English

Quantum algorithms from fluctuation theorems: Thermal-state preparation

Quantum Physics 2022-10-11 v2 Statistical Mechanics

Abstract

Fluctuation theorems provide a correspondence between properties of quantum systems in thermal equilibrium and a work distribution arising in a non-equilibrium process that connects two quantum systems with Hamiltonians H0H_0 and H1=H0+VH_1=H_0+V. Building upon these theorems, we present a quantum algorithm to prepare a purification of the thermal state of H1H_1 at inverse temperature β0\beta \ge 0 starting from a purification of the thermal state of H0H_0. The complexity of the quantum algorithm, given by the number of uses of certain unitaries, is O~(eβ(Δ ⁣Awl)/2)\tilde {\cal O}(e^{\beta (\Delta \! A- w_l)/2}), where Δ ⁣A\Delta \! A is the free-energy difference between H1H_1 and H0,H_0, and wlw_l is a work cutoff that depends on the properties of the work distribution and the approximation error ϵ>0\epsilon>0. If the non-equilibrium process is trivial, this complexity is exponential in βV\beta \|V\|, where V\|V\| is the spectral norm of VV. This represents a significant improvement of prior quantum algorithms that have complexity exponential in βH1\beta \|H_1\| in the regime where VH1\|V\|\ll \|H_1\|. The dependence of the complexity in ϵ\epsilon varies according to the structure of the quantum systems. It can be exponential in 1/ϵ1/\epsilon in general, but we show it to be sublinear in 1/ϵ1/\epsilon if H0H_0 and H1H_1 commute, or polynomial in 1/ϵ1/\epsilon if H0H_0 and H1H_1 are local spin systems. The possibility of applying a unitary that drives the system out of equilibrium allows one to increase the value of wlw_l and improve the complexity even further. To this end, we analyze the complexity for preparing the thermal state of the transverse field Ising model using different non-equilibrium unitary processes and see significant complexity improvements.

Keywords

Cite

@article{arxiv.2203.08882,
  title  = {Quantum algorithms from fluctuation theorems: Thermal-state preparation},
  author = {Zoe Holmes and Gopikrishnan Muraleedharan and Rolando D. Somma and Yigit Subasi and Burak Şahinoğlu},
  journal= {arXiv preprint arXiv:2203.08882},
  year   = {2022}
}

Comments

54 pages, 11 figures

R2 v1 2026-06-24T10:16:12.687Z