Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Add ATLAS_DY_8TEV_2D grid #10

Open
wants to merge 4 commits into
base: master
Choose a base branch
from
Open

Add ATLAS_DY_8TEV_2D grid #10

wants to merge 4 commits into from

Conversation

cschwan
Copy link
Contributor

@cschwan cschwan commented May 3, 2021

Results:

   PineAPPL         MC        sigma      central         min      max 
                              1/100   sigma   1/1000   1/1000   1/1000
----------------------------------------------------------------------
 5.207656e-01  5.207990e-01   0.016   0.402   0.0641   0.0663   0.0613  
 5.195344e-01  5.195012e-01   0.015   0.417   0.0639   0.0815   0.0479  
 5.170471e-01  5.170196e-01   0.011   0.488   0.0532   0.0657   0.0407  
 5.137233e-01  5.137518e-01   0.013   0.435   0.0556   0.0630   0.0511  
 5.092143e-01  5.092375e-01   0.013   0.353   0.0456   0.0468   0.0479  
 5.027619e-01  5.027543e-01   0.013   0.120   0.0151   0.0205   0.0042  
 4.876284e-01  4.875931e-01   0.014   0.500   0.0725   0.0834   0.0542  
 4.438756e-01  4.437821e-01   0.026   0.817   0.2107   0.2035   0.2128  
 3.698733e-01  3.698102e-01   0.016   1.094   0.1706   0.1647   0.1754  
 2.823581e-01  2.823190e-01   0.028   0.498   0.1384   0.1224   0.1601  
 1.858527e-01  1.858548e-01   0.037   0.031   0.0114   0.0067   0.0143  
 8.894726e-02  8.895220e-02   0.088   0.063   0.0555   0.0520   0.0570  
 1.946536e-01  1.946617e-01   0.035   0.120   0.0417   0.0261   0.0584  
 1.940186e-01  1.940163e-01   0.029   0.041   0.0120   0.0084   0.0153  
 1.933111e-01  1.932973e-01   0.035   0.206   0.0716   0.0714   0.0732  
 1.923802e-01  1.923766e-01   0.037   0.051   0.0189   0.0335   0.0021  
 1.900445e-01  1.900553e-01   0.042   0.136   0.0569   0.0498   0.0717  
 1.828015e-01  1.827900e-01   0.033   0.194   0.0631   0.0673   0.0507  
 1.678564e-01  1.678196e-01   0.030   0.722   0.2192   0.2109   0.2261  
 1.474396e-01  1.474101e-01   0.037   0.543   0.1999   0.1852   0.2189  
 1.216504e-01  1.216444e-01   0.060   0.083   0.0496   0.0413   0.0617  
 9.116457e-02  9.116773e-02   0.070   0.050   0.0346   0.0313   0.0382  
 5.840493e-02  5.840635e-02   0.086   0.028   0.0242   0.0154   0.0332  
 2.683728e-02  2.683664e-02   0.151   0.016   0.0240   0.0267   0.0227  
 9.227631e-02  9.226869e-02   0.049   0.169   0.0826   0.0850   0.0791 
 9.205585e-02  9.205836e-02   0.026   0.106   0.0272   0.0184   0.0386 
 9.148106e-02  9.149020e-02   0.025   0.398   0.0998   0.0910   0.1141 
 8.994264e-02  8.993703e-02   0.028   0.226   0.0625   0.0690   0.0517 
 8.640755e-02  8.638591e-02   0.036   0.704   0.2505   0.2589   0.2410 
 8.092138e-02  8.090644e-02   0.030   0.616   0.1847   0.1805   0.1906 
 7.339469e-02  7.338972e-02   0.033   0.204   0.0678   0.0491   0.0887 
 6.339036e-02  6.339265e-02   0.039   0.092   0.0361   0.0365   0.0356 
 5.089755e-02  5.089819e-02   0.052   0.024   0.0127   0.0065   0.0169 
 3.666654e-02  3.666640e-02   0.053   0.007   0.0036   0.0051   0.0044 
 2.216302e-02  2.216402e-02   0.127   0.035   0.0452   0.0476   0.0421 
 9.440051e-03  9.440914e-03   0.280   0.033   0.0914   0.0824   0.1005 
 5.679950e-02  5.679832e-02   0.036   0.057   0.0209   0.0278   0.0092 
 5.421675e-02  5.420623e-02   0.069   0.280   0.1941   0.1940   0.1931 
 4.842174e-02  4.842135e-02   0.046   0.017   0.0080   0.0045   0.0135 
 3.707089e-02  3.706993e-02   0.064   0.040   0.0257   0.0361   0.0177 
 2.042561e-02  2.042777e-02   0.099   0.106   0.1055   0.1051   0.1043 
 5.448566e-03  5.448855e-03   0.252   0.021   0.0531   0.0577   0.0573 
 1.156280e-02  1.156031e-02   0.015   1.460   0.2153   0.2284   0.2022
 1.064932e-02  1.064934e-02   0.019   0.009   0.0018   0.0050   0.0019
 8.568035e-03  8.567875e-03   0.021   0.088   0.0187   0.0103   0.0274
 5.160834e-03  5.161622e-03   0.028   0.546   0.1527   0.1556   0.1483
 1.762013e-03  1.762042e-03   0.069   0.024   0.0167   0.0234   0.0082
 1.923192e-04  1.923111e-04   0.234   0.018   0.0423   0.0441   0.0406

Plots (116 < Mll < 150):

output-0

(150 < Mll < 200):

output-1

(200 < Mll < 300):

output-2

(300 < Mll < 500):

output-3

(500 < Mll < 1500):

output-4

@cschwan cschwan requested a review from enocera May 3, 2021 16:26
@enocera enocera force-pushed the ATLAS_DY_8TEV_2D branch from b8b92c5 to 72c3d3e Compare May 3, 2021 17:55
Copy link
Contributor

@enocera enocera left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

May I suggest to indicate in the label on the y axis of the first panel of all plots to indicate that the distribution is 2D? That is
dsigma/dy -> dsigma/dydM
An unrelated question: in NNPDF4.0 we will include the 2D distribution instead of the 3D distribution. Given that my recollection is that this was implemented, shouldn't we generate the grids also for the 3D distribution?

@enocera enocera self-requested a review May 6, 2021 11:12
@cschwan
Copy link
Contributor Author

cschwan commented May 6, 2021

@enocera That's a good point, on hepdata they are indeed shown as 2D distributions, but the APPLgrids that I used to compare them with were generated as 1D distributions. So we have to either leave things as they are, or correct both the plots and the implementation in apfelcomb.

In any case the slices should be indicated in the plots (right now they aren't), see also NNPDF/pineappl#63 (comment) (one-but-last item).

For the ATLAS 8 TeV 3D distributions the grids are currently running. I'd prefer to generate them as they are published by the experiment, but once we have the 3D distributions we can manually sum over cos theta*; this will require support in PineAPPL: NNPDF/pineappl#67.

@enocera
Copy link
Contributor

enocera commented May 6, 2021

@enocera That's a good point, on hepdata they are indeed shown as 2D distributions, but the APPLgrids that I used to compare them with were generated as 1D distributions. So we have to either leave things as they are, or correct both the plots and the implementation in apfelcomb.

OK. I don't have any preference, and btw changing the apfelcomb implementation is not hard work.

In any case the slices should be indicated in the plots (right now they aren't), see also N3PDF/pineappl#63 (comment) (one-but-last item).

OK. So I guess that this also applies to #8 .

For the ATLAS 8 TeV 3D distributions the grids are currently running. I'd prefer to generate them as they are published by the experiment, but once we have the 3D distributions we can manually sum over cos theta*; this will require support in PineAPPL: N3PDF/pineappl#67.

OK, thanks.

@cschwan
Copy link
Contributor Author

cschwan commented May 6, 2021

If it's not hard work, then I'd say we do it properly. Let me change the bin normalizations and the plot labels.

@cschwan
Copy link
Contributor Author

cschwan commented May 6, 2021

I can easily make the change, but there's also a factor 1/2 that I think is incorrect in the paper in eq. (3). I think instead of abs(yll) the observable really is yll, otherwise I don't see where this factor comes from. Do you agree/disagree? We also have to make sure to take of that in the data/apfelcomb implementation.

