Article · Wikipedia archive · Last revised Jul 17, 2026

Crystal Ball function

The Crystal Ball function, named after the Crystal Ball Collaboration, is a probability density function (PDF) commonly used to model various lossy processes in high-energy physics such as Bremsstrahlung by electrons. It consists of a Gaussian core portion and a power-law low-end tail, below a certain threshold. The function itself and its first derivative are both continuous.

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Jul 17, 2026
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Examples of the Crystal Ball function. source ↗

The Crystal Ball function, named after the Crystal Ball Collaboration (hence the capitalized initial letters), is a probability density function (PDF) commonly used to model various lossy processes in high-energy physics such as Bremsstrahlung by electrons. It consists of a Gaussian core portion and a power-law low-end tail, below a certain threshold. The function itself and its first derivative are both continuous.

The Crystal Ball function is given by:

f ( x ; α , n , x ¯ , σ ) = N { exp ( ( x x ¯ ) 2 2 σ 2 ) , for  x x ¯ σ > α A ( B x x ¯ σ ) n , for  x x ¯ σ α , {\displaystyle f(x;\alpha ,n,{\bar {x}},\sigma )=N\cdot {\begin{cases}\exp(-{\frac {(x-{\bar {x}})^{2}}{2\sigma ^{2}}}),&{\mbox{for }}{\frac {x-{\bar {x}}}{\sigma }}>-\alpha \\A\cdot (B-{\frac {x-{\bar {x}}}{\sigma }})^{-n},&{\mbox{for }}{\frac {x-{\bar {x}}}{\sigma }}\leqslant -\alpha \end{cases}},}

where

A = ( n | α | ) n exp ( | α | 2 2 ) {\displaystyle A=\left({\frac {n}{\left|\alpha \right|}}\right)^{n}\cdot \exp \left(-{\frac {\left|\alpha \right|^{2}}{2}}\right)} ,
B = n | α | | α | {\displaystyle B={\frac {n}{\left|\alpha \right|}}-\left|\alpha \right|} ,
N = 1 σ ( C + D ) {\displaystyle N={\frac {1}{\sigma (C+D)}}} ,
C = n | α | 1 n 1 exp ( | α | 2 2 ) {\displaystyle C={\frac {n}{\left|\alpha \right|}}\cdot {\frac {1}{n-1}}\cdot \exp \left(-{\frac {\left|\alpha \right|^{2}}{2}}\right)} ,
D = π 2 ( 1 + erf ( | α | 2 ) ) {\displaystyle D={\sqrt {\frac {\pi }{2}}}\left(1+\operatorname {erf} \left({\frac {\left|\alpha \right|}{\sqrt {2}}}\right)\right)} ,

with the error function erf.

The parameters of the function (that are usually determined by a fit) are:

  • N {\displaystyle N} is a normalization factor (Skwarnicki 1986)
  • α > 0 {\displaystyle \alpha >0} defines the point where the PDF changes from a power-law to a Gaussian distribution
  • n > 1 {\displaystyle n>1} is the power of the power-law tail
  • x ¯ {\displaystyle {\bar {x}}} and σ {\displaystyle \sigma } are the mean and the standard deviation of the Gaussian
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