MUSE spectroscopy and deep observations of a unique compact JWST target, lensing cluster CLIO

Griffiths, Alex; Conselice, Christopher J.; Alpaslan, Mehmet; Frye, Brenda; Diego, J. M.; Zitrin, Adi; Yan, Haojing; Ma, Zhiyuan; Barone-Nugent, R. L.; Bhatawdekar, Rachana; Driver, Simon P.; Robotham, Aaron S. G.; Windhorst, Rogier A.; Wyithe, J. Stuart B.

doi:10.1093/mnras/stx3364

Cited by 12 publications

(13 citation statements)

References 82 publications

(102 reference statements)

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“…Alternatively, one can identify portions of the critical curves at lower redshift, which have relatively small contributions from microlenses. For example, the critical curves connecting two clusters in the process of merging produce near pristine critical curves in between the two clusters like the ones observed in the G165 cluster (Frye et al 2018;Griffiths et al 2018).…”

Section: The Role Of Microlensesmentioning

confidence: 86%

The Universe at extreme magnification

Diego

2019

A&A

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Extreme magnifications of distant objects by factors of several thousand have recently become a reality. Small very luminous compact objects, such as supernovae (SNe), giant stars at z = 1 -2, Pop III stars at z > 7 and even gravitational waves from merging binary black holes near caustics of gravitational lenses can be magnified to many thousands or even tens of thousands thanks to their small size. We explore the probability of such extreme magnifications in a cosmological context including also the effect of microlenses near critical curves. We show how a natural limit to the maximum magnification appears due to the presence of microlenses near critical curves. We use a combination of state of the art halo mass functions, high-resolution analytical models for the density profiles and inverse ray tracing to estimate the probability of magnification near caustics. We estimate the rate of highly-magnified events in the case of SNe, GW and very luminous stars including Pop III stars. Our findings reveal that future observations will increase the number of events at extreme magnifications opening the door not only to study individual sources at cosmic distances but also to constrain compact dark matter candidates.A&A proofs: manuscript no. main of it), as well as the observation of the relatively abundant low frequency LIGO events. In this work we estimate the probability of observing, not only luminous stars at z > 1 but also discuss other very compact but intrinsically energetic phenomena, such as SNe, or GW.In order to observe distant gravitationally lensed objects, one needs large magnification factors that compensate for the increase in luminosity distance. The smaller probability of lensing is partially compensated by the larger volume which, between z ≈ 0.3 and z ≈ 1.3, grows approximately as (1 + z) 3 (and at a slower rate at higher redshifts). More precisely, the volume per redshift interval peaks at z ≈ 2.5 (with about 55 Gpc 3 in a redshift interval of thickness ∆z = 0.1). Regarding the probability of lensing, background objects at high redshifts have a higher probability of intersecting a gravitational lens along the line of sight. This probability is described by the optical depth. It is well known that the optical depth grows rapidly between z=0 and z=1. Between z=1 and z=3 it continues to grow although at a much slower pace. Beyond z =3 -5, the optical depth is still growing but much more slowly and beyond z =5 it only grows by percent values, specially if one considers large magnification factors where the presence of caustics is required (these caustics are expected to be rare for lenses beyond z ≈ 3). For sources (or events) that trace the star formation history, and at redshifts of the background source between 1 and 3, the small probability of magnification factors can be compensated by the larger volume element and increased volumetric density. In this redshift interval, the probability of seeing extremely magnified events can be maximum.Examples of extreme magnification are the aforementioned ...

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Section: The Role Of Microlensesmentioning

confidence: 86%

The Universe at extreme magnification

Diego

2019

A&A

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“…At the same time, by studying the redshift distribution of other "interloper" galaxies in the field, it is possible to detect compact groups of objects in front of or behind the cluster (i.e., line-of-sight substructures) that are not often obvious in imaging. Over the past few years, several lensing studies have taken advantage of MUSE spectroscopy (e.g., Richard et al 2015;Karman et al 2015;Bina et al 2016;Patrício et al 2016;Grillo et al 2016;Caminha et al 2017b;Griffiths et al 2018;Mahler et al 2018) to great effect.…”

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confidence: 99%

Probing 3D Structure with a Large MUSE Mosaic: Extending the Mass Model of Frontier Field Abell 370

