Optical computing

'''Optical computing''' or '''photonic computing''' uses light waves produced by lasers or incoherent sources for data processing, data storage or data communication for computing. For decades, photons have shown promise to enable a higher bandwidth than the electrons used in conventional computers (see optical fibers).

Most research projects focus on replacing current computer components with optical equivalents, resulting in an optical digital computer system processing binary data. This approach appears to offer the best short-term prospects for commercial optical computing, since optical components could be integrated into traditional computers to produce an optical-electronic hybrid. However, optoelectronic devices consume 30% of their energy converting electronic energy into photons and back; this conversion also slows the transmission of messages. All-optical computers eliminate the need for optical-electrical-optical (OEO) conversions, thus reducing electrical power consumption.<ref>{{cite book |first=D.D. |last=Nolte |title=Mind at Light Speed: A New Kind of Intelligence |url=https://books.google.com/books?id=Q9lB-REWP5EC&pg=PA34 |date=2001 |publisher=Simon and Schuster |isbn=978-0-7432-0501-6 |page=34}}</ref>

Application-specific devices, such as synthetic-aperture radar (SAR) and optical correlators, have been designed to use the principles of optical computing. Correlators can be used, for example, to detect and track objects,<ref>{{cite book |title=Optical Computing: A Survey for Computer Scientists |chapter=Chapter 3: Optical Image and Signal Processing |last=Feitelson |first=Dror G. |date=1988 |publisher=MIT Press |location=Cambridge, Massachusetts |isbn=978-0-262-06112-4 }}</ref> and to classify serial time-domain optical data.<ref>{{cite journal |last1=Kim |first1=S. K. |last2=Goda |first2=K.|last3=Fard |first3=A. M. |last4=Jalali |first4=B.|title= Optical time-domain analog pattern correlator for high-speed real-time image recognition |journal=Optics Letters |volume=36 |issue=2 |pages=220–2 |date=2011 |doi= 10.1364/ol.36.000220|pmid=21263506 |bibcode=2011OptL...36..220K |s2cid=15492810 }}</ref>

==Optical components for binary digital computer== The fundamental building block of modern electronic computers is the transistor. To replace electronic components with optical ones, an equivalent optical transistor is required. This is achieved by crystal optics (using materials with a non-linear refractive index).<ref>{{Cite web |title=These Optical Gates Offer Electronic Access - IEEE Spectrum |url=https://spectrum.ieee.org/optical-computing-picosecond-gates |access-date=2022-12-30 |website=IEEE |language=en}}</ref> In particular, materials exist<ref>{{Cite encyclopedia | url=https://www.rp-photonics.com/nonlinear_index.html | title=Encyclopedia of Laser Physics and Technology - nonlinear index, Kerr effect| encyclopedia=RP Photonics Encyclopedia| date=8 December 2006| last1=Paschotta| first1=Dr Rüdiger}}</ref> where the intensity of incoming light affects the intensity of the light transmitted through the material in a similar manner to the current response of a bipolar transistor. Such an optical transistor<ref>{{cite journal |last1=Jain |first1=K. | last2=Pratt | first2=G. W. Jr. |title=Optical transistor |journal=Appl. Phys. Lett. |volume=28 |issue=12 |page=719 |date=1976 |doi=10.1063/1.88627 |bibcode=1976ApPhL..28..719J }}</ref><ref name=jainprattpatent>{{cite patent | country = US | number = 4382660 | title = Optical transistors and logic circuits embodying the same | pubdate = May 10, 1983 | fdate = Jun 16, 1976 | pridate = Jun 16, 1976 | invent1 = K. Jain | invent2 = G.W. Pratt, Jr. }}</ref> can be used to create optical logic gates,<ref name=jainprattpatent /> which in turn are assembled into the higher level components of the computer's central processing unit (CPU). These will be nonlinear optical crystals used to manipulate light beams into controlling other light beams.

Like any computing system, an optical computing system needs four things to function well: # optical processor # optical data transfer, e.g. fiber-optic cable # optical storage,<ref>{{Cite web|url=https://www.microsoft.com/en-us/research/video/project-silica-storing-data-in-glass|title=Project Silica|website=Microsoft Research|date=4 November 2019 |language=en-US|access-date=2019-11-07}}</ref> # optical power source (light source)

Substituting electrical components will need data format conversion from photons to electrons, which will make the system slower.

