Real-time dynamics of open quantum spin systems driven by dissipative processes

We study the real-time evolution of large open quantum spin systems in two spatial dimensions, whose dynamics is entirely driven by a dissipative coupling to the environment. We consider different dissipative processes and investigate the real-time evolution from an ordered phase of the Heisenberg or XY model towards a disordered phase at late times, disregarding unitary Hamiltonian dynamics. The corresponding Kossakowski-Lindblad equation is solved via an efficient cluster algorithm. We find that the symmetry of the dissipative process determines the time scales, which govern the approach towards a new equilibrium phase at late times. Most notably, we find a slow equilibration if the dissipative process conserves any of the magnetization Fourier modes. In these cases, the dynamics can be interpreted as a diffusion process of the conserved quantity.

Elucidating underlying processes of psychometric intelligence: A comparison of behavioral response latency and P3 latency in a modified Hick reaction time paradigm

The mental speed approach explains individual differences in intelligence by faster information processing in individuals with higher compared to lower intelligence - especially in elementary cognitive tasks (ECTs). One of the most examined ECTs is the Hick paradigm. The present study aimed to contrast reaction time (RT) and P3 latency in a Hick task as predictors of intelligence. Although both, RT and P3 latency, are commonly used as indicators of mental speed, it is also known that they measure different aspects of information processing. Participants were 113 female students. RT and P3 latency were measured while participants completed the Hick task with four levels of complexity. Intelligence was assessed with Cattell's Culture Fair Test. A RT factor and a P3 factor were extracted by employing a PCA across complexity levels. There was no significant correlation between the factors. Commonality analysis was used to determine the proportions of unique and shared variance in intelligence explained by the RT and P3 latency factors. RT and P3 latency explained 5.5% and 5% of unique variance in intelligence. However, the two speed factors did not explain a significant portion of shared variance. This result suggests that RT and P3 latency in the Hick paradigm are measuring different aspects of information processing that explain different parts of variance in intelligence.