If we do something similar on this C168 for swellman, we can check it for a 3rd time.

Best so far for the C168:

[CODE]# norm 2.054099e-016 alpha -8.201051 e 3.712e-013 rroots 5
skew: 13547506.24
c0: -1091049838048076230236436281364364658189135
c1: 504603769573285498246083360215541735
c2: -38768299583337983933127496777
c3: -5351429028937713649315
c4: 100138622851304
c5: 10001628
Y0: -138988572401982466384760027594008
Y1: 1199975415967612259[/CODE]

So far on the C168
[code]
R0: -80132560431598622469656914926773
R1: 341271651656533139
A0: -3925530804863703095840240389104558480
A1: 86410068762700275288821820483762
A2: 706298516970652533739095304
A3: 26497098487745183679
A4: -898254565334150
A5: 157007760
skew 842687.75, size 1.555e-016, alpha -5.723, combined = 3.666e-013 rroots = 5
[/code]

Very slight improvement on the score:
[CODE]# norm 2.052260e-016 alpha -7.555741 e 3.881e-013 rroots 3
skew: 5385621.82
c0: -6257192400192652225441167271091421245545
c1: -3945606052772085028778758471635594
c2: 9308774563991543714210240940
c3: 341618027604120987286
c4: -150607283841495
c5: 10067400
Y0: -138806492519608695178613827452974
Y1: 424596711833392849[/CODE]

C166 for RichD
 

Found one with a bad skew but higher score:

# norm 3.695902e-016 alpha -7.383306 e 5.567e-013 rroots 5
skew: 13474622.03
c0: -33210626476730825697882762404632692697704
c1: 26333818512286988595139568234039746
c2: -1058318687962661120245321539
c3: -482935203367991955378
c4: 1785076260818
c5: 613872
Y0: -106045564800808526376402542337169
Y1: 133157835424250393

So... here are the results of my belated sieving tests on "C166_4788_5159". In ascending order of leading coefficient:

[code]# norm 3.695902e-016 alpha -7.383306 e 5.567e-013 rroots 5
n: 8232663677075268552040028040427962613195004187737038472546008350527350790146813693136042827763089666937337785875075123500306235229888683807658826159126375359853768383
deg: 5
c0: -33210626476730825697882762404632692697704
c1: 26333818512286988595139568234039746
c2: -1058318687962661120245321539
c3: -482935203367991955378
c4: 1785076260818
c5: 613872
Y0: -106045564800808526376402542337169
Y1: 133157835424250393
type: gnfs
skew: 13474622.03
rlim: 134217727
alim: 134217727
lpbr: 31
lpba: 31
mfbr: 62
mfba: 62
rlambda: 2.6
alambda: 2.6
qintsize: 1000

# http://www.mersenneforum.org/showpost.php?p=355359&postcount=269
#-> makeJobFile(): q0=67108863.5, q1=67208863.5.
[b]# total yield: 2151, q=67109923 (0.15340 sec/rel)[/b]
# 53 Special q, 134 reduction iterations
[/code]

[code]# skew 11681526.87, size 2.887e-016, alpha -8.163, combined = 5.314e-013, rroots = 3
n: 8232663677075268552040028040427962613195004187737038472546008350527350790146813693136042827763089666937337785875075123500306235229888683807658826159126375359853768383
deg: 5
c0: -64097545582231836173154185834090974313893
c1: 57038273747787160306728671709353557
c2: -11922305817556816403635714269
c3: -867444673665392023597
c4: 78372426411442
c5: 2715720
Y0: -78764596806719279335948607498706
Y1: 704739813349024603
type: gnfs
skew: 11681526.87
rlim: 134217727
alim: 134217727
lpbr: 31
lpba: 31
mfbr: 62
mfba: 62
rlambda: 2.6
alambda: 2.6
qintsize: 1000

# http://www.mersenneforum.org/showpost.php?p=355359&postcount=260
#-> makeJobFile(): q0=67108863.5, q1=67208863.5.
[b]# total yield: 2356, q=67109923 (0.16306 sec/rel)[/b]
# 62 Special q, 152 reduction iterations
[/code]

[code]# skew 4491515.30, size 2.719e-016, alpha -7.152, combined = 5.143e-013 rroots = 5
n: 8232663677075268552040028040427962613195004187737038472546008350527350790146813693136042827763089666937337785875075123500306235229888683807658826159126375359853768383
deg: 5
c0: 893054565437073468528453235950677733085
c1: 2511797614938907011950743089188765
c2: -2719192542874456010358349743
c3: -460941393242470744181
c4: 126820984786298
c5: 5077296
Y0: -69499481355460328998078506311622
Y1: 465404033160944009
type: gnfs
skew: 4491515.30
rlim: 134217727
alim: 134217727
lpbr: 31
lpba: 31
mfbr: 62
mfba: 62
rlambda: 2.6
alambda: 2.6
qintsize: 1000

# http://www.mersenneforum.org/showpost.php?p=355359&postcount=247
#-> makeJobFile(): q0=67108863.5, q1=67208863.5.
# total yield: 2032, q=67109923 (0.17590 sec/rel)
# 58 Special q, 150 reduction iterations
[/code]

[code]# norm 3.514670e-016 alpha -7.111533 e 5.394e-013 rroots 3
n: 8232663677075268552040028040427962613195004187737038472546008350527350790146813693136042827763089666937337785875075123500306235229888683807658826159126375359853768383
deg: 5
c0: -1532190310404755024435433175347737566139
c1: 3676253136046456933250836564000824
c2: -81541743881566127057867159
c3: -580564695976550014656
c4: 32579659023370
c5: 20850600
Y0: -52394338640184089981223380179140
Y1: 257044554902959283
type: gnfs
skew: 3488617.93
rlim: 134217727
alim: 134217727
lpbr: 31
lpba: 31
mfbr: 62
mfba: 62
rlambda: 2.6
alambda: 2.6
qintsize: 1000