===Controversy=== Researchers dispute the future capabilities of optical computers; whether they will ultimately be able to compete with electronic computers in terms of speed or power consumption is currently unclear. Critics note that real-world logic systems require "logic-level restoration, cascadability, fan-out and input–output isolation", all of which are provided by electronic transistors at low cost, low power, and high speed. For optical logic to be competitive beyond niche applications, major breakthroughs in non-linear optical device technology would be required, or perhaps a change in the nature of computing itself.<ref>{{cite web|last1=Rajan|first1=Renju|last2=Babu|first2=Padmanabhan Ramesh|last3=Senthilnathan|first3=Krishnamoorthy|title=All-Optical Logic Gates Show Promise for Optical Computing|url=https://www.photonics.com/a63226/All-Optical_Logic_Gates_Show_Promise_for_Optical|website=Photonics|publisher=Photonics Spectra|access-date=8 April 2018}}</ref>

==Challenges== A significant challenge to optical computing is that computation is a nonlinear process in which multiple signals must interact. Light (an electromagnetic wave), can interact with another electromagnetic wave only in the presence of electrons in a material,<ref>{{cite book|isbn=978-0-387-94659-7 |author=Philip R. Wallace|title= Paradox Lost: Images of the Quantum|date=1996|publisher=Springer }}</ref> and the strength of this interaction is much weaker for electromagnetic waves, such as light, than for the electronic signals in a conventional computer. This may require processing elements with more power and larger dimensions than those for a conventional electronic computer.{{Citation needed|date=December 2008}}

Since light can travel much faster than the drift velocity of electrons, and at frequencies measured in THz, optical transistors should be capable of extremely high frequencies. However, any electromagnetic wave must obey the transform limit, and therefore the rate at which an optical transistor can respond to a signal is limited by its spectral bandwidth. In fiber-optic communications, practical limits such as dispersion often constrain channels to bandwidths of tens of GHz, only slightly better than many silicon transistors. Obtaining dramatically faster operation than electronic transistors therefore requires practical methods of transmitting ultrashort pulses down dispersive waveguides.

==Photonic logic== [[File:optical-NOT-gate-int.svg|thumb|right|Realization of a photonic controlled-NOT gate for use in quantum computing]]

Photonic logic is the use of photons (light) in logic gates. Switching is obtained using nonlinear optical effects when two or more signals are combined.<ref name=jainprattpatent />

Resonators are especially useful in photonic logic, since they allow build-up of energy from constructive interference, thus enhancing optical nonlinear effects.

Other approaches that have been investigated include photonic logic at a molecular level, using photoluminescent chemicals. Witlicki et al. demonstrated logical operations using molecules and SERS.<ref>{{cite journal | title = Molecular Logic Gates Using Surface-Enhanced Raman-Scattered Light | first9 = Amar H. | last9 = Flood | first8 = Lasse | last8 = Jensen | first7 = Eric W. | last7 = Wong | first6 = Jan O. | last6 = Jeppesen | first5 = Vincent J. | last5 = Bottomley | first4 = Daniel W. | last4 = Silverstein | first3 = Stinne W. | last3 = Hansen | journal = J. Am. Chem. Soc. | first2 = Carsten | date = 2011 | volume = 133 | issue = 19 | last2 = Johnsen | pages = 7288–91 | doi = 10.1021/ja200992x | pmid = 21510609 | first1 = Edward H. | last1 = Witlicki | bibcode = 2011JAChS.133.7288W | url = https://figshare.com/articles/Molecular_Logic_Gates_Using_Surface_Enhanced_Raman_Scattered_Light/2651761 | url-access = subscription }}</ref>

==Unconventional approaches==

===Time delay===

The basic idea is to delay a signal in order to perform useful computations.<ref name="oltean_hamiltonian">{{cite conference|last=Oltean|first=Mihai|title= A light-based device for solving the Hamiltonian path problem |conference=Unconventional Computing| pages= 217–227| publisher= Springer LNCS 4135|doi=10.1007/11839132_18|date=2006|arxiv=0708.1496}}</ref> Of interest would be to solve NP-complete problems as those are difficult problems for conventional computers.

