Plot of the hyperbolic sine integral functionShi(z ) in the complex plane from−2 − 2i to2 + 2i
Special function defined by an integral
Si(x ) (blue) andCi(x ) (green) shown on the same plot.Sine integral in the complex plane, plotted with a variant ofdomain coloring . Cosine integral in the complex plane. Note thebranch cut along the negative real axis.Inmathematics ,trigonometric integrals are afamily ofnonelementary integrals involvingtrigonometric functions .
Plot ofSi(x ) for0 ≤x ≤ 8π . Plot of the cosine integral functionCi(z ) in the complex plane from−2 − 2i to2 + 2i The differentsine integral definitions areSi ( x ) = ∫ 0 x sin t t d t {\displaystyle \operatorname {Si} (x)=\int _{0}^{x}{\frac {\sin t}{t}}\,dt} si ( x ) = − ∫ x ∞ sin t t d t . {\displaystyle \operatorname {si} (x)=-\int _{x}^{\infty }{\frac {\sin t}{t}}\,dt~.}
Note that the integrandsin ( t ) t {\displaystyle {\frac {\sin(t)}{t}}} is thesinc function , and also the zerothspherical Bessel function .Sincesinc is aneven entire function (holomorphic over the entire complex plane),Si is entire, odd, and the integral in its definition can be taken alongany path connecting the endpoints.
By definition,Si(x ) is theantiderivative ofsinx /x whose value is zero atx = 0 , andsi(x ) is the antiderivative whose value is zero atx = ∞ . Their difference is given by theDirichlet integral ,Si ( x ) − si ( x ) = ∫ 0 ∞ sin t t d t = π 2 or Si ( x ) = π 2 + si ( x ) . {\displaystyle \operatorname {Si} (x)-\operatorname {si} (x)=\int _{0}^{\infty }{\frac {\sin t}{t}}\,dt={\frac {\pi }{2}}\quad {\text{ or }}\quad \operatorname {Si} (x)={\frac {\pi }{2}}+\operatorname {si} (x)~.}
Insignal processing , the oscillations of the sine integral causeovershoot andringing artifacts when using thesinc filter , andfrequency domain ringing if using a truncated sinc filter as alow-pass filter .
Related is theGibbs phenomenon : If the sine integral is considered as theconvolution of the sinc function with theHeaviside step function , this corresponds to truncating theFourier series , which is the cause of the Gibbs phenomenon.
Plot ofCi(x ) for0 <x ≤ 8π The differentcosine integral definitions areCin ( x ) ≡ ∫ 0 x 1 − cos t t d t . {\displaystyle \operatorname {Cin} (x)~\equiv ~\int _{0}^{x}{\frac {\ 1-\cos t\ }{t}}\ \operatorname {d} t~.}
Cin is aneven ,entire function . For that reason, some texts define Cin as the primary function, and derive Ci in terms of Cin .
Ci ( x ) ≡ − ∫ x ∞ cos t t d t {\displaystyle \operatorname {Ci} (x)~~\equiv ~-\int _{x}^{\infty }{\frac {\ \cos t\ }{t}}\ \operatorname {d} t~} = γ + ln x − ∫ 0 x 1 − cos t t d t {\displaystyle ~~\qquad ~=~~\gamma ~+~\ln x~-~\int _{0}^{x}{\frac {\ 1-\cos t\ }{t}}\ \operatorname {d} t~}
= γ + ln x − Cin x {\displaystyle ~~\qquad ~=~~\gamma ~+~\ln x~-~\operatorname {Cin} x~} for | Arg ( x ) | < π , {\displaystyle ~{\Bigl |}\ \operatorname {Arg} (x)\ {\Bigr |}<\pi \ ,} where γ ≈ 0.57721566490 ... is theEuler–Mascheroni constant . Some texts use ci instead of Ci . The restriction on Arg(x) is to avoid a discontinuity (shown as the orange vs blue area on the left half of theplot above ) that arises because of abranch cut in the standardlogarithm function ( ln ).
