Alphabeta Math
Pipeline-generated
How statement and proof provenance work

The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.

  • Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
  • AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
  • AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.

These labels describe origin, not correctness: citations and verification chips remain separate evidence.

Minimum energy paths string neb and saddle certificates — Examples

1 · Prerequisites

2 · Summary

Examples

These examples verify a circular double-well MEP and show why its straight chord is wrong, exhibit corner and cusp failures in tangent construction, and reject an index-two maximum as the desired saddle. A two-dimensional matrix calculation shows mode sensitivity as the spectral gap closes, while a quartic potential calculates dimer truncation bias and force-noise error exactly. A zero potential gives both infinitely many continuum MEPs and distinct zero-residual finite NEB chains, illustrating why the stable inverse hypotheses are needed.

3 · Logical flowchart

4 · Definitions, theorems and proofs

None yet.

5 · Examples, counterexamples and false statements

ExampleConstruction: AI-adaptedVerification: AI-generatedOpen item page →

Dimer finite-difference bias competes with force-evaluation error

Example

On R2, let V(x,y)=x4/24+y2/2, take the point (0,0) and direction v=e1. The exact Hessian action is ∇2V(0,0)e1=0. With exact gradients, the central dimer estimate is Dϵ=(ϵ2/6)e1. If the two gradient evaluations have errors +ηe1 and −ηe1, each of norm η, the computed estimate becomes D^ϵ=(ϵ2/6+η/ϵ)e1. The truncation bias decreases with ϵ, while this permitted noise contribution increases as ϵ shrinks.

Facts & Assumptions

Given: The potential, point, direction, finite-difference distance ϵ>0, and opposite evaluation errors of magnitude η≥0.

[F1]

The Hessian matrix and critical points of a scalar field: the Hessian is the Jacobian of the gradient; at the origin its action on e1 is zero.

[F2]

Paired force evaluations give a second-order Hessian-vector estimate: for C4 potentials the paired central gradient difference has truncation error O(ϵ2) and force-evaluation contribution at most η/ϵ.

Given: The data in the Example.

Proof

1.1F1givenalgebra

The gradient is ∇V(x,y)=(x3/6,y). Thus ∇V(ϵe1)=(ϵ3/6,0) and ∇V(−ϵe1)=(−ϵ3/6,0). Their central difference is ((ϵ3/3)/(2ϵ),0)=(ϵ2/6)e1. The Hessian at the origin is diag⁡(0,1), so [F1] gives He1=0.

2.1F2step 1.1givenalgebra

Adding the stated force errors changes the numerator by 2ηe1; division by 2ϵ adds ηe1/ϵ. Hence the computed estimate is exactly D^ϵ=(ϵ2/6+η/ϵ)e1. This realizes both contributions in [F2] for this example.

3.1step 2.1algebra∎

For fixed η>0, the deterministic term ϵ2/6 tends to zero as ϵ→0, but the permitted error term η/ϵ grows without bound. Therefore reducing the dimer separation does not monotonically improve the Hessian-vector estimate when force evaluations are inexact.

ExampleConstruction: AI-adaptedVerification: AI-generatedOpen item page →

A corner has no unique tangent and a cusp gives a zero centered chord

Example

Two elementary paths show why regularity and nondegenerate centered chords are explicit hypotheses. The corner path is Rc(s)=(s,0) for s≤0 and Rc(s)=(0,s) for s≥0. The cusp path is Ru(s)=(s2,0). For equal samples at −h and h, the centered chord is R(h)−R(−h).

Facts & Assumptions

Given: The two displayed paths and any h>0 small enough that their samples lie in the stated parameter intervals.

[F1]

Second-order centered and unequal-step tangent estimates assumes a regular C3 curve and a nonzero centered chord before normalizing it.

[F2]

Finite-image projected-gradient string with arc-length redistribution returns geometry-failure if an interior centered chord is zero.

Proof

Given: The paths and sample spacing in the Example.

1.1givenalgebra

For the corner, the one-sided derivatives at 0 are Rc′(0−)=(1,0) and Rc′(0+)=(0,1). They are distinct, so there is no single tangent at the corner. The centered chord is Rc(h)−Rc(−h)=(h,h), whose unit direction is (1,1)/2; it agrees with neither one-sided tangent.

1.2givenalgebra

For the cusp, Ru(h)=Ru(−h)=(h2,0), so its centered chord is exactly zero. Also Ru′(0)=(0,0), so the path is not regular there.

