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https://github.com/arthurfaria/QC_basic_agorithms_qiskit | arthurfaria | ###### Import Libraries
import numpy as np
from qiskit import Aer
from qiskit_nature.drivers import UnitsType, Molecule
from qiskit_nature.drivers.second_quantization import (
ElectronicStructureDriverType,
ElectronicStructureMoleculeDriver,
)
from qiskit_nature.problems.second_quantization import Ele... |
https://github.com/draentropia/Qiskit_PyLadiesBCN | draentropia | from qiskit import QuantumCircuit, assemble, Aer
from qiskit.visualization import plot_histogram
# create quantum circuit
qc = QuantumCircuit(1) # 1 quantum register, 1 classical register
qc.x(0) # add a gate to the circuit
qc.measure_all() # add measurement a... |
https://github.com/draentropia/Qiskit_PyLadiesBCN | draentropia | from qiskit import QuantumCircuit, assemble, Aer
from qiskit.visualization import plot_bloch_multivector
import numpy as np
# create quantum circuit
qc = QuantumCircuit(1)
qc.h(0) # add h(qubit)
# run
sim = Aer.get_backend('aer_simulator')
qc.save_statevector() ... |
https://github.com/pedroripper/qiskit_tutoriais | pedroripper | # Importando módulos
from qiskit import *
from qiskit.tools.visualization import plot_histogram
# Inicializando o circuito
nQubits = 2
nBits = 2
circuitoQuantico = QuantumCircuit(nQubits, nBits)
# Para aplicar uma porta no circuito devemos seguir o seguinte exemplo onde aplicamos uma Hadamard Gate
circu... |
https://github.com/pedroripper/qiskit_tutoriais | pedroripper | from qiskit import *
# Para representar o qubit em uma esfera de bloch devemos pensar nele na seguinte forma:
# Depois de encontrar o theta, phi que desejamos, vamos ter os valores necessários para plotar nossa
# esfera de bloch
# Para plotar precisamos chamar a função plot_bloch_vector_spherical() que leva... |
https://github.com/pedroripper/qiskit_tutoriais | pedroripper | from qiskit import *
# Primeiramente vamos iniciar um circuito
circuitoQ = QuantumCircuit(1,1)
# No qiskit os qubits são inicializados por default com o estado |0>
# Podemos ver isso plotando a esfera de bloch que representa ele
from qiskit.tools.visualization import plot_bloch_multivector
simulator = ... |
https://github.com/pedroripper/qiskit_tutoriais | pedroripper | from qiskit import *
circuito = QuantumCircuit(2,2)
circuito.draw(output = 'mpl')
from qiskit.tools.visualization import plot_bloch_multivector
simulator = Aer.get_backend('statevector_simulator')
result = execute(circuito, backend = simulator).result()
statevector = result.get_statevector()
plot_bloc... |
https://github.com/pedroripper/qiskit_tutoriais | pedroripper | from qiskit import *
# Para representar o qubit em uma esfera de bloch devemos pensar nele na seguinte forma:
# Depois de encontrar o theta, phi que desejamos, vamos ter os valores necessários para plotar nossa
# esfera de bloch
# Para plotar precisamos chamar a função plot_bloch_vector_spherical() que leva... |
https://github.com/pedroripper/qiskit_tutoriais | pedroripper | from qiskit import *
global c
c = QuantumCircuit(2,2)
def ua(bit_0 , bit_1):
global c
if(bit_0 == 1):
if(bit_1 == 0):
c.x(0)
else:
c.h(0)
ua(0,0)
c.draw()
c.reset(0)
c.reset(1)
c.draw()
def ub(numeo_bob):
2 -> comp
3 -> ... |
https://github.com/pedroripper/qiskit_tutoriais | pedroripper | from qiskit import *
%matplotlib inline
import numpy as np
qc = QuantumCircuit(2,2)
qc.rx(np.pi/2,0)
qc.z(0)
qc.draw(output='mpl')
qc2 = QuantumCircuit(2,2)
qc2.z(0)
qc2.rx(-np.pi/2,0)
qc2.draw(output='mpl')
|
https://github.com/pedroripper/qiskit_tutoriais | pedroripper | from qiskit import *
%matplotlib inline
from qiskit.tools.visualization import plot_histogram
from qiskit.visualization import plot_bloch_vector
from qiskit.visualization import plot_bloch_multivector
import math
theta = math.pi/2
phi = math.pi/2
vetor_bloch = [math.cos(phi)*math.sin(theta),math.sin(theta)*ma... |
https://github.com/pedroripper/qiskit_tutoriais | pedroripper | from qiskit import *
global x
x = QuantumCircuit(2,2)
def ua(bit_0 , bit_1):
global x
if(bit_0 == 1 and bit_1 == 0):
x.cx(0,1)
ua(0,0)
x.draw()
0 == 0
0 == 1
|
https://github.com/pedroripper/qiskit_tutoriais | pedroripper | from qiskit import *
%matplotlib inline
import numpy as np
qc = QuantumCircuit(2,2)
qc.rx(np.pi/2,0)
qc.z(0)
qc.draw(output='mpl')
qc2 = QuantumCircuit(2,2)
qc2.z(0)
qc2.rx(-np.pi/2,0)
qc2.draw(output='mpl')
|
https://github.com/pedroripper/qiskit_tutoriais | pedroripper | # Importando módulos
