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Classicalization is a phenomenon of redistribution of energy - initiallystored in few hard quanta - into the high occupation numbers of the soft modes,described by a final state that is approximately classical. Using an effectiveHamiltonian, we first show why the transition amplitudes that increaseoccupation numbers are exponentially suppressed and how a very special familyof classicalizing theories compensates this suppression. This is thanks to alarge micro-state entropy generated by the emergent gapless modes around thefinal classical state. The dressing of the process by the super-soft quanta ofthese modes compensates the exponential suppression of the transitionprobability. Hence, an unsuppressed classicalization takes place exclusivelyinto the states of exponentially enhanced memory storage capacity. Next, wedescribe this phenomenon in the language of a quantum neural network, in whichthe neurons are represented as interconnected quantum modes with gravity-likenegative-energy synaptic connections. We show that upon an injection of energyin form of a hard quantum stimulus, the network reaches the classicalized stateof exponentially enhanced memory capacity with order one probability. Weconstruct a simple model in which the transition results into classical statesthat carry an area-law micro-state entropy. In this language, a non-WilsonianUV-completion of the Standard Model via classicalization implies that abovecutoff energy the theory operates as a brain network that softens the highenergy quanta by bringing itself into the state of a maximal memory capacity. Asimilar interpretation applies to black hole formation in particle collision.

Classicalization Clearly: Quantum Transition into States of Maximal Memory Storage Capacity