Ci(x ) is the antiderivative of cosx / x (which vanishes as x → ∞ {\displaystyle \ x\to \infty \ } ). The two definitions are related byCi ( x ) = γ + ln x − Cin ( x ) . {\displaystyle \operatorname {Ci} (x)=\gamma +\ln x-\operatorname {Cin} (x)~.}
Hyperbolic sine integral [ edit ] Thehyperbolic sine integral is defined asShi ( x ) = ∫ 0 x sinh ( t ) t d t . {\displaystyle \operatorname {Shi} (x)=\int _{0}^{x}{\frac {\sinh(t)}{t}}\,dt.}
It is related to the ordinary sine integral bySi ( i x ) = i Shi ( x ) . {\displaystyle \operatorname {Si} (ix)=i\operatorname {Shi} (x).}
Hyperbolic cosine integral [ edit ] Thehyperbolic cosine integral is
Plot of the hyperbolic cosine integral functionChi(z ) in the complex plane from−2 − 2i to2 + 2i Chi ( x ) = γ + ln x + ∫ 0 x cosh t − 1 t d t for | Arg ( x ) | < π , {\displaystyle \operatorname {Chi} (x)=\gamma +\ln x+\int _{0}^{x}{\frac {\cosh t-1}{t}}\,dt\qquad ~{\text{ for }}~\left|\operatorname {Arg} (x)\right|<\pi ~,} whereγ {\displaystyle \gamma } is theEuler–Mascheroni constant .
It has the series expansionChi ( x ) = γ + ln ( x ) + x 2 4 + x 4 96 + x 6 4320 + x 8 322560 + x 10 36288000 + O ( x 12 ) . {\displaystyle \operatorname {Chi} (x)=\gamma +\ln(x)+{\frac {x^{2}}{4}}+{\frac {x^{4}}{96}}+{\frac {x^{6}}{4320}}+{\frac {x^{8}}{322560}}+{\frac {x^{10}}{36288000}}+O(x^{12}).}
Auxiliary functions [ edit ] Trigonometric integrals can be understood in terms of the so-called "auxiliary functions "f ( x ) ≡ ∫ 0 ∞ sin ( t ) t + x d t = ∫ 0 ∞ e − x t t 2 + 1 d t = Ci ( x ) sin ( x ) + [ π 2 − Si ( x ) ] cos ( x ) , g ( x ) ≡ ∫ 0 ∞ cos ( t ) t + x d t = ∫ 0 ∞ t e − x t t 2 + 1 d t = − Ci ( x ) cos ( x ) + [ π 2 − Si ( x ) ] sin ( x ) . {\displaystyle {\begin{array}{rcl}f(x)&\equiv &\int _{0}^{\infty }{\frac {\sin(t)}{t+x}}\,dt&=&\int _{0}^{\infty }{\frac {e^{-xt}}{t^{2}+1}}\,dt&=&\operatorname {Ci} (x)\sin(x)+\left[{\frac {\pi }{2}}-\operatorname {Si} (x)\right]\cos(x)~,\\g(x)&\equiv &\int _{0}^{\infty }{\frac {\cos(t)}{t+x}}\,dt&=&\int _{0}^{\infty }{\frac {te^{-xt}}{t^{2}+1}}\,dt&=&-\operatorname {Ci} (x)\cos(x)+\left[{\frac {\pi }{2}}-\operatorname {Si} (x)\right]\sin(x)~.\end{array}}} Using these functions, the trigonometric integrals may be re-expressed as (cf. Abramowitz & Stegun,p. 232 )π 2 − Si ( x ) = − si ( x ) = f ( x ) cos ( x ) + g ( x ) sin ( x ) , and Ci ( x ) = f ( x ) sin ( x ) − g ( x ) cos ( x ) . {\displaystyle {\begin{array}{rcl}{\frac {\pi }{2}}-\operatorname {Si} (x)=-\operatorname {si} (x)&=&f(x)\cos(x)+g(x)\sin(x)~,\qquad {\text{ and }}\\\operatorname {Ci} (x)&=&f(x)\sin(x)-g(x)\cos(x)~.\\\end{array}}}
Nielsen's spiral. Thespiral formed by parametric plot ofsi, ci is known as Nielsen's spiral.x ( t ) = a × ci ( t ) {\displaystyle x(t)=a\times \operatorname {ci} (t)} y ( t ) = a × si ( t ) {\displaystyle y(t)=a\times \operatorname {si} (t)}
The spiral is closely related to theFresnel integrals and theEuler spiral . Nielsen's spiral has applications in vision processing, road and track construction and other areas.[ 1]
Various expansions can be used for evaluation of trigonometric integrals, depending on the range of the argument.