from qiskit import *
# Uma das formas de se inicializar um circuito quântico é usando "QuantumCircuit(x,y)"
# que é armazenado em uma variável.
# Nele, onde x é o número de qubits
# e y o número de bits clássicos.
# Usamos os bits clássicos para armazenar as medições dos qubits.
n... |
https://github.com/pedroripper/qiskit_tutoriais | pedroripper | # Importando módulos
from qiskit import *
from qiskit.tools.visualization import plot_histogram
# Inicializando o circuito
nQubits = 2
nBits = 2
circuitoQuantico = QuantumCircuit(nQubits, nBits)
# Para aplicar uma porta no circuito devemos seguir o seguinte exemplo onde aplicamos uma Hadamard Gate
circu... |
https://github.com/pedroripper/qiskit_tutoriais | pedroripper | from qiskit import *
# Para representar o qubit em uma esfera de bloch devemos pensar nele na seguinte forma:
# Depois de encontrar o theta, phi que desejamos, vamos ter os valores necessários para plotar nossa
# esfera de bloch
# Para plotar precisamos chamar a função plot_bloch_vector_spherical() que leva... |
https://github.com/pedroripper/qiskit_tutoriais | pedroripper | from qiskit import *
# Primeiramente vamos iniciar um circuito
circuitoQ = QuantumCircuit(1,1)
# No qiskit os qubits são inicializados por default com o estado |0>
# Podemos ver isso plotando a esfera de bloch que representa ele
from qiskit.tools.visualization import plot_bloch_multivector
simulator = ... |
https://github.com/pedroripper/qiskit_tutoriais | pedroripper | from qiskit import *
circuito = QuantumCircuit(2,2)
circuito.draw(output = 'mpl')
from qiskit.tools.visualization import plot_bloch_multivector
simulator = Aer.get_backend('statevector_simulator')
result = execute(circuito, backend = simulator).result()
statevector = result.get_statevector()
plot_bloc... |
https://github.com/pedroripper/qiskit_tutoriais | pedroripper | from qiskit import *
%matplotlib inline
qc1 = QuantumCircuit(1)
qc1.h(0)
qc1.draw(output = 'mpl')
qc2 = QuantumCircuit(1)
qc2.x(0)
qc2.draw(output = 'mpl')
print(qc1)
print(qc2)
qc3 = qc1 + qc2
qc3.draw(output = 'mpl')
qc1[0]
qc3.z(0)
qc3.draw(output = 'mpl')
|
https://github.com/pedroripper/qiskit_tutoriais | pedroripper | from qiskit import *
import numpy as np
circuito = QuantumCircuit(2,2)
circuito.x(0)
circuito.z(0)
circuito.h(1)
# circuito.measure([0,1],[0,1])
circuito.draw(output = 'mpl')
# Podemos encontrar a matriz unitária que representa as operacoes no circuito
backend = Aer.get_backend('unitary_simulator')
job ... |
https://github.com/pedroripper/qiskit_tutoriais | pedroripper | from qiskit import *
import numpy as np
# Podemos aplicar uma matriz unitária em um circuito
matriz = [[1,0],
[0,1]]
circuito = QuantumCircuit(1)
circuito.unitary(matriz,[0])
circuito.draw(output='mpl')
# É possivel dar nome para essas operações
circuito = QuantumCircuit(1)
circuito.unitary(... |
https://github.com/pedroripper/qiskit_tutoriais | pedroripper | from qiskit import *
%matplotlib inline
# Podemos transformar o nosso circuito em apenas uma porta
circuito = QuantumCircuit(2)
circuito.x(0)
circuito.h(1)
circuito.draw(output='mpl')
# Para conseguir uma porta que represente essas operações fazemos
# Podemos ainda adicionar um titulo para a nossa porta o... |
https://github.com/pedroripper/qiskit_tutoriais | pedroripper | from qiskit import *
%matplotlib inline
# Para facilitar a visualização dos nossos circuitos podemos usar .barrier() para criar
# "separadores" nos circuitos
# Essas barras tem uma outra função que pode ser vista no futuro, mas por enquanto podemos
# usar apenas para separar partes do circuito
qc = Quantum... |
https://github.com/pedroripper/qiskit_tutoriais | pedroripper | from qiskit import *
%matplotlib inline
import numpy as np
# Podemos encontrar o operador de densidade de estados
# Para isso vamos primeiramente usar o statevector_simulator para encontrar o vetor de
# estado desejado
qc = QuantumCircuit(1)
qc.ry(3*np.pi/2,0)
qc.draw(output='mpl')
backend = Aer.get_b... |
https://github.com/pedroripper/qiskit_tutoriais | pedroripper | from qiskit import *
%matplotlib inline
import numpy as np
qc = QuantumCircuit(2,2)
qc.h(0)
qc.cx(0,1)
qc.measure([0,1],[0,1])
qc.draw(output='mpl')
backend = Aer.get_backend('qasm_simulator')
result = execute(qc,backend).result()
from qiskit.tools.visualization import plot_histogram
plot_histogram(r... |
https://github.com/pedroripper/qiskit_tutoriais | pedroripper | from qiskit import *
%matplotlib inline
# Podemos transformar o nosso circuito em apenas uma porta
circuito = QuantumCircuit(2)
circuito.x(0)
circuito.h(1)
circuito.draw(output='mpl')
