Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Stitching Monte Carlo samples   Monte Carlo (MC) simulations are extensively used for various purposes in
modern high-energy physics (HEP) experiments. Precise measurements of
established Standard Model processes or searches for new physics often require
the collection of vast amounts of data. It is often difficult to produce MC
samples of size matching that of the data, as substantial computing resources
are required to produce and store such samples. One solution often employed
when producing MC samples for HEP experiments is to divide the phase-space of
particle interactions into multiple regions and produce the MC samples
separately for each region, with the size of MC samples being adapted to the
needs of physics analyses that are performed in these regions. In this paper we
present an optimal procedure for combining MC samples that overlap in
phase-space. Our procedure is optimal in the sense that it provides the lowest
statistical uncertainties. We refer to the procedure as "stitching". The paper
includes different examples for applying the procedure to simulated
proton-proton collisions at the CERN Large Hadron Collider.

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The categories of this paper are: hep-th
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The categories of this paper are: gr-qc
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The categories of this paper are: adap-org
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The categories of this paper are: plasm-ph
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The categories of this paper are: chem-ph
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The categories of this paper are: bayes-an
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The categories of this paper are: comp-gas
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The categories of this paper are: eess
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The categories of this paper are: nucl-ex
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The categories of this paper are: hep-ph
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The categories of this paper are: econ
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The categories of this paper are: cmp-lg
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The categories of this paper are: astro-ph
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The categories of this paper are: math
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The categories of this paper are: cs
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The categories of this paper are: nucl-th