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MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band Gap Optimization of 2- Dimensional Photonic Crystals using Semidefinite Programming and Subspace Methods R. Freund, H. Men, C. Nguyen, P. Parrilo and J. Peraire MIT

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Page 1: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

Santiago, July, 2010

One paper in Journal of Computational Physics,another paper submitted to Physics Review

Band Gap Optimization of 2-Dimensional Photonic Crystals using Semidefinite Programming and Subspace Methods

R. Freund, H. Men, C. Nguyen, P. Parrilo and J. Peraire

MIT

Page 2: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

Wave Propagation in Periodic Media

scattering

For most , beam(s) propagate through crystal without scattering (scattering cancels coherently).

But for some (~ 2a), no light can propagate: a band gap

( from S.G. Johnson )

1887 - Rayleigh 1987 – Yablonovitch & John

Page 3: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

Photonic Crystals

S. G. Johnson et al., Appl. Phys. Lett. 77, 3490 (2000)

3D Crystals

By introducing “imperfections”one can develop:

• Waveguides• Hyperlens• Resonant cavities• Switches• Splitters• …

Applications

Mangan, et al., OFC 2004 PDP24

Band Gap: Objective

Page 4: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

The Optimal Design Problem for Photonic Crystals

A photonic crystal with optimized 7th band gap.

Page 5: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

The Optimal Design Problem for Photonic Crystals

Page 6: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

The Optimal Design Problem for Photonic Crystals

Page 7: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

The Optimal Design Problem for Photonic Crystals

?

Page 8: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

Previous Work

There are some approaches proposed for solving the band gap optimization problem:

• Cox and Dobson (2000) first considered the mathematical optimization of the band gap problem and proposed a projected generalized gradient ascent method.

•Sigmund and Jensen (2003) combined topology optimization with the method of moving asymptotes (Svanberg (1987)).

•Kao, Osher, and Yablonovith (2005) used “the level set” method with a generalized gradient ascent method.

However, these earlier proposals are gradient-based methods and use eigenvalues as explicit functions. They suffer from the low regularity of the problem due to eigenvalue multiplicity.

Page 9: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

Our Approach

• Replace original eigenvalue formulation by a subspace method, and

• Convert the subspace problem to a convex semidefinite program (SDP) via semi-definite inclusion and linearization.

Page 10: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

First Step: Standard Discretizaton

Page 11: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

Optimization Formulation: P0

Typically,

Page 12: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

Parameter Dependence

Page 13: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

Change of Decision Variables

Page 14: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

Reformulating the problem: P1

We demonstrate the reformulation in the TE case,

This reformulation is exact, but non-convex and large-scale.

We use a subspace method to reduce the problem size.

Page 15: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

Subspace Method

Page 16: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

Subspace Method, continued

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MASSACHUSETTS INSTITUTE OF TECHNOLOGY

Subspace Method, continued

Page 18: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

Linear Fractional SDP :

Page 19: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

Solution Procedure

The SDP optimization problems can be solved efficiently using modern interior-point methods [Toh et al. (1999)].

Page 20: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

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Results: Optimal Structures

Page 21: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

Results: Computation Time

All computation performed on a Linux PC with Dual Core AMD Opteron 270, 2.0 GHz. The eigenvalue problem is solved by using the ARPACK software.

Page 22: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

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Mesh Adaptivity : Refinement Criteria

• Interface elements

• 2:1 rule

Page 23: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

Mesh Adaptivity : Solution Procedure

Page 24: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

Results: Optimization Process

Page 25: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

Results: Computation Time

Page 26: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

Multiple Band Gap Optimization

Multiple band gap optimization is a natural extension of the previous single band gap optimization that seeks to maximize the minimum of weighted gap-midgap ratios:

Page 27: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

Multiple Band Gap Optimization

Even with other things being the same (e.g., discretization, change of variables, subspace construction), the multiple band gap optimization problem cannot be reformulated as a linear fractional SDP. We start with:

where

Page 28: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

Multiple Band Gap Optimization

This linearizes to:

where

Page 29: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

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Solution Procedure

Page 30: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

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Sample Computational Results:2nd and 5th TM Band Gaps

Page 31: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

Sample Computational Results:2nd and 5th TM Band Gaps

Page 32: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

Optimized Structures

• TE polarization,• Triangular lattice, • 1st and 3rd band gaps

• TEM polarizations,• Square lattice, • Complete band gaps,• 9th and 12th band gaps

Page 33: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

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Results: Pareto Frontiers of 1st and 3rd TE Band Gaps

• TE polarization

Page 34: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

Results: Computational Time

Square lattice

Execution Time (minutes)

Page 35: MASSACHUSETTS INSTITUTE OF TECHNOLOGY Santiago, July, 2010 One paper in Journal of Computational Physics, another paper submitted to Physics Review Band

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

Future work

• Design of 3-dimensional photonic crystals,

• Incorporate robust fabrication constraints,

• Band-gap design optimization for other wave propagation problems, e.g., acoustic, elastic …

• Non-periodic structures, e.g., photonic crystal fibers.