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"""
Qiskit validation stub for the Goldilocks controlled reduce circuit.
Note: Full OpenQASM 3.0 modules/gates may require Qiskit 1.0+ / qiskit-qasm3.
This script provides a skeleton for building an equivalent circuit in pure Qiskit
and running a small test on AerSimulator (classical bits for the data register).
"""

from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister
from qiskit_aer import AerSimulator
from qiskit.compiler import transpile
import numpy as np

def build_goldilocks_controlled_reduce() -> QuantumCircuit:
    """
    Build the circuit equivalent to goldilocks_controlled_reduce_explicit.
    64 data + 1 ctrl + 2 ancilla = 67 qubits (ctrl is separate).
    For simulation we usually measure only the data register.
    """
    x = QuantumRegister(64, "x")
    ctrl = QuantumRegister(1, "ctrl")
    a = QuantumRegister(2, "a")  # a[0], a[1]
    cr = ClassicalRegister(64, "out")

    qc = QuantumCircuit(x, ctrl, a, cr)

    # TODO: Implement the unrolled ping-pong steps using qc.x, qc.cx, qc.ccx
    # or load the .qasm file via qiskit.qasm3.load if available.
    #
    # Example skeleton for one lower_step (bit 0, a0 -> a1):
    # qc.x(x[0])
    # qc.cx(a[0], x[0])
    # qc.x(x[0])
    # qc.ccx(x[0], a[0], a[1])
    # qc.x(x[0])

    qc.measure(x, cr)
    return qc

if __name__ == "__main__":
    qc = build_goldilocks_controlled_reduce()
    print(f"Circuit: {qc.num_qubits} qubits, depth ~{qc.depth()}")

    # Small test (will be identity until the body is filled)
    simulator = AerSimulator(method="matrix_product_state")  # or "statevector" for small cases
    # For 67 qubits only MPS or other approximate methods are feasible.
    # Prefer unit tests on 8-bit or 16-bit truncated versions.

    print("Skeleton ready. Fill in the gate sequence or use qasm3 loader.")

	"""
	Qiskit validation stub for the Goldilocks controlled reduce circuit.

	Note: Full OpenQASM 3.0 modules/gates may require Qiskit 1.0+ / qiskit-qasm3.
	This script provides a skeleton for building an equivalent circuit in pure Qiskit
	and running a small test on AerSimulator (classical bits for the data register).
	"""

	from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister
	from qiskit_aer import AerSimulator
	from qiskit.compiler import transpile
	import numpy as np

	def build_goldilocks_controlled_reduce() -> QuantumCircuit:
	"""
	Build the circuit equivalent to goldilocks_controlled_reduce_explicit.
	64 data + 1 ctrl + 2 ancilla = 67 qubits (ctrl is separate).
	For simulation we usually measure only the data register.
	"""
	x = QuantumRegister(64, "x")
	ctrl = QuantumRegister(1, "ctrl")
	a = QuantumRegister(2, "a") # a[0], a[1]
	cr = ClassicalRegister(64, "out")

	qc = QuantumCircuit(x, ctrl, a, cr)

	# TODO: Implement the unrolled ping-pong steps using qc.x, qc.cx, qc.ccx
	# or load the .qasm file via qiskit.qasm3.load if available.
	#
	# Example skeleton for one lower_step (bit 0, a0 -> a1):
	# qc.x(x[0])
	# qc.cx(a[0], x[0])
	# qc.x(x[0])
	# qc.ccx(x[0], a[0], a[1])
	# qc.x(x[0])

	qc.measure(x, cr)
	return qc

	if __name__ == "__main__":
	qc = build_goldilocks_controlled_reduce()
	print(f"Circuit: {qc.num_qubits} qubits, depth ~{qc.depth()}")

	# Small test (will be identity until the body is filled)
	simulator = AerSimulator(method="matrix_product_state") # or "statevector" for small cases
	# For 67 qubits only MPS or other approximate methods are feasible.
	# Prefer unit tests on 8-bit or 16-bit truncated versions.

	print("Skeleton ready. Fill in the gate sequence or use qasm3 loader.")