Optical computing: Difference between revisions

Content deleted Content added
Citation bot (talk | contribs)
Alter: date, pmc, url, template type, title. URLs might have been anonymized. Add: eprint, class, hdl, pmid, pages, s2cid, bibcode, arxiv, publisher, authors 1-1. Removed proxy/dead URL that duplicated identifier. Removed parameters. Some additions/deletions were parameter name changes. | Use this bot. Report bugs. | Suggested by Flod logic | Category:CS1 maint: PMC format | #UCB_Category 17/20
WikiCleanerBot (talk | contribs)
m v2.05b - Bot T20 CW#61 - Fix errors for CW project (Reference before punctuation)
Line 71:
 
=== 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 an 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===