A Parameter Free Genetic Algorithm for Estimating the Dynamic Structure Factor at Zero and Finite Temperature
ORAL
Abstract
We report on a self adaptive Differential Evolution for Analytic Continuation (DEAC) algorithm that can be used to reconstruct the dynamic structure factor from imaginary time density-density correlations. Our approach to this long-standing problem in quantum many-body physics achieves improved resolution of spectral features over earlier methods based on genetic algorithms. The need for fine-tuning of algorithmic control parameters is reduced by embedding them within the genome to be optimized. Benchmarks are presented for models where the dynamic structure factor is known exactly and we report new results for quantum Monte Carlo simulations of confined superfluid helium at low temperatures.
*This work was supported by the NSF through grants DMR-1809027 and DMR-1808440. Simulations performed on the Vermont Advanced Computing Core were partially supported by NSF grant OAC-1827314.
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Presenters
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Nathan Nichols
- Univ of Vermont
- University of Vermont