View source for Optical computing

{{short description|Computer that uses photons or light waves}}
'''Optical computing''' or '''photonic computing''' uses light waves produced by [[Physics:Laser|laser]]s or incoherent sources for [[Data processing|data processing]], data storage or data communication for [[Computing|computing]]. For decades, [[Physics:Photon|photon]]s have shown promise to enable a higher [[Bandwidth (signal processing)|bandwidth]] than the [[Physics:Electron|electron]]s used in conventional computers (see [[Engineering:Optical fiber|optical fiber]]s).

Most research projects focus on replacing current computer components with optical equivalents, resulting in an optical digital computer system processing [[Binary data|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 [[Engineering:Synthetic-aperture radar|synthetic-aperture radar]] (SAR) and [[Optical correlator|optical correlator]]s, 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 [[Engineering:Transistor|transistor]]. To replace electronic components with optical ones, an equivalent [[Engineering:Optical transistor|optical transistor]] is required. This is achieved by [[Physics:Crystal optics|crystal optics]] (using materials with a [[Physics:Refractive index#Nonlinearity|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=spectrum.ieee.org |language=en}}</ref> In particular, materials exist<ref>{{Cite web | url=https://www.rp-photonics.com/nonlinear_index.html | title=Encyclopedia of Laser Physics and Technology - nonlinear index, Kerr effect}}</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 |pages=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 [[Engineering:Logic gate|logic gate]]s,<ref name=jainprattpatent /> which in turn are assembled into the higher level components of the computer's [[Central processing unit|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 three things to function well:
# optical processor
# optical data transfer, e.g. fiber-optic cable
# [[Engineering:Optical storage|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|language=en-US|access-date=2019-11-07}}</ref>

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

===Controversy===
There are some disagreements between researchers about the future capabilities of optical computers; whether or not they may be able to compete with semiconductor-based electronic computers in terms of speed, power consumption, cost, and size is an open question. Critics note that<ref name="Tucker">{{cite journal |first=R.S. |last=Tucker |title=The role of optics in computing |journal=Nature Photonics |volume=4 |issue=7 |pages=405 |date=2010 |doi=10.1038/nphoton.2010.162 |bibcode=2010NaPho...4..405T |doi-access=free }}</ref> real-world logic systems require "logic-level restoration, cascadability, [[Engineering:Fan-out|fan-out]] and input–output isolation", all of which are currently provided by electronic transistors at low cost, low power, and high speed. For optical logic to be competitive beyond a few 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>

==Misconceptions, challenges, and prospects==
A significant challenge to optical computing is that computation is a nonlinear process in which multiple signals must interact. Light, which is an electromagnetic wave, can only interact with another electromagnetic wave in the presence of electrons in a material,<ref>{{cite book|isbn=978-0387946597 |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 result in the processing elements for an optical computer requiring more power and larger dimensions than those for a conventional electronic computer using transistors.{{Citation needed|date=December 2008}}

A further misconception{{by whom|date=May 2019}} is that since light can travel much faster than the [[Physics:Drift velocity|drift velocity]] of electrons, and at frequencies measured in [[Terahertz (unit)|THz]], optical transistors should be capable of extremely high frequencies. However, any electromagnetic wave must obey the [[Physics:Bandwidth-limited pulse|transform limit]], and therefore the rate at which an optical transistor can respond to a signal is still limited by its spectral bandwidth. In [[Physics:Fiber-optic communication|fiber-optic communication]]s, practical limits such as [[Physics:Dispersion (optics)|dispersion]] often constrain [[Wavelength-division multiplexing|channel]]s to bandwidths of tens of GHz, only slightly better than many silicon transistors. Obtaining dramatically faster operation than electronic transistors would therefore require practical methods of transmitting [[Physics:Ultrashort pulse|ultrashort pulse]]s down highly 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 ([[Physics:Light|light]]) in [[Engineering:Logic gate|logic gate]]s (NOT, AND, OR, NAND, NOR, XOR, XNOR). Switching is obtained using [[Physics:Nonlinear optics|nonlinear optical effect]]s when two or more signals are combined.<ref name=jainprattpatent />

[[Physics:Optical cavity|Resonator]]s are especially useful in photonic logic, since they allow a build-up of energy from [[Physics:Constructive interference|constructive interference]], thus enhancing optical nonlinear effects.

Other approaches that have been investigated include photonic logic at a [[Engineering:Nanotechnology|molecular level]], using [[Physics:Photoluminescence|photoluminescent]] chemicals. In a demonstration, Witlicki et al. performed 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 | url = https://figshare.com/articles/Molecular_Logic_Gates_Using_Surface_Enhanced_Raman_Scattered_Light/2651761 }}</ref>

==Unconventional approaches==

===Time delays optical computing===

The basic idea is to delay light (or any other 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-completeness|NP-complete problem]]s as those are difficult problems for the conventional computers.

