Publications

We report and discuss the discovery of a comoving pair of bright solar-type stars, HD 240430 and HD 240429, with a significant difference in their chemical abundances. The two stars have an estimated 3D separation of ≈0.6 pc (≈0.01 pc projected) at a distance of r≈100 pc with nearly identical three-dimensional velocities, as inferred from Gaia TGAS parallaxes and proper motions, and high-precision radial velocity measurements. Stellar parameters determined from high-resolution Keck HIRES spectra indicate that both stars are ∼4 Gyr old. The more metal-rich of the two, HD 240430, shows an enhancement of refractory (TC>1200 K) elements by ≈0.2 dex and a marginal enhancement of (moderately) volatile elements (TC<1200 K, C, N, O, Na, and Mn). This is the largest metallicity difference found in a wide binary pair yet. Additionally, HD 240430 shows an anomalously high surface lithium abundance (A(Li)=2.75), higher than its companion by 0.5 dex. The proximity in phase-space and ages between the two stars suggests that they formed together with the same composition, at odds with the observed differences in metallicity and abundance patterns. We therefore suggest that the star HD~240430, "Kronos", accreted 15 M⊕ of rocky material after birth, selectively enhancing the refractory elements as well as lithium in its surface and convective envelope.

Understanding the detailed dynamics of neuronal networks will require the simultaneous measurement of spike trains from hundreds of neurons (or more). Currently, approaches to extracting spike times and labels from raw data are time consuming, lack standardization, and involve manual intervention, making it difficult to maintain data provenance and assess the quality of scientific results. Here, we describe an automated clustering approach and associated software package that addresses these problems and provides novel cluster quality metrics. We show that our approach has accuracy comparable to or exceeding that achieved using manual or semi-manual techniques with desktop central processing unit (CPU) runtimes faster than acquisition time for up to hundreds of electrodes. Moreover, a single choice of parameters in the algorithm is effective for a variety of electrode geometries and across multiple brain regions. This algorithm has the potential to enable reproducible and automated spike sorting of larger scale recordings than is currently possible.

Broad-spectrum antibiotics are frequently prescribed to children. Early childhood represents a dynamic period for the intestinal microbial ecosystem, which is readily shaped by environmental cues; antibiotic-induced disruption of this sensitive community may have long-lasting host consequences. Here we demonstrate that a single pulsed macrolide antibiotic treatment (PAT) course early in life is sufficient to lead to durable alterations to the murine intestinal microbiota, ileal gene expression, specific intestinal T-cell populations, and secretory IgA expression. A PAT-perturbed microbial community is necessary for host effects and sufficient to transfer delayed secretory IgA expression. Additionally, early-life antibiotic exposure has lasting and transferable effects on microbial community network topology. Our results indicate that a single early-life macrolide course can alter the microbiota and modulate host immune phenotypes that persist long after exposure has ceased.High or multiple doses of macrolide antibiotics, when given early in life, can perturb the metabolic and immunological development of lab mice. Here, Ruiz et al. show that even a single macrolide course, given early in life, leads to long-lasting changes in the gut microbiota and immune system of mice.

We measure carbon and nitrogen abundances to ≲ 0.1 dex for 450,000 giant stars from their low-resolution (R∼1800) LAMOST DR2 survey spectra. We use these [C/M] and [N/M] measurements, together with empirical relations based on the APOKASC sample, to infer stellar masses and implied ages for 230,000 of these objects to 0.08 dex and 0.2 dex respectively. We use The Cannon, a data-driven approach to spectral modeling, to construct a predictive model for LAMOST spectra. Our reference set comprises 8125 stars observed in common between the APOGEE and LAMOST surveys, taking seven APOGEE DR12 labels (parameters) as ground truth: Teff, logg, [M/H], [α/M], [C/M], [N/M], and Ak. We add seven colors to the Cannon model, based on the g, r, i, J, H, K, W1, and W2 magnitudes from APASS, 2MASS & WISE, which improves our constraints on Teff and logg by up to 20% and on Ak by up to 70%. Cross-validation of the model demonstrates that, for high-SNR objects, our inferred labels agree with the APOGEE values to within 50 K in temperature, 0.04 magnitudes in Ak, and < 0.1 dex in logg, [M/H], [C/M], [N/M], and [α/M]. We apply the model to 450,000 giants in LAMOST DR2 that have not been observed by APOGEE. This demonstrates that precise individual abundances can be measured from low-resolution spectra, and represents the largest catalog of [C/M], [N/M], masses and ages to date. As as result, we greatly increase the number and sky coverage of stars with mass and age estimates.

Gravitational non-linear evolution induces a shift in the position of the baryon acoustic oscillations (BAO) peak together with a damping and broadening of its shape that bias and degrades the accuracy with which the position of the peak can be determined. BAO reconstruction is a technique developed to undo part of the effect of non-linearities. We present and analyse a reconstruction method that consists of displacing pixels instead of galaxies and whose implementation is easier than the standard reconstruction method. We show that this method is equivalent to the standard reconstruction technique in the limit where the number of pixels becomes very large. This method is particularly useful in surveys where individual galaxies are not resolved, as in 21cm intensity mapping observations. We validate this method by reconstructing mock pixelated maps, that we build from the distribution of matter and halos in real- and redshift-space, from a large set of numerical simulations. We find that this method is able to decrease the uncertainty in the BAO peak position by 30-50% over the typical angular resolution scales of 21 cm intensity mapping experiments.

