Publications

Departures of the energy spectrum of the cosmic microwave background (CMB) from a perfect blackbody probe a fundamental property of the universe -- its thermal history. Current upper limits, dating back some 25 years, limit such spectral distortions to 50 parts per million and provide a foundation for the Hot Big Bang model of the early universe. Modern upgrades to the 1980's-era technology behind these limits enable three orders of magnitude or greater improvement in sensitivity. The standard cosmological model provides compelling targets at this sensitivity, spanning cosmic history from the decay of primordial density perturbations to the role of baryonic feedback in structure formation. Fully utilizing this sensitivity requires concurrent improvements in our understanding of competing astrophysical foregrounds. We outline a program using proven technologies capable of detecting the minimal predicted distortions even for worst-case foreground scenarios.

Moiré engineering has recently emerged as a capable approach to control quantum phenomena in condensed matter systems. In van der Waals heterostructures, moiré patterns can be formed by lattice misorientation between adjacent atomic layers, creating long range electronic order. To date, moiré engineering has been executed solely in stacked van der Waals multilayers. Herein, we describe our discovery of electronic moiré patterns in films of a prototypical magnetoresistive oxide La0.67Sr0.33MnO3 (LSMO) epitaxially grown on LaAlO3 (LAO) substrates. Using scanning probe nano-imaging, we observe microscopic moiré profiles attributed to the coexistence and interaction of two distinct incommensurate patterns of strain modulation within these films. The net effect is that both electronic conductivity and ferromagnetism of LSMO are modulated by periodic moiré textures extending over mesoscopic scales. Our work provides an entirely new route with potential to achieve spatially patterned electronic textures on demand in strained epitaxial materials.

Upon chemical substitution of oxygen with fluor, LaMnAsO has been electron-doped in experiments, resulting in samples with remarkably high Seebeck coefficients of around −300 μV/K at room temperature and 3% doping. Within the framework of density functional theory plus dynamical mean-field theory (DFT+DMFT) we not only are able to reproduce these experimental observations, but also can provide a thorough investigation of the underlying mechanisms. By considering electronic correlations in the half-filled Mn-3d shells, we trace the high Seebeck coefficient back to an asymmetry in the spectral function, which is due to the emergence of an incoherent spectral weight under doping and a strong renormalization of the unoccupied states. This is only possible in correlated systems and cannot be explained by DFT-based band structure calculations.

We explore the structure of the element abundance--age--orbit distribution of the stars in the Milky Way's low-α disk, by (re-)deriving precise [Fe/H], [X/Fe] and ages, along with orbits, for red clump stars from the APOGEE survey. There has been a long-standing theoretical expectation and observational evidence that metallicity ([Fe/H]) and age are informative about a star's orbit, e.g. about its angular momentum and the corresponding mean Galactocentric distance or its vertical motion. Indeed, our analysis of the APOGEE data confirms that [Fe/H] or age alone can predict the stars' orbits far less well than the combination of the two. Remarkably, we find and show explicitly, that for known [Fe/H] and age, the other abundances [X/Fe] of Galactic disk stars can be predicted well (on average to 0.02 dex) across a wide range of Galactocentric radii, and therefore provide little additional information, e.g. for predicting their orbit. While the age-abundance space for metal poor stars and potentially for stars near the Galactic center is rich or complex, for the bulk of the Galaxy's low-α disk it is simple: [Fe/H] and age contain most information, unless [X/Fe] can be measured to 0.02, or better. Consequently, we do not have the precision with current (and likely near-future) data to assign stars to their individual (coeval) birth clusters, from which the disk is presumably formed. We can, however, place strong constraints on future models of galactic evolution, chemical enrichment and mixing.

We propose a solution to the problem of Bloch electrons in a homogeneous magnetic field by including the quantum fluctuations of the photon field. A generalized quantum electrodynamical (QED)-Bloch theory from first principles is presented. In the limit of vanishing quantum fluctuations, we recover the standard results of solid-state physics: the fractal spectrum of the Hofstadter butterfly. As a further application, we show how the well-known Landau physics is modified by the photon field and that Landau polaritons emerge. This shows that our QED-Bloch theory does not only allow us to capture the physics of solid-state systems in homogeneous magnetic fields but also novel features that appear at the interface of condensed matter physics and quantum optics.

