Pith. sign in

REVIEW 2 cited by

Optimal linear response for expanding circle maps

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 2310.19191 v1 pith:NOFIW57M submitted 2023-10-29 math.DS nlin.CD

classification math.DSnlin.CD
keywords optimalresponsecircleconsiderexpandingexpectationfeasiblefunction
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
abstract

We consider the problem of optimal linear response for deterministic expanding maps of the circle. To each infinitesimal perturbation $\dot{T}$ of a circle map $T$ we consider (i) the response of the expectation of an observation function and (ii) the response of isolated spectral points of the transfer operator of $T$. In each case, under mild conditions on the set of feasible perturbations $\dot{T}$ we show there is a unique optimal feasible infinitesimal perturbation $\dot{T}_{\rm optimal}$, maximising the increase of the expectation of the given observation function or maximising the increase of the spectral gap of the transfer operator associated to the system. We derive expressions for the unique maximiser $\dot{T}_{\rm optimal}$ in terms of its Fourier coefficients. We also devise a Fourier-based computational scheme and apply it to illustrate our theory.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 2 Pith papers

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

  1. Markov matrix perturbations to optimize dynamical and entropy functionals

    math.DS 2025-07 conditional novelty 6.0 of 10

    Linear-response optimization algorithms are derived for entropy, KL divergence, and entropy production on Markov chains, with a drift-reconstruction protocol linking matrix perturbations to vector field forcing.

  2. Divergence-Kernel method for scores of random systems

    math.PR 2025-07 conditional novelty 6.0 of 10

    New divergence-kernel formulas compute scores of SDEs with multiplicative noise via pathwise Monte Carlo, without hyperbolicity assumptions.

Pith tools