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Ultralight axions and other bosons are dark matter candidates present in many high energy physics theories beyond the Standard Model. In particular, the string axiverse postulates the existence of up to $\mathcal{O}(100)$ light scalar bosons constituting the dark sector. Considering a mixture of axions and cold dark matter, we obtain upper bounds for the axion relic density $\Omega_a h^2 < 0.004$ for axions of mass $10^{-31}\;\mathrm{eV}\leq m_a \leq 10^{-26}\;\mathrm{eV}$ at 95% confidence. We also improve existing constraints by a factor of over 4.5 and 2.1 for axion masses of $10^{-25}$ eV and $10^{-32}$ eV, respectively. We use the Fourier-space galaxy clustering statistics from the Baryon Oscillation Spectroscopic Survey (BOSS) and demonstrate how galaxy surveys break important degeneracies in the axion parameter space compared to the cosmic microwave background (CMB). We test the validity of the effective field theory of large-scale structure approach to mixed ultralight axion dark matter by making our own mock galaxy catalogs and find an anisotropic ultralight axion signature in the galaxy quadrupole. We also observe an enhancement of the linear galaxy bias from 1.8 to 2.4 when allowing for 5% of the dark matter to be composed of a $10^{-28}$ eV axion in our simulations. Finally, we develop an augmented interpolation scheme allowing a fast computation of the axion contribution to the linear matter power spectrum leading to a 70% reduction of the computational cost for the full Monte Carlo Markov chains analysis., Comment: Updated references

(Abridged from Executive Summary) This white paper focuses on the interdisciplinary fields of astrostatistics and astroinformatics, in which modern statistical and computational methods are applied to and developed for astronomical data. Astrostatistics and astroinformatics have grown dramatically in the past ten years, with international organizations, societies, conferences, workshops, and summer schools becoming the norm. Canada's formal role in astrostatistics and astroinformatics has been relatively limited, but there is a great opportunity and necessity for growth in this area. We conducted a survey of astronomers in Canada to gain information on the training mechanisms through which we learn statistical methods and to identify areas for improvement. In general, the results of our survey indicate that while astronomers see statistical methods as critically important for their research, they lack focused training in this area and wish they had received more formal training during all stages of education and professional development. These findings inform our recommendations for the LRP2020 on how to increase interdisciplinary connections between astronomy and statistics at the institutional, national, and international levels over the next ten years. We recommend specific, actionable ways to increase these connections, and discuss how interdisciplinary work can benefit not only research but also astronomy's role in training Highly Qualified Personnel (HQP) in Canada., White paper E017 submitted to the Canadian Long Range Plan LRP2020

In the next few years, the 21cm line will enable direct observations of the Dark Ages, Cosmic Dawn, and Reionization, which represent previously unexplored periods in our cosmic history. With a combination of sky-averaged global signal measurements and spatial mapping surveys, the possible science return is enormous. This potentially includes (but is not limited to) constraints on first-generation galaxies (such as their typical masses and luminosities), constraints on cosmological parameters, a measurement of the Hubble parameter at z~15 to 20, the elimination of the optical depth nuisance parameter in the CMB, and searches for exotic phenomena such as baryon-dark matter couplings. To enable continued Canadian leadership in these science opportunities, we recommend 1) continued investments in 21cm experiments at all redshifts, 2) detailed analysis efforts of current data to overcome systematic effects, 3) new investments in preliminary experiments to explore the truly low-frequency sky as a stepping stone towards the Dark Ages, 4) new investments in line-intensity mapping experiments beyond the 21cm line, 5) continued theory support for 21cm cosmology, and 6) continued participation and knowledge transfer to next-generation international efforts such as the Square Kilometre Array., White paper submitted to Canadian 2020 Long Range Plan committee

The era of data-intensive astronomy is being ushered in with the increasing size and complexity of observational data across wavelength and time domains, the development of algorithms to extract information from this complexity, and the computational power to apply these algorithms to the growing repositories of data. Data-intensive approaches are pushing the boundaries of nearly all fields of astronomy, from exoplanet science to cosmology, and they are becoming a critical modality for how we understand the universe. The success of these approaches range from the discovery of rare or unexpected phenomena, to characterizing processes that are now accessible with precision astrophysics and a deep statistical understanding of the datasets, to developing algorithms that maximize the science that can be extracted from any set of observations. In this white paper, we propose a number of initiatives to maximize Canada's ability to compete in this data-intensive era. We propose joining international collaborations and leveraging Canadian facilities for legacy data potential. We propose continuing to build a more agile computing infrastructure that's responsive to the needs of tackling larger and more complex data, as well as enabling quick prototyping and scaling of algorithms. We recognize that developing the fundamental skills of the field will be critical for Canadian astronomers, and discuss avenues through with the appropriate computational and statistical training could occur. Finally, we note that the transition to data-intensive techniques is not limited to astronomy, and we should coordinate with other disciplines to develop and make use of best practises in methods, infrastructure, and education., A white paper submitted for consideration for the Canadian Long Range Plan 2020 (E075)

