deeq 2.0.3

Quantum Computer Library for Everyone

Deeq

Quantum Computing SDK

Version

Tutorial

https://github.com/Deeq/Deeq-tutorials

Notice

The back end has been changed to tensor network. The previous backend environment can still be used with .run(backend="numpy").

Install

git clone https://github.com/Deeq/Deeq
cd Deeq
pip3 install -e .

or

pip3 install deeq

Circuit

from deeq import Circuit
import math

c = Circuit()

c = Circuit(50)

Method Chain

Circuit().h[0].x[0].z[0]

c = Circuit().h[0]
c.x[0].z[0]

Slice

Circuit().z[1:3] # Zgate on 1,2
Circuit().x[:3] # Xgate on (0, 1, 2)
Circuit().h[:] # Hgate on all qubits
Circuit().x[1, 2] # 1qubit gate with comma

Rotation Gate

Circuit().rz(math.pi / 4)[0]

Run

from deeq import Circuit
Circuit(50).h[:].run()

Run(shots=n)

Circuit(100).x[:].run(shots=100)
# => Counter({'1111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111': 100})

Single Amplitude

Circuit(4).h[:].run(amplitude="0101")

Expectation value of hamiltonian

from deeq.pauli import Z
hamiltonian = 1*Z[0]+1*Z[1]
Circuit(4).x[:].run(hamiltonian=hamiltonian)
# => -2.0

Deeq to QASM

Circuit().h[0].to_qasm()

Hamiltonian

from deeq.pauli import *

hamiltonian1 = (1.23 * Z[0] + 4.56 * X[1] * Z[2]) ** 2
hamiltonian2 = (2.46 * Y[0] + 5.55 * Z[1] * X[2] * X[1]) ** 2
hamiltonian = hamiltonian1 + hamiltonian2
print(hamiltonian)

Simplify the Hamiltonian

hamiltonian = hamiltonian.simplify()
print(hamiltonian)

QUBO Hamiltonian

from deeq.pauli import qubo_bit as q

hamiltonian = -3*q(0)-3*q(1)-3*q(2)-3*q(3)-3*q(4)+2*q(0)*q(1)+2*q(0)*q(2)+2*q(0)*q(3)+2*q(0)*q(4)
print(hamiltonian)

Time Evolution

hamiltonian = [1.0*Z(0), 1.0*X[0]]
a = [term.get_time_evolution() for term in hamiltonian]

time_evolution = Circuit().h[0]
for evo in a:
    evo(time_evolution, np.random.rand())

print(time_evolution)

QAOA

from deeq import Circuit
from deeq.utils import qaoa
from deeq.pauli import qubo_bit as q
from deeq.pauli import X,Y,Z,I

hamiltonian = q(0)-q(1)
step = 1

result = qaoa(hamiltonian, step)
result.circuit.run(shots=100)

Circuit Drawing Backend

from deeq import vqe
from deeq.pauli import *
from deeq.pauli import qubo_bit as q

hamiltonian = Z[0]-3*Z[1]+2*Z[0]*Z[1]+3*Z[2]*Z[3]+Z[4]
step = 8

result = vqe.Vqe(vqe.QaoaAnsatz(hamiltonian, step)).run()
result.circuit.run(backend='draw')

Document

https://deeq.readthedocs.io/en/latest/

Contributors

Contributors

Disclaimer

Copyright 2022 The DeepRecommend Developers.

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