MIGHTEE-HI: the HI Size-Mass relation over the last billion years

We present the observed HI size-mass relation of $204$ galaxies from the MIGHTEE Survey Early Science data. The high sensitivity of MeerKAT allows us to detect galaxies spanning more than 4 orders of magnitude in HI mass, ranging from dwarf galaxies to massive spirals, and including all morphological types. This is the first time the relation has been explored on a blind homogeneous data set which extends over a previously unexplored redshift range of $0 < z < 0.084$, i.e. a period of around one billion years in cosmic time. The sample follows the same tight logarithmic relation derived from previous work, between the diameter ($D_{\rm HI}$) and the mass ($M_{\rm HI}$) of HI discs. We measure a slope of $0.501\pm 0.008$, an intercept of $-3.252^{+0.073}_{-0.074}$, and an observed scatter of $0.057$ dex. For the first time, we quantify the intrinsic scatter of $0.054 \pm 0.003$ dex (${\sim} 10 \%$), which provides a constraint for cosmological simulations of galaxy formation and evolution. We derive the relation as a function of galaxy type and find that their intrinsic scatters and slopes are consistent within the errors. We also calculate the $D_{\rm HI} - M_{\rm HI}$ relation for two redshift bins and do not find any evidence for evolution with redshift. These results suggest that over a period of one billion years in lookback time, galaxy discs have not undergone significant evolution in their gas distribution and mean surface mass density, indicating a lack of dependence on both morphological type and redshift.Comment: 10 pages, 5 figures, accepted for publication in MNRA

MIGHTEE-HI: The first MeerKAT HI mass function from an untargeted interferometric survey

We present the first measurement of the HI mass function (HIMF) using data from MeerKAT, based on 276 direct detections from the MIGHTEE Survey Early Science data covering a period of approximately a billion years ($0 \leq z \leq 0.084$). This is the first HIMF measured using interferometric data over non-group or cluster field, i.e. a deep blank field. We constrain the parameters of the Schechter function which describes the HIMF with two different methods: $1/\rm V_{\rm max}$ and Modified Maximum Likelihood (MML). We find a low-mass slope $\alpha=-1.29^{+0.37}_{-0.26}$, `knee' mass $\log_{10}(M_{*}/{\rm M_{\odot}}) = 10.07^{+0.24}_{-0.24}$ and normalisation $\log_{10}(\phi_{*}/\rm Mpc^{-3})=-2.34^{+0.32}_{-0.36}$ ($H_0 = 67.4$ kms$^{-1}$ Mpc$^{-1}$) for $1/\rm V_{\rm max}$ and $\alpha=-1.44^{+0.13}_{-0.10}$, `knee' mass $\log_{10}(M_{*}/{\rm M_{\odot}}) = 10.22^{+0.10}_{-0.13}$ and normalisation $\log_{10}(\phi_{*}/\rm Mpc^{-3})=-2.52^{+0.19}_{-0.14}$ for MML. When using $1/\rm V_{\rm max}$ we find both the low-mass slope and `knee' mass to be consistent within $1\sigma$ with previous studies based on single-dish surveys. The cosmological mass density of HI is found to be slightly larger than previously reported: $\Omega_{\rm HI}=5.46^{+0.94}_{-0.99} \times 10^{-4}h^{-1}_{67.4}$ from $1/\rm V_{\rm max}$ and $\Omega_{\rm HI}=6.31^{+0.31}_{-0.31} \times 10^{-4}h^{-1}_{67.4}$ from MML but consistent within the uncertainties. We find no evidence for evolution of the HIMF over the last billion years.Comment: 13 pages, 9 figures, accepted for publication in MNRA

MIGHTEE-Hi: Evolution of Hi Scaling Relations of Star-forming Galaxies at z &lt; 0.5*

We present the first measurements of H I galaxy scaling relations from a blind survey at z > 0.15. We perform spectral stacking of 9023 spectra of star-forming galaxies undetected in H I at 0.23 < z < 0.49, extracted from MIGHTEE-H I Early Science data cubes, acquired with the MeerKAT radio telescope. We stack galaxies in bins of galaxy properties (stellar mass M *, star formation rateSFR, and specific star formation rate sSFR, with sSFR ≡ M */SFR), obtaining ≳5σ detections in most cases, the strongest H I-stacking detections to date in this redshift range. With these detections, we are able to measure scaling relations in the probed redshift interval, finding evidence for a moderate evolution from the median redshift of our sample z med ~ 0.37 to z ~ 0. In particular, low-M * galaxies ( {\mathrm{log}}_{10}({M}_{* }/{M}_{\odot })\sim 9 )experienceastrongHIdepletion( 0.5dexinlog10(MHI/M⊙) ), while massive galaxies ( {\mathrm{log}}_{10}({M}_{* }/{M}_{\odot })\sim 11$ ) keep their H I mass nearly unchanged. When looking at the star formation activity, highly star-forming galaxies evolve significantly in M H I (f H I, where f H I ≡ M H I/M *) at fixed SFR (sSFR), while at the lowest probed SFR (sSFR) the scaling relations show no evolution. These findings suggest a scenario in which low-M * galaxies have experienced a strong H I depletion during the last ~5 Gyr, while massive galaxies have undergone a significant H I replenishment through some accretion mechanism, possibly minor mergers. Interestingly, our results are in good agreement with the predictions of the SIMBA simulation. We conclude that this work sets novel important observational constraints on galaxy scaling relations

Discrete Hidden Markov Models In Kernel Feature Space For Speech Recognition

In this paper we address the issues in construction of discrete hidden Markov models (DHMMs) in the high-dimensional feature space of Mercer kernels. The main issues are clustering and vector quantization in the kernel feature space for a large data set consisting of the data of multiple classes. We propose a method to cluster the multiclass data by clustering the data of dierent classes independently and then merging the similar clusters. Each cluster is represented by a small subset of vectors close to the centre of cluster, leading to signi cant reduction in the computational complexity of vector quantization in the kernel feature space. The proposed methods of clustering and vector quantization are used in building DHMMs in the kernel feature space for recognition of spoken digits and spoken letters in the E-set of English alphabet

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Not AvailableWhile the 21st century has been proclaimed as the age of biology, the disciplines of sub-organismal biology have received greater attention, often at a cost to organismal biology. However, the fields of organismal biology – ecology and evolution – are not only fundamental to biology, but are of societal importance in terms of their application in environmental conservation, sustainability and public health. We argue here that organismal and sub-organismal biology differ substantially in their philosophy and practice: while organismal biology focuses on systems and collectives, sub-organismal biology rests on reductionism. Further, we emphasize that these distinctions must be recognized in institutional and funding structures for organismal biology to fully realize its potentialNot Availabl