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Estimates of seismic wave speeds in the Earth (seismic velocity models) are key input parameters to earthquake simulations for ground motion prediction. Owing to the non-uniqueness of the seismic inverse problem, typically many velocity…

Retrieval-Augmented Generation (RAG) has emerged as a widely adopted approach for enhancing LLMs in scenarios that demand extensive factual knowledge. However, current RAG evaluations concentrate primarily on correctness, which may not…

Computation and Language · Computer Science 2026-03-23 Vinh Nguyen , Cuong Dang , Jiahao Zhang , Hoa Tran , Minh Tran , Trinh Chau , Thai Le , Lu Cheng , Suhang Wang

Frequency-domain expressions are found for gradiometer and satellite-to-satellite tracking measurements of a point source on the surface of the Earth. The maximum signal-to-noise ratio as a function of noise in the measurement apparatus is…

Geophysics · Physics 2021-01-06 Robert Spero

Explicit quantification of uncertainty in engineering simulations is being increasingly used to inform robust and reliable design practices. In the aerospace industry, computationally-feasible analyses for design optimization purposes often…

Fluid Dynamics · Physics 2019-11-13 Jayant Mukhopadhaya , Brian T. Whitehead , John F. Quindlen , Juan J. Alonso

Among all forms of routine human activity, the one which produces the strongest gravity-gradient noise in interferometric gravitational-wave detectors (e.g. LIGO) is the beginning and end of weight transfer from one foot to the other during…

General Relativity and Quantum Cosmology · Physics 2009-12-30 Kip S. Thorne , Carolee J. Winstein

Error diagnostics for turbulence models have traditionally focused on engineering quantities of interest, such as the skin-friction coefficient, $C_f$, most often by comparing the predicted $C_f$ against reference data. In wall-bounded…

Fluid Dynamics · Physics 2026-03-13 Shyam S. Nair , Vishal A. Wadhai , Robert F. Kunz , Xiang I. A. Yang

Atomic magnetometers (AMs) offer many advantages over superconducting quantum interference devices (SQUIDs) due to, among other things, having comparable sensitivity while not requiring cryogenics. One of the major limitations of AMs is the…

Instrumentation and Detectors · Physics 2019-09-04 I. A. Sulai , Z. J. DeLand , M. D. Bulatowicz , C. P. Wahl , R. T. Wakai , T. G. Walker

We theoretically analyze the effect of density/refractive-index gradients on the measurement precision of Volumetric Particle Tracking Velocimetry (V-PTV) and Background Oriented Schlieren (BOS) experiments by deriving the Cramer-Rao lower…

Fluid Dynamics · Physics 2020-06-24 Lalit K. Rajendran , Sally P. M. Bane , Pavlos P. Vlachos

Gradient regularization, as described in \citet{barrett2021implicit}, is a highly effective technique for promoting flat minima during gradient descent. Empirical evidence suggests that this regularization technique can significantly…

Machine Learning · Statistics 2023-04-03 Xuran Meng , Yuan Cao , Difan Zou

Despite their widespread use in determining system attitude, Micro-Electro-Mechanical Systems (MEMS) Attitude and Heading Reference Systems (AHRS) are limited by sensor measurement biases. This paper introduces a method called MAgnetometer…

Robotics · Computer Science 2025-03-06 Sebastián Rodríguez-Martínez , Giancarlo Troni

Recent theoretical work suggests that violation of the Equivalence Principle might be revealed in a measurement of the fractional differential acceleration $\eta$ between two test bodies -of different composition, falling in the…

General Relativity and Quantum Cosmology · Physics 2009-11-11 G. L. Comandi , M. L. Chiofalo , R. Toncelli , D. Bramanti , E. Polacco , A. M. Nobili

Aerodynamic optimization is ubiquitous in the design of most engineering systems interacting with fluids. A common approach is to optimize a performance function defined by a choice of an aerodynamic model, e.g., turbulence RANS model, and…

Optimization and Control · Mathematics 2021-05-04 Lluís Jofre , Alireza Doostan

The robust estimation of the mounting angle for millimeter-wave automotive radars installed on moving vehicles is investigated. We propose a novel signal processing pipeline that combines radar and inertial measurement unit (IMU) data to…

Signal Processing · Electrical Eng. & Systems 2026-02-02 Simin Zhu , Satish Ravindran , Lihui Chen , Alexander Yarovoy , Francesco Fioranelli

We present the construction of the two-state model of the atomic gravimeter and the associated Kalman recursion to estimate gravity acceleration from atomic gravimeter. We find the Kalman estimator greatly improve the precision of estimates…

Atomic Physics · Physics 2022-12-14 Bo-Nan Jiang , Yu-Zhu Wang

Gradient Smoothing is an efficient approach to reducing noise in gradient-based model explanation method. SmoothGrad adds Gaussian noise to mitigate much of these noise. However, the crucial hyper-parameter in this method, the variance…

Machine Learning · Computer Science 2025-10-23 Linjiang Zhou , Chao Ma , Zepeng Wang , Libing Wu , Xiaochuan Shi

Optical wireless communication (OWC) is highly vulnerable to the atmospheric turbulence and pointing error. Performance analysis of the OWC system under the combined channel effects of pointing errors and atmospheric turbulence is desirable…

Signal Processing · Electrical Eng. & Systems 2020-07-16 Kartik Wardhan , S. M. Zafaruddin

Retrieval-Augmented Generation (RAG) enhances recency and factuality in answers. However, existing evaluations rarely test how well these systems cope with real-world noise, conflicting between internal and external retrieved contexts, or…

Computation and Language · Computer Science 2025-10-29 Yixiao Zeng , Tianyu Cao , Danqing Wang , Xinran Zhao , Zimeng Qiu , Morteza Ziyadi , Tongshuang Wu , Lei Li

Fluctuations of the earth's gravity field are a major noise source for ground-based experiments investigating general relativity phenomena such as Gravitational Waves (GWs). Mass density variations caused by local seismic or atmospheric…

Optimization with noisy gradients has become ubiquitous in statistics and machine learning. Reparameterization gradients, or gradient estimates computed via the "reparameterization trick," represent a class of noisy gradients often used in…

Machine Learning · Statistics 2017-05-23 Andrew C. Miller , Nicholas J. Foti , Alexander D'Amour , Ryan P. Adams