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Massive galaxies evolve through different phases including starburst-dominated and active galactic nuclei (AGN)-dominated phases. These phases are predicted to be prevalent at earlier times (z ∼ 2 − 3). In this thesis I present high-sensitivity observations from the Atacama Large Millimeter/submillimeter Array to investigate mid-J (Jupper = 4 and 5) CO emission in nine Wide-field Infrared Survey Explorer-selected hyperluminous, hot dust-obscured galaxies (Hot DOGs). These sources are thought to represent a transition phase between starburst- and AGN-dominated galaxies at z ≈ 2.5 − 5. All nine sources are detected in continuum and line emission. I conclude that the sources are gas-rich with Mgas ≈ 1010−11 M . Previous far-infrared spectral energy distribution decomposition revealed that six of the sources have significant cold dust components suggesting high star-formation rates (SFR ≈ 2000 − 9000 M yr−1 ). The molecular gas in the sources is shown to follow roughly the same star-formation trend as a smaller sample of Hot DOGs and other populations of star-forming and quasar-host galaxies at low- and high-redshift. The resolved CO emission line data displays large velocity dispersions (FWHM ≈ 400 − 900 km s−1 ) consistent with other high-z star-forming and quasar-host galaxies. For a subset of the sources, the line data shows disturbed morphologies and velocity gradients possibly consistent with rotation or galaxy interaction. The results from this analysis suggest that the studied sources are heavily dust-obscured quasars undergoing extreme starburst episodes. The estimated gas and dynamical masses of the sources are consistent with other populations of massive galaxies at low- and high-z, indicating that they likely represent a stage in the evolution of massive galaxies., Presentaiton given over zoom platform during COVID-19 pandemic.

Massive galaxies evolve through different phases including starburst-dominated and active galactic nuclei (AGN)-dominated phases. These phases are predicted to be prevalent at earlier times (z ∼ 2 − 3). In this thesis I present high-sensitivity observations from the Atacama Large Millimeter/submillimeter Array to investigate mid-J (Jupper = 4 and 5) CO emission in nine Wide-field Infrared Survey Explorer-selected hyperluminous, hot dust-obscured galaxies (Hot DOGs). These sources are thought to represent a transition phase between starburst- and AGN-dominated galaxies at z ≈ 2.5 − 5. All nine sources are detected in continuum and line emission. I conclude that the sources are gas-rich with Mgas ≈ 1010−11 M . Previous far-infrared spectral energy distribution decomposition revealed that six of the sources have significant cold dust components suggesting high star-formation rates (SFR ≈ 2000 − 9000 M yr−1 ). The molecular gas in the sources is shown to follow roughly the same star-formation trend as a smaller sample of Hot DOGs and other populations of star-forming and quasar-host galaxies at low- and high-redshift. The resolved CO emission line data displays large velocity dispersions (FWHM ≈ 400 − 900 km s−1 ) consistent with other high-z star-forming and quasar-host galaxies. For a subset of the sources, the line data shows disturbed morphologies and velocity gradients possibly consistent with rotation or galaxy interaction. The results from this analysis suggest that the studied sources are heavily dust-obscured quasars undergoing extreme starburst episodes. The estimated gas and dynamical masses of the sources are consistent with other populations of massive galaxies at low- and high-z, indicating that they likely represent a stage in the evolution of massive galaxies., Presentaiton given over zoom platform during COVID-19 pandemic.

Whether any OB stars form in isolation is a question central to theories of massive star formation. To address this, we search for tiny, sparse clusters around 210 field OB stars in the Small Magellanic Cloud (SMC) from the Runaways and Isolated O-Type Star Spectroscopic Survey of the SMC (RIOTS4), using friends-of-friends and nearest neighbors algorithms. We also stack the target fields to evaluate the presence of an aggregate density enhancement. Using several statistical tests, we compare these observations with three random-field data sets, and we also compare the known runaways to nonrunaways. We find that the local environments of nonrunaways show higher aggregate central densities than for runaways, implying the presence of some "tips of icebergs" (TIB) clusters. We find that the frequency of these tiny clusters is low, similar to 4%-5% of our sample. This fraction is much lower than some previous estimates, but is consistent with field OB stars being almost entirely runaway and walkaway stars. The lack of TIB clusters implies that such objects either evaporate on short timescales or do not form, implying a higher cluster lower-mass limit and consistent with a relationship between maximum stellar mass (m(max)) and the mass of the cluster (M-cl). On the other hand, we also cannot rule out that some OB stars may form in highly isolated conditions. Our results set strong constraints on the formation of massive stars in relative isolation.

