Changes between Version 35 and Version 36 of Reweight


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Timestamp:
Feb 1, 2016, 6:36:11 PM (9 years ago)
Author:
Stefano Frixione
Comment:

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  • Reweight

    v35 v36  
    22
    33= Description of the method =
    4  The method consists to use a sample of events (weighted or unweighted events) and associates to those events a new weight corresponding to a new theoretical hypothesis based on the matrix-element. It corresponds to a multidimensional version of the unidimensional re-weighing method commonly used by experiments.
    5  Once computed, this weight can be propagate through the all simulation chain in order to avoid to have to perform the full-simulation on a huge number of sample.
    6  This methods works only if the original hypothesis and the new one are both significant in the same part of the phase-space.
    7  
    8  We support three types of reweightings. One for Leading Order sample and two for the Next-to-Leading Order sample (called Kamikaze Reweighting and NLO Reweighting)
     4 The method consists in using a sample of events (weighted or unweighted) generated under a certain theoretical hypothesis (a model and its parameters with given values), and in associating with those events an additional weight that corresponds to a new theoretical hypothesis (a different model, and/or different parameter choices); both the original and the additional weights are thus based solely on matrix-element computations.
     5 Once computed, the additional weight can be propagated through all of the simulation chain, and saves one from performing eg a full simulation on an additional event sample.
     6 The methods works only if both the original and the new hypothesis give non-negligible contributions to the same parts of the phase-space.
     7 
     8 We support three types of reweightings, one for Leading Order (LO) samples, and two for the Next-to-Leading Order (NLO) samples (dubbed Kamikaze Reweighting and NLO Reweighting)
    99
    1010 '''Leading Order'''[[BR]][[BR]]
    11  At Leading Order, the new weight is given by
     11 At the Leading Order, the new weight is given by
    1212 $$W_{new} = |M^{new}_h|^2 /|M^{old}_h|^2 * W_{old} $$
    13  where h is the helicity associated to the events and $|M^{new/old}_h|^2$ is the matrix element for the corresponding helicity.
    14  If the events is not associated to a specific helicity, then the sum over the helicity is used instead.
    15 
    16  This method is fully LO accurate and do not present any bias. Note that the statistical fluctuation of the original sample can be enhanced by the reweighting.
    17  To get an idea of such propagation, one can use the naive formula of propagation of error:
     13 where h is the helicity associated with the event, and $|M^{new/old}_h|^2$ is the matrix element for the corresponding helicity.
     14 If the event is not associated with a specific helicity, then the sum over the helicity is used instead.
     15
     16 This method is fully LO accurate and does not present any bias. Note that the statistical fluctuations of the original sample can be increased by reweighting.
     17 To have an idea of such an increase, one can use the naive formula of propagation of error:
    1818  $$\Delta\mathcal{O}_{new} = \bar R\cdot \Delta\mathcal{O}_{old} + \Delta R \cdot \mathcal{O}_{old} $$
    1919 where $\bar R$ is the average of the ratio of the matrix-element, $\Delta R$ the associated variance. $\mathcal{O}_{old/new}$ is the value of the observable under consideration for the associated hypothesis and $\Delta\mathcal{O}_{old/new}$ the associated variance.
    2020
    2121 '''Kamikaze Reweighting'''[[BR]][[BR]]
    22  This correspond to a Leading Order type of reweighting. Both the soft and hard events are reweighted according to the associated tree-level matrix element related to the number of particles in the final state. i.e.,
     22 This corresponds to a LO-type of reweighting. Both soft and hard events are reweighted according to the tree-level matrix element associated with the suitable number of final-state particles i.e.,
    2323        $$W^S_{new} = |M^{new}_{born}|^2 /|M^{old}_{born}|^2 * W^S_{old} $$
    2424        $$W^H_{new} = |M^{new}_{real}|^2 /|M^{old}_{real}|^2 * W^H_{old} $$
    … …  
    2828 '''NLO reweighting:'''[[BR]][[BR]]
    2929
    30  For this computation, we extend the basis introduced in http://arxiv.org/pdf/1110.4738v1.pdf to decompose the matrix-element component independent of the scale and pdf variation:
     30 For this computation, we employ the method introduced in http://arxiv.org/pdf/1110.4738v1.pdf to decompose the matrix elements in terms of scale- and PDF-independent coefficients:
    3131    $$d\sigma^{H} = d\sigma^E - d\sigma^{MC} $$
    3232    $$ d\sigma^{S} = d\sigma^{MC} + \sum_{\alpha=S,C,SC} d\sigma^\alpha $$
    … …  
    3636 Additionally, we decompose each of the $\mathcal{W^\alpha_\beta}$ in the component proportional to the born ($\mathcal{W}^\alpha_{\beta,B}$), the finite piece of virtual ($\mathcal{W}^\alpha_{\beta,V}$) and of the real ($\mathcal{W}^\alpha_{\beta,R}$).
