Chae-Yeun Park
Chae-Yeun Park
### Expected behavior `qml.tape.unwrap` convert all ArrayBox in a tape to usual arrays. ### Actual behavior Coefficients of the `Hamiltonian` object instance (accessible via `ham.coeffs`) are not unwrapped. ### Additional...
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For computing gradient for a circuit with expectation values of a Hamiltonian object, Lightning implements OpenMP parallelized function that distributes Hamiltonian terms to threads: https://github.com/PennyLaneAI/pennylane-lightning/blob/58c9e1c66e2d781f7f6547ef19c2a27f6ecc3f03/pennylane_lightning/src/simulator/Observables.hpp#L309-L347 However, the `Util::scaleAndAdd` function calls...
The following code now raises an error from C++ layer: ```python import sys import pennylane as qml from pennylane import numpy as np import json dev = qml.device('lightning.qubit', wires=3) @qml.qnode(dev,...
Now we support `expval` of a sparse Hamiltonian (with Kokkos), but not for the adjoint differentiation method. On the other hand, `expval` of a Hamiltonian involving `Hermitian` is not supported...
As Lightning compiled with GCC is better performing than with Clang, it is better to use GCC for building wheels for macOS. In addition, GCC supports new C++20/23 functionalities better....
Simulation results up to 127x127x127 lattice show that the scaling is not linear. Need to profile (does the greedy implementation of the minimum spanning tree slow down it?) 
Using a naive implementation of a priority queue generate O(n log(n)) code. Using the [Softheap](https://en.wikipedia.org/wiki/Soft_heap) will remain the time complexity but I am not sure whether it is necessary (and...