Feasibility of Probing Dark Energy with Strong Gravitational Lensing Systems: Fisher-Matrix Approach

Yamamoto, Kazuhiro; Kadoya, Yasufumi; Murata, Tsukasa; Futamase, Toshifumi

doi:10.1143/ptp.106.917

Cited by 19 publications

(18 citation statements)

References 25 publications

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“…The inversion of gravitational lensing systems is interesting in its own right, since it puts constraints on the spatial dark matter distribution of the lensing objects and thus helps constrain dark matter physics (Diemand, Moore & Stadel 2004; Navarro et al 2004), but it may also contribute to cosmology. Good reconstructions of lensing systems may help to constrain the density parameter and the redshift evolution of the dark energy (Yamamoto et al 2001; Soucail, Kneib & Golse 2004; Meneghetti et al 2005).…”

Section: Introductionmentioning

confidence: 99%

A genetic algorithm for the non-parametric inversion of strong lensing systems

Liesenborgs

Rijcke

Dejonghe

2006

Monthly Notices of the Royal Astronomical Society

117

126

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We present a non‐parametric technique to infer the projected mass distribution of a gravitational lens system with multiple strong‐lensed images. The technique involves a dynamic grid in the lens plane on which the mass distribution of the lens is approximated by a sum of basis functions, one per grid cell. We used the projected mass densities of Plummer spheres as basis functions. A genetic algorithm then determines the mass distribution of the lens by forcing images of a single source, projected back on to the source plane, to coincide as well as possible. Averaging several tens of solutions removes the random fluctuations that are introduced by the reproduction process of genomes in the genetic algorithm and highlights those features common to all solutions. Given the positions of the images and the redshifts of the sources and the lens, we show that the mass of a gravitational lens can be retrieved with an accuracy of a few percent and that, if the sources sufficiently cover the caustics, the mass distribution of the gravitational lens can also be reliably retrieved. A major advantage of the algorithm is that it makes full use of the information contained in the radial images, unlike methods that minimize the residuals of the lens equation, and is thus able to accurately reconstruct also the inner parts of the lens.

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Section: Introductionmentioning

confidence: 99%

A genetic algorithm for the non-parametric inversion of strong lensing systems

Liesenborgs

Rijcke

Dejonghe

2006

Monthly Notices of the Royal Astronomical Society

117

126

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“…Although not discussed in this paper, a very interesting piece of work would be to investigate the potentiality of an accurate strong lensing analysis as a cosmological tool (e.g. Link & Pierce 1998; Yamamoto et al 2001; Golse, Kneib & Soucail 2002; Soucail, Kneib & Golse 2004). Previous works (Yamamoto et al 2001; Chiba & Takahashi 2002; Sereno 2002; Dalal, Holder & Hennawi 2004) suggest that the lensing observables are primarily dependent on the lens model, while the dependence in the cosmological parameters is minor.…”

Section: Discussionmentioning

confidence: 99%

“…Although cluster lens systems are scarce, the impressive number of lensed images in each system means that they still contain a lot of information, particularly regarding cluster mass profiles. The information is harder to extract because of the relatively complicated gravitational potentials, but if this challenge can be overcome they could be highly useful probes, certainly of cluster physics and potentially also for cosmology (Yamamoto & Futamase 2001; Yamamoto et al 2001; Chiba & Takahashi 2002; Golse, Kneib & Soucail 2002; Sereno 2002; Meneghetti et al 2004). The intention of this paper is to improve the methods for extracting this information.…”

Section: Introductionmentioning

confidence: 99%

Non-parametric inversion of strong lensing systems

Diego

Protopapas

Sandvik

et al. 2005

Monthly Notices of the Royal Astronomical Society

116

154

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We revisit the issue of non-parametric gravitational lens reconstruction and present a new method to obtain the cluster mass distribution using strong lensing data without using any prior information on the underlying mass. The method relies on the decomposition of the lens plane into individual cells. We show how the problem in this approximation can be expressed as a system of linear equations for which a solution can be found. Moreover, we propose to include information about the null space. That is, make use of the pixels where we know there are no arcs above the sky noise. The only prior information is an estimation of the physical size of the sources. No priors on the luminosity of the cluster or shape of the halos are needed thus making the results very robust. In order to test the accuracy and bias of the method we make use of simulated strong lensing data. We find that the method reproduces accurately both the lens mass and source positions and provide error estimates.Comment: This is the accepted version in MNRAS. Thsi includes improvements suggested by the referee and one new plot. Additional material can be found in http://darwin.cfa.harvard.edu/SLAP/index.asp

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“…For strong lensing time delay cosmography, the source should be a bright, time varying object such as an active galactic nucleus (AGN) and the lens is generally a foreground galaxy (as cluster lenses are harder to model). See [12][13][14][15][16][17][18][19][20][21][22] for further details on strong lensing time delays as a cosmological probe.…”

Section: Measuring Time Delay Distancesmentioning

confidence: 99%

Tailoring strong lensing cosmographic observations

Linder

2015

Phys. Rev. D

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Strong lensing time delay cosmography has excellent complementarity with other dark energy probes, and will soon have abundant systems detected. We investigate two issues in the imaging and spectroscopic followup required to obtain the time delay distance. The first is optimization of spectroscopic resources. We develop a code to optimize the cosmological leverage under the constraint of constant spectroscopic time, and find that sculpting the lens system redshift distribution can deliver a 40% improvement in dark energy figure of merit. The second is the role of systematics, correlated between different quantities of a given system or model errors common to all systems. We show how the levels of different systematics affect the cosmological parameter estimation, and derive guidance for the fraction of double image vs quad image systems to follow as a function of differing systematics between them.

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Feasibility of Probing Dark Energy with Strong Gravitational Lensing Systems: Fisher-Matrix Approach

Cited by 19 publications

References 25 publications

A genetic algorithm for the non-parametric inversion of strong lensing systems

A genetic algorithm for the non-parametric inversion of strong lensing systems

Non-parametric inversion of strong lensing systems

Tailoring strong lensing cosmographic observations

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