Asymptotic series (for large argument)[ edit ] Si ( x ) ∼ π 2 − cos x x ( 1 − 2 ! x 2 + 4 ! x 4 − 6 ! x 6 ⋯ ) − sin x x ( 1 x − 3 ! x 3 + 5 ! x 5 − 7 ! x 7 ⋯ ) {\displaystyle \operatorname {Si} (x)\sim {\frac {\pi }{2}}-{\frac {\cos x}{x}}\left(1-{\frac {2!}{x^{2}}}+{\frac {4!}{x^{4}}}-{\frac {6!}{x^{6}}}\cdots \right)-{\frac {\sin x}{x}}\left({\frac {1}{x}}-{\frac {3!}{x^{3}}}+{\frac {5!}{x^{5}}}-{\frac {7!}{x^{7}}}\cdots \right)} Ci ( x ) ∼ sin x x ( 1 − 2 ! x 2 + 4 ! x 4 − 6 ! x 6 ⋯ ) − cos x x ( 1 x − 3 ! x 3 + 5 ! x 5 − 7 ! x 7 ⋯ ) . {\displaystyle \operatorname {Ci} (x)\sim {\frac {\sin x}{x}}\left(1-{\frac {2!}{x^{2}}}+{\frac {4!}{x^{4}}}-{\frac {6!}{x^{6}}}\cdots \right)-{\frac {\cos x}{x}}\left({\frac {1}{x}}-{\frac {3!}{x^{3}}}+{\frac {5!}{x^{5}}}-{\frac {7!}{x^{7}}}\cdots \right)~.}
These series areasymptotic and divergent, although can be used for estimates and even precise evaluation atℜ(x ) ≫ 1 .
Si ( x ) = ∑ n = 0 ∞ ( − 1 ) n x 2 n + 1 ( 2 n + 1 ) ( 2 n + 1 ) ! = x − x 3 3 ! ⋅ 3 + x 5 5 ! ⋅ 5 − x 7 7 ! ⋅ 7 ± ⋯ {\displaystyle \operatorname {Si} (x)=\sum _{n=0}^{\infty }{\frac {(-1)^{n}x^{2n+1}}{(2n+1)(2n+1)!}}=x-{\frac {x^{3}}{3!\cdot 3}}+{\frac {x^{5}}{5!\cdot 5}}-{\frac {x^{7}}{7!\cdot 7}}\pm \cdots } Ci ( x ) = γ + ln x + ∑ n = 1 ∞ ( − 1 ) n x 2 n 2 n ( 2 n ) ! = γ + ln x − x 2 2 ! ⋅ 2 + x 4 4 ! ⋅ 4 ∓ ⋯ {\displaystyle \operatorname {Ci} (x)=\gamma +\ln x+\sum _{n=1}^{\infty }{\frac {(-1)^{n}x^{2n}}{2n(2n)!}}=\gamma +\ln x-{\frac {x^{2}}{2!\cdot 2}}+{\frac {x^{4}}{4!\cdot 4}}\mp \cdots }
These series are convergent at any complexx , although for|x | ≫ 1 , the series will converge slowly initially, requiring many terms for high precision.
