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A pre-calculating computer system

that operates on the logic of color


© W. J. Tomosky



I am proposing a computer that does not use a numbered base such as binary, octal or hexadecimal.


I am proposing a computer that runs on the logic of color. I have chosen the Lab Color Space1 for its fine granularity.


The Lab Color Space may be broken into several partitions2; e.g.,  1, 2, 3 or 4.


1     color-space-1








color-space-2      2









Any section may be used for mapping knowledge bases, micro instructions, programming instructions and floating point instructions. Therefore, any section may be arbitrarily sub-divided into four other sections. 3 This division could go on infinitesimally according to the user’s needs.


color-space-3    3  







We may then arbitrarily assign different types of instructions to different sub-divisions of quadrant 1; 1a for mapping knowledge bases, 1b for micro instructions, 1c for programming instructions and 1d for floating point instructions.4


  color-chart  4 









Note the fine color granularity in each of the subsections in quadrant 1. This allows each hue to be mapped to not only a specific type of instruction but for an individual instruction.


Example; Let us assume that we wished to add two floating point numbers together. The instructions and data would be accessed. There would be an associated color that has been identified when this instruction was link-edited. This link edited color would automatically pass control to the “knowledge base map” which in turn would pass control, via the cloud, to a knowledge base that had stored all previously calculated combinations of floating point instructions. That would allow the computer to know whether this specific operation and numerical values had previously been calculated. If so, the answer would be automatically be retrieved. This would save calculation time. If not, the calculation would be accomplished and then stored on the data base for the next query. This would be a sort of Object Oriented Programming with the results of the calculation stored for the next user. In other words all machines who wished to do a specific calculation would immediately know if it has been previously computed or not. If yes, then the result would be automatically retrieved thus avoiding a potentially time consuming calculation. If no, then the calculation would be completed and stored locally for the next instance that ANY computer wished to use the results. Thus it would become another data base holding pre-calculated data.


This supposes that there are knowledge bases of all types; logarithmic tables, trigonometric tables, previously calculated tables, archaeological data bases, literary data bases, optical character/facial  recognition data bases, etc. Over time, all known epistemological elements could be efficiently stored and quickly retreived.



Color Reception and Management


We will first need to replace the Arithmetical Logic Unit (ALU) of the digital computer with a logic device that recognizes color as well as grey scale; we will call this the Color Logic Unit (CLU). For this we will first require a “front end” system of rods and cones4 to simulate the construction of the eye.









4 https://www.youtube.com/watch?v=jnTLcj6BDKE


The “Argus II” has been FDA approved and therefore it or other follow-on systems could be used to solve this problem. The Argus II works by substituting a small array of electrodes for the light-sensing cells that normally react to light by sending an electric signal toward the back of the retina. Those signals are relayed to the optic nerve behind the eye, and travel back along the nerve to the brain.5


5 http://www.popsci.com/technology/article/2013-02/worlds-first-bionic-eye-receives-fda-approval


This page described the front end of the CLU. The back end must make sense of these signals. For the back end of the CLU we need a comparator unit to simulate the brain. For purposes of reliability I suggest that three comparator units be used in parallel and that a voting system selects the correct results. For example if comparator #1 and #2 agree but the results of #3 are different, then the results of #3 are disregarded. Likewise for any two comparators that agree. The odd result is always disregarded.


The following two abstracts define the basics of color comparison; spectrum management and refinement.


Multicolor cavity soliton.


We show a new class of complex solitary wave that exists in a nonlinear optical cavity with appropriate dispersion characteristics.6  The cavity soliton consists of multiple soliton-like spectro-temporal components that exhibit distinctive colors but coincide in time and share a common phase, formed together via strong inter-soliton four-wave mixing and Cherenkov radiation. The multicolor cavity soliton shows intriguing spectral locking characteristics and remarkable capability of spectrum management to tailor soliton frequencies, which would be very useful for versatile generation and manipulation of multi-octave spanning phase-locked Kerr frequency combs, with great potential for applications in frequency metrology, optical frequency synthesis, and spectroscopy.

6 http://www.ncbi.nlm.nih.gov/pubmed/27464131



Multi-color Cavity Metrology


This technique reduces the effect of the external seismic disturbances by four orders of magnitude and promises to greatly enhance the stability and reliability of the current generation of gravitational wave detector. The possibility for using multi-color techniques to overcome current quantum and thermal noise limits is also discussed.7


7 http://inspirehep.net/record/1113693/



We now have a front end color recognition system and a method for determining and correcting color reliability. This correction method is much like the correction algorithms that discover and correct ‘parity errors’ in digital computer systems.


Selecting a Color Space


Due to the fact that each color quadrant is defined by its intention (instruction type or data) we only need to focus on the finely granulated colors that we so choose from our Lab Color Space.











Three “guns” select the finely granulated colors that the user chooses. The guns are lasers which are ‘aimed’ by a plasma based optical system. This avoids mechanical movement. The lasers can then be pointed at any minute point on the Lab Color Space to select any instruction and its required corresponding data.8  Laser #1 selects the instruction, laser #2 selects the first data operand (if data is needed for this instruction) and likewise laser #3 selects the second data operand if data is required. This eliminates the need for registers to be loaded prior to the instruction being executed; all is done in parallel. 


 optically-aimed-laser   8











The three receiver/decoders9 described as the Color Reception and Management system, ibid, are also matched by a plasma optical system that receives the colors (instructions and data) that were projected by the laser guns.



  color-reception-and-management    9  












All distortion caused by the parallax between the laser and the Lab Color Space will be controlled by the Multicolor cavity soliton and Multi-color Cavity Metrology methods; ibid.


This system could be also be used to help map thought processes. Until there is an ability to recognize minute thought processes the ability to follow eye movements could be mapped. Eye movements would control the laser pointer and the computer would operate on instructions and data.


Consider the example of the ophthalmologist’s “Field of Vision” test where many points of the retina/optic nerve can be tested to find blind spots in the patient’s vision.


An example may be to map what the brain may be doing as a human scans a piece of artwork. Or the eye movements of an architect may be converted to determine what he discerns as opposed to what he ignores (determines not to be useful). This type of mapping could also prove useful in medical, psychological and psychiatric diagnosis. The doctor could study a printed diagnosis much after the patient has been examined.


There exist an infinite number of diagnostic applications from mechanical diagnosis to aptitude diagnosis.


The previous description utilized flat planes. The next description utilizes spherical surfaces.


Additional speed may be added to the computer by using a multiple “eye” laser system that would algorithmically choose the next set(s) of data or instructions that “may” be required. In other words this is a look-ahead system that would prepare the next instruction and data while the current instruction is being executed.


This unit would use a spherical color space that would enclose multiple Argus II systems 10.