State Preparation Boosters for Early Fault-Tolerant Quantum Computation

Guoming Wang; Sukin Sim; Peter D. Johnson

doi:10.22331/q-2022-10-06-829

State Preparation Boosters for Early Fault-Tolerant Quantum Computation

Guoming Wang¹, Sukin Sim², and Peter D. Johnson²

¹Zapata Computing Canada Inc., 25 Adelaide St E, Suite 1500, Toronto, ON M5C 3A1, Canada
²Zapata Computing Inc., 100 Federal Street, 20th Floor, Boston, MA 02110, USA

Published:	2022-10-06, volume 6, page 829
Eprint:	arXiv:2202.06978v3
Doi:	https://doi.org/10.22331/q-2022-10-06-829
Citation:	Quantum 6, 829 (2022).

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Abstract

Quantum computing is believed to be particularly useful for the simulation of chemistry and materials, among the various applications. In recent years, there have been significant advancements in the development of near-term quantum algorithms for quantum simulation, including VQE and many of its variants. However, for such algorithms to be useful, they need to overcome several critical barriers including the inability to prepare high-quality approximations of the ground state. Current challenges to state preparation, including barren plateaus and the high-dimensionality of the optimization landscape, make state preparation through ansatz optimization unreliable. In this work, we introduce the method of ground state boosting, which uses a limited-depth quantum circuit to reliably increase the overlap with the ground state. This circuit, which we call a booster, can be used to augment an ansatz from VQE or be used as a stand-alone state preparation method. The booster converts circuit depth into ground state overlap in a controllable manner. We numerically demonstrate the capabilities of boosters by simulating the performance of a particular type of booster, namely the Gaussian booster, for preparing the ground state of $N_2$ molecular system. Beyond ground state preparation as a direct objective, many quantum algorithms, such as quantum phase estimation, rely on high-quality state preparation as a subroutine. Therefore, we foresee ground state boosting and similar methods as becoming essential algorithmic components as the field transitions into using early fault-tolerant quantum computers.

► BibTeX data

@article{Wang2022statepreparation,
  doi = {10.22331/q-2022-10-06-829},
  url = {https://doi.org/10.22331/q-2022-10-06-829},
  title = {State {P}reparation {B}oosters for {E}arly {F}ault-{T}olerant {Q}uantum {C}omputation},
  author = {Wang, Guoming and Sim, Sukin and Johnson, Peter D.},
  journal = {{Quantum}},
  issn = {2521-327X},
  publisher = {{Verein zur F{\"{o}}rderung des Open Access Publizierens in den Quantenwissenschaften}},
  volume = {6},
  pages = {829},
  month = oct,
  year = {2022}
}

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Cited by

[1] Guoming Wang, Daniel Stilck França, Ruizhe Zhang, Shuchen Zhu, and Peter D. Johnson, "Quantum algorithm for ground state energy estimation using circuit depth with exponentially improved dependence on precision", Quantum 7, 1167 (2023).

[2] César Feniou, Olivier Adjoua, Baptiste Claudon, Julien Zylberman, Emmanuel Giner, and Jean-Philip Piquemal, "Sparse Quantum State Preparation for Strongly Correlated Systems", The Journal of Physical Chemistry Letters 15 11, 3197 (2024).

[3] Pauline J. Ollitrault, Cristian L. Cortes, Jérôme F. Gonthier, Robert M. Parrish, Dario Rocca, Gian-Luca Anselmetti, Matthias Degroote, Nikolaj Moll, Raffaele Santagati, and Michael Streif, "Enhancing Initial State Overlap through Orbital Optimization for Faster Molecular Electronic Ground-State Energy Estimation", Physical Review Letters 133 25, 250601 (2024).

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[5] Amara Katabarwa, Katerina Gratsea, Athena Caesura, and Peter D. Johnson, "Early Fault-Tolerant Quantum Computing", PRX Quantum 5 2, 020101 (2024).

[6] Guoming Wang and Angus Kan, "Option pricing under stochastic volatility on a quantum computer", Quantum 8, 1504 (2024).

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The above citations are from Crossref's cited-by service (last updated successfully 2025-03-04 22:11:11) and SAO/NASA ADS (last updated successfully 2025-03-04 22:11:11). The list may be incomplete as not all publishers provide suitable and complete citation data.

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