Optimizing Nanophotonics: from Photoreceivers to Waveguides

Christopher Lalau Keraly

EECS Department
University of California, Berkeley
Technical Report No. UCB/EECS-2017-20
May 1, 2017

http://www2.eecs.berkeley.edu/Pubs/TechRpts/2017/EECS-2017-20.pdf

Optical communication systems are replacing electrical interconnects on shorter and shorter scales, thanks to the large bandwidth they can provide and their better energy efficiency over long distances. Optical circuit boards or even on-chip interconnects are becoming an increasingly attractive possibility, thanks to tighter integration of photonics and electronics in technology platforms such as Silicon photonics. Nevertheless in order for optical links to become competitive with their electrical counterparts at these very short length scales, their energy efficiency must still be drastically improved. State of the art systems today consume ∼1pJ/bit of energy to communicate information, which is orders of magnitude above theoretical bounds.

In this thesis, the discrepancies between the theoretical limits and real world perfor- mance are explored, with a focus on the photoreceiver, which dictates the sensitivity and therefore much of the energy used by the link.

A thorough modeling of optical links is performed, leading to the determination of optimal receiver circuit topologies to improve the sensitivity and reduce the power con- sumption of photoreceiver systems. This enables the identification of crucial performance bottlenecks and the establishment of a technological roadmap for future generations of optical interconnects.

Additionally an extremely efficient shape optimization technique using the adjoint method for passive nanophotonics is presented, in order to provide lower loss components thereby also offering a path to improve the performance of optical links.

Advisor: Eli Yablonovitch


BibTeX citation:

@phdthesis{Lalau Keraly:EECS-2017-20,
    Author = {Lalau Keraly, Christopher},
    Title = {Optimizing Nanophotonics: from Photoreceivers to Waveguides},
    School = {EECS Department, University of California, Berkeley},
    Year = {2017},
    Month = {May},
    URL = {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2017/EECS-2017-20.html},
    Number = {UCB/EECS-2017-20},
    Abstract = {Optical communication systems are replacing electrical interconnects on shorter and shorter scales, thanks to the large bandwidth they can provide and their better energy efficiency over long distances. Optical circuit boards or even on-chip interconnects are becoming an increasingly attractive possibility, thanks to tighter integration of photonics and electronics in technology platforms such as Silicon photonics. Nevertheless in order for optical links to become competitive with their electrical counterparts at these very short length scales, their energy efficiency must still be drastically improved. State of the art systems today consume ∼1pJ/bit of energy to communicate information, which is orders of magnitude above theoretical bounds.

In this thesis, the discrepancies between the theoretical limits and real world perfor- mance are explored, with a focus on the photoreceiver, which dictates the sensitivity and therefore much of the energy used by the link.

A thorough modeling of optical links is performed, leading to the determination of optimal receiver circuit topologies to improve the sensitivity and reduce the power con- sumption of photoreceiver systems. This enables the identification of crucial performance bottlenecks and the establishment of a technological roadmap for future generations of optical interconnects.

Additionally an extremely efficient shape optimization technique using the adjoint method for passive nanophotonics is presented, in order to provide lower loss components thereby also offering a path to improve the performance of optical links.}
}

EndNote citation:

%0 Thesis
%A Lalau Keraly, Christopher
%T Optimizing Nanophotonics: from Photoreceivers to Waveguides
%I EECS Department, University of California, Berkeley
%D 2017
%8 May 1
%@ UCB/EECS-2017-20
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2017/EECS-2017-20.html
%F Lalau Keraly:EECS-2017-20