Tootfinder

A Correct by Construction Fault Tolerant Voter for Input Selection of a Control System
Arif Ali AP, Jasine Babu, Deepa Sara John
https://arxiv.org/abs/2509.22236 https://…

A Correct by Construction Fault Tolerant Voter for Input Selection of a Control System
Safety-critical systems use redundant input units to improve their reliability and fault tolerance. A voting logic is then used to select a reliable input from the redundant sources. A fault detection and isolation rules help in selecting input units that can participate in voting. This work deals with the formal requirement formulation, design, verification and synthesis of a generic voting unit for an $N$-modular redundant measurement system used for control applications in avionics systems. …

This really saddens me. I absolutely adored the style of Shire Hall - an iconic view from the M4 and local roads. I still vividly remember my one week of Year 10 work experience there at Berkshire County Council at a time when they were preparing for their own demise as they were split into 6 unitary authorities. I wonder what happened to the time capsule that was in reception.
What's being planned to take its place? Surprise, surprise: big, bland industrial warehouse units. #RDGUK
Former council office complex in Reading half demolished | Reading Chronicle
https://www.readingchronicle.co.uk/news/25491410.former-council-office-complex-reading-half-demolished/

Arbitrary mechanical memory encoding via nonlinear waves in bistable metamaterials
Audrey A. Watkins, Giovanni Bordiga, Mingxing Mu, Vincent Tournat, Katia Bertoldi
https://arxiv.org/abs/2508.20321

Arbitrary mechanical memory encoding via nonlinear waves in bistable metamaterials
Mechanical metamaterials composed of bistable elements have recently emerged as promising platforms for mechanical memory. Traditional approaches to writing information in these systems typically rely on localized actuation or predefined coupling schemes, which are often labor-intensive or lack adaptability. In this work, we introduce a one-dimensional metamaterial consisting of mass-in-mass bistable units that are statically decoupled yet dynamically switchable, allowing arbitrary mechanical i…

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs
Jacob Wahlgren, Gabin Schieffer, Ruimin Shi, Edgar A. Le\'on, Roger Pearce, Maya Gokhale, Ivy Peng
https://arxiv.org/abs/2508.12743

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs
Discrete GPUs are a cornerstone of HPC and data center systems, requiring management of separate CPU and GPU memory spaces. Unified Virtual Memory (UVM) has been proposed to ease the burden of memory management; however, at a high cost in performance. The recent introduction of AMD's MI300A Accelerated Processing Units (APUs)--as deployed in the El Capitan supercomputer--enables HPC systems featuring integrated CPU and GPU with Unified Physical Memory (UPM) for the first time. This work present…

Directed Cycles as Higher-Order Units of Information Processing in Complex Networks
Hardik Rajpal, Paul Expert, Vaiva Vasiliauskaite
https://arxiv.org/abs/2508.09808 https://

Directed Cycles as Higher-Order Units of Information Processing in Complex Networks
Directed cycles form the fundamental motifs in natural, social and artificial networks, yet their distinct computational roles remain under-explored, particularly in the context of higher-order structure and function. In this work, we investigate how two types of directed cycles - feedforward and feedback - can act as higher-order structures to facilitate the flow and integration of information in sparse random networks, and how these roles depend on the environment of the cycles. Using informa…

Microlocal analysis of the non-relativistic limit of the Klein--Gordon equation: Estimates
Andrew Hassell, Qiuye Jia, Ethan Sussman, Andras Vasy
https://arxiv.org/abs/2509.09518

Microlocal analysis of the non-relativistic limit of the Klein--Gordon equation: Estimates
This is the more technical half of a two-part work in which we introduce a robust microlocal framework for analyzing the non-relativistic limit of relativistic wave equations with time-dependent coefficients, focusing on the Klein--Gordon equation. Two asymptotic regimes in phase space are relevant to the non-relativistic limit: one corresponding to what physicists call ``natural'' units, in which the PDE is approximable by the free Klein--Gordon equation, and a low-frequency regime in which th…

Phonological Representation Learning for Isolated Signs Improves Out-of-Vocabulary Generalization
Lee Kezar, Zed Sehyr, Jesse Thomason
https://arxiv.org/abs/2509.04745 https://

Phonological Representation Learning for Isolated Signs Improves Out-of-Vocabulary Generalization
Sign language datasets are often not representative in terms of vocabulary, underscoring the need for models that generalize to unseen signs. Vector quantization is a promising approach for learning discrete, token-like representations, but it has not been evaluated whether the learned units capture spurious correlations that hinder out-of-vocabulary performance. This work investigates two phonological inductive biases: Parameter Disentanglement, an architectural bias, and Phonological Semi-Sup…