There are two basic properties of light that are actually used in this approach:

* The light can be delayed by passing it through an optical fiber of a certain length.
* The light can be split into multiple (sub)rays. This property is also essential because we can evaluate multiple solutions in the same time.

When solving a problem with time-delays the following steps must be followed:

* The first step is to create a graph-like structure made from optical cables and splitters. Each graph has a start node and a destination node.
* The 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.
* The light is marked when passing through an arc or through a node so that we can easily identify that fact at the destination node.
* At the destination node we will wait for a signal (fluctuation in the intensity of the signal) which arrives at a particular moment(s) in time. If there is no signal arriving at that moment, it means that we have no solution for our problem. Otherwise the problem has a solution. Fluctuations can be read with a [[Physics:Photodetector|photodetector]] and an [[Engineering:Oscilloscope|oscilloscope]].

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

The simplest one is the [[Subset sum problem|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:

[[File:Optical device for solving the Subset sum problem.png|Optical device for solving the Subset sum problem]]

The light will enter in Start node. It will be divided into two (sub)rays of smaller intensity. These two rays will arrive into the second node at moments ''a1'' and 0. Each of them will be divided into two subrays which
will arrive in the third node at moments 0, ''a1'', ''a2'' and ''a1 + a2''. These represents the all subsets of the set {''a1, a2''}. We expect fluctuations in the intensity of the signal at no more than four different moments. In the destination node we expect fluctuations at no more than 16 different moments (which are all the subsets of the given). If we have a fluctuation in the target moment ''B'', it means that we have a solution of the problem, otherwise there is no subset whose sum of elements equals ''B''. For the practical implementation we cannot have zero-length cables, thus all cables are increased with a small (fixed for all) value ''k'. In this case the solution is expected at moment ''B+n×k''.

=== On-Chip Photonic Tensor Cores ===
With increasing demands on graphical processing unit-based accelerator technologies, in the second decade of the 21st century, there has been a huge emphasis on the use of on-chip integrated optics to create photonics-based processors. The emergence of both 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 |pages=eaau5759 |doi=10.1126/sciadv.aau5759 |issn=2375-2548 |pmc=6377270 |pmid=30793028|arxiv=1801.06228 |bibcode=2019SciA....5.5759R }}</ref> have created a new area of photonic technologies for 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> leading to new photonic computing technologies, all on a chip such as the 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>

===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 [[Boolean satisfiability problem#3-satisfiability|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 are used to discriminate proper 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===
<!-- remember that "xerox" *is* a trademark, and something of an americanism: the globally-understood equivalent is photocopier, to photocopy, a photocopy -->
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> [[Boolean satisfiability problem#3-satisfiability|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>

* Firstly all 2<sup>n</sup> possible assignments of ''n'' variables have been 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|travelling salesman problem]] has been 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> by using an optical approach. All possible TSP paths have been generated and stored in a binary matrix which 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|discrete Fourier transform]] (DFT) – for example in solving differential equations describing propagation of waves or transfer of heat. Though modern GPU technologies typically enable high-speed computation of large 2D DFTs, techniques have been developed that can perform continuous Fourier transform optically by utilising the natural [[Fourier optics#Fourier transforming property of lenses|Fourier transforming property of lens]]es. The input is encoded using a [[Physics:Liquid crystal|liquid crystal]] [[Physics:Spatial light modulator|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|pages=13667|date=2017|doi=10.1038/s41598-017-13733-1|pmid=29057903|pmc=5651838|bibcode=2017NatSR...713667M}}</ref>

=== Ising machines ===

Physical computers whose design was inspired by the theoretical [[Physics:Ising model|Ising model]] are called Ising machines.<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>

[[Biography:Yoshihisa Yamamoto (scientist)|Yoshihisa Yamamoto]]'s lab at [[Organization:Stanford University|Stanford]] pioneered building Ising machines using photons. Initially Yamamoto and his colleagues built an Ising machine using lasers, mirrors, and other optical components commonly found on an [[Physics:Optical table|optical table]].<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 [[Physics:Photonic chip|photonic chip]] design tools and used them to build an Ising machine on a single chip, integrating 1,052 optical components on that single chip.<ref name="courtland">{{Cite news |first=Rachel |last=Courtland |url=https://spectrum.ieee.org/semiconductors/processors/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==
Some additional companies involved with optical computing development include [[Company:IBM|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> [[Company:Microsoft|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> [[Company:Xanadu Quantum Technologies|Xanadu Quantum Technologies]], ORCA Computing, [[Company:PsiQuantum|PsiQuantum]], {{interlanguage link|Quandela|fr}}, and 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>

