001 | 154942 | ||
005 | 20210129213958.0 | ||
024 | 7 | _ | |a 10.1142/S0129183114300036 |2 doi |
024 | 7 | _ | |a 1793-6586 |2 ISSN |
024 | 7 | _ | |a 0129-1831 |2 ISSN |
024 | 7 | _ | |a WOS:000340603000001 |2 WOS |
024 | 7 | _ | |a altmetric:2010196 |2 altmetric |
037 | _ | _ | |a FZJ-2014-04152 |
082 | _ | _ | |a 530 |
100 | 1 | _ | |a Michielsen, K. |0 P:(DE-Juel1)138295 |b 0 |e Corresponding Author |u fzj |
245 | _ | _ | |a Event-based simulation of quantum physics experiments |
260 | _ | _ | |a Singapore [u.a.] |c 2014 |b World Scientific |
336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1407767344_30536 |2 PUB:(DE-HGF) |
336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
336 | 7 | _ | |a ARTICLE |2 BibTeX |
336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
336 | 7 | _ | |a article |2 DRIVER |
520 | _ | _ | |a We review an event-based simulation approach which reproduces the statistical distributions of wave theory not by requiring the knowledge of the solution of the wave equation of the whole system but by generating detection events one-by-one according to an unknown distribution. We illustrate its applicability to various single photon and single neutron interferometry experiments and to two Bell-test experiments, a single-photon Einstein–Podolsky–Rosen experiment employing post-selection for photon pair identification and a single-neutron Bell test interferometry experiment with nearly 100% detection efficiency. |
536 | _ | _ | |a 411 - Computational Science and Mathematical Methods (POF2-411) |0 G:(DE-HGF)POF2-411 |c POF2-411 |f POF II |x 0 |
588 | _ | _ | |a Dataset connected to CrossRef, juser.fz-juelich.de |
700 | 1 | _ | |a De Raedt, H. |0 P:(DE-HGF)0 |b 1 |
773 | _ | _ | |a 10.1142/S0129183114300036 |g Vol. 25, no. 08, p. 1430003 - |0 PERI:(DE-600)2006526-7 |n 08 |p 1430003 - |t International journal of modern physics / C |v 25 |y 2014 |x 1793-6586 |
909 | C | O | |o oai:juser.fz-juelich.de:154942 |p VDB |
910 | 1 | _ | |a Forschungszentrum Jülich GmbH |0 I:(DE-588b)5008462-8 |k FZJ |b 0 |6 P:(DE-Juel1)138295 |
913 | 2 | _ | |a DE-HGF |b Key Technologies |l Supercomputing & Big Data |1 G:(DE-HGF)POF3-510 |0 G:(DE-HGF)POF3-511 |2 G:(DE-HGF)POF3-500 |v Computational Science and Mathematical Methods |x 0 |
913 | 1 | _ | |a DE-HGF |b Schlüsseltechnologien |l Supercomputing |1 G:(DE-HGF)POF2-410 |0 G:(DE-HGF)POF2-411 |2 G:(DE-HGF)POF2-400 |v Computational Science and Mathematical Methods |x 0 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF2 |
914 | 1 | _ | |y 2014 |
915 | _ | _ | |a JCR/ISI refereed |0 StatID:(DE-HGF)0010 |2 StatID |
915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |
915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0110 |2 StatID |b Science Citation Index |
915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0111 |2 StatID |b Science Citation Index Expanded |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Thomson Reuters Master Journal List |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1040 |2 StatID |b Zoological Record |
920 | _ | _ | |l yes |
920 | 1 | _ | |0 I:(DE-Juel1)JSC-20090406 |k JSC |l Jülich Supercomputing Center |x 0 |
980 | _ | _ | |a journal |
980 | _ | _ | |a VDB |
980 | _ | _ | |a I:(DE-Juel1)JSC-20090406 |
980 | _ | _ | |a UNRESTRICTED |
Library | Collection | CLSMajor | CLSMinor | Language | Author |
---|