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Register a new userComparing the Properties of GMCs in M33 from Simulations and Observations
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We compare the properties of clouds in simulated M33 galaxies to those observed in the real M33. We apply a friends of friends algorithm and CPROPS to identify clouds, as well as a pixel by pixel analysis. We obtain very good agreement between the number of clouds, and maximum mass of clouds. Both are lower than occurs for a Milky Way-type galaxy and thus are a function of the surface density, size and galactic potential of M33. We reproduce the observed dependence of molecular cloud properties on radius in the simulations, and find this is due to the variation in gas surface density with radius. The cloud spectra also show good agreement between the simulations and observations, but the exact slope and shape of the spectra depends on the algorithm used to find clouds, and the range of cloud masses included when fitting the slope. Properties such as cloud angular momentum, velocity dispersions and virial relation are also in good agreement between the simulations and observations, but do not necessarily distinguish between simulations of M33 and other galaxy simulations. Our results are not strongly dependent on the level of feedback used here (10 and 20%) although they suggest that 15% feedback efficiency may be optimal. Overall our results suggest that the molecular cloud properties are primarily dependent on the gas and mass surface density, and less dependent on the localised physics such as the details of stellar feedback, or the numerical code used.
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We present low frequency observations at $315$ and $745$ MHz from the upgraded Giant Metrewave Radio Telescope (uGMRT) of the edge-on, near-by galaxy NGC 4631. We compare the observed surface brightness profiles along the minor axis of the galaxy with those obtained from hydrodynamical simulations of galactic outflows. We detect a plateau in the emission at a height of $2-3$ kpc from the mid-plane of the galaxy, in qualitative agreement with that expected from simulations. This plateau is believed to be due to the compression of magnetic fields behind the outer shocks of galactic outflows. The estimated scale height for the synchrotron radio emission of $sim 1$ kpc indicates that cosmic ray diffusion plays as much an important role in forming the radio halo as does the advection due to the outflows. The spectral index image with regions of flatter radio spectral index in the halo appears to indicate possible effects of gas outflow from the plane of the galaxy.
Aims. We aim to perform consistent comparisons between observations and simulations on the mass dependence of the galaxy major merger fraction at low redshift over an unprecedentedly wide range of stellar masses (10^9 to 10^12 solar masses). Methods. We first carry out forward modelling of ideal synthetic images of major mergers and non-mergers selected from the Next Generation Illustris Simulations (IllustrisTNG) to include major observational effects. We then train deep convolutional neural networks (CNNs) using realistic mock observations of galaxy samples from the simulations. Subsequently, we apply the trained CNNs to real the Kilo-Degree Survey (KiDS) images of galaxies selected from the Galaxy And Mass Assembly (GAMA) survey. Based on the major merger samples, which are detected in a consistent manner in the observations and simulations, we determine the dependence of major merger fraction on stellar mass at z around 0.15 and make comparisons between the two. Results. The detected major merger fraction in the GAMA/KiDS observations has a fairly mild decreasing trend with increasing stellar mass over the mass range 10^9 < M_sun < M_star < 10^11.5 M_sun. There is good agreement in the mass dependence of the major merger fraction in the GAMA/KiDS observations and the IllustrisTNG simulations over 10^9.5 M_sun < M_star < 10^10.5 M_sun. However, the observations and the simulations show some differences at M_star > 10^10.5M_sun, possibly due to the supermassive blackhole feedback in its low-accretion state in the simulations which causes a sharp transition in the quenched fractions at this mass scale. The discrepancy could also be due to the relatively small volume of the simulations and/or differences in how stellar masses are measured in simulations and observations.
Cosmological hydrodynamical simulations are rich tools to understand the build-up of stellar mass and angular momentum in galaxies, but require some level of calibration to observations. We compare predictions at $zsim0$ from the Eagle, Hydrangea, Horizon-AGN, and Magneticum simulations with integral field spectroscopic (IFS) data from the SAMI Galaxy Survey, ATLAS3D, CALIFA and MASSIVE surveys. The main goal of this work is to simultaneously compare structural, dynamical, and stellar population measurements in order to identify key areas of success and tension. We have taken great care to ensure that our simulated measurement methods match the observational methods as closely as possible. We find that the Eagle and Hydrangea simulations reproduce many galaxy relations but with some offsets at high stellar masses. There are moderate mismatches in $R_e$ (+), $epsilon$ (-), $sigma_e$ (-), and mean stellar age (+), where a plus sign indicates that quantities are too high on average, and minus sign too low. The Horizon-AGN simulations qualitatively reproduce several galaxy relations, but there are a number of properties where we find a quantitative offset to observations. Massive galaxies are better matched to observations than galaxies at low and intermediate masses. Overall, we find mismatches in $R_e$ (+), $epsilon$ (-), $sigma_e$ (-) and $(V/sigma)_e$ (-). Magneticum matches observations well: this is the only simulation where we find ellipticities typical for disk galaxies, but there are moderate differences in $sigma_e$ (-), $(V/sigma)_e$ (-) and mean stellar age (+). Our comparison between simulations and observational data has highlighted several areas for improvement, such as the need for improved modelling resulting in a better vertical disk structure, yet our results demonstrate the vast improvement of cosmological simulations in recent years.
We present a statistical framework to compare spectral-line data cubes of molecular clouds and use the framework to perform an analysis of various statistical tools developed from methods proposed in the literature. We test whether our methods are sensitive to changes in the underlying physical properties of the clouds or whether their behaviour is governed by random fluctuations. We perform a set of 32 self-gravitating magnetohydrodynamic simulations that test all combinations of five physical parameters -- Mach number, plasma parameter, virial parameter, driving scales, and solenoidal driving fraction -- each of which can be set to a low or high value. We create mock observational data sets of ${rm ^{13}CO}$(1-0) emission from each simulation. We compare these mock data to a those generated from a set of baseline simulations using pseudo-distance metrics based on 18 different statistical techniques that have previously been used to study molecular clouds. We analyze these results using methods from the statistical field of experimental design and find that several of the statistics can reliably track changes in the underlying physics. Our analysis shows that the interactions between parameters are often among the most significant effects. A small fraction of statistics are also sensitive to changes in magnetic field properties. We use this framework to compare the set of simulations to observations of three nearby star-forming regions: NGC 1333, Oph A, and IC 348. We find that no one simulation agrees significantly better with the observations, although there is evidence that the high Mach number simulations are more consistent with the observations.
Numerical simulations that reproduce solar-like magnetic cycles can be used to generate long-term statistics. The variations in N-S hemispheric cycle synchronicity and amplitude produced in simulations has not been widely compared to observations. The observed limits on asymmetry show that hemispheric sunspot area production is no more than 20% asymmetric for cycles 12-23 and phase lags do not exceed 20% (2 yrs) of the total cycle period. Independent studies have found a long-term trend in phase values as one hemisphere leads the other for ~four cycles. Such persistence in phase is not indicative of a stochastic phenomenon. We compare the findings to results from a numerical simulation of solar convection recently produced with the EULAG-MHD model. This simulation spans 1600 yrs and generated 40 regular, sunspot-like cycles. While the simulated cycle length is too long and the toroidal bands remain at too high of latitudes, some solar-like aspects of hemispheric asymmetry are reproduced. The model reproduces the synchrony of polarity
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