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{{Short description|Mathematical function common in physics}}
[[Image:Pibmasterplot.png|325px|thumb|'''Figure 1'''. Illustration of a stretched exponential fit (with ''β''=0.52) to an empirical master curve. For comparison, a least squares single and a [[Laplace distribution|double exponential]] fit are also shown. The data are rotational [[anisotropy]] of [[anthracene]] in [[polyisobutylene]] of several [[molecular mass]]es. The plots have been made to overlap by dividing time (''t'') by the respective characteristic [[time constant]].]]▼
[[File:Stretched exponential.svg|325px|thumb|'''Figure 1'''. Plot of {{math|1=''f''<sub>''β''</sub>(''t'') = ''e''<sup>−''t''<sup>''β''</sup></sup>}} for varying values of ''β'', with stretched exponentials ({{math|1=''β'' < 1}}) in reddish colors, compressed exponentials ({{math|1=''β'' > 1}}) in green and blue colors, and the standard exponential function in yellow. The [[degenerate case]]s {{math|1=''β'' → 0}} and {{math|1=''β'' → +∞}} are marked in dotted lines.]]
The '''stretched exponential function''' <math display="block">f_\beta (t) = e^{ -t^\beta }</math> is obtained by inserting a fractional [[power law]] into the [[exponential function]]. In most applications, it is meaningful only for arguments {{mvar|t}} between 0 and +∞. With {{math|1=''β'' = 1}}, the usual exponential function is recovered. With a ''stretching exponent'' ''β'' between 0 and 1, the graph of log ''f'' versus ''t'' is characteristically ''stretched'', hence the name of the function. The '''compressed exponential function''' (with {{math|1=''β'' > 1}}) has less practical importance, with the notable exceptions of {{math|1=''β'' = 2}}, which gives the [[normal distribution]], and of compressed exponential relaxation in the dynamics of [[amorphous solids]].<ref>{{Cite journal |last1=Trachenko |first1=K. |last2=Zaccone |first2=A.|date=2021-06-14 |title=Slow stretched-exponential and fast compressed-exponential relaxation from local event dynamics |url=https://iopscience.iop.org/article/10.1088/1361-648X/ac04cd |journal=Journal of Physics: Condensed Matter |language=en |volume=33 |issue= |pages=315101 |doi= 10.1088/1361-648X/ac04cd|bibcode= |issn=0953-8984|arxiv=2010.10440 }}</ref>
In mathematics, the stretched exponential is also known as the [[Cumulative distribution function#Complementary cumulative distribution function (tail distribution)|complementary cumulative]] [[Weibull distribution]]. The stretched exponential is also the [[characteristic function (probability theory)|characteristic function]], basically the [[Fourier transform]], of the [[stable distribution|Lévy symmetric alpha-stable distribution]].
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| url = http://gallica.bnf.fr/ark:/12148/bpt6k15176w.pagination| doi = 10.1002/andp.18541670103
| bibcode = 1854AnP...167...56K
}}.</ref> thus it is also known as the '''Kohlrausch function'''. In 1970, G. Williams and D.C. Watts used the [[Fourier transform]] of the stretched exponential to describe [[dielectric spectroscopy|dielectric spectra]] of polymers;<ref>{{cite journal▼
}}.</ref>▼
▲thus it is also known as the '''Kohlrausch function'''. In 1970, G. Williams and D.C. Watts used the [[Fourier transform]] of the stretched exponential to describe [[dielectric spectroscopy|dielectric spectra]] of polymers;<ref>{{cite journal
▲ |author1=Williams, G. |author2=Watts, D. C.
|name-list-style=amp | year = 1970
| title = Non-Symmetrical Dielectric Relaxation Behavior Arising from a Simple Empirical Decay Function
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| pages = 80–85
| doi = 10.1039/tf9706600080
|s2cid=95007734
}}.</ref> in this context, the stretched exponential or its Fourier transform are also called the '''Kohlrausch–Williams–Watts (KWW) function'''. The Kohlrausch–Williams–Watts (KWW) function corresponds to the time ___domain charge response of the main dielectric models, such as the [[Cole–Cole equation]], the [[Cole–Davidson equation]], and the [[Havriliak–Negami relaxation]], for small time arguments.<ref>{{Cite journal |last=Holm|first=Sverre|title=Time ___domain characterization of the Cole-Cole dielectric model |journal=Journal of Electrical Bioimpedance |year=2020 |volume=11 |issue=1 |pages=101–105|doi=10.2478/joeb-2020-0015|pmid=33584910 |pmc=7851980 }}</ref>
In phenomenological applications, it is often not clear whether the stretched exponential function should be used to describe the differential or the integral distribution function—or
|author1=Donsker, M. D. |author2=Varadhan, S. R. S.
|name-list-style=amp | journal = Comm. Pure Appl. Math.
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| title = Stretched exponential decay of the spin-correlation function in the kinetic Ising model below the critical temperature
|bibcode = 1988PhRvB..37.3716T |doi = 10.1103/PhysRevB.37.3716 | pmid = 9944981
}}</ref><ref>{{cite journal
| author = Shore, John E. and Zwanzig, Robert
| journal = The Journal of Chemical Physics
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| title = Dielectric relaxation and dynamic susceptibility of a one-dimensional model for perpendicular-dipole polymers
|doi = 10.1063/1.431279| bibcode = 1975JChPh..63.5445S
}}</ref><ref>{{cite journal
| author = Brey, J. J. and Prados, A.
| journal = Physica A
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| pages = 569–582
| year = 1993
| title = Stretched exponential decay at intermediate times in the one-
|doi = 10.1016/0378-4371(93)90015-V | bibcode = 1993PhyA..197..569B
}}</ref> it can be shown that the asymptotic decay is a stretched exponential, but the prefactor is usually an unrelated power.▼
▲it can be shown that the asymptotic decay is a stretched exponential, but the prefactor is usually an unrelated power.
== Mathematical properties ==
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=== Moments ===
Following the usual physical interpretation, we interpret the function argument ''t'' as time, and ''f''<sub>β</sub>(''t'') is the differential distribution. The area under the curve can thus be interpreted as a ''mean relaxation time''. One finds
where {{math|Γ}} is the [[gamma function]]. For [[exponential decay]],
The higher [[moment (mathematics)|moments]] of the stretched exponential function are<ref name="Zwillinger_2014">{{cite book |author-first1=Izrail Solomonovich |author-last1=Gradshteyn |author-link1=Izrail Solomonovich Gradshteyn |author-first2=Iosif Moiseevich |author-last2=Ryzhik |author-link2=Iosif Moiseevich Ryzhik |author-first3=Yuri Veniaminovich |author-last3=Geronimus |author-link3=Yuri Veniaminovich Geronimus |author-first4=Michail Yulyevich |author-last4=Tseytlin |author-link4=Michail Yulyevich Tseytlin |author-first5=Alan |author-last5=Jeffrey |editor-first1=Daniel |editor-last1=Zwillinger |editor-first2=Victor Hugo |editor-last2=Moll |editor-link2=Victor Hugo Moll |translator=Scripta Technica, Inc. |title=Table of Integrals, Series, and Products |publisher=[[Academic Press, Inc.]] |date=2015 |orig-year=October 2014 |edition=8 |language=English |isbn=978-0-12-384933-5 |lccn=2014010276 <!-- |url=https://books.google.com/books?id=NjnLAwAAQBAJ |access-date=2016-02-21-->|title-link=Gradshteyn and Ryzhik |chapter=3.478. |page=372}}</ref>▼
▲:<math>\langle\tau\rangle \equiv \int_0^\infty dt\, e^{-(t/\tau_K)^\beta} = {\tau_K \over \beta } \Gamma \left({1 \over \beta }\right)</math>
=== Distribution function ===▼
▲where Γ is the [[gamma function]]. For exponential decay, 〈''τ''〉 = ''τ''<sub>''K''</sub> is recovered.
In physics, attempts have been made to explain stretched exponential behaviour as a linear superposition of simple exponential decays. This requires a nontrivial distribution of relaxation times, ''ρ''(''u
▲<ref name="Zwillinger_2014">{{cite book |author-first1=Izrail Solomonovich |author-last1=Gradshteyn |author-link1=Izrail Solomonovich Gradshteyn |author-first2=Iosif Moiseevich |author-last2=Ryzhik |author-link2=Iosif Moiseevich Ryzhik |author-first3=Yuri Veniaminovich |author-last3=Geronimus |author-link3=Yuri Veniaminovich Geronimus |author-first4=Michail Yulyevich |author-last4=Tseytlin |author-link4=Michail Yulyevich Tseytlin |author-first5=Alan |author-last5=Jeffrey |editor-first1=Daniel |editor-last1=Zwillinger |editor-first2=Victor Hugo |editor-last2=Moll |translator=Scripta Technica, Inc. |title=Table of Integrals, Series, and Products |publisher=[[Academic Press, Inc.]] |date=2015 |orig-year=October 2014 |edition=8 |language=English |isbn=978-0-12-384933-5 |lccn=2014010276 <!-- |url=https://books.google.com/books?id=NjnLAwAAQBAJ |access-date=2016-02-21-->|title-link=Gradshteyn and Ryzhik |chapter=3.478. |page=372}}</ref>
Alternatively, a distribution <math display="block">G = u \rho (u)</math> is used.
▲: <math>\langle\tau^n\rangle \equiv \int_0^\infty dt\, t^{n-1}\, e^{-(t/\tau_K)^\beta} = {{\tau_K}^n \over \beta }\Gamma \left({n \over \beta }\right).</math>
▲===Distribution function===
▲In physics, attempts have been made to explain stretched exponential behaviour as a linear superposition of simple exponential decays. This requires a nontrivial distribution of relaxation times, ''ρ(u)'', which is implicitly defined by
▲: <math>e^{-t^\beta} = \int_0^\infty du\,\rho(u)\, e^{-t/u}.</math>
''ρ'' can be computed from the series expansion:<ref>{{cite journal
| author1=Lindsey, C. P.
| name-list-style=amp | year = 1980
| title = Detailed comparison of the Williams-Watts and Cole-Davidson functions
| journal = [[Journal of Chemical Physics]]
| volume = 73
| issue = 7
| pages = 3348–3357
| doi = 10.1063/1.440530 | bibcode = 1980JChPh..73.3348L }}.
For a more recent and general discussion, see {{cite journal
| author = Berberan-Santos, M.N., Bodunov, E.N. and Valeur, B.
Line 118 ⟶ 101:
| doi = 10.1016/j.chemphys.2005.04.006
|bibcode = 2005CP....315..171B }}.</ref>
For rational values of ''β'', ''ρ''(''u'') can be calculated in terms of elementary functions. But the expression is in general too complex to be useful except for the case ''β'' = 1/2 where▼
▲For rational values of ''β'', ''ρ''(''u'') can be calculated in terms of elementary functions. But the expression is in general too complex to be useful except for the case {{math|1=''β''
<math display="block">G(u) = u \rho(u) = { 1 \over 2\sqrt{\pi}} \sqrt{u}
</math>
Figure 2 shows the same results plotted in both a [[linear]] and a [[Logarithm|log]] representation. The curves converge to a [[Dirac delta function]] peaked at {{math|1=''u''
{| class="wikitable" style="margin: 1em auto 1em auto"
|-
| [[Image:KWW dist. function linear.png|300px]] || [[Image:KWW dist. funct. log.png|300px]]
|-
| colspan=2 | '''Figure 2'''. Linear and log-log plots of the stretched exponential distribution function <math>G</math> vs <math>t/\tau</math>
for values of the stretching parameter ''β'' between 0.1 and 0.9.
