. The value ${r_τ^{\rm Run\,2}=1.004\pm0.009\pm0.006}$ is obtained, where the first uncertainty is statistical and the second systematic. This value is averaged with the corresponding value from R…

MorphIt: Flexible Spherical Approximation of Robot Morphology for Representation-driven Adaptation
Nataliya Nechyporenko, Yutong Zhang, Sean Campbell, Alessandro Roncone
https://arxiv.org/abs/2507.14061

MorphIt: Flexible Spherical Approximation of Robot Morphology for Representation-driven Adaptation
What if a robot could rethink its own morphological representation to better meet the demands of diverse tasks? Most robotic systems today treat their physical form as a fixed constraint rather than an adaptive resource, forcing the same rigid geometric representation to serve applications with vastly different computational and precision requirements. We introduce MorphIt, a novel algorithm for approximating robot morphology using spherical primitives that balances geometric accuracy with comp…

Demonstrating Superresolution in Radar Range Estimation Using a Denoising Autoencoder
Robert Czupryniak, Abhishek Chakraborty, Andrew N. Jordan, John C. Howell
https://arxiv.org/abs/2506.14906

Demonstrating Superresolution in Radar Range Estimation Using a Denoising Autoencoder
We apply machine learning methods to demonstrate range superresolution in remote sensing radar detection. Specifically, we implement a denoising autoencoder to estimate the distance between two equal intensity scatterers in the subwavelength regime. The machine learning models are trained on waveforms subject to a bandlimit constraint such that ranges much smaller than the inverse bandlimit are optimized in their precision. The autoencoder achieves effective dimensionality reduction, with the b…

HP2C-DT: High-Precision High-Performance Computer-enabled Digital Twin
E. Iraola (Barcelona Supercomputing Center), M. Garc\'ia-Lorenzo (Barcelona Supercomputing Center), F. Lordan-Gomis (Barcelona Supercomputing Center), F. Rossi (CITCEA, Universitat Polit\`ecnica de Catalunya), E. Prieto-Araujo (CITCEA, Universitat Polit\`ecnica de Catalunya), R. M. Badia (Barcelona Supercomputing Center)

HP2C-DT: High-Precision High-Performance Computer-enabled Digital Twin
Digital twins are transforming the way we monitor, analyze, and control physical systems, but designing architectures that balance real-time responsiveness with heavy computational demands remains a challenge. Cloud-based solutions often struggle with latency and resource constraints, while edge-based approaches lack the processing power for complex simulations and data-driven optimizations. To address this problem, we propose the High-Precision High-Performance Computer-enabled Digital Twin …

Triply heavy tetraquarks $\bar{b}c\bar{q}c$ and $\bar{c}b\bar{q}b$ in a constituent quark model
Gang Yang, Jialun Ping, Jorge Segovia
https://arxiv.org/abs/2507.13728

Triply heavy tetraquarks $\bar{b}c\bar{q}c$ and $\bar{c}b\bar{q}b$ in a constituent quark model
A systematic investigation of $S$-wave triply heavy tetraquark systems with quark content $\bar{b}c\bar{q}c$ and $\bar{c}b\bar{q}b$ $(q = u,\,d,\,s)$, spin-parity quantum numbers $J^P=0^+$, $1^+$, $2^+$ and isospin $I=0,\,\frac{1}{2}$, is carried out within the constituent quark model framework. The four-body bound and resonance states are determined by solving the Schrödinger equation employing the high-precision and efficient Gaussian Expansion Method (GEM) in conjunction with the powerful C…

Characterization of non-planar ring oscillators at a wavelength of 1064 nm for high precision metrology
Henning Vahlbruch, Fabian Meylahn, Benno Willke
https://arxiv.org/abs/2508.10477

Characterization of non-planar ring oscillators at a wavelength of 1064 nm for high precision metrology
Ultra-stable laser light is essential for high-precision interferometric measurements, in particular for the next generation of gravitational wave detectors, where high power lasers with unprecedented low power and frequency noise are demanded. Since the seed laser for high-power laser system has a large influence on the overall noise characteristics, the use of the lowest noise seed laser is beneficial. This study compares a newly developed seed laser, based on a non-planar ring oscillator (NP…

