 CoCalc Public Filessupport / 2014-12-12 qutip.sagews
Description: Jupyter notebook support/2015-06-04-141749-bokeh.ipynb

## Some of Introduction to QuTiP...

from qutip import *
RealNumber = float; Integer = int

q = Qobj([, ])
q

Quantum object: dims = [, ], shape = [2, 1], type = ket Qobj data = [[ 1.] [ 0.]]
# the dimension, or composite Hilbert state space structure
q.dims

[, ]
# the shape of the matrix data representation
q.shape

[2, 1]
# the matrix data itself. in sparse matrix format.
q.data

<2x1 sparse matrix of type '<type 'numpy.complex128'>' with 1 stored elements in Compressed Sparse Row format>
# get the dense matrix representation
q.full()

array([[ 1.+0.j], [ 0.+0.j]])
# some additional properties
q.isherm, q.type

(False, 'ket')
sy = Qobj([[0,-1j], [1j,0]])  # the sigma-y Pauli operator

sy

Quantum object: dims = [, ], shape = [2, 2], type = oper, isherm = True Qobj data = [[ 0.+0.j 0.-1.j] [ 0.+1.j 0.+0.j]]
sz = Qobj([[1,0], [0,-1]]) # the sigma-z Pauli operator

sz

Quantum object: dims = [, ], shape = [2, 2], type = oper, isherm = True Qobj data = [[ 1. 0.] [ 0. -1.]]
# some arithmetic with quantum objects

H = 1.0 * sz + 0.1 * sy

print("Qubit Hamiltonian = \n")
H

Qubit Hamiltonian = Quantum object: dims = [, ], shape = [2, 2], type = oper, isherm = True Qobj data = [[ 1.+0.j 0.-0.1j] [ 0.+0.1j -1.+0.j ]]
# The hermitian conjugate
sy.dag()

Quantum object: dims = [, ], shape = [2, 2], type = oper, isherm = True Qobj data = [[ 0.+0.j 0.-1.j] [ 0.+1.j 0.+0.j]]
# The trace
H.tr()

0.0
# Eigen energies
H.eigenenergies()

array([-1.00498756, 1.00498756])