Quantum algorithms for cooling: A simple case study

Daniel Molpeceres, Sirui Lu, J. Ignacio Cirac, Barbara Kraus
Preparation of low-energy quantum many-body states has a wide range of applications in quantum information processing and condensed-matter physics. Quantum cooling algorithms offer a promising alternative to other methods based, for instance, on variational and adiabatic principles, or on dissipative state preparation. In this work, we investigate a set of cooling algorithms in a simple, solvable fermionic model that allows us to identify the mechanisms that underlie the cooling process and, also, those that prevent it. We derive analytical expressions for the cooling dynamics, steady states, and cooling rates in the weak-coupling limit. We find that multifrequency and randomized cycle strategies can significantly enhance the performance of the quantum algorithm and circumvent some of the obstacles. We also analyze the effects of noise and evaluate the conditions under which cooling remains feasible. Furthermore, we present optimized cooling protocols that can significantly enhance cooling performance in the presence of noise. Additionally, we compare cooling and dissipative state preparation and show that, in the model analyzed here, cooling generally achieves lower energies and is more resilient to noise.

Cite as BiBTeX

@article{4hx7-xnhw,
title = {Quantum algorithms for cooling: A simple case study},
author = {Molpeceres, Daniel and Lu, Sirui and Cirac, J. Ignacio and Kraus, Barbara},
journal = {Phys. Rev. Res.},
volume = {7},
issue = {3},
pages = {033162},
numpages = {36},
year = {2025},
month = {Aug},
publisher = {American Physical Society},
doi = {10.1103/4hx7-xnhw},
url = {https://link.aps.org/doi/10.1103/4hx7-xnhw}
}

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The QCFD (Quantum Computational Fluid Dynamics) project is funded under the European Union’s Horizon Programme (HORIZON-CL4-2021-DIGITAL-EMERGING-02-10), Grant Agreement 101080085 QCFD.