Description
Expected behavior
When the script is executed, the SX operation should be applied to the qubit at index 1, as specified in the circuit definition. The QASM string generated from the circuit should reflect this and include the correct operation on the correct qubit.
Actual behavior
Instead, the SX operation is applied to the first free qubit (at index 0), not the one at index 1. This is evident in the QASM string generated from the circuit, where the SX operation is applied to q[0] instead of q[1].
Additional information
The issue is reproducible 100% of the time. Further testing with more complex circuits has confirmed that the operations are consistently applied to the first free qubit instead of the one specified in the circuit.
The issue is likely linked to the self.wires of the QuantumScript class, as they are not ordered in numeric order.
Source code
import pennylane as qml
from pennylane import numpy as np
dev = qml.device("default.qubit", wires=3)
@qml.qnode(dev)
def circuit():
qml.SX(wires=1)
return [
qml.expval(qml.PauliZ(0)),
qml.expval(qml.PauliZ(1)),
qml.expval(qml.PauliZ(2)),
]
np.random.seed(1)
print("--------------------")
print("Circuit:")
print(qml.draw(circuit, level="device")())
from pennylane.tape import QuantumTape
with QuantumTape(shots=10) as tape:
circuit.construct([], {})
qasm_str_pennylane = circuit.tape.to_openqasm()
print("--------------------")
print("QASM string from PennyLane:")
print(qasm_str_pennylane)
# --------------------
# Circuit:
# 0: ─────┤ <Z>
# 1: ──SX─┤ <Z>
# 2: ─────┤ <Z>
# --------------------
# QASM string from PennyLane:
# OPENQASM 2.0;
# include "qelib1.inc";
# qreg q[3];
# creg c[3];
# rz(1.5707963267948966) q[0];
# ry(1.5707963267948966) q[0];
# rz(-3.141592653589793) q[0];
# u1(1.5707963267948966) q[0];
# measure q[0] -> c[0];
# measure q[1] -> c[1];
# measure q[2] -> c[2];Tracebacks
No error traceback is produced, as the code executes without errors. However, the output is incorrect, and the QASM string does not represent the correct circuit.System information
Name: PennyLane
Version: 0.38.0
Summary: PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.
Home-page: https://github.com/PennyLaneAI/pennylane
Author:
Author-email:
License: Apache License 2.0
Location: /usr/local/lib/python3.10/site-packages
Requires: appdirs, autograd, autoray, cachetools, networkx, numpy, packaging, pennylane-lightning, requests, rustworkx, scipy, toml, typing-extensions
Required-by: PennyLane-qiskit, PennyLane_Lightning
Platform info: Linux-5.4.0-193-generic-x86_64-with-glibc2.36
Python version: 3.10.15
Numpy version: 1.26.4
Scipy version: 1.14.1
Installed devices:
- lightning.qubit (PennyLane_Lightning-0.38.0)
- qiskit.aer (PennyLane-qiskit-0.38.0)
- qiskit.basicaer (PennyLane-qiskit-0.38.0)
- qiskit.basicsim (PennyLane-qiskit-0.38.0)
- qiskit.remote (PennyLane-qiskit-0.38.0)
- default.clifford (PennyLane-0.38.0)
- default.gaussian (PennyLane-0.38.0)
- default.mixed (PennyLane-0.38.0)
- default.qubit (PennyLane-0.38.0)
- default.qubit.autograd (PennyLane-0.38.0)
- default.qubit.jax (PennyLane-0.38.0)
- default.qubit.legacy (PennyLane-0.38.0)
- default.qubit.tf (PennyLane-0.38.0)
- default.qubit.torch (PennyLane-0.38.0)
- default.qutrit (PennyLane-0.38.0)
- default.qutrit.mixed (PennyLane-0.38.0)
- default.tensor (PennyLane-0.38.0)
- null.qubit (PennyLane-0.38.0)Existing GitHub issues
- I have searched existing GitHub issues to make sure the issue does not already exist.