breaking changes to the probability conventions in UnbiasedUncorrelat…

…edNoise
QuantumSavory · Mar 19, 2024 · 5c73f40 · 5c73f40
1 parent 0f9c370
commit 5c73f40
Show file tree

Hide file tree

Showing 11 changed files with 5,403 additions and 4,286 deletions.
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -2,10 +2,18 @@
 
 - `permute` will be a wrapper around to `QuantumInterface.permutesubsystems`. Documentation for `permute!` would be similarly updated
 - reworking the rest of `NoisyCircuits` and moving it out of `Experimental`
-- `random_pauli(...; realphase=true)` should be the default
 
 # News
 
+## v0.9.0 - 2024-03-19
+
+- **(breaking)** The defaults in `random_pauli` are now `realphase=true` and `nophase=true`.
+- **(breaking)** The convention for for flip probability in `random_pauli`.
+- **(breaking)** The convention for noise probability in `UnbiasedUncorrelatedNoise` changed. The input number is the total probability for an error to occur.
+- Implement an inplace `random_pauli!`, a non-allocating alternative to `random_pauli`.
+- Significant improvement in the performance of the ECC decoder pipeline (but many low-hanging fruits still remain).
+
+
 ## v0.8.21 - 2024-03-17
 
 - Implemented the Gottesman code family, also known as [[2^j, 2^j - j - 2, 3]] quantum Hamming codes.

diff --git a/Project.toml b/Project.toml
@@ -1,7 +1,7 @@
 name = "QuantumClifford"
 uuid = "0525e862-1e90-11e9-3e4d-1b39d7109de1"
 authors = ["Stefan Krastanov <stefan@krastanov.org>"]
-version = "0.8.21"
+version = "0.9.0"
 
 [deps]
 Combinatorics = "861a8166-3701-5b0c-9a16-15d98fcdc6aa"

diff --git a/docs/src/notebooks/Noisy_Circuits_Tutorial_with_Purification_Circuits.ipynb b/docs/src/notebooks/Noisy_Circuits_Tutorial_with_Purification_Circuits.ipynb
diff --git a/docs/src/notebooks/Perturbative_Expansions_vs_Monte_Carlo_Simulations.ipynb b/docs/src/notebooks/Perturbative_Expansions_vs_Monte_Carlo_Simulations.ipynb
diff --git a/docs/src/notebooks/Stabilizer_Codes_Based_on_Random_Circuits.ipynb b/docs/src/notebooks/Stabilizer_Codes_Based_on_Random_Circuits.ipynb
diff --git a/docs/src/notebooks/Symbolic_Perturbative_Expansions.ipynb b/docs/src/notebooks/Symbolic_Perturbative_Expansions.ipynb
diff --git a/ext/QuantumCliffordGPUExt/apply_noise.jl b/ext/QuantumCliffordGPUExt/apply_noise.jl
@@ -3,7 +3,7 @@ using QuantumClifford: _div, _mod
 #according to https://github.com/JuliaGPU/CUDA.jl/blob/ac1bc29a118e7be56d9edb084a4dea4224c1d707/test/core/device/random.jl#L33
 #CUDA.jl supports calling rand() inside kernel
 function applynoise!(frame::PauliFrameGPU{T},noise::UnbiasedUncorrelatedNoise,i::Int) where {T <: Unsigned}
-    p = noise.errprobthird
+    p = noise.p
     lowbit = T(1)
     ibig = _div(T,i-1)+1
     ismall = _mod(T,i-1)
@@ -22,14 +22,15 @@ function applynoise_kernel(xzs::DeviceMatrix{Tme},
     p::Real,
     ibig::Int,
     ismallm::Tme,
-    rows::Int) where {Tme <: Unsigned} 
+    rows::Int) where {Tme <: Unsigned}
 
     f = (blockIdx().x - 1) * blockDim().x + threadIdx().x;
     if f > rows
         return nothing
     end
 
     r = rand()
+    p = p/3
     if  r < p # X error
         xzs[ibig,f] ⊻= ismallm
     elseif r < 2p # Z error

diff --git a/src/noise.jl b/src/noise.jl
@@ -22,23 +22,24 @@ function applynoise!(r::Register, n, indices::Base.AbstractVecOrTuple)
     return r
 end
 
-"""Depolarization noise model with total probability of error `3*errprobthird`."""
+"""Depolarization noise model with total probability of error `p`."""
 struct UnbiasedUncorrelatedNoise{T} <: AbstractNoise
-    errprobthird::T
+    p::T
 end
+UnbiasedUncorrelatedNoise(p::Integer) = UnbiasedUncorrelatedNoise(float(p))
 
 """A convenient constructor for various types of Pauli noise models.
 Returns more specific types when necessary."""
 function PauliNoise end
 
