-
### Expected behavior
With default.qubit, cost function is successfully optimized with no warning. Output is as attached:
![default_qubit_output](https://github.com/PennyLaneAI/pennylane/assets/…
-
```python
dev = qml.device("lightning.qubit", wires=2)
def my_quantum_transform(tape: qml.tape.QuantumTape) -> (Sequence[qml.tape.QuantumTape], Callable):
tape1 = tape
tape2 = qml.tape.Q…
-
#### Issue description
When optimizing on certain statevectors inputted to `MottonenStatePreparation`, running into an error with `nan` values.
It seems as if some elements of the gradient were …
-
#### Issue description
Description of the issue - include code snippets and screenshots here
if relevant. You may use the following template below
* *Expected behavior:* (What you expect to h…
-
Project Name: Quantum Chemistry simulation
Team Name: PennyLane Gang
Which challenges would you like to submit your project for?
- Quantum Chemistry Challenge
- Hybrid Quantum-Classical Compu…
-
We need to support numpy 2.0 asap
-
# Quantum NLP with the lambeq–PennyLane integration | PennyLane Blog
The Quantinuum team gives an introduction to quantum natural language processing (QNLP) and showcases the recently published integ…
-
### Feature details
This is not really a feature request, rather a report of an unexpected breaking change for device developers that I do not know how to fix...
Up until v0.35.1, when a custom …
cvjjm updated
3 months ago
-
### Expected behavior
The following example executes with either the `autograd`, `tf` or `torch` interface:
```python
dev = qml.device("default.qubit", wires=3, shots=(2,2)) #
-
-------------------------------------------------------------------------------------------------------------
#### Issue description
Description of the issue - include code snippets and screensh…