vST for Scientific Simulators#

References#

This appendix lists references relevant to scientific simulators, high‑dimensional state‑space analysis, numerical methods, scaling laws, dynamical systems, and validation frameworks. Citations are grouped by category for clarity and presented in a substrate‑agnostic, model‑independent format consistent with the RSM and vST canon.

1. Scientific Simulation Frameworks#

• Staniforth, A., & Côté, J.
  Semi‑Lagrangian Integration Schemes for Atmospheric Models — A Review.
  Monthly Weather Review (1991).

• Birdsall, C. K., & Langdon, A. B.
  Plasma Physics via Computer Simulation.
  McGraw‑Hill (1985).

• Stone, J. M., Tomida, K., White, C. J., et al.
  The Athena++ Adaptive Mesh Refinement Framework.
  ApJS (2020).

• Anderson, J. D.
  Computational Fluid Dynamics: The Basics with Applications.
  McGraw‑Hill (1995).

2. Numerical Methods and Solvers#

• LeVeque, R. J.
  Finite Volume Methods for Hyperbolic Problems.
  Cambridge University Press (2002).

• Hairer, E., Lubich, C., & Wanner, G.
  Geometric Numerical Integration: Structure‑Preserving Algorithms for Ordinary Differential Equations.
  Springer (2006).

• Press, W. H., Teukolsky, S. A., Vetterling, W. T., & Flannery, B. P.
  Numerical Recipes: The Art of Scientific Computing.
  Cambridge University Press (2007).

3. High‑Dimensional Modeling and State‑Space Analysis#

• Coifman, R. R., & Lafon, S.
  Diffusion Maps.
  Applied and Computational Harmonic Analysis (2006).

• Tenenbaum, J. B., de Silva, V., & Langford, J. C.
  A Global Geometric Framework for Nonlinear Dimensionality Reduction.
  Science (2000).

• Brunton, S. L., Proctor, J. L., & Kutz, J. N.
  Discovering Governing Equations from Data: Sparse Identification of Nonlinear Dynamics (SINDy).
  PNAS (2016).

4. Scaling Laws and Multi‑Resolution Behavior#

• Pope, S. B.
  Turbulent Flows.
  Cambridge University Press (2000).

• Frisch, U.
  Turbulence: The Legacy of A. N. Kolmogorov.
  Cambridge University Press (1995).

• Balsara, D. S.
  Higher‑Order Schemes for Multi‑Dimensional MHD.
  Journal of Computational Physics (2012).

5. Dynamical Systems and Regime Behavior#

• Strogatz, S.
  Nonlinear Dynamics and Chaos.
  Westview Press (2014).

• Ott, E.
  Chaos in Dynamical Systems.
  Cambridge University Press (2002).

• Guckenheimer, J., & Holmes, P.
  Nonlinear Oscillations, Dynamical Systems, and Bifurcations of Vector Fields.
  Springer (1983).

6. Validation, Verification, and Drift Detection#

• Oberkampf, W. L., & Roy, C. J.
  Verification and Validation in Scientific Computing.
  Cambridge University Press (2010).

• Roache, P. J.
  Verification and Validation in Computational Science and Engineering.
  Hermosa Publishers (1998).

• Breck, E., Cai, S., Nielsen, E., et al.
  The ML Test Score: A Rubric for ML Production Readiness and Technical Debt Reduction.
  Google Research (2017).

7. Substrate‑Level and Triadic‑Frameworks Canon#

• Loswin, N.
  Resonance Substrate Model (RSM): Structural Foundations for High‑Dimensional Inference.
  TriadicFrameworks (2025).

• Loswin, N.
  Triadic Dimensional Cores: A 3D–9D Substrate for Structural and Inference‑Level Alignment.
  TriadicFrameworks (2025).

• Loswin, N.
  Validation‑Space‑Time (vST): A Substrate‑Level Framework for Reproducibility and Drift Detection.
  TriadicFrameworks (2025).

• Loswin, N.
  Dimensional Substrate Structures: Scaling Laws and High‑Dimensional Regimes.
  TriadicFrameworks (2026).

• Loswin, N.
  vST for Scientific Simulators.
  TriadicFrameworks (2026).