Central Configurations

Gravitational molecules at minimum shape complexity

Aaron Lax — March 2026

Critical points of VS = √Icm × W on the pre-shape sphere. Heavy particles red, light particles blue. 3D positions projected via PCA. N = 100 to 10,000.

Highlights

Click any image to explore.

Bond angles
Bond angle peaks at 107.9° — water is 104.5°
N=1000 1:2000
N=1,000, 1:2000 — mass shell structure
Oblate
Oblate shape — Jupiter-like flattening
V_EM
VEM — magnetic vorticity breaks symmetry

Mass Ratio Progression — N=100, 2D

Equal
1:2
1:10
1:80
1:2000

Scaling — Equal Masses

N=100
N=500
N=1K
N=2K
N=5K

Scaling — Mass Ratio 1:2000

Shell structure strengthens with N.

N=100
N=500
N=1K
N=2K
N=5K

All Configurations

N=100

2D + 3D, 5 mass ratios

N=500, 3D

5 mass ratios

N=1,000, 3D

5 mass ratios

N=2,000, 3D

5 mass ratios

N=5,000, 3D

5 mass ratios

Molecule Search

500 starts, angle distributions, recurring motifs

Oblate Shapes

Jupiter/Saturn-like flattening

VEM

Maria’s 3-body triangle vorticity

Shape Landscape

Bifurcation, structural persistence, bond angles across mass ratios

Shape Complexity Values

ConfigEqual1:21:101:801:2000
N=100, 2D52,231142,7843.6×1065.1×1081.6×1012
N=100, 3D43,325118,8353.0×1064.3×1081.3×1012
N=5002.5×1067.0×1061.8×1082.6×10107.9×1013
N=1,0001.4×1074.0×1071.0×1091.5×10114.5×1014
N=2,0008.2×1072.3×1085.8×1098.6×10112.6×1015
N=5,0008.2×1082.3×1095.8×10108.5×10122.6×1016
N=10,0004.6×1091.5×1017
Method. Minimise VS = √Icm × W on {∑qi=0, ∑|qi|²=1}. Gradient descent with mass preconditioning, cosine-annealed learning rate, 8K–40K iterations, 12–100 random restarts. N≥10,000 uses tiled pairwise computation (O(N×T) memory). JAX float64 on NVIDIA H100 GPUs via Modal.
Data and source code available on request.

N=100

2D results reproduce Maria’s methodology. 3D results projected via PCA.

2D — Maria Comparison

Equal
1:2
1:10
1:80
1:2000

3D

Equal
1:2
1:10
1:80
1:2000

N=500, 3D

Molecular segregation persists at scale.

Equal
1:2
1:10
1:80
1:2000

N=1,000, 3D

Mass-dependent shell structure clearly visible.

Equal
1:2
1:10
1:80
1:2000

N=2,000, 3D

Shell structure increasingly pronounced.

Equal
1:2
1:10
1:80
1:2000

N=5,000, 3D

Five thousand particles. Clear mass-dependent spatial organisation.

Equal
1:2
1:10
1:80
1:2000

Oblate Configurations

z-variance penalty breaks spherical symmetry → Jupiter/Saturn-like shapes. N=200, 3D, aligned to principal axes.

Equal Masses

λ=0 — spherical (z/xy=1.99)
λ=0.5 — mildly oblate (z/xy=0.92)
λ=2.0 — strongly oblate (z/xy=0.39)
λ=10 — pancake (z/xy=0.006)

Mass Ratio 1:80

λ=0 (z/xy=2.00)
λ=0.5 (z/xy=0.91)
λ=2.0 (z/xy=0.40)
λ=10 (z/xy=0.04)

Maria’s VEM

3-body oriented triangle terms: VEM = √I × (α Welec + β Wmag). The magnetic term couples triangle areas to a global vorticity axis — oblate shapes from pure geometry.
Full explainer: mechanism, how to read the figures, what is shown vs open →

N=100, varying β

β=0 (spherical)
β=0.1 (oblate, 0.70)
β=0.5 (0.70)
β=2.0 (0.90)
β=10 (0.85)

N=200

β=0 (spherical)
β=1.0 (0.79)
β=5.0 (0.85)

Molecule Search

500 random starts per mass ratio, keeping all local minima. For each converged configuration we measure the nearest-neighbour bond angle: for every particle, find its two closest neighbours and measure the angle at the vertex.

What This Measures

The “bond angle” here is a packing statistic, not a chemical bond. It answers: when 100 points settle to minimum shape complexity under the gravitational potential, how are they locally arranged? The nearest-neighbour angle is determined by how particles pack in 3D under the constraint of the pre-shape sphere. We mark water’s 104.5° and the ideal tetrahedral angle 109.5° as reference lines — not because we expect to recover water from gravity, but because both are signatures of the same underlying geometry: optimal packing of repulsive points in three dimensions.

Equal Masses — 107.9°

All 500 starts converge to the same minimum — the landscape has a single basin. The mean bond angle is 107.9°, close to the ideal tetrahedral angle (109.5°). This is expected: 100 equal-mass particles minimising ∑ 1/rij on a sphere is essentially the Thomson packing problem, whose local structure is approximately tetrahedral. The proximity to water’s 104.5° is a consequence of shared packing geometry, not a claim about chemistry.

Angle distribution across 500 starts. The spread (100°–115°) reflects variation across particles within the single minimum, not across different minima.
Gallery — all are the same minimum viewed from different PCA projections.

