Papers
Random Number Generation, Theory and Uses
Around January, 1994, inventor and entrepreneur Scott A. Wilber became acutely interested in developing Mind-Matter Interaction (MMI) into a practical science with real-world applications. An essential technology for this development as we currently understand it is the true random number generator. Since appropriate generators were not commercially available at the time, Mr. Wilber designed and built his first prototype hardware random generator, shown to your left. It used a thermal noise source and provided random signals to a computer through an analog-to-digital converter. Mr. Wilber subsequently developed his generators into mass-producible form for commercialization.
Random Numbers Simplified
Random Numbers are numbers you can’t guess or predict by any algorithm. A measurement of something naturally random is required to produce a random number. Random numbers are also described as true, truly, hardware, nondeterministic or quantum.
Entropy, Predictability and Post-Quantum RNG Design
The emergence of quantum computers and potential quantum eavesdropping may make many of the current methods of encryption and information security obsolete within a very few years [MOS15, NI16a]. A clear understanding of the fundamentals of randomness and random number generators is required to address the ever-changing needs of security designers. The proper use of entropy can make certain “chaotic” generators as unpredictable as any quantum RNG, while typically used deterministic post processing methods can result in an overestimation of nondeterminism. Post-quantum randomness may also need to take into account quantum nonlocality, which puts special new requirements on the design of random number generators.
Entropy Analysis and System Design for Quantum Random Number Generators in CMOS Integrated Circuits
A quantum random number generator is implemented in an integrated circuit without the need for complex, bulky and expensive measurement equipment and circuitry. Quantum entropy, chaotic entropy and pseudo-entropy are defined and their combinations mathematically described. Models and design equations are provided for estimating the quantum entropy in the form of shot noise due to sub-threshold leakage, gate tunneling leakage and junction tunneling leakage in MOS transistors and CMOS IC’s.
The CryptoStrong™ Random Number Generator
The development of quantum computers will soon provide a means of weakening or breaking many currently used encryption methods. The CryptoStrong random number generators provide the highest level of unpredictability and reliability available. The Model CS128M includes an entropy source provably surpassing the security of any other known generator, and cryptographic post-processing comprising an AES-256 encryption module as defined by both NIST and the German AIS-20/31. Strong tamper resistance prevents reading or changing firmware and hardware design provides high resistance against side-channel attacks.
Statistical Test Suite for True Random Numbers
The QNGmeter is a continuous real-time statistical tester that uses five powerful and fundamentally different tests on the input data. Unlike other statistical test suites, it is designed to measure the quality of randomness of a continuous sequence of bits up to hundreds of terabits in length (real example shown at 710 trillion bits). The QNGmeter automatically performs metatests of subsequences, which would have to be done manually using other popular test suites. In addition, all popular test suites fail when testing large sequences due to errors or inadequacies in the statistical models used – regardless of the quality of random numbers tested.
Mind-Matter Interaction Technology & Theory
Advances in Mind-Matter Interaction Technology: Is 100 Percent Effect Size Possible?
Very high-speed random number generators in conjunction with amplification algorithms can greatly enhance the measurements of anomalous effects and anomalous cognition. These measurements must be statistically significant and develop rapidly to become relevant and be useful in our everyday experience. Mathematical models based on a random-walk bias amplifier and experiments using GHz to THz true random bit generators hint at the possibility measurements of mentally-influenced outputs of these generators can produce results approaching 100 percent of the corresponding intended outcomes, and at trial rates around one to two per second. Our experiments indicate feedback of results should optimally occur within about a quarter of a second of the generation of each trial so a trend may be noticeable in just a few seconds. Further, it is important the effect size be above a threshold of about 4 to 5 percent – but preferably much higher – to be psychologically “impressive.”
Intelligence Gathering Using Enhanced Anomalous Cognition
The capability to gather and correctly interpret hidden information is a critical resource to gaining and maintaining an advantage in any highly competitive environment. Methods are described which employ trained operators utilizing objective electronic equipment to obtain information that is hidden or not inferable from known data. The equipment contains quantum mechanical elements, which respond directly to the operators’ visualized outcome, producing a type of machine-enhanced cognition. The cognition is anomalous because it is not limited by the classical constraints of sensing equipment or direct observation.
Machine-Enhanced Anomalous Cognition
For at least 45 years researchers have studied the statistical properties of electronic true random number generators for signs of anomalous mental phenomena. Research published over this period shows no significant increase in Effect Size or degree of mental influence, expressed in terms of a derived Information Rate. Methods are presented for increasing the Information Rate by 1,000 to 10,000 times previous levels by using a type of bias “amplifier” with a statistical efficiency approaching 100%, bringing Machine-Enhanced Anomalous Cognition into the realm of practical applications.
