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Fig. 4.16
Synchronized
simulated qubit forcing
identical sampled logic
outputs
Conclusions
This chapter has introduced brain memory elements and illustrated them with
physical circuits. These circuits employ circuit elements as necessary to explain
complex neural operations. Concepts using LTP partly explain biological long-term
memory, but there is also the possibility of recursive neurons for memory. Recur-
sive multivibrating neurons are compatible with known features of human memo-
rization, such as instant, photographic memory, and indefinitely long-lasting
memory. A combination of LTP and multivibration is proposed.
Recursive neurons with qubit properties are termed simulated qubits; they
simulate some, but not all, features of physical qubits. Of interest is that a single
neuron may simultaneously hold true and false with a given probability. Probabi-
listic logic is of interest scientifically and also biologically, such as for cue editing.
Simulated and physical qubits are compared in this chapter. It was noted that
simulated qubits lack the possibility of teleportation, whereas real qubits, if
entangled and physically separated, continue to be in communications without a
(known) physical medium. To achieve teleportation, it is necessary to maintain an
undisturbed quantum system, making it difficult in practice to separate qubits
appreciably.
Qubits within brain cells at the molecular level would increase mental abilities
by orders of magnitude, so this possibility is too important to ignore. Simulated
qubits might also be possible at the molecular level within a brain, without the
difficulty of maintaining a quantum system for significant duration in the face of
thermal agitation.
What is most important about simulated qubits is that they can produce con-
trolled toggles, as suggested by circuitry provided in this chapter, and simulations in
the appendix. Controlled toggling is important to arithmetic and may be important
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