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progress

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Noa Aarts 2026-01-05 16:14:17 +01:00
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@ -64,7 +64,7 @@ High level protocol:
1. Generate a random population
2. Evaluate the fitness
3. Select the better individuals
4. Produce offsprint
4. Produce offspring
5. Repeat until goal reached at 2
Generally Genetic Algorithms but alternatives exist
@ -106,9 +106,7 @@ However:
== What I will be doing
1. Reproduce parts of the paper@genetic-expressibility mentioned before
to have a baseline and something to benchmark against.
As it is closer to what we discussed as TF-QAS@training-free is.
1. Implement Quality-Diversity evolutionary Algorithm that does sampling of the gate space
2. Hardware constraints
- Qubit connectivity
- Per-qubit gate types (for NV-centers etc.)