Publications

It has been demonstrated that the time variability of a star's brightness at different frequencies can be used to infer its surface gravity, radius, mass, and age. With large samples of light curves now available from Kepler and K2, and upcoming surveys like TESS, we wish to quantify the overall information content of this data and identify where the information resides. As a first look into this question, we ask which stellar parameters we can predict from the brightness variations in red-giant stars data and to what precision, using a data-driven, nonparametric model. We demonstrate that the long-cadence (30 minute) Kepler light curves for 2000 red-giant stars can be used to predict their ${T}_{\mathrm{eff}}$ and $\mathrm{log}g$. Our inference makes use of a data-driven model of a part of the autocorrelation function (ACF) of the light curve, where we posit a polynomial relationship between stellar parameters and the ACF pixel values. We find that this model, trained using 1000 stars, can be used to recover the temperature ${T}_{\mathrm{eff}}$ to <100 K, the surface gravity to <0.1 dex, and the asteroseismic power-spectrum parameters ${\nu }_{\max }$ and ${\rm{\Delta }}\nu $ to <11 μHz and <0.9 μHz (lesssim15%). We recover ${T}_{\mathrm{eff}}$ from range of time lags 0.045 < ${T}_{\mathrm{lag}}$ < 370 days and the $\mathrm{log}g$, ${\nu }_{\max }$, and ${\rm{\Delta }}\nu $ from the range 0.045 < ${T}_{\mathrm{lag}}$ < 35 days. We do not discover any information about stellar metallicity in this model of the ACF. The information content of the data about each parameter is empirically quantified using this method, enabling comparisons to theoretical expectations about convective granulation.

We have recently proposed a nonequilibrium Green’s function (NEGF) approach to include Auger decay processes in the ultrafast charge dynamics of photoionized molecules. Within the so-called generalized Kadanoff–Baym ansatz the fundamental unknowns of the NEGF equations are the reduced one-particle density matrix of bound electrons and the occupations of the continuum states. Both unknowns are one-time functions like the density in time-dependent functional theory (TDDFT). In this work, we assess the accuracy of the approach against configuration interaction (CI) calculations in one-dimensional model systems. Our results show that NEGF correctly captures qualitative and quantitative features of the relaxation dynamics provided that the energy of the Auger electron is much larger than the Coulomb repulsion between two holes in the valence shells. For the accuracy of the results dynamical electron-electron correlations or, equivalently, memory effects play a pivotal role. The combination of our NEGF approach with the Sham–Schlüter equation may provide useful insights for the development of TDDFT exchange-correlation potentials with a history dependence.

We extend the first-principles analysis of attosecond transient absorption spectroscopy to two-dimensional materials. As an example of two-dimensional materials, we apply the analysis to monolayer hexagonal boron nitride (h-BN) and compute its transient optical properties under intense few-cycle infrared laser pulses. Nonadiabatic features are observed in the computed transient absorption spectra. To elucidate the microscopic origin of these features, we analyze the electronic structure of h-BN with density functional theory and investigate the dynamics of specific energy bands with a simple two-band model. Finally, we find that laser-induced intraband transitions play a significant role in the transient absorption even for the two-dimensional material and that the nonadiabatic features are induced by the dynamical Franz-Keldysh effect with an anomalous band dispersion.

ulsar-timing analyses are sensitive to errors in the solar-system ephemerides (SSEs) that timing models utilise to estimate the location of the solar-system barycentre, the quasi-inertial reference frame to which all recorded pulse times-of-arrival are referred. Any error in the SSE will affect all pulsars, therefore pulsar timing arrays (PTAs) are a suitable tool to search for such errors and impose independent constraints on relevant physical parameters. We employ the first data release of the International Pulsar Timing Array to constrain the masses of the planet-moons systems and to search for possible unmodelled objects (UMOs) in the solar system. We employ ten SSEs from two independent research groups, derive and compare mass constraints of planetary systems, and derive the first PTA mass constraints on asteroid-belt objects. Constraints on planetary-system masses have been improved by factors of up to 20 from the previous relevant study using the same assumptions, with the mass of the Jovian system measured at 9.5479189(3)×10−4 M⊙. The mass of the dwarf planet Ceres is measured at 4.7(4)×10−10 M⊙. We also present the first sensitivity curves using real data that place generic limits on the masses of UMOs, which can also be used as upper limits on the mass of putative exotic objects. For example, upper limits on dark-matter clumps are comparable to published limits using independent methods. While the constraints on planetary masses derived with all employed SSEs are consistent, we note and discuss differences in the associated timing residuals and UMO sensitivity curves.

We introduce highly local basis sets for electronic structure which are very efficient for correlation calculations near the complete basis set limit. Our approach is based on gausslets, recently introduced wavelet-like smooth orthogonal functions. We adapt the gausslets to particular systems using one dimensional coordinate transformations, putting more basis functions near nuclei, while maintaining orthogonality. Three dimensional basis functions are composed out of products of the 1D functions in an efficient way called multislicing. We demonstrate the new bases with both Hartree Fock and density matrix renormalization group (DMRG) calculations on hydrogen chain systems. With both methods, we can go to higher accuracy in the complete basis set limit than is practical for conventional Gaussian basis sets, with errors near 0.1 mH per atom.

