ArticleACS photonics2025
Dynamic Analysis and Reservoir Computing Application of a Nonlinear Microring Resonator.
Article in ACS photonics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A nonlinear microring resonator is governed by a set of coupled differential equations that model the dynamics of the optical field, temperature, and free carrier concentration within the resonator. These equations capture the mechanisms responsible for self-pulsing and memory effects, which are key in neuromorphic applications of microring resonators. One example is their use as nonlinear nodes in reservoir computing (RC). The dynamical state of a microring resonator is influenced by its control parameters: the input optical power and frequency. While previous studies have relied heavily on computationally intensive simulations to determine the resonator's self-pulsing state or identify optimal control parameters for efficient optical computation, we propose a linearization and stability analysis to identify regions in the control parameter space associated with different dynamical behaviors. Using an adiabatic approximation of the cavity field of the mode, we calculated the Jacobian eigenvalues of the linearized system, which serve as reliable indicators of RC performance for specific input characteristics.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.