def setUp(self):
self.subsys = [2, 2, 2]
self.gmn = gmn([2, 2, 2])
rho = numpy.zeros((8, 8), dtype=numpy.complex128)
rho[0, 0] = rho[0, -1] = rho[-1, 0] = rho[-1, -1] = 0.5
self.ghz = rho
psi = numpy.zeros((8,), dtype=numpy.complex128)
psi[1] = psi[2] = psi[4] = 1.0
self.w = numpy.outer(psi, psi) / 3.0
self.pauli = pauli(3)
measurements = [self.pauli.operator(i) for i in ["xxz", "xzx", "zxx", "zzz"]]
self.measurements = [(o, numpy.trace(numpy.dot(self.w, o).real)) for o in measurements]
# that can be achieved using NMIN/NMIN_PPT measurements.
# The difference between (NMIN, BOUND) and (NMIN, BOUNT_PPT) is that in the first
# fully decomposable witnesses are constructed, wheras in the second one fully
# PPT witnesses are used.
import gmntools, numpy
from gmntools import gmn, randomstates, randomlocalmeas
# number of runs
n = 100
subsystems = [2, 2]
# initialize necesarry classes
locmeas = randomlocalmeas(subsystems)
rho = randomstates(subsystems)
GMN = gmn(subsystems)
dim = numpy.prod(numpy.array(subsystems))
for i in range(n):
GMN.setdensitymatrix(rho.random())
genneg = rho.negativity([0])
if genneg > 0:
meas = []
for j in range(dim ** 2):
expvalue = numpy.trace(numpy.dot(rho.matrix, locmeas.random())).real
meas += [(locmeas.matrix, expvalue)]
xlow = 0
xhigh = dim ** 2
while True:
x = (xhigh + xlow) / 2
y = GMN.gmn_partial_info(meas[:x])
