在數學中,梅林變換是一種以冪函數為核的積分變換,與雙邊拉普拉斯變換有密切關聯。梅林變換定義式如下: { M f } ( s ) = φ ( s ) = ∫ 0 ∞ x s − 1 f ( x ) d x . {\displaystyle \left\{{\mathcal {M}}f\right\}(s)=\varphi (s)=\int _{0}^{\infty }x^{s-1}f(x)dx.} 此條目可參照英語維基百科相應條目來擴充。 (2020年4月28日) 而其逆變換為 { M − 1 φ } ( x ) = f ( x ) = 1 2 π i ∫ c − i ∞ c + i ∞ x − s φ ( s ) d s . {\displaystyle \left\{{\mathcal {M}}^{-1}\varphi \right\}(x)=f(x)={\frac {1}{2\pi i}}\int _{c-i\infty }^{c+i\infty }x^{-s}\varphi (s)\,ds.} 梅林變換有許多應用。出於它與狄利克雷級數的聯繫,它也被用以證明黎曼ζ函數與素數計數函數有關的的函數方程;進一步地,它也與解析數論有關,如在佩龍公式中。 同時,它與伽馬函數密切相關,很多常見函數的梅林變換中都需要用到伽馬函數或它衍生出的貝塔函數;這使得它被運用在梅林-巴恩斯積分和超幾何函數的理論中,衍生出了在計算機代數系統中使用的,可以快速計算大量定積分的Meijer_G-函數。 Remove ads 之所以伽馬函數與積分變換的理論聯繫密切,是因為伽馬函數同時是指數函數的拉普拉斯變換和冪函數的梅林變換,這也展示了兩種積分變換之間的聯繫。 雙邊拉普拉斯變換 雙邊拉普拉斯變換可以用梅林變換來表示,如下式 { B f } ( s ) = { M f ( − ln x ) } ( s ) {\displaystyle \left\{{\mathcal {B}}f\right\}(s)=\left\{{\mathcal {M}}f(-\ln x)\right\}(s)} 梅林變換也可以用雙邊拉普拉斯變換來表示,如下式 { M f } ( s ) = { B f ( e − x ) } ( s ) {\displaystyle \left\{{\mathcal {M}}f\right\}(s)=\left\{{\mathcal {B}}f(e^{-x})\right\}(s)} Remove ads傅立葉變換 傅立葉變換可以用梅林變換來表示,如下式 { F f } ( − s ) = { B f } ( − i s ) = { M f ( − ln x ) } ( − i s ) {\displaystyle \left\{{\mathcal {F}}f\right\}(-s)=\left\{{\mathcal {B}}f\right\}(-is)=\left\{{\mathcal {M}}f(-\ln x)\right\}(-is)\ } 梅林變換變換也可以用傅立葉來表示,如下式 { M f } ( s ) = { B f ( e − x ) } ( s ) = { F f ( e − x ) } ( − i s ) {\displaystyle \left\{{\mathcal {M}}f\right\}(s)=\left\{{\mathcal {B}}f(e^{-x})\right\}(s)=\left\{{\mathcal {F}}f(e^{-x})\right\}(-is)\ } Remove ads Cahen–Mellin 積分 對於 c > 0 {\displaystyle c>0} , ℜ ( y ) > 0 {\displaystyle \Re (y)>0} ,且 y − s {\displaystyle y^{-s}} 在主要分支(principal branch)上,我們有 e − y = 1 2 π i ∫ c − i ∞ c + i ∞ Γ ( s ) y − s d s {\displaystyle e^{-y}={\frac {1}{2\pi i}}\int _{c-i\infty }^{c+i\infty }\Gamma (s)y^{-s}\;ds} 其中 Γ ( s ) {\displaystyle \Gamma (s)} 為 Γ函數。 Remove ads數論 假設 ℜ ( s + a ) < 0 {\displaystyle \Re (s+a)<0} 我們有 f ( x ) = { 0 x < 1 x a x > 1 {\displaystyle f(x)={\begin{cases}0&x<1\\x^{a}&x>1\end{cases}}} 其中 M f ( s ) = − 1 s + a {\displaystyle {\mathcal {M}}f(s)=-{\frac {1}{s+a}}} Remove ads 在任何維度的圓柱坐標系中,拉普拉斯算子總是會包含下式 1 r ∂ ∂ r ( r ∂ f ∂ r ) {\displaystyle {\frac {1}{r}}{\frac {\partial }{\partial r}}\left(r{\frac {\partial f}{\partial r}}\right)} 例如,拉普拉斯算子在二維空間的極坐標表示法 ∇ 2 f = 1 r ∂ ∂ r ( r ∂ f ∂ r ) + 1 r 2 ∂ 2 f ∂ θ 2 {\displaystyle \nabla ^{2}f={\frac {1}{r}}{\frac {\partial }{\partial r}}\left(r{\frac {\partial f}{\partial r}}\right)+{\frac {1}{r^{2}}}{\frac {\partial ^{2}f}{\partial \theta ^{2}}}} 或是在三維空間的柱坐標表示法 ∇ 2 f = 1 r ∂ ∂ r ( r ∂ f ∂ r ) + 1 r 2 ∂ 2 f ∂ φ 2 + ∂ 2 f ∂ z 2 {\displaystyle \nabla ^{2}f={\frac {1}{r}}{\frac {\partial }{\partial r}}\left(r{\frac {\partial f}{\partial r}}\right)+{\frac {1}{r^{2}}}{\frac {\partial ^{2}f}{\partial \varphi ^{2}}}+{\frac {\partial ^{2}f}{\partial z^{2}}}} 而利用梅林變換可以很簡單的處理此項 1 r ∂ ∂ r ( r ∂ f ∂ r ) = f r r + f r r {\displaystyle {\frac {1}{r}}{\frac {\partial }{\partial r}}\left(r{\frac {\partial f}{\partial r}}\right)=f_{rr}+{\frac {f_{r}}{r}}} M ( r 2 f r r + r f r , r → s ) = s 2 M ( f , r → s ) = s 2 F {\displaystyle {\mathcal {M}}\left(r^{2}f_{rr}+rf_{r},r\to s\right)=s^{2}{\mathcal {M}}\left(f,r\to s\right)=s^{2}F} 舉例來說,二維拉普拉斯方程的極坐標表示法具有以下形式 r 2 f r r + r f r + f θ θ = 0 {\displaystyle r^{2}f_{rr}+rf_{r}+f_{\theta \theta }=0} 或是 1 r ∂ ∂ r ( r ∂ f ∂ r ) + 1 r 2 ∂ 2 f ∂ θ 2 = 0 {\displaystyle {\frac {1}{r}}{\frac {\partial }{\partial r}}\left(r{\frac {\partial f}{\partial r}}\right)+{\frac {1}{r^{2}}}{\frac {\partial ^{2}f}{\partial \theta ^{2}}}=0} 利用梅林變換,可以轉換成一個簡諧振子的形式 F θ θ + s 2 F = 0 {\displaystyle F_{\theta \theta }+s^{2}F=0} 通解為 F ( s , θ ) = C 1 ( s ) cos ( s θ ) + C 2 ( s ) sin ( s θ ) {\displaystyle F(s,\theta )=C_{1}(s)\cos(s\theta )+C_{2}(s)\sin(s\theta )} 若給定邊界條件 f ( r , − θ 0 ) = a ( r ) , f ( r , θ 0 ) = b ( r ) {\displaystyle f(r,-\theta _{0})=a(r),\quad f(r,\theta _{0})=b(r)} 其梅林變換為 F ( s , − θ 0 ) = A ( s ) , F ( s , θ 0 ) = B ( s ) {\displaystyle F(s,-\theta _{0})=A(s),\quad F(s,\theta _{0})=B(s)} 則通解可以寫成 F ( s , θ ) = A ( s ) sin ( s ( θ 0 − θ ) ) sin ( 2 θ 0 s ) + B ( s ) sin ( s ( θ 0 + θ ) ) sin ( 2 θ 0 s ) {\displaystyle F(s,\theta )=A(s){\frac {\sin(s(\theta _{0}-\theta ))}{\sin(2\theta _{0}s)}}+B(s){\frac {\sin(s(\theta _{0}+\theta ))}{\sin(2\theta _{0}s)}}} 最後利用逆變換以及卷積定理 M − 1 ( sin ( s φ ) sin ( 2 θ 0 s ) ; s → r ) = 1 2 θ 0 r m sin ( m φ ) 1 + 2 r m cos ( m φ ) + r 2 m {\displaystyle {\mathcal {M}}^{-1}\left({\frac {\sin(s\varphi )}{\sin(2\theta _{0}s)}};s\to r\right)={\frac {1}{2\theta _{0}}}{\frac {r^{m}\sin(m\varphi )}{1+2r^{m}\cos(m\varphi )+r^{2m}}}} 其中 m = π 2 θ 0 {\displaystyle m={\frac {\pi }{2\theta _{0}}}} 可以得到 f ( r , θ ) = r m cos ( m θ ) 2 θ 0 ∫ 0 ∞ { a ( x ) x 2 m + 2 r m x m sin ( m θ ) + r 2 m + b ( x ) x 2 m − 2 r m x m sin ( m θ ) + r 2 m } x m − 1 d x {\displaystyle f(r,\theta )={\frac {r^{m}\cos(m\theta )}{2\theta _{0}}}\int _{0}^{\infty }\left\{{\frac {a(x)}{x^{2m}+2r^{m}x^{m}\sin(m\theta )+r^{2m}}}+{\frac {b(x)}{x^{2m}-2r^{m}x^{m}\sin(m\theta )+r^{2m}}}\right\}x^{m-1}\,dx} Remove ads 因為具有尺度不變性(英語:Scale_invariance),梅林變換廣泛應用於計算機科學的算法分析。