The aim of this analysis was to determine whether or not the given error bars truly represented the dispersion of values in a historical compilation of two cosmological parameters: the amplitude of mass fluctuations (sigma(8)) and Hubble's constant (H-0) parameters in the standard cosmological model. For this analysis, a chi-squared test was executed on a compiled list of past measurements. It was found through analysis of the chi-squared (chi(2)) values of the data that for sigma(8)(60 data points measured between 1993 and 2019 and chi(2) between 182.4 and 189.0) the associated probability Q is extremely low, with Q = 1.6 x 10(-15) for the weighted average and Q = 8.8 x 10(-15) for the best linear fit of the data. This was also the case for the chi(2) values of H-0(163 data points measured between 1976 and 2019 and chi(2) between 480.1 and 575.7), where Q = 1.8 x 10(-33) for the linear fit of the data and Q = 1.0 x 10(-47) for the weighted average of the data. The general conclusion was that the statistical error bars associated with the observed parameter measurements have been underestimated or the systematic errors were not properly taken into account in at least 20% of the measurements. The fact that the underestimation of error bars for H-0 is so common might explain the apparent 4.4 sigma discrepancy formally known today as the Hubble tension.

The aim of this analysis was to determine whether or not the given error bars truly represented the dispersion of values in a historical compilation of two cosmological parameters: the amplitude of mass fluctuations (sigma(8)) and Hubble's constant (H-0) parameters in the standard cosmological model. For this analysis, a chi-squared test was executed on a compiled list of past measurements. It was found through analysis of the chi-squared (chi(2)) values of the data that for sigma(8)(60 data points measured between 1993 and 2019 and chi(2) between 182.4 and 189.0) the associated probability Q is extremely low, with Q = 1.6 x 10(-15) for the weighted average and Q = 8.8 x 10(-15) for the best linear fit of the data. This was also the case for the chi(2) values of H-0(163 data points measured between 1976 and 2019 and chi(2) between 480.1 and 575.7), where Q = 1.8 x 10(-33) for the linear fit of the data and Q = 1.0 x 10(-47) for the weighted average of the data. The general conclusion was that the statistical error bars associated with the observed parameter measurements have been underestimated or the systematic errors were not properly taken into account in at least 20% of the measurements. The fact that the underestimation of error bars for H-0 is so common might explain the apparent 4.4 sigma discrepancy formally known today as the Hubble tension.

The aim of this analysis was to determine whether or not the given error bars truly represented the dispersion of values in a historical compilation of two cosmological parameters: the amplitude of mass fluctuations (sigma(8)) and Hubble's constant (H-0) parameters in the standard cosmological model. For this analysis, a chi-squared test was executed on a compiled list of past measurements. It was found through analysis of the chi-squared (chi(2)) values of the data that for sigma(8)(60 data points measured between 1993 and 2019 and chi(2) between 182.4 and 189.0) the associated probability Q is extremely low, with Q = 1.6 x 10(-15) for the weighted average and Q = 8.8 x 10(-15) for the best linear fit of the data. This was also the case for the chi(2) values of H-0(163 data points measured between 1976 and 2019 and chi(2) between 480.1 and 575.7), where Q = 1.8 x 10(-33) for the linear fit of the data and Q = 1.0 x 10(-47) for the weighted average of the data. The general conclusion was that the statistical error bars associated with the observed parameter measurements have been underestimated or the systematic errors were not properly taken into account in at least 20% of the measurements. The fact that the underestimation of error bars for H-0 is so common might explain the apparent 4.4 sigma discrepancy formally known today as the Hubble tension.

