Waveform-Based Computer Language for Data Compression and Optical Computing
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Solution Overview
Problem
Current computer technologies face limitations in data representation and processing due to the binary number system, which requires extensive memory and time for data communication and can lead to inaccuracies, especially as transistor sizes approach molecular and atomic levels, necessitating advancements in computer languages and data compression for faster and more efficient computing.
Innovation Solution
A computer language and code that utilizes waveforms, specifically square and sine waves in the electromagnetic spectrum, to represent and communicate data, allowing for reduced bit usage and enabling optical and quantum computing capabilities, including data compression methods that use logarithmic and prime number representations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If the binary number system is used to represent and communicate data, then data can be stored and processed using conventional digital devices, but extensive memory and time are required for data communication and processing
Solution Approach 1:
The patent replaces the conventional binary digital system (mechanical/electrical switching of transistors) with an optical system using photons and waveforms. This substitution enables parallel processing of multiple data elements simultaneously, dramatically reducing memory requirements while increasing processing speed. The optical system uses properties of light such as wavelength, frequency, and phase to encode multiple bits of information in a single photon stream.
Solution Approach 2:
The patent introduces additional dimensions for data encoding beyond the traditional binary 0/1 states. By utilizing waveform properties such as amplitude, frequency, phase, and polarization, the system can represent multiple states simultaneously, effectively adding dimensional capacity to the data representation. This allows exponential reduction in the quantity of data required to represent the same information.
2Device complexity
If transistor sizes are reduced to increase computing density, then more transistors can be packed into limited space, but the transistors approach molecular and atomic levels causing inaccuracies and limitations
Solution Approach 1:
The patent replaces the mechanical transistor switching system with an optical photon-based system. This eliminates the physical limitations of transistor miniaturization, as photons do not suffer from the same quantum mechanical effects and manufacturing tolerances that plague sub-10nm transistors. The optical system maintains reliability while achieving higher density through parallel processing capabilities.
Solution Approach 2:
The patent changes the fundamental operating parameters from electrical resistance-based switching to optical wave properties. By using wavelength, frequency, and phase as the basis for data encoding rather than voltage states, the system avoids the reliability issues inherent in scaled-down transistor operation while maintaining high density through efficient data representation.
3Loss of time
If the binary system is used for data communication, then data can be transmitted using square waves with amplitude representation, but data must be communicated sequentially consuming substantial time and memory
Solution Approach 1:
The patent adds temporal and spectral dimensions to data communication by using waveform modulation techniques. Multiple data elements can be encoded in different frequency bands or time slots within a single communication channel, enabling parallel transmission that dramatically reduces communication time while decreasing the memory buffer requirements for sequential processing.
Solution Approach 2:
The patent transitions from discrete binary state transitions to continuous waveform modulation. This allows for smooth, uninterrupted data transmission where information is encoded in the continuous parameters of the waveform (amplitude, frequency, phase), eliminating the start-stop nature of sequential binary communication and enabling sustained high-speed data flow with reduced buffering requirements.
Data Source
AI summary
The present disclosure relates to a computer language and code for software application development, data compression, and use with conventional, optical, hybrid electro-optical and quantum computers.