[1]對於純虛輸入,原函數函數的梅林變換與對其進行尺度伸縮後函數的梅林變換幅度相同。尺度不變性類似於傅里葉變換的時移不變性,即原函數與對其進行時移的函數的傅里葉變換幅度相同。這一性質對圖像識別非常有用:當物體與攝像機的距離發生變化時,圖像尺度會發生變化。 在量子力學(特別是量子場論)中,由於動量和位置之間存在傅里葉變化的關係,傅里葉空間被廣泛應用。2011年,A. Liam Fitzpatrick、Jared Kaplan、João Penedones(英語:João_Penedones)、Suvrat Raju(英語:Suvrat_Raju)和Balt C. van Rees證明了梅林空間在AdS/CFT對偶中具有類似的效用。[2][3][4] 下表展示了部分函數的梅林變化結果,在Bracewell (2000) harvtxt模板錯誤: 無指向目標: CITEREFBracewell2000 (幫助)與Erdélyi (1954) harvtxt模板錯誤: 無指向目標: CITEREFErdélyi1954 (幫助)中可以找到。 更多信息 函數 ... 梅林變化表 函數 f ( x ) {\displaystyle f(x)} 梅林變換 f ~ ( s ) = M { f } ( s ) {\displaystyle {\tilde {f}}(s)={\mathcal {M}}\{f\}(s)} 收斂域 注釋 e − x {\displaystyle e^{-x}} Γ ( s ) {\displaystyle \Gamma (s)} 0 < ℜ s < ∞ {\displaystyle 0<\Re s<\infty } e − x − 1 {\displaystyle e^{-x}-1} Γ ( s ) {\displaystyle \Gamma (s)} − 1 < ℜ s < 0 {\displaystyle -1<\Re s<0} e − x − 1 + x {\displaystyle e^{-x}-1+x} Γ ( s ) {\displaystyle \Gamma (s)} − 2 < ℜ s < − 1 {\displaystyle -2<\Re s<-1} 一般來說, Γ ( s ) {\displaystyle \Gamma (s)} 是 e − x − ∑ n = 0 N − 1 ( − 1 ) n n ! x n , for − N < ℜ s < − N + 1 {\displaystyle e^{-x}-\sum _{n=0}^{N-1}{\frac {(-1)^{n}}{n!}}x^{n},{\text{ for }}-N<\Re s<-N+1} 的梅林變換。[5] e − x 2 {\displaystyle e^{-x^{2}}} 1 2 Γ ( 1 2 s ) {\displaystyle {\tfrac {1}{2}}\Gamma ({\tfrac {1}{2}}s)} 0 < ℜ s < ∞ {\displaystyle 0<\Re s<\infty } e r f c ( x ) {\displaystyle \mathrm {erfc} (x)} Γ ( 1 2 ( 1 + s ) ) π s {\displaystyle {\frac {\Gamma ({\tfrac {1}{2}}(1+s))}{{\sqrt {\pi }}\;s}}} 0 < ℜ s < ∞ {\displaystyle 0<\Re s<\infty } e − ( ln x ) 2 {\displaystyle e^{-(\ln x)^{2}}} π e 1 4 s 2 {\displaystyle {\sqrt {\pi }}\,e^{{\tfrac {1}{4}}s^{2}}} − ∞ < ℜ s < ∞ {\displaystyle -\infty <\Re s<\infty } δ ( x − a ) {\displaystyle \delta (x-a)} a s − 1 {\displaystyle a^{s-1}} − ∞ < ℜ s < ∞ {\displaystyle -\infty <\Re s<\infty } a > 0 , δ ( x ) {\displaystyle a>0,\;\delta (x)} 是狄拉克函數。 u ( 1 − x ) = { 1 if 0 < x < 1 0 if 1 < x < ∞ {\displaystyle u(1-x)=\left\{{\begin{aligned}&1&&\;{\text{if}}\;0<x<1&\\&0&&\;{\text{if}}\;1<x<\infty &\end{aligned}}\right.} 1 s {\displaystyle {\frac {1}{s}}} 0 < ℜ s < ∞ {\displaystyle 0<\Re s<\infty } u ( x ) {\displaystyle u(x)} 是單位階躍函數。 − u ( x − 1 ) = { 0 if 0 < x < 1 − 1 if 1 < x < ∞ {\displaystyle -u(x-1)=\left\{{\begin{aligned}&0&&\;{\text{if}}\;0<x<1&\\&-1&&\;{\text{if}}\;1<x<\infty &\end{aligned}}\right.