Derivation of series expansion [ edit ] From the Maclaurin series expansion of sine:sin x = x − x 3 3 ! + x 5 5 ! − x 7 7 ! + x 9 9 ! − x 11 11 ! + ⋯ {\displaystyle \sin \,x=x-{\frac {x^{3}}{3!}}+{\frac {x^{5}}{5!}}-{\frac {x^{7}}{7!}}+{\frac {x^{9}}{9!}}-{\frac {x^{11}}{11!}}+\cdots } sin x x = 1 − x 2 3 ! + x 4 5 ! − x 6 7 ! + x 8 9 ! − x 10 11 ! + ⋯ {\displaystyle {\frac {\sin \,x}{x}}=1-{\frac {x^{2}}{3!}}+{\frac {x^{4}}{5!}}-{\frac {x^{6}}{7!}}+{\frac {x^{8}}{9!}}-{\frac {x^{10}}{11!}}+\cdots } ∴ ∫ sin x x d x = x − x 3 3 ! ⋅ 3 + x 5 5 ! ⋅ 5 − x 7 7 ! ⋅ 7 + x 9 9 ! ⋅ 9 − x 11 11 ! ⋅ 11 + ⋯ {\displaystyle \therefore \int {\frac {\sin \,x}{x}}dx=x-{\frac {x^{3}}{3!\cdot 3}}+{\frac {x^{5}}{5!\cdot 5}}-{\frac {x^{7}}{7!\cdot 7}}+{\frac {x^{9}}{9!\cdot 9}}-{\frac {x^{11}}{11!\cdot 11}}+\cdots }
Relation with the exponential integral of imaginary argument [ edit ] The functionE 1 ( z ) = ∫ 1 ∞ exp ( − z t ) t d t for ℜ ( z ) ≥ 0 {\displaystyle \operatorname {E} _{1}(z)=\int _{1}^{\infty }{\frac {\exp(-zt)}{t}}\,dt\qquad ~{\text{ for }}~\Re (z)\geq 0} is called theexponential integral . It is closely related toSi andCi ,E 1 ( i x ) = i ( − π 2 + Si ( x ) ) − Ci ( x ) = i si ( x ) − ci ( x ) for x > 0 . {\displaystyle \operatorname {E} _{1}(ix)=i\left(-{\frac {\pi }{2}}+\operatorname {Si} (x)\right)-\operatorname {Ci} (x)=i\operatorname {si} (x)-\operatorname {ci} (x)\qquad ~{\text{ for }}~x>0~.}
As each respective function is analytic except for the cut at negative values of the argument, the area of validity of the relation should be extended to (Outside this range, additional terms which are integer factors ofπ appear in the expression.)
Cases of imaginary argument of the generalized integro-exponential function are∫ 1 ∞ cos ( a x ) ln x x d x = − π 2 24 + γ ( γ 2 + ln a ) + ln 2 a 2 + ∑ n ≥ 1 ( − a 2 ) n ( 2 n ) ! ( 2 n ) 2 , {\displaystyle \int _{1}^{\infty }\cos(ax){\frac {\ln x}{x}}\,dx=-{\frac {\pi ^{2}}{24}}+\gamma \left({\frac {\gamma }{2}}+\ln a\right)+{\frac {\ln ^{2}a}{2}}+\sum _{n\geq 1}{\frac {(-a^{2})^{n}}{(2n)!(2n)^{2}}}~,} which is the real part of∫ 1 ∞ e i a x ln x x d x = − π 2 24 + γ ( γ 2 + ln a ) + ln 2 a 2 − π 2 i ( γ + ln a ) + ∑ n ≥ 1 ( i a ) n n ! n 2 . {\displaystyle \int _{1}^{\infty }e^{iax}{\frac {\ln x}{x}}\,dx=-{\frac {\pi ^{2}}{24}}+\gamma \left({\frac {\gamma }{2}}+\ln a\right)+{\frac {\ln ^{2}a}{2}}-{\frac {\pi }{2}}i\left(\gamma +\ln a\right)+\sum _{n\geq 1}{\frac {(ia)^{n}}{n!n^{2}}}~.}
