Experimental Evidence Architecture

Typed Observable Registries, Uncertainty Decomposition, Data Lineage & Falsification Gates

Spine Position

Science Root · Experimental Evidence Governance, Observable Registries & Metrology

Public Status Boundary. This gateway defines the formal metrological and experimental standards of the Science of Fabric Reality. It establishes typed observable registries, mathematical uncertainty decomposition, cryptographic data lineage, and pre-registered falsification gates. It explains scientific methodology without asserting unacquired physical data.

$$\boxed{{\displaystyle \mathbf{\text{Protocol definition}}\ne \mathbf{\text{empirical validation}}}}$$$$\boxed{{\displaystyle \mathbf{\text{Simulation model}}\ne \mathbf{\text{detector acquisition}}}}$$$$\boxed{{\displaystyle \mathbf{\text{Active prospective predictions (P4)}}=\mathbf{0}(\text{Zero synthetic claims})}}$$

Figure 6.1 — Experimental Evidence Promotion Spine: Multi-stage metrological promotion pipeline enforcing explicit verification gates from protocol draft to independent laboratory replication.

Maps the ten-stage operational lifecycle of experimental observables from theoretical candidate and pre-registered protocol to data acquisition, frozen analysis, and independent replication.

Credit: Ivan Pasev / GILC Research·CC BY-NC-SA 4.0·SCHEMATIC

---

1. The 10-Stage Experimental Promotion Spine

Every physical quantity, spectral signature, or laboratory test in the corpus advances through a 10-stage lifecycle orthogonal to the theoretical P0–P6 evidence ladder:

Stage	Status Identifier	Operational Definition	Metrological Gate
1	OBSERVABLE_CANDIDATE	Physical quantity defined with SI units and theoretical mapping.	Observable contract drafted.
2	PROTOCOL_DRAFT	Initial design of excitation sources, detectors, and transfer functions.	Apparatus parameters specified.
3	PROTOCOL_FROZEN	Pre-registered experiment protocol sealed with cryptographic timestamp.	Immutable SHA-256 seal.
4	INSTRUMENT_READY	Physical apparatus, vacuum chambers, and diagnostics aligned in laboratory.	Pre-flight vacuum/optical check.
5	CALIBRATION_COMPLETE	Diagnostic channels calibrated against versioned reference standards.	NIST-traceable calibration file.
6	DATA_ACQUIRED	Raw detector signals captured and sealed immediately with SHA-256 hash.	Raw acquisition receipt.
7	DATA_QC_PASSED	Automated data quality screening (signal-to-noise, baseline stability).	QC audit pass script.
8	ANALYSIS_FROZEN	Signal deconvolution and uncertainty propagation executed deterministically.	Frozen analysis pipeline hash.
9	EMPIRICAL_RESULT	Processed observable compared against null and alternative hypotheses.	Falsification evaluation.
10	INDEPENDENT_REPLICATION	Protocol reproduced by independent laboratory team on external facility.	Blinded replication report.

---

2. The 7-Fold Uncertainty Decomposition Framework

To eliminate ambiguous error bars, all experimental measurements and numerical comparisons decompose uncertainty into seven orthogonal components:

$$\boxed{{\displaystyle u_c^2(y)=\sum _{i=1}^N{\left(\frac{\partial f}{\partial x_i}\right)}^2{u}^2(x_i)+2\sum _{i=1}^{N-1}\sum _{j=i+1}^N\frac{\partial f}{\partial x_i}\frac{\partial f}{\partial x_j}u(x_i,x_j)}}$$

Figure 6.2 — 7-Fold Uncertainty Decomposition Framework: Complete metrological uncertainty budget separating numerical solver errors from instrumental calibrations and external reference errors.

Details the rigorous decomposition of experimental and computational uncertainty into numerical, parametric, calibration, statistical, systematic, model, and reference error components.

