Publications

We introduce a new general-purpose time-dependent ionisation network (IN) and a radiation transport (RT) module in the magneto-hydrodynamic (MHD) code PLUTO. Our ionisation network is reliable for temperatures ranging from 5e3 to 3e8 K, and includes all ionisation states of H, He, C, N, O, Ne, Mg, Si, S and Fe making it suitable for studying a variety of astrophysical scenarios. Radiation loss for each ion-electron pair is calculated using CLOUDY-17 data on-the-fly. Photo-ionisation and charge exchange are the chemical heating mechanisms. The IN is fully coupled to the radiation transport module over a very large range of opacities at different frequencies. The RT module employs a method of short characteristics assuming spherical symmetry. The radiation module requires the assumption of spherical symmetry, while the IN is compatible with full 3D. We also include a simple prescription for dust opacity, grain destruction, and the dust contribution to radiation pressure. We present numerical tests to show the reliability and limitations of the new modules. We also present a post-processing tool to calculate projected column densities and emission spectra.

The most popular algorithm for the nonuniform fast Fourier transform (NUFFT) uses the dilation of a kernel $\phi$ to spread (or interpolate) between given nonuniform points and a uniform upsampled grid, combined with an FFT and diagonal scaling (deconvolution) in frequency space. The high performance of the recent FINUFFT library is in part due to its use of a new ``exponential of semicircle'' kernel $\phi(z)=e^{\beta \sqrt{1-z^2}}$, for $z\in[-1,1]$, zero otherwise, whose Fourier transform $\hat\phi$ is unknown analytically. We place this kernel on a rigorous footing by proving an aliasing error estimate which bounds the error of the one-dimensional NUFFT of types 1 and 2 in exact arithmetic. Asymptotically in the kernel width measured in upsampled grid points, the error is shown to decrease with an exponential rate arbitrarily close to that of the popular Kaiser--Bessel kernel. This requires controlling a conditionally-convergent sum over the tails of $\hat\phi$, using steepest descent, other classical estimates on contour integrals, and a phased sinc sum. We also draw new connections between the above kernel, Kaiser--Bessel, and prolate spheroidal wavefunctions of order zero, which all appear to share an optimal exponential convergence rate.

We present an extension of constrained-path auxiliary-field quantum Monte Carlo (CP-AFQMC) for the treatment of correlated electronic systems coupled to phonons. The algorithm follows the standard CP-AFQMC approach for description of the electronic degrees of freedom while phonons are described in first quantization and propagated via a diffusion Monte Carlo approach. Our method is tested on the one- and two-dimensional Holstein and Hubbard-Holstein models. With a simple semiclassical trial wavefunction, our approach is remarkably accurate for ω/(2dtλ) < 1 for all parameters in the Holstein model considered in this study. In addition, we empirically show that the autocorrelation time scales as 1/ω for ω/t 1, which is an improvement over the 1/ω

Convolutional neural networks (CNN) have become a standard approach for modeling genomic sequences. CNNs can be effectively built by Neural Architecture Search (NAS) by trading computing power for accurate neural architectures. Yet, the consumption of immense computing power is a major practical, financial, and environmental issue for deep learning. Here, we present a novel NAS framework,
AMBIENT, that generates highly accurate CNN architectures for biological sequences of diverse functions, while substantially reducing the computing cost of conventional NAS.

Blazars emit a highly variable non-thermal spectrum. It is usually assumed that the same non-thermal electrons are responsible for the IR-optical-UV emission (via synchrotron) and the gamma-ray emission (via inverse Compton). Hence, the light curves in the two bands should be correlated. Orphan gamma-ray flares (i.e. lacking a luminous low-frequency counterpart) challenge our theoretical understanding of blazars. By means of large-scale two-dimensional radiative particle-in-cell simulations, we show that orphan gamma-ray flares may be a self-consistent by-product of particle energization in turbulent magnetically dominated pair plasmas. The energized particles produce the gamma-ray flare by inverse Compton scattering an external radiation field, while the synchrotron luminosity is heavily suppressed since the particles are accelerated nearly along the direction of the local magnetic field. The ratio of inverse Compton to synchrotron luminosity is sensitive to the initial strength of turbulent fluctuations (a larger degree of turbulent fluctuations weakens the anisotropy of the energized particles, thus increasing the synchrotron luminosity). Our results show that the anisotropy of the non-thermal particle population is key to modelling the blazar emission.

