Publications

Studying the formation and evolution of galaxies at the earliest cosmic times, and their role in reionization, requires the deepest imaging possible. Ultra-deep surveys like the HUDF and HFF have pushed to mag \mAB∼30, revealing galaxies at the faint end of the LF to z∼9−11 and constraining their role in reionization. However, a key limitation of these fields is their size, only a few arcminutes (less than a Mpc at these redshifts), too small to probe large-scale environments or clustering properties of these galaxies, crucial for advancing our understanding of reionization. Achieving HUDF-quality depth over areas ∼100 times larger becomes possible with a mission like the Wide Field Infrared Survey Telescope (WFIRST), a 2.4-m telescope with similar optical properties to HST, with a field of view of ∼1000 arcmin2, ∼100× the area of the HST/ACS HUDF.
This whitepaper motivates an Ultra-Deep Field survey with WFIRST, covering ∼100−300× the area of the HUDF, or up to ∼1 deg2, to \mAB∼30, potentially revealing thousands of galaxies and AGN at the faint end of the LF, at or beyond z\,∼\,9−10 in the epoch of reionization, and tracing their LSS environments, dramatically increasing the discovery potential at these redshifts.
(Note: This paper is a somewhat expanded version of one that was submitted as input to the Astro2020 Decadal Survey, with this version including an Appendix (which exceeded the Astro2020 page limits), describing how the science drivers for a WFIRST Ultra Deep Field might map into a notional observing program, including the filters used and exposure times needed to achieve these depths.)

Asteroseismology is the only observational tool in astronomy that can probe the interiors of stars, and is a benchmark method for deriving fundamental properties of stars and exoplanets. Over the coming decade, space-based and ground-based observations will provide a several order of magnitude increase of solar-like oscillators, as well as a dramatic increase in the number and quality of classical pulsator observations, providing unprecedented possibilities to study stellar physics and galactic stellar populations. In this white paper, we describe key science questions and necessary facilities to continue the asteroseismology revolution into the 2020's.

The bond dissociation energies of a set of 44 3d transition metal-containing diatomics are computed with phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC) utilizing a correlated sampling technique. We investigate molecules with H, N, O, F, Cl, and S ligands, including those in the 3dMLBE20 database first compiled by Truhlar and co-workers with calculated and experimental values that have since been revised by various groups. In order to make a direct comparison of the accuracy of our ph-AFQMC calculations with previously published results from 10 DFT functionals, CCSD(T), and icMR-CCSD(T), we establish an objective selection protocol which utilizes the most recent experimental results except for a few cases with well-specified discrepancies. With the remaining set of 41 molecules, we find that ph-AFQMC gives robust agreement with experiment superior to that of all other methods, with a mean absolute error (MAE) of 1.4(4) kcal/mol and maximum error of 3(3) kcal/mol (parenthesis account for reported experimental uncertainties and the statistical errors of our ph-AFQMC calculations). In comparison, CCSD(T) and B97, the best performing DFT functional considered here, have MAEs of 2.8 and 3.7 kcal/mol, respectively, and maximum errors in excess of 17 kcal/mol for both methods. While a larger and more diverse data set would be required to demonstrate that ph-AFQMC is truly a benchmark method for transition metal systems, our results indicate that the method has tremendous potential, exhibiting unprecedented consistency and accuracy compared to other approximate quantum chemical approaches.

Over the past century, major advances in astronomy and astrophysics have been largely driven by improvements in instrumentation and data collection. With the amassing of high quality data from new telescopes, and especially with the advent of deep and large astronomical surveys, it is becoming clear that future advances will also rely heavily on how those data are analyzed and interpreted. New methodologies derived from advances in statistics, computer science, and machine learning are beginning to be employed in sophisticated investigations that are not only bringing forth new discoveries, but are placing them on a solid footing. Progress in wide-field sky surveys, interferometric imaging, precision cosmology, exoplanet detection and characterization, and many subfields of stellar, Galactic and extragalactic astronomy, has resulted in complex data analysis challenges that must be solved to perform scientific inference. Research in astrostatistics and astroinformatics will be necessary to develop the state-of-the-art methodology needed in astronomy. Overcoming these challenges requires dedicated, interdisciplinary research. We recommend: (1) increasing funding for interdisciplinary projects in astrostatistics and astroinformatics; (2) dedicating space and time at conferences for interdisciplinary research and promotion; (3) developing sustainable funding for long-term astrostatisics appointments; and (4) funding infrastructure development for data archives and archive support, state-of-the-art algorithms, and efficient computing.

