J-PLUS: A catalogue of globular cluster candidates around the M81/M82/NGC3077 triplet of galaxies

Chies-Santos, Ana L.; Caso, Juan Pablo; Ennis, Ana Inés; Souza, Camila P. E. de; Barbosa, Renan Santos; Chen, Peng; Cenarro, A. J.; Ederoclite, A.; Cristóbal-Hornillos, D.; Hernández-Monteagudo, Carlos; López-Sanjuán, C.; Marín-Franch, A.; Moles, M.; Varela, J.; Ramió, H. Vázquez; Alcaniz, J. S.; Dupke, Renato A.; Sodré, L.; Angulo, Raúl E.

doi:10.48550/arxiv.2202.11472

Cited by 4 publications

(4 citation statements)

References 103 publications

(128 reference statements)

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“…This work showcases that accounting for uncertainties can further benefit machine learning algorithms by correcting the data projection and enhancing the distinguishability between groups. Possible applications include the use in multi-band surveys to find stellar clusters in color-color and colour-magnitude diagrams (Chies-Santos et al 2022).…”

Section: Analysis and Discussionmentioning

confidence: 99%

yonder: A python package for data denoising and reconstruction

Chen,

de Souza

2022

Preprint

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We present a standalone implementation of a data-deconvolution method based on singular value decomposition. The tool is written in python and packaged in the open-source yonder package. yonder receives as input two matrices, one for the data and another for the errors, and outputs a denoised version of the original dataset. In this Research Note, we briefly describe the methodology and show a demonstration of the yonder on a simulated dataset.

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Section: Analysis and Discussionmentioning

confidence: 99%

yonder: A python package for data denoising and reconstruction

Chen,

de Souza

2022

Preprint

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“…Harris et al 2020b), in the Fornax cluster (e.g. Chaturvedi et al 2022), and even in the M81/M82/NGC3077 system of galaxies (Chies-Santos et al 2022). When compared to the X-ray surface brightness distribution, the GCs in the Abell 1689 cluster show more substructure (Alamo-Martínez et al 2013), but those in Virgo show a similar distribution to the hot gas (Durrell et al 2014).…”

Section: Introductionmentioning

confidence: 98%

Constraining the shape of dark matter haloes with globular clusters

Reina-Campos¹,

Trujillo-Gomez²,

Pfeffer³

et al. 2022

Preprint

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We explore how diffuse stellar light and globular clusters (GCs) can be used to trace the matter distribution of their host halo using an observational methodology. For this, we use 117 simulated dark matter (DM) haloes from the (34.4 cMpc) 3 periodic volume of the E-MOSAICS project. For each halo, we compare the stellar surface brightness and GC projected number density maps to the surface densities of DM and total mass. We find that the dominant structures identified in the stellar light and in the GCs correspond closely with those from the DM and total mass. Our method is unaffected by the presence of satellites and its precision improves with fainter GC samples. We recover tight relations between the profiles of stellar surface brightness and GC number density to those of the DM, suggesting that the profile of DM can be accurately recovered from the stars and GCs (𝜎 ≤ 0.5 dex). We quantify the projected morphology of DM, stars and GCs, and find that the stars and GCs are more flattened than the DM. Additionally, the semi-major axes of the distribution of stars and GCs are typically misaligned by ∼ 10 degrees from that of DM. We demonstrate that deep imaging of diffuse stellar light and GCs can place constraints on the shape, profile and orientation of their host halo. These results extend down to haloes with central galaxies 𝑀 ★ ≥ 10 10 M , and the analysis will be applicable to future data from the Euclid, Roman and the Rubin observatories

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“…We will show later that this catalogue in particular is extremely contaminated with foreground stars, in great part because the metallicity ([Fe/H] ∼ −1) and low velocities of faint MW halo stars is similar to the metallicity and velocity 𝑣 𝑟 ,𝑀 81 = −34 km/s signatures expected of M81 GC candidates. Finally, a recent study used medium-band data to select 642 candidate GCs in the M81 group (Chies-Santos et al 2022); again, with the scale of this catalogue contamination is highly likely and spectroscopic, multi-wavelength or high-resolution imaging follow-up investigation will be necessary.…”

Section: Introductionmentioning

confidence: 99%

New globular cluster candidates in the M81 group

Pan

Bell

Smercina

et al. 2022

Monthly Notices of the Royal Astronomical Society

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The study of outer halo globular cluster (GC) populations can give insight into galaxy merging, globular cluster accretion and the origin of GCs. We use archival Subaru Hyper Suprime-Cam (HSC) data in concert with space-based GALEX, IRAC and Gaia EDR3 data to select candidate Globular clusters (GCs) in the outer halo of the M81 group for confirmation and future study. We use a small sample of previously-discovered GCs to tune our selection criteria, finding that bright already-known GCs in the M81 group have sizes that are typically slightly larger than the Subaru PSF in our fields. In the optical bands, GCs appear to have colours that are only slightly different from stars. The inclusion of archival IRAC data yields dramatic improvements in colour separation, as the long wavelength baseline aids somewhat in the separation from stars and clearly separates GCs from many compact background galaxies. We show that some previously spectroscopically-identified GCs in the M81 group are instead foreground stars or background galaxies. GCs close to M82 have radial velocities suggesting that they fell into the M81 group along with M82. The overall M81 GC luminosity function is similar to the Milky Way and M31. M81’s outer halo GCs are similar to the Milky Way in their metallicities and numbers, and much less numerous than M31’s more metal-rich outer halo GC population. These properties reflect differences in the three galaxies’ merger histories, highlighting the possibility of using outer halo GCs to trace merger history in larger samples of galaxies.

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J-PLUS: A catalogue of globular cluster candidates around the M81/M82/NGC3077 triplet of galaxies

Cited by 4 publications

References 103 publications

yonder: A python package for data denoising and reconstruction

yonder: A python package for data denoising and reconstruction

Constraining the shape of dark matter haloes with globular clusters

New globular cluster candidates in the M81 group

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