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.




Contents






  • 1 Formulation


  • 2 Distribution theory


    • 2.1 Well-definedness as a distribution


    • 2.2 More general definitions




  • 3 Examples


  • 4 Notation


  • 5 See also


  • 6 References





Formulation


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:

limε0+[∫ab−εf(x)dx+∫b+εcf(x)dx]{displaystyle lim _{varepsilon rightarrow 0^{+}}left[int _{a}^{b-varepsilon }f(x),mathrm {d} x+int _{b+varepsilon }^{c}f(x),mathrm {d} xright]}{displaystyle lim _{varepsilon rightarrow 0^{+}}left[int _{a}^{b-varepsilon }f(x),mathrm {d} x+int _{b+varepsilon }^{c}f(x),mathrm {d} xright]}

where b is a point at which the behavior of the function f is such that


abf(x)dx=±{displaystyle int _{a}^{b}f(x),mathrm {d} x=pm infty }int _{a}^{b}f(x),mathrm {d} x=pm infty for any a < b and



bcf(x)dx=∓{displaystyle int _{b}^{c}f(x),mathrm {d} x=mp infty }int _{b}^{c}f(x),mathrm {d} x=mp infty for any c > b

(see plus or minus for precise usage of notations ±, ∓).


2) For a singularity at infinity:

lima→aaf(x)dx{displaystyle lim _{arightarrow infty }int _{-a}^{a}f(x),mathrm {d} x}lim _{arightarrow infty }int _{-a}^{a}f(x),mathrm {d} x

where 0f(x)dx=±{displaystyle int _{-infty }^{0}f(x),mathrm {d} x=pm infty }int _{-infty }^{0}f(x),mathrm {d} x=pm infty

and 0∞f(x)dx=∓{displaystyle int _{0}^{infty }f(x),mathrm {d} x=mp infty }int _{0}^{infty }f(x),mathrm {d} x=mp infty .

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


limε0+[∫b−b−εf(x)dx+∫b+εb+1εf(x)dx].{displaystyle 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} xright].}{displaystyle 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} xright].}

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]


P∫Cf(z) dz=limε0+∫C(ε)f(z) dz,{displaystyle mathrm {P} int _{C}f(z) mathrm {d} z=lim _{varepsilon to 0^{+}}int _{C(varepsilon )}f(z) mathrm {d} z,}{displaystyle mathrm {P} int _{C}f(z) mathrm {d} z=lim _{varepsilon to 0^{+}}int _{C(varepsilon )}f(z) mathrm {d} z,}

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 theory


Let Cc∞(R){displaystyle {C_{c}^{infty }}(mathbb {R} )}{C_{c}^{infty }}(mathbb {R} ) be the set of bump functions, i.e., the space of smooth functions with compact support on the real line R{displaystyle mathbb {R} }mathbb {R} . Then the map


p.v.⁡(1x):Cc∞(R)→C{displaystyle operatorname {p.!v.} left({frac {1}{x}}right),:,{C_{c}^{infty }}(mathbb {R} )to mathbb {C} }operatorname {p.!v.} left({frac {1}{x}}right),:,{C_{c}^{infty }}(mathbb {R} )to mathbb {C}

defined via the Cauchy principal value as


[p.v.⁡(1x)](u)=limε0+∫R∖[−ε]u(x)xdx=∫0+∞u(x)−u(−x)xdxfor u∈Cc∞(R){displaystyle left[operatorname {p.!v.} left({frac {1}{x}}right)right](u)=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} xquad {text{for }}uin {C_{c}^{infty }}(mathbb {R} )}left[operatorname {p.!v.} left({frac {1}{x}}right)right](u)=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} xquad {text{for }}uin {C_{c}^{infty }}(mathbb {R} )

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 distribution


To prove the existence of the limit


0+∞u(x)−u(−x)xdx{displaystyle int _{0}^{+infty }{frac {u(x)-u(-x)}{x}},mathrm {d} x}int _{0}^{+infty }{frac {u(x)-u(-x)}{x}},mathrm {d} x

for a Schwartz function u(x){displaystyle u(x)}u(x), first observe that u(x)−u(−x)x{displaystyle {frac {u(x)-u(-x)}{x}}}{frac {u(x)-u(-x)}{x}} is continuous on [0,∞){displaystyle [0,infty )}[0,infty ), as




limx↘0u(x)−u(−x)=0{displaystyle lim limits _{xsearrow 0}u(x)-u(-x)=0}lim limits _{xsearrow 0}u(x)-u(-x)=0 and hence

limx↘0u(x)−u(−x)x=limx↘0u′(x)+u′(−x)1=2u′(0),{displaystyle lim limits _{xsearrow 0}{frac {u(x)-u(-x)}{x}}=lim limits _{xsearrow 0}{frac {u'(x)+u'(-x)}{1}}=2u'(0),}lim limits _{xsearrow 0}{frac {u(x)-u(-x)}{x}}=lim limits _{xsearrow 0}{frac {u'(x)+u'(-x)}{1}}=2u'(0),


since u′(x){displaystyle u'(x)}u'(x) is continuous and L'Hospital's rule applies.