Credit: Ivan Pasev / GILC Research·CC BY-NC-SA 4.0·SCHEMATIC

Component	Error Class	Physical / Computational Origin	Control & Evaluation Method
$U_{\text{NUM}}$	Numerical Discretization	Spatial/temporal grid spacing ($\mathrm{\Delta }x,\mathrm{\Delta }t$), domain truncation, floating-point roundoff	Richardson extrapolation, grid convergence tests (Residual $\ne$ Error)
$U_{\text{PARAM}}$	Input Parameters	Laser pulse energy jitter, beam waist uncertainty, target density variations	Monte Carlo parameter propagation, Jacobian sensitivity analysis
$U_{\text{CAL}}$	Calibration Reference	Diagnostic transfer function, detector spectral response curves, optical comb locks	Calibration against primary NIST standards
$U_{\text{STAT}}$	Statistical Measurement	Poissonian photon/ion counting noise, pulse-to-pulse shot noise	Standard error over protocol-defined independent acquisitions ($s/\sqrt{N}$)
$U_{\text{SYS}}$	Systematic Instrumental	Focal volume spatial integration, stray fields, parasitic thermal leaks	Apparatus variation, spatial deconvolution, differential subtraction
$U_{\text{MODEL}}$	Model Discrepancy	Theoretical approximations (dipole approximation, infinite nuclear mass, frozen core)	Cross-level comparison (non-relativistic $\to$ Dirac $\to$ QED)
$U_{\text{REF}}$	Reference Standard	Published uncertainty in external reference databases (NIST ASD v5.12, CODATA 2018)	Direct extraction from versioned metrological literature

Metrological Law: Solver Residual ≠ Numerical Uncertainty

An algebraic solver residual measures how closely a discrete algorithm satisfies an algebraic equation. Numerical uncertainty quantifies the difference between the discrete numerical solution and the continuous analytical truth. Conflating solver residuals with uncertainty is strictly prohibited.

---

3. Immutable Cryptographic Data Lineage

Every empirical dataset and analysis artifact follows a tamper-evident, hash-chained lineage:

Figure 6.3 — Immutable Data Lineage Pipeline: Cryptographically chained data transformation pipeline ensuring bit-level reproducibility and tamper-evident provenance.

Illustrates the cryptographic hash-chained provenance of experimental data from raw detector acquisitions to calibrated, quality-controlled, and analysis-ready datasets.

Credit: Ivan Pasev / GILC Research·CC BY-NC-SA 4.0·SCHEMATIC

[DATA LINEAGE CONTRACT]
├── RAW DATA (D_raw) -> SHA-256 sealed immediately upon acquisition
│   ↓ (Calibration Transfer Function: Script SHA-256)
├── CALIBRATED DATA (D_cal) -> Scaled into standard SI physical units
│   ↓ (Automated Quality Control: QC Script SHA-256)
├── QC PASSED DATA (D_qc) -> Filtered for noise thresholds and baseline drift
│   ↓ (Frozen Analysis Pipeline: Analysis Script SHA-256)
├── ANALYSIS READY DATA (D_ready) -> Formatted for statistical hypothesis evaluation
│   ↓ (Statistical Comparator: Reduction Script SHA-256)
└── DERIVED PUBLIC RESULT (D_pub) -> Final observable published with complete lineage

Each transformation record logs: inputSHA256, outputSHA256, scriptSHA256, environmentHash, timestampUTC, operator, parameters, and schemaVersion.

---

4. Pre-Registered Prediction Seal Protocol

To protect against hindsight bias and post-hoc parameter fitting, the Science of Fabric Reality enforces strict prediction sealing:

Figure 6.4 — Prospective Prediction Seal vs Calibrated Retrodiction: Strict epistemic firewall separating sealed prospective predictions from post-hoc calibrated retrodictions.

Contrasts prospective cryptographically sealed predictions (P4) with post-hoc calibrated retrodictions (P2), enforcing the epistemic firewall before empirical testing.

