Towards noise-aware surrogate models of carrier population dynamics in optically excited GaN

Brent Kraczek; Sara Shishehchi; Enrico Bellotti

doi:10.1117/12.2261697

19 May 2017 Towards noise-aware surrogate models of carrier population dynamics in optically excited GaN

Brent Kraczek, Sara Shishehchi, Enrico Bellotti

Proceedings Volume 10206, Disruptive Technologies in Sensors and Sensor Systems; 102060O (2017) https://doi.org/10.1117/12.2261697
Event: SPIE Defense + Security, 2017, Anaheim, CA, United States

Abstract

Monte Carlo (MC) methods have been shown to capture the ultrafast dynamics of carriers and resulting luminescence in photo-excited GaN. These calculations have assumed a homogeneous material under uniform illumination. We investigate the development of surrogate models to represent the carrier dynamics with fewer degrees of freedom, with the ultimate goal of computing the response of structured materials under inhomogeneous illumination profiles. These models are presently based on the extraction of mean and variance information from single data sets, through the use of fits to s piece-wise linear basis. Two models are then developed, one based on the mean and variance directly, and one on a Gaussian process regression model. New carrier populations with similar statistical profiles are then generated from these models to determine the amount of data reduction that can be obtained.

Citation Download Citation

Brent Kraczek, Sara Shishehchi, and Enrico Bellotti "Towards noise-aware surrogate models of carrier population dynamics in optically excited GaN", Proc. SPIE 10206, Disruptive Technologies in Sensors and Sensor Systems, 102060O (19 May 2017); https://doi.org/10.1117/12.2261697

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

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.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available