==See also==
*[[Linear optical quantum computing]]
*[[Engineering:Optical interconnect|Optical interconnect]]
*[[Optical neural network]]
*{{section link|Photonic crystal|Applications}}
*[[Engineering:Photonic integrated circuit|Photonic integrated circuit]]
*[[Physics:Photonic molecule|Photonic molecule]]
*Photonic transistor
*[[Physics:Silicon photonics|Silicon photonics]]
*[[Unconventional computing]]

==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. Opt. |volume=27 |issue=9 |pages=1687–91 |date=1988 |doi=10.1364/AO.27.001687 |pmid=20531637|bibcode=1988ApOpt..27.1687B |s2cid=43648075 }}
* {{cite journal |author=Streibl N.|author2=Brenner K.-H.|author3=Huang A.|author4=Jahns J.|author5=Jewell J.L.|author6=Lohmann A.W.|author7=Miller D.A.B.|author8=Murdocca M.J.|author9=Prise M.E.|author10=Sizer II T. |title=Digital Optics |journal=Proc. IEEE |volume=77 |issue=12 |pages=1954–69 |date=1989 |doi=10.1109/5.48834 |s2cid=59276160 }}
* ''[https://web.archive.org/web/20000510201540/http://science.nasa.gov/headlines/y2000/ast28apr_1m.htm NASA scientists working to improve optical computing technology]'', 2000
* ''[http://www.tcreate.org/optical Optical solutions for NP-complete problems]''
* {{cite book |first1=S. |last1=Dolev |first2=T. |last2=Haist |first3=M.|last3= Oltean |title=Optical SuperComputing: First International Workshop, OSC 2008, Vienna, Austria, August 26, 2008, Proceedings |url=https://books.google.com/books?id=G6ZYwjKh_QcC |date=2008 |publisher=Springer |isbn=978-3-540-85672-6}}
* {{cite book |first1=S. |last1=Dolev |first2=M. |last2=Oltean |title=Optical Supercomputing: Second International Workshop, OSC 2009, Bertinoro, Italy, November 18–20, 2009, Proceedings |url=https://books.google.com/books?id=sl44EkMjcIkC |date=2009 |publisher=Springer |isbn=978-3-642-10441-1}}
* {{cite book |first1=S. |last1=Dolev |first2=M. |last2=Oltean |title=Optical Supercomputing: Third International Workshop, OSC 2010, Bertinoro, Italy, November 17–19, 2010, Revised Selected Papers |url=https://books.google.com/books?id=uf65jCXgFvwC |date=2011 |publisher=Springer |isbn=978-3-642-22493-5}}
* {{cite book |first1=S. |last1=Dolev |first2=M. |last2=Oltean |title=Optical Supercomputing: 4th International Workshop, OSC 2012, in Memory of H. John Caulfield, Bertinoro, Italy, July 19–21, 2012. Revised Selected Papers |url=https://books.google.com/books?id=Sy-7BQAAQBAJ |date=2013 |publisher=Springer |isbn=978-3-642-38250-5}}
* [https://web.archive.org/web/20090913002603/http://www.newscientist.com/article/mg19526136.400-speedoflight-computing-comes-a-step-closer.html Speed-of-light computing comes a step closer] ''New Scientist''
* {{cite journal |author= Caulfield H.|author2= Dolev S.|title= Why future supercomputing requires optics| journal= Nature Photonics| volume=4 |issue= 5|pages=261–263 |date=2010 |doi=10.1038/nphoton.2010.94}}
* {{cite journal |author= Cohen E.|author2= Dolev S.|author3=Rosenblit M.| title= All-optical design for inherently energy-conserving reversible gates and circuits| journal= Nature Communications| volume=7 |pages=11424 |date=2016 |doi=10.1038/ncomms11424 | pmid=27113510 | pmc=4853429|bibcode=2016NatCo...711424C}}
* {{cite book |first1=Yevgeny B.|last1=Karasik |title=Optical Computational Geometry |url=https://www.amazon.com/Optical-Computational-Geometry-computational-constructions-dp-B095MQJ8NJ/dp/B095MQJ8NJ |date=2019 |isbn=979-8511243344}}

==External links==
* [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]

{{emerging technologies|topics=yes|infocom=yes}}
{{Photonics}}

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

{{Sourceattribution|Optical computing}}