Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A population-based approach to background discrimination in particle
  physics   Background properties in experimental particle physics are typically
estimated using control samples corresponding to large numbers of events. This
can provide precise knowledge of average background distributions, but
typically does not consider the effect of fluctuations in a data set of
interest. A novel approach based on mixture model decomposition is presented as
a way to estimate the effect of fluctuations on the shapes of probability
distributions in a given data set, with a view to improving on the knowledge of
background distributions obtained from control samples. Events are treated as
heterogeneous populations comprising particles originating from different
processes, and individual particles are mapped to a process of interest on a
probabilistic basis. The proposed approach makes it possible to extract from
the data information about the effect of fluctuations that would otherwise be
lost using traditional methods based on high-statistics control samples. A
feasibility study on Monte Carlo is presented, together with a comparison with
existing techniques. Finally, the prospects for the development of tools for
intensive offline analysis of individual events at the Large Hadron Collider
are discussed.

13
The categories of this paper are: quant-ph
28
The categories of this paper are: alg-geom
11
The categories of this paper are: hep-lat
16
The categories of this paper are: stat
4
The categories of this paper are: cond-mat
32
The categories of this paper are: atom-ph
2
The categories of this paper are: math
34
The categories of this paper are: chem-ph
22
The categories of this paper are: chao-dyn
29
The categories of this paper are: funct-an
7
The categories of this paper are: hep-th
12
The categories of this paper are: nucl-th
37
The categories of this paper are: supr-con
25
The categories of this paper are: patt-sol
9
The categories of this paper are: nlin
18
The categories of this paper are: econ