Geometry & moduli · An interactive explorer

At the wall.

A small change.
An enormous response.

A geometric structure can be stable and still be close to losing its grip. Near the boundary, some changes cost almost no energy. Its metric becomes exquisitely sensitive.

Here a four-dimensional complex manifold leaves a surprisingly small footprint: four vertices, four edges, and three numbers tending to zero.

Move toward the wall

01 · Geometry becomes a network

Find the soft direction.

Drag the point toward an edge. A connection weakens, a mode becomes cheaper, and the response grows.

Stable interior
A

The chamber

A square slice
A square cross-section of the stable coneDrag the point, or use the two sliders below. The interior is stable; the four edges are semistable boundaries.
B

The network

Four stable factors

Positive Negative mode amplitude

Edge width shows relative coupling. Vertex colour and signed labels show a unit mode. Animation is a visual aid, not geometric flow.

C

The response

Leading model

Smaller eigenvalue.
Larger sensitivity.

Mode / eigenvalue νResponse 1/ν
Energy of the selected unit mode—

Bars share a fixed logarithmic scale from 10⁻¹⁰ to 1; each interval is a factor of ten. Response values are reciprocal eigenvalues of the finite model.

What to notice

A vector bundle has a slope: degree per rank. Stability asks that every proper subsheaf have smaller slope than the whole. A wall is where one of those strict inequalities becomes an equality. Changing the polarization changes the slopes.

For this tangent bundle, four line factors and their extensions control what happens near a meeting of walls. The square above is a slice of its local chamber. The graph’s small eigenvalues measure the energy of relative changes between factors; their reciprocals describe the leading sensitivity of the Hermitian–Einstein metric.

The geometry and the calculation

The example is the tangent bundle of X = ℙB(O ⊕ L) ×B ℙB(O ⊕ L), with B = ℙ¹ × ℙ¹ and L = O(1, −1). This is a smooth projective weak-Fano fourfold, not a Fano fourfold. Its tangent sequence has factors R₁, R₂, Q₁, Q₂, all of rank one.

Set x = σ(p, 1 − p) and y = σ(q, 1 − q). The stable inequalities are x₁, x₂, y₁, y₂ > 0, with x₁ + x₂ = y₁ + y₂ = σ. The leading edge weights are kij = xiyj/σ. The explorer diagonalizes L = D diag(k) Dᵀ on the subspace whose coordinates sum to zero. All quantities displayed are computed from this finite operator.

For the actual Hermitian–Einstein metric in the strict chamber, λj = νj(L)(1 + O(σ)), j = 1, 2, 3, while the remaining spectrum has a uniform positive gap. In the paper’s slope coordinates and normalized L² norms, the three metric-response singular values are νj−1(1 + O(σ)). These are singular values, not an identification of every response direction with a plotted graph eigenvector.

The theorem is uniform through separated positive scales. It supplies no numerical value for the error constant displayed here, so σ is not a certified percentage error. On a nonsplit semistable boundary bundle this stationary Hermitian–Einstein metric is not asserted; boundary graphs are limiting finite models only. This is an endomorphism Dolbeault spectrum, not the full Yang–Mills Hessian.

02 · One bundle, three different speeds

Three ways to lose rigidity.

Follow one path toward the cone tip. The three small eigenvalues separate into three powers of the same parameter.

Solid: computed graph eigenvalues. Dashed: leading powers. Both axes are logarithmic.

1ν₁ ∼ ⁴⁄₃t⁶—

2ν₂ ∼ ³⁄₂t⁴—

3ν₃ ∼ 2t²—

The softest direction becomes softer much faster than the others. In the geometric theorem, the next eigenvalue stays bounded away from zero. The disappearing modes are a specific, finite part of the spectrum.

The path is realized by polarizations

Set x₁ = t⁶, x₂ = t², y₁ = t⁴, y₂ = t² − t⁴ + t⁶. These positive demands are realized by the paper’s ample chart on the fixed tangent bundle. Its actual eigenvalues satisfy λ₁ = (4/3)t⁶(1 + O(t²)), λ₂ = (3/2)t⁴(1 + O(t²)), λ₃ = 2t²(1 + O(t²)), and λ₄ ≥ γ > 0. The plotted solid curves are graph eigenvalues; the dashed curves are their asymptotic leading terms. The wider end of the plot illustrates the finite model without asserting a numerical geometric error bound.

03 · A separate extension experiment

What the slopes forget.

Keep the ranks and slope demands fixed. A tree has no freedom left. A cycle can remember more.

The extra datum changes how the same demands are carried around the cycle.

A

The tree

No cycle datum

Removing the R₂–Q₁ edge leaves a connected path. Its three positive weights are forced by the demands.

B

The cycle

One extra datum

All four edges remain present. Their balance is fixed; their cycle ratio can vary.

Same slopes, different spectrum

Fixed demands and the missing datum

Both graphs have unit vertex masses and demands b = ρ(2, 1, −1, −2), with ρ = 0.02. The tree weights are ρ(1, 1, 0, 1). For the cycle, k = ρ[[a, 2 − a], [1 − a, a]], where 0 < a < 1 solves a²/((2 − a)(1 − a)) = θ. Thus every row and column sum stays fixed.

The ratio θ = c₁₁c₂₂/(c₁₂c₂₁) comes from harmonic extension data, invariant under factor rescaling. This is an instance of Paper III’s general cyclic mechanism. It is not a free control on the fixed tangent bundle in experiments 1–2: that geometric example has a reference symmetry fixing its leading cycle ratio.

04 · The two-factor flow

There is another side.

Move the signed slope gap through zero. The long-time profile changes from a positive limit, to inverse-time decay, to exponential decay.

Three signed profiles, with your selected gap highlighted. Vertical axis logarithmic; time starts at τ = 1.

Stable side—Small-eigenvalue profile Pδ(τ)

The profile and what the flow theorem says

Pδ(τ) = δ / (1 − exp(−2δτ)),   P₀(τ) = 1/(2τ).

These are exact evaluations of the profile in Paper V, not numerical solutions of the Hermitian Yang–Mills PDE. For the paper’s fixed two-factor extension and any smooth positive initial-metric family, each tolerance admits one sufficiently late time and then one parameter neighborhood such that the actual smallest eigenvalue divided by this profile stays within that tolerance for every subsequent time. Both signs of δ and δ = 0 are included.

For δ > 0, P tends to δ. At the wall it equals 1/(2τ). For δ < 0, P ∼ |δ| exp(−2|δ|τ). The experiment does not claim that a stationary Hermitian–Einstein metric continues across the wall, or that this scalar formula describes a general many-factor flow.

From picture to paper

The geometry behind the controls.

The finite models are computed in your browser. Their connection with bundles, metrics, and flow is proved under the hypotheses of the following preprints.

IV · The chamberNonsimplicial local stability chambers of toric tangent bundles III · The spectrumUniform Hermitian–Einstein spectra for bipartite two-step extensions V · Metrics and flowMetric response and Hermitian Yang–Mills flow for two-step extensions Further reading · Matrix modesUniform Hermitian–Einstein spectra with repeated stable factors

The experiments above illustrate scalar graph models. The repeated-factor sequel treats the additional matrix modes in the stationary two-step problem.