Blog
Performance of the MORA Apparatus for Testing Time-Reversal Invariance in Nuclear Beta Decay
The MORA experimental setup is designed to measure the triple-correlation D parameter in nuclear beta decay. The D coefficient is sensitive to possible violations of time-reversal invariance. The experimental configuration consists of a transparent Paul trap surrounded by a detection setup with...
Vision Controlled Orthotic Hand Exoskeleton
This paper presents the design and implementation of an AI vision-controlled orthotic hand exoskeleton to enhance rehabilitation and assistive functionality for individuals with hand mobility impairments. The system leverages a Google Coral Dev Board Micro with an Edge TPU to enable real-time...
Eigendecomposition Parameterization of Penalty Matrices for Enhanced Control Design: Aerospace Applications
Modern control algorithms require tuning of square weight/penalty matrices appearing in quadratic functions/costs to improve performance and/or stability output. Due to simplicity in gain-tuning and enforcing positive-definiteness, diagonal penalty matrices are used extensively in control methods such as linear quadratic regulator (LQR),...
Analyzing stripes in crossing pedestrian flows using temporal matrices and a geometric model
Understanding pattern formation in crossing pedestrian flows is essential for analyzing and managing high-density crowd dynamics in urban environments. This study presents two complementary methodological approaches to detect and characterize stripe formations, an emergent structure observed when two pedestrian groups cross at...
Terahertz field effect in a two-dimensional semiconductor MoS2
Layered two-dimensional (2D) materials, with their atomic-scale thickness and tunable electronic, optical, and mechanical properties, open many promising pathways to significantly advance modern electronics. The field effect caused by a strong electric field, typically of MV/cm level, applied perpendicular to the material...
Deep Neural Network Emulation of the Quantum-Classical Transition via Learned Wigner Function Dynamics
The emergence of classical behavior from quantum mechanics as Planck’s constant $\hbar$ approaches zero remains a fundamental challenge in physics [1-3]. This paper introduces a novel approach employing deep neural networks to directly learn the dynamical mapping from initial quantum state parameters...
MPAD: A New Dimension-Reduction Method for Preserving Nearest Neighbors in High-Dimensional Vector Search
High-dimensional vector embeddings are widely used in retrieval systems, yet dimensionality reduction (DR) is seldom applied due to its tendency to distort nearest-neighbor (NN) structure critical for search. Existing DR techniques such as PCA and UMAP optimize global or manifold-preserving criteria, rather...
Review of the experimental and theoretical landscape of electron transport in noble liquids
We present a review of the current experimental and theoretical understanding of electron transport in noble liquids. Special attention is given to recent measurements that coincide with the development of time projection chambers (TPCs) using liquid xenon and argon as detector media....
Transitive Array: An Efficient GEMM Accelerator with Result Reuse
Deep Neural Networks (DNNs) and Large Language Models (LLMs) have revolutionized artificial intelligence, yet their deployment faces significant memory and computational challenges, especially in resource-constrained environments. Quantization techniques have mitigated some of these issues by reducing data precision, primarily focusing on General...
Real-time Bayesian inference at extreme scale: A digital twin for tsunami early warning applied to the Cascadia subduction zone
We present a Bayesian inversion-based digital twin that employs acoustic pressure data from seafloor sensors, along with 3D coupled acoustic-gravity wave equations, to infer earthquake-induced spatiotemporal seafloor motion in real time and forecast tsunami propagation toward coastlines for early warning with quantified...