Two basic properties of light are used in this approach:

* Light can be delayed by passing it through an optical fiber. * Light can be split into multiple rays. This property allows multiple solutions to be evaluated concurrently.

Solving a problem with time-delays involves the following steps:

* Create a graph-like structure made from optical cables and splitters. Each graph has a start node and a destination node. * Light enters through the start node and traverses the graph until it reaches the destination. It is delayed when passing through arcs and divided inside nodes. * Light is marked when passing through an arc or through a node to identify that fact at the destination node. * The destination node waits for a signal (fluctuation in the intensity of the signal) which arrives at a particular moment in time. If no signal arrives at that moment, it means no solution was found. Otherwise the problem has a solution. Fluctuations can be read with a photodetector and an oscilloscope.

The first problem attacked in this way was the Hamiltonian path problem.<ref name="oltean_hamiltonian"/>

The simplest problem is the subset sum problem.<ref>{{cite journal|author=Mihai Oltean, Oana Muntean| title = Solving the subset-sum problem with a light-based device|journal= Natural Computing| volume= 8| issue= 2|pages =321–331| doi=10.1007/s11047-007-9059-3| date=2009 |arxiv=0708.1964| s2cid = 869226}}</ref> An optical device solving an instance with four numbers {''a1, a2, a3, a4''} is depicted below:

Optical device for solving the Subset sum problem

The light enters Start node where it divides into two rays of smaller intensity. These two rays arrive at the second node at moments ''a1'' and 0. Each is further divided into two rays that arrive at the third node at moments 0, ''a1'', ''a2'' and ''a1 + a2''. These represent all subsets of set {''a1, a2''}. Intensity fluctuations occur at no more than four moments. The destination node expects fluctuations at no more than 16 different moments (subsets of the initial). A fluctuation at the target moment ''B'' means that a solution has arisen, otherwise no subset sums to ''B''. Zero-length cables are not possible, thus all cables are lengthened by a small (fixed for all) value ''k''. In this case the solution is expected at moment ''B+n×k''.

=== <span class="anchor" id="On-chip photonic tensor cores"></span> Photonic tensor operations === With increasing demands on GPU-based accelerator technologies, the 2010s experienced emphasis on on-chip integrated optics. The emergence of deep learning neural networks based on phase modulation,<ref>{{Cite journal |last1=Shen |first1=Yichen |last2=Harris |first2=Nicholas C. |last3=Skirlo |first3=Scott |last4=Prabhu |first4=Mihika |last5=Baehr-Jones |first5=Tom |last6=Hochberg |first6=Michael |last7=Sun |first7=Xin |last8=Zhao |first8=Shijie |last9=Larochelle |first9=Hugo |last10=Englund |first10=Dirk |last11=Soljačić |first11=Marin |date=July 2017 |title=Deep learning with coherent nanophotonic circuits |url=https://www.nature.com/articles/nphoton.2017.93 |journal=Nature Photonics |language=en |volume=11 |issue=7 |pages=441–446 |doi=10.1038/nphoton.2017.93 |arxiv=1610.02365 |bibcode=2017NaPho..11..441S |s2cid=13188174 |issn=1749-4893}}</ref> and more recently amplitude modulation using photonic memories<ref>{{Cite journal |last1=Ríos |first1=Carlos |last2=Youngblood |first2=Nathan |last3=Cheng |first3=Zengguang |last4=Le Gallo |first4=Manuel |last5=Pernice |first5=Wolfram H. P. |last6=Wright |first6=C. David |last7=Sebastian |first7=Abu |last8=Bhaskaran |first8=Harish |date=February 2019 |title=In-memory computing on a photonic platform |journal=Science Advances |language=en |volume=5 |issue=2 |article-number=eaau5759 |doi=10.1126/sciadv.aau5759 |issn=2375-2548 |pmc=6377270 |pmid=30793028|arxiv=1801.06228 |bibcode=2019SciA....5.5759R }}</ref> has created photonic technologies assisting neuromorphic computing.<ref>{{Cite book |last1=Prucnal |first1=Paul R. |url=https://books.google.com/books?id=VbvODgAAQBAJ |title=Neuromorphic Photonics |last2=Shastri |first2=Bhavin J. |date=2017-05-08 |publisher=CRC Press |isbn=978-1-4987-2524-8 |language=en}}</ref><ref>{{Cite journal |last1=Shastri |first1=Bhavin J. |last2=Tait |first2=Alexander N. |last3=Ferreira de Lima |first3=T. |last4=Pernice |first4=Wolfram H. P. |last5=Bhaskaran |first5=Harish |last6=Wright |first6=C. D. |last7=Prucnal |first7=Paul R. |date=February 2021 |title=Photonics for artificial intelligence and neuromorphic computing |url=https://www.nature.com/articles/s41566-020-00754-y |journal=Nature Photonics |language=en |volume=15 |issue=2 |pages=102–114 |doi=10.1038/s41566-020-00754-y |arxiv=2011.00111 |bibcode=2021NaPho..15..102S |s2cid=256703035 |issn=1749-4893}}</ref> Evolving technology had allowed these parallel operations to be performed on-chip on an integrated photonic tensor core.<ref>{{Cite journal |last1=Feldmann |first1=J. |last2=Youngblood |first2=N. |last3=Karpov |first3=M. |last4=Gehring |first4=H. |last5=Li |first5=X. |last6=Stappers |first6=M. |last7=Le Gallo |first7=M. |last8=Fu |first8=X. |last9=Lukashchuk |first9=A. |last10=Raja |first10=A. S. |last11=Liu |first11=J. |last12=Wright |first12=C. D. |last13=Sebastian |first13=A. |last14=Kippenberg |first14=T. J. |last15=Pernice |first15=W. H. P. |date=January 2021 |title=Parallel convolutional processing using an integrated photonic tensor core |url=https://www.nature.com/articles/s41586-020-03070-1 |journal=Nature |language=en |volume=589 |issue=7840 |pages=52–58 |doi=10.1038/s41586-020-03070-1 |pmid=33408373 |arxiv=2002.00281 |bibcode=2021Natur.589...52F |hdl=10871/124352 |s2cid=256823189 |issn=1476-4687}}</ref>

