The effects of massive neutrinos on the linear point of the correlation function

Parimbelli, G.; Anselmi, Stefano; Viel, Matteo; Carbone, C.; Villaescusa-Navarro, Francisco; Corasaniti, Pier-Stefano; Sheth, Ravi K.; Starkman, Glenn D.; Zehavi, Idit

doi:10.1088/1475-7516/2021/01/009

Cited by 28 publications

(37 citation statements)

References 73 publications

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“…(Most previous LP analyses increase the measured LP by a factor of 1.005 [e.g. [16][17][18][19]]. We do not; but if we had, the result would still be offset from linear theory by about 1%.)…”

Section: A Idealized Analysis: Perfect Prior Informationmentioning

confidence: 61%

“…For the mock galaxy samples, there are 12 realizations of each HOD in each of the 20 simulation boxes, for a total of 240 correlation functions from which to estimate the (HOD-dependent) covariance matrix. In practice, these covariance matrices are well approximated by the analytic estimate described in [13,19], provided we use the tracer number density and bias factor that is appropriate for each HOD, and we set the survey volume equal to 20 × (1.1h −1 Gpc) 3 . Since the analytic covariance matrices are smoother, we use them when fitting.…”

Section: A Idealized Analysis: Perfect Prior Informationmentioning

confidence: 99%

“…The convolution is approximately an isotropic Gaussian, so this motivated the fitting of a set of (integer or half-integer) generalized Laguerre functions to the measured two-point correlation function of galaxies. We used the Linear Point feature in this clustering signal [16][17][18][19][20] to quantify the gains in accuracy and precision which result from Laguerre re-construction of the correlation functions of dark matter, low and high mass halos, finding that they are comparable to those returned by more traditional and sophisticated algorithms which seek to reconstruct the density field rather than just its two-point statistics.…”

Section: Introductionmentioning

confidence: 99%

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Laguerre reconstruction of the BAO feature in halo-based mock galaxy catalogues

Nikakhtar,

Sheth,

Zehavi

2021

Preprint

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Fitting half-integer generalized Laguerre functions to the evolved, real-space dark matter and halo correlation functions provides a simple way to reconstruct their initial shapes. We show that this methodology also works well in a wide variety of realistic, assembly biased, velocity biased and redshift-space distorted mock galaxy catalogs. We use the linear point feature in the monopole of the redshift-space distorted correlation function to quantify the accuracy of our approach. We find that the linear point estimated from the mock galaxy catalogs is insensitive to the details of the biasing scheme at the subpercent level. However, the linear point scale in the nonlinear, biased, and redshiftspace distorted field is systematically offset from its scale in the unbiased linear density fluctuation field by more than 1%. In the Laguerre reconstructed correlation function, this is reduced to subpercent values, so it provides comparable accuracy and precision to methods that reconstruct the full density field before estimating the distance scale. The linear point in the reconstructed density fields provided by these other methods is likewise precise, accurate, and insensitive to galaxy bias. All reconstructions depend on some input parameters, and marginalizing over uncertainties in the input parameters required for reconstruction can degrade both accuracy and precision. The linear point simplifies the marginalization process, enabling more realistic estimates of the precision of the distance scale estimate for negligible additional computational cost. We show this explicitly for Laguerre reconstruction.

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Section: A Idealized Analysis: Perfect Prior Informationmentioning

confidence: 61%

Section: A Idealized Analysis: Perfect Prior Informationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Laguerre reconstruction of the BAO feature in halo-based mock galaxy catalogues

Nikakhtar,

Sheth,

Zehavi

2021

Preprint

View full text Add to dashboard Cite

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“…In what follows, we outline a rather different approach which is much cheaper and less tied to a cosmological model. We use the Linear Point (LP) -the scale that lies midway between the peak and dip, which previous work has shown can be used as a standard cosmological ruler [12][13][14][15][16] -to quantify the accuracy of our approach.…”

Section: Introductionmentioning

confidence: 99%

Laguerre reconstruction of the correlation function on Baryon Acoustic Oscillation scales

Nikakhtar,

Sheth,

Zehavi

2021

Preprint

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The baryon acoustic oscillation feature can be used as a standard cosmological ruler. In practice, for sub-percent level accuracy on the distance scale, it must be standardized. The physical reason why is understood, so we use this to develop an algorithm which improves the estimated scale. The algorithm exploits the fact that, over the range of scales where the initial correlation function is wellfit by a polynomial, the leading order effects which distort the length of the ruler can be accounted for analytically. Tests of the method in numerical simulations show that it provides simple and fast reconstruction of the full shape of the BAO feature, as well as subpercent determination of the linear point in the correlation function of biased tracers with minimal assumptions about the underlying cosmological model or the nature of the observed tracers.

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“…In all cases, the correlation functions in these boxes are measured in bins of width 1h −1 Mpc, and all our analyses only make use of the scales between 70 and 110h −1 Mpc. On these scales, the covariance between the different scales is well described by a simple 'smeared linear theory plus Poisson shot-noise model' [4,7,8].…”

Section: Introductionmentioning

confidence: 99%

The smearing scale in Laguerre reconstructions of the correlation function

Nikakhtar,

Sheth,

Zehavi

2021

Preprint

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To a good approximation, on large cosmological scales the evolved two-point correlation function of biased tracers is related to the initial one by a convolution. For Gaussian initial conditions, the smearing kernel is Gaussian, so if the initial correlation function is parametrized using simple polynomials then the evolved correlation function is a sum of generalized Laguerre functions of halfinteger order. This motivates an analytic 'Laguerre reconstruction' algorithm which previous work has shown is fast and accurate. This reconstruction requires as input the width of the smearing kernel. We show that the method can be extended to estimate the width of the smearing kernel from the same dataset. This estimate, and associated uncertainties, can then be used to marginalize over the distribution of reconstructed shapes, and hence provide error estimates on the value of the distance scale which are not tied to a particular cosmological model. We also show that if, instead, we parametrize the evolved correlation function using simple polynomials, then the initial one is a sum of Hermite polynomials, again enabling fast and accurate deconvolution. If one is willing to use constraints on the smearing scale from other datasets, then marginalizing over its value is simpler for Hermite reconstruction, potentially providing further speed-up in cosmological analyses.

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The effects of massive neutrinos on the linear point of the correlation function

Cited by 28 publications

References 73 publications

Laguerre reconstruction of the BAO feature in halo-based mock galaxy catalogues

Laguerre reconstruction of the BAO feature in halo-based mock galaxy catalogues

Laguerre reconstruction of the correlation function on Baryon Acoustic Oscillation scales

The smearing scale in Laguerre reconstructions of the correlation function

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