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Quantum Annealing meets Machine Learning
Published on Sep 17, 20123449 Views
Quantum Computing offers the theoretical promise of dramatically faster computation through direct utilization of the underlying quantum aspects of reality. This idea, first proposed in the early 1980
Chapter list
Quantum Annealing meets Machine Learning00:00
The good news - The bad news00:36
The good news03:24
What’s ahead?06:19
Idealized Quantum Mechanics07:01
Dynamics of many qubits09:54
Hamiltonians and Minimization11:57
Adding quantum mechanics…13:44
Quantum annealing15:30
Use quantum effects to explore the search space19:31
Quantum Annealing21:29
What limits the speed of QA?23:01
How fast is QA?24:53
A physical qubit26:15
Coupling qubits: a unit cell27:54
Tiling the chip with unit cells28:52
C8 chip29:57
The full package (1)32:06
The full package (2)32:28
The full package (3)32:44
Practical realities: from ideal to realistic QM32:59
Prognosis: scalable quantum annealing?35:53
Benchmarking37:44
Annealing time40:49
Putting QA to work41:06
QA→ML: applications of QA42:53
ML→QA: outstanding problems46:07
Circumventing a sparse pairwise factor graph47:35
Problem decomposition49:48
Monte Carlo50:15
Summary50:35
[email protected]51:52