Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: SVD Approach to Data Unfolding   Distributions measured in high energy physics experiments are usually
distorted and/or transformed by various detector effects. A regularization
method for unfolding these distributions is re-formulated in terms of the
Singular Value Decomposition (SVD) of the response matrix. A relatively simple,
yet quite efficient unfolding procedure is explained in detail. The concise
linear algorithm results in a straightforward implementation with full error
propagation, including the complete covariance matrix and its inverse. Several
improvements upon widely used procedures are proposed, and recommendations are
given how to simplify the task by the proper choice of the matrix. Ways of
determining the optimal value of the regularization parameter are suggested and
discussed, and several examples illustrating the use of the method are
presented.

32
The categories of this paper are: atom-ph
36
The categories of this paper are: cmp-lg
8
The categories of this paper are: hep-ex
10
The categories of this paper are: q-bio
5
The categories of this paper are: gr-qc
29
The categories of this paper are: funct-an
24
The categories of this paper are: dg-ga
2
The categories of this paper are: math
31
The categories of this paper are: ao-sci
35
The categories of this paper are: mtrl-th
7
The categories of this paper are: hep-th
30
The categories of this paper are: q-alg
37
The categories of this paper are: supr-con
22
The categories of this paper are: chao-dyn
6
The categories of this paper are: astro-ph
16
The categories of this paper are: stat