1. Analog-Faster-Cheaper-Better An Optical Signal Processing View Terry Turpin Chief Scientist Essex Corporation Turpin@essexcorp.com

2. Facts The “The Universe” is analog Human technology is still mostly analog –(did you ever see a digital bicycle) Digital has dominated the information processing and communications world for more than three decades Analog processing has been ignored by educational institutions There are at least two generations of scientists and engineers that have never learned analog processing or communications technology Analog optical processing in the past as been a small but persistent exception Optical communications and analog optical processing are merging the same way that digital processing and digital communications did in the past

3. Processing Overload World of Analog Signals AtoD Digital Stream 17,905,340 Tbs!! (2002 Data!) Spread Spectrum Fiber Optic Microwave Land Lines Radio 3,488 Tbs Television 68,955 Tbs Telephone 17,300,000 Tbs Internet 532,897 Tbs

4. So much information… so little time to process it Processing power is the key to superiority in a world market The Information Superiority Problem Summary of electronic information flows of new information in 2002 in terabytes … 17.7 exabytes each year, and growing

5. “Era of Tera”* *Pat Gelsinger, CTO Intel (Keynote address at Intel Developer Forum Feb 2004) … a Digital Perspective

6. Digital Dilemma over Power “Power density is increasing at a rate that implies that tens of thousands of watts per centimeter (w/cm 2 ) will be needed to scale the performance of Pentium processor architecture over the next several years. But that would produce more heat than the surface of the Sun…”* *Pat Gelsinger, CTO Intel (Keynote address at Intel Developer Forum Feb 2004)

7. … Begins the Age of Optical *Pat Gelsinger, CTO Intel (Keynote address at Intel Developer Forum Feb 2004) Optical Processors * References to Optical Processors added by Essex Corp. Analog Optical Processors excel at - Images - Signals - Correlations

8. Analog Optical Processing Overview

9. An Unclassified Success in Size, Weight and Power Acousto-Optic Spectrometer AOS launched late 1998 on SWAS for a 2 year mission 4 channel 1400 point Fourier transform in real time on a 1.4 GHz analog signal Compute power is 500 Gigaflops (Sustained) for 12 Watts electrical power Analog input eliminated the need for high speed A/D converters Mission to study the chemical composition of interstellar clouds SWAS would be impossible without the AOS optical computer

10. Optical Processor/Computer? Functions most frequently used Fourier Transform (demultiplexing/multiplexing) Correlation (pattern detection) Data distribution and replication … a machine that performs mathematical functions with light rather than electrons

11. Why go to Analog Optical Processors? Speed Reduced size and power consumption OEO Overhead & Cost are Excessive (optical - electrical - optical) Natural Fit: Optical Processing for - Optical Communications - Images - Signals - Correlations Typical improvement is a factor of 50000 Advantages

12. Information on Light Information is carried by the complex-valued property of light (spatial frequency, amplitude and phase) When an information-carrying beam is passed through a special lens or coating, or interfered with another reference beam, light performs mathematical functions

13. Massive Parallelism Operates simultaneously on an entire wave front and more than one variable — e.g., direction, amplitude and phase Digital systems are serial in nature Example: A lens simultaneously acts on the entire light beam

14. Computational Set Analog optics can perform mathematical functions –add –copy –multiply –Fourier transforms –correlation –convolution Operates on one- and two-dimensional arrays of numbers in parallel A single analog optical computer “instruction” might require thousands or millions of individual instructions for a conventional computer

15. Analog Optical Computing Smaller, Lower Power, Lighter Computers Many Parallel Electronic Processors Optical Computational Module Combines the best of both worlds: precision of electronics with massive computational power of light. Vs. Supercomputer power where it can’t go now. Head of a missile UAV Mobile ICBM Defenders Satellites 12 inches square

16. Cutting Edge Elements Materials Photonic Crystals Non-Linear Materials Silicon Germanium III-V & II-VI Materials Systems VCELS Optical Fiber Optical Amplifiers SOA EDFA Optical Correlators Optical Signal Processors New Components Technology Photon Echo Optical Tap Delay Solotons

17. Example: Analog Optical Encryption Digital Encryption –ATM at 10Gbps soon –No 40 Gbps on horizon –Protocol specific –Cost increases linearly with number of signals on a fiber Analog Encryption –5000 Gbps on horizon (ESSEX Eclipse Module) –Potential for multi-band encryption (L,C, and S) –Protocol agnostic –Cost is market driven and grows slowly with capacity on a fiber –100 Teraflops for less than 10 Watts of electrical power

18. Hyperfine Analog Optical Encryptor Hyperfine Device Phase Key Control Computer Phase Key Control Computer … Sub-channels Analog Decoding “key” “key” Sub-channels X Gbps WDM Devic e X Gbps Device or C Band Comms Device Hyperfine Device … Analog Encoding “key” Point A Point B X Gbps X Gbps Device WDM Devic e C Band Comms Device or Reflective Phase Modulator Array Reflective Phase Modulator Array

19. How Does it Work? Input Transmitted Recovered Scrambled Photons Simulated Data

20. Terabit Security – Cost Perspective * * *Assumes that aggregate bandwidths above 10 Gbps will be encrypted using multiple 10 Gbps encryptor pairs – 1 pair per wavelength ** Estimated costs are based on a multiplexed optical signal with aggregate bandwidth as indicated, and single optical encryptor pair per optical link **

21. Additional Advantages Analog optical processing provides an alternate approach to thinking about problems This alternate approach often leads to solutions that are radically different and sometimes better For example, to implement continuous scale change and Fourier transforms on data that has not been sampled or digitized Enable solutions to problems that are thought to be too complex to solve economically In supercomputing applications the improvement is about a factor of 50000

22. Summary Analog is faster, cheaper and better Examples are –Separating signal channels in frequency –Optical Encryption –Optical Communications –Optical Signal Processing Analog is a key technology Analog optical technology will force analog electronics because of the A/D conversion limitation In optical communications, analog encryption and wavelength routing will provide growth at low cost per terabit