20200521, 12:58  #45  
Jun 2012
2^{5}×3×5×7 Posts 
Quote:
Max has also stated that he has found a way to lower the skew while keeping the escore constant for a given poly. Sounded promising but I have no details. Keep in mind that not every poly can be spun, and even when it can the spin doesn’t always improve the escore all that much. But it is a very cool innovation which is definitely a +1 to the art of poly searching. 

20200521, 14:01  #46  
"Ed Hall"
Dec 2009
Adirondack Mtns
3·1,399 Posts 
Quote:


20200527, 11:19  #47 
Jun 2012
2^{5}·3·5·7 Posts 
My best so far in the 6070M range is only 2.23e15. But I am still plugging away.
Still collecting data on my various CADO runs on a separate machine. One thing that pops out is that P=8M consistently produces higher scoring polynomials than P=14M for reasons unknown to me. Maybe CADO hits an internal deadline before fully exploring all candidates with the higher P? I’ll post some data by the weekend but it will take another month fo fully fill the test matrix. 
20200527, 14:05  #48  
"Ed Hall"
Dec 2009
Adirondack Mtns
1000001100101_{2} Posts 
Quote:


20200527, 18:17  #49  
Jun 2012
2^{5}·3·5·7 Posts 
Quote:
Should sopteffort = k * ropteffort, say with k near 1? 0.5? 

20200528, 18:07  #50 
"Curtis"
Feb 2005
Riverside, CA
13×397 Posts 
sizeopt effort and rootopt effort should be unrelated in principle.
I haven't found a use yet for sopteffort, nor does the CADO default poly select params. However, ropteffort is invoked on every CADO default params file, and is usually rather high (10 as early as c130, from what I recall I don't have the stock params handy). playing with sopteffort = 1 may be fruitful, but I wouldn't relate it to ropteffort at all. 
20200528, 20:21  #51  
Jun 2012
2^{5}·3·5·7 Posts 
Quote:


20200608, 05:03  #52  
"Max"
Jun 2016
Toronto
919 Posts 
C204 poly
Quote:
Code:
Y0: 1380919701727219820649855819252436663945 Y1: 237213586863942644893691 c0: 80233576744915037044865695237775462973210633888 c1: 3360691848973590722240522959473879950752 c2: 543390370730403386816602011237354 c3: 1415383168580686569709049 c4: 23044654864848822 c5: 318686760 skew: 71702279.00367 # size 4.734e20, alpha 7.634, combined = 2.607e15 rroots = 3 

20200608, 05:24  #53  
"Max"
Jun 2016
Toronto
919 Posts 
Quote:
Code:
R0: 1385041351659143177987030365622752942014 R1: 262954605447105862796669 A0: 653169167883331137294520872848350376000509290 A1: 199697587868029354778396563237441296355 A2: 117792697822385272998589389784161 A3: 2071256675570232894540458 A4: 455228324762132184 A5: 2511784800 skew: 16424161.34054 # size 3.958e20, alpha 6.662, combined = 2.315e15 rroots = 5 

20210904, 14:46  #54 
Jun 2012
2^{5}×3×5×7 Posts 
Bumping this thread.
Reviewing the past work, it seems ad was searched up to 70M. I did many CADO searches in the 6070M range playing with parameters and never found any poly worth reporting. Folks can go back and rerun searches with different parameters but the best escore for this composite (2.607e15 found by EdH) is pretty good. I think it is ready to sieve. Last fiddled with by swellman on 20210905 at 11:16 
20210908, 00:08  #55 
Apr 2020
2×3^{3}×11 Posts 
I used some top secret methods to figure out the presizeopt leading coefficients of Ed's polys, and he appears to have searched some range from 100M upwards  perhaps to 110M?  at incr=420 and a very large P value of 16M.
I'm not convinced we can't do better here. 2.6 feels a bit low, and the sample size of c204s is too small for the record to be particularly meaningful. The switch to incr=4620 was made quite early, so I'm going to break one of the fundamental rules of poly selection and duplicate some existing work by doing 500k5M at P=8M, incr=420. I may go further if this looks promising. 
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