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Quantum memory and quanturn-enhanced experiments
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Classroom Contents
Dequantization and Quantum Advantage in Learning from Experiments - IPAM at UCLA
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- 1 Intro
- 2 Quantum machine learning & data advantage
- 3 A motivating example for data assisted problems
- 4 The power of data in quantum machine learning
- 5 What kinds of problems are learnable from a little data?
- 6 Quantum memory and quantum-enhanced experiments
- 7 Quantum memory and quanturn-enhanced experiments
- 8 What's the simplest task we can have an advantage on?
- 9 The best possible conventional experiments
- 10 Summarizing the scale of the separation
- 11 Bell measurements as a feature in learning
- 12 Imagining and emulating a quantum data pipeline
- 13 Experimental demonstration of advantage
- 14 We've learned about states... how about processes?
- 15 Unsupervised discovery
- 16 Unsupervised classification of processes
- 17 SWAPs and virtual distillation to the quantum PCA
- 18 SWAP and virtual distillation to the quanturn PCA
- 19 Recal dequantization
- 20 Summary & Outlook
