Entanglement in the Dicke model

We show how an ion trap, configured for the coherent manipulation of external and internal quantum states, can be used to simulate the irreversible dynamics of a collective angular momentum model known as the Dicke model. In the special case of two ions, we show that entanglement is created in the coherently driven steady state with linear driving. For the case of more than two ions we calculate the entanglement between two ions in the steady state of the Dicke model by tracing over all the other ions. The entanglement in the steady state is a maximum for the parameter values corresponding roughly to a bifurcation of a fixed point in the corresponding semiclassical dynamics. We conjecture that this is a general mechanism for entanglement creation in driven dissipative quantum systems.Comment: Minor changes: Reference added and references correcte

On Communication Complexity in Evolution-Communication P Systems

Looking for a theory of communication complexity for P systems, we consider here so-called evolution-communication (EC for short) P systems, where objects evolve by multiset rewriting rules without target commands and pass through membranes by means of symport/antiport rules. (Actually, in most cases below we use only symport rules.) We first propose a way to measure the communication costs by means of “quanta of energy” (produced by evolution rules and) consumed by communication rules. EC P systems with such costs are proved to be Turing complete in all three cases with respect to the relation between evolution and communication operations: priority of communication, mixing the rules without priority for any type, priority of evolution (with the cost of communication increasing in this ordering in the universality proofs). More appropriate measures of communication complexity are then defined, as dynamical parameters, counting the communication steps or the number (and the weight) of communication rules used during a computation. Such parameters can be used in three ways: as properties of P systems (considering the families of sets of numbers generated by systems with a given communication complexity), as conditions to be imposed on computations (accepting only those computations with a communication complexity bounded by a given threshold), and as standard complexity measures (defining the class of problems which can be solved by P systems with a bounded complexity). Because we ignore the evolution steps, in all three cases it makes sense to consider hierarchies starting with finite complexity thresholds. We only give some preliminary results about these hierarchies (for instance, proving that already their lower levels contain complex – e.g., non-semilinear – sets), and we leave open many problems and research issues.Junta de Andalucía P08 – TIC 0420

Symmetry-enhanced supertransfer of delocalized quantum states

Coherent hopping of excitation rely on quantum coherence over physically extended states. In this work, we consider simple models to examine the effect of symmetries of delocalized multi-excitation states on the dynamical timescales, including hopping rates, radiative decay, and environmental interactions. While the decoherence (pure dephasing) rate of an extended state over N sites is comparable to that of a non-extended state, superradiance leads to a factor of N enhancement in decay and absorption rates. In addition to superradiance, we illustrate how the multi-excitonic states exhibit `supertransfer' in the far-field regime: hopping from a symmetrized state over N sites to a symmetrized state over M sites at a rate proportional to MN. We argue that such symmetries could play an operational role in physical systems based on the competition between symmetry-enhanced interactions and localized inhomogeneities and environmental interactions that destroy symmetry. As an example, we propose that supertransfer and coherent hopping play a role in recent observations of anomolously long diffusion lengths in nano-engineered assembly of light-harvesting complexes.Comment: 6 page

QDQD-Learning: A Collaborative Distributed Strategy for Multi-Agent Reinforcement Learning Through Consensus + Innovations

The paper considers a class of multi-agent Markov decision processes (MDPs), in which the network agents respond differently (as manifested by the instantaneous one-stage random costs) to a global controlled state and the control actions of a remote controller. The paper investigates a distributed reinforcement learning setup with no prior information on the global state transition and local agent cost statistics. Specifically, with the agents' objective consisting of minimizing a network-averaged infinite horizon discounted cost, the paper proposes a distributed version of $Q$-learning, $\mathcal{QD}$-learning, in which the network agents collaborate by means of local processing and mutual information exchange over a sparse (possibly stochastic) communication network to achieve the network goal. Under the assumption that each agent is only aware of its local online cost data and the inter-agent communication network is \emph{weakly} connected, the proposed distributed scheme is almost surely (a.s.) shown to yield asymptotically the desired value function and the optimal stationary control policy at each network agent. The analytical techniques developed in the paper to address the mixed time-scale stochastic dynamics of the \emph{consensus + innovations} form, which arise as a result of the proposed interactive distributed scheme, are of independent interest.Comment: Submitted to the IEEE Transactions on Signal Processing, 33 page