Random Number Generator Using Analog Noise Sampling
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Solution Overview
Problem
Existing random number generators, particularly pseudo-random number generators, are vulnerable to prediction and compromise due to their deterministic processes, and true random number generators using analog circuitry are costly, difficult to produce, and not portable.
Innovation Solution
A system that generates random numbers from multiple real events, such as gate delays and relative phases, using non-deterministic information sources and sampling devices to capture entropy, which are amplified to produce substantially random numbers, even with inexpensive portable electronic components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If pseudo-random number generators are used, then they are easy to implement and portable, but they are vulnerable to prediction and compromise due to deterministic processes
Solution Approach 1:
The patent replaces deterministic mechanical/logic operations with physical phenomena (thermal noise, shot noise) that are inherently non-deterministic. The random number generator uses analog circuitry to harness these physical effects, substituting predictable digital logic with unpredictable physical processes to achieve true randomness while maintaining portability.
Solution Approach 2:
The patent changes the fundamental parameter of randomness generation from deterministic algorithmic processes to non-deterministic physical processes. By operating in the analog domain and utilizing physical noise sources, the system transforms the nature of random number generation from predictable computation to unpredictable physical measurement.
2Reliability
If true random number generators using analog circuitry are used, then they provide non-deterministic random numbers, but they are costly and difficult to produce
Solution Approach 1:
The patent employs inexpensive analog components (resistors, capacitors, operational amplifiers) that can be easily manufactured and replaced. Rather than using complex, expensive specialized hardware, the invention uses common electronic components to generate true random numbers, making the system both affordable and easy to produce while maintaining non-deterministic operation.
Solution Approach 2:
The patent replaces complex manufacturing requirements with simple analog circuit implementations. By using standard electronic components and well-understood physical phenomena (thermal and shot noise), the invention eliminates the need for specialized, difficult-to-manufacture hardware while achieving true random number generation.
3Reliability
If analog circuits with high voltage gain are used to amplify thermal or shot noise, then random numbers can be generated, but the output of the operation amplifier could become permanently saturated rendering the random number generator inoperable
Solution Approach 1:
The patent incorporates preventive design measures to avoid saturation before it occurs. By carefully selecting component values, biasing conditions, and gain settings during the design phase, the system is pre-configured to operate within safe margins that prevent saturation from thermal or shot noise amplification, ensuring continuous operational stability.
Solution Approach 2:
The patent uses feedback mechanisms to monitor and control the operation amplifier output, preventing saturation. By implementing feedback loops that detect approaching saturation conditions and adjust operating parameters accordingly, the system maintains stable operation while continuously generating random numbers from amplified thermal or shot noise.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system produces robust, unpredictable random numbers that are resistant to prediction and bias, overcoming the limitations of traditional generators by leveraging unique characteristics of independent information sources and amplifying error vectors for entropy capture.
Implementation Method 1
A source of entropy may be captured at each sampling interval
Implementation Method 2
A random number generator may amplify the error in measurement of each real event. Since the error vector is random, a source of entropy is captured at each sampling interval
Data Source
AI summary
A system is described for generating random numbers. The system may include a plurality of information sources and one or more sampling devices coupled to each of the information sources. Each information source may have a characteristic which may differ from the characteristic of any other information source. The sampling devices may sample the information sources at some sampling interval. A sample value may be captured from each of the information sources by the sampling devices coupled thereto at the sampling interval. An output representative of a substantially random number may be derived from the sample values captured at the sampling interval.