|}
The moments of the original function can be expressed as
The first logarithmic moment of the distribution of simple-exponential relaxation times is
where Eu is the [[Euler constant]].<ref>{{cite journal
| doi = 10.1063/1.1446035
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| issue = 6
| pages = 061510
| doi = 10.1103/physreve.65.061510
| bibcode = 2002PhRvE..65f1510H
| s2cid = 16276298
}}</ref> For practical purposes, the Fourier transform may be approximated by the [[Havriliak–Negami relaxation|Havriliak–Negami function]],<ref>{{cite journal
| author = Alvarez, F., Alegría, A. and Colmenero, J.
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| doi = 10.1103/PhysRevB.44.7306
| pmid = 9998642
| bibcode = 1991PhRvB..44.7306A }}</ref> though nowadays the numeric computation can be done so efficiently<ref>{{cite journal
| author = Wuttke, J.
| year = 2012
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| issue = 4
| pages = 604–628
| doi = 10.3390/a5040604 | arxiv = 0911.4796
| s2cid = 15030084
| doi-access = free
}}</ref> that there is no longer any reason not to use the Kohlrausch–Williams–Watts function in the frequency ___domain.
== History and further applications ==
▲[[Image:Pibmasterplot.png|325px|thumb|'''Figure
As said in the introduction, the stretched exponential was introduced by the [[Germans|German]] [[physics|physicist]] [[Rudolf Kohlrausch]] in 1854 to describe the discharge of a capacitor ([[Leyden jar]]) that used glass as dielectric medium. The next documented usage is by [[Friedrich Kohlrausch (physicist)|Friedrich Kohlrausch]], son of Rudolf, to describe torsional relaxation. [[A. Werner]] used it in 1907 to describe complex luminescence decays; [[Theodor Förster]] in 1949 as the fluorescence decay law of electronic energy donors.▼
▲As said in the introduction, the stretched exponential was introduced by the [[Germans|German]] [[
Outside condensed matter physics, the stretched exponential has been used to describe the removal rates of small, stray bodies in the solar system,<ref>{{cite journal▼
▲Outside [[condensed matter physics]], the stretched exponential has been used to describe the removal rates of small, stray bodies in the solar system,<ref>{{cite journal
| author = Dobrovolskis, A., Alvarellos, J. and Lissauer, J.
| year = 2007
Line 207 ⟶ 184:
| issue = 2
| pages = 481–505
| doi = 10.1016/j.icarus.2006.11.024 | bibcode = 2007Icar..188..481D }}</ref> the diffusion-weighted MRI signal in the brain,<ref>{{cite journal
| author = Bennett, K. | year = 2003
| title = Characterization of Continuously Distributed Water Diffusion Rates in Cerebral Cortex with a Stretched Exponential Model
| journal = Magn. Reson. Med.
Line 214 ⟶ 191:
| issue = 4
| pages = 727–734
| doi = 10.1002/mrm.10581 | pmid = 14523958
| display-authors=etal | doi-access = free}}</ref> and the production from unconventional gas wells.<ref>{{Cite journal |last1=Valko|first1=Peter P. |last2=Lee|first2=W. John |date=2010-01-01 |title=A Better Way To Forecast Production From Unconventional Gas Wells|journal=SPE Annual Technical Conference and Exhibition |language=english | publisher=Society of Petroleum Engineers | doi=10.2118/134231-ms | isbn=9781555633004}}</ref>
=== In probability
If the integrated distribution is a stretched exponential, the normalized [[
Note that confusingly some authors have been known to use the name "stretched exponential" to refer to the [[Weibull distribution]].<ref>{{cite book▼
▲:<math> p(\tau \mid \lambda, \beta)~d\tau = \frac{\lambda}{\Gamma(1 + \beta^{-1})}~e^{-(\tau \lambda)^\beta}~d\tau</math>
| author = Sornette, D.
| year = 2004
| title = Critical Phenomena in Natural Science: Chaos, Fractals, Self-organization, and Disorder}}.</ref>
▲have been known to use the name "stretched exponential" to refer to the [[Weibull distribution]].
