Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Estimating initial conditions for dynamical systems with incomplete
  information   In this paper we study the problem of inferring the initial conditions of a
dynamical system under incomplete information. Studying several model systems,
we infer the latent microstates that best reproduce an observed time series
when the observations are sparse,noisy and aggregated under a (possibly)
nonlinear observation operator. This is done by minimizing the least-squares
distance between the observed time series and a model-simulated time series
using gradient-based methods. We validate this method for the Lorenz and
Mackey-Glass systems by making out-of-sample predictions. Finally, we analyze
the predicting power of our method as a function of the number of observations
available. We find a critical transition for the Mackey-Glass system, beyond
which it can be initialized with arbitrary precision.

20
The categories of this paper are: acc-phys
17
The categories of this paper are: q-fin
27
The categories of this paper are: comp-gas
7
The categories of this paper are: hep-th
36
The categories of this paper are: cmp-lg
29
The categories of this paper are: funct-an
13
The categories of this paper are: quant-ph
21
The categories of this paper are: adap-org
11
The categories of this paper are: hep-lat
18
The categories of this paper are: econ
34
The categories of this paper are: chem-ph
3
The categories of this paper are: physics
33
The categories of this paper are: plasm-ph
12
The categories of this paper are: nucl-th
32
The categories of this paper are: atom-ph
37
The categories of this paper are: supr-con