Entanglement devised barren plateau mitigation
نویسندگان
چکیده
Hybrid quantum-classical variational algorithms are one of the most propitious implementations quantum computing on near-term devices, offering classical machine-learning support to scale solution spaces. However, numerous studies have demonstrated that rate at which this space grows in qubit number could preclude learning deep circuits, a phenomenon known as barren plateaus. In work, we implicate random entanglement, i.e., entanglement is formed due state evolution with unitaries, source plateaus and characterize them terms many-body dynamics, detailing their formation function system size, circuit depth, connectivity. Using comprehension propose demonstrate plateau ameliorating techniques, including initial partitioning cost non-cost registers, meta-learning low-entanglement initializations, selective inter-register interaction, regularization, addition Langevin noise, rotation into preferred eigenbases. We find limiting, both automatic engineered, hallmark high-accuracy training emphasize that, because an iterative organization process whereas consequence randomization, they not necessarily unavoidable or inescapable. Our work forms theoretical characterization practical toolbox; first defining then employing expertise strategically combat them.
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ژورنال
عنوان ژورنال: Physical review research
سال: 2021
ISSN: ['2643-1564']
DOI: https://doi.org/10.1103/physrevresearch.3.033090