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Cauchy principal value

In mathematics, the Cauchy principal value, named after Augustin Louis Cauchy, is a method for assigning values to certain improper integrals which would otherwise be undefined.


Depending on the type of singularity in the integrand f, the Cauchy principal value is defined according to the following rules:

1) For a singularity at the finite number b:
where b is a point at which the behavior of the function f is such that
  for any a < b and
  for any c > b
(see plus or minus for precise usage of notations ±, ∓).
2) For a singularity at infinity:
and  .

In some cases it is necessary to deal simultaneously with singularities both at a finite number b and at infinity. This is usually done by a limit of the form


The Cauchy principal value can also be defined in terms of contour integrals of a complex-valued function f(z); z = x + iy, with a pole on a contour C. Define C(ε) to be the same contour where the portion inside the disk of radius ε around the pole has been removed. Provided the function f(z) is integrable over C(ε) no matter how small ε becomes, then the Cauchy principal value is the limit:[1]


In the case of Lebesgue-integrable functions, that is, functions which are integrable in absolute value, these definitions coincide with the standard definition of the integral.

If the function f(z) is meromorphic, the Sokhotski–Plemelj theorem relates the principal value of the integral over C with the mean-value of the integrals with the contour displaced slightly above and below, so that the residue theorem can be applied to those integrals.

Principal value integrals play a central role in the discussion of Hilbert transforms.[2]

Distribution theoryEdit

Let   be the set of bump functions, i.e., the space of smooth functions with compact support on the real line  . Then the map


defined via the Cauchy principal value as


is a distribution. The map itself may sometimes be called the principal value (hence the notation p.v.). This distribution appears, for example, in the Fourier transform of the Sign function and the Heaviside step function.

Well-definedness as a distributionEdit

To prove the existence of the limit


for a Schwartz function  , first observe that   is continuous on  , as

  and hence

since   is continuous and L'Hospital's rule applies.

Therefore,   exists and by applying the mean value theorem to  , we get that


As furthermore


we note that the map   is bounded by the usual seminorms for Schwartz functions  . Therefore, this map defines, as it is obviously linear, a continuous functional on the Schwartz space and therefore a tempered distribution.

Note that the proof needs   merely to be continuously differentiable in a neighbourhood of   and   to be bounded towards infinity. The principal value therefore is defined on even weaker assumptions such as   integrable with compact support and differentiable at 0.

More general definitionsEdit

The principal value is the inverse distribution of the function   and is almost the only distribution with this property:


where   is a constant and   the Dirac distribution.

In a broader sense, the principal value can be defined for a wide class of singular integral kernels on the Euclidean space  . If   has an isolated singularity at the origin, but is an otherwise "nice" function, then the principal-value distribution is defined on compactly supported smooth functions by


Such a limit may not be well defined, or, being well-defined, it may not necessarily define a distribution. It is, however, well-defined if   is a continuous homogeneous function of degree   whose integral over any sphere centered at the origin vanishes. This is the case, for instance, with the Riesz transforms.


Consider the difference in values of two limits:


The former is the Cauchy principal value of the otherwise ill-defined expression


Similarly, we have




The former is the principal value of the otherwise ill-defined expression



Different authors use different notations for the Cauchy principal value of a function  , among others:

as well as   P.V.,       and V.P.

See alsoEdit


  1. ^ Ram P. Kanwal (1996). Linear Integral Equations: theory and technique (2nd ed.). Boston: Birkhäuser. p. 191. ISBN 0-8176-3940-3.
  2. ^ Frederick W. King (2009). Hilbert Transforms. Cambridge: Cambridge University Press. ISBN 978-0-521-88762-5.