The outer regions of globular clusters can enable us to answer many fundamental questions concerning issues ranging from the formation and evolution of clusters and their multiple stellar populations to the study of stars near and beyond the hydrogen-burning limit and to the dynamics of the Milky Way. The outskirts of globular clusters are still uncharted territories observationally. A very efficient way to explore them is through high-precision proper motions of low-mass stars over a large field of view. The Wide Field InfraRed Survey Telescope (WFIRST) combines all these characteristics in a single telescope, making it the best observational tool to uncover the wealth of information contained in the clusters' outermost regions.

There is a dichotomy in the Milky Way in the [α/Fe]-[Fe/H] plane, in which stars fall into high-α, and low-α sequences. The high-α sequence comprises mostly old stars, and the low-α sequence comprises primarily young stars. The origin of this dichotomy is uncertain. To better understand how the high- and low-α stars are affiliated, we examine if the high- and low-α sequences have distinct orbits at all ages, or if age sets the orbital properties of stars irrespective of their α-enhancement. Orbital actions JR, Jz, and Jϕ (or Lz) are our labels of stellar dynamics. We use ages for 58,278 LAMOST stars (measured to a precision of 40\%) within ≤2kpc of the Sun and we calculate orbital actions from proper motions and parallaxes given by Gaia's DR2. We find that \emph{at all ages}, the high- and low-α sequences are dynamically distinct. This implies separate formation and evolutionary histories for the two sequences; a star's membership in the high- or low-α sequence indicates its dynamical properties at a given time. We use action space to make an efficient selection of halo stars and subsequently report a group of old, low-α stars in the halo, which may be a discrete population from an infall event.

We examine the interactions between actively rotating proteins moving in a membrane. Experimental evidence suggests that such rotor proteins, like the ATP synthases of the inner mitochondrial membrane, can arrange themselves into lattices. We show that crystallization is possible through a combination of hydrodynamic and repulsive interactions between the rotor proteins. In particular, hydrodynamic interactions induce rotational motion of the rotor protein assembly that, in the presence of repulsion, drives the system into a hexagonal lattice. The entire crystal rotates with an angular velocity which increases with motor density and decreases with lattice diameter - larger and sparser arrays rotate at a slower pace. The rotational interactions allow ensembles of proteins to sample configurations and reach an ordered steady state, which are inaccessible to the quenched nonrotational system. Rotational interactions thus act as a sort of temperature that removes disorder, except that actual thermal diffusion leads to expansion and loss of order. In contrast, the rotational interactions are bounded in space. Hence, once an ordered state is reached, it is maintained at all times.

Prior to the detection of black holes (BHs) via the gravitational waves (GWs) they generate at merger, the presence of BHs was inferred in X-ray binaries, mostly via dynamical measurements, with measured masses in the range between ∼5−20 M⊙
The LIGO discovery of the first BHs via GWs was surprising in that the two BHs that merged had masses of 35.6 and 28.6 M⊙
, which are both above the range inferred from X-ray binaries. With 10 binary BH detections to date, it has become apparent that, while the two distributions are not disjoint, they are most certainly distinct. In this Letter, we suggest that the reason for the apparent dichotomy is due to a predominance of different formation channels: isolated binary evolution for X-ray binaries, and dynamical exchanges in dense star clusters for the LIGO BHs. We show, via timescale arguments, that BHs in high-masss X-ray binaries are preferentially seen when they have lower mass accretors. We then perform high-resolution N-body simulations of a cluster of isolated BHs with a range of initial mass spectra, and show that BH binaries are preferentially formed by the most massive BHs, and additionally that these tend to be the tightest binaries (hence with shorter merger timescales). We also perform a simulation with neutron stars (NSs) in addition to BHs, more abundant by a factor of 5, and show that the formation of NS-BH binaries is <1%
that of BH-BH binaries, hence making the dynamical formation of NS-BH systems much less likely than that of binary BHs.