Lagattuta

Richard

Bauer

et al. 2019

Monthly Notices of the Royal Astronomical Society

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We present an updated strong-lensing analysis of the massive cluster Abell 370 (A370), continuing the work first presented in Lagattuta et al. (2017). In this new analysis, we take advantage of the deeper imaging data from the Hubble Space Telescope (HST) Frontier Fields program, as well as a large spectroscopic mosaic obtained with the Multi-Unit Spectroscopic Explorer (MUSE). Thanks to the extended coverage of this mosaic, we probe the full 3D distribution of galaxies in the field, giving us a unique picture of the extended structure of the cluster and its surroundings. Our final catalog contains 584 redshifts, representing the largest spectroscopic catalog of A370 to date. Constructing the model, we measure a total mass distribution that is quantitatively similar to our previous work -though to ensure a low rms error in the model fit, we invoke a significantly large external shear term. Using the redshift catalog, we search for other bound groups of galaxies, which may give rise to a more physical interpretation of this shear. We identify three structures in narrow redshift ranges along the line of sight, highlighting possible infalling substructures into the main cluster halo. We also discover additional substructure candidates in low-resolution imaging at larger projected radii. More spectroscopic coverage of these regions (pushing close to the A370 virial radius) and more extended, high-resolution imaging will be required to investigate this possibility, further advancing the analysis of these interesting developments.

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“…In current and upcoming eras of astronomy, there is a wealth of information that multi-object IFU observations can provided within these dense, or blank field areas of the universe. This includes finding galaxies that cannot be seen in the deepest optical imaging (Bacon et al 2017), as well as in the study of galaxy clusters (e.g., Griffiths et al 2018;Mahler et al 2018). Not only does an IFU give information on the radial velocity, and thus membership and physical properties of member galaxies, it also provides information on the background lensed systems.…”

Section: Introductionmentioning

confidence: 99%

“…These software packages employ computational techniques to perform blind searches of a datacube in order to identify emission lines. In fact, a combination of photometric pre-selection and blind searches has been found to be favorable (e.g., Bacon et al 2017;Griffiths et al 2018;Mahler et al 2018) to produce source catalogs for spectral extraction. Unfortunately, the optimal method for obtaining one dimensional spectra from an IFU datacube still remains unclear.…”

Section: Introductionmentioning

confidence: 99%

“…To circumvent some of these issues, an object's morphology can be used when defining spectral extraction regions. IFU studies of galaxy clusters such as Griffiths et al (2018) and Mahler et al (2018) implement the use of SExtractor segmentation maps derived from deep imaging data as a basis of weighted spectral extraction. The work recently carried out on MUSE observations of the Hubble Ultra Deep Field (Bacon et al 2017) also follows similar extraction methods.…”

Section: Introductionmentioning

confidence: 99%

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AutoSpec: Fast Automated Spectral Extraction Software for IFU Data Cubes

Griffiths

Conselice

2018

ApJ

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With the ever growing popularity of integral field unit (IFU) spectroscopy, countless observations are being performed over multiple object systems such as blank fields and galaxy clusters. With this, an increasing amount of time is being spent extracting one dimensional object spectra from large three dimensional datacubes. However, a great deal of information available within these datacubes is overlooked in favor of photometrically based spatial information. Here we present a novel, yet simple approach of optimal source identification, utilizing the wealth of information available within an IFU datacube, rather than relying on ancillary imaging. Through the application of these techniques, we show that we are able to obtain object spectra comparable to deep photometry weighted extractions without the need for ancillary imaging. Further, implementing our custom designed algorithms can improve the signal-to-noise of extracted spectra and successfully deblend sources from nearby contaminants. This will be a critical tool for future IFU observations of blank and deep fields, especially over large areas where automation is necessary. We implement these techniques into the Python based spectral extraction software, AutoSpec which is available via GitHub at: https://github.com/a-griffiths/AutoSpec and Zenodo at: https://doi.org/10.5281/zenodo.1305848

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MUSE spectroscopy and deep observations of a unique compact JWST target, lensing cluster CLIO

Cited by 12 publications

References 82 publications

The Universe at extreme magnification

The Universe at extreme magnification

Probing 3D Structure with a Large MUSE Mosaic: Extending the Mass Model of Frontier Field Abell 370

AutoSpec: Fast Automated Spectral Extraction Software for IFU Data Cubes

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