skip to main content

Title: Automation and control of laser wakefield accelerators using Bayesian optimization
Abstract Laser wakefield accelerators promise to revolutionize many areas of accelerator science. However, one of the greatest challenges to their widespread adoption is the difficulty in control and optimization of the accelerator outputs due to coupling between input parameters and the dynamic evolution of the accelerating structure. Here, we use machine learning techniques to automate a 100 MeV-scale accelerator, which optimized its outputs by simultaneously varying up to six parameters including the spectral and spatial phase of the laser and the plasma density and length. Most notably, the model built by the algorithm enabled optimization of the laser evolution that might otherwise have been missed in single-variable scans. Subtle tuning of the laser pulse shape caused an 80% increase in electron beam charge, despite the pulse length changing by just 1%.
Authors:
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more » ; ; ; ; ; ; ; ; ; « less
Award ID(s):
1804463
Publication Date:
NSF-PAR ID:
10273602
Journal Name:
Nature Communications
Volume:
11
Issue:
1
ISSN:
2041-1723
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract Temperature control is essential for regulating material properties in laser-based manufacturing. Motion and power of the scanning laser affect local temperature evolution, which in turn determines the a posteriori microstructure. This paper addresses the problem of adjusting the laser speed and power to achieve the desired values of key process parameters: cooling rate and melt pool size. The dynamics of a scanning laser system is modeled by a one-dimensional (1D) heat conduction equation, with laser power as the heat input and heat dissipation to the ambient. Since the model is 1D, length and size are essentially the same. Wemore »pose the problem as a regulation problem in the (moving) laser frame. The first step is to obtain the steady-state temperature distribution and the corresponding input based on the desired cooling rate and melt pool size. The controller adjusts the input around the steady-state feedforward based on the deviation of the measured temperature field from the steady-state distribution. We show that with suitably defined outputs, the system is strictly passive from the laser motion and power. To avoid over-reliance on the model, the steady-state laser speed and power are adaptively updated, resulting in an integral-like update law for the feedforward. Moreover, the heat transfer coefficient to the ambient may be uncertain, and can also be adaptively updated. The final form of the control law combines passive error temperature field feedback with adaptive feedforward and parameter estimation. The closed-loop asymptotical stability is shown using the Lyapunov arguments, and the controller performance is demonstrated in a simulation.« less
  2. Continuous advancements in LiDAR technology have enabled compelling wind turbulence measurements within the atmospheric boundary layer with range gates shorter than 20 m and sampling frequency of the order of 10 Hz. However, estimates of the radial velocity from the back-scattered laser beam are inevitably affected by an averaging process within each range gate, generally modeled as a convolution between the actual velocity projected along the LiDAR line-of-sight and a weighting function representing the energy distribution of the laser pulse along the range gate. As a result, the spectral energy of the turbulent velocity fluctuations is damped within the inertialmore »sub-range with respective reduction of the velocity variance, and, thus, not allowing to take advantage of the achieved spatio-temporal resolution of the LiDAR technology. In this article, we propose to correct this turbulent energy damping on the LiDAR measurements by reversing the effect of a low-pass filter, which can be estimated directly from the LiDAR measurements. LiDAR data acquired from three different field campaigns are analyzed to describe the proposed technique, investigate the variability of the filter parameters and, for one dataset, assess the procedure for spectral LiDAR correction against sonic anemometer data. It is found that the order of the low-pass filter used for modeling the energy damping on the LiDAR velocity measurements has negligible effects on the correction of the second-order statistics of the wind velocity. In contrast, its cutoff frequency plays a significant role in the spectral correction encompassing the smoothing effects connected with the LiDAR gate length.« less
  3. The generation of colloidal solutions of chemically clean nanoparticles through pulsed laser ablation in liquids (PLAL) has evolved into a thriving research field that impacts industrial applications. The complexity and multiscale nature of PLAL make it difficult to untangle the various processes involved in the generation of nanoparticles and establish the dependence of nanoparticle yield and size distribution on the irradiation parameters. Large-scale atomistic simulations have yielded important insights into the fundamental mechanisms of ultrashort (femtoseconds to tens of picoseconds) PLAL and provided a plausible explanation of the origin of the experimentally observed bimodal nanoparticle size distributions. In this paper,more »we extend the atomistic simulations to short (hundreds of picoseconds to nanoseconds) laser pulses and focus our attention on the effect of the pulse duration on the mechanisms responsible for the generation of nanoparticles at the initial dynamic stage of laser ablation. Three distinct nanoparticle generation mechanisms operating at different stages of the ablation process and in different parts of the emerging cavitation bubble are identified in the simulations. These mechanisms are (1) the formation of a thin transient metal layer at the interface between the ablation plume and water environment followed by its decomposition into large molten nanoparticles, (2) the nucleation, growth, and rapid cooling/solidification of small nanoparticles at the very front of the emerging cavitation bubble, above the transient interfacial metal layer, and (3) the spinodal decomposition of a part of the ablation plume located below the transient interfacial layer, leading to the formation of a large population of nanoparticles growing in a high-temperature environment through inter-particle collisions and coalescence. The coexistence of the three distinct mechanisms of the nanoparticle formation at the initial stage of the ablation process can be related to the broad nanoparticle size distributions commonly observed in nanosecond PLAL experiments. The strong dependence of the nanoparticle cooling and solidification rates on the location within the low-density metal–water mixing region has important implications for the long-term evolution of the nanoparticle size distribution, as well as for the ability to quench the nanoparticle growth or dope them by adding surface-active agents or doping elements to the liquid environment.« less
  4. The efficiency of an accelerator depends on three factors—mapping, deep neural network (DNN) layers, and hardware—constructing extremely complicated design space of DNN accelerators. To demystify such complicated design space and guide the DNN accelerator design for better efficiency, we propose an analytical cost model, MAESTRO. MAESTRO receives DNN model description and hardware resources information as a list, and mapping described in a data-centric representation we propose as inputs. The data centric representation consists of three directives that enable concise description of mappings in a compiler-friendly form. MAESTRO analyzes various forms of data reuse in an accelerator based on inputs quicklymore »and generates more than 20 statistics including total latency, energy, throughput, etc., as outputs. MAESTRO’s fast analysis enables various optimization tools for DNN accelerators such as hardware design exploration tool we present as an example.« less
  5. Microneedles provide a transdermal pathway for drug delivery, cosmetic infusion, vaccine administration, and disease diagnostics. Microneedle fabrication relies on the interplay of several variables which include design parameters, material properties, and processing conditions. In this research, our group explores the effect of design parameters and process variables for laser ablation of microneedles within a Polymethyl methacrylate (PMMA) mold. An Ytterbium laser (200W) was utilized to study the effect of five inputs factors (laser power, pulse width, number of repetitions, laser waveform, and interval time between laser pulses) on two output factors (diameter and height) of the fabricated microneedles. Polydimethylsiloxane (PDMS)more »polymer was cast within the PMMA microneedle mold. Scanning electron microscopy (SEM) was employed to image topographical features of the microneedles. Further, mechanical testing of the microneedles was conducted to evaluate the buckling load and deformation behavior of the microneedle array. A 20W pulse laser with trapezoidal waveform resulted in optimal microneedle topography with an aspect ratio of 1.2. ANOVA results (α = 0.05) depicted that laser power and number of repetitions were significant factors determining the geometrical features of the microneedle array. This research establishes a framework for the design and manufacturing of customized microneedles for precision medicine.« less