Therefore, 01u(x)−u(−x)xdx{displaystyle int limits _{0}^{1}{frac {u(x)-u(-x)}{x}},mathrm {d} x}int limits _{0}^{1}{frac {u(x)-u(-x)}{x}},mathrm {d} x exists and by applying the mean value theorem to u(x)−u(−x){displaystyle u(x)-u(-x)}u(x)-u(-x), we get that



|∫01u(x)−u(−x)xdx|≤01|u(x)−u(−x)|xdx≤012xxsupx∈R|u′(x)|dx≤2supx∈R|u′(x)|{displaystyle left|int limits _{0}^{1}{frac {u(x)-u(-x)}{x}},mathrm {d} xright|leq int limits _{0}^{1}{frac {|u(x)-u(-x)|}{x}},mathrm {d} xleq int limits _{0}^{1}{frac {2x}{x}}sup limits _{xin mathbb {R} }|u'(x)|,mathrm {d} xleq 2sup limits _{xin mathbb {R} }|u'(x)|}left|int limits _{0}^{1}{frac {u(x)-u(-x)}{x}},mathrm {d} xright|leq int limits _{0}^{1}{frac {|u(x)-u(-x)|}{x}},mathrm {d} xleq int limits _{0}^{1}{frac {2x}{x}}sup limits _{xin mathbb {R} }|u'(x)|,mathrm {d} xleq 2sup limits _{xin mathbb {R} }|u'(x)|.

As furthermore


|∫1∞u(x)−u(−x)xdx|≤2supx∈R|x⋅u(x)|∫1∞1x2dx=2supx∈R|x⋅u(x)|,{displaystyle left|int limits _{1}^{infty }{frac {u(x)-u(-x)}{x}},mathrm {d} xright|leq 2sup limits _{xin mathbb {R} }|xcdot u(x)|int limits _{1}^{infty }{frac {1}{x^{2}}},mathrm {d} x=2sup limits _{xin mathbb {R} }|xcdot u(x)|,}left|int limits _{1}^{infty }{frac {u(x)-u(-x)}{x}},mathrm {d} xright|leq 2sup limits _{xin mathbb {R} }|xcdot u(x)|int limits _{1}^{infty }{frac {1}{x^{2}}},mathrm {d} x=2sup limits _{xin mathbb {R} }|xcdot u(x)|,

we note that the map p.v.⁡(1x):Cc∞(R)→C{displaystyle operatorname {p.!v.} left({frac {1}{x}}right),:,{C_{c}^{infty }}(mathbb {R} )to mathbb {C} }operatorname {p.!v.} left({frac {1}{x}}right),:,{C_{c}^{infty }}(mathbb {R} )to mathbb {C} is bounded by the usual seminorms for Schwartz functions u{displaystyle u}u. 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 u{displaystyle u}u merely to be continuously differentiable in a neighbourhood of 0{displaystyle 0} 0 and xu{displaystyle xu}xu to be bounded towards infinity. The principal value therefore is defined on even weaker assumptions such as u{displaystyle u}u integrable with compact support and differentiable at 0.



More general definitions


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


xf=1⇒f=p.v.⁡(1x)+Kδ,{displaystyle xf=1quad Rightarrow quad f=operatorname {p.!v.} left({frac {1}{x}}right)+Kdelta ,}xf=1quad Rightarrow quad f=operatorname {p.!v.} left({frac {1}{x}}right)+Kdelta ,

where K{displaystyle K}K is a constant and δ{displaystyle delta }delta 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 Rn{displaystyle mathbb {R} ^{n}}mathbb {R} ^{n}. If K{displaystyle K}K 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


[p.v.⁡(K)](f)=limε0∫Rn∖(0)f(x)K(x)dx.{displaystyle [operatorname {p.!v.} (K)](f)=lim _{varepsilon to 0}int _{mathbb {R} ^{n}setminus B_{varepsilon (0)}}f(x)K(x),mathrm {d} x.}[operatorname {p.!v.} (K)](f)=lim _{varepsilon to 0}int _{mathbb {R} ^{n}setminus B_{varepsilon (0)}}f(x)K(x),mathrm {d} x.

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 K{displaystyle K}K is a continuous homogeneous function of degree n{displaystyle -n}-n 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:


lima→0+(∫1−adxx+∫a1dxx)=0,{displaystyle lim _{arightarrow 0+}left(int _{-1}^{-a}{frac {mathrm {d} x}{x}}+int _{a}^{1}{frac {mathrm {d} x}{x}}right)=0,}lim _{arightarrow 0+}left(int _{-1}^{-a}{frac {mathrm {d} x}{x}}+int _{a}^{1}{frac {mathrm {d} x}{x}}right)=0,

lima→0+(∫1−2adxx+∫a1dxx)=ln⁡2.{displaystyle lim _{arightarrow 0+}left(int _{-1}^{-2a}{frac {mathrm {d} x}{x}}+int _{a}^{1}{frac {mathrm {d} x}{x}}right)=ln 2.}lim _{arightarrow 0+}left(int _{-1}^{-2a}{frac {mathrm {d} x}{x}}+int _{a}^{1}{frac {mathrm {d} x}{x}}right)=ln 2.

