Condensed Matter Theory

Abstract:

We study fermionic quantum spin liquids (QSLs) on the three-dimensional trillium lattice of corner-sharing triangles. We are motivated by recent experimental and theoretical investigations that have explored various classical and quantum spin liquid states on similar networks of triangular motifs with strong geometric frustration. Using the framework of projective symmetry groups (PSG), we obtain a classification of all symmetric ${\mathsf{Z}}_2$ and $\mathsf{U}\left(1\right)$ QSLs on the trillium lattice. We find two ${\mathsf{Z}}_2$ spin-liquids, and a single $\mathsf{U}\left(1\right)$ spin-liquid that is proximate to one of the ${\mathsf{Z}}_2$ states. The small number of solutions reflects the constraints imposed by the nonsymmorphic symmetries in the space group of the trillium lattice. Using self-consistency conditions of the mean-field equations, we obtain the spinon band-structure and spin structure factors corresponding to these states. All three of our spin liquids are gapless at their saddle points: one of the two ${\mathsf{Z}}_2$ QSLs is nodal, while the $\mathsf{U}\left(1\right)$ case hosts a spinon Fermi surface. One of our ${\mathsf{Z}}_2$ spin liquids hosts a stable gapless nodal star that is protected by projective symmetries against additions of further neighbor terms in the mean-field ansatz. We comment on directions for further work.

Abstract:

Multifarious assembly models consider multiple structures assembled from a shared set of components, reflecting the efficient usage of components in biological self-assembly. These models are subject to a high-dimensional parameter space, with only a finite region of parameter space giving reliable self-assembly. Here, we use a continuous-time Gillespie simulation method to study multifarious self-assembly and find that the region of parameter space in which reliable self-assembly can be achieved is smaller than what was obtained previously using a discrete-time Monte Carlo simulation method. We explain this discrepancy through a detailed analysis of the stability of assembled structures against chimera formation. We find that our continuous-time simulations of multifarious self-assembly can expose this instability in large systems even at moderate simulation times. In contrast, discrete-time simulations are slow to show this instability, particularly for large system sizes. For the remaining state space, we find good agreement between the predictions of continuous- and discrete-time simulations. We present physical arguments that can help us predict the state boundaries in the parameter space and gain a deeper understanding of multifarious self-assembly.

Abstract:

In the context of self-assembly, where complex structures can be assembled from smaller units, it is desirable to devise strategies toward disassembly and reassembly processes that reuse the constituent parts. A non-reciprocal multifarious self-organization strategy has been recently introduced and shown to have the capacity to exhibit this complex property. In this work, we study the model using continuous-time Gillespie simulations and compare the results against discrete-time Monte Carlo simulations investigated previously. Furthermore, using the continuous-time simulations, we explore important features in our system, namely, the nucleation time and interface growth velocity, which comprise the timescale of shape-shifting. We develop analytical calculations for the associated timescales and compare the results to those measured in simulations, allowing us to pin down the key mechanisms behind the observed timescales at different parameter values.