Many problems in physics and modern computing are inverse problems -- problems where the desired output is known, and the task is to find the set of input parameters that will best reproduce that output in a hydrodynamics code (hydrocode). Optimization methods tackle this type of problem, and a central task in applying optimization methods is to be able to determine the gradient of the output with respect to the input parameters that are being adjusted. Presented here is the authors' progress (through the use of adjoint differentiation) in obtaining those gradients in the case of some relatively simple hydrocodes.
Keywords: adjoint differentiation, hydrodynamics, sensitivity
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