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Top persons sorted by score

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.

rankpersonprimesscore
1 Curtis Cooper 15 56.5769
2 Patrick Laroche 1 56.4714
3 Jonathan (Jon) Pace 1 56.2664
4 Edson Smith 1 54.4841
5 Odd Magnar Strindmo 1 54.4507
6 Hans-Michael Elvenich 1 54.0294
7 Ryan Propper 53.5 53.7500
8 Steven R. Boone 1 53.5273
9 Péter Szabolcs 1 53.4922
10 Dr. Martin Nowak 1 52.9330
11 Josh Findley 1 52.6968
12 Serge Batalov 280.833 52.6625
13 Rob Gahan 21 52.4918
14 Dr. James Scott Brown 133 52.2845
15 Michael Shafer 1 52.2829
16 Sylvanus A. Zimmerman 10 52.2599
17 Ben Maloney 3 52.0380
18 Tom Greer 82 51.7149
19 Diego Bertolotti 1 51.6397
20 SRBase 111 51.4653
 
move down list ↓

Notes:


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)).

Printed from the PrimePages <primes.utm.edu> © Chris Caldwell.