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Public trial lecture:
A review of the state of the art
for optical computer
Presented on the 6th of May 2011
Andreas Kimsås
Department of Telematics
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Agenda
 Introduction
• Definition, Motivation, History & Classification
 Special purpose optical computers
 Linear optics, miniaturisation, application
 General purpose optical computer
 Logic classes, optical ‘’transistors’’
 Quantum computer
 Principles, Method & Properties
 Summary
 References
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Motivation, Evolution & Classification
INTRODUCTION
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Definition
«An optical computer is a physical information processing device that uses
photons to transport data from one memory location to another, and
processes the data while it is in this form» – Naughton & Woods, 2009




It is not necessarily programmable
It may be part of a larger (electronic) system
Logic gates may be actuated using a different technology
Optical transport is necessary, but not sufficient
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Comparison optics/electronics
Property
Optical
Electronic
Information signal
Photon
Electromagnetic pulse
Cross-talk
None (free space)
Yes
Electromagnetic
interference
None
Yes
Parallel processing
Space & frequency in
the same device
Space
Material & information
signal coupling
Poor to moderate
Excellent
Integrated circuits
Research stage
Mature
Gate size
Limited by wavelength
Quantum limit
Gate speed
Milli- to Picoseconds
Picoseconds
Fan in/out
Poor to moderate
Excellent
Heat dissipation
Debated
Bottleneck
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Optical computer research
• A story of advances and setbacks
Laser invented
• Solid state
Ruby
• Pulsed
operaton
1st wave
2nd wave
• Quenched
laser
• Parallel
optical logic
• CW semiconductor
laser at room
temperature
• Non-linear
effects
• Greater
progress in
other fields
1960
3rd wave
• Optical fibers
get
commercial
• Stronger
nonlinearities
• Weak effects
• Integration
• Speed
1970
4th wave
1980
5th wave
• Optically
switched
Internet
• Integrated
photonic
circuits
• Nanotechnology
• Quantum
effects
• Moore’s law
lives on
• Integration
1990
2000
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Classification
Optical
Computer
Signal/Image
Processing
Pattern
recognition
3R
Regenerator
Numerical
Processing
Fourier
transformation
Neural
Networks
Analogue
computing
Linear algebra
Digital
compting
Label
Processing
General
Purpose
Computer
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Classic Linear Optics & Refinements
SPECIAL PURPOSE
COMPUTERS
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Using classic linear optics
•
Perfect shuffle –permutes an
analogue/digital address into
any other adress in (logN)2
steps.
•
Requires additional capability of
exchanging nearest neigbours
•
High spatial 3D paralellism
•
Applications
• All-optical label swapping
• Image analysis (rotation)
Ref. & figure from Lohmann, 1985
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Micro-lenses (lenslets)
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•
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Classic Lens (a) - Fresnel Zone Plate (b) – SWG (c)
Subwavelength grating technical data:
• Thickness 150 nm, λ=1550nm
• Focal length 17.3 mm, diameter 0.3mm
Applications:
• Micro-scale classical optics,
• Replace Bragg reflector in Vertical Cavity Surface Emitting Laser (VCSEL)
Figure from Chrostowsky (2010)
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Micro & Nano-scale devices
All-optical recirculation buffer
Active MZI element is a GaAs modulator
Silicon waveguides on Silicon substrate
MZI switches. Loop delay = 2.6m or 13 ns
Ultralow threshold VCSEL laser.
Threshold of 180nA @ 50K, 287nA @ 150K.
GaAs active region is confined by quantum
dots.
Ref: Burmeister (2008), Paniccia (2010), Ellis (2011)
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3R optical regeneration



Lithographically etched, modelocked ring laser
 Retiming and reshaping
Amplification performed by SOA
Used for clock recovery in all-optical networks
Ref. and figure: Koch et al. (2008)
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Optical matrix multiplier
 16 Teraflops computation
capability
 Low power consumption (<1W)
 Spatial light modulator (SLM)
modulated @ 125 MHz (5ns)
 SLM matrix is multiplied with
VCSEL input vector
 (1x256x8bits).(256x256x8bits)
 Multiplication is the interaction of
a vector element and a pixel
 Addition is the superposition of
intensities
 Applications:
 Co-processor
 Image processing
 Element for: correlaton,
convolution, Fourier
transform, Hamiltonian path
problem ++
Ref: Caulfield (2010), Tamir (2009).