Inverse Weak measurement in SERF magnetometer
Qian Cao, Liang Xu, Ziqian Yue, Jianqi Yang, Yueyang Zhai
https://arxiv.org/abs/2508.12306 https://arxiv.org/…

Inverse Weak measurement in SERF magnetometer
Weak measurement techniques have been extensively applied in the field of quantum precision measurement to detect ultra-small signals due to the amplification effect. In this work, we propose an optical detection system for a spin-exchange relaxation-free (SERF) magnetometer based on the inverse weak measurement (IWM) framework. By using the spatial pattern of a probe laser as the measurement pointer, we successfully detect ultra-weak magnetic fields. In our model, the spatial pattern of the pr…

Hallucination vs interpretation: rethinking accuracy and precision in AI-assisted data extraction for knowledge synthesis
Xi Long, Christy Boscardin, Lauren A. Maggio, Joseph A. Costello, Ralph Gonzales, Rasmyah Hammoudeh, Ki Lai, Yoon Soo Park, Brian C. Gin
https://arxiv.org/abs/2508.09458

Hallucination vs interpretation: rethinking accuracy and precision in AI-assisted data extraction for knowledge synthesis
Knowledge syntheses (literature reviews) are essential to health professions education (HPE), consolidating findings to advance theory and practice. However, they are labor-intensive, especially during data extraction. Artificial Intelligence (AI)-assisted extraction promises efficiency but raises concerns about accuracy, making it critical to distinguish AI 'hallucinations' (fabricated content) from legitimate interpretive differences. We developed an extraction platform using large language m…

A Hyperactive FRB Pinpointed in an SMC-Like Satellite Host Galaxy
M. Bhardwaj, M. P. Snelders, J. W. T. Hessels, A. Gil de Paz, S. Bhandari, B. Marcote, A. Kirichenko, O. S. Ould-Boukattine, F. Kirsten, E. K. Bempong-Manful, V. Bezrukovs, J. D. Bray, S. Buttaccio, A. Corongiu, R. Feiler, M. P. Gawronski, M. Giroletti, D. M. Hewitt, M. Lindqvist, G. Maccaferri, A. Moroianu, K. Nimmo, Z. Paragi, W. Puchalska, N. Wang, D. Williams-Baldwin, J. P. Yuan

A Hyperactive FRB Pinpointed in an SMC-Like Satellite Host Galaxy
Precise localizations of fast radio bursts (FRBs) are essential for uncovering their host galaxies and immediate environments. We present the milliarcsecond-precision European VLBI Network (EVN) localization of FRB 20240114A, a hyper-active repeating FRB, achieving <90x30 mas (1-sigma) accuracy. This precision places the burst 0.5 kpc from the nucleus of its low-metallicity star-forming dwarf host at a spectroscopic redshift of z = 0.1300. Our Gran Telescopio CANARIAS (GTC) spectroscopic follow…

MedReasoner: Reinforcement Learning Drives Reasoning Grounding from Clinical Thought to Pixel-Level Precision
Zhonghao Yan, Muxi Diao, Yuxuan Yang, Jiayuan Xu, Kaizhou Zhang, Ruoyan Jing, Lele Yang, Yanxi Liu, Kongming Liang, Zhanyu Ma
https://arxiv.org/abs/2508.08177

MedReasoner: Reinforcement Learning Drives Reasoning Grounding from Clinical Thought to Pixel-Level Precision
Accurately grounding regions of interest (ROIs) is critical for diagnosis and treatment planning in medical imaging. While multimodal large language models (MLLMs) combine visual perception with natural language, current medical-grounding pipelines still rely on supervised fine-tuning with explicit spatial hints, making them ill-equipped to handle the implicit queries common in clinical practice. This work makes three core contributions. We first define Unified Medical Reasoning Grounding (UMRG…

A new hierarchical distribution on arbitrary sparse precision matrices
Gianluca Mastrantonio, Pierfrancesco Alaimo Di Loro, Marco Mingione
https://arxiv.org/abs/2506.09607