# Para conseguir uma porta que represente essas operações fazemos
# Podemos ainda adicionar um titulo para a nossa porta o... |
https://github.com/pedroripper/qiskit_tutoriais | pedroripper | from qiskit import *
%matplotlib inline
# Para facilitar a visualização dos nossos circuitos podemos usar .barrier() para criar
# "separadores" nos circuitos
# Essas barras tem uma outra função que pode ser vista no futuro, mas por enquanto podemos
# usar apenas para separar partes do circuito
qc = Quantum... |
https://github.com/pedroripper/qiskit_tutoriais | pedroripper | from qiskit import *
%matplotlib inline
import numpy as np
# Podemos encontrar o operador de densidade de estados
# Para isso vamos primeiramente usar o statevector_simulator para encontrar o vetor de
# estado desejado
qc = QuantumCircuit(1)
qc.rx(np.pi/2,0)
qc.draw(output='mpl')
backend = Aer.get_bac... |
https://github.com/pedroripper/qiskit_tutoriais | pedroripper | from qiskit import *
%matplotlib inline
import numpy as np
qc = QuantumCircuit(2,2)
qc.h(0)
qc.cx(0,1)
qc.measure([0,1],[0,1])
qc.draw(output='mpl')
backend = Aer.get_backend('qasm_simulator')
result = execute(qc,backend).result()
from qiskit.tools.visualization import plot_histogram
plot_histogram(r... |
https://github.com/Fergus-Hayes/qiskit_tools | Fergus-Hayes | from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister, execute, Aer, IBMQ
import qiskit_tools as qt
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
in_digit = np.pi
print(in_digit)
n = 20
nint = qt.get_nint(in_digit)
print(nint)
in_binary = qt.my_binary_repr(in_dig... |
https://github.com/Fergus-Hayes/qiskit_tools | Fergus-Hayes | def QFT(N):
'''
Constructing the fourier transform of size NxN.
'''
return np.array([[(np.exp(2.*i*j*1j*np.pi/N))
for j in np.arange(N)]
for i in np.arange(N)])*1./np.sqrt(N)
from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister, execute, A... |
https://github.com/Fergus-Hayes/qiskit_tools | Fergus-Hayes | from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister, execute, Aer, IBMQ
import qiskit_tools as qt
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
n = 5
xreg = QuantumRegister(n, 'x')
circ = QuantumCircuit(xreg)
circ = qt.QFT(circ, xreg)
circ.draw(output="latex")
... |
https://github.com/Fergus-Hayes/qiskit_tools | Fergus-Hayes | from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister, execute, Aer, IBMQ
import qiskit_tools as qt
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
digit_A = 5.25
digit_B = 7.5
print(digit_A,'+',digit_B,'=',digit_A+digit_B)
nint = qt.get_nint([digit_A+digit_B,digit_A,d... |
https://github.com/Fergus-Hayes/qiskit_tools | Fergus-Hayes | from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister, execute, Aer, IBMQ
import qiskit_tools as qt
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
phase = True
digit_A = 5.25
digit_B = 7.5
print(digit_A,'x',digit_B,'=',digit_A*digit_B)
nintA = qt.get_nint(digit_A)
... |
https://github.com/Fergus-Hayes/qiskit_tools | Fergus-Hayes | from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister, execute, Aer, IBMQ
import qiskit_tools as qt
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
digit = 10.25
k = 2
target = np.power(digit, k)
print(digit,'^'+str(k),'=',target)
nintx = qt.get_nint(digit)
npresx = ... |
https://github.com/Fergus-Hayes/qiskit_tools | Fergus-Hayes | from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister, execute, Aer, IBMQ
import qiskit_tools as qt
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
digit = 2
a = 1
phase = False
nint = qt.get_nint([digit,a])
npres = qt.get_npres([digit,a])
n = nint + npres
if phas... |
https://github.com/Fergus-Hayes/qiskit_tools | Fergus-Hayes | import qiskit_tools as qt
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
matplotlib.rcParams['mathtext.fontset'] = 'stix'
matplotlib.rcParams['font.family'] = 'STIXGeneral'
width=0.75
color='black'
fontsize=28
ticksize=22
figsize=(10,8)
def f_x(x):
return np.arctan(x)
phase ... |
https://github.com/Fergus-Hayes/qiskit_tools | Fergus-Hayes | from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister, execute, Aer, IBMQ
import qiskit_tools as qt
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
matplotlib.rcParams['mathtext.fontset'] = 'stix'
matplotlib.rcParams['font.family'] = 'STIXGeneral'
width=0.75
color='black'
... |
https://github.com/Fergus-Hayes/qiskit_tools | Fergus-Hayes | from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister, execute, Aer, IBMQ
import qiskit_tools as qt
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
from qiskit.circuit.library.standard_gates import RYGate
matplotlib.rcParams['mathtext.fontset'] = 'stix'
matplotlib.rcParams[... |
