Black-Hole evaporation from the perspective of neural networks
arXiv:1901.00731 · doi:10.1209/0295-5075/124/50002
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
References in corpus (9)
- Physics of Trans-Planckian Gravity
- Effects of energy dependent spacetime on geometrical thermodynamics and heat engine of black holes: gravity's rainbow
- Self-Completeness of Einstein Gravity
- Probing microstructure of black hole spacetimes with gravitational wave echoes
- Dynamics of Unitarization by Classicalization
- Gauge Assisted Quadratic Gravity: A Framework for UV Complete Quantum Gravity
- Finding Critical States of Enhanced Memory Capacity in Attractive Cold Bosons
- Critically excited states with enhanced memory and pattern recognition capacities in quantum brain networks: Lesson from black holes
- Classicalization Clearly: Quantum Transition into States of Maximal Memory Storage Capacity
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- Spin precession in the gravity wave analogue black hole spacetime
- Hawking radiation as a manifestation of spontaneous symmetry breaking
- On the loss of learning capability inside an arrangement of neural networks