Similarly∫ 1 ∞ e i a x ln x x 2 d x = 1 + i a [ − π 2 24 + γ ( γ 2 + ln a − 1 ) + ln 2 a 2 − ln a + 1 ] + π a 2 ( γ + ln a − 1 ) + ∑ n ≥ 1 ( i a ) n + 1 ( n + 1 ) ! n 2 . {\displaystyle \int _{1}^{\infty }e^{iax}{\frac {\ln x}{x^{2}}}\,dx=1+ia\left[-{\frac {\pi ^{2}}{24}}+\gamma \left({\frac {\gamma }{2}}+\ln a-1\right)+{\frac {\ln ^{2}a}{2}}-\ln a+1\right]+{\frac {\pi a}{2}}{\Bigl (}\gamma +\ln a-1{\Bigr )}+\sum _{n\geq 1}{\frac {(ia)^{n+1}}{(n+1)!n^{2}}}~.}
Efficient evaluation [ edit ] Padé approximants of the convergent Taylor series provide an efficient way to evaluate the functions for small arguments. The following formulae, given by Rowe et al. (2015),[ 2] are accurate to better than10−16 for0 ≤x ≤ 4 ,Si ( x ) ≈ x ⋅ ( 1 − 4.54393409816329991 ⋅ 10 − 2 ⋅ x 2 + 1.15457225751016682 ⋅ 10 − 3 ⋅ x 4 − 1.41018536821330254 ⋅ 10 − 5 ⋅ x 6 + 9.43280809438713025 ⋅ 10 − 8 ⋅ x 8 − 3.53201978997168357 ⋅ 10 − 10 ⋅ x 10 + 7.08240282274875911 ⋅ 10 − 13 ⋅ x 12 − 6.05338212010422477 ⋅ 10 − 16 ⋅ x 14 1 + 1.01162145739225565 ⋅ 10 − 2 ⋅ x 2 + 4.99175116169755106 ⋅ 10 − 5 ⋅ x 4 + 1.55654986308745614 ⋅ 10 − 7 ⋅ x 6 + 3.28067571055789734 ⋅ 10 − 10 ⋅ x 8 + 4.5049097575386581 ⋅ 10 − 13 ⋅ x 10 + 3.21107051193712168 ⋅ 10 − 16 ⋅ x 12 ) Ci ( x ) ≈ γ + ln ( x ) + x 2 ⋅ ( − 0.25 + 7.51851524438898291 ⋅ 10 − 3 ⋅ x 2 − 1.27528342240267686 ⋅ 10 − 4 ⋅ x 4 + 1.05297363846239184 ⋅ 10 − 6 ⋅ x 6 − 4.68889508144848019 ⋅ 10 − 9 ⋅ x 8 + 1.06480802891189243 ⋅ 10 − 11 ⋅ x 10 − 9.93728488857585407 ⋅ 10 − 15 ⋅ x 12 1 + 1.1592605689110735 ⋅ 10 − 2 ⋅ x 2 + 6.72126800814254432 ⋅ 10 − 5 ⋅ x 4 + 2.55533277086129636 ⋅ 10 − 7 ⋅ x 6 + 6.97071295760958946 ⋅ 10 − 10 ⋅ x 8 + 1.38536352772778619 ⋅ 10 − 12 ⋅ x 10 + 1.89106054713059759 ⋅ 10 − 15 ⋅ x 12 + 1.39759616731376855 ⋅ 10 − 18 ⋅ x 14 ) {\displaystyle {\begin{array}{rcl}\operatorname {Si} (x)&\approx &x\cdot \left({\frac {\begin{array}{l}1-4.54393409816329991\cdot 10^{-2}\cdot x^{2}+1.15457225751016682\cdot 10^{-3}\cdot x^{4}-1.41018536821330254\cdot 10^{-5}\cdot x^{6}\\~~~+9.43280809438713025\cdot 10^{-8}\cdot x^{8}-3.53201978997168357\cdot 10^{-10}\cdot x^{10}+7.08240282274875911\cdot 10^{-13}\cdot x^{12}\\~~~-6.05338212010422477\cdot 10^{-16}\cdot x^{14}\end{array}}{\begin{array}{l}1+1.01162145739225565\cdot 10^{-2}\cdot x^{2}+4.99175116169755106\cdot 10^{-5}\cdot x^{4}+1.55654986308745614\cdot 10^{-7}\cdot x^{6}\\~~~+3.28067571055789734\cdot 10^{-10}\cdot x^{8}+4.5049097575386581\cdot 10^{-13}\cdot x^{10}+3.21107051193712168\cdot 10^{-16}\cdot x^{12}\end{array}}}\right)\\&~&\\\operatorname {Ci} (x)&\approx &\gamma +\ln(x)+\\&&x^{2}\cdot \left({\frac {\begin{array}{l}-0.25+7.51851524438898291\cdot 10^{-3}\cdot x^{2}-1.27528342240267686\cdot 10^{-4}\cdot x^{4}+1.05297363846239184\cdot 10^{-6}\cdot x^{6}\\~~~-4.68889508144848019\cdot 