An integrated photonics engine for unsupervised correlation detection.


Journal

Science advances
ISSN: 2375-2548
Titre abrégé: Sci Adv
Pays: United States
ID NLM: 101653440

Informations de publication

Date de publication:
03 Jun 2022
Historique:
entrez: 1 6 2022
pubmed: 2 6 2022
medline: 2 6 2022
Statut: ppublish

Résumé

With more and more aspects of modern life and scientific tools becoming digitized, the amount of data being generated is growing exponentially. Fast and efficient statistical processing, such as identifying correlations in big datasets, is therefore becoming increasingly important, and this, on account of the various compute bottlenecks in modern digital machines, has necessitated new computational paradigms. Here, we demonstrate one such novel paradigm, via the development of an integrated phase-change photonics engine. The computational memory engine exploits the accumulative property of Ge

Identifiants

pubmed: 35648858
doi: 10.1126/sciadv.abn3243
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

eabn3243

Auteurs

Syed Ghazi Sarwat (S)

IBM Research Europe, Säumerstrasse 4, 8803 Rüschlikon, Switzerland.

Frank Brückerhoff-Plückelmann (F)

Center for Soft Nanoscience, University of Münster, Busso-Peuss-Str. 10, 48149 Münster, Germany.

Santiago García-Cuevas Carrillo (SG)

Department of Engineering of Engineering, University of Exeter, Exeter EX4 4QF, UK.

Emanuele Gemo (E)

Department of Engineering of Engineering, University of Exeter, Exeter EX4 4QF, UK.

Johannes Feldmann (J)

Department of Materials, University of Oxford, Oxford OX26HT, UK.

Harish Bhaskaran (H)

Department of Materials, University of Oxford, Oxford OX26HT, UK.

C David Wright (CD)

Department of Engineering of Engineering, University of Exeter, Exeter EX4 4QF, UK.

Wolfram H P Pernice (WHP)

Center for Soft Nanoscience, University of Münster, Busso-Peuss-Str. 10, 48149 Münster, Germany.

Abu Sebastian (A)

IBM Research Europe, Säumerstrasse 4, 8803 Rüschlikon, Switzerland.

Classifications MeSH