ترغب بنشر مسار تعليمي؟ اضغط هنا

Shapes and alignments of dark matter haloes and their brightest cluster galaxies in 39 strong lensing clusters

84   0   0.0 ( 0 )
 نشر من قبل Taizo Okabe
 تاريخ النشر 2020
  مجال البحث فيزياء
والبحث باللغة English




اسأل ChatGPT حول البحث

We study shapes and alignments of 45 dark matter (DM) haloes and their brightest cluster galaxies (BCGs) using a sample of 39 massive clusters from Hubble Frontier Field (HFF), Cluster Lensing And Supernova survey with Hubble (CLASH), and Reionization Lensing Cluster Survey (RELICS). We measure shapes of the DM haloes by strong gravitational lensing, whereas BCG shapes are derived from their light profiles in Hubble Space Telescope images. Our measurements from a large sample of massive clusters presented here provide new constraints on dark matter and cluster astrophysics. We find that DM haloes are on average highly elongated with the mean ellipticity of $0.482pm 0.028$, and position angles of major axes of DM haloes and their BCGs tend to be aligned well with the mean value of alignment angles of $22.2pm 3.9$ deg. We find that DM haloes in our sample are on average more elongated than their BCGs with the mean difference of their ellipticities of $0.11pm 0.03$. In contrast, the Horizon-AGN cosmological hydrodynamical simulation predicts on average similar ellipticities between DM haloes and their central galaxies. While such a difference between the observations and the simulation may well be explained by the difference of their halo mass scales, other possibilities include the bias inherent to strong lensing measurements, limited knowledge of baryon physics, or a limitation of cold dark matter.



قيم البحث

اقرأ أيضاً

81 - Qiuhan He , Ran Li , Sungsoon Lim 2017
Small distortions in the images of Einstein rings or giant arcs offer the exciting prospect of detecting dark matter haloes or subhaloes of mass below $10^9$M$_{odot}$, most of which are too small to have made a visible galaxy. A very large number of such haloes are predicted to exist in the cold dark matter model of cosmogony; in contrast other models, such as warm dark matter, predict no haloes below a mass of this order which depends on the properties of the warm dark matter particle. Attempting to detect these small perturbers could therefore discriminate between different kinds of dark matter particles, and even rule out the cold dark matter model altogether. Globular clusters in the lens galaxy also induce distortions in the image which could, in principle, contaminate the test. Here, we investigate the population of globular clusters in six early type galaxies in the Virgo cluster. We find that the number density of globular clusters of mass $sim10^6$M$_{odot}$ is comparable to that of the dark matter perturbers (including subhaloes in the lens and haloes along the line-of-sight). We show that the very different degrees of mass concentration in globular clusters and dark matter haloes result in different lensing distortions. These are detectable with milli-arcsecond resolution imaging which can distinguish between globular cluster and dark matter halo signals.
It is known observationally that the major axes of galaxy clusters and their brightest cluster galaxies are roughly aligned with each other. To understand the origin of the alignment, we identify 40 cluster-sized dark matter (DM) haloes with masses h igher than $5times10^{13}~M_{odot}$ and their central galaxies (CGs) at $zapprox 0$ in the Horizon-AGN cosmological hydrodynamical simulation. We trace the progenitors at 50 different epochs between $0<z<5$. We then fit their shapes and orientations with a triaxial ellipsoid model. While the orientations of both DM haloes and CGs change significantly due to repeated mergers and mass accretions, their relative orientations are well aligned at each epoch even at high redshifts, $z>1$. The alignment becomes tighter with cosmic time; the major axes of the CGs and their host DM haloes at present are aligned on average within $sim 30^{circ}$ in the three dimensional space and $sim 20^{circ}$ in the projected plane. The orientations of the major axes of DM haloes on average follow one of the eigen-vectors of the surrounding tidal field that corresponds to the {it slowest collapsing} (or even stretching) mode, and the alignment with the tidal field also becomes tighter. This implies that the orientations of CGs and DM haloes at the present epoch are largely imprinted in the primordial density field of the Universe, whereas strong dynamical interactions such as mergers are important to explain their mutual alignment at each epoch.
We compare the shapes and intrinsic alignments of galaxies in the MassiveBlack-II cosmological hydrodynamic simulation (MBII) to those in a dark matter-only (DMO) simulation performed with the same volume (100$h^{-1}$Mpc)$^{3}$, cosmological paramete rs, and initial conditions. Understanding the impact of baryonic physics on galaxy shapes and alignments and their relation to the dark matter distribution should prove useful to map the intrinsic alignments of galaxies from hydrodynamic to dark matter-only simulations. We find that dark matter subhalos are typically rounder in MBII, and the shapes of stellar matter in low mass galaxies are more misaligned with the shapes of the dark matter of the corresponding subhalos in the DMO simulation. At $z=0.06$, the fractional difference in the mean misalignment angle between MBII and DMO simulations varies from $sim 28 % - 12 %$ in the mass range $10^{10.8} - 6.0 times 10^{14} h^{-1}M_{odot}$. We study the dark matter halo shapes and alignments as a function of radius, and find that while galaxies in MBII are more aligned with the inner parts of their dark matter subhalos, there is no radial trend in their alignments with the corresponding subhalo in the DMO simulation. This result highlights the importance of baryonic physics in determining the alignment of the galaxy with respect to the inner parts of the halo. Finally, we compare the ellipticity-direction (ED) correlation for galaxies to that for dark matter halos, finding that it is suppressed on all scales by stellar-dark matter misalignment. In the projected shape-density correlation ($w_{delta+}$), which includes ellipticity weighting, this effect is partially canceled by the higher mean ellipticities of the stellar component, but differences of order $30-40%$ remain on scales $> 1$ Mpc over a range of subhalo masses, with scale-dependent effects below $1$ Mpc.
Galaxy-galaxy weak lensing is a direct probe of the mean matter distribution around galaxies. The depth and sky coverage of the CFHT Legacy Survey yield statistically significant galaxy halo mass measurements over a much wider range of stellar masses ($10^{8.75}$ to $10^{11.3} M_{odot}$) and redshifts ($0.2 < z < 0.8$) than previous weak lensing studies. At redshift $z sim 0.5$, the stellar-to-halo mass ratio (SHMR) reaches a maximum of $4.0pm0.2$ percent as a function of halo mass at $sim 10^{12.25} M_{odot}$. We find, for the first time from weak lensing alone, evidence for significant evolution in the SHMR: the peak ratio falls as a function of cosmic time from $4.5 pm 0.3$ percent at $z sim 0.7$ to $3.4 pm 0.2$ percent at $z sim 0.3$, and shifts to lower stellar mass haloes. These evolutionary trends are dominated by red galaxies, and are consistent with a model in which the stellar mass above which star formation is quenched downsizes with cosmic time. In contrast, the SHMR of blue, star-forming galaxies is well-fit by a power law that does not evolve with time. This suggests that blue galaxies form stars at a rate that is balanced with their dark matter accretion in such a way that they evolve along the SHMR locus. The redshift dependence of the SHMR can be used to constrain the evolution of the galaxy population over cosmic time.
We investigate the possibility of applying machine learning techniques to images of strongly lensed galaxies to detect a low mass cut-off in the spectrum of dark matter sub-halos within the lens system. We generate lensed images of systems containing substructure in seven different categories corresponding to lower mass cut-offs ranging from $10^9M_odot$ down to $10^6M_odot$. We use convolutional neural networks to perform a multi-classification sorting of these images and see that the algorithm is able to correctly identify the lower mass cut-off within an order of magnitude to better than 93% accuracy.
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا