Publications

The orbital properties of stars in the disk are signatures of their formation, but they are also expected to change over time due to the dynamical evolution of the Galaxy. Stellar orbits can be quantified by three dynamical actions, J_r, L_z, and J_z, which provide measures of the orbital eccentricity, guiding radius, and non-planarity, respectively. Changes in these dynamical actions over time reflect the strength and efficiency of the evolutionary processes that drive stellar redistributions. We examine how dynamical actions of stars are correlated with their age using two samples of stars with well-determined ages: 78 solar twin stars (with ages to ~5%) and 4376 stars from the APOKASC2 sample (~20%). We compute actions using spectroscopic radial velocities from previous surveys and parallax and proper motion measurements from Gaia DR2. We find weak gradients in all actions with stellar age, of (7.51 +/- 0.52, -29.0 +/- 1.83, 1.54 +/- 0.18) kpc km/s/Gyr for J_r, L_z, and J_z, respectively. There is, however, significant scatter in the action-age relation. We caution that our results will be affected by the restricted spatial extent of our sample, particularly in the case of J_z. Nevertheless, these action-age gradients and their associated variances provide strong constraints on the efficiency of the mechanisms that drive the redistribution of stellar orbits over time and demonstrate that actions are informative as to stellar age. The shallow action-age gradients combined with the large dispersion in each action at a given age, however, renders the prospect of age inference from orbits of individual stars bleak. Using the precision measurements of [Fe/H] and [α/Fe] for our stars we investigate the abundance-action relationship and find weak correlations. Similar to our stellar age results, dynamical actions afford little discriminating power between low- and high-α stars.

Stars with unusual elemental abundances offer clues about rare astrophysical events or nucleosynthetic pathways. Stars with significantly depleted magnesium and enhanced potassium ([Mg/Fe] < -0.5; [K/Fe] > 1) have to date only been found in the massive globular cluster NGC 2419 and, to a lesser extent, NGC 2808. The origin of this abundance signature remains unknown, as does the reason for its apparent exclusivity to these two globular clusters. Here we present 112 field stars, identified from 454,180 LAMOST giants, that show significantly enhanced [K/Fe] and possibly depleted [Mg/Fe] abundance ratios. Our sample spans a wide range of metallicities (-1.5 < [Fe/H] < 0.3), yet none show abundance ratios of [K/Fe] or [Mg/Fe] that are as extreme as those observed in NGC 2419. If confirmed, the identified sample of stars represents evidence that the nucleosynthetic process producing the anomalous abundances ratios of [K/Fe] and [Mg/Fe] probably occurs at a wide range of metallicities. This would suggest that pollution scenarios that are limited to early epochs (such as Population III supernovae) are an unlikely explanation, although they cannot be ruled out entirely. This sample is expected to help guide modelling attempts to explain the origin of the Mg-K abundance signature.

The three-band Hubbard model is a fundamental model for understanding properties of the Copper-Oxygen planes in cuprate superconductors. We use cutting-edge auxiliary-field quantum Monte Carlo (AFQMC) methods to investigate ground state properties of the model in the parent compound. Large supercells combined with twist averaged boundary conditions are studied to reliably reach the thermodynamic limit. Benchmark quality results are obtained on the magnetic correlations and charge gap. A key parameter of this model is the charge-transfer energy Δ between the Oxygen p and the Copper d orbitals, which appears to vary significantly across different families of cuprates and whose ab initio determination is subtle. We show that the system undergoes a quantum phase transition from an antiferromagnetic insulator to a paramagnetic metal as Δ is lowered to 3 eV.

The past year has witnessed discovery of the first identified counterparts to a gravitational wave transient (GW 170817A) and a very high-energy neutrino (IceCube-170922A). These source identifications, and ensuing detailed studies, have realized longstanding dreams of astronomers and physicists to routinely carry out observations of cosmic sources by other than electromagnetic means, and inaugurated the era of "multi-messenger" astronomy. While this new era promises extraordinary physical insights into the universe, it brings with it new challenges, including: highly heterogeneous, high-volume, high-velocity datasets; globe-spanning cross-disciplinary teams of researchers, regularly brought together into transient collaborations; an extraordinary breadth and depth of domain-specific knowledge and computing resources required to anticipate, model, and interpret observations; and the routine need for adaptive, distributed, rapid-response observing campaigns to fully exploit the scientific potential of each source. We argue, therefore, that the time is ripe for the community to conceive and propose an Institute for Multi-Messenger Astrophysics that would coordinate its resources in a sustained and strategic fashion to efficiently address these challenges, while simultaneously serving as a center for education and key supporting activities. In this fashion, we can prepare now to realize the bright future that we see, beyond, through these newly opened windows onto the universe.

The stellar populations in the inner kiloparsecs of the Milky Way (MW) show complex kinematical and chemical structures. The origin and evolution of these structures is still under debate. Here we study the central region of a fully cosmological hydrodynamical simulation of a disc galaxy that reproduces key properties of the inner kiloparsecs of the Milky Way: it has a boxy morphology and shows an overall rotation and dispersion profile in agreement with observations. We use a clustering algorithm on stellar kinematics to identify a number of discrete kinematic components: a thin and thick disc, a stellar halo and two bulge components; one fast rotating and one non-rotating. We focus on the two bulge components and show that the slow rotating one is spherically symmetric while the fast rotating component shows a boxy/peanut morphology. Although the two bulge components are kinematically discrete populations, they are both mostly formed over similar time scales, from disc material. We find that stellar particles with lower initial birth angular momentum end up in the non-rotating spherical bulge, while stars with higher birth angular momentum are found in the peanut bulge. This has the important consequence that a bulge population with a spheroidal morphology does not necessarily indicate a merger origin. In fact, we do find that only ∼2.3\% of the stars in the bulge components are ex-situ stars brought in by accreted dwarf galaxies early on. We identify these ex-situ stars as the oldest and most metal-poor stars in the bulge.

