Publications

Multivariate regression techniques are commonly applied to explore the associations between large numbers of outcomes and predictors. In real-world applications, the outcomes are often of mixed types, including continuous measurements, binary indicators, and counts, and the observations may also be incomplete. Building upon the recent advances in mixed-outcome modeling and sparse matrix factorization, generalized co-sparse factor regression (GOFAR) is proposed, which utilizes the flexible vector generalized linear model framework and encodes the outcome dependency through a sparse singular value decomposition (SSVD) of the integrated natural parameter matrix. To avoid the estimation of the notoriously difficult joint SSVD, GOFAR proposes both sequential and parallel unit-rank estimation procedures. By combining the ideas of alternating convex search and majorization–minimization, an efficient algorithm is developed to solve the sparse unit-rank problem and implemented in the R package gofar. Extensive simulation studies and two real-world applications demonstrate the effectiveness of the proposed approach.

The Bayesian approach to data analysis provides a powerful way to handle uncertainty in all observations, model parameters, and model structure using probability theory. Probabilistic programming languages make it easier to specify and fit Bayesian models, but this still leaves us with many options regarding constructing, evaluating, and using these models, along with many remaining challenges in computation. Using Bayesian inference to solve real-world problems requires not only statistical skills, subject matter knowledge, and programming, but also awareness of the decisions made in the process of data analysis. All of these aspects can be understood as part of a tangled workflow of applied Bayesian statistics. Beyond inference, the workflow also includes iterative model building, model checking, validation and troubleshooting of computational problems, model understanding, and model comparison. We review all these aspects of workflow in the context of several examples, keeping in mind that in practice we will be fitting many models for any given problem, even if only a subset of them will ultimately be relevant for our conclusions.

Gaussian processes (GPs) are commonly used as a model of stochastic variability in astrophysical time series. In particular, GPs are frequently employed to account for correlated stellar variability in planetary transit light curves. The efficient application of GPs to light curves containing thousands to tens of thousands of data points has been made possible by recent advances in GP methods, including the celerite method. Here we present an extension of the celerite method to two input dimensions where, typically, the second dimension is small. This method scales linearly with the total number of data points when the noise in each large dimension is proportional to the same celerite kernel and only the amplitude of the correlated noise varies in the second dimension. We demonstrate the application of this method to the problem of measuring precise transit parameters from multiwavelength light curves and show that it has the potential to improve transit parameters measurements by orders of magnitude. Applications of this method include transit spectroscopy and exomoon detection, as well a broader set of astronomical problems.

We present a novel numerical scheme for simulating the motion of relativistic charged particles in magnetospheres of compact objects, typically filled with highly magnetized collisionless plasmas. The new algorithm is based on a dynamic switch between the full system of equations of motion and a guiding-center approximation. The switch between the two formulations is based on the magnetization of the plasma particles, such that the dynamics are accurately captured by the guiding-center motion even when the gyrofrequency is underresolved by the time step. For particles with a large gyroradius, due to acceleration in, e.g., reconnecting current sheets, the algorithm adaptively switches to solve the full equations of motion instead. The new scheme is directly compatible with standard particle-in-cell codes, and is readily applicable in curved spacetimes via a dedicated covariant formulation. We test the performance of the coupled algorithm by evolving charged particles in electromagnetic configurations of reconnecting current sheets in magnetized plasma, obtained from special- and general-relativistic particle-in-cell simulations. The new coupled pusher is capable of producing highly accurate particle trajectories even when the time step is many orders of magnitude larger than the gyroperiod, substantially reducing the restrictions of the temporal resolution.

We present a novel numerical scheme for simulating the motion of relativistic charged particles in magnetospheres of compact objects, typically filled with highly magnetized collisionless plasmas. The new algorithm is based on a dynamic switch between the full system of equations of motion and a guiding-center approximation. The switch between the two formulations is based on the magnetization of the plasma particles, such that the dynamics are accurately captured by the guiding-center motion even when the gyrofrequency is underresolved by the time step. For particles with a large gyroradius, due to acceleration in, e.g., reconnecting current sheets, the algorithm adaptively switches to solve the full equations of motion instead. The new scheme is directly compatible with standard particle-in-cell codes, and is readily applicable in curved spacetimes via a dedicated covariant formulation. We test the performance of the coupled algorithm by evolving charged particles in electromagnetic configurations of reconnecting current sheets in magnetized plasma, obtained from special- and general-relativistic particle-in-cell simulations. The new coupled pusher is capable of producing highly accurate particle trajectories even when the time step is many orders of magnitude larger than the gyroperiod, substantially reducing the restrictions of the temporal resolution.

