High-Fidelity Magic-State Preparation with a Biased-Noise Architecture
- URL: http://arxiv.org/abs/2109.02677v1
- Date: Mon, 6 Sep 2021 18:02:01 GMT
- Title: High-Fidelity Magic-State Preparation with a Biased-Noise Architecture
- Authors: Shraddha Singh, Andrew S. Darmawan, Benjamin J. Brown, and Shruti Puri
- Abstract summary: Magic state distillation is a resource intensive subroutine that consumes noisy input states to produce high-fidelity resource states.
We propose an error-detecting code which detects the dominant errors that occur during state preparation.
Our approach promises considerable savings in overheads with near-term technology.
- Score: 2.624902795082451
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Magic state distillation is a resource intensive subroutine that consumes
noisy input states to produce high-fidelity resource states that are used to
perform logical operations in practical quantum-computing architectures. The
resource cost of magic state distillation can be reduced by improving the
fidelity of the raw input states. To this end, we propose an initialization
protocol that offers a quadratic improvement in the error rate of the input
magic states in architectures with biased noise. This is achieved by preparing
an error-detecting code which detects the dominant errors that occur during
state preparation. We obtain this advantage by exploiting the native gate
operations of an underlying qubit architecture that experiences biases in its
noise profile. We perform simulations to analyze the performance of our
protocol with the XZZX surface code. Even at modest physical parameters with a
two-qubit gate error rate of $0.7\%$ and total probability of dominant errors
in the gate $O(10^3)$ larger compared to that of non-dominant errors, we find
that our preparation scheme delivers magic states with logical error rate
$O(10^{-8})$ after a single round of the standard 15-to-1 distillation
protocol; two orders of magnitude lower than using conventional state
preparation. Our approach therefore promises considerable savings in overheads
with near-term technology.
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