Top persons sorted by score
(Another of the Prime Pages' resources)
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The Prover-Account Top 20
Persons by: number score normalized score
Programs by: number score normalized score
Projects by: number score normalized score

At this site we keep several lists of primes, most notably the list of the 5,000 largest known primes. Who found the most of these record primes? We keep separate counts for persons, projects and programs. To see these lists click on 'number' to the right.

Clearly one 100,000,000 digit prime is much harder to discover than quite a few 100,000 digit primes. Based on the usual estimates we score the top persons, provers and projects by adding ‎(log n)3 log log n‎ for each of their primes n. Click on 'score' to see these lists.

Finally, to make sense of the score values, we normalize them by dividing by the current score of the 5000th prime. See these by clicking on 'normalized score' in the table on the right.

61 Scott Gilvey 2 48.6840
62 Vladimir Volynsky 1 48.6527
63 Mariusz Szafrański 33 48.6353
64 Lennart Vogel 62 48.6231
65 Dennis R. Gesker 1 48.6097
66 Steven Wong 19 48.5973
67 Predrag Kurtovic 15 48.5658
68 Håkan Lind 4 48.5101
69 David Mumper 1 48.4921
70 William de Thomas 4 48.4631
71 Vaughan Davies 40 48.4404
72 David Yost 27 48.4175
73 James P. Burt 67 48.3677
74 Jochen Beck 7 48.3477
75 Seonghwan Kim 17 48.3405
76 Roman Vogt 2 48.3345
77 Martyn Elvy 1 48.3296
78 Rod Skinner 2 48.3211
79 Larry Soule 30.5 48.3153
80 Mark Molder 21 48.3147

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Score for Primes

To find the score for a person, program or project's primes, we give each prime n the score (log n)3 log log n; and then find the sum of the scores of their primes. For persons (and for projects), if three go together to find the prime, each gets one-third of the score. Finally we take the log of the resulting sum to narrow the range of the resulting scores. (Throughout this page log is the natural logarithm.)

How did we settle on (log n)3 log log n? For most of the primes on the list the primality testing algorithms take roughly O(log(n)) steps where the steps each take a set number of multiplications. FFT multiplications take about

O( log n . log log n . log log log n )
operations. However, for practical purposes the O(log log log n) is a constant for this range number (it is the precision of numbers used during the FFT, 64 bits suffices for numbers under about 2,000,000 digits).

Next, by the prime number theorem, the number of integers we must test before finding a prime the size of n is O(log n) (only the constant is effected by prescreening using trial division).  So to get a rough estimate of the amount of time to find a prime the size of n, we just multiply these together and we get

O( (log n)3 log log n ).
Finally, for convenience when we add these scores, we take the log of the result.  This is because log n is roughly 2.3 times the number of digits in the prime n, so (log n)3 is quite large for many of the primes on the list. (The number of decimal digits in n is floor((log n)/(log 10)+1)).