Arithmetic Using Simulated Qubits - Brain Theory from a Circuits and Systems Perspective - page 112

Chapter 7
Arithmetic Using Simulated Qubits
Introduction
Arithmetic is generally accomplished by continually swapping the contents of local
registers and random access memory, running all numbers through a central
processor to build a result. Unfortunately this is inefficient, and impractical in a
neural environment. The register-stationary manipulations of controlled toggles are
far more efficient, plus they are biologically convenient. Registers of simulated
qubits operating as controlled toggles also happen to be logically reversible, with
implications for lower energy dissipation. Controlled toggles directed by codes
taken from long-term memory are well suited to massively parallel brain
computations.
Simulated qubits imitate, to some extent, the logical nature of real qubits. In
particular, with the aid of interneurons, they may support a system of unconditional
toggles (UT), single controlled toggles (SCT), and multiple controlled toggles
(MCT).
Physics parlance has used the term “NOT” in place of the term “toggle.” To
them, for example the UT is called UN, or unconditional NOT. Names are impor-
tant; so for the record, NOT refers to an inverter whose output depends on a
nonlinear way on a steady input such that the output maps to the input. A NOT
gate has no memory whatsoever.
In contrast, a toggle device is a memory device; it remembers its most recent
value. A toggle has no input although it is innately capable of being triggered by a
brief pulse to change states. Once established, output is held indefinitely, or at least
until power is removed. The differences between a NOT and a toggle are
fundamental.
Each simulated qubit may be configured to be in a given logic state with 100 %
probability. A toggle means a switch to the opposite logic state with 100 %
probability. Thus, true goes to false, and vice versa.
Image priority follows by adding the weighting factors that are associated with
important attributes in an image, such as indicators of danger. Calculations are