2.1F1F2step 1.1step 1.2∎

The corner violates the differentiability/unique-tangent hypotheses of [F1], while the cusp violates regularity and makes the algorithmic centered direction undefined. By [F2], a finite string update encountering this zero chord must return geometry-failure; neither example can be covered by the second-order normalized-tangent estimate of [F1].

ExampleConstruction: AI-adaptedVerification: AI-generatedOpen item page →

A curved double well has an exact circular minimum-energy path

Example

Prescribe Cbad={(0,0)}. Let D=(−π/4,π/4)×(−1/4,1/4) and define

X(s,n)=(1+n)(cos⁡s,sin⁡s),U:=X(D).

The domain satisfies U⊆R2∖Cbad. Indeed, it is an open annular sector: its points have radius 3/4<∥x∥2<5/4, positive first coordinate, and angular coordinate in (−π/4,π/4). The displayed polar map is one-to-one on D with smooth inverse s=arctan⁡(y/x) and n=x2+y2−1. Let a=π/6, W(s)=(s2−a2)2, and define V(X(s,n))=W(s)+n2/2 on U. The curve R(t)=X(−a+2at,0), 0≤t≤1, is a regular MEP joining the two minima X(−a,0) and X(a,0). Its image is the circular arc of radius one. The point X(0,0) is an index-one saddle.

Facts & Assumptions

Given: The chart, potential, a=π/6, and path in the Example.

[F1]

Regular minimum-energy paths on a declared collision-free tube: a regular MEP has zero gradient component normal to its unit tangent, and the endpoints are fixed data.

[F2]

The Hessian matrix and critical points of a scalar field: at a critical point the Hessian is the matrix of second partial derivatives and its negative-eigenvalue count is the Morse index used here. Since V is C2, The Hessian of a C2 scalar field is symmetric makes that Hessian symmetric.

[F3]

The chain rule for total derivatives: D(g∘f)(a)=Dg(f(a))∘Df(a): derivatives of a scalar field in the displayed chart equal its ambient gradient paired with the chart tangent vectors.

[F4]

Since U is open, a sufficiently small convex open ball centered at X(0,0) has its closure in U. The potential is C∞ on that ball, so Multivariable Taylor formula with a Lagrange remainder along a line segment applies there; bounded third derivatives on the compact closure give a quadratic expansion with remainder O(∥x−X(0,0)∥23)=o(∥x−X(0,0)∥22).

Given: The data above.

Proof

1.1F1F3givenalgebra

Write T(s)=(−sin⁡s,cos⁡s) and N(s)=(cos⁡s,sin⁡s). Then Xs=(1+n)T(s) and Xn=N(s) are orthogonal, with lengths 1+n>0 and 1. By [F3], ∇V(X(s,n))⋅T(s)=W′(s)/(1+n) and ∇V(X(s,n))⋅N(s)=n. At n=0, the path tangent is T(s) and its unit normal is N(s), so the normal gradient component vanishes. The path is regular because ∥R′(t)∥2=2a>0; hence it is a regular MEP by [F1].

1.2givenalgebra

Since W(s)≥0 and n2/2≥0, the potential is nonnegative and equals zero exactly at (s,n)=(−a,0) and (a,0). Thus both specified endpoints are global minima on U.

2.1F2F4step 1.1givenalgebra

At (s,n)=(0,0), W′(0)=0 and n=0, so step 1.1 gives ∇V(X(0,0))=0. The coordinate Hessian of V∘X=W(s)+n2/2 is diag⁡(W′′(0),1)=diag⁡(−4a2,1). By [F4], the quadratic Taylor term of V at X(0,0) is 12vT(D2V)v+o(∥v∥22). Substituting v=X(s,n)−X(0,0)=DX(0,0)(s,n)+O(s2+n2) shows the coordinate quadratic form is DX(0,0)T(D2V)DX(0,0); the linear term vanishes because the point is critical. Since DX(0,0)=[T(0),N(0)] is orthogonal, this is an orthogonal representation of the ambient Hessian. By [F2] it has exactly one negative eigenvalue, making the point an index-one saddle.

3.1givenstep 2.1∎

The fixed-endpoint finite-image string of Finite-image projected-gradient string with arc-length redistribution can sample and redistribute this arc, but that finite procedure alone does not imply convergence to it from arbitrary initial images.