A new hierarchical distribution on arbitrary sparse precision matrices
We introduce a general strategy for defining distributions over the space of sparse symmetric positive definite matrices. Our method utilizes the Cholesky factorization of the precision matrix, imposing sparsity through constraints on its elements while preserving their independence and avoiding the numerical evaluation of normalization constants. In particular, we develop the S-Bartlett as a modified Bartlett decomposition, recovering the standard Wishart as a particular case. By incorporating…

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration
Mukul Lokhande, Santosh Kumar Vishvakarma
https://arxiv.org/abs/2506.08785

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration
The increasing complexity of AI models requires flexible hardware capable of supporting diverse precision formats, particularly for energy-constrained edge platforms. This work presents PARV-CE, a SIMD-enabled, multi-precision MAC engine that performs efficient multiply-accumulate operations using a unified data-path for 4/8/16-bit fixed-point, floating point, and posit formats. The architecture incorporates a layer adaptive precision strategy to align computational accuracy with workload sensi…

MoCap2GT: A High-Precision Ground Truth Estimator for SLAM Benchmarking Based on Motion Capture and IMU Fusion
Zichao Shu, Shitao Bei, Jicheng Dai, Lijun Li, Zetao Chen
https://arxiv.org/abs/2507.12920

MoCap2GT: A High-Precision Ground Truth Estimator for SLAM Benchmarking Based on Motion Capture and IMU Fusion
Marker-based optical motion capture (MoCap) systems are widely used to provide ground truth (GT) trajectories for benchmarking SLAM algorithms. However, the accuracy of MoCap-based GT trajectories is mainly affected by two factors: spatiotemporal calibration errors between the MoCap system and the device under test (DUT), and inherent MoCap jitter. Consequently, existing benchmarks focus primarily on absolute translation error, as accurate assessment of rotation and inter-frame errors remains c…

Searching for actual causes: Approximate algorithms with adjustable precision
Samuel Reyd, Ada Diaconescu, Jean-Louis Dessalles
https://arxiv.org/abs/2507.07857

Searching for actual causes: Approximate algorithms with adjustable precision
Causality has gained popularity in recent years. It has helped improve the performance, reliability, and interpretability of machine learning models. However, recent literature on explainable artificial intelligence (XAI) has faced criticism. The classical XAI and causality literature focuses on understanding which factors contribute to which consequences. While such knowledge is valuable for researchers and engineers, it is not what non-expert users expect as explanations. Instead, these users…

🌼 Flowers unfold with surprising precision, despite unruly genes
#flowers

Flowers unfold with surprising precision, despite unruly genes
Flowers grow stems, leaves and petals in a perfect pattern again and again. A new Cornell study shows that even in this precise, patterned formation in plants, gene activity inside individual cells is far more chaotic than it appears from the outside.

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…

Testing halo models for constraining astrophysical feedback with multi-probe modeling: I. 3D Power spectra and mass fractions
Pranjal R. S., Shivam Pandey, Dhayaa Anbajagane, Elisabeth Krause, Klaus Dolag
https://arxiv.org/abs/2507.13317

Testing halo models for constraining astrophysical feedback with multi-probe modeling: I. 3D Power spectra and mass fractions
Upcoming Stage-IV surveys will deliver measurements of distribution of matter with unprecedented precision, demanding highly accurate theoretical models for cosmological parameter inference. A major source of modeling uncertainty lies in astrophysical processes associated with galaxy formation and evolution, which remain poorly understood. Probes such as the thermal and kinematic Sunyaev-Zel'dovich effects, X-rays, and dispersion measure from fast radio bursts offer a promising avenue for mappi…

Selective Quantization Tuning for ONNX Models
Nikolaos Louloudakis, Ajitha Rajan
https://arxiv.org/abs/2507.12196 https://arxiv.org/p…

Selective Quantization Tuning for ONNX Models
Quantization is a process that reduces the precision of deep neural network models to lower model size and computational demands, often at the cost of accuracy. However, fully quantized models may exhibit sub-optimal performance below acceptable levels and face deployment challenges on low-end hardware accelerators due to practical constraints. To address these issues, quantization can be selectively applied to only a subset of layers, but selecting which layers to exclude is non-trivial. To th…