In a 2025 paper titled "Direct tensor processing with coherent light," researchers demonstrated "single-shot" tensor computing through an algorithm titled "parallel optical matrix–matrix multiplication (POMMM)."<ref>{{Cite journal |last=Zhang |first=Yufeng |last2=Liu |first2=Xiaobing |last3=Yang |first3=Chenguang |last4=Xiang |first4=Jinlong |last5=Yan |first5=Hao |last6=Fu |first6=Tianjiao |last7=Wang |first7=Kaizhi |last8=Su |first8=Yikai |last9=Sun |first9=Zhipei |last10=Guo |first10=Xuhan |date=2025-11-14 |title=Direct tensor processing with coherent light |url=https://www.nature.com/articles/s41566-025-01799-7 |journal=Nature Photonics |language=en |volume=20 |issue=1 |pages=102–108 |doi=10.1038/s41566-025-01799-7 |issn=1749-4893}}</ref> POMMM allows for tensor operations such as multiplication to be performed in a single shot of light at high speeds. POMMM has the potential to replace GPUs for tasks such as convolutions and attention layers.<ref>{{Cite web |last=Azania |first=Malcolm |date=2025-12-10 |title=Single-shot light-speed computing might replace GPUs |url=https://newatlas.com/computers/single-shot-tensor-optical-computing/ |access-date=2025-12-12 |website=New Atlas |language=en-US}}</ref>

===Wavelength-based computing===

Wavelength-based computing<ref>{{cite conference|author=Sama Goliaei, Saeed Jalili|title= An Optical Wavelength-Based Solution to the 3-SAT Problem|conference=Optical SuperComputing Workshop|date=2009|doi=10.1007/978-3-642-10442-8_10| pages=77–85|bibcode=2009LNCS.5882...77G}}</ref> can be used to solve the 3-SAT problem with ''n'' variables, ''m'' clauses and with no more than three variables per clause. Each wavelength, contained in a light ray, is considered as possible value-assignments to ''n'' variables. The optical device contains prisms and mirrors that discriminate wavelengths which satisfy the formula.<ref>{{Cite journal|last1=Bartlett|first1=Ben|last2=Dutt|first2=Avik|last3=Fan|first3=Shanhui|date=2021-12-20|title=Deterministic photonic quantum computation in a synthetic time dimension|url=https://www.osapublishing.org/optica/abstract.cfm?uri=optica-8-12-1515|journal=Optica|language=EN|volume=8|issue=12|pages=1515–1523|doi=10.1364/OPTICA.424258|arxiv=2101.07786|bibcode=2021Optic...8.1515B|s2cid=231639424 |issn=2334-2536}}</ref>