https://github.com/Fergus-Hayes/qiskit_tools | Fergus-Hayes | from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister, execute, Aer, IBMQ
from qiskit.circuit.library import PhaseGate
from qiskit.extensions import HamiltonianGate
from qiskit.quantum_info import random_hermitian
import qiskit_tools as qt
import numpy as np
import matplotlib.pyplot as plt
import... |
https://github.com/Fergus-Hayes/qiskit_tools | Fergus-Hayes | from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister, execute, Aer, IBMQ
from qiskit.circuit.library import ExactReciprocal
from qiskit.extensions import HamiltonianGate
from qiskit.quantum_info import random_hermitian
import qiskit_tools as qt
import numpy as np
import matplotlib.pyplot as plt
... |
https://github.com/Fergus-Hayes/qiskit_tools | Fergus-Hayes | from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister, execute, Aer, IBMQ
from qiskit.circuit.library import StatePreparation, RYGate
from qiskit.quantum_info import Statevector
import qiskit_tools as qt
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
from tqdm import tqdm
f... |
https://github.com/Fergus-Hayes/qiskit_tools | Fergus-Hayes | from qiskit.utils import algorithm_globals
from qiskit import QuantumCircuit, Aer, execute
from qiskit.circuit.library import RealAmplitudes
from qiskit.primitives import Sampler
from qiskit_machine_learning.connectors import TorchConnector
from qiskit_machine_learning.neural_networks import SamplerQNN
from torch... |
https://github.com/Fergus-Hayes/qiskit_tools | Fergus-Hayes | from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister, execute, Aer, IBMQ
from scipy.interpolate import approximate_taylor_polynomial
from qiskit.circuit.library import RGQFTMultiplier, DraperQFTAdder, ExactReciprocal
from qiskit.circuit.library.basis_change import QFT as QFT_pre
from qiskit.extensi... |
https://github.com/googlercolin/Qiskit-Course | googlercolin | import numpy as np
# Importing standard Qiskit libraries
from qiskit import QuantumCircuit, transpile, assemble, Aer, IBMQ, execute
from qiskit.quantum_info import Statevector
from qiskit.visualization import plot_bloch_multivector, plot_histogram
from qiskit_textbook.problems import dj_problem_oracle
from qi... |
https://github.com/googlercolin/Qiskit-Course | googlercolin | import numpy as np
from mitiq import cdr, Observable, PauliString, Executor
import cirq
from cirq.contrib.qasm_import import circuit_from_qasm
from cirq.circuits.qasm_output import QasmUGate
from qiskit import *
from qiskit import transpile, assemble, IBMQ
from qiskit.visualization import *
from qiskit i... |
https://github.com/googlercolin/Qiskit-Course | googlercolin | import numpy as np
# Importing standard Qiskit libraries
from qiskit import QuantumCircuit, transpile, Aer, IBMQ
from qiskit.tools.jupyter import *
from qiskit.visualization import *
from ibm_quantum_widgets import *
from qiskit.providers.aer import QasmSimulator
# Loading your IBM Quantum account(s)
provid... |
https://github.com/googlercolin/Qiskit-Course | googlercolin | import numpy as np
from qiskit.quantum_info import state_fidelity, Statevector
def getStatevector(circuit):
return Statevector(circuit).data
import warnings
warnings.filterwarnings('ignore')
def P_haar(N, F):
if F == 1:
return 0
else:
return (N - 1) * ((1 - F) ** (N - 2))
... |
https://github.com/googlercolin/Qiskit-Course | googlercolin | import numpy as np
import matplotlib.pyplot as plt
import torch
from torch.autograd import Function
from torchvision import datasets, transforms
import torch.optim as optim
import torch.nn as nn
import torch.nn.functional as F
from torchsummary import summary
import qiskit
from qiskit import transpile, ... |
https://github.com/googlercolin/Qiskit-Course | googlercolin | # !pip install -r 'requirements.txt' --quiet
import numpy as np
import torch
from torchvision.transforms import ToTensor
from torch import no_grad
from torchvision import datasets
import torch.optim as optim
from torch.nn import (Module, Conv2d, Linear, Dropout2d, NLLLoss, MaxPool2d, Flatten, Sequential, ReL... |
https://github.com/googlercolin/Qiskit-Course | googlercolin | import numpy as np
import torch
from torchvision.transforms import ToTensor
from torch import no_grad
from torchvision import datasets
import torch.optim as optim
from torch.nn import (Module, Conv2d, Linear, Dropout2d, NLLLoss, MaxPool2d, Flatten, Sequential, ReLU)
import torch.nn as nn
import torch.nn.funct... |
https://github.com/googlercolin/Qiskit-Course | googlercolin | # !pip install -r 'requirements.txt' --quiet
import numpy as np
import torch
from torchvision.transforms import ToTensor
from torch import no_grad
from torchvision import datasets
import torch.optim as optim
