Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Iterative initial condition reconstruction   Motivated by recent developments in perturbative calculations of the
nonlinear evolution of large-scale structure, we present an iterative algorithm
to reconstruct the initial conditions in a given volume starting from the dark
matter distribution in real space. In our algorithm, objects are first moved
back iteratively along estimated potential gradients, with a progressively
reduced smoothing scale, until a nearly uniform catalog is obtained. The linear
initial density is then estimated as the divergence of the cumulative
displacement, with an optional second-order correction. This algorithm should
undo nonlinear effects up to one-loop order, including the higher-order
infrared resummation piece. We test the method using dark matter simulations in
real space. At redshift $z=0$, we find that after eight iterations the
reconstructed density is more than $95\%$ correlated with the initial density
at $k\le 0.35\; h\mathrm{Mpc}^{-1}$. The reconstruction also reduces the power
in the difference between reconstructed and initial fields by more than 2
orders of magnitude at $k\le 0.2\; h\mathrm{Mpc}^{-1}$, and it extends the
range of scales where the full broadband shape of the power spectrum matches
linear theory by a factor of 2-3. As a specific application, we consider
measurements of the baryonic acoustic oscillation (BAO) scale that can be
improved by reducing the degradation effects of large-scale flows. In our
idealized dark matter simulations, the method improves the BAO signal-to-noise
ratio by a factor of 2.7 at $z=0$ and by a factor of 2.5 at $z=0.6$, improving
standard BAO reconstruction by $70\%$ at $z=0$ and $30\%$ at $z=0.6$, and
matching the optimal BAO signal and signal-to-noise ratio of the linear density
in the same volume. For BAO, the iterative nature of the reconstruction is the
most important aspect.

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The categories of this paper are: dg-ga
36
The categories of this paper are: cmp-lg
14
The categories of this paper are: math-ph
12
The categories of this paper are: nucl-th
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The categories of this paper are: patt-sol
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The categories of this paper are: quant-ph
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The categories of this paper are: funct-an
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The categories of this paper are: ao-sci
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The categories of this paper are: alg-geom
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The categories of this paper are: stat
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The categories of this paper are: cond-mat
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The categories of this paper are: adap-org
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The categories of this paper are: q-fin
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The categories of this paper are: nlin
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The categories of this paper are: nucl-ex
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The categories of this paper are: plasm-ph