Community access to deep (i ~ 25), highly-multiplexed optical and near-infrared multi-object spectroscopy (MOS) on 8-40m telescopes would greatly improve measurements of cosmological parameters from LSST. The largest gain would come from improvements to LSST photometric redshifts, which are employed directly or indirectly for every major LSST cosmological probe; deep spectroscopic datasets will enable reduced uncertainties in the redshifts of individual objects via optimized training. Such spectroscopy will also determine the relationship of galaxy SEDs to their environments, key observables for studies of galaxy evolution. The resulting data will also constrain the impact of blending on photo-z's. Focused spectroscopic campaigns can also improve weak lensing cosmology by constraining the intrinsic alignments between the orientations of galaxies. Galaxy cluster studies can be enhanced by measuring motions of galaxies in and around clusters and by testing photo-z performance in regions of high density. Photometric redshift and intrinsic alignment studies are best-suited to instruments on large-aperture telescopes with wider fields of view (e.g., Subaru/PFS, MSE, or GMT/MANIFEST) but cluster investigations can be pursued with smaller-field instruments (e.g., Gemini/GMOS, Keck/DEIMOS, or TMT/WFOS), so deep MOS work can be distributed amongst a variety of telescopes. However, community access to large amounts of nights for surveys will still be needed to accomplish this work. In two companion white papers we present gains from shallower, wide-area MOS and from single-target imaging and spectroscopy., Science white paper submitted to the Astro2020 decadal survey. A table of time requirements is available at http://d-scholarship.pitt.edu/36036/

The expansion of the Universe is understood to have accelerated during two epochs: in its very first moments during a period of Inflation and much more recently, at $z < 1$, when Dark Energy is hypothesized to drive cosmic acceleration. The undiscovered mechanisms behind these two epochs represent some of the most important open problems in fundamental physics. The large cosmological volume at $2 < z < 5$, together with the ability to efficiently target high-$z$ galaxies with known techniques, enables large gains in the study of Inflation and Dark Energy. A future spectroscopic survey can test the Gaussianity of the initial conditions up to a factor of ~50 better than our current bounds, crossing the crucial theoretical threshold of $��(f_{NL}^{\rm local})$ of order unity that separates single field and multi-field models. Simultaneously, it can measure the fraction of Dark Energy at the percent level up to $z = 5$, thus serving as an unprecedented test of the standard model and opening up a tremendous discovery space., Science white paper submitted to the Astro2020 Decadal Survey

We review the measurements of dark energy enabled by observations of the Deep Drilling Fields and the optimization of survey design for cosmological measurements. This white paper is the result of efforts by the LSST DESC Observing Strategy Task Force (OSTF), which represents the entire collaboration, and aims to make recommendations on observing strategy for the DDFs that will benefit all cosmological analyses with LSST. It is accompanied by the DESC-WFD white paper (Lochner et al.). We argue for altering the nominal deep drilling plan to have $>6$ month seasons, interweaving $gri$ and $zy$ observations every 3 days with 2, 4, 8, 25, 4 visits in $grizy$, respectively. These recommendations are guided by metrics optimizing constraints on dark energy and mitigation of systematic uncertainties, including specific requirements on total number of visits after Y1 and Y10 for photometric redshifts (photo-$z$) and weak lensing systematics. We specify the precise locations for the previously-chosen LSST deep fields (ELAIS-S1, XMM-LSS, CDF-S, and COSMOS) and recommend Akari Deep Field South as the planned fifth deep field in order to synergize with Euclid and WFIRST. Our recommended DDF strategy uses $6.2\%$ of the LSST survey time. We briefly discuss synergy with white papers from other collaborations, as well as additional mini-surveys and Target-of-Opportunity programs that lead to better measurements of dark energy., The LSST DESC response (DDF) to the Call for White Papers on LSST Cadence Optimization. Comments welcome

The Photometric LSST Astronomical Time Series Classification Challenge (PLAsTiCC) is an open data challenge to classify simulated astronomical time-series data in preparation for observations from the Large Synoptic Survey Telescope (LSST), which will achieve first light in 2019 and commence its 10-year main survey in 2022. LSST will revolutionize our understanding of the changing sky, discovering and measuring millions of time-varying objects. In this challenge, we pose the question: how well can we classify objects in the sky that vary in brightness from simulated LSST time-series data, with all its challenges of non-representativity? In this note we explain the need for a data challenge to help classify such astronomical sources and describe the PLAsTiCC data set and Kaggle data challenge, noting that while the references are provided for context, they are not needed to participate in the challenge., Research note to accompany the https://www.kaggle.com/c/PLAsTiCC-2018 challenge

The Large Synoptic Survey Telescope (LSST) Dark Energy Science Collaboration (DESC) will use five cosmological probes: galaxy clusters, large scale structure, supernovae, strong lensing, and weak lensing. This Science Requirements Document (SRD) quantifies the expected dark energy constraining power of these probes individually and together, with conservative assumptions about analysis methodology and follow-up observational resources based on our current understanding and the expected evolution within the field in the coming years. We then define requirements on analysis pipelines that will enable us to achieve our goal of carrying out a dark energy analysis consistent with the Dark Energy Task Force definition of a Stage IV dark energy experiment. This is achieved through a forecasting process that incorporates the flowdown to detailed requirements on multiple sources of systematic uncertainty. Future versions of this document will include evolution in our software capabilities and analysis plans along with updates to the LSST survey strategy., 32 pages + 60 pages of appendices. This is v1.0.2 of the DESC SRD, an internal collaboration document that is being made public and is not planned for submission to a journal. Data products for reproducing key plots are available on Zenodo, https://doi.org/10.5281/zenodo.1409815 ; see "Executive Summary and User Guide" for how to use and cite those products