=== Modified functions ===
A modified stretched exponential function
with a slowly ''t''-dependent exponent ''
|author1=B. M. Weon |author2=J. H. Je
|name-list-style=amp | year = 2009
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| journal = Biogerontology
| volume = 10
| issue = 1
| pages = 65–71
| doi = 10.1007/s10522-008-9156-4 | pmid=18560989
|s2cid=8554128
}}</ref><ref>
{{cite journal
| author = B. M. Weon
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}}</ref>
=== Wireless communications ===
==References==▼
In wireless communications, a scaled version of the stretched exponential function has been shown to appear in the Laplace Transform for the interference power <math>I</math> when the transmitters' locations are modeled as a 2D [[Poisson point process|Poisson Point Process]] with no exclusion region around the receiver.<ref>{{cite book
| author = Ammar, H. A., Nasser, Y. and Artail, H.
| title = 2018 IEEE International Conference on Communications (ICC)
| chapter = Closed Form Expressions for the Probability Density Function of the Interference Power in PPP Networks
| year = 2018
| pages = 1–6
| doi = 10.1109/ICC.2018.8422214 | arxiv = 1803.10440 | isbn = 978-1-5386-3180-5
| s2cid = 4374550
The [[Laplace transform]] can be written for arbitrary [[fading]] distribution as follows:
<math display="block"> L_I(s) = \exp\left(-\pi \lambda \mathbb{E}{\left[g^\frac{2}{\eta} \right]} \Gamma{\left(1 - \frac{2}{\eta} \right)} s^\frac{2}{\eta}\right) = \exp\left(- t s^\beta \right)</math>
where <math>g</math> is the power of the fading, <math>\eta</math> is the [[Path loss#Loss exponent|path loss exponent]], <math>\lambda</math> is the density of the 2D Poisson Point Process, <math>\Gamma(\cdot)</math> is the Gamma function, and <math>\mathbb{E}[x]</math> is the expectation of the variable <math>x</math>.{{Citation needed|date=May 2023}}
The same reference also shows how to obtain the inverse Laplace Transform for the stretched exponential <math>\exp\left(-s^\beta \right)</math> for higher order integer <math>\beta = \beta_q \beta_b </math> from lower order integers <math>\beta_a</math> and <math>\beta_b</math>.{{Citation needed|date=May 2023}}
=== Internet streaming ===
The stretched exponential has been used to characterize Internet media accessing patterns, such as YouTube and other stable [[streaming media]] sites.<ref>{{Cite conference |author= Lei Guo, Enhua Tan, Songqing Chen, Zhen Xiao, and Xiaodong Zhang| title="The Stretched Exponential Distribution of Internet Media Access Patterns" |conference= PODC' 08| pages=283–294|year=2008 | doi=10.1145/1400751.1400789 }}</ref> The commonly agreed power-law accessing patterns of Web workloads mainly reflect text-based content Web workloads, such as daily updated news sites.<ref>{{cite journal |last1=Adamic|first1=Lada A. |last2=Bernardo A. |first2=Huberman |year=2000 |title=Power-Law Distribution of the World Wide Web |url= |journal=Science |volume=287 |issue=5461 |pages=2115-2115 |doi=10.1126/science.287.5461.2115a}}</ref>
▲== References ==
<references/>
== External links ==
* J. Wuttke: [http://apps.jcns.fz-juelich.de/kww libkww] C library to compute the Fourier transform of the stretched exponential function
[[Category:Exponentials]]
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