} 1 s {\displaystyle {\frac {1}{s}}} − ∞ < ℜ s < 0 {\displaystyle -\infty <\Re s<0} u ( 1 − x ) x a = { x a if 0 < x < 1 0 if 1 < x < ∞ {\displaystyle u(1-x)\,x^{a}=\left\{{\begin{aligned}&x^{a}&&\;{\text{if}}\;0<x<1&\\&0&&\;{\text{if}}\;1<x<\infty &\end{aligned}}\right.} 1 s + a {\displaystyle {\frac {1}{s+a}}} − ℜ a < ℜ s < ∞ {\displaystyle -\Re a<\Re s<\infty } − u ( x − 1 ) x a = { 0 if 0 < x < 1 − x a if 1 < x < ∞ {\displaystyle -u(x-1)\,x^{a}=\left\{{\begin{aligned}&0&&\;{\text{if}}\;0<x<1&\\&-x^{a}&&\;{\text{if}}\;1<x<\infty &\end{aligned}}\right.} 1 s + a {\displaystyle {\frac {1}{s+a}}} − ∞ < ℜ s < − ℜ a {\displaystyle -\infty <\Re s<-\Re a} u ( 1 − x ) x a ln x = { x a ln x if 0 < x < 1 0 if 1 < x < ∞ {\displaystyle u(1-x)\,x^{a}\ln x=\left\{{\begin{aligned}&x^{a}\ln x&&\;{\text{if}}\;0<x<1&\\&0&&\;{\text{if}}\;1<x<\infty &\end{aligned}}\right.} 1 ( s + a ) 2 {\displaystyle {\frac {1}{(s+a)^{2}}}} − ℜ a < ℜ s < ∞ {\displaystyle -\Re a<\Re s<\infty } − u ( x − 1 ) x a ln x = { 0 if 0 < x < 1 − x a ln x if 1 < x < ∞ {\displaystyle -u(x-1)\,x^{a}\ln x=\left\{{\begin{aligned}&0&&\;{\text{if}}\;0<x<1&\\&-x^{a}\ln x&&\;{\text{if}}\;1<x<\infty &\end{aligned}}\right.} 1 ( s + a ) 2 {\displaystyle {\frac {1}{(s+a)^{2}}}} − ∞ < ℜ s < − ℜ a {\displaystyle -\infty <\Re s<-\Re a} 1 1 + x {\displaystyle {\frac {1}{1+x}}} π sin ( π s ) {\displaystyle {\frac {\pi }{\sin(\pi s)}}} 0 < ℜ s < 1 {\displaystyle 0<\Re s<1} 1 1 − x {\displaystyle {\frac {1}{1-x}}} π tan ( π s ) {\displaystyle {\frac {\pi }{\tan(\pi s)}}} 0 < ℜ s < 1 {\displaystyle 0<\Re s<1} 1 1 + x 2 {\displaystyle {\frac {1}{1+x^{2}}}} π 2 sin ( 1 2 π s ) {\displaystyle {\frac {\pi }{2\sin({\tfrac {1}{2}}\pi s)}}} 0 < ℜ s < 2 {\displaystyle 0<\Re s<2} ln ( 1 + x ) {\displaystyle \ln(1+x)} π s sin ( π s ) {\displaystyle {\frac {\pi }{s\,\sin(\pi s)}}} − 1 < ℜ s < 0 {\displaystyle -1<\Re s<0} sin ( x ) {\displaystyle \sin(x)} sin ( 1 2 π s ) Γ ( s ) {\displaystyle \sin({\tfrac {1}{2}}\pi s)\,\Gamma (s)} − 1 < ℜ s < 1 {\displaystyle -1<\Re s<1} cos ( x ) {\displaystyle \cos(x)} cos ( 1 2 π s ) Γ ( s ) {\displaystyle \cos({\tfrac {1}{2}}\pi s)\,\Gamma (s)} 0 < ℜ s < 1 {\displaystyle 0<\Re s<1} e i x {\displaystyle e^{ix}} e i π s / 2 Γ ( s ) {\displaystyle e^{i\pi s/2}\,\Gamma (s)} 0 < ℜ s < 1 {\displaystyle 0<\Re s<1} J 0 ( x ) {\displaystyle J_{0}(x)} 2 s − 1 π sin ( π s / 2 ) [ Γ ( s / 2 ) ] 2 {\displaystyle {\frac {2^{s-1}}{\pi }}\,\sin(\pi s/2)\,\left[\Gamma (s/2)\right]^{2}} 0 < ℜ s < 3 2 {\displaystyle 0<\Re s<{\tfrac {3}{2}}} J 0 ( x ) {\displaystyle J_{0}(x)} 是第一類貝塞爾函數。 