#!/usr/bin/env python3 """ Deutsch-Josza Algorithm is one of the first examples of a quantum algorithm that is exponentially faster than any possible deterministic classical algorithm Premise: We are given a hidden Boolean function f, which takes as input a string of bits, and returns either 0 or 1: f({x0,x1,x2,...}) -> 0 or 1, where xn is 0 or 1 The property of the given Boolean function is that it is guaranteed to either be balanced or constant. A constant function returns all 0's or all 1's for any input, while a balanced function returns 0's for exactly half of all inputs and 1's for the other half. Our task is to determine whether the given function is balanced or constant. References: - https://en.wikipedia.org/wiki/Deutsch-Jozsa_algorithm - https://qiskit.org/textbook/ch-algorithms/deutsch-jozsa.html """ import numpy as np import qiskit as q def dj_oracle(case: str, num_qubits: int) -> q.QuantumCircuit: """ Returns a Quantum Circuit for the Oracle function. The circuit returned can represent balanced or constant function, according to the arguments passed """ # This circuit has num_qubits+1 qubits: the size of the input, # plus one output qubit oracle_qc = q.QuantumCircuit(num_qubits + 1) # First, let's deal with the case in which oracle is balanced if case == "balanced": # First generate a random number that tells us which CNOTs to # wrap in X-gates: b = np.random.randint(1, 2**num_qubits) # Next, format 'b' as a binary string of length 'n', padded with zeros: b_str = format(b, f"0{num_qubits}b") # Next, we place the first X-gates. Each digit in our binary string # correspopnds to a qubit, if the digit is 0, we do nothing, if it's 1 # we apply an X-gate to that qubit: for index, bit in enumerate(b_str): if bit == "1": oracle_qc.x(index) # Do the controlled-NOT gates for each qubit, using the output qubit # as the target: for index in range(num_qubits): oracle_qc.cx(index, num_qubits) # Next, place the final X-gates for index, bit in enumerate(b_str): if bit == "1": oracle_qc.x(index) # Case in which oracle is constant if case == "constant": # First decide what the fixed output of the oracle will be # (either always 0 or always 1) output = np.random.randint(2) if output == 1: oracle_qc.x(num_qubits) oracle_gate = oracle_qc.to_gate() oracle_gate.name = "Oracle" # To show when we display the circuit return oracle_gate def dj_algorithm(oracle: q.QuantumCircuit, num_qubits: int) -> q.QuantumCircuit: """ Returns the complete Deustch-Jozsa Quantum Circuit, adding Input & Output registers and Hadamard & Measurement Gates, to the Oracle Circuit passed in arguments """ dj_circuit = q.QuantumCircuit(num_qubits + 1, num_qubits) # Set up the output qubit: dj_circuit.x(num_qubits) dj_circuit.h(num_qubits) # And set up the input register: for qubit in range(num_qubits): dj_circuit.h(qubit) # Let's append the oracle gate to our circuit: dj_circuit.append(oracle, range(num_qubits + 1)) # Finally, perform the H-gates again and measure: for qubit in range(num_qubits): dj_circuit.h(qubit) for i in range(num_qubits): dj_circuit.measure(i, i) return dj_circuit def deutsch_jozsa(case: str, num_qubits: int) -> q.result.counts.Counts: """ Main function that builds the circuit using other helper functions, runs the experiment 1000 times & returns the resultant qubit counts >>> deutsch_jozsa("constant", 3) {'000': 1000} >>> deutsch_jozsa("balanced", 3) {'111': 1000} """ # Use Aer's qasm_simulator simulator = q.Aer.get_backend("qasm_simulator") oracle_gate = dj_oracle(case, num_qubits) dj_circuit = dj_algorithm(oracle_gate, num_qubits) # Execute the circuit on the qasm simulator job = q.execute(dj_circuit, simulator, shots=1000) # Return the histogram data of the results of the experiment. return job.result().get_counts(dj_circuit) if __name__ == "__main__": print(f"Deutsch Jozsa - Constant Oracle: {deutsch_jozsa('constant', 3)}") print(f"Deutsch Jozsa - Balanced Oracle: {deutsch_jozsa('balanced', 3)}")