Diffuse gamma-ray and neutrino emission from the Milky Way and the local knee in the cosmic ray spectrum
C. Prevotat, Zh. Zhu, S. Koldobskiy, A. Neronov, D. Semikoz, M. Ahlers
https://arxiv.org/abs/2507.10823

Diffuse gamma-ray and neutrino emission from the Milky Way and the local knee in the cosmic ray spectrum
The LHAASO observatory has recently measured details of the cosmic-ray (CR) spectrum in the knee region (1 -- 10 PeV) with unprecedented precision, including its average CR mass composition and the spectrum of the proton component. We use these precision measurements, combined with direct measurements of CRs by space-based detectors, to derive predictions for the spectrum of diffuse gamma-ray and neutrino emission from the interstellar medium under the assumption that the CR spectrum is univers…

Performance Bounds of Ranging Precision in SPAD-Based dToF LiDAR
Hao Wu, Shiyi Sun, Lijie Zhao, Yingyu Wang, Limin Tong, Linjie Shen
https://arxiv.org/abs/2507.11404

Performance Bounds of Ranging Precision in SPAD-Based dToF LiDAR
Lidar with direct time-of-flight (dToF) technology based on single-photon avalanche diode detectors (SPAD) has been widely adopted in various applications. However, a comprehensive theoretical understanding of its fundamental ranging performance limits--particularly the degradation caused by pile-up effects due to system dead time and the potential benefits of photon-number-resolving architectures--remains incomplete. In this work, the Cramer-Rao lower bound (CRLB) for dToF systems is theoretic…

Double Duty: FPGA Architecture to Enable Concurrent LUT and Adder Chain Usage
Junius Pun, Xilai Dai, Grace Zgheib, Mahesh A. Iyer, Andrew Boutros, Vaughn Betz, Mohamed S. Abdelfattah
https://arxiv.org/abs/2507.11709

Double Duty: FPGA Architecture to Enable Concurrent LUT and Adder Chain Usage
Flexibility and customization are key strengths of Field-Programmable Gate Arrays (FPGAs) when compared to other computing devices. For instance, FPGAs can efficiently implement arbitrary-precision arithmetic operations, and can perform aggressive synthesis optimizations to eliminate ineffectual operations. Motivated by sparsity and mixed-precision in deep neural networks (DNNs), we investigate how to optimize the current logic block architecture to increase its arithmetic density. We find that…

Dark Count Rate Stability of JUNO 20-inch PMTs in Mass Testing
Min Li, Narongkiat Rodphai, Caimei Liu, Zhimin Wang, Zhaoyuan Peng, Jun Wang, Nikolay Anfimov, Denis Korablev, Tobias Lachenmaier, Alexander G. Olshevskiy, Zhonghua Qin, Tobias Sterr, Alexander Felix Tietzsch, Rong Zhao, Wei Wang, Kaile Wen, Bjoern Soenke Wonsak, Wan Xie, Meihang Xu, Yu Zhang

Dark Count Rate Stability of JUNO 20-inch PMTs in Mass Testing
The Jiangmen Underground Neutrino Observatory (JUNO) is an ambitious multipurpose neutrino experiment designed to determine the neutrino mass ordering, with an impressive energy resolution goal of at least 3% at 1 MeV. To achieve a photon detection coverage of approximately 75%, JUNO will utilize two types of 20-inch photomultiplier tubes (PMTs): the large PMT (LPMT) and the microchannel plate PMT (MCP-PMT). A significant concern in high-precision neutrino measurements is the dark count rate (D…

Modeling Uncertainties on the Z Boson Background in the Context of High Precision W Boson Mass Measurements
Maarten Boonekamp, Matthias Schott, Chen Wang
https://arxiv.org/abs/2507.07835

Modeling Uncertainties on the Z Boson Background in the Context of High Precision W Boson Mass Measurements
The precise determination of the $W$ boson mass, $m_W$, is a cornerstone of electroweak precision tests and a critical input to global fits of the Standard Model (SM). While most existing measurements of $m_W$ are in agreement with SM predictions, the recent result from the CDF collaboration exhibits a significant deviation from the SM prediction but also exceeding $4σ$ from the global average of all other high precision measurements. This prompts renewed scrutiny of potential sources of syste…

