Hello,
Happy New Year 2023!
I was trying to use qml.matrix() and found that there seems to be a bug! See the two screen captures below.
The two CNOT should have different matrix outputs but it was not the case as shown in the first figure.
Then, test0_mat() and test1_mat() should have the same output but it was not the case as shown in the first figure.
Then, test2_mat() and test3_mat() should have the same output but it was not the case as shown in the 2nd figure.
Not sure whether I use it in the wrong way. Version information is given below. Thanks!
import numpy as np
from pennylane.optimize import AdamOptimizer
from pennylane import numpy as qml_np
import pennylane as qml
qml.about()
Name: PennyLane
Version: 0.28.0
Summary: PennyLane is a Python quantum machine learning library by Xanadu Inc.
Home-page: GitHub - PennyLaneAI/pennylane: PennyLane is a cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network.
Author:
Author-email:
License: Apache License 2.0
Location: c:\users\user\anaconda3\envs\py310penl028\lib\site-packages
Requires: appdirs, autograd, autoray, cachetools, networkx, numpy, pennylane-lightning, requests, retworkx, scipy, semantic-version, toml
Required-by: PennyLane-Lightning
Platform info: Windows-10-10.0.19045-SP0
Python version: 3.10.8
Numpy version: 1.23.5
Scipy version: 1.9.3
Installed devices:
- default.gaussian (PennyLane-0.28.0)
- default.mixed (PennyLane-0.28.0)
- default.qubit (PennyLane-0.28.0)
- default.qubit.autograd (PennyLane-0.28.0)
- default.qubit.jax (PennyLane-0.28.0)
- default.qubit.tf (PennyLane-0.28.0)
- default.qubit.torch (PennyLane-0.28.0)
- default.qutrit (PennyLane-0.28.0)
- null.qubit (PennyLane-0.28.0)
- lightning.qubit (PennyLane-Lightning-0.28.0)