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


11dxx (which gives −+∞).{displaystyle int _{-1}^{1}{frac {mathrm {d} x}{x}}{ }left({mbox{which}} {mbox{gives}} -infty +infty right).}int _{-1}^{1}{frac {mathrm {d} x}{x}}{ }left({mbox{which}} {mbox{gives}} -infty +infty right).

Similarly, we have


lima→aa2xdxx2+1=0,{displaystyle lim _{arightarrow infty }int _{-a}^{a}{frac {2x,mathrm {d} x}{x^{2}+1}}=0,}lim _{arightarrow infty }int _{-a}^{a}{frac {2x,mathrm {d} x}{x^{2}+1}}=0,

but


lima→2aa2xdxx2+1=−ln⁡4.{displaystyle lim _{arightarrow infty }int _{-2a}^{a}{frac {2x,mathrm {d} x}{x^{2}+1}}=-ln 4.}lim _{arightarrow infty }int _{-2a}^{a}{frac {2x,mathrm {d} x}{x^{2}+1}}=-ln 4.

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


2xdxx2+1 (which gives −+∞).{displaystyle int _{-infty }^{infty }{frac {2x,mathrm {d} x}{x^{2}+1}}{ }left({mbox{which}} {mbox{gives}} -infty +infty right).}int _{-infty }^{infty }{frac {2x,mathrm {d} x}{x^{2}+1}}{ }left({mbox{which}} {mbox{gives}} -infty +infty right).


Notation


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


PV∫f(x)dx,{displaystyle PVint f(x),mathrm {d} x,}PVint f(x),mathrm {d} x,

p.v.∫f(x)dx,{displaystyle mathrm {p.v.} int f(x),mathrm {d} x,}{displaystyle mathrm {p.v.} int f(x),mathrm {d} x,}

L∗f(z)dz,{displaystyle int _{L}^{*}f(z),mathrm {d} z,}int _{L}^{*}f(z),mathrm {d} z,

f(x)dx,{displaystyle -!!!!!!int f(x),mathrm {d} x,}-!!!!!!int f(x),mathrm {d} x,

as well as P,{displaystyle P,}P, P.V., P,{displaystyle {mathcal {P}},}{mathcal {P}}, Pv,{displaystyle P_{v},}P_{v}, (CPV),{displaystyle (CPV),}(CPV), and V.P.


See also



  • Hadamard finite part integral

  • Hilbert transform

  • Sokhotski–Plemelj theorem



References




  1. ^ Ram P. Kanwal (1996). Linear Integral Equations: theory and technique (2nd ed.). Boston: Birkhäuser. p. 191. ISBN 0-8176-3940-3..mw-parser-output cite.citation{font-style:inherit}.mw-parser-output q{quotes:"""""""'""'"}.mw-parser-output code.cs1-code{color:inherit;background:inherit;border:inherit;padding:inherit}.mw-parser-output .cs1-lock-free a{background:url("//upload.wikimedia.org/wikipedia/commons/thumb/6/65/Lock-green.svg/9px-Lock-green.svg.png")no-repeat;background-position:right .1em center}.mw-parser-output .cs1-lock-limited a,.mw-parser-output .cs1-lock-registration a{background:url("//upload.wikimedia.org/wikipedia/commons/thumb/d/d6/Lock-gray-alt-2.svg/9px-Lock-gray-alt-2.svg.png")no-repeat;background-position:right .1em center}.mw-parser-output .cs1-lock-subscription a{background:url("//upload.wikimedia.org/wikipedia/commons/thumb/a/aa/Lock-red-alt-2.svg/9px-Lock-red-alt-2.svg.png")no-repeat;background-position:right .1em center}.mw-parser-output .cs1-subscription,.mw-parser-output .cs1-registration{color:#555}.mw-parser-output .cs1-subscription span,.mw-parser-output .cs1-registration span{border-bottom:1px dotted;cursor:help}.mw-parser-output .cs1-hidden-error{display:none;font-size:100%}.mw-parser-output .cs1-visible-error{font-size:100%}.mw-parser-output .cs1-subscription,.mw-parser-output .cs1-registration,.mw-parser-output .cs1-format{font-size:95%}.mw-parser-output .cs1-kern-left,.mw-parser-output .cs1-kern-wl-left{padding-left:0.2em}.mw-parser-output .cs1-kern-right,.mw-parser-output .cs1-kern-wl-right{padding-right:0.2em}


  2. ^ Frederick W. King (2009). Hilbert Transforms. Cambridge: Cambridge University Press. ISBN 978-0-521-88762-5.








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