Data from Distinguishability (06-2018)

Interference lies at the heart of quantum mechanics and thus its promise of fundamental advantages over non-quantum technologies, with far-reaching ramifications in communication, metrology, sensing, simulation and computation. The nemesis of quantum interference is distinguishability, with the Hong-Ou-Mandel (HOM) effect being a prototypical example. Rather than the usual second quantized approach to such situations, we can gain insight by bringing quantum information concepts to bear in first quantization. Distinguishability can then be modelled, for example, as entanglement between controlled and uncontrolled degrees of freedom of individual particles, with loss of interference being caused by the decoherence that results when the uncontrolled Hilbert space is marginalized. This project deals with a variety of properties of distinguishability, from discrimination, through filtering, modelling loss, and boson sampling.

Creator(s) Peter Turner, Stasja Stanisic, Alexandra Moylett
Publication date 04 Jun 2018
Language eng
Publisher University of Bristol
Licence Non-Commercial Government License for public sector information
DOI 10.5523/bris.3bj7o4rqo2kxd2f8nnfdx5gw6p
Complete download (zip) https://data.bris.ac.uk/datasets/3bj7o4rqo2kxd2f8nnfdx5gw6p/3bj7o4rqo2kxd2f8nnfdx5gw6p.zip
Citation Peter Turner, Stasja Stanisic, Alexandra Moylett (2018): Data from Distinguishability (06-2018). https://doi.org/10.5523/bris.3bj7o4rqo2kxd2f8nnfdx5gw6p
Total size 72.9 MiB

Data Resources