from torch.nn import (Module, Conv2d, Linear, Dropout2d, NLLLoss, MaxPool2d, Flatten, Sequential, ReL... |
https://github.com/googlercolin/Qiskit-Course | googlercolin | import numpy as np
import networkx as nx
import timeit
from qiskit import Aer
from qiskit.circuit.library import TwoLocal
from qiskit_optimization.applications import Maxcut
from qiskit.algorithms import VQE, NumPyMinimumEigensolver
from qiskit.algorithms.optimizers import SPSA
from qiskit.utils import algori... |
https://github.com/googlercolin/Qiskit-Course | googlercolin | !pip install mitiq --quiet
import warnings
warnings.filterwarnings(action='ignore') # Optional warning filter
from qiskit import IBMQ
IBMQ.save_account('0238b0afc0dc515fe7987b02706791d1719cb89b68befedc125eded0607e6e9e9f26d3eed482f66fdc45fdfceca3aab2edb9519d96b39e9c78040194b86e7858', overwrite=True)
import ... |
https://github.com/googlercolin/Qiskit-Course | googlercolin | import numpy as np
from sklearn.datasets.samples_generator import make_blobs
from qiskit.aqua.utils import split_dataset_to_data_and_labels
from sklearn import svm
from utility import breast_cancer_pca
from matplotlib import pyplot as plt
%matplotlib inline
%load_ext autoreload
%autoreload 2
n = 2 # number ... |
https://github.com/googlercolin/Qiskit-Course | googlercolin | import numpy as np
# Importing standard Qiskit libraries
from qiskit import QuantumCircuit, transpile, Aer, IBMQ
from qiskit.tools.jupyter import *
from qiskit.visualization import *
from ibm_quantum_widgets import *
from qiskit.providers.aer import QasmSimulator
# Loading your IBM Quantum account(s)
provid... |
https://github.com/googlercolin/Qiskit-Course | googlercolin | #!pip install PySCF --upgrade
import networkx as nx
import numpy as np
import plotly.graph_objects as go
import matplotlib as mpl
import pandas as pd
from IPython.display import clear_output
from plotly.subplots import make_subplots
from matplotlib import pyplot as plt
from qiskit import Aer, transpile, asse... |
https://github.com/googlercolin/Qiskit-Course | googlercolin | import numpy as np
from numpy import pi
# Importing standard Qiskit libraries
from qiskit import QuantumCircuit, transpile, assemble, Aer, IBMQ, execute
from qiskit.quantum_info import Statevector
from qiskit.visualization import plot_bloch_multivector, plot_histogram
from qiskit_textbook.problems import dj_pro... |
https://github.com/googlercolin/Qiskit-Course | googlercolin | import numpy as np
from qiskit.opflow import I, X, Y, Z, MatrixEvolution, PauliTrotterEvolution
from qiskit.circuit import Parameter
from qiskit import QuantumCircuit
from qiskit import Aer
from qiskit.compiler import transpile
import qc_grader
# Define which will contain the Paulis
pauli_list = []
# D... |
https://github.com/googlercolin/Qiskit-Course | googlercolin | import numpy as np
import qiskit
from qiskit.circuit.library import RXGate
from qiskit.providers.aer.noise import NoiseModel, ReadoutError, depolarizing_error, coherent_unitary_error
from scipy.stats import norm
from scipy.optimize import curve_fit
import matplotlib.pylab as plt
import qc_grader
# Create ... |
https://github.com/googlercolin/Qiskit-Course | googlercolin | import numpy as np
import matplotlib.pyplot as plt
plt.rcParams.update({'font.size': 16}) # enlarge matplotlib fonts
# Import qubit states Zero (|0>) and One (|1>), Pauli operators (X, Y, Z), and the identity operator (I)
from qiskit.opflow import Zero, One, X, Y, Z, I
# Returns the XXX Heisenberg model for 3... |
https://github.com/greatdevaks/geopython-qiskit | greatdevaks | import numpy as np
# Importing standard Qiskit libraries
from qiskit import QuantumCircuit, transpile, assemble, Aer, IBMQ
from qiskit.tools.jupyter import *
from qiskit.visualization import *
from ibm_quantum_widgets import *
# Importing basic math libraries
from math import pi, sqrt
# Loading your IBM Q acc... |
https://github.com/greatdevaks/geopython-qiskit | greatdevaks | import numpy as np
# Importing standard Qiskit libraries
from qiskit import QuantumCircuit, transpile, assemble, Aer, IBMQ
from qiskit.tools.jupyter import *
from qiskit.visualization import *
from ibm_quantum_widgets import *
# Importing basic math libraries
from math import pi, sqrt
# Loading your IBM Q acc... |
https://github.com/mhlr/qiskit-meetup | mhlr | #%pip install qiskit-aqua qiskit
from qiskit.visualization import iplot_histogram, plot_histogram
%pylab inline
import qiskit as qk
qr = qk.QuantumRegister(2)
cr = qk.ClassicalRegister(2)
qc = qk.QuantumCircuit(qr,cr)
qc.h(qr[0])
qc.draw(output='mpl')
qc.cx(qr[0], qr[1])
qc.draw(output='mpl')
q... |
https://github.com/AbeerVaishnav13/Using-Qiskit | AbeerVaishnav13 | import qiskit as q
