 |
 |
 |
| |
|
|
| This is part of the ves module | |
| It is only available if you configure PLUMED with ./configure –enable-modules=ves . Furthermore, this feature is still being developed so take care when using it and report any problems on the mailing list. |
Exponential distribution (static).
Employ a target distribution given by an exponential distribution that is defined as
\[ p(s) = \lambda e^{-\lambda(s-a)} \]
where \(a\) is the minimum of the distribution that is defined on the interval \([a,\infty)\), and \(\lambda>0\) is the so-called rate parameter.
The minimum \(a\) is given using the MINIMUM keyword, and the rate parameter \(\lambda\) is given using the LAMBDA keyword.
This target distribution action is only defined for one dimension, for multiple dimensions it should be used in combination with TD_PRODUCT_DISTRIBUTION action.
| MINIMUM | The minimum of the exponential distribution. |
| LAMBDA | The \(\lambda\) parameter of the exponential distribution given as positive number. |
| SHIFT_TO_ZERO | ( default=off ) Shift the minimum value of the target distribution to zero. This can for example be used to avoid negative values in the target distribution. If this option is active the distribution will be automatically normalized. |
| NORMALIZE | ( default=off ) Renormalized the target distribution over the intervals on which it is defined to make sure that it is properly normalized to 1. In most cases this should not be needed as the target distributions should be normalized. The code will issue a warning (but still run) if this is needed for some reason. |
| WELLTEMPERED_FACTOR | Broaden the target distribution such that it is taken as [p(s)]^(1/ \(\gamma\)) where \(\gamma\) is the well tempered factor given here. If this option is active the distribution will be automatically normalized. |
Exponential distribution with \(a=10.0\) and \(\lambda=0.5\)
td: TD_EXPONENTIAL MINIMUM=-10.0 LAMBDA=0.5
The exponential distribution is only defined for one dimension so for multiple dimensions we have to use it in combination with the TD_PRODUCT_DISTRIBUTION action as shown in the following example where we have a uniform distribution for argument 1 and and an exponential distribution for argument 2
td_uni: TD_UNIFORM td_exp: TD_EXPONENTIAL MINIMUM=-10.0 LAMBDA=0.5 td_pd: TD_PRODUCT_DISTRIBUTION DISTRIBUTIONS=td_uni,td_exp
1.8.14