pyqpanda_alg.QCmp

Submodules

Functions

int_comparator(value, q_state, q_anc_cmp[, function, ...])

This function provides comparators to compare basis states(can be superposition states)

interpolation_comparator(value, q_state, q_anc_cmp[, ...])

This function provides comparators to compare basis states(generate from a smooth distribution)

qubit_comparator(q_state_1, q_state_2, q_anc_cmp[, ...])

This function provides comparators to compare between two basis states(can be superposition states).

qft_comparator(value, q_state, q_cmp[, function])

This function provides qft_based comparators to compare basis states(can be superposition states)

qft_qubit_comparator(q_state_1, q_state_2, q_cmp[, ...])

This function provides qft_based comparators to compare between two basis states(can be superposition states).

Package Contents

pyqpanda_alg.QCmp.int_comparator(value, q_state, q_anc_cmp, function='geq', reuse=False)

This function provides comparators to compare basis states(can be superposition states) against a given classical integer.

Parameters

value : int

The given classical integer.

q_state : Qubit, QVec

State qubits.

q_anc_cmp : QVec

Ancilla and comparison result qubits. The comparison result qubit should be the last element. The qubit number of this register should be equal to q_state.

function : str{'geq', 'g', 'seq', 's'}, optional

Evaluate conditions:

  • geq : evaluate a >= condition. (Default)

  • g : evaluate a > condition.

  • seq : evaluate a <= condition.

  • s : evaluate a < condition.

reuse : bool

Set to True to add a reverse circuit part to reuse ancilla qubits.

Returns

circuit : QCircuit

The result this function return is a quangtum circuit. The comparison result qubit would be in state \(|1\rangle\) when the quantum state satisfies the comparison condition, otherwise \(|0\rangle\). Therefore we can get a probability outcome of the comparison.

Examples

An example of implementing a two-qubit uniform superposition state compared with 2.

>>> from pyqpanda_alg import QCmp
>>> import numpy as np
>>> from pyqpanda3.core import *
>>> value = 2
>>> m = CPUQVM()
>>> prog = QProg()
>>> prog << H(0) << H(1)
>>> cir = QCmp.int_comparator(value, [0, 1], [2, 3], function='g', reuse=True)
>>> prog << cir
>>> m.run(prog, 1000)
>>> prob_dict_result = m.result().get_prob_dict([3])
>>> print(prob_dict_result)
{'0': 0.7500000000000003, '1': 0.2500000000000001}
pyqpanda_alg.QCmp.interpolation_comparator(value, q_state, q_anc_cmp, function='g', reuse=False)

This function provides comparators to compare basis states(generate from a smooth distribution) against a given classical number(can be float). This function introduces an interpolation method to make qubits “look” like a float number when compared, so that comparisons can be made in the real number domain. In detail, when sampling, we regard the quantum state a as the interval from inf:=a-0.5 to sup:=a+1.5. When comparing the quantum state with inf+delta, the probability of smaller is delta.

Parameters

value : float

The given classical number.

q_state : Qubit, QVec

State qubits.

q_anc_cmp : QVec

Ancilla and comparison result qubits. The comparison result qubit should be the last element. The qubit number of this register should be equal to q_state.

function : str{'g', 's'}, optional

Evaluate conditions:

  • g : evaluate a > condition.(Default)

  • s : evaluate a < condition.

reuse : bool

Set to True to add a reverse circuit part to reuse ancilla qubits.

Returns

circuit : QCircuit

The result this function return is a quangtum circuit. The comparison result qubit would be in state \(|1\rangle\) when the quantum state satisfies the comparison condition, otherwise \(|0\rangle\). Therefore we can get a probability outcome of the comparison.

Examples

An example of implementing qubit state ‘110’ compared with 3.3.

>>> from pyqpanda_alg import QCmp
>>> import numpy as np
>>> from pyqpanda3.core import *
>>> value = 3.3
>>> m = CPUQVM()
>>> prog = QProg()
>>> prog << X(0) << X(1) << I(2)
>>> cir = QCmp.interpolation_comparator(value, [0, 1, 2], [3, 4, 5], function='g', reuse=True)
>>> prog << cir
>>> m.run(prog, 1000)
>>> prob_dict_result = m.result().get_prob_dict([5])
>>> print(prob_dict_result)
{'0': 0.7999999999999997, '1': 0.20000000000000023}
pyqpanda_alg.QCmp.qubit_comparator(q_state_1, q_state_2, q_anc_cmp, function='geq')

This function provides comparators to compare between two basis states(can be superposition states).