Stars with peculiar element abundances are important markers of chemical enrichment mechanisms. We present a simple method, tangent space projection (TSP), for the detection of X-enriched stars, for arbitrary elements X, even from blended lines. Our method does not require stellar labels, but instead directly estimates the counterfactual unrenriched spectrum from other unlabelled spectra. As a case study, we apply this method to the 6708 Å Li doublet in LAMOST DR5, identifying 8,428 Li-enriched stars seamlessly across evolutionary state. We comment on the explanation for Li-enrichement for different subpopulations, including planet accretion, nonstandard mixing, and youth.

Lyman-α (Lyα) emitting galaxies are powerful tools to probe the late stages of cosmic reionization. The observed sudden drop in Lyα fraction at z>6 is often interpreted as a sign of reionization, since the intergalactic medium (IGM) is more neutral and opaque to Lyα photons. Crucially, this interpretation of the observations is only valid under the assumption that galaxies themselves experience a minimal evolution at these epochs. By modelling Lyα radiative transfer effects in and around galaxies, we examine whether a change in the galactic properties can reproduce the observed drop in the Lyα fraction. We find that an increase in the galactic neutral hydrogen content or a reduction in the outflow velocity toward higher redshift both lead to a lower Lyα escape fraction, and can thus mimic an increasing neutral fraction of the IGM. We furthermore find that this change in galactic properties leads to systematically different Lyα spectra which can be used to differentiate the two competing effects. Using the CANDELSz7 survey measurements which indicate slightly broader lines at z∼6, we find that the scenario of a mere increase in the galactic column density towards higher z is highly unlikely. We also show that a decrease in outflow velocity is not ruled out by existing data but leads to more prominent blue peaks at z>6. Our results caution the use of Lyα observations to estimate the IGM neutral fraction without accounting for the potential change in the galactic properties, e.g., by mapping out the evolution of Lyα spectral characteristics.

We present the checkpointing scheme of Abacus, an N-body simulation code that allocates all persistent state in POSIX shared memory, or ramdisk. Checkpointing becomes as simple as copying files from ramdisk to external storage. The main simulation executable is invoked once per time step, memory mapping the input state, computing the output state directly into ramdisk, and unmapping the input state. The main executable remains unaware of the concept of checkpointing, with the top-level driver code launching a file-system copy between executable invocations when a checkpoint is needed. Since the only information flow is through files on ramdisk, the checkpoint must be correct so long as the simulation is correct. However, we find that with multi-GB of state, there is a significant overhead to unmapping the shared memory. This can be partially mitigated with multithreading, but ultimately, we do not recommend shared memory for use with a large state.

Statistical analysis of microbial genomic data within epidemiological cohort studies holds the promise to assess the influence of environmental exposures on both the host and the host-associated microbiome. The observational character of prospective cohort data and the intricate characteristics of microbiome data make it, however, challenging to discover causal associations between environment and microbiome. Here, we introduce a causal inference framework based on the Rubin Causal Model that can help scientists to investigate such environment-host microbiome relationships, to capitalize on existing, possibly powerful, test statistics, and test plausible sharp null hypotheses. Using data from the German KORA cohort study, we illustrate our framework by designing two hypothetical randomized experiments with interventions of (i) air pollution reduction and (ii) smoking prevention. We study the effects of these interventions on the human gut microbiome by testing shifts in microbial diversity, changes in individual microbial abundances, and microbial network wiring between groups of matched subjects via randomization-based inference. In the smoking prevention scenario, we identify a small interconnected group of taxa worth further scrutiny, including Christensenellaceae and Ruminococcaceae genera, that have been previously associated with blood metabolite changes. These findings demonstrate that our framework may uncover potentially causal links between environmental exposure and the gut microbiome from observational data. We anticipate the present statistical framework to be a good starting point for further discoveries on the role of the gut microbiome in environmental health.

The radio emission anomaly coincident with the 2016 glitch of the Vela pulsar may be caused by a star quake that launches Alfvén waves into the magnetosphere, disturbing the original radio emitting region. To quantify the lifetime of the Alfvén waves, we investigate a possible energy loss mechanism, the conversion of Alfvénwaves into fast magnetosonic waves. Using axisymmetric force-free simulations, we follow the propagation of Alfvén waves launched from the stellar surface with small amplitude into the closed zone of a force-free dipolar pulsar magnetosphere. We observe mode conversion happening in the ideal force-free regime. The conversion efficiency during the first passage of the Alfvén wave through the equator can be large, for waves that reach large amplitudes as they travel away from the star, or propagate on the field lines passing close to the Y-point. However, the conversion efficiency is reduced due to dephasing on subsequent passages and considerable Alfvén power on the closed field lines remains. Thus while some leakage into the fast mode happens, we need detailed understanding of the original quenching in order to say whether mode conversion alone can lead to reactivation of the pulsar on a short timescale.