As a result of the standardizability of SNe Ia light curves over a wide range of photometric bands, they are used as standard candles to accurately measure distances in the cosmos up to z ≈ 1 [22]. As dust extinction is smaller in the NIR than in the optical [21] there is less dispersion seen in the peak brightnesses of SNe Ia, making them truly standard candles. We use SNPY to fit light curves for 192 SNe Ia. The mean of all Hubble residuals of our sample is ≈ 0.101 mag with a standard deviation of ≈ 0.234 mag. After applying an original set of cuts, the mean of 173 Hubble residuals reduces to ≈ 0.080 mag with a standard deviation of 0.203 mag. We next estimate host galaxy stellar masses of 175 SNe. From our sample we detect a 0.039 ± 0.026 mag (1−2σ) mass-step. For reasons outlined in section 4.1.1 and 4.1.2 respectively, we increase our sBV cut to sBV > 0.8 and decrease our extinction cut to E(B −V ) ≤ 0.2 mag to see the mass step disappear entirely (0.004 ± 0.034 mag). Fast-declining SNe occur with preference in high-mass galaxies, possibly pointing to an intrinsic contribution to this mass step [22]. As NIR data is seen to significantly reduce the 3−4σ [14] mass-step detected with optical data, it is concluded that extinction likely plays a large role in the mass-step, as proposed in Brout & Scolnic 2020 [2]., Presentation given over zoom due to the COVID-19 crisis.

The aim of this analysis was to determine whether or not the given error bars truly represented the dispersion of values in a historical compilation of two cosmological parameters: the amplitude of mass fluctuations (sigma(8)) and Hubble's constant (H-0) parameters in the standard cosmological model. For this analysis, a chi-squared test was executed on a compiled list of past measurements. It was found through analysis of the chi-squared (chi(2)) values of the data that for sigma(8)(60 data points measured between 1993 and 2019 and chi(2) between 182.4 and 189.0) the associated probability Q is extremely low, with Q = 1.6 x 10(-15) for the weighted average and Q = 8.8 x 10(-15) for the best linear fit of the data. This was also the case for the chi(2) values of H-0(163 data points measured between 1976 and 2019 and chi(2) between 480.1 and 575.7), where Q = 1.8 x 10(-33) for the linear fit of the data and Q = 1.0 x 10(-47) for the weighted average of the data. The general conclusion was that the statistical error bars associated with the observed parameter measurements have been underestimated or the systematic errors were not properly taken into account in at least 20% of the measurements. The fact that the underestimation of error bars for H-0 is so common might explain the apparent 4.4 sigma discrepancy formally known today as the Hubble tension.

Whether any OB stars form in isolation is a question central to theories of massive star formation. To address this, we search for tiny, sparse clusters around 210 field OB stars from the Runaways and Isolated O-Type Star Spectroscopic Survey of the SMC (RIOTS4), using friends-of-friends (FOF) and nearest neighbors (NN) algorithms. We also stack the target fields to evaluate the presence of an aggregate density enhancement. Using several statistical tests, we compare these observations with three random-field datasets, and we also compare the known runaways to non-runaways. We find that the local environments of non-runaways show higher aggregate central densities than for runaways, implying the presence of some "tips-of-iceberg" (TIB) clusters. We find that the frequency of these tiny clusters is low, $\sim 4-5\%$ of our sample. This fraction is much lower than some previous estimates, but is consistent with field OB stars being almost entirely runaway and walkaway stars. The lack of TIB clusters implies that such objects either evaporate on short timescales, or do not form, implying a higher cluster lower-mass limit and consistent with a relationship between maximum stellar mass ($m_{\rm max}$) and the mass of the cluster ($M_{\rm cl}$). On the other hand, we also cannot rule out that some OB stars may form in highly isolated conditions. Our results set strong constraints on the formation of massive stars in relative isolation., Comment: 24 pages, 13 figures, Accepted to ApJ