%matplotlib inline
circuit = q.QuantumCircuit(3, 2)
# Grover Search algorithm for 2 qubits and 1 control bit
# Preparation using superposition
circuit.h(0)
circuit.h(1)
circuit.x(2)
circuit.h(2)
circuit.barrier()
# Function Uw
circuit.x(0)
circuit.ccx(0, 1, 2)
circuit.x(0)
circu... |
https://github.com/AbeerVaishnav13/Using-Qiskit | AbeerVaishnav13 | import numpy as np
from qiskit import *
from qiskit.visualization import plot_histogram, plot_gate_map
from qiskit.tools.monitor import job_monitor
from qiskit.test.mock import FakeProvider
import matplotlib.pyplot as plt
import warnings
warnings.filterwarnings('ignore')
%matplotlib inline
backends = list(fi... |
https://github.com/at2005/hodl-qiskit | at2005 | from qiskit import *
from qiskit.visualization import plot_histogram
import re
import subprocess
import os
### define a class to hold hodl oracle code alongside parameters
### this allows many instances of an oracle to be defined --> not limited to
### input-dependent compilation
class HODLOracle:
def ... |
https://github.com/oierajenjo/q-Grover-Algorithm | oierajenjo | import qiskit
qiskit.__qiskit_version__
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
# importing Qiskit
from qiskit import BasicAer, IBMQ
from qiskit import QuantumCircuit, ClassicalRegister, QuantumRegister, execute
from qiskit.compiler import transpile
from qiskit.tools.visualiza... |
https://github.com/oierajenjo/q-Grover-Algorithm | oierajenjo | # -*- coding: utf-8 -*-
# This code is part of Qiskit.
#
# (C) Copyright IBM 2017, 2018.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.... |
https://github.com/apozas/qaoa-color | apozas | from functools import reduce
from itertools import product
from qiskit import BasicAer, QuantumRegister
from qiskit_aqua import QuantumInstance
from qiskit_aqua import Operator, run_algorithm
from qiskit.quantum_info import Pauli
from qiskit_aqua.components.optimizers import COBYLA
from constrainedqaoa impor... |
https://github.com/apozas/qaoa-color | apozas | #!/usr/bin/env python
# coding: utf-8
# In[65]:
# useful additional packages
import matplotlib.pyplot as plt
get_ipython().run_line_magic('matplotlib', 'inline')
import numpy as np
import time
from pprint import pprint
# importing Qiskit
from qiskit import Aer, IBMQ
from qiskit.providers.ibmq import... |
https://github.com/apozas/qaoa-color | apozas | from functools import reduce
from itertools import product
from qiskit import BasicAer, QuantumRegister, ClassicalRegister
from qiskit_aqua import QuantumInstance
from qiskit_aqua import Operator, run_algorithm
from qiskit.quantum_info import Pauli
from qiskit_aqua.components.optimizers import COBYLA
from qisk... |
https://github.com/apozas/qaoa-color | apozas | from functools import reduce
from itertools import product
from qiskit import BasicAer, QuantumRegister
from qiskit_aqua import QuantumInstance
from qiskit_aqua import Operator, run_algorithm
from qiskit.quantum_info import Pauli
from qiskit_aqua.components.optimizers import COBYLA
from qiskit_aqua.components.... |
https://github.com/apozas/qaoa-color | apozas | # Copied and modified from qiskit_aqua.algorithms.adaptive.qaoa.qaoa.py
# and qiskit_aqua.algorithms.adaptive.qaoa.varform.py
# =============================================================================
import logging
from qiskit_aqua.algorithms import QuantumAlgorithm
from qiskit_aqua import AquaError, Plu... |
https://github.com/apozas/qaoa-color | apozas | import qiskit
qiskit.__version__
from functools import reduce
from itertools import product
from qiskit import BasicAer, QuantumRegister
from qiskit_aqua import QuantumInstance
from qiskit_aqua import Operator, run_algorithm
from qiskit.quantum_info import Pauli
from qiskit_aqua.components.optimizers import... |
https://github.com/apozas/qaoa-color | apozas | from qiskit import QuantumRegister, ClassicalRegister, QuantumCircuit
from qiskit import IBMQ
from qiskit import BasicAer, execute
from qiskit.providers.aer import QasmSimulator
from qiskit.tools.visualization import plot_histogram
import matplotlib.pyplot as plt
import numpy as np
import numpy.random as rand
i... |
https://github.com/apozas/qaoa-color | apozas | from qiskit.tools.visualization import plot_histogram
import matplotlib.pyplot as plt
import numpy as np
import numpy.random as rand
import networkx as nx
from random_graph import random_graph
from itertools import product
from ast import literal_eval
import qutip as qt
import os
def get_probs(filename):
... |
https://github.com/apozas/qaoa-color | apozas | import time
# Import the Qiskit modules(Qiskit Terra)
from qiskit import QuantumCircuit, ClassicalRegister, QuantumRegister, QISKitError
