The Stochastic Self-Consistent Harmonic Approximation: Calculating Vibrational Properties of Materials with Full Quantum and Anharmonic Effects

TL;DR

This paper introduces a Python implementation of the stochastic self-consistent harmonic approximation method, enabling accurate calculation of vibrational properties of materials considering full quantum and anharmonic effects, useful for phase diagram and phonon spectrum analysis.

Contribution

The paper presents a modular Python code for the stochastic self-consistent harmonic approximation, allowing comprehensive thermodynamic and vibrational analysis of crystals with anharmonic effects.

Findings

Accurate phase boundary determination from free energy Hessian.

Calculation of anharmonic phonon spectra and linewidths.

Validation with a toy-model example.

Abstract

The efficient and accurate calculation of how ionic quantum and thermal fluctuations impact the free energy of a crystal, its atomic structure, and phonon spectrum is one of the main challenges of solid state physics, especially when strong anharmonicy invalidates any perturbative approach. To tackle this problem, we present the implementation on a modular Python code of the stochastic self-consistent harmonic approximation method. This technique rigorously describes the full thermodyamics of crystals accounting for nuclear quantum and thermal anharmonic fluctuations. The approach requires the evaluation of the Born-Oppenheimer energy, as well as its derivatives with respect to ionic positions (forces) and cell parameters (stress tensor) in supercells, which can be provided, for instance, by first principles density-functional-theory codes. The method performs crystal geometry relaxation on the quantum free energy landscape, optimizing the free energy with respect to all degrees of freedom of the crystal structure. It can be used to determine the phase diagram of any crystal at finite temperature. It enables the calculation of phase boundaries for both first-order and second-order phase transitions from the Hessian of the free energy. Finally, the code can also compute the anharmonic phonon spectra, including the phonon linewidths, as well as phonon spectral functions. We review the theoretical framework of the stochastic self-consistent harmonic approximation and its dynamical extension, making particular emphasis on the physical interpretation of the variables present in the theory that can enlighten the comparison with any other anharmonic theory. A modular and flexible Python environment is used for the implementation, which allows for a clean interaction with other packages. We briefly present a toy-model calculation to illustrate the potential of the code.