Submitted:
12 November 2025
Posted:
14 November 2025
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Abstract
Keywords:
1. Introduction
1.1. Motivation
1.2. Foundational Puzzles as Threshold Phenomena
1.3. Scope and Structure
- Section 2 reviews the empirical and theoretical foundations of quantum emergence, highlighting three pillars: dual-threshold behavior in quantum materials, complexity measures that render computable, and emergent spacetime programs that link geometry to entanglement.
- Section 3 formalizes as , defines each parameter operationally, and extracts dual critical values directly from many-body localization (MBL) data.
- Section 4 translates those thresholds into cosmological language, showing how Big Bang regularization, time asymmetry, and dark-sector phenomena follow from staged emergence.
- Section 5 evaluates the framework against alternative proposals via a problem-solving matrix, quantifying strengths and remaining gaps.
- Section 6 lays out seventeen falsifiable predictions, organized by timescale and experimental feasibility, to keep the framework Popperian.
- Section 7 discusses the philosophical and cross-scale implications of layered emergence, including dimensional correlation patterns and cosmic metabolism.
- Section 8 summarizes the path forward, including data needs, collaborations, and dissemination plans.
2. Three Pillars of Quantum Emergence
2.1. Condensed-Matter and MBL Evidence
2.2. Quantum Information and Complexity Tools
2.3. Emergent Spacetime and Gravity Programs
2.4. Synthesis for
3. Formalism and Parameter Calibration
3.1. Definition of
3.2. Operational Definitions of Parameters
- Energy density (). For lattice systems we take = E/N, where E is the energy expectation value and N the number of degrees of freedom. Yin et al. (2024) proved the existence of a mobility edge for generic few-body Hamiltonians in terms of energy density, justifying the use of as a primary control knob [3]. In cosmology, corresponds to the local T_{00} component of the stress-energy tensor, making directly compatible with Friedmann dynamics.
- Complexity (). We operationalize through Krylov complexity. Starting from an operator O, the Lanczos algorithm generates coefficients {b_n} that quantify how O spreads across the operator basis. The Shannon entropy of the normalized coefficients, , gives [4,5]. This definition is experimentally accessible via out-of-time-order correlators and has been applied to superconducting qubit arrays and trapped ions. In tensor network language, tracks the logarithm of bond dimensions required to represent the state, linking complexity to entanglement structure [6].
- Entropy (S). We adopt the symmetric decomposition described by Chen et al. (2024): total von Neumann entropy separates into number entropy and configuration entropy , with [2]. The configuration component dominates near the MBL transition and therefore controls the suppression term . In practice S can be estimated via quantum state tomography or inferred from entanglement spectra.
- Global vs. local scales. Throughout the manuscript we distinguish between the global entropy scale nats (denoted simply as in the exponential ) that governs fully coarse-grained regions, and the local entropy scale nats (measured by Chen et al. 2024 at the MBL transition point for small subsystems). The local windows are nested within the global scale, reflecting the hierarchical nature of emergence. Examples quoting values around 10–12 nats refer to intermediate coarse-graining between these limits. For clarity, we use to denote the global scale (50 nats) unless explicitly specified as local.
- Critical exponents (, ) and entropy scale (). By fitting to numerical and experimental datasets—spanning Rydberg arrays, superconducting qubits, and exact diagonalization of Heisenberg chains—we find , , and nats (from combined regression yielding nats, rounded to for consistency). The sublinear exponents prevent runaway growth in and reflect diminishing returns in complexity contributions at high energy density.
| Parameter | Operational definition | Typical calibrated value | Primary source |
| Energy density per degree of freedom () or local | Critical density range 0.1–0.5 (natural units) | [3] | |
| Shannon entropy of normalized Lanczos coefficients | Logarithm of bond dimension (chi between and in benchmarks) | [4,5] | |
| S | Symmetry-resolved von Neumann entropy | Local critical entropy window 4–6 nats near transition | [2] |
| Energy-density exponent in fit | Central value | Combined regression (this work) | |
| Complexity exponent in fit | Central value | Combined regression (this work) | |
| Global entropy scale entering | Global critical entropy nats (local windows 4–6 nats nested) | Combined regression (this work) |
3.3. Dual Threshold Architecture
3.4. Computational Practice
- Diagonalize or simulate the Hamiltonian to obtain energy spectra and eigenstates, delivering and raw state vectors.
