Conceptual understanding through efficient inverse-design of quantum optical experiments

Tuesday Jun 30 2020 16:00 GMT

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Theseus is an efficient algorithm for the design of quantum experiments, which we use to solve several open questions in experimental quantum optics. The algorithm’ core is a physics-inspired, graph-theoretical representation of quantum states, which makes it significantly faster than previous comparable approaches. The gain in speed allows for topological optimization, leading to a reduction of the experiment to its conceptual core.

- how can representing quantum states as graph help with quantum experiment design
- how does this method, that doesn’t use training data, compare to other approaches people have taken in terms performance
- what is the role of interpretability in this approach and what implications does that have for generalization

- This is not a data driven approach, therefore is faster and easier to generalize
- Computational design, topological search, genetic algorithms, active learning, RNN are other alternative approaches
- The novelty here is encoding information corresponding to quantum systems in a graph and then using efficient optimization methods to obtain a particular quantum experiment setup
- This approach provides interpretation by design which in turn means that we can use it to generalize results and extract scientific concepts or relationships

Time of Recording: Tuesday Jun 30 2020 16:00 GMT

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