We report on a successful implementation of a wavelet-based Poisson solver for use in three-dimensional particle-in-cell simulations. Our method harnesses advantages afforded by the wavelet formulation, such as sparsity of operators and data sets, existence of effective preconditioners, and the ability simultaneously to remove numerical noise and additional compression of relevant data sets. We present and discuss preliminary results relating to the application of the new solver to test problems in accelerator physics and astrophysics.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1196/annals.1350.006 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Detecting Spontaneous Neural Oscillation Events in Primate Auditory Cortex.
eNeuro
August 2022
Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY 10962.
Electrophysiological oscillations in the brain have been shown to occur as multicycle events, with onset and offset dependent on behavioral and cognitive state. To provide a baseline for state-related and task-related events, we quantified oscillation features in resting-state recordings. We developed an open-source wavelet-based tool to detect and characterize such oscillation events (OEvents) and exemplify the use of this tool in both simulations and two invasively-recorded electrophysiology datasets: one from human, and one from nonhuman primate (NHP) auditory system.
View Article and Find Full Text PDFThe comparative performance of wavelet-based outbreak detector, exponential weighted moving average, and Poisson regression-based methods in detection of pertussis outbreaks in Iranian infants: A simulation-based study.
Pediatr Pulmonol
December 2020
Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Background: Early detection of outbreaks of transmissible diseases is essential for public health. This study aimed to determine the performance of the wavelet-based outbreak detection method (WOD) in detecting outbreaks and to compare its performance with the Poisson regression-based model and exponentially weighted moving average (EWMA) using data of simulated pertussis outbreaks in Iran.
Method: The data on suspected cases of pertussis from 25th February 2012 to 23rd March 2018 in Iran was used.
Noise Estimation for Image Sensor Based on Local Entropy and Median Absolute Deviation.
Sensors (Basel)
January 2019
Key Laboratory of Beam Control, Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China.
Noise estimation for image sensor is a key technique in many image pre-processing applications such as blind de-noising. The existing noise estimation methods for additive white Gaussian noise (AWGN) and Poisson-Gaussian noise (PGN) may underestimate or overestimate the noise level in the situation of a heavy textured scene image. To cope with this problem, a novel homogenous block-based noise estimation method is proposed to calculate these noises in this paper.
View Article and Find Full Text PDFTotal variation versus wavelet-based methods for image denoising in fluorescence lifetime imaging microscopy.
J Biophotonics
May 2012
Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109-2099, USA.
We report the first application of wavelet-based denoising (noise removal) methods to time-domain box-car fluorescence lifetime imaging microscopy (FLIM) images and compare the results to novel total variation (TV) denoising methods. Methods were tested first on artificial images and then applied to low-light live-cell images. Relative to undenoised images, TV methods could improve lifetime precision up to 10-fold in artificial images, while preserving the overall accuracy of lifetime and amplitude values of a single-exponential decay model and improving local lifetime fitting in live-cell images.
View Article and Find Full Text PDFPoint-process analysis of neural spiking activity of muscle spindles recorded from thin-film longitudinal intrafascicular electrodes.
Annu Int Conf IEEE Eng Med Biol Soc
June 2012
Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital – Harvard Medical School, Boston, MA 02114, USA.
Recordings from thin-film Longitudinal Intra-Fascicular Electrodes (tfLIFE) together with a wavelet-based de-noising and a correlation-based spike sorting algorithm, give access to firing patterns of muscle spindle afferents. In this study we use a point process probability structure to assess mechanical stimulus-response characteristics of muscle spindle spike trains. We assume that the stimulus intensity is primarily a linear combination of the spontaneous firing rate, the muscle extension, and the stretch velocity.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!