===Computing by xeroxing on transparencies===  This approach uses a photocopier and transparent sheets for performing computations.<ref>{{cite conference|last=Head|first=Tom|title= Parallel Computing by Xeroxing on Transparencies|conference= Algorithmic Bioprocesses|date= 2009|pages=631–637|publisher=Springer|doi=10.1007/978-3-540-88869-7_31}}</ref> The k-SAT problem with ''n'' variables, ''m'' clauses and at most ''k'' variables per clause has been solved in three steps:<ref>{{Citation |title=Computing by xeroxing on transparencies |url=https://www.youtube.com/watch?v=4DeXPB3RU8Y |date=April 21, 2015 |language=en |access-date=2022-08-14}}</ref>

* All 2<sup>n</sup> possible assignments of ''n'' variables are generated by performing ''n'' photocopies. * Using at most 2''k'' copies of the truth table, each clause is evaluated at every row of the truth table simultaneously. * The solution is obtained by making a single copy operation of the overlapped transparencies of all ''m'' clauses.

===Masking optical beams===

The travelling salesman problem was solved by Shaked ''et al.'' (2007)<ref>{{cite journal| author= NT Shaked, S Messika, S Dolev, J Rosen |title=Optical solution for bounded NP-complete problems|journal= Applied Optics|pages=711–724|volume=46|issue=5|date=2007|doi=10.1364/AO.46.000711|pmid=17279159|bibcode=2007ApOpt..46..711S|s2cid=17440025}}</ref> via an optical approach. All possible TSP paths were generated and stored in a binary matrix that was multiplied with another gray-scale vector containing the distances between cities. The multiplication is performed optically by using an optical correlator.

===Optical Fourier co-processors===

Many computations, particularly in scientific applications, require frequent use of the 2D discrete Fourier transform (DFT) – for example in solving differential equations describing wave propagation of waves or heat transfer. Though GPU technologies typically enable high-speed computation of large 2D DFTs, other techniques can perform continuous Fourier transform optically by utilising the natural Fourier transforming property of lenses. The input is encoded using a liquid crystal spatial light modulator and the result is measured using a conventional CMOS or CCD image sensor. Such optical architectures can offer superior scaling of computational complexity due to the inherently highly interconnected nature of optical propagation, and have been used to solve 2D heat equations.<ref>{{cite journal| author= A. J. Macfaden, G. S. D. Gordon, T. D. Wilkinson |title=An optical Fourier transform coprocessor with direct phase determination|journal= Scientific Reports | volume = 7 |issue=1|article-number=13667|date=2017|doi=10.1038/s41598-017-13733-1|pmid=29057903|pmc=5651838|bibcode=2017NatSR...713667M}}</ref>

=== Ising machines ===

Ising machines are computers whose design was inspired by the theoretical Ising model.<ref name="courtland" /><ref name="cartlidge" /><ref>{{Cite news |first=Adrian |last=Cho |url=https://www.science.org/content/article/odd-computer-zips-through-knotty-tasks |title=Odd computer zips through knotty tasks |work=Science |date=2016-10-20}}</ref>

Yoshihisa Yamamoto's lab at Stanford pioneered building Ising machines using photons. Initially Yamamoto and his colleagues built an Ising machine using lasers, mirrors, and other optical components.<ref name="courtland" /><ref name="cartlidge">{{Cite news |first=Edwin |last=Cartlidge |url=http://physicsworld.com/cws/article/news/2016/oct/31/new-ising-machine-computers-are-taken-for-a-spin |title=New Ising-machine computers are taken for a spin |date=31 October 2016 |work=Physics World}}</ref>

