Inferring the one-electron reduced density matrix of molecular crystals from experimental data sets through...

Area of Science:

• Quantum mechanics
• Solid-state physics
• Materials science

Background:

• Quantum crystal descriptions are vital for understanding macroscopic properties and validating theoretical models.
• Existing methods for reconstructing the one-electron reduced density matrix (1-RDM) rely on strong assumptions, limiting their applicability and potentially introducing bias.

Purpose of the Study:

• To develop a method for inferring the one-electron reduced density matrix (1-RDM) with minimal assumptions.
• To overcome limitations and biases associated with current 1-RDM reconstruction techniques.

Main Methods:

• Utilized the mathematical framework of semidefinite programming.
• Addressed complex constraints on the 1-RDM that hindered previous models.

Main Results:

• Successfully inferred the 1-RDM with significantly reduced assumptions.
• The semidefinite programming approach effectively handled challenging 1-RDM constraints.
• Applied the method to the dry ice crystal, yielding satisfactory results.

Conclusions:

• The developed semidefinite programming framework offers a robust and less assumption-reliant approach for quantum crystal descriptions.
• This method serves as a valuable reference for interpreting experimental scattering data.
• Results align well with established periodic ab initio calculations, validating the approach.