Distributed Integrated Sensing, Localization, and Communications over LEO Satellite Constellations
Yuchen Zhang, Francis Soualle, Musa Furkan Keskin, Yuan Liu, Linlong Wu, Jos\'e A. del Peral-Rosado, Bhavani Shankar M. R., Gonzalo Seco-Granados, Henk Wymeersch, Tareq Y. Al-Naffouri
https://arxiv.org/abs/2508.11029

Distributed Integrated Sensing, Localization, and Communications over LEO Satellite Constellations
Low Earth orbit (LEO) satellite constellations are rapidly becoming essential enablers of next-generation wireless systems, offering global broadband access, high-precision localization, and reliable sensing beyond terrestrial coverage. However, the inherent limitations of individual LEO satellites, including restricted power, limited antenna aperture, and constrained onboard processing, hinder their ability to meet the growing demands of 6G applications. To address these challenges, this artic…

Thermodynamics of Heavy Quarkonium in a Bayesian Holographic QCD model
Liqiang Zhu, Ou-Yang Luo, Xun Chen, Kai Zhou, Hanzhong Zhang, Defu Hou
https://arxiv.org/abs/2508.12756 ht…

Thermodynamics of Heavy Quarkonium in a Bayesian Holographic QCD model
Leveraging high-precision lattice QCD data on the equation of state and baryon number susceptibility at vanishing chemical potential, we construct a Bayesian holographic QCD model and systematically analyze the thermodynamic properties of heavy quarkonium in QCD matter under varying temperatures and chemical potentials. We compute the quark-antiquark interquark distance, potential energy, entropy, binding energy, and internal energy. We present detailed posterior distribution results of the the…

Mechanical Automation with Vision: A Design for Rubik's Cube Solver
Abhinav Chalise, Nimesh Gopal Pradhan, Nishan Khanal, Prashant Raj Bista, Dinesh Baniya Kshatri
https://arxiv.org/abs/2508.12469 …

Mechanical Automation with Vision: A Design for Rubik's Cube Solver
The core mechanical system is built around three stepper motors for physical manipulation, a microcontroller for hardware control, a camera and YOLO detection model for real-time cube state detection. A significant software component is the development of a user-friendly graphical user interface (GUI) designed in Unity. The initial state after detection from real-time YOLOv8 model (Precision 0.98443, Recall 0.98419, Box Loss 0.42051, Class Loss 0.2611) is virtualized on GUI. To get the solution…

Monolithic interferometric modules for multi-axis coordinate positioning with sub-nanometre precision
Simon Rerucha, Ondrej Cip, Miroslava Hola, Josef Lazar, Bretislav Mikel
https://arxiv.org/abs/2507.07642

Monolithic interferometric modules for multi-axis coordinate positioning with sub-nanometre precision
We report on developing, characterizing, and verifying a compact, monolithic laser interferometric assembly designed for high-precision two- and three-axis displacement measurements in coordinate positioning systems. The design targets OEM integration into advanced precision motion platforms, including nanometrology instruments, semiconductor manufacturing equipment, and ultra-high vacuum (UHV) environments. Using a single laser source, the assembly integrates multiple interferometers into a mo…

Theoretical uncertainties for primordial black holes from cosmological phase transitions
Maciej Kierkla, Nicklas Ramberg, Philipp Schicho, Daniel Schmitt
https://arxiv.org/abs/2506.15496

Theoretical uncertainties for primordial black holes from cosmological phase transitions
Strongly supercooled first-order phase transitions have been proposed as a primordial black hole (PBH) production mechanism. While previous works rely on simplified models with limited thermodynamic precision, we stress that reliable theoretical PBH predictions require precise nucleation dynamics within realistic, classically conformal extensions of the Standard Model. By employing high-temperature dimensional reduction and computing the one-loop fluctuation determinants, we provide a state-of-…