- Run the Lanczos procedure to generate Krylov coefficients and compute . For large systems we use tensor network compression to keep the basis manageable.
- Perform entropy estimation via reduced density matrices or entanglement spectroscopy, yielding and .
- Fit parameters using the supplementary fitting script (Appendix~Appendix I, entry I1) to minimise deviations between observed thresholds and predictions.
- Map across parameter space to locate regions corresponding to , , and .
3.5. Limits and Roadmap to Multi-Threshold Models
4. Cosmological Translation of Thresholds
4.1. Big Bang as Threshold Crossing
4.2. Arrow of Time from Complexity Selection
4.3. Dark Matter and Dark Energy as Partial Emergence
4.4. Measurement, Decoherence, and Quantum Gravity
4.5. Cosmic Metabolism and Open-System Cosmology
5. Problem-Solving Matrix
5.1. Evaluation Criteria
5.2. Framework Performance
5.3. Comparative Analysis
5.4. Anticipated Critiques and Responses
6. Falsifiability and Experimental Program
6.1. Popperian Framing
6.2. Near-Term Tests (2025–2030)
6.3. Mid-Term Tests (2030–2040)
6.4. Long-Term and Speculative Tests
6.5. Status Tracking and Risk Assessment
7. Philosophical Outlook and Cross-Scale Insights
7.1. Layered Ontology
7.2. Dimensions as Correlation Patterns
7.3. Open-System Metabolism
7.4. Beyond Physics
7.5. Limits and Outlook
8. Conclusion
8.1. Summary of Contributions
8.2. Outlook and Immediate Priorities
- Publish calibration assets: finalise the regression tables, release the scripts, and complete the LaTeX build so that others can reproduce , , and .
- Execute near-term tests: prioritise coherence-scaling measurements and CMB reanalysis, then target the gravitational-noise and Hawking-spectrum experiments as facilities come online.
- Probe higher thresholds: use the forthcoming data to refine the exponents of , search for additional levels, and examine the cross-disciplinary hypotheses outlined in Section 7.
8.3. Call for Collaboration and Review
8.4. Cross-Scale Interpretation
8.5. Consolidated Validation Snapshot
Data Availability
- Main data archive: https://zenodo.org/record/17589654 (DOI: 10.5281/zenodo.17589654)
- Supplementary materials: Included in zenodo_appendix.zip (I1–I25)
-
Specific datasets:
- -
- Parameter fitting data: Appendix I1, I7, I9
- -
- Trapped-ion measurements: Appendix I9, I18
- -
- Photonic decoherence: Appendix I15, I16, I17
- -
- Black-hole collapse analysis: Appendix I23, I24
- -
- Mathematical derivations: Appendix I21, I22
- Analysis scripts: Python scripts in Appendix I1, I11, I17, I19, I23
Code Availability
- fit_lambda_parameters.py (I1): Parameter calibration workflow
- atomic_lambda_simulation.py (I11): Atomic tuning simulations
- simulate_photon_decoherence.py (I17): Photonic Lindblad dynamics
- compare_lambda_constraints.py (I19): Constraint aggregation
- Black-hole reverse-engineering scripts (I23): Oppenheimer–Snyder and Tolman–Bondi analysis
Acknowledgments
Conflicts of Interest
Appendix A. Parameter-Fit Datasets
- Rydberg atom chain: Data from Rispoli et al. [12] calibrate and trace near the many-body localisation transition using 48 time-series segments sampled at 200 ns and detrended via polynomial fits.
- Superconducting qubits: Gong et al. [13] provide coherence-decay curves for 10–20 qubit arrays; Bayesian regression evaluates with a noise floor of .
- Random-graph simulations: García-Mata et al. [14] contribute eigenstate statistics across coordination ; Lanczos algorithms compute proxies and confirm .
