I am having the following issue.
I am evaluating a numerical integral, and I need high precision to get good values of the function being integrated.
NIntegrate[
Integrand1P12[Q1, Q2, a, b, c, massrho^2] /. solsR[[1]], {Q1, 0, ∞}, {Q2, 0, ∞},
MaxRecursion -> 2000,
WorkingPrecision -> 30,
MinRecursion -> 40,
AccuracyGoal -> 8]
Where previously I have defined the function Integrand1P12 and
solsR = {a -> ..., b -> ..., c -> ...}
are replacement rules where a, b, and c are to be replaced with exact quantities such as 234/23.
Up to this point there is no problem; my code works perfectly. However, next, I would like to perform some Monte Carlo where the replacement rules are obtained from a random number generation. To do this I need two steps:
Generate random parameteres through:
para = RandomReal[NormalDistribution[a[[1]], a[[2]]], 10, WorkingPrecision -> 34];where a[[1]] and a[[2]] are the relevant parameters of the distribution.
Finally, I want to plug these random numbers into a formula containing simple sums, multiplications, and divisions to obtain the replacement rules tp use in the integral.
However, when Mathematica evaluates the integral, it complains that the precision of the argument is smaller than the requested one (30)
Can anybody tell me where the precision is lost and how to fix it?
