Publications

We develop a density-matrix renormalization group (DMRG) algorithm for the simulation of quantum circuits. This algorithm can be seen as the extension of the time-dependent DMRG from the usual situation of Hermitian Hamiltonian matrices to quantum circuits defined by unitary matrices. For small circuit depths, the technique is exact and equivalent to other matrix product state–based techniques. For larger depths, it becomes approximate in exchange for an exponential speed up in computational time. Like an actual quantum computer, the quality of the DMRG results is characterized by a finite fidelity. However, unlike a quantum computer, the fidelity depends strongly on the quantum circuit considered. For the most difficult possible circuit for this technique, the so-called "quantum supremacy" benchmark of Google LLC [Arute et al., Nature 574, 505 (2019)], we find that the DMRG algorithm can generate bit strings of the same quality as the seminal Google experiment on a single computing core. For a more structured circuit used for combinatorial optimization (quantum approximate optimization algorithm), we find a drastic improvement of the DMRG results with error rates dropping by a factor of 100 compared with random quantum circuits. Our results suggest that the current bottleneck of quantum computers is their fidelities rather than the number of qubits.

A major challenge in ART is to select high-quality oocytes and embryos. The metabolism of oocytes and embryos has long been linked to their viability, suggesting the potential utility of metabolic measurements to aid in selection. Here, we review recent work on noninvasive metabolic imaging of cumulus cells, oocytes, and embryos. We focus our discussion on fluorescence lifetime imaging microscopy (FLIM) of the autofluorescent coenzymes NAD(P)H and flavine adenine dinucleotide (FAD+), which play central roles in many metabolic pathways. FLIM measurements provide quantitative information on NAD(P)H and FAD+ concentrations and engagement with enzymes, leading to a robust means of characterizing the metabolic state of cells. We argue that FLIM is a promising approach to aid in oocyte and embryo selection.

Systems neuroscientists seek a mechanistic and computational understanding of neural activity. In the visual system, the jump from sub-cortical to cortical brings about many important changes in representation and circuitry. By focusing on the important transformation of spatial information between thalamus and cortex, this work provides a better understanding of the computations that underlie visual processing. We performed a series of experiments in anesthetized primates, recording from individual neurons in the lateral geniculate nucleus (LGN) of the thalamus and the primary visual cortex (V1) using single grating stimuli and mixtures of gratings. To make sense of these different recordings, we fit the measured responses to both mechanistic and more computational models.
In the first chapter, we bring together previous accounts - in both the LGN and in V1 - of shifts in spatial frequency tuning with image contrast. We use a common stimulus set comprised of sinusoidal gratings that vary in spatial frequency and contrast. Fitting canonical, mechanistic models which capture our understanding of each area's receptive field structure, we show that the tuning shifts in V1 are larger than those in the LGN. This result suggests that shifts in LGN selectivity are inherited in V1, but further intracortical processing contributes to the more pronounced tuning shifts.

In the second and third chapters, we turn our focus to stimuli of intermediate complexity. We used superimposed mixtures of gratings as well as a more direct masking experiment to measure the tuning of spatial frequency suppression. In the second chapter, we report stronger spatial frequency-dependent suppression in V1 than in LGN, and find that suppression is typically strongest for frequencies at or below the cell's preference. These stimulus sets were also designed to evoke a broad range of responses which help constrain our computational model of spatial frequency selectivity. In the third chapter, we fit this model to the observed neuronal responses. The model implements divisive normalization, a canonical computation in cortical processing that accounts for a wide variety of observed neural activity. In the standard model of normalization, the response of a given neuron is normalized by the activity of nearby neurons that are selective across a wide range of stimulus values and features. We show that introducing a spatial-frequency tuned weighting of the normalization signal can preserve gain control while also better accounting for shifts in spatial frequency tuning and the observed suppression to complex stimuli. The tuning of the normalization was typically found to be stronger for frequencies below the cell’s peak, highlighting the role of low frequency suppression in shaping selectivity.

