Codes for Quantum Computing Tutorial

Note: If you choose to download anything from this tutorial, it is at your own risk.  You are free to read the codes if you do not want to download or use the IBM platform. 

# (indents need to be converted to tabs if you cut and paste)
# (Check the " or ' come out in the Python format)

#Code 1

conda create --name  QCTutorial
conda activate QCTutorial

conda install ipykernel
python -m ipykernel install --user --name QCTutorial --display-name "QCTutorial"
conda install jupyter
conda install numpy
conda install scipy
jupyter notebook

#Code 2

#Explicit Euler Simulation:

import numpy as np
psi1 = np.array([1, 0, 0, 0])

Hp = np.array([[2,0,0,0], [0,3,0,0],[0,0,5,0],[0,0,0,10]]) 
Hd = np.array([[3,0,0,0], [0,1,0,0],[0,0,2,0],[0,0,0,6]]) 
beta = 1.5 
hbar = 1.054571817e-34 
timeOp = 10e-10 
sizeStep = 1e-10 
numSteps = int(np.floor(timeOp/sizeStep +0.5)) 
timeMatrix = np.empty(numSteps + 1) 
stateVecMatrix = np.empty((numSteps + 1,4),dtype=complex)


time = 0 
timeMatrix[0] = time 
stateVecMatrix[0] = psi1 
for i in range(numSteps):             
     psi1 = psi1 + sizeStep*(-1j/hbar*Hp@psi1 - 1j/hbar*beta*Hd@psi1)     
     stateVecMatrix[i+1] = psi1     
     time = time+sizeStep     
     timeMatrix[i+1] = time

print(psi1)


#Code 3

#Quantum State Simulation Using Matrix Exponentials from [1, 0, 0, 0]:

import numpy as np
from scipy.linalg import expm 
psi1 = np.array([1, 0, 0, 0]) 

Hp = np.array([[2,0,0,0], [0,3,0,0],[0,0,5,0],[0,0,0,10]]) 

Hd = np.array([[3,0,0,0], [0,1,0,0],[0,0,2,0],[0,0,0,6]]) 

beta = 1.5 

hbar = 1.054571817e-34 

timeOp = 10e-10 

sizeStep = 1e-10 

HCombo = -1j/hbar*(Hp + beta*Hd) 

statev = expm(HCombo*timeOp)@psi1 

print(statev)


#Code 4
#Quantum State Simulation Using Matrix Exponentials from an Equal Superposition State and With Measurements Added:

import numpy as np
from scipy.linalg import expm 
psi1 = np.array([0.5, 0.5, 0.5, 0.5]) 

Hp = np.array([[2,0,0,0], [0,3,0,0],[0,0,5,0],[0,0,0,10]]) 

Hd = np.array([[3,0,0,0], [0,1,0,0],[0,0,2,0],[0,0,0,6]]) 

beta = 1.5 

hbar = 1.054571817e-34 

timeOp = 10e-10 

sizeStep = 1e-10 

HCombo = -1j/hbar*(Hp + beta*Hd) 

statev = expm(HCombo*timeOp)@psi1 

print(statev)

probBfSquare = np.abs(statev) 
print(probBfSquare)
probs = probBfSquare**2

print(probs)

items = ['00','01','10','11']
measurement = np.random.choice(items, p=probs)
print(measurement)


#Code 5
#State Vector Simulation of a Hadamard Applied to a Qubit in the |0> State:

H = 1/np.sqrt(2)*np.array([[1, 1],[1,-1]])

print(H)

qubitState = np.array([1,0])

qubitSuperpos = H@qubitState

print(qubitSuperpos)

#Code 6
#Some Extra Conda Stuff to Get Ready to Run Qiskit:

conda install qiskit 
conda install matplotlib 
conda install qiskit-ibm-runtime 
conda install pylatexenc 
conda install qiskit-aer



#Code 7
#Example of a Hadamard Gate Applied to 1 Qubit and Measured, Using IBM's Aer Simulator (Note: A Simulator is Not a Quantum Computer):

from qiskit import QuantumCircuit 
from qiskit_aer import AerSimulator
qc = QuantumCircuit(1,1)
  qc.h(0) 
qc.measure(0,0)

sim=AerSimulator() 
result=sim.run(qc,shots=1000).result()
print(result.get_counts()) 
qc.draw('mpl')



#Code 8
#One-Time Set-Up to Use QPUs on IBM Quantum Platform with a Given API Token (check all '' are in the right way in Python and also you will need to replace the places "copy and past your API key or token" and "type your instance name"):

from qiskit_ibm_runtime import QiskitRuntimeService 

QiskitRuntimeService.save_account(channel="ibm_quantum_platform",token=“copy and paste your API key or token",instance=“type your instance name")



