ERG volume
GRG Sphere — Points • Surface • ERG Volume • Smooth
the reconstructed surface is perfect at scale $\varepsilon$ (geometric error $\le \varepsilon$); area and ERG volume converge with $O(h^2)$ error.
1) Definitions
- Resolution $\varepsilon$: admissible indistinguishability threshold.
- Step $h$: distance between nearby surface samples.
- Curvature $\kappa$: for a sphere, $\kappa = 1/R$.
- Perfect at scale $\varepsilon$: Hausdorff distance (ideal ↔ reconstructed) $\le \varepsilon$.
Geometric reminder (sagitta of an arc of radius $R$):
2) Points → Surface → ERG volume
2.1 Points (quasi-uniform sampling)
- Spherical Fibonacci lattice: simple and isotropic.
- Icosphere (subdivided icosahedron): regular connectivity.
Point count (triangles near-equilateral, area $(\sqrt{3}/2)\,h^2$):
It grows linearly with $R/\varepsilon$.
2.2 Surface (closed, oriented mesh)
Triangulate coherently on the spherical manifold. Face normal: $\mathbf{n}_f \propto (p_j-p_i)\times(p_k-p_i)$.
Discrete area:
2.3 ERG volume (from closed surface)
With an oriented closed mesh (tetrahedra w.r.t. the origin):
Convergence: $A$ and $V_{\mathrm{ERG}}$ approach the ideal values with $O(h^2)$ error.
3) Smooth$_{\varepsilon}$ (when and how)
Goal: stabilize normals and reflections without exceeding $\varepsilon$.
- Local Taubin/MLS filter (forward/backward pass to avoid shrinkage).
- Projection onto the sphere ($\lVert v\rVert \to R$).
- Check: Hausdorff (pre/post) $\le \varepsilon/2$.
- Smoothed normals from local MLS fit ($\ge C^{1}$ continuity).
When it’s not needed: if you only measure area/ERG volume and faceting is already below the $\varepsilon$-scale threshold.
4) Algorithm (concise)
input: R, ε
κ ← 1/R
h_max ← 2*sqrt(ε/κ) # = 2*sqrt(εR)
N ← round((2π/√3) * R/ε)
P ← fibonacci_sphere(N) # or icosphere(h_max)
T ← triangulate_on_sphere(P)
orient(T) # outward normals
A ← sum_areas(T)
V_ERG ← tetra_volume(T)
if need_smooth_normals:
P' ← taubin_mls(P, T) # controlled smoothing
P' ← project_to_sphere(P', R)
assert hausdorff(P, P') ≤ ε/2
recompute_normals(P', T)
output: (P, T, A, V_ERG, normals)
5) Checks & validation
- Hausdorff distance (ideal ↔ mesh) $\le \varepsilon$.
- Triangle quality (avoid extreme angles).
- No self-intersections.
- $O(h^{2})$ convergence for area and ERG volume.
6) Why it matters
The sphere is an ideal testbed: constant curvature and closed-form $A,V$. The chain points → surface → ERG volume → smooth at scale $\varepsilon$ sets the general GRG/ERG procedure for solids.
7) Figures (inline SVG)
8) FAQ
Is “perfect” absolute?
No: it is perfect at scale $\varepsilon$. Details $<\,\varepsilon$ are not guaranteed.
Do we always need smoothing?
No: needed for normals/optics stability; otherwise optional.
Fibonacci or icosphere?
Both work: Fibonacci is simple and isotropic; icosphere offers regular connectivity.
How do I choose $\varepsilon$?
Based on use: measurement accuracy, rendering, fabrication, etc.
ERG Quick Calculator
This compact tool computes the quarter-sampling step Δu and the grid size K from the dyadic level b, previews the uk values, and exports the grid to CSV.
Inputs
- Dyadic level b ∈ ℕ≥0 (recommended range: 0–18)
- Optional: recent estimates V2b-1 and V2b to check the dyadic stopping rule
Calculator
Results
- Δu =
—(exact:—) - K =
—(i.e., number of grid points) - N =
—(turns-first level, N = 2b)
Preview of u-grid uk = k · Δu
First 8: —
Last 8: —
Practical checklist
- Use dyadic refinement: increase b until the dyadic difference falls below ε.
- Quarter-sampling is assumed: Δu = 2-(b+2).
- Grid is deterministic; CSV can be versioned for reproducibility.