Observation of many-body Fock space dynamics in two dimensions

Quantum many-body simulation provides a straightforward way to understand fundamental physics and connect with quantum information applications. However, suffering from exponentially growing Hilbert space size, characterization in terms of few-body probes in real space is often insufficient to tackle challenging problems such as quantum critical behavior and many-body localization (MBL) in higher dimensions. Here, we experimentally employ a new paradigm on a superconducting quantum processor, exploring such elusive questions from a Fock space view: mapping the many-body system onto an unconventional Anderson model on a complex Fock space network of many-body states. By observing the wave packet propagating in Fock space and the emergence of a statistical ergodic ensemble, we reveal a fresh picture for characterizing representative many-body dynamics: thermalization, localization, and scarring. In addition, we observe a quantum critical regime of anomalously enhanced wave packet width and deduce a critical point from the maximum wave packet fluctuations, which lend support for the two-dimensional MBL transition in finite-sized systems. Our work unveils a new perspective of exploring many-body physics in Fock space, demonstrating its practical applications on contentious MBL aspects such as criticality and dimensionality. Moreover, the entire protocol is universal and scalable, paving the way to finally solve a broader range of controversial many-body problems on future larger quantum devices.Comment: 8 pages, 4 figures + supplementary informatio

Tuning the Growth and Mechanical Properties of Calcite Using Impurities: Insight from Molecular Simulation

Over many millions of years, evolution has provided living organisms with the tools to control the growth and properties of materials from the molecular scale upward. One of the many ways this is achieved is through the introduction of impurities into the solution in which these materials grow. A long-term goal of materials scientists is to harness nature's control mechanisms and apply them in the world of engineering. However, these mechanisms of growth control are highly complex, and understanding them requires insight into physical processes at the molecular scale. While experiments are so-far unable to offer such a high resolution, computer simulations can be used to directly model these physical process with no limit on the resolution. Throughout this thesis, an array of computational methodologies is applied to calcite in an attempt to understand how impurities are able to drive the growth process, and ultimately alter the mechanical properties of the crystal. A series of metadynamics simulations are applied to calcite kink sites, revealing a more complex growth mechanism in which kink-terminating ions do not initially occupy their crystal lattice sites, and only do so upon the adsorption of an additional solute. A combination of metadynamics and Kinetic Monte Carlo simulations are used to examine the adsorption free energies and growth inhibiting properties of amino acids and polyamines, the results of which are compared directly to experiment. This offers a robust insight into the molecular mechanisms that underpin how organic molecules are able to tune the growth of calcite. Simulations are also applied to two case studies of impure calcite. By examining lattice spacings, determining stress distributions and simulating a series of crack propagation events, insight into mechanisms through which biogenic crystals exhibit superior mechanical properties is found. Finally, the nature of non-Markovianity when using reaction coordinates -such as those used in rare event methodologies applied throughout this thesis- are investigated. By introducing non-Markovianity into the system, barrier crossing rates in a coarse-grained system more closely resemble those in the original two-dimensional system. Furthermore, we study the breakdown in rare-events sampling when a poor reaction coordinate is used, and identify which rare-events sampling techniques are more appropriate for detecting poor reaction coordinate choices