Parameters

q_state_1 : Qubit, QVec

The first state qubits.

q_state_2 : Qubit, QVec

The second state qubits.

q_anc_cmp : QVec

Ancilla and comparison result qubits. The comparison result qubit should be the last element. The qubit number of this register should be equal to q_state.

function : str{'geq', 'g', 'seq', 's', 'eq', 'neq'}, optional

Evaluate conditions:

  • geq : evaluate a >= condition. (Default)

  • g : evaluate a > condition.

  • seq : evaluate a <= condition.

  • s : evaluate a < condition.

  • eq : evaluate a == condition.

  • neq : evaluate a != condition.

reuse : bool

Set to True to add a reverse circuit part to reuse ancilla qubits.

Returns

circuit : QCircuit

The result this function return is a quangtum circuit. The comparison result qubit would be in state \(|1\rangle\) when the quantum state satisfies the comparison condition, otherwise \(|0\rangle\). Therefore we can get a probability outcome of the comparison.

Examples

An example of implementing a two-qubit uniform superposition state compared with qubit state ‘01’.

>>> from pyqpanda_alg import QCmp
>>> import numpy as np
>>> from pyqpanda3.core import *
>>> m = CPUQVM()
>>> prog = QProg()
>>> prog << H(0) << H(1) << X(3)
>>> cir = QCmp.qubit_comparator([0, 1], [2, 3],  [4, 5], function='g')
>>> prog << cir
>>> m.run(prog, 1000)
>>> prob_dict_result = m.result().get_prob_dict([5])
>>> print(prob_dict_result)
{'0': 0.7500000000000003, '1': 0.2500000000000001}
pyqpanda_alg.QCmp.qft_comparator(value, q_state, q_cmp, function='geq')

This function provides qft_based comparators to compare basis states(can be superposition states) against a given classical integer.

Parameters

value : int

The given classical integer in range [0,N).

q_state : Qubit, QVec

State qubits.

q_cmp : QVec

The comparison result qubit.

function : str{'geq', 'g', 'seq', 's'}, optional

Evaluate conditions:

  • geq : evaluate a >= condition. (Default)

  • g : evaluate a > condition.

  • seq : evaluate a <= condition.

  • s : evaluate a < condition.

Returns

circuit : QCircuit

The result this function return is a quangtum circuit. The comparison result qubit would be in state \(|1\rangle\) when the quantum state satisfies the comparison condition, otherwise \(|0\rangle\). Therefore we can get a probability outcome of the comparison.

Examples

An example of implementing a two-qubit uniform superposition state compared with 2.

>>> from pyqpanda_alg import QCmp
>>> import numpy as np
>>> from pyqpanda3.core import *
>>> value = 2
>>> m = CPUQVM()
>>> prog = QProg()
>>> prog << H(0) << H(1)
>>> cir = QCmp.qft_comparator(value, [0, 1], [2], function='g')
>>> prog << cir
>>> m.run(prog, 1000)
>>> prob_dict_result = m.result().get_prob_dict([2])
>>> print(prob_dict_result)
{'0': 0.750000000000001, '1': 0.2500000000000002}
pyqpanda_alg.QCmp.qft_qubit_comparator(q_state_1, q_state_2, q_cmp, function='geq')

This function provides qft_based comparators to compare between two basis states(can be superposition states).

Parameters

q_state_1 : Qubit, QVec

The first state qubits.

q_state_2 : Qubit, QVec

The second state qubits.

q_cmp : QVec

Comparison result qubit.

function : str{'geq', 'g', 'seq', 's'}, optional

Evaluate conditions:

  • geq : evaluate a >= condition. (Default)

  • g : evaluate a > condition.

  • seq : evaluate a <= condition.

  • s : evaluate a < condition.

Returns

circuit : QCircuit

The result this function return is a quangtum circuit. The comparison result qubit would be in state \(|1\rangle\) when the quantum state satisfies the comparison condition, otherwise \(|0\rangle\). Therefore we can get a probability outcome of the comparison.

Examples

An example of implementing a two-qubit uniform superposition state compared with qubit state ‘01’.

>>> from pyqpanda_alg import QCmp
>>> import numpy as np
>>> from pyqpanda3.core import *
>>> m = CPUQVM()
>>> prog = QProg()
>>> prog << H(0) << H(1) << X(3)
>>> cir = QCmp.qft_qubit_comparator([0, 1], [2, 3], [4], function='g')
>>> prog << cir
>>> m.run(prog, 1000)
>>> prob_dict_result = m.result().get_prob_dict([4])
>>> print(prob_dict_result)
{'0': 0.7500000000000007, '1': 0.2500000000000002}