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Preprint . 2025
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2025
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2025
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2025
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2025
License: CC BY
Data sources: Datacite
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RGE-256: A New ARX-Based Pseudorandom Number Generator With Structured Entropy and Empirical Validation

Authors: Reid, Steven;

RGE-256: A New ARX-Based Pseudorandom Number Generator With Structured Entropy and Empirical Validation

Abstract

This paper introduces RGE-256, a new 256-bit ARX-based pseudorandom number generator (PRNG) designed to promote strong internal state diffusion through a structured combination of modular addition, rotation, XOR operations, and cross-coupled mixing flows. RGE-256 employs a dual-quad state update mechanism with cascaded nonlinear mixing, incorporates a geometric rotation schedule derived from Recursive Division Tree (RDT) entropy constants, and supports an optional BLAKE3-based whitening layer applied to output blocks. We evaluate RGE-256 using the full Dieharder test suite (114 tests), along with avalanche analysis, autocorrelation measurements, and bit-distribution analysis. Comprehensive streaming validation shows that all RGE-256 variants complete Dieharder without failures, pass the full SmokeRand default battery (42 tests) with Quality 4.0 ratings, and process approximately 145 GB per core. Internal measurements indicate near-maximal entropy (7.999999 bits per byte), an ideal avalanche effect (15.97 bits), and near-zero autocorrelation. Independent testing further reports successful completion of TestU01 BigCrush and PractRand testing up to 1 TiB of output.

Keywords

prng, Pseudorandom number generation ARX design, ; statistical randomness testing, SmokeRand, structured entropy, Dieharder

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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