- Exact diagonalisation: internal scripts (fit_lambda_parameters.py) diagonalise random-field Heisenberg chains up to , sampling 100 disorder realisations per h while tracking and .
- Tripartite entanglement (NMR): digitised negativity curves from Singh et al. [16] (Figure 5 and 8) cover GHZ, W, and states under XY-16/ decoupling; datasets reside in data/fig5_fig8_tripartite_negativity.csv.
- Photonic W-state decoherence: longitudinal Bell correlations from Berrada & Bougouffa [17] (Figure 2 and 3) benchmark Markovian and non-Markovian regimes; data live in data/symmetry2025_w_state_lbc.csv.
- Lindblad simulations: QuTiP runs (simulate_photon_decoherence.py) explore GHZ/W state decoherence under amplitude/phase damping for , producing data/ghz_w_lindblad_simulation.csv.
- Trapped-ion state tracking: NIST datasets (mds2-3216/2956/3389) with superconducting SNSPD readout populate quantumvalidation/data/raw/; processed metrics appear in research/results/trapped_ion_real_data_summary.csv and research/results/trapped_ion_lambda_mapping.csv.
Appendix B. Regression Procedure for α, β, and S crit
- Assemble observations from Appendix A and compute .
- Perform log-linear regression on to estimate and ; constrain via non-linear least squares.
- Bootstrap with 1000 resamples to obtain uncertainties: , , nats.
- Validate residuals across disorder fields h to confirm no systematic drift beyond .
Appendix C. Cosmological Conversion Factors
- Planck density: .
- Vacuum energy: implies .
- Hawking temperature: ; for , .
- Casimir energy density (parallel plates, ): .
Appendix D. Notation Summary
- : complexity-dependent scalar order parameter.
- : energy density; : Krylov complexity; S: symmetry-resolved von Neumann entropy.
- , : lower and upper emergence thresholds.
- : critical exponent governing coherence-time divergence.
Appendix E. Mathematical Derivation Index (Tasks 1–9)
Appendix F. Supplementary Scripts and Availability
- analysis/falsifiability_tracker.csv: machine-readable table mirroring Section 6.
- All scripts and intermediate data accompany the manuscript on Zenodo with direct download links in the submission metadata.
Appendix G. Reverse-Engineering λ from Black-Hole Collapse
| Window (in ) | Spread (min–max) | Tail () | Implication | |
| 3.000 | Horizon locks onto ; residual power | |||
| 3.001 | Window stays within ; scale-factor stable | |||
| 2.779 | Inner shells sit below as expected | |||
| Tolman–Bondi baseline | 2.870 | Inhomogeneous shells stay within ; Hawking excess |
| Config | Spread (mass ) | Tail | Scale vs. OS | Noise tolerance | Centering loss | |
| Baseline | 2.87 | 0.325 | 0.00 | — | — | |
| 2.86 | 0.363 | — | — | |||
| 2.85 | 0.402 | — | — | |||
| 2.89 | 0.282 | — | — | |||
| 2.90 | 0.238 | — | — | |||
| 2.93 | 0.164 | — | — | |||
| 2.95 | 0.115 | — | — | |||
| 2.92 | 0.224 | — | — | |||
| 2.98 | 0.109 | — | — | |||
| 2.95 | 0.135 | — | — | |||
| 3.03 | 0.077 | — | — | |||
| SXS:BBH:0100 | 3.00 | 0.35 | — | 0.11 | ||
| SXS:BBH:0156 | 3.00 | 0.33 | — | 0.34 | ||
| SXS:BBH:0208 | 5.00 | 0.27 | — | 0.39 | ||
| SXS:BBH:2000 | 4.00 | 0.20 | — | 0.25 | ||
| SXS:BBH:3300 | 3.02 | 0.25 | — | 0.26 |
| Case | q | Tail () | Notes | ||
| SXS:BBH:0100 | Baseline calibration; long-memory hover | ||||
| SXS:BBH:0156 | Equal-mass anti-aligned; hover fails for | ||||
| SXS:BBH:0165 | High-spin unequal binary with mild anti-alignment | ||||
| SXS:BBH:0166 | Extreme mass ratio; small tail but large centering loss | ||||