10^{-9}\cdot x^{8}+1.06480802891189243\cdot 10^{-11}\cdot x^{10}-9.93728488857585407\cdot 10^{-15}\cdot x^{12}\\\end{array}}{\begin{array}{l}1+1.1592605689110735\cdot 10^{-2}\cdot x^{2}+6.72126800814254432\cdot 10^{-5}\cdot x^{4}+2.55533277086129636\cdot 10^{-7}\cdot x^{6}\\~~~+6.97071295760958946\cdot 10^{-10}\cdot x^{8}+1.38536352772778619\cdot 10^{-12}\cdot x^{10}+1.89106054713059759\cdot 10^{-15}\cdot x^{12}\\~~~+1.39759616731376855\cdot 10^{-18}\cdot x^{14}\\\end{array}}}\right)\end{array}}}
The integrals may be evaluated indirectly viaauxiliary functions f ( x ) {\displaystyle f(x)} andg ( x ) {\displaystyle g(x)} , which are defined by
Forx ≥ 4 {\displaystyle x\geq 4} thePadé rational functions given below approximatef ( x ) {\displaystyle f(x)} andg ( x ) {\displaystyle g(x)} with error less than 10−16 :[ 2]
f ( x ) ≈ 1 x ⋅ ( 1 + 7.44437068161936700618 ⋅ 10 2 ⋅ x − 2 + 1.96396372895146869801 ⋅ 10 5 ⋅ x − 4 + 2.37750310125431834034 ⋅ 10 7 ⋅ x − 6 + 1.43073403821274636888 ⋅ 10 9 ⋅ x − 8 + 4.33736238870432522765 ⋅ 10 10 ⋅ x − 10 + 6.40533830574022022911 ⋅ 10 11 ⋅ x − 12 + 4.20968180571076940208 ⋅ 10 12 ⋅ x − 14 + 1.00795182980368574617 ⋅ 10 13 ⋅ x − 16 + 4.94816688199951963482 ⋅ 10 12 ⋅ x − 18 − 4.94701168645415959931 ⋅ 10 11 ⋅ x − 20 1 + 7.46437068161927678031 ⋅ 10 2 ⋅ x − 2 + 1.97865247031583951450 ⋅ 10 5 ⋅ x − 4 + 2.41535670165126845144 ⋅ 10 7 ⋅ x − 6 + 1.47478952192985464958 ⋅ 10 9 ⋅ x − 8 + 4.58595115847765779830 ⋅ 10 10 ⋅ x − 10 + 7.08501308149515401563 ⋅ 10 11 ⋅ x − 12 + 5.06084464593475076774 ⋅ 10 12 ⋅ x − 14 + 1.43468549171581016479 ⋅ 10 13 ⋅ x − 16 + 1.11535493509914254097 ⋅ 10 13 ⋅ x − 18 ) g ( x ) ≈ 1 x 2 ⋅ ( 1 + 8.1359520115168615 ⋅ 10 2 ⋅ x − 2 + 2.35239181626478200 ⋅ 10 5 ⋅ x − 4 + 3.12557570795778731 ⋅ 10 7 ⋅ x − 6 + 2.06297595146763354 ⋅ 10 9 ⋅ x − 8 + 6.83052205423625007 ⋅ 10 10 ⋅ x − 10 + 1.09049528450362786 ⋅ 10 12 ⋅ x − 12 + 7.57664583257834349 ⋅ 10 12 ⋅ x − 14 + 1.81004487464664575 ⋅ 10 13 ⋅ x − 16 + 6.43291613143049485 ⋅ 10 12 ⋅ x − 18 − 1.36517137670871689 ⋅ 10 12 ⋅ x − 20 1 + 8.19595201151451564 ⋅ 10 2 ⋅ x − 2 + 2.40036752835578777 ⋅ 10 5 ⋅ x − 4 + 3.26026661647090822 ⋅ 10 7 ⋅ x − 6 + 2.23355543278099360 ⋅ 10 9 ⋅ x − 8 + 7.87465017341829930 ⋅ 10 10 ⋅ x − 10 + 1.39866710696414565 ⋅ 10 12 ⋅ x − 12 + 1.17164723371736605 ⋅ 10 13 ⋅ x − 14 + 4.01839087307656620 ⋅ 10 13 ⋅ x − 16 + 3.99653257887490811 ⋅ 10 13 ⋅ x − 18 ) {\displaystyle {\begin{array}{rcl}f(x)&\approx &{\dfrac {1}{x}}\cdot \left({\frac {\begin{array}{l}1+7.44437068161936700618\cdot 10^{2}\cdot x^{-2}+1.96396372895146869801\cdot 10^{5}\cdot x^{-4}+2.37750310125431834034\cdot 10^{7}\cdot