Reduced Density Matrix Formulation of Quantum Linear Response.

Area of Science:

• Quantum chemistry
• Computational spectroscopy
• Quantum computing applications

Background:

• Linear response (LR) theory is crucial for predicting spectral properties and understanding photoinduced processes.
• Quantum computing offers new avenues for quantum chemistry calculations.
• Previous work adapted LR theory for quantum hardware as quantum linear response (qLR) using truncated active space and orbital rotation.

Purpose of the Study:

• To reduce the classical computational cost of the hybrid quantum-classical qLR approach.
• To enable the calculation of spectral properties for larger molecules and basis sets using quantum hardware.
• To investigate the impact of shot noise on spectral predictions.

Main Methods:

• Derivation and implementation of a reduced density matrix (RDM) driven approach for qLR.
• Application of the qLR method to benzene and R-methyloxirane using a cc-pVTZ basis set.
• Simulation of valence and oxygen K-edge absorption spectra for H2O, including the effect of shot noise.

Main Results:

• The RDM-driven qLR method allows for spectral property calculations with significantly larger basis sets.
• Accurate qLR results were obtained for benzene and R-methyloxirane.
• The study characterized the influence of shot noise on absorption spectra.

Conclusions:

• The RDM-driven qLR method is a promising hybrid approach for efficient spectral property prediction.
• This method expands the capability of quantum computing for molecular spectroscopy.
• Understanding shot noise effects is important for reliable quantum spectral predictions.