•
𝑎
𝑑
𝑔
𝑏
𝑒
ℎ
𝑜1
𝑐
𝑖1
𝑓 . 𝑖2 = 𝑜2
𝑜3
𝑖3
𝑘
Figure from Tamir et al. - 2009
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Versatility of matrix multiplier
General form
General form
(analogue or digital)
Permutation, Spatial
rotation & Shuffle
Addition & Logical OR
Multiplication & Logical
AND
Notes: Binary OR requires boolean interpretation of addition output.
Binary AND uses the SLM matrix and input vector as inputs
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Logic schemes & devices
GENERAL PURPOSE
OPTICAL COMPUTER
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Conventional and Directed logic circuits
Conventional
Directed
 Very common in ICs of today
 CMOS transistor is the building block
 Energy is dissipated at (almost) every
step
 Sequential stabilizaton of gates
 Min Clock period = longest path delay +
SUM of ALL rise/fall times
 Inspired by Fredkin gates
 Cross-Bar switch is main element
 The same light pulse along the path,
main energy cost is to set the switch
 All gates can be set at the same time !
 Min. Clock period = longest path delay
+ switch reconfiguration time
Refs.: Dadamundi (2005), Hardy et al. (2007)
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Directed logic circuit examples
 A XOR B
 Initialised with
True=(1,0)
 F(A) is cross if A=True
 F(A) is bar if A=False
 A OR B
 Feedback is required
 At most 3 levels is
required to perform
any logical operation
 Algebraic functions
 Not yet defined for
directed logic
 Matrix operations ??
Refs.: Hardy et al. (2009)
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Mechanical switch example
Micro electromechanical mirror (MEMS)
High spatial paralellism: 100 x100 (Fijutsu)
Footprint about 8 x 6 x 3 cm3
Ref. and figures Wu & Solgaard (2006).
2x2 MEMS add-drop switch (cross-bar)
20μs switching time
Collimating lenses are required for coupling
Extendable to several WDM channels
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Mechanical switch example
Micro electromechanical mirror (MEMS)
High spatial paralellism: 100 x100 (Fijutsu)
Footprint about 8 x 6 x 3 cm3
Ref. Wu & Solgaard (2006).
2x2 MEMS add-drop switch (cross-bar)
20μs switching time
Collimating lenses are required for coupling
Extendable to several WDM channels
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Guided wave switches
Directed Coupler type
Phased Array Switch
Phase-shift e.g. via electro-optic effect.
Top, three couplers, bottom Mach-Zender
Interferometer
Based on coupled mode theory
Electronically induced phase shift
Footprint 4x3 mm2 , 1x16 switch with 24
array waveguides
11 & 5 ns rise/fall time.
Ref. : Caulfield (2010) & Tanamura et al. 2011
Essex M.Sc course notes
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Other basic switching elements
Description
Active
Passive
Type
Techical data
On-off
SOAs
Couplers
2x2
GHz, noise
Polarisation
TFF or LCD
PBS
2x2
kHz-GHz, PDL
Y-junction
Org. Polymer
Coupler
1x2
GHz, weak nonlinearity
AWJ
LiNbO2
Couplers
1x2
GHz, drive voltage
Thermo-electric
Phase shift
AWG/Couplers
1xn,2x2
kHz, slow
Acousto-optic
Phase shift
AWG/Couplers
1xn,2x2
MHz, loss/stability
Refs.: Borella (1997), Hardy (2007), Yang (2010),
& Essex M.Sc. Course notes
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All-optical SOA logic



Pump, SOA and BPF is used for logic via non-linear effects (XGM,XPM & FWM)
40 GHz speed demonstrated!
Cascadability demands VOA (stable output power), fast wavelength tuning,
polarization control and is limited by amplifer noise.
Ref. and figure: Zhang (2009)
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Principles & Advantages
QUANTUM COMPUTING
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Basic elements
Any distinguishable quantity can be
used to encode the qubit value, e.g.
polarisation, time bin or space
State of a qubit is fully described as
a sum of vector elements:
a|H> + b|V>, with a2 + b2 = 1
State changed though phase shifts
or by switching in space.
Linear optical elements can be
used without major problems
(determinsitic), but loss and noise
will destroy the system
Non-linear effects are far too weak
to be used; was the phase shift in
the MZI applied or not?
Refs. O’Brien (2007) & Thompson (2011). Figures from O’Brien
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Entangled states
The system should work as a
CNOT gate, without using nonlinear effects.
Beam splitters act on qubits inside
the probabilistic gate and creates a
total of 16 output combinations.
