scholarly journals Simulations and symmetries

2020 ◽  
Vol 492 (4) ◽  
pp. 5754-5763 ◽  
Author(s):  
Chirag Modi ◽  
Shi-Fan Chen ◽  
Martin White

ABSTRACT We investigate the range of applicability of a model for the real-space power spectrum based on N-body dynamics and a (quadratic) Lagrangian bias expansion. This combination uses the highly accurate particle displacements that can be efficiently achieved by modern N-body methods with a symmetries-based bias expansion which describes the clustering of any tracer on large scales. We show that at low redshifts, and for moderately biased tracers, the substitution of N-body-determined dynamics improves over an equivalent model using perturbation theory by more than a factor of two in scale, while at high redshifts and for highly biased tracers the gains are more modest. This hybrid approach lends itself well to emulation. By removing the need to identify haloes and subhaloes, and by not requiring any galaxy-formation-related parameters to be included, the emulation task is significantly simplified at the cost of modelling a more limited range in scale.

2019 ◽  
Vol 485 (2) ◽  
pp. 2407-2416 ◽  
Author(s):  
Lehman H Garrison ◽  
Daniel J Eisenstein

ABSTRACT We present a method for generating suites of dark matter halo catalogues with only a few N-body simulations, focusing on making small changes to the underlying cosmology of a simulation with high precision. In the context of blind challenges, this allows us to re-use a simulation by giving it a new cosmology after the original cosmology is revealed. Starting with full N-body realizations of an original cosmology and a target cosmology, we fit a transfer function that displaces haloes in the original so that the galaxy/HOD power spectrum matches that of the target cosmology. This measured transfer function can then be applied to a new realization of the original cosmology to create a new realization of the target cosmology. For a 1 per cent change in σ8, we achieve 0.1 per cent accuracy to $k = 1\, h\, \mathrm{Mpc}^{-1}$ in the real-space power spectrum; this degrades to 0.3 per cent when the transfer function is applied to a new realization. We achieve similar accuracy in the redshift-space monopole and quadrupole. In all cases, the result is better than the sample variance of our $1.1\, h^{-1}\, \mathrm{Gpc}$ simulation boxes.


1999 ◽  
Vol 305 (3) ◽  
pp. 527-546 ◽  
Author(s):  
H. Tadros ◽  
W. E. Ballinger ◽  
A. N. Taylor ◽  
A. F. Heavens ◽  
G. Efstathiou ◽  
...  

2012 ◽  
Vol 2012 (11) ◽  
pp. 029-029 ◽  
Author(s):  
Héctor Gil-Marín ◽  
Christian Wagner ◽  
Licia Verde ◽  
Cristiano Porciani ◽  
Raul Jimenez

1995 ◽  
Vol 276 (1) ◽  
pp. L59-L63 ◽  
Author(s):  
W. E. Ballinger ◽  
A. F. Heavens ◽  
A. N. Taylor
Keyword(s):  

Author(s):  
Marcus Shaker ◽  
Edmond S. Chan ◽  
Jennifer LP. Protudjer ◽  
Lianne Soller ◽  
Elissa M. Abrams ◽  
...  

Mathematics ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1148
Author(s):  
Jewgeni H. Dshalalow ◽  
Ryan T. White

In a classical random walk model, a walker moves through a deterministic d-dimensional integer lattice in one step at a time, without drifting in any direction. In a more advanced setting, a walker randomly moves over a randomly configured (non equidistant) lattice jumping a random number of steps. In some further variants, there is a limited access walker’s moves. That is, the walker’s movements are not available in real time. Instead, the observations are limited to some random epochs resulting in a delayed information about the real-time position of the walker, its escape time, and location outside a bounded subset of the real space. In this case we target the virtual first passage (or escape) time. Thus, unlike standard random walk problems, rather than crossing the boundary, we deal with the walker’s escape location arbitrarily distant from the boundary. In this paper, we give a short historical background on random walk, discuss various directions in the development of random walk theory, and survey most of our results obtained in the last 25–30 years, including the very recent ones dated 2020–21. Among different applications of such random walks, we discuss stock markets, stochastic networks, games, and queueing.


Sign in / Sign up

Export Citation Format

Share Document