Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Exploring Sensitivity of ICF Outputs to Design Parameters in Experiments
  Using Machine Learning   Building a sustainable burn platform in inertial confinement fusion (ICF)
requires an understanding of the complex coupling of physical processes and the
effects that key experimental design changes have on implosion performance.
While simulation codes are used to model ICF implosions, incomplete physics and
the need for approximations deteriorate their predictive capability.
Identification of relationships between controllable design inputs and
measurable outcomes can help guide the future design of experiments and
development of simulation codes, which can potentially improve the accuracy of
the computational models used to simulate ICF implosions. In this paper, we
leverage developments in machine learning (ML) and methods for ML feature
importance/sensitivity analysis to identify complex relationships in ways that
are difficult to process using expert judgment alone. We present work using
random forest (RF) regression for prediction of yield, velocity, and other
experimental outcomes given a suite of design parameters, along with an
assessment of important relationships and uncertainties in the prediction
model. We show that RF models are capable of learning and predicting on ICF
experimental data with high accuracy, and we extract feature importance metrics
that provide insight into the physical significance of different controllable
design inputs for various ICF design configurations. These results can be used
to augment expert intuition and simulation results for optimal design of future
ICF experiments.

19
The categories of this paper are: eess
17
The categories of this paper are: q-fin
7
The categories of this paper are: hep-th
29
The categories of this paper are: funct-an
28
The categories of this paper are: alg-geom
6
The categories of this paper are: astro-ph
10
The categories of this paper are: q-bio
26
The categories of this paper are: bayes-an
14
The categories of this paper are: math-ph
27
The categories of this paper are: comp-gas
8
The categories of this paper are: hep-ex
11
The categories of this paper are: hep-lat
18
The categories of this paper are: econ
22
The categories of this paper are: chao-dyn
0
The categories of this paper are: hep-ph
37
The categories of this paper are: supr-con