Causal Inference Under Network Interference
Subhankar Bhadra, Michael Schweinberger
https://arxiv.org/abs/2508.06808 https://arxiv.org/pdf/2508.06808

Causal Inference Under Network Interference
We review and conceptualize recent advances in causal inference under network interference, drawing on a complex and diverse body of work that ranges from causal inference, statistical network analysis, economics, the health sciences, and the social sciences. Network interference arises in connected populations when the treatment assignments of units affect the outcomes of other units. Examples include economic, financial, and public health interventions with spillover in connected populations,…

Accelerating Inference for Multilayer Neural Networks with Quantum Computers
Arthur G. Rattew, Po-Wei Huang, Naixu Guo, Lirand\"e Pira, Patrick Rebentrost
https://arxiv.org/abs/2510.07195

Accelerating Inference for Multilayer Neural Networks with Quantum Computers
Fault-tolerant Quantum Processing Units (QPUs) promise to deliver exponential speed-ups in select computational tasks, yet their integration into modern deep learning pipelines remains unclear. In this work, we take a step towards bridging this gap by presenting the first fully-coherent quantum implementation of a multilayer neural network with non-linear activation functions. Our constructions mirror widely used deep learning architectures based on ResNet, and consist of residual blocks with m…

Balanced Spanning Tree Distributions Have Separation Fairness
Harry Chen, Kamesh Munagala, Govind S. Sankar
https://arxiv.org/abs/2509.15137 https://arxiv.…

Balanced Spanning Tree Distributions Have Separation Fairness
Sampling-based methods such as ReCom are widely used to audit redistricting plans for fairness, with the balanced spanning tree distribution playing a central role since it favors compact, contiguous, and population-balanced districts. However, whether such samples are truly representative or exhibit hidden biases remains an open question. In this work, we introduce the notion of separation fairness, which asks whether adjacent geographic units are separated with at most a constant probability …

RF-Powered Batteryless Plant Movement Sensor for Precision Agriculture
Jona Cappelle, Jarne Van Mulders, Sarah Goossens, Thomas Reher, Liesbet Van der Perre, Lieven De Strycker, Bram Van de Poel, Gilles Callebaut
https://arxiv.org/abs/2509.13004

RF-Powered Batteryless Plant Movement Sensor for Precision Agriculture
Precision agriculture demands non-invasive, energy-efficient, and sustainable plant monitoring solutions. In this work, we present the design and implementation of a lightweight, batteryless plant movement sensor powered solely by RF energy. This sensor targets Controlled Environment Agriculture (CEA) and utilizes inertial measurements units (IMUs) to monitor leaf motion, which correlates with plant physiological responses to environmental stress. By eliminating the battery, we reduce the ecolo…

Accelerating cosmological simulations on GPUs: a portable approach using OpenMP
M. D. Lepinzan, G. Lacopo, D. Goz, G. Taffoni, P. Monaco, P. J. Elahi, U. Varetto, M. Cytowski
https://arxiv.org/abs/2510.02873

Accelerating cosmological simulations on GPUs: a portable approach using OpenMP
In this work we present the porting to Graphics Processing Units (GPUs, using OpenMP target directives) and optimization of a key module within the cosmological {\pinocchio} code, a Lagrangian Perturbation Theory (LPT)-based framework widely used for generating dark matter (DM) halo catalogs. Our optimization focuses on a specific segment of the code responsible for calculating the collapse time of each particle involved in the simulation. Due to the embarrassingly parallel nature of this compu…

Understanding the Landscape of Ampere GPU Memory Errors
Zhu Zhu, Yu Sun, Dhatri Parakal, Bo Fang, Steven Farrell, Gregory H. Bauer, Brett Bode, Ian T. Foster, Michael E. Papka, William Gropp, Zhao Zhang, Lishan Yang
https://arxiv.org/abs/2508.03513

Understanding the Landscape of Ampere GPU Memory Errors
Graphics Processing Units (GPUs) have become a de facto solution for accelerating high-performance computing (HPC) applications. Understanding their memory error behavior is an essential step toward achieving efficient and reliable HPC systems. In this work, we present a large-scale cross-supercomputer study to characterize GPU memory reliability, covering three supercomputers - Delta, Polaris, and Perlmutter - all equipped with NVIDIA A100 GPUs. We examine error logs spanning 67.77 million GPU…