Scalable, Room Temperature, Cheap Quantum Computing could compromise cryptography with Project METRONOME
The key to scalable cheap room temperature quantum computing is likely to not come from expensive cyrogenics, lasers, or exotic topological codes, but might already be available at room temperature and scale - something optimized through millions of years of evolution. Testing this hypothesis directly is the aim of Project METRONOME and could undermine cryptography as we know it.
Evidence has been accruing that neural tissue requires nonclassical physics to explain behavior. At only 20 watts, electrochemical theories cannot adequately explain how the brain processes memory, achieves perceptual binding across disparate regions, and achieves the equivalent of backpropagation. Max Tegmark famously wrote a rebuke that quantum theories of mind could be viable, claiming that the "warm wet and noisy" tissue would cause any quantum system to rapidly decohere - especially at scale. Many classical theories have been proposed, but none explain newer evidence.
Superradiance has been observed in the tissue, and it is known that long term potentiation and long term depression is modulated by light. Experiments with Xenon isotopes in anesthetics found that the isotope of Xenon used modulated anesthetic potency which is difficult to explain unless an optical/spin physics is implicated in the way in which the brain processes information.
In my discussions with Dr. Frank Barnes at CU he commented that evidence does clearly show there are biophotonic signaling pathways are critical for various cellular processes, and theories that treat the neuron as a classical logic gate fail to adequately explain complex learning behavior found in single celled organisms. The premise of Projects SIDECHANNEL and BLUEBIRD under the GATE research program under the supervision of Dr. Peter Hore at Oxford University are designed specifically to test this hypothesis and its role in avian magnetoreception (unfortunately I've been banned from CU Boulder since 2019 for correctly criticizing the inconsistencies in which the covid restrictions were rolled out which is a larger problem of policing speech at the University).
Furthermore, current models do not explain complex behaviors that cannot currently be replicated by AI models that are critical towards social development and adjustment in people like interbrain synchrony, which is measured in hyperscanning studies. As a part of the AI business model, it must collect information en masse and then sell it back to individuals at a price with a binary logic gate - but has already run into thermodynamic limits of scale. The physics by which people interact, socialize, and communicate may prove to be much more efficient at scale than AI systems which do not share the collective consciousness and collective effervesence characteristic of groups of people at the fundamental level of physics.
The emerging fields of quantum econophysics and quantum sociophysics already show that human behavior is not characteristic of what would be expected from any classical system - and that decision trees display statistical properties consistent with interferencs patterns. This is a profound observation that could prove that the very physics which makes AI inefficient and thermodynamically limited and energy inefficient at scale is the same physics that is embedded within its business model and ultimately doomed to fail.
While previous theories have been criticized, such as Dr. Penrose's Orch-OR theory that suggests gravity could be critical towards understanding the perceptual binding problem on the grounds that the gravitational force is far too weak, as the force that warps spacetime itself it also governs the fabric all other systems operate - and thus also sets thermodynamic bounds on information stored in regions of space (entropic/thermodynamic gravity) which signal phase transitions which could be critical towards understanding the role that cascades of superradiant majorana-like biophotons with a property called orbital angular momentum might play. Understanding this physics would explain why the brain is so efficient at only 20 watts and help us to understand what differentiates is from machines.
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