Magic State Distillation: Not as Costly as You Think

By Daniel Litinski. Quantum, 2019

331 citations recorded by the source corpus.

Despite significant overhead reductions since its first proposal, magic state distillation is often considered to be a very costly procedure that dominates the resource cost of fault-tolerant quantum computers. The goal of this work is to demonstrate that this is not true. By writing distillation circuits in a form that separates qubits that are capable of error detection from those that are not, most logical qubits used for distillation can be encoded at a very low code distance. This significantly reduces the space-time cost of distillation, as well as the number of qubits. In extreme cases, it can cost less to distill a magic state than to perform a logical Clifford gate on full-distance logical qubits.

Subfields: Artificial Intelligence, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/b02a6dabb736337bf97bda656f40019e769e935a

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Citations in the corpus

Magic state cultivation: growing T states as cheap as CNOT gates (2024, methodology): “The main inefficiency of magic state distillation is the fact that it’s performed with logical operations [Fow+12; GF19a; Lit19].”
The future of quantum computing with superconducting qubits (2022, background): “…proposed recently for reducing this overhead, including high-yield magic state distillation methods 62,63 , better strategies for preparing “raw” noisy magic states that reduce the required number of distillation rounds 64 , and better surface code implementations of distillation circuits 65–68 .”
How to factor 2048 bit RSA integers in 8 hours using 20 million noisy qubits (2019, background): “In fact, in the week before we ﬁrst released this paper, Daniel Litinsky made [65] available.”
Quantum error mitigation (2022, methodology): “The magic state distillation process needed for implementing fault-tolerant T gates accounts for significant costs in fault-tolerant computation even with recent advances (Litinski, 2019; O’Gorman and Campbell, 2017).”