from qiskit import QISKitError,execute, IBMQ, Aer
import numpy as np
# Set your API Token.
# You can get it from https://quantumexperience.ng.bluemix.net/qx/account,
# lo... |
https://github.com/GBisi/QiskitFallFest2023 | GBisi | |
https://github.com/GBisi/QiskitFallFest2023 | GBisi | from qiskit import QuantumCircuit # Importiamo la libreria Qiskit e in particolare la classe QuantumCircuit
qc = QuantumCircuit(3, 3) # Creiamo un QuantumCircuit chiamato qc avente 3 qubit e 3 bit classici
qc.draw() # Visualizziamo graficamente il circuito
from qiskit import QuantumCircuit
qc = QuantumCirc... |
https://github.com/GBisi/QiskitFallFest2023 | GBisi | import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit
from qiskit import(QuantumCircuit, QuantumRegister, ClassicalRegister, transpile)
from qiskit.visualization import plot_histogram, plot_gate_map
from qiskit.quantum_info import Statevector
from qiskit.circuit.library import ... |
https://github.com/simanraj1123/n-qubit-Grover-s-search-on-IBM-Qiskit | simanraj1123 | # Importing libraries
from qiskit import QuantumCircuit, execute, Aer, IBMQ, QuantumRegister, ClassicalRegister
from qiskit.compiler import transpile, assemble
from qiskit.tools.jupyter import *
from qiskit.visualization import *
import numpy as np
import matplotlib.pyplot as plt
from qiskit.converters import ci... |
https://github.com/QForestCommunity/launchpad | QForestCommunity | import qiskit
qiskit.__qiskit_version__
from qiskit import QuantumRegister, ClassicalRegister
from qiskit import Aer, execute, QuantumCircuit
from qiskit.circuit.library.standard_gates import RYGate
from qiskit.tools.visualization import circuit_drawer
from numpy import pi, e, sqrt, arccos, log2
from scipy.int... |
https://github.com/QForestCommunity/launchpad | QForestCommunity | from pyqubo import Spin, solve_ising
x1, x2, x3 = Spin("x1"), Spin("x2"), Spin("x3")
Quad_form = 2*(x1) + x2 - 3*(x3)
model = Quad_form.compile()
deg1, deg2, off = model.to_ising()
print('Degree1:',deg1,' Degree2:',deg2,' Offset:',off)
res = solve_ising(deg1,deg2)
print(res)
shots = 10 #variable use... |
https://github.com/QForestCommunity/launchpad | QForestCommunity | import qiskit
qiskit.__qiskit_version__
from qiskit import QuantumCircuit, BasicAer, execute
from qiskit.visualization import plot_histogram
qcSwap = QuantumCircuit(2, 2) #create a quantum circuit with 2 quantum bits and 2 classical bits.
qcSwap.x(0) #apply a pauli X gate to the first qubit to better demonst... |
https://github.com/QForestCommunity/launchpad | QForestCommunity | import qiskit
qiskit.__qiskit_version__
from qiskit import QuantumRegister, ClassicalRegister
from qiskit import Aer, execute, QuantumCircuit
from qiskit.circuit.library.standard_gates import RYGate
from numpy import pi, e, sqrt, arccos, log2
from scipy.integrate import quad
%matplotlib inline
import matplotl... |
https://github.com/QForestCommunity/launchpad | QForestCommunity | import qiskit
qiskit.__qiskit_version__
from qiskit import QuantumCircuit, BasicAer, execute
from qiskit.visualization import plot_histogram
qcSwap = QuantumCircuit(2, 2) #create a quantum circuit with 2 quantum bits and 2 classical bits.
qcSwap.x(0) #apply a pauli X gate to the first qubit to better demonst... |
https://github.com/jenglick/scipy22-qiskit-runtime-tutorial | jenglick | # import functionality from qiskit for building and running circuits
from qiskit import QuantumCircuit, BasicAer, transpile
# here we'll create a GHZ state
circuit = QuantumCircuit(3)
circuit.h(0)
circuit.cnot(0,1)
circuit.cnot(1,2)
circuit.measure_all()
print(circuit.draw())
# select a quantum backend a... |
https://github.com/jenglick/scipy22-qiskit-runtime-tutorial | jenglick | # import functionality from qiskit for building and running circuits
from qiskit import QuantumCircuit, BasicAer, transpile
import numpy as np
# define a quantum circuit with a single "X" gate
circuit = QuantumCircuit(1)
circuit.x(0)
circuit.measure_all()
circuit.draw()
# select a quantum backend and run ... |
https://github.com/jenglick/scipy22-qiskit-runtime-tutorial | jenglick | # Authenticate with the server.