ExampleConstruction: AI-adaptedVerification: AI-generatedOpen item page →

The straight chord misses the curved double-well minimum-energy path

Example

Let D=(−π/4,π/4)×(−1/4,1/4), X(s,n)=(1+n)(cos⁡s,sin⁡s), and U=X(D). Put a=π/6, W(s)=(s2−a2)2, and V(X(s,n))=W(s)+n2/2 on U. The endpoints of the circular MEP are (cos⁡a,−sin⁡a) and (cos⁡a,sin⁡a). Their straight chord is the vertical segment C(y)=(cos⁡a,y) for −sin⁡a≤y≤sin⁡a. The chord lies inside the annular sector, but it is not a MEP.

Facts & Assumptions

Given: The sector chart and potential above, with a=π/6.

[F1]

Regular minimum-energy paths on a declared collision-free tube: a regular path is a MEP only if its gradient component normal to the path tangent vanishes at every point.

[F2]

Finite-budget improved-tangent NEB with a climbing image: the NEB tangent is constructed from adjacent image differences; an energy-selected tangent does not change the continuous MEP equation.

[F3]

The chain rule for total derivatives: D(g∘f)(a)=Dg(f(a))∘Df(a): the chart-coordinate derivative in the n direction equals the ambient gradient paired with N.

Proof

Given: The chord and potential in the Example.

1.1givenalgebra

Along C, the first coordinate is cos⁡a>0, and ∣y∣/cos⁡a≤tan⁡a<1, so the polar angle lies in [−a,a]⊂(−π/4,π/4). Its radius is between cos⁡a=3/2>3/4 and 1<5/4. Thus the whole chord is in the declared sector.

1.2F3givenalgebra

The chord's tangent is e2=(0,1). At its midpoint x0=(cos⁡a,0)=X(0,n0) with n0=cos⁡a−1≠0. In the chart Xs=(1+n)T and Xn=N, where T(0)=e2 and N(0)=e1. The coordinate derivatives of V there are ∂sV=W′(0)=0 and ∂nV=n0, so by [F3] ∇V(x0)⋅e1=n0≠0.

2.1F1F2step 1.2∎

Since e1 is perpendicular to the chord tangent e2, step 1.2 gives a nonzero normal component of the gradient at the chord midpoint. This violates the MEP condition in [F1], proving the chord is not the circular MEP. The improved tangent rule in [F2] only changes the discrete force direction; it does not make this straight segment satisfy the continuous normal-gradient equation.

ExampleConstruction: AI-adaptedVerification: AI-generatedOpen item page →

A local maximum has the wrong Morse index for the saddle certificate

Example

Let V(x,y)=−x2−y2 on U=R2. The origin is a critical point and a strict local maximum, but its Hessian has two negative eigenvalues. It therefore fails the index-one enclosure required by Validated ordered eigenvalue enclosures for an index-one Hessian and cannot be certified by Validated Hessian enclosures and a small gradient residual certify a nearby index-one saddle.

Facts & Assumptions

Given: The quadratic potential on R2 and the definitions of index-one enclosure and the local saddle certificate.

[F1]

Validated ordered eigenvalue enclosures for an index-one Hessian: an index-one enclosure requires u1≤−γ and ℓj≥γ for every j≥2.

[F2]

Validated Hessian enclosures and a small gradient residual certify a nearby index-one saddle: the nearby-saddle claim requires such an index-one enclosure at the reported point.

Given: V(x,y)=−x2−y2 and the origin.

Proof

1.1givenalgebra

The gradient is ∇V=(−2x,−2y), so it vanishes at (0,0); the Hessian is H=−2I, with ordered eigenvalues λ1=λ2=−2.

2.1F1step 1.1

For any γ>0, an interval enclosing λ2=−2 cannot have lower endpoint ℓ2≥γ>0. Thus no exact validated enclosure of this Hessian satisfies [F1].

3.1F2step 2.1∎

The point is a maximum with Morse index two, not index one. Since the required enclosure premise in [F2] fails by step 2.1, the theorem makes no certification claim for it; this example illustrates why a small gradient or critical-point report alone does not establish the desired saddle type.

ExampleConstruction: AI-adaptedVerification: AI-generatedOpen item page →

A small spectral gap makes the dimer mode sensitive to perturbations

Example

For each δ>0, let

Hδ=(−δ00δ),Eδ=(0δδ0),H^δ=Hδ+Eδ.