We study the cross correlation of damped Ly$\alpha$ systems (DLAs) and their background quasars, using the most updated DLA catalog and the Planck 2018 CMB lensing convergence field. Our measurement suggests that the DLA bias $b_{\rm DLA}$ is smaller than $3.1$, corresponding to $\log(M/M_\odot h^{-1})\leq 12.3$ at a confidence of $90\%$. These constraints are broadly consistent with Alonso et al. (2018) and previous measurements by cross-correlation between DLAs and the Ly$\alpha$ forest (e.g. Font-Ribera et al. 2012; Perez-Rafols et al. 2018). Further, our results demonstrate the potential of obtaining a more precise measurement of the halo mass of high-redshift sources using next generation CMB experiments with a higher angular resolution. The python-based codes and data products of our analysis are available at \href{https://github.com/LittleLin1999/CMB-lensingxDLA}{this https URL}.

Tailored nanostructures can confine electromagnetic waveforms in extremely sub-wavelength volumes, opening new avenues in lightwave sensing and control down to sub-molecular resolution. Atomic light–matter interaction depends critically on the absolute strength and the precise time evolution of the near field, which may be strongly influenced by quantum-mechanical effects. However, measuring atom-scale field transients has remained out of reach. Here we introduce quantitative atomic-scale waveform sampling in lightwave scanning tunnelling microscopy to resolve a tip-confined near-field transient. Our parameter-free calibration employs a single-molecule switch as an atomic-scale voltage standard. Although salient features of the far-to-near-field transfer follow classical electrodynamics, we develop a comprehensive understanding of the atomic-scale waveforms with time-dependent density functional theory. The simulations validate our calibration and confirm that single-electron tunnelling ensures minimal back-action of the measurement process on the electromagnetic fields. Our observations access an uncharted domain of nano-opto-electronics where local quantum dynamics determine femtosecond atomic near fields.

Ultrafast optical control of ferroelectricity using intense terahertz fields has attracted significant interest. Here we show that the nonlinear interactions between two optical phonons in SnTe, a two-dimensional in-plane ferroelectric material, enables a dynamical amplification of the electric polarization within subpicoseconds time domain. Our first-principles time-dependent simulations show that the infrared-active out-of-plane phonon mode, pumped to nonlinear regimes, spontaneously generates in-plane motions, leading to rectified oscillations in the in-plane electric polarization. We suggest that this dynamical control of ferroelectric material, by nonlinear phonon excitation, can be utilized to achieve ultrafast control of the photovoltaic or other nonlinear optical responses.

In this brief review, we summarize and elaborate on some of the nomenclature of polaritonic phenomena and systems as they appear in the literature on quantum materials and quantum optics. Our summary includes at least 70 different types of polaritonic light–matter dressing effects. This summary also unravels a broad panorama of the physics and applications of polaritons. A constantly updated version of this review is available at https://infrared.cni.columbia.edu/research/polariton-panorama-2-2/

Femtosecond X-ray laser pulses synchronized with an optical laser were employed to investigate the reaction dynamics of the photooxidation of CO on the anatase TiO2(101) surface in real time. Our time-resolved soft X-ray photoemission spectroscopy results provide evidence of ultrafast timescales and, coupled with theoretical calculations, clarify the mechanism of oxygen activation that is crucial to unraveling the underlying processes for a range of photocatalytic reactions relevant to air purification and self-cleaning surfaces. The reaction takes place between 1.2 and 2.8 (±0.2) ps after irradiation with an ultrashort laser pulse leading to the formation of CO2, prior to which no intermediate species were observed on a picosecond time scale. Our theoretical calculations predict that the presence of intragap unoccupied O2 levels leads to the formation of a charge-transfer complex. This allows the reaction to be initiated following laser illumination at a photon energy of 1.6 eV (770 nm), taking place via a proposed mechanism involving the direct transfer of electrons from TiO2 to physisorbed O2.