Speaker: Werner Dobrautz, Helmholtz-Zentrum Dresden-Rossendorf; Center for Advanced Systems Understanding; Center for Scalable Data Analytics and Artificial Intelligence

Accurately exploring molecular energy landscapes remains a central challenge in computational quantum chemistry, particularly for systems exhibiting strong correlation. Quantum computers promise new capabilities in this regard, yet practical progress is hindered by noise, limited qubit counts, shallow circuit depths, and optimization difficulties in variational quantum algorithms (VQAs).

In this talk, I will present how transcorrelated quantum simulation—based on a similarity-transformed Hamiltonian incorporating electron–electron cusp information—reshapes the energy landscape to improve convergence toward chemically accurate solutions. This reformulation reduces basis set incompleteness errors[1] and enables more compact circuit representations[2], which are especially valuable on noisy, near-term quantum devices.

To fully leverage these benefits, we combine transcorrelation with adaptive ansätze[4], which iteratively construct compact quantum circuits tailored to the problem at hand. This combination significantly reduces both qubit requirements and gate counts.

To address the optimization challenges commonly encountered in flat or rugged variational landscapes, we developed qBang—a hybrid optimization scheme that interweaves geometric information from the Fubini–Study metric with adaptive momentum-based updates[4].

I will illustrate our method using benchmark studies on Hubbard models and small molecular systems, highlighting recent implementations of transcorrelated variational imaginary time evolution (TC-VarQITE). Results from both classical circuit simulations and runs on actual quantum hardware demonstrate that this approach enables more realistic and noise-resilient approximations to ground state energies—bringing us closer to chemically accurate energy landscapes using near-term quantum resources.

[1] W. Dobrautz et al., J. Chem. Theory Comput. 2024, 20, 10, 4146–4160
[2] I.O. Sokolov, W. Dobrautz, H. Luo, A. Alavi, I. Tavernelli, Phys. Rev. Research 5, 023174
[3] E. Magnusson, A. Fitzpatrick, S. Knecht, M. Rahm, Werner Dobrautz, Faraday Discuss., 2024, 254, 402-428
[4] D. Fitzek, R.S. Jonsson, W. Dobrautz, C. Schäfer, Quantum 8, 1313 (2024)