The exact lowest eigenvector is e1. For every z∈R2, the perturbation satisfies ∥Eδz∥2=δ∥z∥2, and this amplification tends to zero with the gap, but the lowest eigenvector of H^δ remains at angle arctan⁡(2−1)>0 from e1. Thus an absolute perturbation tolerance alone cannot guarantee a mode error tending to zero as the spectral gap collapses.

Facts & Assumptions

Given: The matrices above and the mode-separation context in A separated dimer mode gives a local inexact saddle error bound.

[F1]

A separated dimer mode gives a local inexact saddle error bound: the mode-angle bound depends on the error-to-gap ratio, not on absolute error alone.

Proof

Given: δ>0 and the two symmetric matrices in the Example.

1.1givenalgebra

The eigenvalues of Hδ are −δ and δ, with exact lowest eigenvector e1 and spectral gap 2δ. Also EδTEδ=δ2I, so for every z we have ∥Eδz∥22=zTEδTEδz=δ2∥z∥22 and hence ∥Eδz∥2=δ∥z∥2.

1.2givenalgebra

The eigenvalues of H^δ are ±2 δ. For the negative eigenvalue, the first row equation gives (−1+2)x+y=0, so a lowest unit eigenvector is proportional to (1,1−2). Its angle with e1 is therefore arctan⁡(∣1−2∣)=arctan⁡(2−1), a positive constant independent of δ.

2.1F1step 1.1step 1.2∎

As δ↓0, the perturbation norm tends to zero while this angle stays fixed at arctan⁡(2−1)>0. The spectral gap also tends to zero, so this does not contradict the separated-mode bound [F1]; it shows why that bound must include a gap scale.

ExampleConstruction: AI-adaptedVerification: AI-generatedOpen item page →

Zero discrete force does not select a unique continuum path

Example

Prescribe Cbad=∅, and let U=R2 and V≡0. Every regular path from A=(0,0) to B=(1,0) satisfies the MEP equation, so there are infinitely many distinct continuum MEPs. For a finite string with M=2, both chains

R1(0)=(1/2,0),R1(1)=(1/2,1)

have equal adjacent segment lengths and zero projected force. The improved-tangent NEB ordinary force also vanishes for both. Thus their discrete residuals are exactly zero, although their interior images differ.

Facts & Assumptions

Given: The zero potential, fixed endpoints A,B, two finite chains, and the definitions of the string, NEB, and stable path comparison.

[F1]

Regular minimum-energy paths on a declared collision-free tube: a regular path is an MEP when the normal gradient vanishes; fixed endpoints are part of the path data.

[F2]

Finite-image projected-gradient string with arc-length redistribution: the string stops when the projected-force and equal-spacing residuals are both within tolerance.

[F3]

Finite-budget improved-tangent NEB with a climbing image: the ordinary NEB force is projected gradient plus a tangential spring term.

[F4]

A gauge-fixed stable discrete path lies within second order of a smooth MEP: a local path error conclusion requires an invertible residual Jacobian with a uniform inverse bound and other stated consistency/stability hypotheses.

Proof

Given: The potential, endpoints, and finite chains in the Example.

1.1F1givenalgebra

For each c∈R, Rc(t)=(t,csin⁡(πt)) on [0,1] is regular because its first coordinate derivative is 1, and it has endpoints A,B. Since ∇V=0, every normal gradient component is zero, so [F1] makes every Rc an MEP. Distinct c give distinct paths.

1.2F2F3givenalgebra

For M=2, each listed interior point is equidistant from A and B: the two distances are 1/2 when R1=(1/2,0) and both 5/2 when R1=(1/2,1). Thus the adjacent lengths agree. Since the gradient is zero, the string projected force is zero by [F2], and the ordinary NEB spring term is also zero by [F3]. Both chains therefore have exactly zero force and spacing residuals.

2.1F4step 1.1step 1.2algebra∎

The two chains differ in their interior image, and the continuum family in step 1.1 is nonunique. In this example the string residual map has no locally invertible Jacobian that can isolate a path: its force components vanish identically and its spacing equation alone cannot determine the two coordinates of the interior image. Thus the inverse/stability premise [F4] is absent. Independently of that missing premise, the two distinct MEPs and two zero-residual chains explicitly prove nonuniqueness. Each chain's midpoint lies on its corresponding exact MEP Rc, so this is not an assertion of inaccuracy relative to every MEP. Relative to the prescribed reference R0([0,1]), however, the second chain's midpoint has Euclidean distance 1 while its residual is zero. Therefore residual alone cannot select a unique continuum MEP or bound distance to that reference by an error bound that vanishes with the residual.

Sources