The CNOT is sucessful for one
combination, measured by singlephoton detection at each detector
In a cascade the probability of
success at all CNOTs decreases
exponentially!
Partily soved via quantum
teleportation. If successful, the
target qubit is output to the next
stage.
Ref and figures from O’Brien (2007)
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Summary
• Paralellism is a key property for high performance optical
computing
• NP to P computational complexity
• Reduces footprint
• Optical signal processing is useful for special purpose
applications; e.g. for optical networking
• The general purpose computer should not be an optical blueprint of electronic systems
• Poor cascadability is currently the main impediment to general
purpose optical computer
• Quantum effects enables small, power-efficient and
computationally efficient algorithms, but a realization is far from
immediate
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Properties of a quantum
computer
•
•
•
•
Power efficient
Very compact (but not much smaller than other)
Spatial paralellism represents a speedup
Probabilistic overhead is compensated for by «quantum speedup». Ignoring overhead gives exponential speedup for some
specific problems.
• Identify states that correspond to a certain problem is difficult
• Known applications:
• Factorisation problem
• Fourier transform
• Probabilistic database search
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References
Naughton, T. J. and D. Woods (2009). “Optical Computing”. Encyclopedia of Complexity and Systems
Science. R. A. Meyers, Springer New York
2. Lohmann, A. W. (1986). "What classical optics can do for the digital optical computer." Appl. Opt. 25(10):
1543-1549
3. Abdeldayem, H., D. Frazier, et al. (2008). «Recent Advances in Photonic Devices for Optical Super
Computing». Optical SuperComputing. S. Dolev, T. Haist and M. Oltean, Springer Berlin / Heidelberg.
4. Chrostowski, L. (2010). "Optical gratings: Nano-engineered lenses." Nat Photon 4(7): 413-415.
5. Dandamudi, S. (2005). Digital Logic Circuits. Guide to Assembly Language Programming in Linux, Springer
US: 11-44
6. Ellis, B., M. A. Mayer, et al. (2011). "Ultralow-threshold electrically pumped quantum-dot photonic-crystal
nanocavity laser." Nat Photon 5(5): 297-300
7. Tamir, D. E., N. T. Shaked, et al. (2008). Electro-Optical DSP of Tera Operations per Second and Beyond
(Extended Abstract). Proceedings of the 1st international workshop on Optical SuperComputing. Vienna,
Austria, Springer-Verlag: 56-69.
8. Hardy, J. and J. Shamir (2007). "Optics inspired logic architecture." Opt. Express 15(1): 150-165
9. Wu, M. C., O. Solgaard, et al. (2006). "Optical MEMS for Lightwave Communication." J. Lightwave Technol.
24(12): 4433-4454.
10. Caulfield, H. J. and S. Dolev (2010). "Why future supercomputing requires optics." Nat Photon 4(5): 261263.
11. Borella, M. S., J. P. Jue, et al. (1997). "Optical components for WDM lightwave networks." Proceedings of
the IEEE 85(8): 1274-1307.
12. Yang, W., Y. Liu, et al. (2010). "Wavelength-Tunable Erbium-Doped Fiber Ring Laser Employing an
Acousto-Optic Filter." J. Lightwave Technol. 28(1): 118-122.
1.
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References II
13. Koch, B. R., A. W. Fang, et al. (2008). All-Optical Clock Recovery with Retiming and Reshaping Using a
Silicon Evanescent Mode Locked Ring Laser. Optical Fiber communication/National Fiber Optic Engineers
Conference
14. Paniccia, M., (2010), Integrating silicon photonics, Nature Photonics, Interview | Focus, Vol. 4.
15. Burmeister, E. F., J. Mack, et al. (2008). SOA Gate Array Recirculating Buffer for Optical Packet Switching,
Optical Society of America
16. Zhang, X., J. Xu, et al. (2009). All-Optical Logic Gates Based on Semiconductor Optical Amplifiers and
Tunable Filters. Optical SuperComputing. S. Dolev and M. Oltean, Springer Berlin / Heidelberg. 5882: 1929.
17. Tucker, R. S. (2006). "The Role of Optics and Electronics in High-Capacity Routers." Lightwave
Technology, Journal of 24(12): 4655-4673
18. Thompson, M. G., A. Politi, et al. (2011). "Integrated waveguide circuits for optical quantum computing."
Circuits, Devices & Systems, IET 5(2): 94-102
19. O'Brien, J. L. (2007). "Optical Quantum Computing." Science 318(5856): 1567-1570
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Optical label processing
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Klonidis et al.
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