# http://www.mersenneforum.org/showpost.php?p=355359&postcount=250
#-> makeJobFile(): q0=67108863.5, q1=67208863.5.
# total yield: 2100, q=67109923 (0.16070 sec/rel)
# 55 Special q, 150 reduction iterations
[/code]

[code]# norm 3.534603e-016 alpha -7.217812 e 5.388e-013 rroots 5
n: 8232663677075268552040028040427962613195004187737038472546008350527350790146813693136042827763089666937337785875075123500306235229888683807658826159126375359853768383
deg: 5
c0: -406863124232228097770612251596630707808
c1: 1397008484147485063276690890434320
c2: 1959559479994289870016918286
c3: -223873981131455264775
c4: -309981426719886
c5: 34871760
Y0: -47273014953449373402503531152735
Y1: 1730317388101909
type: gnfs
skew: 2475815.23
rlim: 134217727
alim: 134217727
lpbr: 31
lpba: 31
mfbr: 62
mfba: 62
rlambda: 2.6
alambda: 2.6
qintsize: 1000

# http://www.mersenneforum.org/showpost.php?p=355359&postcount=245
#-> makeJobFile(): q0=67108863.5, q1=67208863.5.
# total yield: 2016, q=67109923 (0.14132 sec/rel)
# 55 Special q, 161 reduction iterations

[/code]

[code]# skew 1317757.94, size 2.912e-016, alpha -6.998, combined = 5.374e-013 rroots = 5
n: 8232663677075268552040028040427962613195004187737038472546008350527350790146813693136042827763089666937337785875075123500306235229888683807658826159126375359853768383
deg: 5
c0: 198597517620071762000877347570258564216
c1: 739534886795844444800384897768926
c2: -366246626185683843435072111
c3: -1046052875115274054676
c4: 300988932539270
c5: 206658060
Y0: -33117504503117161374368743175645
Y1: 289745110476613783
type: gnfs
skew: 1317757.94
rlim: 134217727
alim: 134217727
lpbr: 31
lpba: 31
mfbr: 62
mfba: 62
rlambda: 2.6
alambda: 2.6
qintsize: 1000

# http://www.mersenneforum.org/showpost.php?p=355359&postcount=248
#-> makeJobFile(): q0=67108863.5, q1=67208863.5.
# total yield: 1836, q=67109923 (0.16997 sec/rel)
# 51 Special q, 152 reduction iterations
[/code]

The winners are, this time again, the two polynomials with the lowest leading coefficients...
* the first one is faster than the second one but sieves less productively;
* the fifth one sieves faster than the first and second ones, but less productively than either, so we'd have to sieve over a wider range;
* polynomials 3, 4 and 6 sieve both more slowly and less productively than polynomial 2. The one with the highest leading coefficient is the worst...

My commentary: while it remains true that the extremely low leading coefficients (up to several thousands, maybe several dozen thousands) seldom yield the best polynomials, we already knew that high leading coefficients (dozens of millions, for a number of this difficulty) are bad.
The older pol5sel quickly increases the leading coefficient, and it produces polynomials which sieve noticeably less productively than msieve-produced polynomials.
I think that [i]for numbers of that size[/i], with run-of-the-mill polsel code, looking for polynomials with a leading coefficient above several dozen millions is a waste of electrons :smile:

Were all scores computed with the same version of msieve, BTW ?

Currently the scores msieve produces are generated with a certain set of parameters(the same as pol5 from memory). Would higher(closer to reality) parameters on the best few polys provide a better idea of which is best?

C166 for RichD
 

[QUOTE=debrouxl;355478]
Were all scores computed with the same version of msieve, BTW ?[/QUOTE]

One more poly to ckeck, it might sieve better :)

msieve v.1.52 (svn942)
# norm 3.682170e-016 alpha -7.976362 e 5.494e-013 rroots 5
skew: 11610079.61
c0: -9847862849022242800155773023665624456000
c1: 16301817747869811410359170706479000
c2: 7452362045018712127753989554
c3: -742047366030036453403
c4: -50776706006862
c5: 673200
Y0: -104106839917340321574536010026327
Y1: 169908656891663867

Swellman's C168
[code]
R0: -131875157916698331712033954516273
R1: 143947380856205903
A0: 10863135549907575815531071201377087481440
A1: 3680619155268645580126871328996976
A2: -4101959133382108448147843462
A3: -715128181658682572315
A4: 353098812987408
A5: 13006224
skew 3934944.07, size 1.931e-016, alpha -7.392, combined = 4.170e-013 rroots = 5
[/code]

debrouxl, thanks for running through all of those--this is very helpful information (at least for me). My scores were produced from MSieve 1.52 (svn 944).

sashamkrt, welcome to the poly sieving group!

[QUOTE=debrouxl;355478]So... here are the results of my belated sieving tests on "C166_4788_5159". In ascending order of leading coefficient:

[code]# norm 3.695902e-016 alpha -7.383306 e 5.567e-013 rroots 5
[/code]

[code]# skew 11681526.87, size 2.887e-016, alpha -8.163, combined = 5.314e-013, rroots = 3
[/code]

[/QUOTE]

Could the yield/speed difference between #1 and #2 be explained by the e score difference?