arXiv Machine Learning By Janani Gomathi, Alex Meiburg

Gradient descent reliably finds depth- and gate-optimal circuits for generic unitaries

Read the original on arXiv Machine Learning →

arXiv:2601. 03123v2 Announce Type: replace-cross Abstract: When the gate set has continuous parameters, synthesizing a unitary operator as a quantum circuit is, in principle, always possible using exact methods.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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