 """Constructs an unbiased Pauli noise model with total probability of error `p`."""
 function PauliNoise(p)
-    UnbiasedUncorrelatedNoise(p/3)
+    UnbiasedUncorrelatedNoise(p)
 end
 
 function applynoise!(s::AbstractStabilizer,noise::UnbiasedUncorrelatedNoise,i::Int)
     n = nqubits(s)
-    infid = noise.errprobthird
+    infid = noise.p/3
     r = rand()
     if r<infid
         apply_single_x!(s,i)
@@ -121,11 +122,11 @@ end
 function applynoise_branches(s::AbstractStabilizer,noise::UnbiasedUncorrelatedNoise,indices; max_order=1)
     n = nqubits(s)
     l = length(indices)
-    infid = noise.errprobthird
+    infid = noise.p/3
     if l==0
         return [s,one(infid)]
     end
-    error1 = 3*infid
+    error1 = noise.p
     no_error1 = 1-error1
     no_error = no_error1^l
     results = [(copy(s),no_error,0)] # state, prob, order

diff --git a/src/pauli_frames.jl b/src/pauli_frames.jl
@@ -120,13 +120,14 @@ function apply!(frame::PauliFrame, op::sMRZ) # TODO sMRY, and faster sMRX
 end
 
 function applynoise!(frame::PauliFrame,noise::UnbiasedUncorrelatedNoise,i::Int)
-    p = noise.errprobthird
+    p = noise.p
     T = eltype(frame.frame.tab.xzs)
 
     lowbit = T(1)
     ibig = _div(T,i-1)+1
     ismall = _mod(T,i-1)
     ismallm = lowbit<<(ismall)
+    p = p/3
 
     @inbounds @simd for f in eachindex(frame)
         r = rand()

diff --git a/test/test_gpu.jl b/test/test_gpu.jl
@@ -142,6 +142,6 @@ end
         ]).measurements
         avg_result = to_cpu(sum(measurements, dims=1) / trajectories)
         error_threshold = 0.02
-        approx(vec(avg_result), [0, .5, 2p, .5], error_threshold)
+        approx(vec(avg_result), [0, .5, 2p/3, .5], error_threshold)
     end
 end
diff --git a/test/test_noisycircuits.jl b/test/test_noisycircuits.jl
@@ -1,4 +1,5 @@
 # TODO split in separate files
+using Test
 using Random
 using QuantumClifford
 
@@ -12,7 +13,7 @@ import AbstractAlgebra
     g2 = SparseGate(tCNOT, [2,3])
     g3 = sCNOT(4,5)
     g4 = sHadamard(6)
-    n = UnbiasedUncorrelatedNoise(1/3)
+    n = UnbiasedUncorrelatedNoise(1)
     ng1 = NoisyGate(g1, n)
     ng2 = NoisyGate(g2, n)
     ng3 = NoisyGate(g3, n)
@@ -33,7 +34,7 @@ end
                         ZZ"
     canonicalize_rref!(good_bell_state)
     v = VerifyOp(good_bell_state,[1,2])
-    n = NoiseOpAll(UnbiasedUncorrelatedNoise(0.01))
+    n = NoiseOpAll(UnbiasedUncorrelatedNoise(0.03))
     init = Register(MixedDestabilizer(good_bell_state⊗good_bell_state))
     with_purification = mctrajectories(init, [n,g1,g2,m,v], trajectories=500)
     @test with_purification[failure_stat] > 5
@@ -61,7 +62,7 @@ end
                             ZZ"
         canonicalize_rref!(good_bell_state)
         v = VerifyOp(good_bell_state,[1,2])
-        n = NoiseOpAll(UnbiasedUncorrelatedNoise(0.01))
+        n = NoiseOpAll(UnbiasedUncorrelatedNoise(0.03))
         init = Register(MixedDestabilizer(good_bell_state⊗good_bell_state))
         mc = mctrajectories(init, [n,g1,g2,m,v], trajectories=500)
         pe = petrajectories(init, [n,g1,g2,m,v])
@@ -88,8 +89,8 @@ end
         g2 = SparseGate(tCNOT, [2,4]) # CNOT between qubit 2 and qubit 4 (both with Bob)
         m = BellMeasurement([sMX(3),sMX(4)]) # Bell measurement on qubit 3 and 4
         v = VerifyOp(good_bell_state,[1,2]) # Verify that qubit 1 and 2 indeed form a good Bell pair
-        epsilon = e # The error rate
-        n = NoiseOpAll(UnbiasedUncorrelatedNoise(epsilon))
+        epsilon = e # The X or Y or Z error rate
+        n = NoiseOpAll(UnbiasedUncorrelatedNoise(3epsilon))
         circuit = [n,g1,g2,m,v]
         pe_symbolic = petrajectories(initial_state, circuit, branch_weight=unity) # perturbative expansion
         @test pe_symbolic[false_success_stat] == -162.0*e^4 + 162.0*e^3 + -54.0*e^2 + 6.0*e