Pith. sign in

REVIEW 1 cited by

An information theoretical analysis of quantum optimal control

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 1401.5047 v1 pith:NM2OIYEM submitted 2014-01-20 quant-ph cond-mat.other

classification quant-phcond-mat.other
keywords controloptimalquantumdynamicsefficientlynecessaryproblemssize
verification ladder T0 review T1 audit T2 compute T3 formal

Signed reviews

No signed human review yet.

0 comments
read the original abstract

We show that if an efficient classical representation of the dynamics exists, optimal control problems on many-body quantum systems can be solved efficiently with finite precision. We show that the size of the space of parameters necessary to solve quantum optimal control problems defined on pure, mixed states and unitaries is polynomially bounded from the size of the of the set of reachable states in polynomial time. We provide a bound for the minimal time necessary to perform the optimal process given the bandwidth of the control pulse, that is the continuous version of the Solovay-Kitaev theorem. We explore the connection between entanglement present in the system and complexity of the control problem, showing that one-dimensional slightly entangled dynamics can be efficiently controlled. Finally, we quantify how noise affects the presented results.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Minimal Quantum Reservoirs with Hamiltonian Encoding

    quant-ph 2025-05 conditional novelty 6.0 of 10

    A memoryless quantum reservoir that encodes inputs into Hamiltonian parameters can perform nonlinear regression and time-series prediction when its readouts are augmented with delay embeddings.

Pith tools