The impact of dispersion and saturation energy Esat on the mode-locking states in an Yb-doped fiber with near-zero net dispersion was investigated by simulation. We observed the transition states between the three stable mode-locking states: dissipative soliton, similariton, and soliton-like pulse, with the tuning of dispersion and Esat.
KEYWORDS: Ultrafast phenomena, Mode locking, Fiber lasers, Education and training, Neural networks, Solitons, Data modeling, Deep learning, Systems modeling, Engineering
In this paper, we propose using the EfficientNet deep learning neural network to classify the ultrashort pulses in an Yb-doped mode-locked fiber laser. The results showed that the model achieved a classification accuracy of 99.8% for solitons, self-similar pulses, and amplifier similaritons, demonstrating its effectiveness in classifying ultrashort pulses.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.