Precision spectral measurements of Chromium and Titanium from 10 to 250 GeV$/n$ and sub-Iron to Iron ratio with the Calorimetric Electron Telescope on the ISS
O. Adriani, Y. Akaike, K. Asano, Y. Asaoka, E. Berti, P. Betti, G. Bigongiari, W. R. Binns, M. Bongi, P. Brogi, A. Bruno, N. Cannady, G. Castellini, C. Checchia, M. L. Cherry, G. Collazuol, G. A. de Nolfo, K. Ebisawa, A. W. Ficklin, H. Fuke, S. Gonzi, T. G. Guzik, T. Hams, K. Hibino, M. Ichimura, M. H. Israel, K. Kasahara, J. Kat…

Precision spectral measurements of Chromium and Titanium from 10 to 250 GeV$/n$ and sub-Iron to Iron ratio with the Calorimetric Electron Telescope on the ISS
The Calorimetric Electron Telescope (CALET), in operation on the International Space Station since 2015, collected a large sample of cosmic-ray (CR) iron and sub-iron events over a wide energy interval. In this paper we report an update of our previous measurement of the iron flux and we present - for the first time - a high statistics measurement of the spectra of two sub-iron elements Cr and Ti in the energy interval from 10 to 250 GeV/n. The analyses are based on 8 years of data. Differently…

Unmodulated Visible Light Positioning: A Deep Dive into Techniques, Studies, and Future Prospects
Morteza Alijani, Wout Joseph, David Plets
https://arxiv.org/abs/2507.13080

Unmodulated Visible Light Positioning: A Deep Dive into Techniques, Studies, and Future Prospects
Visible Light Positioning (VLP) has emerged as a promising technology for next-generation indoor positioning systems (IPS), particularly within the scope of sixth-generation (6G) wireless networks. Its attractiveness stems from leveraging existing lighting infrastructures equipped with light-emitting diodes (LEDs), enabling cost-efficient deployments and achieving high-precision positioning accuracy in the centimeter-todecimeter range. However, widespread adoption of traditional VLP solutions f…

Learning to Restore Heisenberg Limit in Noisy Quantum Sensing via Quantum Digital Twin
Hang Xu, Tailong Xiao, Jingzheng Huang, Jianping Fan, Guihua Zeng
https://arxiv.org/abs/2508.11198

Learning to Restore Heisenberg Limit in Noisy Quantum Sensing via Quantum Digital Twin
Quantum sensors leverage nonclassical resources to achieve sensing precision at the Heisenberg limit, surpassing the standard quantum limit attainable through classical strategies. However, a critical issue is that the environmental noise induces rapid decoherence, fundamentally limiting the realizability of the Heisenberg limit. In this Letter, we propose a quantum digital twin protocol to overcome this issue. The protocol first establishes observable-constrained state reconstruction to infer …

This https://arxiv.org/abs/2411.18065 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAR_…

FlexiBit: Fully Flexible Precision Bit-parallel Accelerator Architecture for Arbitrary Mixed Precision AI
Recent research has shown that large language models (LLMs) can utilize low-precision floating point (FP) quantization to deliver high efficiency while maintaining original model accuracy. In particular, recent works have shown the effectiveness of non-power-of-two precisions, such as FP6 and FP5, and diverse sensitivity to low-precision arithmetic of LLM layers, which motivates mixed precision arithmetic including non-power-of-two precisions in LLMs. Although low-precision algorithmically lead…

Flavoured jet algorithms: a comparative study
Arnd Behring, Simone Caletti, Francesco Giuli, Radoslaw Grabarczyk, Andreas Hinzmann, Alexander Huss, Joey Huston, Ezra D. Lesser, Simone Marzani, Davide Napoletano, Rene Poncelet, Daniel Reichelt, Alberto Rescia, Gavin P. Salam, Ludovic Scyboz, Federico Sforza, Andrzej Siodmok, Giovanni Stagnitto, James Whitehead, Ruide Xu

Flavoured jet algorithms: a comparative study
The accurate identification of heavy-flavour jets, those which originate from bottom or charm quarks, is crucial for precision studies of the Standard Model and searches for new physics. However, assigning flavour to jets presents significant challenges, primarily due to issues with infrared and collinear (IRC) safety. This paper aims to address these challenges by evaluating recently-proposed jet algorithms designed to be IRC-safe and applicable in high-precision measurements. We compare these…

