Publications
Steering self-organisation through confinement
Self-organisation is the spontaneous emergence of spatio-temporal structures and patterns from the interaction of smaller individual units. Examples are found across many scales in very different systems and scientific disciplines, from physics, materials science and robotics to biology, geophysics and astronomy. Recent research has highlighted how self-organisation can be both mediated and controlled by confinement.
A Drift-Diffusion Based Modeling and Optimization Framework for Nanoscale Spin-Orbit Torque Devices
We present a comprehensive set of experimentally validated/calibrated models that capture the physics of the nanoscale spin-orbit torque (SOT) devices. We consider various effects that are prominent at nanoscale including incomplete current redistribution, interface spin mixing, and nonuniform resistivity that were ignored in the prior modeling efforts. We develop a formalism based on drift-diffusion equations and the transfer matrix method to accurately estimate spin current distribution.
Exciton density waves in Coulomb-coupled dual moiré lattices
Strongly correlated bosons in a lattice are a platform that can realize rich bosonic states of matter and quantum phase transitions1. While strongly correlated bosons in a lattice have been studied in cold-atom experiments2–4, their realization in a solid-state system has remained challenging5. Here we trap interlayer excitons–bosons composed of bound electron–hole pairs, in a lattice provided by an angle-aligned WS2/bilayer WSe2/WS2 multilayer. The heterostructure supports Coulomb-coupled triangular moiré lattices of nearly identical period at the top and bottom interfaces.
Measurement-induced entanglement transitions in quantum circuits of non-interacting fermions: Born-rule versus forced measurements
Machine learning discovery of new phases in programmable quantum simulator snapshots
Machine learning has recently emerged as a promising approach for studying complex phenomena characterized by rich datasets. In particular, data-centric approaches lead to the possibility of automatically discovering structures in experimental datasets that manual inspection may miss. Here, we introduce an interpretable unsupervised-supervised hybrid machine learning approach, the hybrid-correlation convolutional neural network (hybrid-CCNN), and apply it to experimental data generated using a programmable quantum simulator based on Rydberg atom arrays.
Fractionalization and Topology in Amorphous Electronic Solids
Band topology is traditionally analyzed in terms of gauge-invariant observables associated with crystalline Bloch wave functions. Recent work has demonstrated that many of the free fermion topological characteristics survive even in an amorphous setting. In this Letter, we extend these studies to incorporate the effect of strong repulsive interactions on the fate of topology and other correlation induced phenomena.
Supercooling of the A phase of 3He
Because of the extreme purity, lack of disorder, and complex order parameter, the first-order superfluid 3He A–B transition is the leading model system for first order transitions in the early universe. Here we report on the path dependence of the supercooling of the A phase over a wide range of pressures below 29.3 bar at nearly zero magnetic field. The A phase can be cooled significantly below the thermodynamic A–B transition temperature.
Intermediate-scale theory for electrons coupled to frustrated local moments
A classic route for destroying long-lived electronic quasiparticles in a weakly interacting Fermi liquid is to couple them to other low-energy degrees of freedom that effectively act as a bath. We consider here the problem of electrons scattering off the spin fluctuations of a geometrically frustrated antiferromagnet, whose nonlinear Landau-Lifshitz dynamics, which remains nontrivial at all temperatures, we model in detail.
Conceptual understanding of sources of uncertainty: A new perspective on classifying student thinking about measurement
Determining biomolecular structures near room temperature using X-ray crystallography: Concepts, methods and future optimization
For roughly two decades, cryocrystallography has been the overwhelmingly dominant method for determining high-resolution biomolecular structures.