The aim of this analysis was to determine whether or not the given error bars truly represented the dispersion of values in a historical compilation of two cosmological parameters: the amplitude of mass fluctuations ($\sigma_8$) and Hubble's constant ($H_0$) parameters in the standard cosmological model. For this analysis, a chi-squared test was executed on a compiled list of past measurements. It was found through analysis of the chi-squared ($\chi^2$) values of the data that for $\sigma_8$ (60 data points measured between 1993 and 2019 and $\chi^2$ between 182.4 and 189.0) the associated probability Q is extremely low, with $Q = 1.6 \times 10^{-15}$ for the weighted average and $Q = 8.8 \times 10^{-15}$ for the best linear fit of the data. This was also the case for the $\chi^2$ values of $H_0$ (163 data points measured between 1976 and 2019 and $\chi^2$ between 480.1 and 575.7), where $Q = 1.8 \times 10^{-33}$ for the linear fit of the data and $Q = 1.0 \times 10^{-47}$ for the weighted average of the data. The general conclusion was that the statistical error bars associated with the observed parameter measurements have been underestimated or the systematic errors were not properly taken into account in at least 20\% of the measurements. The~fact that the underestimation of error bars for $H_0$ is so common might explain the apparent 4.4$\sigma$ discrepancy formally known today as the Hubble tension., Comment: 21 pages, 5 figures, published in Universe, special issue 5th anniversary

The aim of this analysis was to determine whether or not the given error bars truly represented the dispersion of values in a historical compilation of two cosmological parameters: the amplitude of mass fluctuations (sigma(8)) and Hubble's constant (H-0) parameters in the standard cosmological model. For this analysis, a chi-squared test was executed on a compiled list of past measurements. It was found through analysis of the chi-squared (chi(2)) values of the data that for sigma(8)(60 data points measured between 1993 and 2019 and chi(2) between 182.4 and 189.0) the associated probability Q is extremely low, with Q = 1.6 x 10(-15) for the weighted average and Q = 8.8 x 10(-15) for the best linear fit of the data. This was also the case for the chi(2) values of H-0(163 data points measured between 1976 and 2019 and chi(2) between 480.1 and 575.7), where Q = 1.8 x 10(-33) for the linear fit of the data and Q = 1.0 x 10(-47) for the weighted average of the data. The general conclusion was that the statistical error bars associated with the observed parameter measurements have been underestimated or the systematic errors were not properly taken into account in at least 20% of the measurements. The fact that the underestimation of error bars for H-0 is so common might explain the apparent 4.4 sigma discrepancy formally known today as the Hubble tension.

For this project, a historical statistical analysis of the Amplitude of Mass Fluctuations ($\sigma_8$) and Hubble's Constant ($H_0$) parameters in the Standard Cosmological Model was carried out to determine whether or not the given error bars truly represent the dispersion of values. It was found through analysis of the Chi-Squared ($\chi^2$) values of the data that for $\sigma_8$ (60 data points and $\chi^2$ between 183.167 and 189.037) that the associated probability Q is extremely low, with $Q = 1.5597*10^{-15}$ for the weighted average and $Q = 1.2107*10^{-14}$ for the best fit of the data. This was also the case for the $\chi^2$ values (163 data points and $\chi^2$ between 484.3977 and 575.655) of $H_0$, where $Q = 4.2176*10^{-34}$ for the linear fit of the data and $Q = 1.0342*10^{-47}$ for the weighted average of the data. Through further analysis, it is shown in question, a linear fit is a better estimate of the data than the weighted average. The general conclusion is that the statistical error bars have been underestimated (in around 20\% of the measurements), or the systematic errors were not properly taken into account.

For this project, a historical statistical analysis of the Amplitude of Mass Fluctuations ($\sigma_8$) and Hubble's Constant ($H_0$) parameters in the Standard Cosmological Model was carried out to determine whether or not the given error bars truly represent the dispersion of values. It was found through analysis of the Chi-Squared ($\chi^2$) values of the data that for $\sigma_8$ (60 data points and $\chi^2$ between 183.167 and 189.037) that the associated probability Q is extremely low, with $Q = 1.5597*10^{-15}$ for the weighted average and $Q = 1.2107*10^{-14}$ for the best fit of the data. This was also the case for the $\chi^2$ values (163 data points and $\chi^2$ between 484.3977 and 575.655) of $H_0$, where $Q = 4.2176*10^{-34}$ for the linear fit of the data and $Q = 1.0342*10^{-47}$ for the weighted average of the data. Through further analysis, it is shown in question, a linear fit is a better estimate of the data than the weighted average. The general conclusion is that the statistical error bars have been underestimated (in around 20\% of the measurements), or the systematic errors were not properly taken into account.