Pragmatic Computational Randomness

Eightomic articulates the practical application of quantum-level entropy generated using internal temporal precision captured slowly from a classical TRNG algorithm.

Explanation

Computational randomness is the only way for humans to comprehend the origin of chaotic randomness in the universe.

While developing Entropy, a randomness generation pylon, Eightomic articulated the following efficient and error-resistant alternative to extracting bits of quantum randomness from collapsed qubits.

In quantum computing, the probability of capturing a result of either 0 or 1 after collapsing a superpositioned qubit is calculated with deterministic mathematical formulas.

These formulas depend on tangible quantum wave functions that leverage entropic oscillations from external interactions.

In lieu of quantum computing, hardware-generated activity is sufficient for cryptographic number generation in most instances, but all numbers captured from external, inconsistent, pre-captured interactions are non-random based on subjectivity to both overlap and theoretical proof that ignores fundamental laws of space and time.

True randomness must always be captured from a source that's always oscillating relative to the capturing program exclusively. In other words, it's either random consistently or it's not random at all.

Therefore, the only valid source of classical, theoretically-sound entropy is from constant computation that creates a consistent, deterministic range of CPU oscillations measured at a substantially-high precision relative to the low precision of the computed duration.

The aforementioned process creates a chaotic, intangible temporal pool that emits a tangible binary number representing the computed duration to be captured as a truncated bit of true entropy.

Temporal mechanics are clearly-defined with time as a simple measurement within the constraints of classical physics. Time changes at a linear interval with a huge amount of precision relative to the third dimension.

In practical implementations, the CPU must be confirmed to spend at least a few nanoseconds processing each % and / operation. Anything less would be approaching an irrelevant discovery of temporal transcendence.

Therefore, the pure chaotic factor isn't pollutable by hardware intervention or lack thereof with pre-captured noise.

For example, the following TRNG library implementation is capable of generating the same level of single-bit quantum entropy by combining classical and quantum computing methodologies.

It uses a computationally-expensive sequence of algorithms using the aforementioned pseudo-quantum principles that rely on temporal mechanics to generate 8-bit, random binary numbers. oscillate() simulates quantum waves and capture_entropy() simulates collapsed qubit.

It adheres to the C99 standard draft (ISO/IEC 9899:1999), although it's convertible to other programming languages and standards.

It's compatible with both 32-bit and 64-bit systems with the following requirements.

It requires a POSIX-compatible system with adherence to POSIX.1-2001, POSIX.1-2008 and SUSv2.

The system must have resilience to the year 2038 problem for implementations with long-term usage intent.

The clock_gettime() implementation must support high-resolution, system-wide clock reads with guaranteed nanosecond time precision using CLOCK_REALTIME. If this is unavailable or not guaranteed by the implementation, the std::chrono library in C++ may offer a sensible alternative.

It's impossible for the aforementioned TRNG to capture non-random, predetermined bits due to the verified temporal precision of the system clock on each implemented device far exceeding the fastest processing time of repeating computations between each random bit capture.

The conditional statement if (oscillation == 0) captures an additional random bit in rare instances to ensure oscillation doesn't pollute entropy while preventing compilers from unintentionally removing CPU oscillations.

The rare instance of system clock failure is handled by abruptly stopping with exit(EXIT_FAILURE), but alternate error handling methods may be appropriate in specific implementations, such as querying a trusted TRNG API.

The standard of true entropy in classical computing is now defined within the constraints of time. Theoretical randomness and denying the existence of free will beyond these computations is the topic of an irrelevant philisophical discussion.

Generating random-looking numbers to consistently pass statistical tests is an irrelevant, subjective concern, so it usually fails statistical randomness tests at all bit sizes after a few KB of output.

Therefore, the output creates reliable test vectors for researching and developing computational randomness analyses that ignore deterministic, random-looking distribution requirements.