x^{-6}\\~~~+1.43073403821274636888\cdot 10^{9}\cdot x^{-8}+4.33736238870432522765\cdot 10^{10}\cdot x^{-10}+6.40533830574022022911\cdot 10^{11}\cdot x^{-12}\\~~~+4.20968180571076940208\cdot 10^{12}\cdot x^{-14}+1.00795182980368574617\cdot 10^{13}\cdot x^{-16}+4.94816688199951963482\cdot 10^{12}\cdot x^{-18}\\~~~-4.94701168645415959931\cdot 10^{11}\cdot x^{-20}\end{array}}{\begin{array}{l}1+7.46437068161927678031\cdot 10^{2}\cdot x^{-2}+1.97865247031583951450\cdot 10^{5}\cdot x^{-4}+2.41535670165126845144\cdot 10^{7}\cdot x^{-6}\\~~~+1.47478952192985464958\cdot 10^{9}\cdot x^{-8}+4.58595115847765779830\cdot 10^{10}\cdot x^{-10}+7.08501308149515401563\cdot 10^{11}\cdot x^{-12}\\~~~+5.06084464593475076774\cdot 10^{12}\cdot x^{-14}+1.43468549171581016479\cdot 10^{13}\cdot x^{-16}+1.11535493509914254097\cdot 10^{13}\cdot x^{-18}\end{array}}}\right)\\&&\\g(x)&\approx &{\dfrac {1}{x^{2}}}\cdot \left({\frac {\begin{array}{l}1+8.1359520115168615\cdot 10^{2}\cdot x^{-2}+2.35239181626478200\cdot 10^{5}\cdot x^{-4}+3.12557570795778731\cdot 10^{7}\cdot x^{-6}\\~~~+2.06297595146763354\cdot 10^{9}\cdot x^{-8}+6.83052205423625007\cdot 10^{10}\cdot x^{-10}+1.09049528450362786\cdot 10^{12}\cdot x^{-12}\\~~~+7.57664583257834349\cdot 10^{12}\cdot x^{-14}+1.81004487464664575\cdot 10^{13}\cdot x^{-16}+6.43291613143049485\cdot 10^{12}\cdot x^{-18}\\~~~-1.36517137670871689\cdot 10^{12}\cdot x^{-20}\end{array}}{\begin{array}{l}1+8.19595201151451564\cdot 10^{2}\cdot x^{-2}+2.40036752835578777\cdot 10^{5}\cdot x^{-4}+3.26026661647090822\cdot 10^{7}\cdot x^{-6}\\~~~+2.23355543278099360\cdot 10^{9}\cdot x^{-8}+7.87465017341829930\cdot 10^{10}\cdot x^{-10}+1.39866710696414565\cdot 10^{12}\cdot x^{-12}\\~~~+1.17164723371736605\cdot 10^{13}\cdot x^{-14}+4.01839087307656620\cdot 10^{13}\cdot x^{-16}+3.99653257887490811\cdot 10^{13}\cdot x^{-18}\end{array}}}\right)\\\end{array}}}
Mathar, R.J. (2009). "Numerical evaluation of the oscillatory integral over exp(iπx )·x 1/x between 1 and ∞". Appendix B.arXiv :0912.3844 [math.CA ]. Press, W.H.; Teukolsky, S.A.; Vetterling, W.T.; Flannery, B.P. (2007)."Section 6.8.2 – Cosine and Sine Integrals" .Numerical Recipes: The Art of Scientific Computing (3rd ed.). New York: Cambridge University Press.ISBN 978-0-521-88068-8 . Sloughter, Dan."Sine Integral Taylor series proof" (PDF) .Difference Equations to Differential Equations . Temme, N.M. (2010),"Exponential, Logarithmic, Sine, and Cosine Integrals" , inOlver, Frank W. J. ; Lozier, Daniel M.; Boisvert, Ronald F.; Clark, Charles W. (eds.),NIST Handbook of Mathematical Functions , Cambridge University Press,ISBN 978-0-521-19225-5 ,MR 2723248 .