Loss of precision, real numbers

Roundoff errors

A floating point number like $$ \begin{equation} x= 1.234567891112131468 = 0.1234567891112131468\times 10^{1} \tag{15} \end{equation} $$ may be stored in the following way. The exponent is small and is stored in full precision. However, the mantissa is not stored fully. In double precision (64 bits), digits beyond the 15th are lost since the mantissa is normally stored in two words, one which is the most significant one representing 123456 and the least significant one containing 789111213. The digits beyond 3 are lost. Clearly, if we are summing alternating series with large numbers, subtractions between two large numbers may lead to roundoff errors, since not all relevant digits are kept. This leads eventually to the next problem, namely