Particle-in-cell (PIC) simulations of relativistic flowing plasmas are of key interest to several fields of physics (including, e.g., laser-wakefield acceleration, when viewed in a Lorentz-boosted frame) but remain sometimes infeasible due to the well-known numerical Cherenkov instability (NCI). In this article, we show that, for a plasma drifting at a uniform relativistic velocity, the NCI can be eliminated by simply integrating the PIC equations in Galilean coordinates that follow the plasma (also sometimes known as comoving coordinates) within a spectral analytical framework. The elimination of the NCI is verified empirically and confirmed by a theoretical analysis of the instability. Moreover, it is shown that this method is applicable both to Cartesian geometry and to cylindrical geometry with azimuthal Fourier decomposition.
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http://dx.doi.org/10.1103/PhysRevE.94.053305 | DOI Listing |
J Chem Phys
August 2023
Department of Chemistry, Tulane University, New Orleans, Louisiana 70118, USA.
Optical phonons serve as the fast and efficient carriers of energy across periodic polymers due to their delocalization, large group velocity because of covalent bonding, and large energy quantum compared to that for acoustic phonons as it was observed in a number of recent measurements in different oligomers. However, this transport is dramatically sensitive to anharmonic interactions, including the unavoidable interaction with acoustic phonons responsible for transport decoherence, suppressing ballistic transport at long distances. Here, we show that this decoherence is substantially suppressed if the group velocity of optical phonons is less than the sound velocity of acoustic phonons; otherwise, ballistic transport is substantially suppressed by a Cherenkov-like emission of acoustic phonons.
View Article and Find Full Text PDFBiomed Opt Express
February 2023
Department of Medical Physics, University of Wisconsin-Madison, Madison, WI 53705, USA.
As an emerging imaging technique, Cherenkov-excited luminescence scanned tomography (CELST) can recover a high-resolution 3D distribution of quantum emission fields within tissue using X-ray excitation for deep penetrance. However, its reconstruction is an ill-posed and under-conditioned inverse problem because of the diffuse optical emission signal. Deep learning based image reconstruction has shown very good potential for solving these types of problems, however they suffer from a lack of ground-truth image data to confirm when used with experimental data.
View Article and Find Full Text PDFJ Biomed Opt
February 2023
University of Wisconsin-Madison, Department of Medical Physics, Madison, Wisconsin, United States.
Significance: X-ray Cherenkov-luminescence tomography (XCLT) produces fast emission data from megavoltage (MV) x-ray scanning, in which the excitation location of molecules within tissue is reconstructed. However standard filtered backprojection (FBP) algorithms for XCLT sinogram reconstruction can suffer from insufficient data due to dose limitations, so there are limits in the reconstruction quality with some artifacts. We report a deep learning algorithm for XCLT with high image quality and improved quantitative accuracy.
View Article and Find Full Text PDFPhys Med Biol
February 2023
Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, People's Republic of China.
Fluorescence molecular tomography (FMT) is a promising molecular imaging modality for quantifying the three-dimensional (3D) distribution of tumor probes in small animals. However, traditional deep learning reconstruction methods that aim to minimize the mean squared error (MSE) and iterative regularization algorithms that rely on optimal parameters are typically influenced by strong noise, resulting in poor FMT reconstruction robustness.In this letter, we propose an adaptive adversarial learning strategy (3D-UR-WGAN) to achieve robust FMT reconstructions.
View Article and Find Full Text PDFBiomed Opt Express
April 2022
Centre for Vision, Speech and Signal Processing, University of Surrey, GU2 7XH, United Kingdom.
Numerical experiments based on Monte Carlo simulations and clinical CT data are performed to investigate the spatial and spectral characteristics of Cherenkov light emission and the relationship between Cherenkov light intensity and deposited dose in molecular radiotherapy of hyperthyroidism and papillary thyroid carcinoma. It is found that Cherenkov light is emitted mostly in the treatment volume, the spatial distribution of Cherenkov light at the surface of the patient presents high-value regions at locations that depend on the symmetry and location of the treatment volume, and the surface light in the near-infrared spectral region originates from the treatment site. The effect of inter-patient variability in the tissue optical parameters and radioisotope uptake on the linear relationship between the dose absorbed by the treatment volume and Cherenkov light intensity at the surface of the patient is investigated, and measurements of surface light intensity for which this effect is minimal are identified.
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