    3737  $\mathcal{W^\alpha_\beta} = B*\mathcal{C}^\alpha_{\beta,B} + V*\mathcal{C}^\alpha_{\beta,V} + R*\mathcal{C}^\alpha_{\beta,R} \equiv \mathcal{W}^\alpha_{\beta,B} + \mathcal{W}^\alpha_{\beta,V} + \mathcal{W}^\alpha_{\beta,R}$
    38  In our implementation, the various value of $\mathcal{W}^\alpha_{\beta,\delta}$ are computed by MG5_aMC at running time and kept in the final events. More details on the basis are available in  the appendix of  http://arxiv.org/pdf/1110.4738v1.pdf and in a paper in preparation.
     38 In our implementation, the various $\mathcal{W}^\alpha_{\beta,\delta}$ are computed by MG5_aMC@NLO at running time and kept in the final events. More details on the decomposition are available in  the appendix of  http://arxiv.org/pdf/1110.4738v1.pdf (and in a paper in preparation).
    3939
    4040
    … …  
    5353 Such reweighting is fully NLO accurate. As in the LO case, the statistical uncertainty can be enhanced by the reweighting. Additionally the trick to support the virt-tricks adds an additional contribution to statistical uncertainty.
    5454 
    55  '''This method will be released in a future version of MadGraph5_aMC@NLO''' and can currently be provided on request. Since this reweighting is based on a dedicated basis the NLO sample must be generated in a specific way to have the additional information in the leshouches event.
     55 '''This method will be released in a future version of MadGraph5_aMC@NLO''' and can currently be provided on request. Since this reweighting is based on a dedicated decomposition, the NLO sample must be generated in a specific way to have the additional information in the Les Houches event file.
    5656
    5757[[PageOutline]]
    5858= Technical details
    5959== Limitation
    60   1. We do not perform any PDF and/or cut reweighting.
    61   2. We do not allowed to change the functional form / central value of alpha_S
    62   3. In presence of decay chain the order of the particles in the events file is important. This is important if you want to use this tools with LHE events not produced by MadGraph5_aMC@NLO.
     60  1. Changes of PDFs and/or of cuts are not permitted with this method of reweighting.
     61  2. Likewise, changes are not allowed in the functional forms used to compute the hard scales, and hence alpha_S
     62  3. In the presence of a decay chain, the order of the particles in the event file is important, and especially so with LHE events not produced by MadGraph5_aMC@NLO.
    6363
    6464
    … …  
    7272 === Running simultaneously with event generation
    7373
    74  When running event generation at LO or NLO (either via ./bin/generate_events from the local directory or "launch" via the mg5 interface). You will be asked two questions. The phrasing/options of those two questions depends if you run at LO or NLO but both follow the same strategy. Here we will take the example of a NLO generation.
     74 When running event generation at the LO or NLO (either via ./bin/generate_events from the local directory or by executing"launch" through the MG5_aMC@NLO interface), you will be asked two questions. The phrasing/options of those two questions depend on whether you run at the LO or NLO, but both follow the same strategy. Here we will take the example of an NLO generation.
    7575 In that case, the first question is:
    7676 {{{
    … …  
    8787}}}
    8888
    89  As you can see, the question presents a series of switch which can take different value (in the example "NLO", "ON", "OFF"). In order to perform the reweighting, you need to put the reweight switch to "ON".
     89 As you can see, the question presents a series of switches which can take different value (in the example "NLO", "ON", "OFF"). In order to perform the reweighting, you need to put the reweight switch to "ON".
