The Bloch sphere provides an intuitive way to understand and visualize the state of a quantum system.
The code generates a random quantum state vector and uses a 3D plot with a Bloch sphere representation to visualize it.
- First, we import the necessary libraries, NumPy and Matplotlib, to work with numerical operations and plotting.
- We set the variable num_qubits to the desired number of qubits. This determines the dimensionality of the quantum state vector.
- The rand_ket() function generates a random quantum state vector with a specified dimension, which in this case is 2 ** num_qubits. This means the state vector will have a length of 2 for a single qubit (2 ** 1 = 2), 4 for two qubits (2 ** 2 = 4), and so on.
- Next, we create a 3D plot using matplotlib.pyplot and specify that it should have a 3D projection using the projection=’3d’ parameter.
- We create a Bloch object, which is a part of the qutip library. This object allows us to visualize quantum states on a Bloch sphere representation.
- We add the generated state to the Bloch object using the add_states() method. This visualizes the state on the Bloch sphere.
- Finally, we call the show() method on the Bloch object to display the 3D plot representing the quantum state.
- Method #1
import numpy as np import matplotlib.pyplot as plt from qutip import * # Generate a random quantum state vector num_qubits = 1 # Number of qubits state = rand_ket(2 ** num_qubits) # Visualize the state using a 3D plot fig = plt.figure() ax = fig.add_subplot(111, projection='3d') sphere = Bloch(axes=ax) sphere.add_states(state) sphere.show()
- Method #2
import numpy as np import matplotlib.pyplot as plt from qutip import * # Generate a random quantum state vector num_qubits = 1 # Number of qubits state = rand_ket(2 ** num_qubits) # Alternatively, visualize the state using a Bloch sphere representation bloch = Bloch() bloch.add_states(state) bloch.show() # Show the plots plt.show()