Development and application of Quantum Subspace-Based Algorithms for energy transition materials
Key words: quantum computing, quantum algorithms, quantum Lanczos, subspace methods, electronic structure, energy materials, CO2 storage and capture, energy conversion.
Context and topic: The modeling of electronic structure of physico-chemical systems rely on solving the Schrödinger equation. Classical subspace-based algorithms, such as the Lanczos method, outperform classical diagonalization algorithms in obtaining precise results but remain computationally expensive. The advent of quantum computing promises a revolution, enabling theoretically accurate simulations of exponentially larger electronic systems. This breakthrough is expected to address societal and environmental challenges, such as the development of new materials for CO2 capture and storage, and energy conversion.
Current quantum computing research on the electronic structure problem has primarily focused on two approaches: hybrid variational quantum eigensolver (VQE) methods for noisy quantum computers, and Quantum Phase Estimation (QPE) algorithms targeting long-term fault-tolerant devices [1,2]. Recently, the adaptation of classical subspace methods to quantum computing has demonstrated a versatile framework [3]. This framework can be adapted to both noisy devices, using physically motivated or variational subspace construction [4-6], and to fault-tolerant devices by explicitly constructing the Krylov subspace using propagators or block encoding [7,8].
In this context and in strong collaboration between the academy (LOMA, University of Bordeaux) and an industrial partner (CIFRE scholarship within TotalEnergies, based in Saclay), this PhD thesis aims to develop, adapt and evaluate quantum subspace methods to simulate the electronic structure of materials. Specifically, the goal are to:
1. Establish and implement an algorithmic framework that enables both noisy (subspace construction) and fault-tolerant (block encoding) quantum simulations, and a comparison with fault-tolerant QPE approaches.
2. Test, benchmark and document the performances of these methods on various electronic systems. The target systems are of interest for the use-case of material design for CO 2 capture. In addition, systems exhibiting strongly-interacting electrons, such as those based on transition metals, will be considered to benchmark the results.
Profile and requirements:
• Master of quantum or condensed-matter physics, quantum or theoretical chemistry.
• Appealing for quantum computing and multi-disciplinary projects.
• Strong taste for numerical work (Python, Quantum packages (Qiskit or myQLM)).
Logistic:
• The PhD will take place mainly in Saclay at TotalEnergy with regular visits in Bordeaux.
• Duration 3 years starting in September 2025.
Contacts:
• Jérémie Messud –
jeremie.messud@totalenergies.com
• Matthieu Saubanère –
matthieu.saubanere@cnrs.fr
Refs:
[1] B. Bauer, S. Bravyi, M. Motta, and G. K.-L. Chan, Chem. Rev. 120, 12685 (2020).
[2] K. Bharti, A. Cervera-Lierta, T. H. Kyaw, T. Haug, S. Alperin-Lea, A. Anand, M. Degroote, H. Heimonen, J. S.
Kottmann, T. Menke, W.-K. Mok, S. Sim, L.-C. Kwek, and A. Aspuru-Guzik, Rev. Mod. Phys. 94, 015004 (2022).
[3] M. Motta, W. Kirby, I. Liepuoniute, K. J. Sung, J. Cohn, A. Mezzacapo, K. Klymko, N. Nguyen, N. Yoshioka, and J. E.
Rice, Electron. Struct. 6, 013001 (2024).
[4] J. R. McClean, M. E. Kimchi-Schwartz, J. Carter, and W. A. de Jong, Phys. Rev. A 95, 042308 (2017).
[5] Robledo-Moreno et. al., arXiv:2405.05068 (2024).
[6] H. A. Akande, B. Senjean and M. Saubanère, arXiv:2411.16915 (2024)
[7] N. H. Stair, C. L. Cortes, R. M. Parrish, J. Cohn, and M. Motta, Phys. Rev. A 107, 032414 (2023).
[8] W. Kirby, M. Motta, and A. Mezzacapo, Quantum 7, 1018 (2023).
Modifié 1 fois. Dernière modification le 17/03/25 12:28 par
matthieu.saubanere@cnrs.fr.