Leveraging LLMs for Mission Planning in Precision Agriculture
Marcos Abel Zuzu\'arregui, Stefano Carpin
https://arxiv.org/abs/2506.10093 https://

Leveraging LLMs for Mission Planning in Precision Agriculture
Robotics and artificial intelligence hold significant potential for advancing precision agriculture. While robotic systems have been successfully deployed for various tasks, adapting them to perform diverse missions remains challenging, particularly because end users often lack technical expertise. In this paper, we present an end-to-end system that leverages large language models (LLMs), specifically ChatGPT, to enable users to assign complex data collection tasks to autonomous robots using na…

One For All: LLM-based Heterogeneous Mission Planning in Precision Agriculture
Marcos Abel Zuzu\'arregui, Mustafa Melih Toslak, Stefano Carpin
https://arxiv.org/abs/2506.10106

One For All: LLM-based Heterogeneous Mission Planning in Precision Agriculture
Artificial intelligence is transforming precision agriculture, offering farmers new tools to streamline their daily operations. While these technological advances promise increased efficiency, they often introduce additional complexity and steep learning curves that are particularly challenging for non-technical users who must balance tech adoption with existing workloads. In this paper, we present a natural language (NL) robotic mission planner that enables non-specialists to control heterogen…

Enhancing Measurement Precision of Non-Degenerate Two-Photon Absorption
Gaurav Shukla, Shahram Panahiyan, Devendra Kumar Mishra, Frank Schlawin
https://arxiv.org/abs/2506.07384

Enhancing Measurement Precision of Non-Degenerate Two-Photon Absorption
Recent theoretical and experimental studies have shown that squeezed states of light can be engineered to enhance the resolution of nonlinear optical measurements. Here, we analyze non-degenerate two-photon absorption signals obtained from transmission measurements using two-mode squeezed light and compare different measurement strategies. In particular, we investigate how correlations between the light modes may be used to improve the achievable precision. We find that intensity correlation me…

Reaching the Ultimate Quantum Precision Limit at Colliders: Conditions and Case Studies
Tengyu Ai, Qi Bi, Yuxin He, Jia Liu, Xiao-Ping Wang
https://arxiv.org/abs/2506.10673

Reaching the Ultimate Quantum Precision Limit at Colliders: Conditions and Case Studies
We investigate whether collider experiments can reach the quantum limit of precision, defined by the quantum Fisher information (QFI), using only classical observables such as particle momenta. As a case study, we focus on the $τ^+τ^-$ system and the decay channel $τ\to πν$, which offers maximal spin-analyzing power and renders the decay a projective measurement. We develop a general framework to determine when collider measurements can, in principle, saturate the QFI in an entangled bipar…

Precision $e^ e^-$ Hemisphere Masses in the Dijet Region with Power Corrections
Andre H. Hoang, Vicent Mateu, Matthew D. Schwartz, Iain W. Stewart
https://arxiv.org/abs/2506.09130

Precision $e^+e^-$ Hemisphere Masses in the Dijet Region with Power Corrections
We derive high-precision results for the $e^+e^-$ heavy jet mass (HJM) $d σ/d ρ$ and dihemisphere mass (DHM) $d^2σ/(d s_1 d s_2)$ distributions, for $s_1\sim s_2$, in the dijet region. New results include: i) the N$^3$LL resummation for HJM of large logarithms $\ln^n(ρ)$ at small $ρ$ including the exact two-loop non-global hemisphere soft function, the 4-loop cusp anomalous dimension and the 3-loop hard and jet functions, ii) N$^3$LL results for DHM with resummation of logarithms $\ln(s_{1…

GAMORA: A Gesture Articulated Meta Operative Robotic Arm for Hazardous Material Handling in Containment-Level Environments
Farha Abdul Wasay, Mohammed Abdul Rahman, Hania Ghouse
https://arxiv.org/abs/2506.14513

