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Documentation Index

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The Bitwise Xor (denoted as ’^’) is implemented by applying this truth table between each pair of qubits (or qubit and bit) in variables A and B. Note that integer and fixed-point numbers are represented in a two-complement method during function evaluation. The binary number is extended in the case of a variable size mismatch. For example, the positive signed number (110)2=6(110)_2=6 is expressed as (00110)2(00110)_2 when operating with a five-qubit variable. Similarly, the negative signed number (110)2=−2(110)_2=-2 is expressed as (11110)2(11110)_2. Examples: 5 ^ 3 = 6 since 101 ^ 011 = 110 5 ^ -3 = -8 since 0101 ^ 1101 = 1000 -5 ^ -3 = 6 since 1011 ^ 1101 = 0110

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Examples

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Example 1: Two Quantum Variables

This example generates a quantum program that performs bitwise ‘xor’ between two variables. The left arg is a signed with five qubits and the right arg is unsigned with three qubits. 
from classiq import *


@qfunc
def main(a: Output[QNum], b: Output[QNum], res: Output[QNum]) -> None:
    allocate(5, SIGNED, 0, a)
    allocate(3, UNSIGNED, 0, b)
    a ^= 4
    b ^= 5
    res |= a ^ b


qmod = create_model(main)


qprog = synthesize(qmod)

result = execute(qprog).result_value()
print(result.parsed_counts)
print(result.counts_of_multiple_outputs(["a", "b", "res"]))
Output:
[{'a': 4.0, 'b': 5.0, 'res': 1.0}: 1000]
  {('00100', '101', '10000'): 1000}

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Example 2: Integer and Quantum Variable

This example generates a quantum program that performs a bitwise ‘xor’ between a quantum variable and an integer. The left arg is an integer equal to three and the right arg is an unsigned quantum variable with three qubits. 
@qfunc
def main(a: Output[QNum], res: Output[QNum]) -> None:
    a |= 4
    res |= 3 ^ a


qmod = create_model(main)


qprog = synthesize(qmod)

result = execute(qprog).result_value()
result.parsed_counts
Output:
[{'a': 4.0, 'res': 7.0}: 1000]