Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: MHT-X: Offline Multiple Hypothesis Tracking with Algorithm X   An efficient and versatile implementation of offline multiple hypothesis
tracking with Algorithm X for optimal association search was developed using
Python. The code is intended for scientific applications that do not require
online processing. Directed graph framework is used and multiple scans with
progressively increasing time window width are used for edge construction for
maximum likelihood trajectories. The current version of the code was developed
for applications in multiphase hydrodynamics, e.g. bubble and particle
tracking, and is capable of resolving object motion, merges and splits.
Feasible object associations and trajectory graph edge likelihoods are
determined using weak mass and momentum conservation laws translated to
statistical functions for object properties. The code is compatible with
n-dimensional motion with arbitrarily many tracked object properties. This
framework is easily extendable beyond the present application by replacing the
currently used heuristics with ones more appropriate for the problem at hand.
The code is open-source and will be continuously developed further.

13
The categories of this paper are: quant-ph
2
The categories of this paper are: math
20
The categories of this paper are: acc-phys
32
The categories of this paper are: atom-ph
37
The categories of this paper are: supr-con
35
The categories of this paper are: mtrl-th
33
The categories of this paper are: plasm-ph
7
The categories of this paper are: hep-th
10
The categories of this paper are: q-bio
0
The categories of this paper are: hep-ph
27
The categories of this paper are: comp-gas
36
The categories of this paper are: cmp-lg
15
The categories of this paper are: nucl-ex
31
The categories of this paper are: ao-sci
14
The categories of this paper are: math-ph
4
The categories of this paper are: cond-mat