Emerging Correlations from Strong Driving: A Tensor Network Projection Variational Monte Carlo Approach to 2D Quantum Lattice Systems

  • Clark, Stephen (PI)

Project: Research council

Project Details


Much of the technology we have is based on exploiting special materials like semiconductors. The next revolution is likely to emerge from so-called quantum materials. However, while their behaviour has the potential to be extremely useful, it is also complex to understand and control. Insights gained from this research will help determine the viability of controlling quantum materials with light and the possible exploitation of dynamical non-equilibrium properties in future nano-devices.

Controlling materials with light is interesting because it is well known that driven systems can exhibit behaviour not seen when stationary. There are two simple examples of this. The first is a so-called Kapitza pendulum. This is a normal pendulum whose pivot point undergoes vertical oscillations that are rapid but small in amplitude. What is striking about this pendulum is that the inverted position, normally unstable to gravity, is dynamically stabilised by the periodic driving. The second is a ball on a rotating saddle. The ball cannot be stably positioned at the inflection point when the saddle is stationary. However, if the saddle is rotated above some threshold angular velocity then the ball can be balanced in the time-averaged bowl swept out by the saddle. The same ideas apply to many-body systems like materials and it is becoming increasingly relevant to study their behaviour.

An important class of many-body systems are those that exhibit strong correlations due to interactions between their constituents. The everyday world is full of such systems. For example traffic jams form along roads due to a combination of many vehicles and a strong repulsion between them to avoid occupying the same piece of road. However, ants marching in a line never suffer from such traffic jams despite facing very similar restrictions because they don't overtake one another. These two examples demonstrate how subtle differences in the precise microscopic nature of interactions may lead to qualitatively different macroscopic properties. Describing such correlations poses major challenges for the theoretical study of interacting systems, and no more so than for the case of quantum systems. In the quantum case strong interactions lead to some of the least well-understood phenomena of condensed matter, like high-Tc superconductivity, frustration, and topological phases such as fractional quantum Hall physics. These effects only appear at low temperatures and typically in materials with a dominant two-dimensional character.

Since quantum materials exhibit functional properties there is a major research effort to stabilise and optimise them at higher temperatures for future technological applications. A recent approach to this is to periodically drive a many-body quantum system to "dynamically stabilise" macroscopic quantum effects beyond where they occur in equilibrium. The question is made even more compelling by spectacular advances in high-field THz generation technology. This allows selective driving of low-energy excitations of real solids, like vibrations, enabling a crystal lattice to be shaken, modulated or distorted in controlled ways. This has created an exciting interface between driven systems and many-body physics engaging a large body of researchers worldwide.

A crucial issue hampering the use of periodic driving in engineering materials is heating that might wash out the desired effects. This project examines this problem within the context of one of the most important model Hamiltonians, the Hubbard model, which captures the essential physics of strong correlations. Current numerical methods struggle to give a conclusive answer to this issue. A unique feature of this project will be the development of a combined Monte Carlo and tensor network approach potentially rich enough to accurately describe the dynamical behaviour of the driven Hubbard model. The resulting high performance software will be publically available.
Effective start/end date1/08/1731/07/19


  • Engineering and Physical Sciences Research Council


Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.