This paper presents a simple formalism for calculating X-ray absorption (XAS) and resonant inelastic x-ray scattering (RIXS) that has as input orbital-resolved density of states from a single-particle or many-body

Thin films of the solid solution NdLaNiO3 are grown in order to study the expected 0 K phase transitions at a specific composition. We experimentally map out the structural, electronic and magnetic properties as a function of x and a discontinuous, possibly first order, insulator–metal transition is observed at low temperature when x = 0.2. Raman spectroscopy and scanning transmission electron microscopy show that this is not associated with a correspondingly discontinuous global structural change. On the other hand, results from density functional theory (DFT) and combined DFT and dynamical mean field theory calculations produce a 0 K first order transition at around this composition. We further estimate the temperature-dependence of the transition from thermodynamic considerations and find that a discontinuous insulator–metal transition can be reproduced theoretically and implies a narrow insulator–metal phase coexistence with x. Finally, muon spin rotation (µSR) measurements suggest that there are non-static magnetic moments in the system that may be understood in the context of the first order nature of the 0 K transition and its associated phase coexistence regime.

Dynamic manipulation of magnetism in topological materials is demonstrated here via a Floquet engineering approach using circularly polarized light. Increasing the strength of the laser field, besides the expected topological phase transition, the magnetically doped topological insulator thin film also undergoes a magnetic phase transition from ferromagnetism to paramagnetism, whose critical behavior strongly depends on the quantum quenching. In sharp contrast to the equilibrium case, the non-equilibrium Curie temperatures vary for different time scale and experimental setup, not all relying on change of topology. Our discoveries deepen the understanding of the relationship between topology and magnetism in the non-equilibrium regime and extend optoelectronic device applications to topological materials.

Floquet engineering consists in the modification of physical systems by the application of periodic time-dependent perturbations. The search for the shape of the periodic perturbation that best modifies the properties of a system in order to achieve some predefined metastable target behavior can be formulated as an optimal control problem. We discuss several ways to formulate and solve this problem. We present, as examples, some applications in the context of material science, although the methods discussed here are valid for any quantum system (from molecules and nanostructures to extended periodic and non periodic quantum materials). In particular, we show how one can achieve the manipulation of the Floquet pseudo-bandstructure of a transition metal dichalcogenide monolayer (MoS2).

The coupling of light to electrical charge carriers in semiconductors is the foundation of many technological applications. Attosecond transient absorption spectroscopy measures simultaneously how excited electrons and the vacancies they leave behind dynamically react to the applied optical fields. In compound semiconductors, these dynamics can be probed via any of their atomic constituents. Often, the atomic species forming the compound contribute comparably to the relevant electronic properties of the material. One therefore expects to observe similar dynamics, irrespective of the choice of atomic species via which it is probed. Here, we show in the two-dimensional transition metal dichalcogenide semiconductor MoSe

Quantum computing has emerged as a promising platform for simulating strongly correlated systems in chemistry, for which the standard quantum chemistry methods are either qualitatively inaccurate or too expensive. However, due to the hardware limitations of the available noisy near-term quantum devices, their application is currently limited only to small chemical systems. One way for extending the range of applicability can be achieved within the quantum embedding approach. Herein, we employ the projection-based embedding method for combining the variational quantum eigensolver (VQE) algorithm, although not limited to, with density functional theory (DFT). The developed VQE-in-DFT method is then implemented efficiently on a real quantum device and employed for simulating the triple bond breaking process in butyronitrile. The results presented herein show that the developed method is a promising approach for simulating systems with a strongly correlated fragment on a quantum computer. The developments as well as the accompanying implementation will benefit many different chemical areas including the computer aided drug design as well as the study of metalloenzymes with a strongly correlated fragment.

We present a semilocal exchange-correlation energy functional for noncollinear spin density functional theory based on short-range expansions of the spin-resolved exchange hole and the two-body density matrix. Our functional is explicitly derived for noncollinear magnetism, U(1) and SU(2) gauge invariant, and gives rise to nonvanishing exchange-correlation torques. Testing the functional for frustrated antiferromagnetic chromium clusters, the exchange part is shown to perform favorably compared to the far more expensive Slater and optimized effective potentials, and a delicate interplay between exchange and correlation torques is uncovered.