1:10 — 98.1°

Still a single basin. Introducing mass asymmetry shifts the packing: heavy particles claim more “space” in the potential (their mimj/r terms dominate), compressing the angles of lighter particles’ local neighbourhoods. Two light-particle clusters emerge.

Angles shift below tetrahedral
Gallery

1:80 — 86.6°

The landscape bifurcates — 3 distinct minima from 500 starts. The dominant minimum (434/500 starts) has 7 light-particle clusters and a mean angle of 86.6°. Two rarer configurations exist at slightly higher complexity. The angle compression continues: heavy particles force light particles into tighter local arrangements.

Angles
Three distinct minima visible

1:2000 — 71.4°

Two distinct minima. The dominant (447/500 starts) has a mean angle of 71.4° — well below tetrahedral, reflecting the extreme mass asymmetry. At this ratio (comparable to proton/electron), heavy particles form a rigid scaffold and light particles are confined to tight clusters in the interstices, compressing local angles far below the equal-mass packing value.

Distribution now bimodal
Molecular segregation at extreme mass ratio

Angle Trend with Mass Ratio

Mass RatioDistinct MinimaDominant AngleLight Clusters
Equal1107.9°
1:10198.1°2
1:80386.6°7
1:2000271.4°

The trend is monotonic: 108° → 98° → 87° → 71°. The equal-mass angle reflects Thomson-like packing on the shape sphere. As mass ratio increases, the heavy-particle scaffold increasingly constrains light-particle geometry, compressing bond angles. The question for further work is whether specific mass ratios select for angles that match known molecular geometries — and if so, whether that is coincidence (shared packing geometry) or something deeper (the shape potential encoding chemical structure through ratios alone).

Shape Landscape Analysis

What happens when we run 500 independent minimisations of VS for the same (N, mass ratio) and keep every result? Each start lands in a local minimum. How many distinct minima exist? How do they differ?

The Main Result: Landscape Bifurcation

For mass ratios below 1:50, all 500 starts converge to the same minimum — the shape potential has a single basin. At 1:50 and above, two distinct minima appear. The landscape topology changes with mass ratio.

This is not a numerical artifact. The two minima have measurably different VS values, different local structure, and different bond-angle distributions. The lower-VS minimum attracts the vast majority of starts (434–447 out of 500); the higher one is a rarer basin.

Mass RatioDistinct MinimaStarts in DominantVS Gap
Equal1500 / 500
1:21500 / 500
1:51500 / 500
1:101500 / 500
1:502~434 / 50026,000
1:2002~447 / 500982,000
1:20002~447 / 500700,000,000

What the Two Minima Look Like

For each bifurcated family, we show the two distinct configurations side by side. Left is the lower-VS (dominant) minimum, right is the higher-VS (rare) one. Both are PCA projections of 3D positions. Red = heavy particles, blue = light.

The key observation: the heavy-particle scaffold (red dots) is similar in both minima. What differs is how the light particles (blue dots) arrange themselves within that scaffold. This is the “fossil” idea — the scaffold is a structural trace that persists across the two basins. It is NOT a time sequence. It is two static configurations that share partial structure.

1:200 — two minima. The red scaffold is similar; the blue clusters rearrange.
1:2000 — two minima. Same pattern: shared scaffold, different light-particle clustering.

Measuring Structural Similarity

To quantify how much the two minima share, we compute three similarity scores between them:

  • Shape persistence (Procrustes) — align the two configs optimally, measure residual distance. Higher = more similar overall shape.
  • Angle similarity — compare the distribution of nearest-neighbour bond angles. Higher = same local packing geometry.
  • Radial similarity — compare how particles distribute by distance from centre. Higher = same density profile.
1:50
1:200
1:2000

Angle similarity is consistently high (0.85–0.90): the two minima have nearly identical local packing. Shape persistence is lower (0.50–0.63): the global arrangement differs. This is what we’d expect if the scaffold persists but the light-particle clusters rearrange.

Bond Angle and Structure vs Mass Ratio

Left: the mean nearest-neighbour bond angle at the dominant minimum, measured across all particles. It decreases monotonically: 108° (equal) to 71° (1:2000). At equal masses this is Thomson-like sphere packing (near the tetrahedral angle 109.5°). At high mass ratios, the heavy-particle scaffold compresses light-particle local geometry. Blue bars = single-basin families; red = bifurcated (2 minima).

Right: a composite structural score measuring how “non-trivial” each configuration is. It combines: asphericity (deviation from spherical shape), nearest-neighbour distance variation (uneven spacing = internal landmarks), cluster count (distinct sub-groups within the config), and low radial entropy (concentrated rather than uniform density). The score is not calibrated to any external standard — it ranks configurations relative to each other. Higher mass ratios produce more internally structured configurations.

Limitations

At N=100 with 500 gradient-descent starts, we find at most 2 distinct minima per mass-ratio family. This is not enough for rich “age tracks” or “growth sequences.” To test whether longer sequences of partially-persistent configurations exist, we would need:

  • Larger N (more complex landscape with more basins)
  • Saddle-point methods (GAD/HiSD) to find transition states between basins
  • More mass species (not just 2-species 50/50 split)
  • Systematic continuation methods that trace solution branches

Face-like or household-object forms do not emerge from pure N-body at N=100. The strongest recurring motifs are mass-shell segregation and heavy-particle scaffolds.