    9090 Type
    9191{{{
    … …  
    106106 [0, 1, 2, 3, 4, 5, auto, done, order=LO, ... ][60s to answer]
    107107}}}
    108  This allow you to change any other switch (note that "fixed_order" needs to stay on OFF). You can type enter when you want to pass to the next question:
     108 This allows you to change any other switch (note that "fixed_order" needs to stay on OFF). You can type <enter> when you want to pass to the next question:
    109109 {{{
    110110Do you want to edit a card (press enter to bypass editing)?
    … …  
    123123}}}
    124124
    125  For a NLO accurate reweighting (available since 2.4.0), type
     125 For an NLO-accurate reweighting (which will be available from version 2.4.0), type
    126126 {{{
    127127set keep_rwgt_info True
    128128 }}}
    129  This can also be done via the manual edition of the run_card (by typing 2). With this option on False (the default) the kamikaze reweighting will be performed.
     129 This can also be done via the manual edition of the run_card (by typing 2). With this option set equal to False (the default) the kamikaze reweighting will be performed.
    130130
    131131 Then type
    … …  
    134134}}}
    135135 to open an editor (in most system this use vi) where you can edit the content of the reweight_card. The format/options of that file are describe below and at the beginning of the file. It allows you to specify which model/benchmark you want to use.
    136  When you are done, exit the file and press enter.
     136 When you are done, exit the file and press <enter>.
    137137
    138138 The code will then start the event generation and when done will directly run the reweighting.
    139139
    140  === Running the code after the generation of events as been completed.
    141 
    142  In order to run the reweighting on previously generated samples. You need to go to the associated process directory and run either '''./bin/madevent''' or '''./bin/aMC@NLO'''script for  respectively LO/NLO event generation.
    143  You can then type  '''reweight RUN_NAME''' (RUN_NAME is typically run_01) and you will be asked the same questions as above.
     140 === Running the code after the generation of events has been completed.
     141
     142 In order to run the reweighting on previously-generated samples, you need to go to the relevant process directory and run either the '''./bin/madevent''' or the '''./bin/aMC@NLO''' script for LO or NLO event generation respectively. You can then type  '''reweight RUN_NAME''' (RUN_NAME is typically run_01) and you will be asked the same questions as above.
    144143
    145144 Another options is to manually edit the Cards/reweight_card.dat file and then run one of the two following command:
    … …  
    153152 
    154153 
    155  The cards is compose of two sections:
     154 This card is composed of two sections:
    156155 1. '''Options''': [[BR]]
    157    Those are options which change the behavior of the reweighting. Those lines need to be specified before the first 'launch' line to have effects.
    158    1. '''change model <XXX>''' performed the reweighting within a new model (you then need to profide a full param_card and not a difference)
    159    2. '''change process <XXX>''' change the process definition of the process.
    160    3. '''change process <XXX> --add''' add one process definition of the process to the new list.
     156   These are options which change the behaviour of the reweighting. Those lines need to be specified before the first 'launch' command in order to be effective.
     157   1. '''change model <XXX>''' performs the reweighting within a new model (you then need to provide a full param_card and not the difference between two cards)
     158   2. '''change process <XXX>''' change the process definition.
     159   3. '''change process <XXX> --add''' add one process definition to the new list.
    161160   4. '''change output <i>''': Three options: 'default'(i.e. lhef version3 format), '2.0' (i.e. lhef version2 format, the main weight is replace), 'unweight' (a new unweighting is applied on the events sample.)
    162    5. '''change helicity <True|False>''': perform reweighting for the given helicity (True --default--) or do the sum over helicity.
    163    6. '''change rwgt_dir <PATH>''': change directory where the computation is performed. This can be use to avoid to recreate/recompile the fortran executable if pointing to a previously existing directory.
    164    7. '''change mode LO''': For NLO sample, this flag force to use the kamikaze reweighting (available in 2.4.0)
     161   5. '''change helicity <True|False>''': perform reweighting for the given helicity (True --default--) or carry out the sum over helicity.
     162   6. '''change rwgt_dir <PATH>''': change directory where the computation is performed. This can be used to avoid to recreate/recompile the fortran executable if pointing to a previously existing directory.
     163   7. '''change mode LO''': For NLO samples, this flag forces the code to perform the kamikaze reweighting (available in 2.4.0)
    165164
    166165 2. '''benchmark definition''':[[BR]]