Surface code error correction in a modular quantum computer
ORAL
Abstract
We consider error correction in a quantum computer formed by planar
modules connected along the edges, assuming that error probability for
two-qubit gates across the boundary be larger than that for
intra-modular gates. First, we prove a general structure theorem for
modular stabilizer codes: the total number of logical qubits supported
by individual modules after separation cannot exceed the dimension $k$
of the original code. Second, we use a statistical-mechanical map to
get semi-analytical estimates for the maximum-likelihood
error-correction threshold as a function of the module size $L$.
Namely, with ideal measurements, one gets a planar modulated
random-bond Ising model (MRBIM), and otherwise, assuming
phenomenological error model and repeated measurements, a
cubic-lattice MRBIM. We construct the corresponding phase diagrams
approximately using the mean-field effective couplings between block
spins, and exactly in 2D using the loop-counting technique. Finally,
we also locate the threshold using circuit simulations and
minimum-weight perfect matching decoder.
modules connected along the edges, assuming that error probability for
two-qubit gates across the boundary be larger than that for
intra-modular gates. First, we prove a general structure theorem for
modular stabilizer codes: the total number of logical qubits supported
by individual modules after separation cannot exceed the dimension $k$
of the original code. Second, we use a statistical-mechanical map to
get semi-analytical estimates for the maximum-likelihood
error-correction threshold as a function of the module size $L$.
Namely, with ideal measurements, one gets a planar modulated
random-bond Ising model (MRBIM), and otherwise, assuming
phenomenological error model and repeated measurements, a
cubic-lattice MRBIM. We construct the corresponding phase diagrams
approximately using the mean-field effective couplings between block
spins, and exactly in 2D using the loop-counting technique. Finally,
we also locate the threshold using circuit simulations and
minimum-weight perfect matching decoder.
–
Presenters
-
Denis Sedov
ITMO University
Authors
-
Denis Sedov
ITMO University
-
Renyu Wang
University of California, Riverside
-
Leonid P Pryadko
University of California, Riverside