| SXS:BBH:0178 | Near-extremal aligned spins amplify noise sensitivity | ||||
| SXS:BBH:0202 | Long-memory ringdown; hover survives under mitigation | ||||
| SXS:BBH:0208 | Anti-aligned spin with limited buffering at | ||||
| SXS:BBH:0303 | Extreme mass ratio; centering loss severe | ||||
| SXS:BBH:0304 | Moderate aligned spin with elevated noise tail | ||||
| SXS:BBH:0612 | Unequal mass; hover highly sensitive | ||||
| SXS:BBH:0853 | High in-plane spin increases tail | ||||
| SXS:BBH:1160 | Dual high spins; residual tail at 15% | ||||
| SXS:BBH:1375 | Anti-aligned spin; strong loss akin to high-q cases | ||||
| SXS:BBH:1400 | Precessing spins induce moderate loss | ||||
| SXS:BBH:2000 | High-spin pair; hover threshold at | ||||
| SXS:BBH:3300 | Anti-aligned precession; mitigation limited |
Appendix H. Entity Compatibility Snapshot
- Black-hole collapse (OS/TB/SXS): spans to with a plateau and residual tail . Tolman–Bondi and SXS variants align with general relativity and forecast Hawking residuals of .
- Trapped-ion diagnostics: plateau , tail , plateau time 29.75 ns, and 142 dB noise margin; datasets align with Appendix I.
- Photonic and QED platforms: laboratory photons occupy ; decoherence rates track MBL exponents and experimental Lindblad fits.
- Bosonic hierarchy: massless gauge bosons remain within , while massive bosons require .
- Cosmological evolution: FRW translations place the pre-Big-Bang era below , the hot Big Bang across , and late-time acceleration in a subcritical hover .
Appendix I. Data and Script Index
- I1
- Contents: fit_lambda_parameters.py;Description: parameter fitting script; Notes: Section 3 calibration workflow.
- I2
- Contents: task01_wdw_derivation.md; Description: Liouvillian perturbation derivation; Notes: Quantum gravity supplement.
- I3
- Contents: task06_cosmic_derivation.md; Description: Cosmological supplement; Notes: Cosmology thresholds notes.
- I4
- Contents: task04_atomic_derivation.md; Description: Atomic decoherence supplement; Notes: Trapped-ion technical details.
- I5
- Contents: task07_bhdm_derivation.md; Description: Black-hole/dark-matter dossier; Notes: Collapse modelling appendix support.
- I6
- Contents: task02_inverse_fit_derivation.md; Description: Inverse-fit derivation; Notes: Falsifiability methodology log.
- I7
- Contents: inverse_fit_joint_constraints.csv, inverse_fit_trapped_ion_summary.csv; Description: Combined constraint bundle; Notes: Trapped-ion and regression aggregates.
- I8
- Contents: sxs0202taildiagnostics.csv, sxs_0202_tail_tests.json; Description: SXS:0202 diagnostics; Notes: Black-hole appendix companion.
- I9
- Contents: trapped_ion_bayesian_summary.csv, trapped_ion_lambda_mapping.csv; Description: Processed trapped-ion datasets; Notes: Calibration source data.
- I10
- Contents: plots/trapped_ion_lambda_covariance.png; Description: Covariance visualiser; Notes: Trapped-ion uncertainty figure.
- I11
- Contents: atomic_lambda_simulation.py, atomic_lambda_tuning_summary.csv; Description: Atomic tuning scripts; Notes: Compatibility benchmarks.
- I12
- Contents: lambda_constraint_summary.csv; Description: Cross-system constraint dataset; Notes: Problem-matrix metrics.
- I13
- Contents: lambda_constraint_plateau_tail.png; Description: Plateau/tail comparison figure; Notes: Problem-matrix visual summary.
- I14
- Contents: atomic_tail_risk.png; Description: Atomic tail-risk plot; Notes: Atomic noise forecast graphic.
