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This research advances quantum computing by introducing time-varying driven-dissipative protocols that prepare ground states from arbitrary initial conditions without requiring large overlaps. By leveraging randomized Lindbladians derived from random matrix unitary evolution, the study establishes mixing time bounds dependent solely on eigenvalue distributions, offering a robust solution for "cold start" scenarios in quantum state preparation.
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Driven-Dissipative Ground State Preparation: Mixing Time and Randomness

arXiv2 min read

arXiv:2610.03860v1 Announce Type: new Abstract: Dissipative protocols offer a route to ground state preparation that does not require a large initial overlap with the ground state. To move beyond time independent Lindbladians and randomized Lindbladians sampled from a fixed distribution, we study driven-dissipative protocols in which the generator varies over time. Our construction uses a family of randomized Lindbladians whose jump operators are obtained by averaging the unitary evolution of random matrices under a fixed target Hamiltonian. We show that empirical averages of these Lindbladians drive arbitrary initial density matrices to low energy states. The resulting mixing time bounds depend on the Hamiltonian only through its eigenvalue distribution and remain valid even for cold starts.

Abstract:Dissipative protocols offer a route to ground state preparation that does not require a large initial overlap with the ground state. To move beyond time independent Lindbladians and randomized Lindbladians sampled from a fixed distribution, we study driven-dissipative protocols in which the generator varies over time. Our construction uses a family of randomized Lindbladians whose jump operators are obtained by averaging the unitary evolution of random matrices under a fixed target Hamiltonian. We show that empirical averages of these Lindbladians drive arbitrary initial density matrices to low energy states. The resulting mixing time bounds depend on the Hamiltonian only through its eigenvalue distribution and remain valid even for cold starts.

arXiv:2610.03860 [quant-ph]

(or arXiv:2610.03860v1 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2610.03860 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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Full text under the publisher's open licence · 201 words

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