@cschwan
Copy link
Contributor Author

cschwan commented May 31, 2021

This grid has the same problem as reported in #20. One can see that the first bin of the slice 300 < Mll < 500 is too large. It's obvious in the bin limits:

bin   Mll      yll    dsig/dyll   neg unc pos unc
---+---+----+---+---+------------+-------+-------
  0 116  150   0 0.2  2.6038280e0  -2.34%   2.05%
  1 116  150 0.2 0.4  2.5976720e0  -2.33%   2.05%
  2 116  150 0.4 0.6  2.5852353e0  -2.34%   2.05%
  3 116  150 0.6 0.8  2.5686164e0  -2.34%   2.06%
  4 116  150 0.8   1  2.5460713e0  -2.34%   2.07%
  5 116  150   1 1.2  2.5138096e0  -2.33%   2.06%
  6 116  150 1.2 1.4  2.4381421e0  -2.31%   1.95%
  7 116  150 1.4 1.6  2.2193781e0  -2.23%   1.69%
  8 116  150 1.6 1.8  1.8493666e0  -2.19%   1.67%
  9 116  150 1.8   2  1.4117903e0  -2.20%   1.78%
 10 116  150   2 2.2 9.2926358e-1  -2.18%   1.87%
 11 116  150 2.2 2.4 4.4473631e-1  -2.19%   1.93%
 12 150  200   0 0.2 9.7326781e-1  -1.51%   1.69%
 13 150  200 0.2 0.4 9.7009295e-1  -1.50%   1.69%
 14 150  200 0.4 0.6 9.6655564e-1  -1.51%   1.69%
 15 150  200 0.6 0.8 9.6190119e-1  -1.51%   1.71%
 16 150  200 0.8   1 9.5022225e-1  -1.51%   1.68%
 17 150  200   1 1.2 9.1400759e-1  -1.49%   1.56%
 18 150  200 1.2 1.4 8.3928179e-1  -1.49%   1.50%
 19 150  200 1.4 1.6 7.3719804e-1  -1.49%   1.58%
 20 150  200 1.6 1.8 6.0825215e-1  -1.48%   1.66%
 21 150  200 1.8   2 4.5582284e-1  -1.48%   1.74%
 22 150  200   2 2.2 2.9202465e-1  -1.48%   1.78%
 23 150  200 2.2 2.4 1.3418643e-1  -1.51%   1.83%
 24 200  300   0 0.2 4.6138156e-1  -1.24%   1.49%
 25 200  300 0.2 0.4 4.6027925e-1  -1.24%   1.49%
 26 200  300 0.4 0.6 4.5740532e-1  -1.23%   1.48%
 27 200  300 0.6 0.8 4.4971322e-1  -1.20%   1.45%
 28 200  300 0.8   1 4.3203777e-1  -1.17%   1.41%
 29 200  300   1 1.2 4.0460691e-1  -1.20%   1.44%
 30 200  300 1.2 1.4 3.6697347e-1  -1.24%   1.49%
 31 200  300 1.4 1.6 3.1695181e-1  -1.28%   1.54%
 32 200  300 1.6 1.8 2.5448773e-1  -1.32%   1.59%
 33 200  300 1.8   2 1.8333268e-1  -1.37%   1.64%
 34 200  300   2 2.2 1.1081511e-1  -1.40%   1.69%
 35 200  300 2.2 2.4 4.7200258e-2  -1.43%   1.72%
 36 300  500   0 0.2 2.8399752e-1  -1.17%   1.39%
 37 300  500 0.4 0.8 1.3554187e-1  -1.16%   1.38%
 38 300  500 0.8 1.2 1.2105434e-1  -1.22%   1.45%
 39 300  500 1.2 1.6 9.2677217e-2  -1.27%   1.52%
 40 300  500 1.6   2 5.1064029e-2  -1.36%   1.61%
 41 300  500   2 2.4 1.3621416e-2  -1.44%   1.69%
 42 500 1500   0 0.4 2.8906994e-2  -1.54%   1.67%
 43 500 1500 0.4 0.8 2.6623300e-2  -1.63%   1.74%
 44 500 1500 0.8 1.2 2.1420087e-2  -1.78%   1.86%
 45 500 1500 1.2 1.6 1.2902085e-2  -2.01%   2.04%
 46 500 1500 1.6   2 4.4050316e-3  -2.43%   2.39%
 47 500 1500   2 2.4 4.8079805e-4  -3.17%   3.03%

Bin 36 has the wrong boundaries.

