Publications

We derive here a new highly selective photoelectron-based chirality-sensing technique that utilizes 'locally-chiral' laser pulses. We show that this approach results in strong chiral discrimination, where the standard forwards/backwards asymmetry of photoelectron circular dichroism (PECD) is lifted. The resulting dichroism is much larger and more robust than conventional PECD, is found in all hemispheres, and is not symmetric or antisymmetric with respect to any symmetry operator. Remarkably, a CD of up to 10 percent survives in the angularly-integrated above-threshold ionization (ATI) spectra, and of up to 5 percent in the total ionization rates. We demonstrate these results through ab-initio calculations in the chiral molecules Bromochlorofluoromethane, Limonene, Fenchone, and Camphor. We also explore the parameter-space of the locally-chiral field and show that the observed CD is strongly correlated to the degree of chirality of the light, validating it as a measure for chiral-interaction strengths. Our results pave the way for highly selective probing of ultrafast chirality in ATI, can potentially lead to all-optical enantio-separation, and motivate the use of locally-chiral light for enhancing ultrafast spectroscopies.

Cavity modification of material properties and phenomena is a novel research field largely motivated by the advances in strong light-matter interactions. Despite this progress, exact solutions for extended systems strongly coupled to the photon field are not available, and both theory and experiments rely mainly on finite-system models. Therefore a paradigmatic example of an exactly solvable extended system in a cavity becomes highly desireable. To fill this gap we revisit Sommerfeld's theory of the free electron gas in cavity quantum electrodynamics (QED). We solve this system analytically in the long-wavelength limit for an arbitrary number of non-interacting electrons, and we demonstrate that the electron-photon ground state is a Fermi liquid which contains virtual photons. In contrast to models of finite systems, no ground state exists if the diamagentic

Fermi surface is at the heart of our understanding of metals and strongly correlated many-body systems. An abrupt change in the Fermi surface topology, also called Lifshitz transition, can lead to the emergence of fascinating phenomena like colossal magnetoresistance and superconductivity. While Lifshitz transitions have been demonstrated for a broad range of materials by equilibrium tuning of macroscopic parameters such as strain, doping, pressure and temperature, a non-equilibrium dynamical route toward ultrafast modification of the Fermi surface topology has not been experimentally demonstrated. Combining time-resolved multidimensional photoemission spectroscopy with state-of-the-art TDDFT+U simulations, we introduce a novel scheme for driving an ultrafast Lifshitz transition in the correlated type-II Weyl semimetal T

Electronic materials properties are determined by the interplay of many competing factors. Electro-magnetic fields strong enough to rival atomic interactions can disturb the balance between kinematic effects due to electrons hopping between lattice sites and the Coulomb repulsion between electrons that limits the band formation. This allows for new insights into quantum phases, as well as the time-scales and energies involved in using quantum effects for possible applications. Here we show that 0.2 V/Å ultrashort optical fields in the high harmonic generation regime lead to a pronounced transient inter-site charge transfer in NiO, a prototypical correlated electron insulator. Element-specific transient x-ray absorption spectroscopy detects a negligible change in electron correlations of Ni 3d-states. This behaviour is captured by time-dependent density functional theory and points to a speed limit for the dynamical screening of the Coulomb interaction taking place above our experimental 6.9 femtoseconds optical cycle.

Graphene moiré superlattices display electronic flat bands. At integer fillings of these flat bands, energy gaps due to strong electron-electron interactions are generally observed. However, the presence of other correlation-driven phases in twisted graphitic systems at non-integer fillings is unclear. Here, we report scanning tunneling microscopy (STM) measurements that reveal the existence of threefold rotational (C3) symmetry breaking in twisted double bilayer graphene (tDBG). Using spectroscopic imaging over large and uniform areas to characterize the direction and degree of C3 symmetry breaking, we find it to be prominent only at energies corresponding to the flat bands and nearly absent in the remote bands. We demonstrate that the C3 symmetry breaking cannot be explained by heterostrain or the displacement field, and is instead a manifestation of an interaction-driven electronic nematic phase, which emerges even away from integer fillings. Comparing our experimental data with a combination of microscopic and phenomenological modeling, we show that the nematic instability is not associated with the local scale of the graphene lattice, but is an emergent phenomenon at the scale of the moiré lattice, pointing to the universal character of this ordered state in flat band moiré materials.

We study an interacting quantum dot in contact with a small superconducting island described by the interacting pairing model with charging (Coulomb) energy E

Over the past years, machine learning has emerged as a powerful computational tool to tackle complex problems over a broad range of scientific disciplines. In particular, artificial neural networks have been successfully deployed to mitigate the exponential complexity often encountered in quantum many-body physics, the study of properties of quantum systems built out of a large number of interacting particles. In this Article, we overview some applications of machine learning in condensed matter physics and quantum information, with particular emphasis on hands-on tutorials serving as a quick-start for a newcomer to the field. We present supervised machine learning with convolutional neural networks to learn a phase transition, unsupervised learning with restricted Boltzmann machines to perform quantum tomography, and variational Monte Carlo with recurrent neural-networks for approximating the ground state of a many-body Hamiltonian. We briefly review the key ingredients of each algorithm and their corresponding neural-network implementation, and show numerical experiments for a system of interacting Rydberg atoms in two dimensions.