1 <chapter name="Event Information">
3 <h2>Event Information</h2>
5 The <code>Info</code> class collects various one-of-a-kind information,
6 some relevant for all events and others for the current event.
7 An object <code>info</code> is a public member of the <code>Pythia</code>
8 class, so if you e.g. have declared <code>Pythia pythia</code>, the
9 <code>Info</code> methods can be accessed by
10 <code>pythia.info.method()</code>. Most of this is information that
11 could also be obtained e.g. from the event record, but is here more
12 directly available. It is primarily intended for processes generated
13 internally in PYTHIA, but many of the methods would work also for
14 events fed in via the Les Houches Accord.
17 Here are the currently available methods related to each event:
19 <method name="list()">
20 a listing of most of the information set for the current event.
23 <method name="idA(), idB()">
24 the identities of the two beam particles.
27 <method name="pzA(), pzB()">
28 the longitudinal momenta of the two beam particles.
31 <method name="eA(), eB()">
32 the energies of the two beam particles.
35 <method name="mA(), mB()">
36 the masses of the two beam particles.
39 <method name="eCM(), s()">
40 the cm energy and its square for the two beams.
43 <method name="name(), code()">
44 the name and code of the process that occured.
47 <method name="nFinal()">
48 the number of final-state partons in the hard process.
51 <method name="isResolved()">
52 are beam particles resolved, i.e. were PDF's used for the process?
55 <method name="isDiffractiveA(), isDiffractiveB()">
56 is either beam diffractively excited?
59 <method name="isMinBias()">
60 is the process a minimum-bias one?
63 <method name="isLHA()">
64 has the process been generated from external Les Houches Accord
68 <method name="atEndOfFile()">
69 true if a linked Les Houches class refuses to return any further
70 events, presumably because it has reached the end of the file from
71 which events have been read in.
74 <method name="hasSub()">
75 does the process have a subprocess classification?
76 Currently only true for minbias and Les Houches events, where it allows
77 the hardest collision to be identified.
80 <method name="nameSub(), codeSub(), nFinalSub()">
81 the name, code and number of final-state partons in the subprocess
82 that occured when <code>hasSub()</code> is true. For a minimum-bias event
83 the <code>code</code> would always be 101, while <code>codeSub()</code>
84 would vary depending on the actual hardest interaction, e.g. 111 for
85 <ei>g g -> g g</ei>. For a Les Houches event the <code>code</code> would
86 always be 9999, while <code>codeSub()</code> would be the external
87 user-defined classification code. The methods below would also provide
88 information for such particular subcollisions.
91 <method name="id1(), id2()">
92 the identities of the two partons coming in to the hard process.
95 <method name="x1(), x2()">
96 <ei>x</ei> fractions of the two partons coming in to the hard process.
99 <method name="y(), tau()">
100 rapidity and scaled mass-squared of the hard-process subsystem, as
101 defined by the above <ei>x</ei> values.
104 <method name="pdf1(), pdf2()">
105 parton densities <ei>x*f(x,Q^2</ei> )evaluated for the two incoming
106 partons; could be used e.g. for reweighting purposes.
109 <method name="QFac(), Q2Fac()">
110 the <ei>Q^2</ei> or <ei>Q^2</ei> factorization scale at which the
111 densities were evaluated.
114 <method name="isValence1(), isValence2()">
115 <code>true</code> if the two hard incoming partons have been picked
116 to belong to the valence piece of the parton-density distribution,
117 else <code>false</code>. Should be interpreted with caution.
118 Information is not set if you switch off parton-level processing.
121 <method name="alphaS(), alphaEM()">
122 the <ei>alpha_strong</ei> and <ei>alpha_electromagnetic</ei> values used
123 for the hard process.
126 <method name="QRen(), Q2Ren()">
127 the <ei>Q</ei> or <ei>Q^2</ei> renormalization scale at which
128 <ei>alpha_strong</ei> and <ei>alpha_electromagnetic</ei> were evaluated.
131 <method name="mHat(), sHat()">
132 the invariant mass and its square for the hard process.
135 <method name="tHat(), uHat()">
136 the remaining two Mandelstam variables; only defined for <ei>2 -> 2</ei>
140 <method name="pTHat(), pT2Hat()">
141 transverse momentum and its square in the rest frame of a <ei>2 -> 2</ei>
145 <method name="m3Hat(), m4Hat()">
146 the masses of the two outgoing particles in a <ei>2 -> 2</ei> processes.
149 <method name="thetaHat(), phiHat()">
150 the polar and azimuthal scattering angles in the rest frame of
151 a <ei>2 -> 2</ei> process.
154 <method name="weight()">
155 weight assigned to the current event. Is normally 1 and thus uninteresting.
156 However, for Les Houches events some strategies allow negative weights,
157 which then after unweighting lead to events with weight -1. There are also
158 strategies where no unweighting is done, and therefore a nontrivial event
159 weight must be used e.g. when filling histograms.
162 <method name="bMI()">
163 the impact parameter <ei>b</ei> assumed for the current collision when
164 multiple interactions are simulated. Is not expressed in any physical
165 size (like fm), but only rescaled so that the average should be unity
166 for minimum-bias events (meaning less than that for events with hard
170 <method name="enhanceMI()">
171 The choice of impact parameter implies an enhancement or depletion of
172 the rate of subsequent interactions, as given by this number. Again
173 the average is normalized be unity for minimum-bias events (meaning
174 more than that for events with hard processes).
177 <method name="nMI()">
178 the number of hard interactions in the current event. Is 0 for elastic
179 and diffractive events, and else at least 1, with more possible from
180 multiple interactions.
183 <method name="codeMI(i), pTMI(i)">
184 the process code and transverse momentum of the <code>i</code>'th
185 subprocess, with <code>i</code> in the range from 0 to
186 <code>nMI() - 1</code>. The values for subprocess 0 is redundant with
187 information already provided above.
190 <method name="nISR(), nFSRinProc(), nFSRinRes()">
191 the number of emissions in the initial-state showering, in the final-state
192 showering excluding resonance decys, and in the final-state showering
193 inside resonance decays, respectively.
197 Here are the currently available methods related to the event sample
198 as a whole. While continuously updated during the run, it is recommended
199 only to study these properties at the end of the event generation,
200 when the full statistics is available.
202 <method name="nTried(), nSelected(), nAccepted()">
203 the total number of tried phase-space points, selected hard processes
204 and finally accepted events, summed over all allowed subprocesses.
205 The first number is only intended for a study of the phase-space selection
206 efficiency. The last two numbers usually only disagree if the user introduces
207 some veto during the event-generation process; then the former is the number
208 of acceptable events found by PYTHIA and the latter the number that also
209 were approved by the user. If you set <aloc href="ASecondHardProcess">a
210 second hard process</aloc> there may also be a mismatch.
213 <method name="sigmaGen(), sigmaErr()">
214 the estimated cross section and its estimated error,
215 summed over all allowed subprocesses, in units of mb. The numbers refer to
216 the accepted event sample above, i.e. after any user veto.
221 <!-- Copyright (C) 2008 Torbjorn Sjostrand -->