One-shot distillation with constant overhead using catalysts

• URL: http://arxiv.org/abs/2410.14547v2
• Date: Tue, 14 Oct 2025 09:03:25 GMT
• Title: One-shot distillation with constant overhead using catalysts
• Authors: Kun Fang, Zi-Wen Liu,
• Abstract summary: Minimizing the overhead distillation is crucial for the realization of quantum computation and other technologies.<n>In particular, for magic state distillation our method paves a path for tackling the diverging batch size problem.<n>We extend techniques to dynamical quantum resources and show that mutual information determines one-shot catalytic channel transformation.
• Score: 3.771547570340179
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Quantum resource distillation is a fundamental task in quantum information science and technology. Minimizing the overhead of distillation is crucial for the realization of quantum computation and other technologies. Here we explicitly demonstrate how, for general quantum resources, suitably designed quantum catalysts (i.e., auxiliary systems that remain unchanged before and after the process) enable distillation with constant overhead in the practical one-shot setting, thereby overcoming the established logarithmic lower bound for one-shot distillation overhead. In particular, for magic state distillation, our catalysis method paves a path for tackling the diverging batch size problem associated with code-based low-overhead protocols by enabling arbitrary reduction of the protocol size for any desired accuracy. Notably, this first yields constant-overhead magic state distillation methods with controllable protocol size. Furthermore, we demonstrate a tunable spacetime trade-off between overhead and success probability enabled by catalysts which offers significant versatility for practical implementation. Finally, we extend catalysis techniques to dynamical quantum resources and show that channel mutual information determines one-shot catalytic channel transformation, thereby advancing our understanding for both dynamical catalysis and information theory.

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