We describe how to incorporate symmetries of the Hamiltonian into auxiliary-field quantum Monte Carlo calculations (AFQMC). Focusing on the case of Abelian symmetries, we show that the computational cost of most steps of an AFQMC calculation is reduced by $N_k^{-1}$, where $N_k$ is the number of irreducible representations of the symmetry group. We apply the formalism to a molecular system as well as to several crystalline solids. In the latter case, the lattice translational group provides increasing savings as the number of k points is increased, which is important in enabling calculations that approach the thermodynamic limit. The extension to non-Abelian symmetries is briefly discussed.

We study the dynamics of charge transfer insulators after photoexcitation using the three-band Emery model and a nonequilibrium extension of
Hartree
−
Fock
+
EDMFT
(extended dynamical mean field theory) and
GW
+
EDMFT
. While the equilibrium properties are accurately reproduced by the Hartree-Fock treatment of the ligand bands, dynamical correlations are essential for a proper description of the photodoped state. Photodoping leads to a renormalization of the charge transfer gap and to a substantial broadening of the bands. We calculate the time-resolved photoemission spectrum and optical conductivity and find qualitative agreement with experiments. Our formalism enables the realistic description of nonequilibrium phenomena in materials with ligand bands. It provides a tool to explore the optical manipulation of interaction and correlation effects, including insulator-metal and magnetic transitions.

We present a statistical learning framework for robust identification of partial differential equations from noisy spatiotemporal data. Extending previous sparse regression approaches for inferring PDE models from simulated data, we address key issues that have thus far limited the application of these methods to noisy experimental data, namely their robustness against noise and the need for manual parameter tuning. We address both points by proposing a stability-based model selection scheme to determine the level of regularization required for reproducible recovery of the underlying PDE. This avoids manual parameter tuning and provides a principled way to improve the method's robustness against noise in the data. Our stability selection approach, termed PDE-STRIDE, can be combined with any sparsity-promoting penalized regression model and provides an interpretable criterion for model component importance. We show that in particular the combination of stability selection with the iterative hard-thresholding algorithm from compressed sensing provides a fast, parameter-free, and robust computational framework for PDE inference that outperforms previous algorithmic approaches with respect to recovery accuracy, amount of data required, and robustness to noise. We illustrate the performance of our approach on a wide range of noise-corrupted simulated benchmark problems, including 1D Burgers, 2D vorticity-transport, and 3D reaction-diffusion problems. We demonstrate the practical applicability of our method on real-world data by considering a purely data-driven re-evaluation of the advective triggering hypothesis for an embryonic polarization system in C. elegans. Using fluorescence microscopy images of C. elegans zygotes as input data, our framework is able to recover the PDE model for the regulatory reaction-diffusion-flow network of the associated proteins.

The Simons Observatory (SO) is a ground-based cosmic microwave background (CMB) experiment sited on Cerro Toco in the Atacama Desert in Chile that promises to provide breakthrough discoveries in fundamental physics, cosmology, and astrophysics. Supported by the Simons Foundation, the Heising-Simons Foundation, and with contributions from collaborating institutions, SO will see first light in 2021 and start a five year survey in 2022. SO has 287 collaborators from 12 countries and 53 institutions, including 85 students and 90 postdocs.
The SO experiment in its currently funded form ('SO-Nominal') consists of three 0.4 m Small Aperture Telescopes (SATs) and one 6 m Large Aperture Telescope (LAT). Optimized for minimizing systematic errors in polarization measurements at large angular scales, the SATs will perform a deep, degree-scale survey of 10% of the sky to search for the signature of primordial gravitational waves. The LAT will survey 40% of the sky with arc-minute resolution. These observations will measure (or limit) the sum of neutrino masses, search for light relics, measure the early behavior of Dark Energy, and refine our understanding of the intergalactic medium, clusters and the role of feedback in galaxy formation.
With up to ten times the sensitivity and five times the angular resolution of the Planck satellite, and roughly an order of magnitude increase in mapping speed over currently operating ("Stage 3") experiments, SO will measure the CMB temperature and polarization fluctuations to exquisite precision in six frequency bands from 27 to 280 GHz. SO will rapidly advance CMB science while informing the design of future observatories such as CMB-S4.

As we enter a new era of quantum technology, it is increasingly important to develop methods to aid in the accurate preparation of quantum states for a variety of materials, matter, and devices. Computational techniques can be used to reconstruct a state from data, however the growing number of qubits demands ongoing algorithmic advances in order to keep pace with experiments. In this paper, we present an open-source software package called QuCumber that uses machine learning to reconstruct a quantum state consistent with a set of projective measurements. QuCumber uses a restricted Boltzmann machine to efficiently represent the quantum wavefunction for a large number of qubits. New measurements can be generated from the machine to obtain physical observables not easily accessible from the original data.