mindquantum.algorithm.library

Circuit library

mindquantum.algorithm.library.amplitude_encoder(x, n_qubits)

Quantum circuit for amplitude encoding

Note

the length of classic data ought to be the power of 2, otherwise will be filled up with 0 the vector should be normalized

Parameters

• x (list[float] or numpy.array(list[float]) – the vector of data you want to encode, which should be normalized

• n_qubits (int) – the number of qubits of the encoder circuit

Examples

>>> from mindquantum.algorithm.library import amplitude_encoder
>>> from mindquantum.simulator import Simulator
>>> sim = Simulator('projectq', 8)
>>> encoder, parameterResolver = amplitude_encoder([0.5, -0.5, 0.5, 0.5], 8)
>>> sim.apply_circuit(encoder, parameterResolver)
>>> print(sim.get_qs(True))
1/2¦00000000⟩
-1/2¦00000001⟩
1/2¦00000010⟩
1/2¦00000011⟩
>>> sim.reset()
>>> encoder, parameterResolver = amplitude_encoder([0, 0, 0.5, 0.5, -0.5, 0.5], 8)
>>> sim.apply_circuit(encoder, parameterResolver)
>>> print(sim.get_qs(True))
1/2¦00000010⟩
1/2¦00000011⟩
-1/2¦00000100⟩
1/2¦00000101⟩

mindquantum.algorithm.library.bitphaseflip_operator(phase_inversion_index, n_qubits)

This operator generate a circuit that can flip the sign of any calculation bases.

Parameters

• phase_inversion_index (list[int]) – Index of calculation bases want to flip phase.

• n_qubits (int) – Total number of qubits.

Examples

>>> from mindquantum.core.circuit import Circuit
>>> from mindquantum import UN, H, Z
>>> from mindquantum.algorithm.library import bitphaseflip_operator
>>> circuit = Circuit()
>>> circuit += UN(H, 3)
>>> circuit += bitphaseflip_operator([1, 3], 3)
>>> print(circuit.get_qs(ket=True))
√2/4¦000⟩
-√2/4¦001⟩
√2/4¦010⟩
-√2/4¦011⟩
√2/4¦100⟩
√2/4¦101⟩
√2/4¦110⟩
√2/4¦111⟩

Returns

Circuit, the bit phase flip circuit.

mindquantum.algorithm.library.general_ghz_state(qubits)

Circuit that prepare a general GHZ State based on zero state.

Parameters

qubits (list[int]) – Qubits you want to apply general GHZ state.

Examples

>>> from mindquantum.algorithm.library import general_ghz_state
>>> print(general_ghz_state(range(3)).get_qs(ket=True))
√2/2¦000⟩
√2/2¦111⟩
>>> print(general_ghz_state([1, 2]).get_qs(ket=True))
√2/2¦000⟩
√2/2¦110⟩

Returns

Circuit, circuit that can prepare ghz state.

mindquantum.algorithm.library.general_w_state(qubits)

General W State.

Note

Please refer https://quantumcomputing.stackexchange.com/questions/4350/general-construction-of-w-n-state.

Parameters

qubits (list[int]) – Qubits you want to apply general W state.

Examples

>>> from mindquantum.algorithm.library import general_w_state
>>> print(general_w_state(range(3)).get_qs(ket=True))
0.5773502691896257¦001⟩
0.5773502691896258¦010⟩
0.5773502691896257¦100⟩

Returns

Circuit, circuit that can prepare w state.

mindquantum.algorithm.library.qft(qubits)

Quantum fourier transform.

Note

Please refer Nielsen, M., & Chuang, I. (2010) for more information.

Parameters

qubits (list[int]) – Qubits you want to apply quantum fourier transform.

Examples

>>> from mindquantum.algorithm.library import qft
>>> print(qft([0, 1]).get_qs(ket=True))
1/2¦00⟩
1/2¦01⟩
1/2¦10⟩
1/2¦11⟩

Returns

Circuit, circuit that can do fourier transform.