<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>

COPY SCRIPT

For further information contact us at helpdesk@openaire.eu

Black-hole evaporation from the perspective of neural networks

Name: Black-hole evaporation from the perspective of neural networks
Creator: Ivan Arraut
Keywords: High Energy Physics - Theory, Quantum Physics, High Energy Physics - Theory (hep-th), Quantum Gases (cond-mat.quant-gas), 0103 physical sciences, FOS: Physical sciences, Condensed Matter - Quantum Gases, Quantum Physics (quant-ph), 01 natural sciences

descriptionPublicationkeyboard_double_arrow_right Article , Preprint , Other literature type 10 Dec 2018Embargo end date: 01 Jan 2019Publisher:IOP PublishingJournal:EPL (Europhysics Letters), volume 124, page 50,002 (eissn: 1286-4854,

Authors: Ivan Arraut;

doi: 10.1209/0295-5075/124/50002 , 10.48550/arxiv.1901.00731

arXiv: http://arxiv.org/abs/1901.00731

Black-hole evaporation from the perspective of neural networks

- Summary
- Subjects
- Metrics

Abstract

We study the black-hole evaporation from the perspective of neural networks. We then analyze the evolution of the Hamiltonian, finding in this way the conditions under which the synapse connecting the neurons changes from gravitatory to inhibitory during the evaporation process.

4 pages, Published version

Related Organizations

Open University of Hong Kong
China (People's Republic of)

Keywords

High Energy Physics - Theory, Quantum Physics, High Energy Physics - Theory (hep-th), Quantum Gases (cond-mat.quant-gas), FOS: Physical sciences, Condensed Matter - Quantum Gases, Quantum Physics (quant-ph)

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	9
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average

Found an issue? Give us feedback

Top 10%

Average

Green

bronze

Fields of Science

Fields of Science