## Thursday, June 2, 2016

### Approximating the Non-Trivial Zeros

So far we have concentrated on approximations of ζ(s) for real values of s.

Of course, the Riemann zeta function is also defined for complex values of s (a + it). However apart from the hugely important complex values of s for which ζ(s) = 0, i.e. the famed Riemann zeros, I am not going to suggest further approximation formulas.

It is postulated according to the Riemann Hypothesis that all complex solutions for ζ(s) = 0, lie on the line through .5 and are of the form .5 + it and .5 – it respectively.

So we will concentrate here on the values of t for which ζ(s) = 0.

I had already approached this issue in an earlier blog entry "Using Frequency Formula to Estimate Location of Riemann Zeros"

The approximation here was based on  realisation of the amazing accuracy of the formula that is used to calculate the frequency of zeros up to a given t.

This formula is given as t/2π(log t/2π –  1). However, I found that a very slight adjustment (through addition of 1) gave an even better estimate.

So the formula I am using is  t/2π(log t/2π –  1) + 1.

In fact in all the examples I calculated up to numbers in the region of 1022, this formula either yielded exactly the correct frequency (in absolute terms) or was out by at most 1.

This then suggested to me a way for attempting to approximate the value of each zero by successively inserting the integer values 1, 2, 3, 4,.... representing frequency of zeros as the result form the formula, and then working backwards to find the value of t to which these results related.

I then provided the estimates I thereby obtained - correct to 2 decimal places - for the first 10 values for t in this manner.

However following from the initial observation that the first t thus calculated (17.08) was very close to exactly half-way as between the 1st and 2nd actual zeros, I then realised that a much closer approximation could be obtained by adjusting these values (using the deviations existing between the approximation results).

So for example with respect to the 1st estimated zero, the idea is to subtract half of the deviation as between 1st and 2nd calculated values to better approximate the result for this 1st zero.

Therefore we obtain 17.08 - 2.74 = 14.34 which indeed compares very favourably with the actual result (i.e. 14.13).

I have now drawn up a new table which provides these latest approximations (with % relative accuracy) for the first 10 zeros.

 Riemann Zeros Predicted Location (1) Deviation of zeros Predicted Location (2) Actual Location % accuracy 1st 17.08 14.34 14.13 98.5 2nd 22.56 5.48 20.27 21.02 96.4 3rd 27.14 4.58 25.09 25.01 99.7 4th 31.24 4.10 29.34 30.43 96.4 5th 35.04 3.80 33.28 32.94 99.0 6th 38.56 3.52 36.88 37.59 98.1 7th 41.92 3.36 40.29 40.92 98.5 8th 45.18 3.26 43.60 43.33 99.4 9th 48.34 3.16 46.84 48.01 97.6 10th 51.34 3.00 49.96 49.77 99.6 11th 54.31 2.97

As can be seen, the predicted (approximate) results are accurate to a surprising level of accuracy.

The nature of the Riemann zeros complements in a dynamic interactive manner that of the prime nos.

Whereas the behaviour of the primes is locally as independent as possible (compatible with an overall collective relationship with the natural numbers being maintained), it is somewhat the reverse with the Riemann zeros. The very nature of these zeros is to smooth out as much as possible local incompatibilities as between the quantitative (independent) and qualitative (interdependent) nature of the primes, thus entailing a continuous regularity enabling the precise calculation of their frequency (in absolute terms) to an extraordinary degree of accuracy.