Later a team at Hewlett Packard Labs developed photonic chip design tools and used them to build a single chip Ising machine, integrating 1,052 optical components.<ref name="courtland">{{Cite news |first=Rachel |last=Courtland |url=https://spectrum.ieee.org/hpes-new-chip-marks-a-milestone-in-optical-computing |title=HPE's New Chip Marks a Milestone in Optical Computing |date=2 January 2017 |work=IEEE Spectrum}}</ref>

==Industry== Companies involved with optical computing development include IBM,<ref>{{Cite web |first= Daphne |last=Leprince-Ringuet |date=2021-01-08 |title=IBM is using light, instead of electricity, to create ultra-fast computing |url=https://www.zdnet.com/article/ibm-is-using-light-instead-of-electricity-to-create-ultra-fast-computing/ |access-date=2023-07-02 |website=ZDNET |language=en}}</ref> Microsoft,<ref>{{Cite news |last=Wickens |first=Katie |date=2023-06-30 |title=Microsoft's light-based computer marks 'the unravelling of Moore's Law' |language=en |work=PC Gamer |url=https://www.pcgamer.com/microsofts-light-based-computer-marks-the-unravelling-of-moores-law/ |access-date=2023-07-02}}</ref> Procyon Photonics,<ref>{{Cite arXiv |last=Redrouthu |first=Sathvik|date=2022-08-13 |title=Tensor Algebra on an Optoelectronic Microchip|class=cs.PL |eprint=2208.06749 }}</ref> Lightelligence,<ref>{{Cite web |date=2021-06-02 |first=Daniel |last=de Wolff |title=Accelerating AI at the speed of light |url=https://news.mit.edu/2021/lightelligence-accelerating-ai-speed-light-0602 |access-date=2023-07-02 |website=MIT News |language=en}}</ref> Lightmatter,<ref>{{cite news |last1=Metz |first1=Rachel |title=Photonic Computing Startup Lightmatter Hits $1.2 Billion Valuation |url=https://www.bloomberg.com/news/articles/2023-12-19/gv-co-leads-funding-round-for-photonic-computing-startup-lightmatter?srnd=premium&sref=CIpmV6x8 |access-date=19 December 2023 |work=Bloomberg.com |date=19 December 2023 |language=en}}</ref> Optalysys,<ref>{{Cite web |date=2019-03-07 |title=Optalysys launches FT:X 2000 - The world's first commercial optical processing system |url=https://insidehpc.com/2019/03/optalysys-launches-ftx-2000-the-worlds-first-commercial-optical-processing-system/ |access-date=2023-07-02 |website=insideHPC.com |language=en-US}}</ref> Xanadu Quantum Technologies, Q/C Technologies, QuiX Quantum, ORCA Computing, PsiQuantum, {{interlanguage link|Quandela|fr}}, TundraSystems Global,<ref>{{Cite web |first=Kerem |last=Gülen |date=2022-12-15 |title=What Is Optical Computing: How Does It Work, Companies And More |url=https://dataconomy.com/2022/12/15/optical-computing-photonic/ |website=Dataconomy.com |access-date=2023-07-02 |language=en-US}}</ref> and Q.ANT.<ref>{{Cite web |date=2025-10-30 |title=Duquesne Family Office Invests in Q.ANT to Drive Sustainable, Photonic AI Infrastructure |url=https://finance.yahoo.com/news/duquesne-family-office-invests-q-092600876.html?guccounter=1 |website=finance.yahoo.com |access-date=2025-11-25 |language=en-US}}</ref>