To understand superconductivity in Chevrel phase compounds and guide the search for interesting properties in materials created with Chevrel phase molecules as building blocks, we use ab-initio methods to study the properties of single Mo6X8 molecules with X=S, Se, Te as well as the bulk solid PbMo6S8. In bulk PbMo6S8, the different energy scales from strong to weak are: the band kinetic energy, the intra-molecular Coulomb interaction, the on-molecule Jahn-Teller energy and the Hund's exchange coupling. The metallic state is stable with respect to Mott and polaronic insulating states. The bulk compound is characterized by a strong electron-phonon interaction with the largest coupling involving phonon modes with energies in the range from 11 meV to 17 meV and with a strong inter-molecule (Peierls) character. A two-band Eliashberg equation analysis shows that the superconductivity is strong-coupling, with different gaps on the two Fermi surface sheets. A Bergman-Rainer analysis of the functioanl derivative of the transition temperature with respect to the electron-phonon coupling reveals that the Peierls modes provide the most important contribution to the superconductivity. This work illustrates the importance of inter-molecular coupling for collective phenomena in molecular solids.

Measuring the centroid of a spectral line is a common problem in astronomy. Many methods have been devised to overcome limitations due to either noise in the spectra or asymmetric profiles, the most common of which are the intensity weighted averages (first moment) or fits of analytical (typically Gaussian) profiles. If the spectral line can be considered a single component, we demonstrate that a simple quadratic fit to the pixel of maximum intensity and its two neighboring pixels provides a robust measure of the line centroid. This approach allows for a sub-velocity resolution precision on the line centroid, without be biases by noise or asymmetric features in the line profile and outperforming traditional methods in most situations.

Measuring the centroid of a spectral line is a common problem in astronomy. Many methods have been devised to overcome limitations due to either noise in the spectra or asymmetric profiles, the most common of which are the intensity weighted averages (first moment) or fits of analytical (typically Gaussian) profiles. If the spectral line can be considered a single component, we demonstrate that a simple quadratic fit to the pixel of maximum intensity and its two neighboring pixels provides a robust measure of the line centroid. This approach allows for a sub-velocity resolution precision on the line centroid, without be biases by noise or asymmetric features in the line profile and outperforming traditional methods in most situations.

A key challenge in precision medicine lies in understanding molecular-level underpinnings of complex human disease. Biological networks in multicellular organisms can generate hypotheses about disease genes, pathways, and their behavior in disease-related tissues. Diverse functional genomic data, including expression, protein-protein interaction, and relevant sequence and literature information, can be utilized to build integrative networks that provide both genome-wide coverage as well as contextual specificity and accuracy. By carefully extracting the relevant signal in thousands of heterogeneous functional genomics experiments through integrative analysis, these networks model how genes work together in specific contexts to carry out cellular processes, thereby contributing to a molecular-level understanding of complex human disease and paving the way toward better therapy and drug treatment. Here, we discuss current methods to build context-specific integrative networks, focusing on tissue-specific networks. We highlight applications of these networks in predicting tissue-specific molecular response, identifying candidate disease genes, and increasing power by amplifying the disease signal in quantitative genetics data. Altogether, these exciting developments enable biomedical scientists to characterize disease from pathophysiology to cellular system and, finally, to specific gene alterations-making significant strides toward the goal of precision medicine.

Converting a noisy parallax measurement into a posterior belief over distance requires inference with a prior. Usually this prior represents beliefs about the stellar density distribution of the Milky Way. However, multi-band photometry exists for a large fraction of the \textsl{\small{Gaia}} \textsl{\small{TGAS}} Catalog and is incredibly informative about stellar distances. Here we use \textsl{\small{2MASS}} colors for 1.4 million \textsl{\small{TGAS}} stars to build a noise-deconvolved empirical prior distribution for stars in color--magnitude space. This model contains no knowledge of stellar astrophysics or the Milky Way, but is precise because it accurately generates a large number of noisy parallax measurements under an assumption of stationarity; that is, it is capable of combining the information from many stars. We use the Extreme Deconvolution (\textsl{\small{XD}}) algorithm---an Empirical Bayes approximation to a full hierarchical model of the true parallax and photometry of every star---to construct this prior. The prior is combined with a \textsl{\small{TGAS}} likelihood to infer a precise photometric parallax estimate and uncertainty (and full posterior) for every star. Our parallax estimates are more precise than the \textsl{\small{TGAS}} catalog entries by a median factor of 1.2 (14% are more precise by a factor >2) and are more precise than previous Bayesian distance estimates that use spatial priors. We validate our parallax inferences using members of the Milky Way star cluster M67, which is not visible as a cluster in the \textsl{\small{TGAS}} parallax estimates, but appears as a cluster in our posterior parallax estimates. Our results, including a parallax posterior pdf for each of 1.4 million \textsl{\small{TGAS}} stars, are available in companion electronic tables.