Blind topological measurement-based quantum computation

TLDR

Blind quantum computation lets a client with limited quantum resources delegate a computation to a server while keeping the algorithm, input, and output secret, yet recent experiments have revealed scalability challenges in noisy environments, motivating robust topological solutions. The study demonstrates that fault‑tolerant blind quantum computation can be achieved in a topologically protected manner. This is accomplished via the Raussendorf–Harrington–Goyal scheme. The scheme attains an error threshold of 4.3 × 10⁻³, comparable to the 7.5 × 10⁻³ of non‑blind topological quantum computation, indicating that secure cloud quantum computation is within reach given current experimental error rates.

Abstract

Blind quantum computation is a novel secure quantum-computing protocol that enables Alice, who does not have sufficient quantum technology at her disposal, to delegate her quantum computation to Bob, who has a fully fledged quantum computer, in such a way that Bob cannot learn anything about Alice's input, output and algorithm. A recent proof-of-principle experiment demonstrating blind quantum computation in an optical system has raised new challenges regarding the scalability of blind quantum computation in realistic noisy conditions. Here we show that fault-tolerant blind quantum computation is possible in a topologically protected manner using the Raussendorf–Harrington–Goyal scheme. The error threshold of our scheme is 4.3×10−3, which is comparable to that (7.5×10−3) of non-blind topological quantum computation. As the error per gate of the order 10−3 was already achieved in some experimental systems, our result implies that secure cloud quantum computation is within reach. Blind quantum computation is a protocol that permits an algorithm, its input and output to be kept secret from the owner of the computational resource doing the calculation. Morimae and Fujii propose a strategy for topologically protected fault-tolerant blind quantum computation that is robust to environmental noise.