Comments (3)
Hi @bernalde! By taking a look ate Optim.jl I can say that it looks like a good reference, but not very plug-and-play: 1. they're focused in continuous-valued functions (methods might even be broken for T <: Integer
) 2. the code is very neat and easy to understand.
LANL's QuantumAnnealing.jl's code was a bit harder to grasp but I've managed to figure out what was happening and that gave me very good insights into the QA internals. After a few tweaks I've managed to implement my own Anneal+JuMP-powered QA simulator. This also made me very tempted to try out new stuff in this sense.
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Fantastic! I'm glad you were able to assess the level of interactions that we can have with those codes. Feel free to ask me any questions you have on the Quantum Annealing side, besides you can reach out to Carleton who is great and I'm sure would love to hear about this interface! If you have that interface, setting up an example (either a notebook or a script) would be really interesting to see.
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QuantumAnnealingInterface.jl is ready.
from anneal.jl.
Related Issues (12)
- Register Anneal.jl HOT 2
- Incorrect values on multiple results
- Stabilize Interface HOT 1
- Add Formatter
- Add a License
- PrimalStatus not implemented HOT 1
- Renaming package HOT 1
- Split DWave solver to remove the python dependency. HOT 9
- TagBot trigger issue HOT 21
- Error during build HOT 1
- Example doesn't work, and minor installation issue HOT 1
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