Empirical Metrology Dataset for the Sigma Cryptographic Framework

Empirical Metrology Dataset for the Sigma Cryptographic Framework

This dataset contains the raw, structured empirical metrology outputs generated by the validation suite for the Sigma Framework—a hardware-adaptive, non-Markovian cryptographic architecture designed to mitigate entropic degradation in iterative algorithms (such as Key Derivation Functions and Proof-of-Work) via a monotonic Temporal Tensor and a constant-time ARX core (Ψ).

These machine-readable JSON files constitute the foundational raw data backing the figures and empirical claims presented in the associated paper. Specifically, this dataset substantiates two primary research domains:

Thermodynamic Performance & Phase Transitions: Raw execution latencies, asymptotic throughput scaling across microarchitectural boundaries, Proof-of-Work (PoW) temporal linearity (O(R)), and Hardware Performance Monitoring Unit (PMU) data detailing L1 cache confinement.

Cryptographic & Side-Channel Resilience: Rigorous validation outputs including Test Vector Leakage Assessment (TVLA) statistical arrays proving Constant-Time execution, Monte Carlo simulations for the Strict Avalanche Criterion (SAC) and Shannon stream entropy, as well as Transient Fault Injection results demonstrating Differential Fault Analysis (DFA) resilience.

All datasets were generated in isolated environments using the framework's native sigma.metrology.orchestrator pipeline, guaranteeing absolute traceability, data integrity, and open-source reproducibility.