add some notes

papers/Training-Free Quantum Architecture Search.md

@@ -0,0 +1,48 @@
+AAAI <- blijkbaar goeie
+
+= The process
+
+1. sample N random circuits
+2. Calculate the number of paths through the DAG.
+3. sort by number of paths
+4. filter top-R
+5. Calculate expressibility for each C in top-R
+6. output top-K circuits
+
+
+= The search-space
+
+This search space is used to generate the random circuits to sample from, in the paper they use two(?) methods
+
+== Layerwise
+
+In this seach space they apply a certain gate type to either all even or all odd qubits.
+
+== Gatewise with IBM's topology
+
+Here they only allow gates available on the topology
+
+
+
+= Glossary
+
+What the heck do the terms they're using all mean.
+
+== Query
+
+I presume something like "try to optimize this circuit on the quantum computer"
+but **I'm unsure**
+
+== PQAS
+
+Either Neural Predictor based QAS or, GradSign or Tensorcircuit
+
+Probably the Neural Predictor one. (more [here]())
+
+== QAS
+
+Quantum Architecture Search
+
+== HEA-3 till 5
+
+Hardware Efficient Ansatze, specifically number 3 to 5 from ([this paper](https://www.nature.com/articles/nature23879))