Frequency-Dependent Polarization Propagator Calculation for Quantum Dots Using Optimized Inverse Krylov Subspace and Folded-Spectrum Method

TL;DR

This paper introduces an efficient computational method combining inverse Krylov subspace and folded-spectrum techniques to accurately predict the frequency-dependent polarization response of quantum dots, reducing computational cost for large systems.

Contribution

It develops a novel frequency-dependent polarization propagator calculation method using inverse Krylov subspace and folded-spectrum techniques for quantum dots.

Findings

Accurate UV-VIS spectra for PbS and CdS quantum dots were computed.

The method significantly reduces computational cost compared to full diagonalization.

The approach provides an efficient approximation for large quantum systems.

Abstract

Accurate prediction of the frequency response of quantum dots under electromagnetic radiation is essential for investigating absorption spectra, excitonic effects, and nonlinear optical behavior in quantum dots and semiconductor nanoparticles. The polarization propagator provides a rigorous framework for evaluating these properties, but its construction is computationally demanding. Challenges arise from the level of electron correlation, the size of the excitonic basis, and the cost of evaluating two-electron integrals. This work addresses these difficulties by developing first- and second-order frequency-dependent polarization propagator calculations for PbS and CdS quantum dots. The propagator is formulated using the electron propagator approach and expressed as the resolvent of the Hamiltonian superoperator. Light-matter interaction is treated using the dipole approximation and represented in a particle-hole excitation operator basis. The correlated ground state is treated at the MP2 level, and all response-matrix terms up to second order in the fluctuating potential are included. A frequency-dependent inverse Krylov subspace method is derived and combined with the folded-spectrum technique to isolate excitation energies within a chosen frequency window. This strategy avoids full diagonalization of the response matrix and significantly reduces computational cost for large systems. The method is implemented in a matrix-free manner in which no explicit response matrix is assembled, and all operations rely on matrix-vector products. UV-VIS excitation spectra of PbS and CdS quantum dots were computed, demonstrating that the inverse Krylov subspace projection approach provides an efficient and accurate approximation for excitation spectra when full diagonalization is computationally prohibitive.