==References== {{Reflist|30em}}

==Further reading== * {{cite book |title=Optical Computing: A Survey for Computer Scientists |last=Feitelson |first=Dror G. |date=1988 |publisher=MIT Press |location=Cambridge, Massachusetts |isbn=978-0-262-06112-4}} * {{cite book |title=Optical Computer Architectures: The Application of Optical Concepts to Next Generation Computers |last=McAulay |first=Alastair D. |date=1991 |publisher=John Wiley & Sons |location=New York, NY |isbn=978-0-471-63242-9}} * {{cite journal |author=Ibrahim TA|author2=Amarnath K|author3=Kuo LC|author4=Grover R|author5=Van V|author6=Ho PT |title=Photonic logic NOR gate based on two symmetric microring resonators |journal=Opt Lett |volume=29 |issue=23 |pages=2779–81 |date=2004 |doi=10.1364/OL.29.002779 |pmid=15605503|bibcode=2004OptL...29.2779I}} * {{cite journal |author=Biancardo M|author2=Bignozzi C|author3=Doyle H|author4=Redmond G |title=A potential and ion switched molecular photonic logic gate |journal=Chem. Commun. |issue=31 |pages=3918–20 |date=2005 |doi=10.1039/B507021J |pmid=16075071}} * {{cite book |editor-first=J. |editor-last=Jahns |editor2-first=S.H. |editor2-last=Lee |title=Optical Computing Hardware: Optical Computing |url=https://books.google.com/books?id=SqCjBQAAQBAJ |date=1993 |publisher=Elsevier Science |isbn=978-1-4832-1844-1}} * {{cite journal |author=Barros S|author2=Guan S|author3=Alukaidey T |title=An MPP reconfigurable architecture using free-space optical interconnects and Petri net configuring |journal=Journal of System Architecture |volume=43 |issue=6–7 |pages=391–402 |date=1997 |doi=10.1016/S1383-7621(96)00053-7 }} * D. Goswami, "Optical Computing", Resonance, June 2003; ibid July 2003. [https://web.archive.org/web/20071215005609/http://www.iisc.ernet.in/academy/resonance/June2003/June2003p56-71.html Web Archive of www.iisc.ernet.in/academy/resonance/July2003/July2003p8-21.html] * {{cite journal |author=Main T|author2=Feuerstein RJ|author3=Jordan HF|author4=Heuring VP|author5=Feehrer J|author6=Love CE |title=Implementation of a general-purpose stored-program digital optical computer |journal=Applied Optics |volume=33 |issue=8|pages=1619–28 |date=1994 |doi=10.1364/AO.33.001619 |pmid=20862187|bibcode=1994ApOpt..33.1619M|s2cid=25927679 }} * {{cite book |first1=T.S. |last1=Guan |first2=S.P.V. |last2=Barros |chapter=Reconfigurable Multi-Behavioural Architecture using Free-Space Optical Communication |title=Proceedings of the IEEE International Workshop on Massively Parallel Processing using Optical Interconnections |publisher=IEEE |date=April 1994 |isbn=978-0-8186-5832-7 |pages=293–305 |doi=10.1109/MPPOI.1994.336615|s2cid=61886442 }} * {{cite book |first1=T.S. |last1=Guan |first2=S.P.V. |last2=Barros |chapter=Parallel Processor Communications through Free-Space Optics |title=TENCON '94. IEEE Region 10's Ninth Annual International Conference. Theme: Frontiers of Computer Technology |publisher=IEEE |date=August 1994 |isbn=978-0-7803-1862-5 |pages=677–681 |volume=2 |doi=10.1109/TENCON.1994.369219|s2cid=61493433 }} * {{cite book |author=Guha A.|author2=Ramnarayan R.|author3=Derstine M. |chapter=Architectural issues in designing symbolic processors in optics |title=Proceedings of the 14th annual international symposium on Computer architecture (ISCA '87) |publisher=ACM |date=1987 |isbn=978-0-8186-0776-9 |pages=145–151 |doi=10.1145/30350.30367|s2cid=14228669}} * K.-H. Brenner, Alan Huang: "Logic and architectures for digital optical computers (A)", J. Opt. Soc. Am., A 3, 62, (1986) * {{cite journal |last=Brenner |first=K.-H. |title=A programmable optical processor based on symbolic substitution |journal=Appl. 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John Caulfield, Bertinoro, Italy, July 19–21, 2012. 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==External links== {{Commons category-inline}} * [https://www.wired.com/news/technology/0,1282,69033,00.html?tw=newsletter_topstories_html This Laser Trick's a Quantum Leap] * [http://www.extremetech.com/article2/0,1558,1779951,00.asp Photonics Startup Pegs Q2'06 Production Date] {{Webarchive|url=https://archive.today/20070516050912/http://www.extremetech.com/article2/0,1558,1779951,00.asp |date=2007-05-16 }} * [http://www.physorg.com/news6123.html Stopping light in quantum leap] * [http://www.physorg.com/news199470370.html High Bandwidth Optical Interconnects]

Category:Photonics Category:Classes of computers Category:Models of computation