QecsimAdaptors module

Adaptors for using tensor-network codes within the Qecsim framework.

Code, QecsimTNCode, and decoder, QecsimTNDecoder, implementations are provided to be used with Qecsim error models for QEC simulations using the Qecsim App module.

QecsimTNCode <: Qecsim.StabilizerCode

QecsimTNCode(code::TensorNetworkCode; distance=missing, label=nothing)

Qecsim stabilizer code implementation based on a tensor-network code.

Pauli operators such as stabilizers and logicals are converted to Qecsim's format on construction. These are available via Qecsim API methods of the same name. The Qecsim nkd method returns calculated values for n (number of physical qubits) and k (number of logical qubits) and the given distance for d, if provided, otherwise missing. The Qecsim label method returns the given label, if provided, otherwise the label is constructed from [n,k,d].

Public fields:

tn_code::TensorNetworkCode  # the given tensor-network code

Examples

julia> using TensorNetworkCodes.QecsimAdaptors

julia> using Qecsim: label, nkd, validate

julia> tn_code = TensorNetworkCode(five_qubit_code());

julia> qs_code = QecsimTNCode(tn_code; distance=3);

julia> label(qs_code)
"QecsimTNCode: [5,1,3]"

julia> nkd(qs_code)
(5, 1, 3)

julia> validate(qs_code)  # no error indicates success

QecsimTNDecoder <: Decoder

QecsimTNDecoder(chi::Union{Nothing,Integer}=nothing)

Qesim decoder implementation based on the TNDecode module. A null value of chi corresponds to exact contraction, otherwise chi defines the bond dimension used in MPS/MPO contraction.

An ArgumentError is thrown if chi is not null or positive. The Qecsim label method returns a label constructed from chi. The Qecsim decode method expects the keyword argument p for error probability, which defaults to 0.1, and returns a DecodeResult object with custom_values containing the success probability. The success probability is defined as the ratio of the probability of the mostly-likely logical coset to the sum of the probabilities of all logical cosets, for example:

DecodeResult.custom_values = [[0.92]] # e.g. where 0.92 is the success probability

The success probability is added to custom_values as a vector so that as Qecsim App.qec_run aggregates success probabilities over many runs it extends the vector rather than simply summing over values.

Examples

julia> using TensorNetworkCodes.QecsimAdaptors

julia> using Qecsim, Qecsim.GenericModels

julia> using Random:MersenneTwister  # use RNG for reproducible example

julia> code = QecsimTNCode(rotated_surface_code(3); distance=3);

julia> error_model = DepolarizingErrorModel();

julia> decoder = QecsimTNDecoder(4);

julia> label(decoder)
"QecsimTNDecoder (chi=4)"

julia> result = qec_run_once(code, error_model, decoder, 0.1, MersenneTwister(11))
RunResult{Vector{Vector{Float64}}}(true, 1, Bool[0, 0], [[0.9249813981321253]])

julia> success_flag = result.success
true

julia> success_probability = result.custom_values[1][1]
0.9249813981321253