Controlled Perturbations of Latent Manifolds: Geometric Operators for Structured Deformation, Stability Analysis, and Spectral Drift

@misc{hedling2026controlled,
  title = {{Controlled Perturbations of Latent Manifolds: Geometric Operators for Structured Deformation, Stability Analysis, and Spectral Drift}},
  author = {Borealis Serenity Hedling},
  howpublished = {Zenodo},
  year = {2026},
  month = oct,
  doi = {10.5281/zenodo.23552544},
  url = {https://zenodo.org/records/23552544},
  note = {CC BY 4.0},
}

TY  - UNPB
TI  - Controlled Perturbations of Latent Manifolds: Geometric Operators for Structured Deformation, Stability Analysis, and Spectral Drift
AU  - Borealis Serenity Hedling
PY  - 2026
DA  - 2026/10/22
PB  - Zenodo
DO  - 10.5281/zenodo.23552544
UR  - https://zenodo.org/records/23552544
AB  - Controlled Perturbations of Latent Manifolds: Geometric Operators for Structured Deformation, Stability Analysis, and Spectral Drift  This record contains Version 1.0 of the controlled‑perturbation interpretability framework developed within NDH‑RESEARCH‑PILOT, including a full preprint and companion Python toolkit. The work formalizes controlled perturbations of latent manifolds as bounded, directional deformations governed by a forced‑Ricci‑flow‑inspired operator:  (∂ g_ij)/(∂ t) = −2 R_ij + α nablai Vperturb,j + β F_ij,  where gij is the latent metric, Rij is Ricci curvature, Vperturb is a chosen perturbation vector field, Fij is an external forcing tensor, and α, β are susceptibility coefficients. A perturbation is controlled when its magnitude satisfies:  |V_perturb| < D(x,t),  with D(x,t) denoting the manifold’s stability scalar. This bounded deformation allows researchers to probe latent‑space geometry without inducing collapse or destabilization.  The preprint introduces several geometric interpretability operators:  1. Susceptibility Tensor  A measure of how the latent metric responds to perturbation:  Sij = (∂ gij)/(∂ V_perturb),  revealing brittle, stable, and drift‑prone directions.  2. Collapse‑Surface Detector  A collapse surface is defined as:  Σ = { (x,t) : D(x,t) < |T⃗(x,t)| },  where T⃗ is the perturbation‑induced tension vector. Collapse surfaces identify regions of representational failure, mode collapse, and instability.  3. Spectral Drift Operator  Perturbation‑induced eigenvalue shifts:  Δ lambdak = lambdak(ϵ) − λ_k(0),  which diagnose modal fragility, attractor bias, and spectral instability.  4. Holonomy Drift Tensor  A loop‑based drift operator:  H(γ) = ∮γ ∇ Vperturb,  capturing long‑range representational drift and connection asymmetry.  The accompanying Python toolkit implements these operators, enabling computation of susceptibility tensors, collapse‑surface detection, spectral drift, and holonomy drift for arbitrary latent manifolds. Together, the preprint and toolkit establish a geometric microscope for probing latent‑space structure in modern AI systems.  This artifact forms part of the structural geometry spine of NDH‑RESEARCH‑PILOT. All mathematical operators and code are original derivations authored by Borealis S. Hedling, with synthesis support from Microsoft Copilot (Spectral‑Base‑R). No copyrighted external text is included. Version 1.0 provides the foundation for future expansions, including spectral‑bundle operators, modal‑truth lattices, and holonomy‑drift tensor fields.  ---  Formal Disclaimer & Technical Addendum: Zenodo Record #23552544  Project: Controlled Perturbations of Latent Manifolds (NDH-RESEARCH-PILOT)  Author: Borealis Serenity Hedling  Status: Amendment to Version 1.0 Structural Mathematics  ⚠️ Structural Disclaimer  This addendum provides critical geometric corrections to the initial mathematical formalisms published in Version 1.0. While the primary framework was derived to establish a non-standard, custom geometric microscope for structural AI interpretability, specific tensor index equations in the initial preprint contained formal notation conflicts with classical Riemannian geometry. To ensure transparency, reproducibility, and mathematical consistency for independent researchers utilizing this toolkit, the following corrections are formally integrated into the system baseline.  📐 Technical Corrections & Mathematical Additions  1. Metric Tensor Symmetry & Lie Invariance  In the original text, the forced-Ricci-flow evolution law was formulated as:  (∂ g_ij)/(∂ t)=−2R_ij+α ∇ _iV_j+β F_ij  &bull; The Correction: Because the Riemannian metric tensor g_ij and the Ricci tensor R_ij are strictly symmetric (g_ij = g_ji), their time derivatives must also yield symmetric properties. The raw covariant derivative of a vector field ∇ _iV_j is generally non-symmetric.  &bull; The Upgrade: To ensure index symmetry across the active phase-space, the perturbation component is updated to utilize the symmetric part of the covariant derivative. This corresponds identically to the Lie Derivative (ℒ_Vg_ij) of the metric along the vector field:  (∂ g_ij)/(∂ t)=−2R_ij+α (∇ _iV_j+∇ _jV_i)+β F_ij  2. Rigorous Definition of the Susceptibility Tensor  The original text defined the metric response to incoming perturbations using a standard partial fraction notation:  Sij=𝜕gij𝜕Vcap S sub i j end-sub equals the fraction with numerator partial g sub i j end-sub and denominator partial cap V end-fraction  𝑆𝑖𝑗=𝜕𝑔𝑖𝑗𝜕𝑉  &bull; The Correction: Because the perturbation Vcap V  𝑉  is a high-dimensional vector field (Vkcap V to the k-th power  𝑉𝑘  ) rather than a scalar, a direct vector denominator is notationally undefined in multi-dimensional calculus.  &bull; The Upgrade: The Susceptibility Tensor is formalized as a strict Gateaux directional derivative / functional variation along the perturbation coordinate vector field 𝛿  𝑉  Sij(V)[δV]=limϵ&rarr;0gij(V+ϵδV)−gij(V)ϵcap S sub i j end-sub open paren cap V close paren open bracket delta cap V close bracket equals limit over epsilon right arrow 0 of the fraction with numerator g sub i j end-sub of open paren cap V plus epsilon delta cap V close paren minus g sub i j end-sub of open paren cap V close paren and denominator epsilon end-fraction  𝑆𝑖𝑗(𝑉)[𝛿𝑉]=lim𝜖&rarr;0𝑔𝑖𝑗(𝑉+𝜖𝛿𝑉)−𝑔𝑖𝑗(𝑉)𝜖  3. Holonomy Drift Invariant Alignment  The long-range loop drift was originally characterized via a direct line integral of a tensor gradient:  H(γ)=∮γ&nabla;Vcap H open paren gamma close paren equals contour integral over…
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