Credit: Ivan Pasev / GILC Research·CC BY-NC-SA 4.0·SCHEMATIC

• Prospective Sealed Prediction (P4): A mathematical prediction $Q_{\text{pred}}\pm \mathrm{\Delta }Q$ sealed with cryptographic SHA-256 before the acquisition of test data.
• Calibrated Retrodiction (P2): A model fit adjusted to match known historical or laboratory measurements.
• Current Corpus Truth: The active sealed prospective prediction count across the entire repository is:$$\text{ACTIVE\_P4\_SEALS}\mathbf{=}\mathbf{0}$$All existing numerical parameter matches (e.g. FQFT lepton masses) are explicitly classified as P2 Calibrated Retrodictions with zero residual degrees of freedom ($N_{\text{data}}=3,N_{\text{tuned}}=3,\text{DOF}=0$).

---

Figure 6.5 — Multiscale Scientific Evidence Lattice: Epistemic structure binding Lean 4 formalization targets, external consensus benchmarks, metrology-governance references, and experimental contract candidates.

Integrates formal Lean 4 verification targets, theoretical benchmarks, metrology-governance references, and experimental contract candidates.

Credit: Ivan Pasev / GILC Research·CC BY-NC-SA 4.0·SCHEMATIC

---

5. Experimental Canon Navigation & Reference Atlases

Explore the authoritative registries, reference atlases, and experimental testbeds:

• Public Master Reference Atlas & Citations → — Master public literature registry with BibTeX and CSL-JSON exports.
• Atomic Physics Reference Atlas → — NIST ASD v5.12, CODATA 2022, Drake 2006 helium benchmarks.
• Strong-Field Reference Atlas → — Corkum 1993, Lewenstein 1994 SFA, L'Huillier 1993, ADK 1986.
• Thermophysics Reference Atlas → — NIST IR emittance, PTB vacuum emissivity standards.
• Metrology & Uncertainty Reference Atlas → — JCGM 100:2008 (GUM), JCGM 100/Amd.1:2026, JCGM 101:2008, VIM 2.39/2.41.
• Research Data Reference Atlas → — NIST RDaF v2.0, FAIR Guiding Principles.
• Atomic Physics & Complexity Ladder → — Hydrogen, Helium, and isoelectronic sequences.
• LPFR Laboratory Interface → — High-intensity laser-plasma diagnostic loops.
• FSR Thermophysics & Metrology → — Cryogenic vacuum differential radiator testbeds.
• Simulation Atlas → — Numerical surrogates and solvers.

---

⚖

SOURCE AUTHORITY & BOUNDARY LOCK

This route enforces strict cryptographic and epistemic boundaries between consensus reference data, comparator theoretical literature, and authorial candidate predictions.

ESTABLISHED BASELINE

• NIST ASD v5.12 (2024-11-07)
  Versioned consensus spectroscopic transition data.
• CODATA 2022 (2025)
  Fundamental physical constants authority.

COMPARATOR LITERATURE

• Corkum 1993 / Lewenstein 1994 / L'Huillier 1993 (1993-1994)
  Strong-Field Approximation (SFA) baseline and macroscopic propagation cutoff.
• PTB 2009/2015 / NIST 2004 (2004-2015)
  Directional spectral emissivity metrology.

METROLOGY / DATA STANDARDS

• JCGM 100:2008 (GUM) / Amd.1:2026
  Law of propagation of uncertainty with full covariance.
• JCGM 101:2008 (Monte Carlo)
  Nonlinear propagation of distribution functions.
• NIST RDaF v2.0 / FAIR 2016
  Bit-level provenance and machine-actionable metadata.

AUTHORIAL EXTENSION BOUNDARY

EVIDENTIARY_GOVERNANCE_SYSTEM

Establishes formal metrological protocols and validation criteria. External consensus comparator sources define the baseline and do not constitute empirical validation of authorial field equations.

Explore Master Reference Atlas & Citations (BibTeX / CSL) →