Black Hole Inspired Quantum Teleportation Protocol Wiki

Prepare an input state, create a Bell pair, perform the sender's Bell measurement, and apply classically controlled corrections at the receiver.

from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister

q = QuantumRegister(3, "q")
c = ClassicalRegister(2, "c")
circuit = QuantumCircuit(q, c)

# Prepare an example input state on q[0]
circuit.ry(0.7, q[0])
circuit.rz(0.4, q[0])

# Create the Bell pair between q[1] and q[2]
circuit.h(q[1])
circuit.cx(q[1], q[2])

# Bell-basis measurement on the input and sender qubit
circuit.cx(q[0], q[1])
circuit.h(q[0])
circuit.measure(q[0], c[0])
circuit.measure(q[1], c[1])

# Conditional Pauli corrections on the receiver qubit
with circuit.if_test((c[1], 1)):
    circuit.x(q[2])
with circuit.if_test((c[0], 1)):
    circuit.z(q[2])

print(circuit)

Encapsulate the entanglement resource in a reusable circuit function for experiments and larger teleportation layouts.

from qiskit import QuantumCircuit

def prepare_bell_pair(circuit, sender, receiver):
    """Prepare the |Phi+> Bell state between two qubits."""
    circuit.h(sender)
    circuit.cx(sender, receiver)
    return circuit

bell_circuit = QuantumCircuit(2)
prepare_bell_pair(bell_circuit, 0, 1)
print(bell_circuit)

Apply a compact entangling layer that mixes information across several qubits. Randomized Clifford or parameterized layers can be substituted for more advanced experiments.

from qiskit import QuantumCircuit

def apply_scrambling_layer(circuit, qubits):
    """Apply a simple reversible information-mixing layer."""
    for qubit in qubits:
        circuit.h(qubit)

    for index in range(len(qubits) - 1):
        circuit.cx(qubits[index], qubits[index + 1])

    if len(qubits) > 2:
        circuit.cx(qubits[-1], qubits[0])

    return circuit

scrambled = QuantumCircuit(4)
apply_scrambling_layer(scrambled, [0, 1, 2, 3])
print(scrambled)

Use a simulator backend to sample classical measurement outcomes. The counts show the distribution of the sender's Bell-measurement results.

from qiskit.transpiler import transpile
from qiskit_aer import AerSimulator

simulator = AerSimulator()
compiled = transpile(circuit, simulator)
result = simulator.run(compiled, shots=1024).result()
counts = result.get_counts()
print(counts)

For a statevector simulation, calculate the overlap between the intended input state and the recovered receiver state after decoding.

from qiskit.quantum_info import Statevector, state_fidelity

input_state = Statevector.from_label("0")
output_state = Statevector.from_instruction(circuit)

# In a full verification workflow, extract the receiver subsystem
# and compare it with the target input density matrix.
print("Simulation completed")

Draw the circuit as text or a Matplotlib figure to inspect gate order, measurements, and conditional operations.

from qiskit.visualization import circuit_drawer

print(circuit_drawer(circuit, output="text"))
# For a graphical figure:
# circuit_drawer(circuit, output="mpl")