If a smooth real phase has a unique nondegenerate interior maximum at , thenFor a maximum at an endpoint with , the leading factor is .
If a real smooth phase has its strict maximum at the upper endpoint and , then . The endpoint coordinate has scale . At a nondegenerate stationary endpoint the scale is instead and the leading contribution is half a Gaussian integral.
A Laplace integral contains a large parameter in an exponential weight, typically in the form or . Its asymptotic behavior is controlled by the points where the real part of the phase is largest.
A linear differential-equation solution may be sought as . Integration by parts transfers the factor to derivatives of , giving an equation for the amplitude and boundary terms. Admissible contours must cancel those terms and make the integral converge.
If the maximum of the smooth real phase is an endpoint, , and , the local Gaussian is integrated over only one side of its peak. Consequentlywith the analogous formula for a right endpoint.
If a Laplace integral has finitely many separated nondegenerate global maxima with the same phase value, its leading term is the sum of their local Gaussian contributions. An interior maximum contributes a full Gaussian integral, while a stationary endpoint maximum contributes half of one.
Suppose a real phase has its unique minimum at the left endpoint and , with and integer . For a continuous amplitude with , localization followed by givesThis uses the Gamma integral. It assumes sufficient decay away from the minimum to make the remaining integral negligible. A cubic endpoint has width ; an ordinary quadratic endpoint has width .
For a Laplace integral with local phase , , an interior minimum approaches the endpoint as . The distinguished limit is , . With , its leading local integral isThe cubic Laplace transition integral joins the ordinary endpoint estimate for positive , the cubic endpoint estimate at zero, and the interior Laplace's method estimate for negative . Separate fixed-parameter formulas fail to be uniform when the minimum is within its own width of the endpoint.
The discrete Laplace method estimates a sum whose positive terms concentrate near the maximum of a smooth exponent. When the Gaussian concentration width contains asymptotically many lattice points, the sum is a Riemann-sum version of Laplace's method with the corresponding lattice-spacing factor.