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.
Formulation
Depending on the type of singularity in the integrand f, the Cauchy principal value is defined as one of the following:
- 1) The finite number
- where b is a point at which the behavior of the function f is such that
 for any a < b and for any a < b and
 
 for any c > b for any c > b
- (see plus or minus for precise usage of notations ±, ∓).
 
- 2) The infinite number
- where  
 
- where 
- and  . .
 
- 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
- 3) In terms of contour integrals
of a complex-valued function f(z); z = x + iy, with a pole on the contour. The pole is enclosed with a circle of radius ε and the portion of the path outside this circle is denoted L(ε). Provided the function f(z) is integrable over L(ε) no matter how small ε becomes, then the Cauchy principal value is the limit:[1]
- where two of the common notations for the Cauchy principal value appear on the left of this equation.
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.
Principal value integrals play a central role in the discussion of Hilbert transforms.[2]
Distribution theory
Let  be the set of bump functions, i.e., the space of smooth functions with compact support on the real line
 be the set of bump functions, i.e., the space of smooth functions with compact support on the real line  . Then the map
. 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 Heaviside step function.
Well-definedness as a distribution
To prove the existence of the limit
for a Schwartz function  , first observe that
, first observe that  is continuous on
  is continuous on   , as
, as
 and hence and hence
 
since  is continuous and LHospitals rule applies.
 is continuous and LHospitals rule applies.
Therefore,   exists and by applying the mean value theorem to
 exists and by applying the mean value theorem to  , we get that
, we get that
 . .
As furthermore
we note that the map  is bounded by the usual seminorms for Schwartz functions
 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.
. 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
 merely to be continuously differentiable in a neighbourhood of  and
 and  to be bounded towards infinity. The principal value therefore is defined on even weaker assumptions such as
 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.
 integrable with compact support and differentiable at 0.
More general definitions
The principal value is the inverse distribution of the function  and is almost the only distribution with this property:
 and is almost the only distribution with this property:
where  is a constant and
 is a constant and  the Dirac distribution.
 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
. 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
 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
 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.
 whose integral over any sphere centered at the origin vanishes. This is the case, for instance, with the Riesz transforms.
Examples
Consider the difference in values of two limits:
The former is the Cauchy principal value of the otherwise ill-defined expression
Similarly, we have
but
The former is the principal value of the otherwise ill-defined expression
Nomenclature
The Cauchy principal value of a function  can take on several nomenclatures, varying for different authors. Among these are:
 can take on several nomenclatures, varying for different authors. Among these are:
-  as well as  P.V., P.V.,     and V.P. and V.P.
See also
References
- ↑ Ram P. Kanwal (1996). Linear Integral Equations: theory and technique (2nd ed.). Boston: Birkhäuser. p. 191. ISBN 0-8176-3940-3.
- ↑ Frederick W. King (2009). Hilbert Transforms. Cambridge: Cambridge University Press. ISBN 978-0-521-88762-5.
![\lim_{\varepsilon\rightarrow 0+} \left[\int_a^{b-\varepsilon} f(x)\,\mathrm{d}x+\int_{b+\varepsilon}^c f(x)\,\mathrm{d}x\right]](../I/m/1f57a4f36dedbb7128e6e67a5e8d9967.png)

![\lim_{\varepsilon \rightarrow 0+} \left[\int_{b-\frac{1}{\varepsilon}}^{b-\varepsilon} f(x)\,\mathrm{d}x+\int_{b+\varepsilon}^{b+\frac{1}{\varepsilon}}f(x)\,\mathrm{d}x \right].](../I/m/33bdc0417410697e8c18c022eb15d73d.png)

 = \lim_{\varepsilon \to 0^{+}} \int_{\mathbb{R} \setminus [- \varepsilon;\varepsilon]} \frac{u(x)}{x} \, \mathrm{d} x = \int_{0}^{+ \infty} \frac{u(x) - u(- x)}{x} \, \mathrm{d} x \quad \text{for } u \in {C_{c}^{\infty}}(\mathbb{R})](../I/m/71b0e6ce0b054a3e849a32c6278d87c2.png)



 = \lim_{\varepsilon \to 0} \int_{\mathbb{R}^{n} \setminus B_{\varepsilon(0)}} f(x) K(x) \, \mathrm{d} x.](../I/m/4040efb84e0f9385c33e70b1fa4567e7.png)