Y 0 ( x ) {\displaystyle Y_{0}(x)} − 2 s − 1 π cos ( π s / 2 ) [ Γ ( s / 2 ) ] 2 {\displaystyle -{\frac {2^{s-1}}{\pi }}\,\cos(\pi s/2)\,\left[\Gamma (s/2)\right]^{2}} 0 < ℜ s < 3 2 {\displaystyle 0<\Re s<{\tfrac {3}{2}}} Y 0 ( x ) {\displaystyle Y_{0}(x)} 是第二類貝塞爾函數。 K 0 ( x ) {\displaystyle K_{0}(x)} 2 s − 2 [ Γ ( s / 2 ) ] 2 {\displaystyle 2^{s-2}\,\left[\Gamma (s/2)\right]^{2}} 0 < ℜ s < ∞ {\displaystyle 0<\Re s<\infty } K 0 ( x ) {\displaystyle K_{0}(x)} 是第二類修正貝塞爾函數。 关闭 Galambos, Janos; Simonelli, Italo. Products of random variables: applications to problems of physics and to arithmetical functions. Marcel Dekker, Inc. 2004. ISBN 0-8247-5402-6. [1]Philippe Flajolet and Robert Sedgewick. The Average Case Analysis of Algorithms: Mellin Transform Asymptotics. Research Report 2956. 93 pages. Institut National de Recherche en Informatique et en Automatique (INRIA), 1996. [2]Fitzpatrick, A. Liam; Kaplan, Jared; Penedones, Joao; Raju, Suvrat; van Rees, Balt C. A Natural Language for AdS/CFT Correlators. Journal of High Energy Physics. 2011-11, 2011 (11) [2015-11-27]. ISSN 1029-8479. doi:10.1007/JHEP11(2011)095. (原始內容存檔於2022-12-25). [3]Fitzpatrick, A. Liam; Kaplan, Jared. Unitarity and the Holographic S-Matrix. Journal of High Energy Physics. 2012-10, 2012 (10) [2015-11-27]. ISSN 1029-8479. doi:10.1007/JHEP10(2012)032. (原始內容存檔於2023-11-16). [4]A. Liam Fitzpatrick. "AdS/CFT and the Holographic S-Matrix" (頁面存檔備份,存於網際網路檔案館), video lecture. [5]Jacqueline Bertrand, Pierre Bertrand, Jean-Philippe Ovarlez. The Mellin Transform. The Transforms and Applications Handbook, 1995, 978-1420066524. ffhal-03152634f Wikiwand in your browser!Seamless Wikipedia browsing. On steroids.Every time you click a link to Wikipedia, Wiktionary or Wikiquote in your browser's search results, it will show the modern Wikiwand interface.Wikiwand extension is a five stars, simple, with minimum permission required to keep your browsing private, safe and transparent.Wikiwand for ChromeWikiwand for EdgeWikiwand for FirefoxRemove ads
Every time you click a link to Wikipedia, Wiktionary or Wikiquote in your browser's search results, it will show the modern Wikiwand interface.Wikiwand extension is a five stars, simple, with minimum permission required to keep your browsing private, safe and transparent.