Automated discovery and optimization of autonomous quantum error correction codes for a general open quantum system

• URL: http://arxiv.org/abs/2504.15070v1
• Date: Mon, 21 Apr 2025 12:56:10 GMT
• Title: Automated discovery and optimization of autonomous quantum error correction codes for a general open quantum system
• Authors: Sahel Ashhab,
• Abstract summary: We develop a method to implement autonomous quantum error correction (AQEC) for a general open quantum system.<n>We use a gradient-based search to update the code words, induced decay matrix and control Hamiltonian matrix.<n>We apply the method to optimize AQEC codes for a variety of few-level systems.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We develop a method to search for the optimal code space, induced decay rates and control Hamiltonian to implement autonomous quantum error correction (AQEC) for a general open quantum system. The system is defined by a free-evolution Lindbladian superoperator, which contains the free Hamiltonian and naturally occurring decoherence terms, as well as the control superoperators. The performance metric for optimization is the fidelity between the projector onto the code space and the same projector after Lindbladian evolution for a specified time. We use a gradient-based search to update the code words, induced decay matrix and control Hamiltonian matrix. We apply the method to optimize AQEC codes for a variety of few-level systems. The four-level system with uniform decay rates offers a simple example for testing and illustrating the operation of our approach. The algorithm reliably succeeds in finding the optimal code in this case, while success becomes probabilistic for more complicated cases. For a five-level system with photon loss decay, the algorithm finds good AQEC codes, but these codes are not as good as the well-known binomial code. We use the binomial code as a starting point to search for the optimal code for a perturbed five-level system. In this case, the algorithm finds a code that is better than both the original binomial code and any other code obtained numerically when starting from a random initial guess.

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