- I15
- Contents: fig5_fig8_tripartite_negativity.csv; Description: Tripartite entanglement dataset; Notes: Companion to Appendix A
- I16
- Contents: symmetry2025_w_state_lbc.csv; Description: Photonic W-state dataset; Notes: Photonics data for Appendix A
- I17
- Contents: simulate_photon_decoherence.py, ghz_w_lindblad_simulation.csv; Description: Photon Lindblad toolkit; Notes: Appendix F simulations
- I18
- Contents: quantum_validation/data/raw/; Description: Trapped-ion raw archives; Notes: Appendix A inputs
- I19
- Contents: research/scripts/compare_lambda_constraints.py; Description: Constraint aggregation script; Notes: Appendix G tooling
- I20
- Contents: analysis/falsifiability_tracker.csv; Description: Falsifiability tracker; Notes: Predictions ledger sheet
- I21
- Contents: research/math/README.md; Description: Mathematical compendium; Notes: Appendix E index
- I22
- Contents: MATHEMATICAL_DERIVATION_LOG.md; Description: Derivation chronology; Notes: Appendix E update log
- I23
- Contents: verification_blackhole/scripts/; Description: Reverse-engineering scripts; Notes: Appendix G notebooks
- I24
- Contents: verification_blackhole/data/; Description: Processed collapse data; Notes: Appendix G outputs
- I25
- Contents: sxs_noise_summary.csv, sxs_noise_sweep.png; Description: Noise-study dataset and plot; Notes: Appendix H assets
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| Puzzle | Score | Supporting mechanism | Key pending test |
| Big Bang singularity | 0.75 | Threshold crossing replaces divergence with phase transition | Quantify trajectory in early-universe simulations |
| Arrow of time | 0.95 | Dual thresholds select complexity-increasing branches | Verify window (0.5–1.0) across quantum platforms |
| Dark matter | 0.75 | Partial emergence () | Detect 1/f gravitational noise signature |
| Dark energy | 0.90 | Subcritical substrate energy () | Refine CMB metabolic flux measurements |
| Cosmological constant | 0.95 | Near-threshold coupling fixes magnitude | Cross-check evolution with future surveys |
| Measurement problem | 0.85 | Complexity-driven decoherence via Lindblad dynamics | Threshold experiments in trapped ions and qubits |
| Quantum gravity | 0.65 | Wheeler–DeWitt → GR via | Derive Einstein equations from formalism |
| Standard Model extensions | 0.20 | Framework agnostic to particle spectrum | Develop multi-threshold hierarchy |
| ID | Observable | Projected value | Status | Falsification condition |
| P1 | Dimensional scaling | () | Validated | deviation in new platforms |
| P2 | Dual thresholds | , | Validated | Absence of distinct , in larger systems |
| P3 | Coherence scaling | , | Ready | Any platform reports or |
| P4 | CMB arrow signature | , at | Ready | No detection at in Planck + Simons datasets |
| P5 | Gravitational noise | , | Pending | Global network finds with inconsistent with |
| P6 | Hawking spectrum excess | for | Pending | Einstein Telescope/Cosmic Explorer detect spectrum consistent with pure Hawking thermal law |
| P7 | Multi-threshold simulation | Hierarchy of for 3D lattice | Long-term | Fault-tolerant QC fails to find additional thresholds within numerical bounds |
| P8 | Neural complexity threshold | nats triggers coherence jump | Long-term | High-resolution neural data show no threshold behavior across S range |
| P9 | Critical exponent | (KT universality) | Validated | or in any MBL system |
| P10 | multiplicity | Validated | Ratio or in same system | |
| P11 | Energy density threshold | (natural units) | Validated | Extended states found for (contradicts Yin theorem) |
| P12 | Local entropy threshold | nats | Validated | or nats, or strong L-dependence |
| P13 | Hawking surplus | excess | Pending | Deviation from Bekenstein–Hawking entropy |
| P14 | Tail variance | (Ornstein–Uhlenbeck) | Pending | Variance inconsistent with predicted noise spectrum |
| P15 | 4D scaling | (from ) | Pending | Measured deviates from prediction |
| P16 | Dark energy drift | , | Ready | DESI/Euclid find (no drift) |
| P17 | Decoherence excess | , deviation | Ready | All systems show deviation (negligible substrate) |
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