#Code 9
#Running the Hadamard Gate and Measure Example on QPUs (After the API Token is Set Up - also you need to replace "PUT YOUR JOB HERE"):

from qiskit import QuantumCircuit, transpile 
from qiskit_ibm_runtime import QiskitRuntimeService, SamplerV2 
qc = QuantumCircuit(1,1) 
qc.h(0) 
qc.measure(0,0) 
qc.draw(output='mpl')


service = QiskitRuntimeService() 
qpus = service.backends(simulator=False, operational=True) 
print(qpus) 
back_lb = service.least_busy(operational=True) 
back_lb.num_qubits 
sampler_lb = SamplerV2(back_lb)

qc_lb_t=transpile(qc,backend=back_lb) 
qc_lb_t.draw(output='mpl',idle_wires=False) 
no_shots = 1024 
lb_job=sampler_lb.run([(qc_lb_t,None,no_shots)]) 
retrieve=QiskitRuntimeService().job('PUT YOUR JOB HERE’) 
result = retrieve.result() 
pub_result = result[0] 
counts = pub_result.data.c.get_counts() 
print(counts)



#Code 10
#2 X's and 2 CNOT's on the Aer Simulator:

from qiskit import QuantumCircuit 
from qiskit_aer import AerSimulator 
qc = QuantumCircuit(3) 
qc.x(0) 
qc.x(1) 
qc.cx(1,2) 
qc.cx(0,1) 
qc.measure_all()

sim=AerSimulator() 
result=sim.run(qc,shots=1000).result() 
print(result.get_counts()) 
qc.draw('mpl')


#Code 11
#2 X's and 2 CNOT's on a QPU (replace "PUT YOUR JOB HERE" and be sure your '' is right in Python):


from qiskit import QuantumCircuit, transpile 
from qiskit_ibm_runtime import QiskitRuntimeService, SamplerV2

qc = QuantumCircuit(3) 
qc.x(0) 
qc.x(1) 
qc.cx(1,2) 
qc.cx(0,1) 
qc.measure_all()

service = QiskitRuntimeService() 
qpus = service.backends(simulator=False, operational=True) 
print(qpus) 
back_lb = service.least_busy(operational=True) 
back_lb.num_qubits 
sampler_lb = SamplerV2(back_lb)

qc_lb_t=transpile(qc,backend=back_lb) 
qc_lb_t.draw(output='mpl',idle_wires=False) 
no_shots = 1024 
lb_job=sampler_lb.run([(qc_lb_t,None,no_shots)]) 
retrieve=QiskitRuntimeService().job('PUT YOUR JOB HERE’) 
result = retrieve.result() 
pub_result = result[0] 
counts = pub_result.data.meas.get_counts() 
print(counts)



#Code 12
#Grover's Algorithm Simulation with Matrices as Operators (Not Gates) Using numpy:

import numpy as np 
H = np.array([[1/np.sqrt(2),1/np.sqrt(2)],[1/np.sqrt(2),-1/np.sqrt(2)]]) 
HOTimes = np.kron(H,np.kron(H,H)) 
initState = np.array([1,0,0,0,0,0,0,0]) 
psi1 = HOTimes@initState 
print(psi1) 



Up = np.array([[1,0,0,0,0,0,0,0],[0,1,0,0,0,0,0,0],[0,0,1,0,0,0,0,0],[0,0,0,1,0,0,0,0],[0,0,0,0,-1,0,0,0],[0,0,0,0,0,1,0,0],[0,0,0,0,0,0,1,0],[0,0,0,0,0,0,0,1]]) 
print(Up) 
psi2 = Up@psi1 
print(psi2)


Us=np.array([[-1+2/8,2/8,2/8,2/8,2/8,2/8,2/8,2/8],
[2/8,-1+2/8,2/8,2/8,2/8,2/8,2/8,2/8],
[2/8,2/8,-1+2/8,2/8,2/8,2/8,2/8,2/8],
[2/8,2/8,2/8,-1+2/8,2/8,2/8,2/8,2/8],
[2/8,2/8,2/8,2/8,-1+2/8,2/8,2/8,2/8],
[2/8,2/8,2/8,2/8,2/8,-1+2/8,2/8,2/8], 
[2/8,2/8,2/8,2/8,2/8,2/8,-1+2/8,2/8],
[2/8,2/8,2/8,2/8,2/8,2/8,2/8,-1+2/8],
]) 
print(Us) 
psi3 = Us@psi2 
print(psi3)

psi4 = Up@psi3 
print(psi4)

psi5 = Us@psi4 
print(psi5)