2016
Journal article  Open Access

Simple indicators for Lorentzian causets

Bolognesi T., Lamb A.

General Relativity and Quantum Cosmology  Physics and Astronomy (miscellaneous)  Lorentzian manifold  Graph Theory  Emergence  Pseudo-randomness  Discrete spacetime automata  FOS: Physical sciences  Causal set  Quantum gravity  General Relativity and Quantum Cosmology (gr-qc) 

Several classes of directed acyclic graphs have been investigated in the last two decades, in the context of the causal set program, in search for good discrete models of spacetime. We introduce some statistical indicators that can be used for comparing these graphs and for assessing their closeness to the ideal Lorentzian causal sets ('causets') - those obtained by sprinkling points in a Lorentzian manifold. In particular, with the reversed triangular inequality of Special Relativity in mind, we introduce 'longest/shortest path plots',an easily implemented tool to visually detect the extent to which a generic causet matches the wide range of path lengths between events of Lorentzian causets. This tool can attribute some degree of 'Lorentzianity' - in particular 'non-locality' - also to causets that are not (directly) embeddable and that, due to some regularity in their structure, would not pass the key test for Lorentz invariance: the absence of preferred reference frames. We compare the discussed indicators and use them for assessing causets both of stochastic and of deterministic, algorithmic origin, finding examples of the latter that behave optimally w.r.t. our longest/shortest path plots.

Source: Classical and quantum gravity (Print) 33 (2016). doi:10.1088/0264-9381/33/18/185004

Publisher: IOP Pub., Bristol , Regno Unito


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BibTeX entry
@article{oai:it.cnr:prodotti:357864,
	title = {Simple indicators for Lorentzian causets},
	author = {Bolognesi T. and Lamb A.},
	publisher = {IOP Pub., Bristol , Regno Unito},
	doi = {10.1088/0264-9381/33/18/185004 and 10.48550/arxiv.1407.1649},
	journal = {Classical and quantum gravity (Print)},
	volume = {33},
	year = {2016}
}