from qiskit_ibm_runtime import QiskitRuntimeService
service = QiskitRuntimeService(channel="ibm_quantum")
# Prepare the circuit.
from qiskit import QuantumCircuit
qc1 = QuantumCircuit(1, 1)
qc1.x(0)
qc1.measure_all()
# Prepare the operators.
from qiskit.quantum_info impo... |
https://github.com/jenglick/scipy22-qiskit-runtime-tutorial | jenglick | # Import the module needed to access Qiskit Runtime
from qiskit_ibm_runtime import QiskitRuntimeService
# Save account on disk.
# QiskitRuntimeService.save_account(channel="ibm_quantum", token=<IBM Quantum API token>)
# Load your IBM Quantum account or enable the account if it's not previously saved.
service ... |
https://github.com/jenglick/scipy22-qiskit-runtime-tutorial | jenglick | from qiskit_nature.drivers import Molecule
from qiskit_nature.drivers.second_quantization import ElectronicStructureDriverType, ElectronicStructureMoleculeDriver
dist = 0.72
molecule = Molecule(geometry=[['H', [0., 0., 0.]], ['H', [0., 0., dist]]])
driver = ElectronicStructureMoleculeDriver(molecule, basis='sto3g... |
https://github.com/jenglick/scipy22-qiskit-runtime-tutorial | jenglick | from qiskit.quantum_info import SparsePauliOp
op = SparsePauliOp.from_list([("ZZII", 1)])
num_qubits = op.num_qubits
ops = [op]
print(op)
target_energy = -1
from qiskit.circuit.library import EfficientSU2
circuit = EfficientSU2(num_qubits, reps=1, entanglement="linear", insert_barriers=True)
circuit.d... |
https://github.com/jenglick/scipy22-qiskit-runtime-tutorial | jenglick | import numpy as np
w = np.array([[0., 1., 1., 1.],
[1., 0., 1., 0.],
[1., 1., 0., 1.],
[1., 0., 1., 0.]])
from qiskit_optimization.applications import Maxcut
max_cut = Maxcut(w)
qp = max_cut.to_quadratic_program()
print(qp.export_as_lp_string())
qubitOp, offset = qp.to_ising()
num_qubits =... |
https://github.com/jayeshparashar/Bloch-sphere- | jayeshparashar | # in this step, we will generate a 2 dim random statevector using quantum_info random_statevector method
from qiskit.quantum_info import random_statevector, Statevector
rand_sv = random_statevector(2).data
print(rand_sv) # print the vector components (complex amplitudes) associated with bais |0> and |1> from ran... |
https://github.com/jayeshparashar/Bloch-sphere- | jayeshparashar | from qiskit import *
import numpy as np
import math
from qiskit.visualization import plot_bloch_multivector, plot_state_qsphere, plot_histogram
# Define a function which will return a gate equivalent to (control-Z)^n, this gate is used in a below circuit to change
# the phase of control qubits by various power... |
https://github.com/jayeshparashar/Bloch-sphere- | jayeshparashar | #Let's start with importing packages
from qiskit import QuantumRegister, ClassicalRegister,QuantumCircuit, Aer, assemble, execute
from qiskit.visualization import plot_histogram, plot_bloch_vector, plot_bloch_multivector
import numpy as np
# import random_statevector to get a random two state quantum system
... |
https://github.com/bringthehouse/qiskit-2019-purple-qubits-server | bringthehouse | #!/usr/bin/env python3
from qiskit import QuantumRegister, ClassicalRegister
from qiskit import QuantumCircuit, Aer, execute
def run_qasm(qasm, backend_to_run="qasm_simulator"):
qc = QuantumCircuit.from_qasm_str(qasm)
backend = Aer.get_backend(backend_to_run)
job_sim = execute(qc, backend)
... |
https://github.com/ashishpatel26/IBM-Quantum-Challenge-Africa-2021 | ashishpatel26 | from qiskit import *
from qiskit.visualization import plot_histogram
import numpy as np
def NOT(inp):
"""An NOT gate.
Parameters:
inp (str): Input, encoded in qubit 0.
Returns:
QuantumCircuit: Output NOT circuit.
str: Output value measured from qubit 0.
... |
https://github.com/ashishpatel26/IBM-Quantum-Challenge-Africa-2021 | ashishpatel26 | import numpy as np
# Importing standard Qiskit libraries
from qiskit import QuantumCircuit, transpile, Aer, execute
from qiskit.tools.jupyter import *
from qiskit.visualization import *
from qiskit.providers.aer import QasmSimulator
backend = Aer.get_backend('statevector_simulator')
qc1 = QuantumCircuit(4)... |
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