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arXiv:2606.04295

Quantum simulations of ultrafast optical spectroscopy of semiconductors on digital quantum computers in the semi-classical approximation

Mykhailo Klymenko, Bahar Goldozian, Thong Hoang, Jared H. Cole, Muhammad Usman

quant-phSubmitted Jun 2, 2026• Announced Jun 4, 2026• 0 citations
v1 · Jun 2, 2026v2 · Oct 25, 2026
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Abstract

We present a digital quantum simulation framework for ultrafast optical spectroscopy of semiconductor materials. The framework is based on Brillouin-zone discretization and the second-quantization formalism, and is designed as a quantum alternative to classical simulations based on the semiconductor Bloch equations. Its current capabilities include quantum simulations of linear absorption and optical gain spectra, incorporating Lorentzian broadening, finite-temperature band-filling effects, and reduced-dimensionality effects. Benchmark comparisons with classical simulations for GaAs demonstrate quantitative agreement in the noiseless limit. The inclusion of realistic hardware noise of NISQ-era quantum computers effectively manifests itself as an additional source of scattering processes, resulting in increased spectral broadening. While no exponential quantum advantage is expected in the single-particle approximation, the framework naturally extends to many-body regimes where classical simulations face the hierarchy problem and exponential scaling and provable quantum advantage will be possible. The quantum simulations considered in this work capture central elements of semiconductor spectroscopy, the aspects such as open quantum systems, light-matter interactions, statistical mechanics, non-equilibrium quantum dynamics, and many-body physics. As such, it provides a physically motivated and scalable model for benchmarking quantum computers in applications to complex, real-world problems.

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We present a digital quantum simulation framework for ultrafast optical spectroscopy of semiconductor materials. The framework is based on Brillouin-zone discretization and the second-quantization formalism, and is designed as a quantum alternative to classical simulations based on the semiconductor Bloch equations. Its current capabilities include quantum simulations of linear absorption and optical gain spectra, incorporating Lorentzian broadening, finite-temperature band-filling effects, and reduced-dimensionality effects. Benchmark comparisons with classical simulations for GaAs demonstrate quantitative agreement in the noiseless limit. The inclusion of realistic hardware noise of NISQ-era quantum computers effectively manifests itself as an additional source of scattering processes, resulting in increased spectral broadening. While no exponential quantum advantage is expected in the single-particle approximation, the framework naturally extends to many-body regimes where classical simulations face the hierarchy problem and exponential scaling and provable quantum advantage will be possible. The quantum simulations considered in this work capture central elements of semiconductor spectroscopy, the aspects such as open quantum systems, light-matter interactions, statistical mechanics, non-equilibrium quantum dynamics, and many-body physics. As such, it provides a physically motivated and scalable model for benchmarking quantum computers in applications to complex, real-world problems.
Multidimensional optical spectroscopies are powerful techniques to investigate energy transfer pathways in natural and artificial systems. Because of the high information content of the spectra, numerical simulations of the optical response are of primary importance to assist the interpretation of spectral features. However, the increasing complexity of the investigated systems and their quantum dynamics call for the development of novel simulation strategies. In this work, we consider using digital quantum computers. By combining quantum dynamical simulation and nonlinear response theory, we present a quantum algorithm for computing the optical response of molecular systems. The quantum advantage stems from the efficient quantum simulation of the dynamics governed by the molecular Hamiltonian, and it is demonstrated by explicitly considering exciton-vibrational coupling. The protocol is tested on a near-term quantum device, providing the digital quantum simulation of the linear and nonlinear response of simple molecular models.
Spectroscopy is an indispensable tool in understanding the structures and dynamics of molecular systems. However computational modelling of spectroscopy is challenging due to the exponential scaling of computational complexity with system sizes unless drastic approximations are made. Quantum computer could potentially overcome these classically intractable computational tasks, but existing approaches using quantum computers to simulate spectroscopy can only handle isolated and static molecules. In this work we develop a workflow that combines multi-scale modeling and time-dependent variational quantum algorithm to compute the linear spectroscopy of systems interacting with their condensed-phase environment via the relevant time correlation function. We demonstrate the feasibility of our approach by numerically simulating the UV-Vis absorption spectra of organic semiconductors. We show that our dynamical approach captures several spectral features that are otherwise overlooked by static methods. Our method can be directly used for other linear condensed-phase spectroscopy and could potentially be extended to nonlinear multi-dimensional spectroscopy.
Spectroscopy is an indispensable tool for understanding the structures and dynamics of molecular systems. However, computational modeling of spectroscopy is challenging due to the exponential scaling of computational complexity with system sizes unless drastic approximations are made. Quantum computers could potentially overcome these classically intractable computational tasks, but the existing approaches using quantum computers to simulate spectroscopy can only handle isolated and static molecules. In this work, we develop a workflow that combines multi-scale modeling and a time-dependent variational quantum algorithm to compute the linear spectroscopy of systems interacting with their condensed-phase environment via the relevant time correlation function. We demonstrate the feasibility of our approach by numerically simulating the UV-vis absorption spectra of organic semiconductors. We show that our dynamical approach captures several spectral features that are otherwise overlooked by static methods. Our method can be directly used for other linear condensed-phase spectroscopy and could potentially be extended to nonlinear multi-dimensional spectroscopy.
Ultrafast nonlinear optical spectroscopy is used to study the coherent dynamics of optically excited electron-hole pairs in semiconductors. Coulomb interaction implies that the optical inter-band transitions are dominated, at least at low temperatures, by excitonic effects. They are further enhanced in quantum confined lower-dimensional systems, where exciton and biexciton effects dominate the spectra even at room temperature. The coherent dynamics of excitons are at modest densities well described by the optical Bloch equations and a number of the dynamical effects known from atomic and molecular systems are found and studied in the exciton-biexciton system of semiconductors. At densities where strong exciton interactions, or many-body effects, become dominant, the semiconductor Bloch equations present a more rigorous treatment of the phenomena. Ultrafast degenerate four-wave mixing is used as a tool to study the coherent exciton dynamics, and the importance of performing transform limited spectroscopy is demonstrated throughout.
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Quantum computation provides new avenues for the simulation of complex systems, which are beyond the capability of classical computation. In this paper, we describe an efficient simulator for quantum computing models, particularly designed for simulating complex systems. Through hybrid quantum–classical methods, noise-tolerant algorithms, and adaptive parameter updating, the method addresses several limitations of NISQ-era methods. The framework proves to be more scalable, accurate, and domain-transparent in applications to molecular dynamics, material science, and quantum chemistry. Experimental results verify the benefit compared to the state of the art in terms of both convergence rate and fidelity, demonstrating its applicability for future simulation tasks.