GAMORA: A Gesture Articulated Meta Operative Robotic Arm for Hazardous Material Handling in Containment-Level Environments
The convergence of robotics and virtual reality (VR) has enabled safer and more efficient workflows in high-risk laboratory settings, particularly virology labs. As biohazard complexity increases, minimizing direct human exposure while maintaining precision becomes essential. We propose GAMORA (Gesture Articulated Meta Operative Robotic Arm), a novel VR-guided robotic system that enables remote execution of hazardous tasks using natural hand gestures. Unlike existing scripted automation or trad…

Generation of Near-ideal Indistinguishable Two-Photon State by Incoherent Light
Yue-Wei Song, Ming-Yuan Gao, Zhi-Cheng Guo, Zheng-He Zhou, Yin-Hai Li, Guang-Can Guo, Zhi-Yuan Zhou, Bao-Sen Shi
https://arxiv.org/abs/2507.12066

Generation of Near-ideal Indistinguishable Two-Photon State by Incoherent Light
High-quality quantum states lie at the heart of advanced quantum information processing. The degree of photon indistinguishability is critical for applications from photonic quantum computation to precision metrology. The two-photon Hong-Ou-Mandel (HOM) interference effect provides a rigorous quantification method, with its visibility serving as the ultimate benchmark for source quality. Generally, the coherent pumping is widely regarded as indispensable for the preparation of quantum sources. …

Automatic Cannulation of Femoral Vessels in a Porcine Shock Model
Nico Zevallos, Cecilia G. Morales, Andrew Orekhov, Tejas Rane, Hernando Gomez, Francis X. Guyette, Michael R. Pinsky, John Galeotti, Artur Dubrawski, Howie Choset
https://arxiv.org/abs/2506.14467

Automatic Cannulation of Femoral Vessels in a Porcine Shock Model
Rapid and reliable vascular access is critical in trauma and critical care. Central vascular catheterization enables high-volume resuscitation, hemodynamic monitoring, and advanced interventions like ECMO and REBOA. While peripheral access is common, central access is often necessary but requires specialized ultrasound-guided skills, posing challenges in prehospital settings. The complexity arises from deep target vessels and the precision needed for needle placement. Traditional techniques, li…

Fast evaluation of Feynman integrals for Monte Carlo generators
Pau Petit Ros\`as, William J. Torres Bobadilla
https://arxiv.org/abs/2507.12548 https://

Fast evaluation of Feynman integrals for Monte Carlo generators
Building on the idea of numerically integrating differential equations satisfied by Feynman integrals, we propose a novel strategy for handling branch cuts within a numerical framework. We develop an integrator capable of evaluating a basis of integrals in both double and quadruple precision, achieving significantly reduced computational times compared to existing tools. We demonstrate the performance of our integrator by evaluating one- and two-loop five-point Feynman integrals with up to nine…

Tree-SLAM: semantic object SLAM for efficient mapping of individual trees in orchards
David Rapado-Rincon, Gert Kootstra
https://arxiv.org/abs/2507.12093 h…

Tree-SLAM: semantic object SLAM for efficient mapping of individual trees in orchards
Accurate mapping of individual trees is an important component for precision agriculture in orchards, as it allows autonomous robots to perform tasks like targeted operations or individual tree monitoring. However, creating these maps is challenging because GPS signals are often unreliable under dense tree canopies. Furthermore, standard Simultaneous Localization and Mapping (SLAM) approaches struggle in orchards because the repetitive appearance of trees can confuse the system, leading to mapp…

Design and Development of an Automated Contact Angle Tester (ACAT) for Surface Wettability Measurement
Connor Burgess, Kyle Douin, Amir Kordijazi
https://arxiv.org/abs/2507.12431 …

Design and Development of an Automated Contact Angle Tester (ACAT) for Surface Wettability Measurement
The Automated Contact Angle Tester (ACAT) is a fully integrated robotic work cell developed to automate the measurement of surface wettability on 3D-printed materials. Designed for precision, repeatability, and safety, ACAT addresses the limitations of manual contact angle testing by combining programmable robotics, precise liquid dispensing, and a modular software-hardware architecture. The system is composed of three core subsystems: (1) an electrical system including power, control, and safe…