The intriguing task of evaluating, in a Quantum Monte Carlo simulation, the dynamic structure factor of a condensed matter sample, hence gaining informations about the elementry excitations which may be observed in a thermal neutrons scattering experiment, is yet a very delicate one. The difficulties arise because, in a simulation, dynamics takes place in the imaginary time domain, and analytic continuation is required to translate the results into real time dynamical correlations functions. This is far from trivial since one has to care for the role of the statistical noise, which, if not properly taken into account, may lead to uncontrolled incertainties and only qualitatively interesting results. We suggest a new analytic continuation technique, relying on genetic optimization algorithms, and assuming the first few momenta as the only prior knoledge about the spectral function. As an example, we show the results of the method when applied to the study of a sample of 4 He atoms at zero-temperature in te liquid phase.

Real time dynamics from quantum Monte Carlo data: A genetic algorithm approach / E. Vitali, D. E. Galli, L. Reatto. - In: JOURNAL OF PHYSICS. CONFERENCE SERIES. - ISSN 1742-6588. - 150:3(2009), pp. 032116.032116-032116.032116.

Real time dynamics from quantum Monte Carlo data: A genetic algorithm approach

E. Vitali
Primo
;
D. E. Galli
Secondo
;
L. Reatto
2009

Abstract

The intriguing task of evaluating, in a Quantum Monte Carlo simulation, the dynamic structure factor of a condensed matter sample, hence gaining informations about the elementry excitations which may be observed in a thermal neutrons scattering experiment, is yet a very delicate one. The difficulties arise because, in a simulation, dynamics takes place in the imaginary time domain, and analytic continuation is required to translate the results into real time dynamical correlations functions. This is far from trivial since one has to care for the role of the statistical noise, which, if not properly taken into account, may lead to uncontrolled incertainties and only qualitatively interesting results. We suggest a new analytic continuation technique, relying on genetic optimization algorithms, and assuming the first few momenta as the only prior knoledge about the spectral function. As an example, we show the results of the method when applied to the study of a sample of 4 He atoms at zero-temperature in te liquid phase.
Settore FIS/03 - Fisica della Materia
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/189582
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