Development and integration of photonic Doppler velocimetry as a diagnostic for radiation driven experiments on the Z-machine

Swanson, K. J.; Jaar, G. S.; Mayes, Daniel; Mancini, Roberto; Иванов, В. В.; Astanovitskiy, A. L.; Dmitriev, O.; Klemmer, A. W.; Cruz, C. De La; Dolan, Daniel H.; Porwitzky, Andrew; Loisel, Guillaume; Bailey, J. E.

doi:10.1063/5.0084638

Cited by 4 publications

(1 citation statement)

References 29 publications

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“…However, CW lidars rely on a phase or frequency sweep of the light, which restricts their ability to operate in a single shot for swiftly moving platforms like CubeSats or airborne lidars 23 . In addition, despite the fact that the CW configuration improves range resolution and offers simultaneous velocimetry capability via the Doppler effect [24][25][26][27][28] , the maximum detection range, or the laser's coherence length, is limited by the laser phase noise.…”

Section: Introductionmentioning

confidence: 99%

Machine-learning-enhanced, phase-based multi-tone continuous-wave lidar

Bayer¹,

Demirel²,

Atalar³

et al. 2023

Photonic Instrumentation Engineering X

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Lidar technologies have been investigated and commercialized for various applications such as autonomous driving and aerial vehicles. The pulsed time of flight and frequency-modulated continuous-wave lidars are the two common lidar technologies that dominate. As an alternative to the available lidars, we developed the phase-based multi-tone continuouswave (PB-MTCW) technology that can perform single-shot simultaneous ranging and velocimetry measurements with a high resolution at distances far beyond the coherence length of a CW laser, without employing any form of sweeping. The proposed technique utilizes relative phase accumulations at phase-locked RF sidebands to identify the range of the target after a heterodyne detection of the beating of the echo signal with an unmodulated CW optical local oscillator (LO). Upto-date, we demonstrated that the PB-MTCW lidar could perform ranging ×500 beyond the coherence length of the laser with <1cm precision. Here, we implement machine learning (ML) algorithms to the PB-MTCW architecture to improve the ranging resolution, as well as to provide a solution to multi-target reflections using tone-amplitude variations. We used four different training schemes by utilizing the acquired RF tones and phases from simulation results, experimental results, and their combinations in a convolutional neural network model. We demonstrate that the ML algorithm yields an average mean square error of ~0.3mm compared to the actual target distance, hence enhancing the ranging resolution of PB-MTCW lidar. It is also shown that the ML algorithm can distinguish multiple targets in the same line of sight with a 98%±0.7% success rate depending on the targets' reflectance and distances.

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Section: Introductionmentioning

confidence: 99%

Machine-learning-enhanced, phase-based multi-tone continuous-wave lidar

Bayer¹,

Demirel²,

Atalar³

et al. 2023

Photonic Instrumentation Engineering X

View full text Add to dashboard Cite

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Development of spatially and temporally resolved electron density measurements for the assessment of radiation hydrodynamics simulations of laboratory X-ray photoionized plasmas

Jaar,

Swanson,

Mancini

et al. 2024

High Energy Density Physics

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Radiatively cooled magnetic reconnection experiments driven by pulsed power

Datta,

Chandler,

Myers

et al. 2024

Physics of Plasmas

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We present evidence for strong radiative cooling in a pulsed-power-driven magnetic reconnection experiment. Two aluminum exploding wire arrays, driven by a 20 MA peak current, 300 ns rise time pulse from the Z machine (Sandia National Laboratories), generate strongly driven plasma flows (MA≈7) with anti-parallel magnetic fields, which form a reconnection layer (SL≈120) at the mid-plane. The net cooling rate far exceeds the Alfvénic transit rate (τcool−1/τA−1≫1), leading to strong cooling of the reconnection layer. We determine the advected magnetic field and flow velocity using inductive probes positioned in the inflow to the layer, and inflow ion density and temperature from analysis of visible emission spectroscopy. A sharp decrease in x-ray emission from the reconnection layer, measured using filtered diodes and time-gated x-ray imaging, provides evidence for strong cooling of the reconnection layer after its initial formation. X-ray images also show localized hotspots, regions of strong x-ray emission, with velocities comparable to the expected outflow velocity from the reconnection layer. These hotspots are consistent with plasmoids observed in 3D radiative resistive magnetohydrodynamic simulations of the experiment. X-ray spectroscopy further indicates that the hotspots have a temperature (170 eV) much higher than the bulk layer (≤75 eV) and inflow temperatures (about 2 eV) and that these hotspots generate the majority of the high-energy (>1 keV) emission.

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Development and integration of photonic Doppler velocimetry as a diagnostic for radiation driven experiments on the Z-machine

Cited by 4 publications

References 29 publications

Machine-learning-enhanced, phase-based multi-tone continuous-wave lidar

Machine-learning-enhanced, phase-based multi-tone continuous-wave lidar

Development of spatially and temporally resolved electron density measurements for the assessment of radiation hydrodynamics simulations of laboratory X-ray photoionized plasmas

Radiatively cooled magnetic reconnection experiments driven by pulsed power

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