The spreading of correlations after a quantum quench is studied in a wide class of lattice systems, with short- and long-range interactions. Using a unifying quasiparticle framework, we unveil a rich structure of the correlation cone, which encodes the footprints of several microscopic properties of the system. When the quasiparticle excitations propagate with a bounded group velocity, we show that the correlation edge and correlation maxima move with different velocities that we derive. For systems with a divergent group velocity, especially relevant for long-range interacting systems, the correlation edge propagates slower than ballistic. In contrast, the correlation maxima propagate faster than ballistic in gapless systems but ballistic in gapped systems. Our results shed light on existing experimental and numerical observations and pave the way to the next generation of experiments. For instance, we argue that the dynamics of correlation maxima can be used as a witness of the elementary excitations of the system.

We theoretically investigate the role of intraband transitions in laser-induced carrier generation for different photon energy regimes: (i) strongly off resonant, (ii) multiphoton resonant, and (iii) resonant conditions. Based on the analysis for the strongly off resonant and multiphoton resonant cases, we find that intraband transitions strongly enhance photocarrier generation in both multiphoton absorption and tunneling excitation regimes, and thus, they are indispensable for describing the nonlinear photocarrier generation processes. Furthermore, we find that intraband transitions enhance photocarrier generation even in the resonant condition, opening additional multiphoton excitation channels once the laser irradiation becomes sufficiently strong. The above findings suggest a potential for efficient control of photocarrier generation via multicolor laser pulses through optimization of the contributions from intraband transitions.

We present a kinetic-energy density-functional theory and the corresponding kinetic-energy Kohn–Sham (keKS) scheme on a lattice and show that, by including more observables explicitly in a density-functional approach, already simple approximation strategies lead to very accurate results. Here, we promote the kinetic-energy density to a fundamental variable alongside the density and show for specific cases (analytically and numerically) that there is a one-to-one correspondence between the external pair of on-site potential and site-dependent hopping and the internal pair of density and kinetic-energy density. On the basis of this mapping, we establish two unknown effective fields, the mean-field exchange-correlation potential and the mean-field exchange-correlation hopping, which force the keKS system to generate the same kinetic-energy density and density as the fully interacting one. We show, by a decomposition based on the equations of motions for the density and the kinetic-energy density, that we can construct simple orbital-dependent functionals that outperform the corresponding exact-exchange Kohn–Sham (KS) approximation of standard density-functional theory. We do so by considering the exact KS and keKS systems and comparing the unknown correlation contributions as well as by comparing self-consistent calculations based on the mean-field exchange (for the effective potential) and a uniform (for the effective hopping) approximation for the keKS and the exact-exchange approximation for the KS system, respectively.

The cosmological exploitation of modern photometric galaxy surveys requires both accurate (unbiased) and precise (narrow) redshift probability distributions derived from broadband photometry. Existing methodologies do not meet those requirements. Standard template fitting delivers interpretable models and errors, but lacks flexibility to learn inaccuracies in the observed photometry or the spectral templates. Machine learning addresses those issues, but requires representative training data, and the resulting models and uncertainties cannot be interpreted in the context of a physical model or outside of the training data. We present a hierarchical modeling approach simultaneously addressing the issues of flexibility, interpretability, and generalization. It combines template fitting with flexible (machine learning-like) models to correct the spectral templates, model their redshift distributions, and recalibrate the photometric observations. By optimizing the full posterior distribution of the model and solving for its (thousands of) parameters, one can perform a global statistical calibration of the data and the SED model. We apply this approach to the public Dark Energy Survey Science Verification data, and show that it provides more accurate and compact redshift posterior distributions than existing methods, as well as insights into residual photometric and SED systematics. The model is causal, makes predictions for future data (e.g., additional photometric bandpasses), and its internal parameters and components are interpretable. This approach does not formally require the training data to be complete or representative; in principle it can even work in regimes in which few or no spectroscopic redshifts are available.

GIANT2 (Genome-wide Integrated Analysis of gene Networks in Tissues) is an interactive web server that enables biomedical researchers to analyze their proteins and pathways of interest and generate hypotheses in the context of genome-scale functional maps of human tissues. The precise actions of genes are frequently dependent on their tissue context, yet direct assay of tissue-specific protein function and interactions remains infeasible in many normal human tissues and cell-types. With GIANT2, researchers can explore predicted tissue-specific functional roles of genes and reveal changes in those roles across tissues, all through interactive multi-network visualizations and analyses. Additionally, the NetWAS approach available through the server uses tissue-specific/cell-type networks predicted by GIANT2 to re-prioritize statistical associations from GWAS studies and identify disease-associated genes. GIANT2 predicts tissue-specific interactions by integrating diverse functional genomics data from now over 61 400 experiments for 283 diverse tissues and cell-types. GIANT2 does not require any registration or installation and is freely available for use at http://giant-v2.princeton.edu.