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--- 2013:groups:tools:substructure [2013/06/05 18:42]
loch.peter [Configurations]
+++ 2013:groups:tools:substructure [2013/06/06 11:51]
gregory.soyez [Methods]
@@ Line 31: / Line 31: @@
-===== Configurations =====
+===== Configurations & Software =====
+The following configurations for the (average) number of pile-up interactions $\langle\mu\rangle$ are suggested
+$$ \langle\mu\rangle = \{ 30, 60, 120, 240 \} $$
+The actual number of pile-up interactions added to the signal event is taken from a Poisson distribution around $\langle\mu\rangle$.
+==== Software version 1 ====
+Pile-up can be added dynamically using this **{{:2013:groups:tools:anal02.tar.gz| software}}**. The main concept here is that the ROOT based raw data is converted into an ''Event'' obejct containing lists of ''PseudoJet''s (from ''Fastjet'') representing
+  * the total particle (hadron) level event (signal + pile-up)
+  * the particle (hadron) level signal event
+  * the particle (hadron) level pile-up event
+The code is not very convenient to use in this version. After unpacking with
+<code>
+tar zxvf <archive>.tar.gz
+</code>
+on most systems I expect a
+<code>make all</code> should work to compile the library and the example in ''anal02.C''.  For implementing your own analysis, please check the ''anal02.C'' and ''Zprime_Py8::analyze(Event& rEvt)'' (your playground) in ''Zprime_Py8.C'' as examples. The program supports a few command line arguments
+<code>
+anal02.exe --help --mu=<mu> --nevts=<number of (signal) events>
+           --sigflist=<text file with list of signal files>
+           --puflist=<text file with list of pile-up files>
+</code>
+Some hints:
+  * ''--help'' prints a brief usage instruction (which I think is not up-to-date, so please ignore!)
+  * ''--mu=<mu>'' expects the number of interactions per event. if ''<mu> < 0'', exactly ''|<mu>|'' interactions are collected into one event. ''<mu> > 0'' means a Poisson-distributed number of pile-up interactions will be collected from the pile-up (minimum bias) event samples.
+    * if you specify both signal and pile-up input, ''<mu>'' should be the number of pile-up events to be added to one signal event
+  * ''--sigflist=<file>'' specifies a text file (no "" around file name!) with a list of signal files to be processed. If this list is not given, ''Zprime_Py8::analyze(...)'' will not be invoked.
+  * ''--puflist=<file>'' specifies a text file (no "" around file name!) with a list of pile-up files to be processed. If this list is not given, only signal events are analyzed (you should set ''--mu=1'' in this case!).
-Pile-up can be added dynamically using this **{{:2013:groups:tools:anal02.tar.gz| software}}**.
 ===== Methods =====
+The idea is to test filtering/grooming techniques as a way to reduce the sensiticity to bsoft backgrounds (initially the filter used with the BDRS tagger was meant to reduce the sensitivity to the UE).
+Following the Filter tool in FastJet3, we need (i) a jet definition to break the jet into subjets and (ii) a selection criterion that decides what subjets are kept. We'll consider 3 options:
+  * "Filtering":
+    * cluster with Cambridge/Aachen, $R_{\rm filt} = \eta_{\rm filt} R_{\rm jet}$ [$\eta_{\rm filt}$ between 1/3 and 1/2 sounds about right]
+    * keep the $n_{\rm filt}$ hardest subjets [$n_{\rm filt}$=2.3.4]
+  * "Trimming":
+    * cluster with Cambridge/Aachen, $R_{\rm filt} = 0.2$
+    * keep all subjets with $p_{t,\rm sub} > f p_{t,jet}$ [$f$ between 0.01 and 0.05 should be fine]
+  * "Area-filtering":
+    * cluster with Cambridge/Aachen, $R_{\rm filt} = 0.2$
+    * keep all subjets with $p_{t,\rm sub} > \rho A_{\rm sub} + n \sigma \sqrt{A_{\rm sub}}$ [$n$ between 2 and 5]
+The 3rd option is new and based on the idea that the PU scales $\rho$ and $\sigma$ should set the scale of the PU/noise removal.
+For pileup sutraction, one usually want to first subtract the average PU contamination ($\rho A_{\rm sub}$) from each subjet before deciding which subjets are to be kept. This is implemented in the fastjet::Filter. Note that with "Area-filtering" you should then cut with   $p_{t,\rm sub} > n \sigma \sqrt{A_{\rm sub}}$ since the baseline has already been subtracted.

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