ODE Corridor Enclosures #
This file formalizes the real-analysis endpoint used by Tanaka and Yatabe, Learn and Verify: A Framework for Rigorous Verification of Physics-Informed Neural Networks, arXiv:2601.19818.
The paper trains candidate lower/upper PINN corridors and then verifies, using interval arithmetic, that they are sub- and super-solutions of a scalar ODE. Once those inequalities are certified, the mathematical argument is independent of the neural-network producer:
- Local corridor enclosure. A solution of the clamped ODE
u' = f(t, clampToCorridor uL uU t (u t))cannot cross the verified corridor[uL(t), uU(t)]. Inside the corridor, clamping is a no-op, so the same trajectory solves the original ODEu' = f(t,u). - Constant-extension enclosure. The finite-time corridor can be extended after
Tby holding both walls constant, provided the paper's sign/monotonicity hypotheses forfhold beyondT.
The proof is deliberately stated over exact ℝ functions. Floating-point or executable backends
must first justify these real hypotheses; EnclosureBackends.lean only reuses this theorem through
backend toReal views. The trust boundary is at that toReal bridge.
The theorems assume a continuous solution with the stated derivative; they do not construct a
solution or prove existence or uniqueness.
Corridor clamping #
The paper's truncation function 𝒯u(t) (Eq. 16), named here by what it does:
clamp the current value into the certified corridor [uL(t), uU(t)].
If u is below the lower wall we feed the vector field uL(t); if it is above the upper wall we
feed uU(t); otherwise we feed u itself. The enclosure theorem then proves the clamped solution
never actually needs those emergency branches.
Instances For
Local corridor enclosure #
This is the comparison theorem used in the paper's local enclosure result. It is a
“no first crossing” statement: if u evolves according to the clamped ODE
u' = f(t, clampToCorridor uL uU t (u t)), and uL,uU are a sub- and
super-solution pair for the original ODE, then u cannot leave the corridor.
We implement this by reducing to mathlib’s 1D fencing theorem
image_le_of_deriv_right_lt_deriv_boundary' twice:
- an upper fence
u ≤ uU + ε(1+t)for anyε>0; - a lower fence via the same argument applied to
-u.
Core local corridor theorem:
If u solves the clamped ODE (right-derivative form), and uL,uU are sub- and
super-solutions for the original ODE, then u is trapped between uL and uU on [0,T].
The solution and its right derivative are hypotheses; no existence or uniqueness claim is made.
Local unclamping theorem.
Once the local enclosure proves uL(t) ≤ u(t) ≤ uU(t), clampToCorridor_eq_self gives
equality of the clamped value and u(t).
A solution of the clamped ODE is therefore enclosed and solves the original ODE on the same
interval. This is the exact real-analysis contract that interval/PINN certificate producers
must establish before TorchLean can claim a verified ODE solve.
Constant-extension corridor #
Constant extension used by the paper's global-time argument: follow g until the verified
time horizon T, then freeze it at g T.
The function is intentionally right-derivative friendly. At and after T, viewed from the
right-neighborhood Ici t, the extension is locally constant and has derivative zero.
Instances For
Constant-extension enclosure theorem:
Assume we have uL,uU on [0,T] satisfying the local corridor hypotheses, and assume the paper's
extra sign/monotonicity conditions for f beyond T. Then for any horizon τ (the case of
interest being τ ≥ T; for τ ≤ T the statement reduces to the local one), any solution u of
the clamped ODE built from the constant extensions is enclosed on [0,τ] and is a genuine solution
of u' = f(t,u) on [0,τ].
This is the reusable Lean form of the paper's global-in-time step: after the verified horizon, the walls stop moving, and the vector field points inward at those frozen walls.