- added correct bin boundaries
- made the differential distributions two-dimensional
@cschwan
Copy link
Contributor Author

cschwan commented May 31, 2021

Here the results with the corrected bin limits (notice that the differential cross section is two-dimensional now):

bin   Mll      yll   d2sig/dMll/dyll neg unc pos unc
---+---+----+---+---+---------------+-------+-------
  0 116  150   0 0.2    7.6583177e-2  -2.34%   2.05%
  1 116  150 0.2 0.4    7.6402118e-2  -2.33%   2.05%
  2 116  150 0.4 0.6    7.6036332e-2  -2.34%   2.05%
  3 116  150 0.6 0.8    7.5547540e-2  -2.34%   2.06%
  4 116  150 0.8   1    7.4884450e-2  -2.34%   2.07%
  5 116  150   1 1.2    7.3935578e-2  -2.33%   2.06%
  6 116  150 1.2 1.4    7.1710062e-2  -2.31%   1.95%
  7 116  150 1.4 1.6    6.5275826e-2  -2.23%   1.69%
  8 116  150 1.6 1.8    5.4393137e-2  -2.19%   1.67%
  9 116  150 1.8   2    4.1523243e-2  -2.20%   1.78%
 10 116  150   2 2.2    2.7331282e-2  -2.18%   1.87%
 11 116  150 2.2 2.4    1.3080480e-2  -2.19%   1.93%
 12 150  200   0 0.2    1.9465356e-2  -1.51%   1.69%
 13 150  200 0.2 0.4    1.9401859e-2  -1.50%   1.69%
 14 150  200 0.4 0.6    1.9331113e-2  -1.51%   1.69%
 15 150  200 0.6 0.8    1.9238024e-2  -1.51%   1.71%
 16 150  200 0.8   1    1.9004445e-2  -1.51%   1.68%
 17 150  200   1 1.2    1.8280152e-2  -1.49%   1.56%
 18 150  200 1.2 1.4    1.6785636e-2  -1.49%   1.50%
 19 150  200 1.4 1.6    1.4743961e-2  -1.49%   1.58%
 20 150  200 1.6 1.8    1.2165043e-2  -1.48%   1.66%
 21 150  200 1.8   2    9.1164569e-3  -1.48%   1.74%
 22 150  200   2 2.2    5.8404931e-3  -1.48%   1.78%
 23 150  200 2.2 2.4    2.6837285e-3  -1.51%   1.83%
 24 200  300   0 0.2    4.6138156e-3  -1.24%   1.49%
 25 200  300 0.2 0.4    4.6027925e-3  -1.24%   1.49%
 26 200  300 0.4 0.6    4.5740532e-3  -1.23%   1.48%
 27 200  300 0.6 0.8    4.4971322e-3  -1.20%   1.45%
 28 200  300 0.8   1    4.3203777e-3  -1.17%   1.41%
 29 200  300   1 1.2    4.0460691e-3  -1.20%   1.44%
 30 200  300 1.2 1.4    3.6697347e-3  -1.24%   1.49%
 31 200  300 1.4 1.6    3.1695181e-3  -1.28%   1.54%
 32 200  300 1.6 1.8    2.5448773e-3  -1.32%   1.59%
 33 200  300 1.8   2    1.8333268e-3  -1.37%   1.64%
 34 200  300   2 2.2    1.1081511e-3  -1.40%   1.69%
 35 200  300 2.2 2.4    4.7200258e-4  -1.43%   1.72%
 36 300  500   0 0.4    7.0999380e-4  -1.17%   1.39%
 37 300  500 0.4 0.8    6.7770936e-4  -1.16%   1.38%
 38 300  500 0.8 1.2    6.0527171e-4  -1.22%   1.45%
 39 300  500 1.2 1.6    4.6338609e-4  -1.27%   1.52%
 40 300  500 1.6   2    2.5532015e-4  -1.36%   1.61%
 41 300  500   2 2.4    6.8107079e-5  -1.44%   1.69%
 42 500 1500   0 0.4    2.8906994e-5  -1.54%   1.67%
 43 500 1500 0.4 0.8    2.6623300e-5  -1.63%   1.74%
 44 500 1500 0.8 1.2    2.1420087e-5  -1.78%   1.86%
 45 500 1500 1.2 1.6    1.2902085e-5  -2.01%   2.04%
 46 500 1500 1.6   2    4.4050316e-6  -2.43%   2.39%
 47 500 1500   2 2.4    4.8079805e-7  -3.17%   3.03%

Corrected plots (116 < Mll < 150):

output-0

150 < Mll < 200:

output-1

200 < Mll < 300:

output-2

300 < Mll < 500:

output-3

500 < Mll < 1500:

output-4

@cschwan
Copy link
Contributor Author

cschwan commented May 31, 2021

@enocera: the last commit should take care of the requested changes.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

Successfully merging this pull request may close these issues.

2 participants