We examine the fraction of massive (M∗>1010M⊙), compact star-forming galaxies (cSFGs) that host an active galactic nucleus (AGN) at z∼2. These cSFGs are likely the direct progenitors of the compact quiescent galaxies observed at this epoch, which are the first population of passive galaxies to appear in large numbers in the early Universe. We identify cSFGs that host an AGN using a combination of Hubble WFC3 imaging and Chandra X-ray observations in four fields: the Chandra Deep Fields, the Extended Groth Strip, and the UKIDSS Ultra Deep Survey field. We find that 39.2+3.9−3.6\% (65/166) of cSFGs at 1.4<z<3.0 host an X-ray detected AGN. This fraction is 3.2 times higher than the incidence of AGN in extended star-forming galaxies with similar masses at these redshifts. This difference is significant at the 6.2σ level. Our results are consistent with models in which cSFGs are formed through a dissipative contraction that triggers a compact starburst and concurrent growth of the central black hole. We also discuss our findings in the context of cosmological galaxy evolution simulations that require feedback energy to rapidly quench cSFGs. We show that the AGN fraction peaks precisely where energy injection is needed to reproduce the decline in the number density of cSFGs with redshift. Our results suggest that the first abundant population of massive, quenched galaxies emerged directly following a phase of elevated supermassive black hole growth and further hints at a possible connection between AGN and the rapid quenching of star formation in these galaxies.

Background: Inflammatory bowel diseases (IBD) are believed to be driven by dysregulated interactions between the host and the gut microbiota. Our goal is to characterize and infer relationships between mucosal T cells, the host tissue environment, and microbial communities in patients with IBD who will serve as basis for mechanistic studies on human IBD.

Methods: We characterized mucosal CD4+ T cells using flow cytometry, along with matching mucosal global gene expression and microbial communities data from 35 pinch biopsy samples from patients with IBD. We analyzed these data sets using an integrated framework to identify predictors of inflammatory states and then reproduced some of the putative relationships formed among these predictors by analyzing data from the pediatric RISK cohort.

Results: We identified 26 predictors from our combined data set that were effective in distinguishing between regions of the intestine undergoing active inflammation and regions that were normal. Network analysis on these 26 predictors revealed SAA1 as the most connected node linking the abundance of the genus Bacteroides with the production of IL17 and IL22 by CD4+ T cells. These SAA1-linked microbial and transcriptome interactions were further reproduced with data from the pediatric IBD RISK cohort.

Conclusions: This study identifies expression of SAA1 as an important link between mucosal T cells, microbial communities, and their tissue environment in patients with IBD. A combination of T cell effector function data, gene expression and microbial profiling can distinguish between intestinal inflammatory states in IBD regardless of disease types.

Future high-resolution measurements of the cosmic microwave background (CMB) will produce catalogs of tens of thousands of galaxy clusters through the thermal Sunyaev-Zel'dovich (tSZ) effect. We forecast how well different configurations of a CMB Stage-4 experiment can constrain cosmological parameters, in particular the amplitude of structure as a function of redshift σ8(z), the sum of neutrino masses Σmν, and the dark energy equation of state w(z). A key element of this effort is calibrating the tSZ scaling relation by measuring the lensing signal around clusters. We examine how the mass calibration from future optical surveys like the Large Synoptic Survey (LSST) compares with a purely internal calibration using lensing of the CMB itself. We find that, due to its high-redshift leverage, internal calibration gives constraints on cosmological parameters comparable to the optical calibration, and can be used as a cross-check of systematics in the optical measurement. We also show that in contrast to the constraints using the CMB lensing power spectrum, lensing-calibrated tSZ cluster counts can detect a minimal Σmν at the 3-5σ level even when the dark energy equation of state is freed up.

We develop the first algorithm able to jointly compute the maximum {\it a posteriori} estimate of the Cosmic Microwave Background (CMB) temperature and polarization fields, the gravitational potential by which they are lensed, and cosmological parameters such as the tensor-to-scalar ratio, r. This is an important step towards sampling from the joint posterior probability function of these quantities, which, assuming Gaussianity of the CMB fields and lensing potential, contains all available cosmological information and would yield theoretically optimal constraints. Attaining such optimal constraints will be crucial for next-generation CMB surveys like CMB-S4, where limits on r could be improved by factors of a few over currently used sub-optimal quadratic estimators. The maximization procedure described here depends on a newly developed lensing algorithm, which we term \textsc{LenseFlow}, and which lenses a map by solving a system of ordinary differential equations. This description has conceptual advantages, such as allowing us to give a simple non-perturbative proof that the lensing determinant is equal to unity in the weak-lensing regime. The algorithm itself maintains this property even on pixelized maps, which is crucial for our purposes and unique to \textsc{LenseFlow} as compared to other lensing algorithms we have tested. It also has other useful properties such as that it can be trivially inverted (i.e. delensing) for the same computational cost as the forward operation, and can be used to compute lensing adjoint, Jacobian, and Hessian operators. We test and validate the maximization procedure on flat-sky simulations covering up to 600\,deg2 with non-uniform noise and masking.

We derive the reciprocal cluster mean-field method to study the strongly interacting bosonic Harper-Hofstadter-Mott model. The system exhibits a rich phase diagram featuring band insulating, striped superfluid, and supersolid phases. Furthermore, for finite hopping anisotropy, we observe gapless uncondensed liquid phases at integer fillings, which are analyzed by exact diagonalization. The liquid phases at fillings ν = 1, 3 exhibit the same band fillings as the fermionic integer quantum Hall effect, while the phase at ν = 2 is CT-symmetric with zero charge response. We discuss how these phases become gapped on a quasi-one-dimensional cylinder, leading to a quantized Hall response, which we characterize by introducing a suitable measure for nontrivial many-body topological properties. Incompressible metastable states at fractional filling are also observed, indicating competing fractional quantum Hall phases. The combination of reciprocal cluster mean-field and exact diagonalization yields a promising method to analyze the properties of bosonic lattice systems with nontrivial unit cells in the thermodynamic limit.