def run3Drandom(size=4,tSteps=5,p=0.05,pLie=0.01,timespace=[1,1]):
L=toric_lattice.PlanarLattice(size)
PL=toric_lattice.Lattice3D(size)
for i in range(tSteps): # loop over time
L.applyRandomErrors(p,p)
L.measurePlaquettes(pLie)
L.measureStars(pLie)
PL.addMeasurement(L) # add the updated 2D lattice to 3D array
L.measurePlaquettes(0) # measure one more layer with
L.measureStars(0) # perfect stabilizers and add
PL.addMeasurement(L) # this to the parity Lattice
PL.findAnyons()
matchingX=perfect_matching.match_toric_3D(size,PL.anyon_positions_P,timespace)
matchingZ=perfect_matching.match_toric_3D(size,PL.anyon_positions_S,timespace)
flipsX=squashMatching(size,matchingX)
flipsZ=squashMatching(size,matchingZ)
L.apply_flip_array("Z",flipsZ)
L.apply_flip_array("X",flipsX)
# uncomment to display the final error state of the array
# L.showArrayText("errors","X")
return L.measure_logical()
def run2D(size=4, p=0.1):
L = toric_lattice.PlanarLattice(size)
L.applyRandomErrors(p, p)
L.measureStars()
L.measurePlaquettes()
#L.showArray("errors","Z")
#L.showArray("stabilizers","X")
L.findAnyons()
#print L.positions_anyons_P
matchingX = perfect_matching.match_toric_2D(size, L.positions_anyons_P)
matchingZ = perfect_matching.match_toric_2D(size, L.positions_anyons_S)
#print matching
L.apply_matching("X", matchingX)
L.apply_matching("Z", matchingZ)
#L.showArray("errors","Z")
#L.showArray("errors","Z")
return L.measure_logical()
def run3D(size=4,tSteps=5,errorVec=testvec4,timespace=[1,1],stabilizersNotComplete=0):
L=toric_lattice.PlanarLattice(size)
PL=toric_lattice.Lattice3D(size)
xcount = 0
zcount = 0
for i in range(tSteps): # loop over time
L.measureNoisyStabilizers("plaquette",errorVec,stabilizersNotComplete)
L.measureNoisyStabilizers("star",errorVec,stabilizersNotComplete)
PL.addMeasurement(L) # add the updated 2D lattice to 3D array
L.measurePlaquettes(0) # measure one more layer with
L.measureStars(0) # perfect stabilizers and add
PL.addMeasurement(L) # this to the parity Lattice
PL.findAnyons()
matchingX=perfect_matching.match_toric_3D(size,PL.anyon_positions_P,timespace)
matchingZ=perfect_matching.match_toric_3D(size,PL.anyon_positions_S,timespace)
flipsX=squashMatching(size,matchingX)
flipsZ=squashMatching(size,matchingZ)
L.apply_flip_array("Z",flipsZ)
L.apply_flip_array("X",flipsX)
return L.measure_logical()
def run2D(size=4,p=0.1):
L=toric_lattice.PlanarLattice(size)
L.applyRandomErrors(p,p)
L.measureStars()
L.measurePlaquettes()
#Uncomment display function for debugging
#L.showArrayText("errors","Z")
L.findAnyons()
matchingX=perfect_matching.match_toric_2D(size,L.positions_anyons_P)
matchingZ=perfect_matching.match_toric_2D(size,L.positions_anyons_S)
L.apply_matching("X",matchingX)
L.apply_matching("Z",matchingZ)
return L.measure_logical()
def run3Dtest(size=8, tSteps=100, errorVec=testvec4, timespace=[1, 1]):
errvec_file = "error_vectors/basic_0.txt"
error_vector3, error_vector4 = [[] if x == {} else x[0.0]
for x in load_errors.load(errvec_file)]
errorVec = error_vector4
# print error_vector3
# print error_vector4
L = toric_lattice.PlanarLattice(size)
PL = toric_lattice.Lattice3D(size)
L.applyRandomErrors(0, 0) # leave this here for initialisation
xcount = 0
zcount = 0
#t0=time.time()
for i in range(tSteps): # loop over time
L.measureNoisyStabilizers("plaquette", errorVec)
L.measureNoisyStabilizers("star", errorVec)
#for p0,p1 in L.positions_Q:
# x,z = L.array[p0][p1]
# if x ==-1: xcount +=1
# if z ==-1: zcount +=1
PL.addMeasurement(L) # add the updated 2D lattice to 3D array
# print xcount, zcount
# t1 = time.time()
# print 'tsteps completed ',t1-t0
L.measurePlaquettes(0) # measure one more layer with
L.measureStars(0) # perfect stabilizers and add
PL.addMeasurement(L) # this to the parity Lattice
PL.findAnyons()
# print 'P anyons', sum([len(_) for _ in PL.anyon_positions_P])
# print 'S anyons', sum([len(_) for _ in PL.anyon_positions_S])
#print PL.anyon_positions_P
# t2 = time.time()
#print 'find anyons ',t2-t1
matchingX = perfect_matching.match_toric_3D(size, PL.anyon_positions_P,
timespace)
# t3 = time.time()
#print 'matching X ',t3-t2
matchingZ = perfect_matching.match_toric_3D(size, PL.anyon_positions_S,
timespace)
flipsX = squashMatching(size, matchingX)
flipsZ = squashMatching(size, matchingZ)
# t4 = time.time()
# print 'squash matching ',t4-t3
# L.showArray("errors","X")
L.apply_flip_array("Z", flipsZ)
L.apply_flip_array("X", flipsX)
# L.showArray("errors","X")
#L.showArray("errors","Z")
return L.measure_logical()