A Deterministic and Nondestructively-Verifiable Photon Number Source

We present a deterministic approach based on continuous measurement and real-time quantum feedback control to prepare arbitrary photon number states of a cavity mode. The procedure passively monitors the number state actually achieved in each feedback stabilized measurement trajectory, thus providing a nondestructively verifiable photon source. The feasibility of a possible cavity QED implementation in the many-atom good-cavity coupling regime is analyzed

CAMMD: Context Aware Mobile Medical Devices

Telemedicine applications on a medical practitioners mobile device should be context-aware. This can vastly improve the effectiveness of mobile applications and is a step towards realising the vision of a ubiquitous telemedicine environment. The nomadic nature of a medical practitioner emphasises location, activity and time as key context-aware elements. An intelligent middleware is needed to effectively interpret and exploit these contextual elements. This paper proposes an agent-based architectural solution called Context-Aware Mobile Medical Devices (CAMMD). This framework can proactively communicate patient records to a portable device based upon the active context of its medical practitioner. An expert system is utilised to cross-reference the context-aware data of location and time against a practitioners work schedule. This proactive distribution of medical data enhances the usability and portability of mobile medical devices. The proposed methodology alleviates constraints on memory storage and enhances user interaction with the handheld device. The framework also improves utilisation of network bandwidth resources. An experimental prototype is presented highlighting the potential of this approach

Cooperative Glutamatergic and Cholinergic Mechanisms Generate Short-Term Modifications of Synaptic Effectiveness in Prepositus Hypoglossi Neurons

To maintain horizontal eye position on a visual target after a saccade, extraocular motoneurons need a persistent (tonic) neural activity, called "eye-position signal," generated by prepositus hypoglossi (PH) neurons. We have shown previously in vitro and in vivo that this neural activity depends, among others mechanisms, on the interplay of glutamatergic transmission and cholinergic synaptically triggered depolarization. Here, we used rat sagittal brainstem slices, including PH nucleus and paramedian pontine reticular formation (PPRF). We made intracellular recordings of PH neurons and studied their synaptic activation from PPRF neurons. Train stimulation of the PPRF area evoked a cholinergic-sustained depolarization of PH neurons that outlasted the stimulus. EPSPs evoked in PH neurons by single pulses applied to the PPRF presented a short-term potentiation (STP) after train stimulation. APV (an NMDA-receptor blocker) or chelerythrine (a protein kinase-C inhibitor) had no effect on the sustained depolarization, but they did block the evoked STP, whereas pirenzepine (an M1 muscarinic antagonist) blocked both the sustained depolarization and the STP of PH neurons. Thus, electrical stimulation of the PPRF area activates both glutamatergic and cholinergic axons terminating in the PH nucleus, the latter producing a sustained depolarization probably involved in the genesis of the persistent neural activity required for eye fixation. M1-receptor activation seems to evoke a STP of PH neurons via NMDA receptors. Such STP could be needed for the stabilization of the neural network involved in the generation of position signals necessary for eye fixation after a saccade

The Master Equation for Large Population Equilibriums

We use a simple N-player stochastic game with idiosyncratic and common noises to introduce the concept of Master Equation originally proposed by Lions in his lectures at the Coll\`ege de France. Controlling the limit N tends to the infinity of the explicit solution of the N-player game, we highlight the stochastic nature of the limit distributions of the states of the players due to the fact that the random environment does not average out in the limit, and we recast the Mean Field Game (MFG) paradigm in a set of coupled Stochastic Partial Differential Equations (SPDEs). The first one is a forward stochastic Kolmogorov equation giving the evolution of the conditional distributions of the states of the players given the common noise. The second is a form of stochastic Hamilton Jacobi Bellman (HJB) equation providing the solution of the optimization problem when the flow of conditional distributions is given. Being highly coupled, the system reads as an infinite dimensional Forward Backward Stochastic Differential Equation (FBSDE). Uniqueness of a solution and its Markov property lead to the representation of the solution of the backward equation (i.e. the value function of the stochastic HJB equation) as a deterministic function of the solution of the forward Kolmogorov equation, function which is usually called the decoupling field of the FBSDE. The (infinite dimensional) PDE satisfied by this decoupling field is identified with the \textit{master equation}. We also show that this equation can be derived for other large populations equilibriums like those given by the optimal control of McKean-Vlasov stochastic differential equations. The paper is written more in the style of a review than a technical paper, and we spend more time and energy motivating and explaining the probabilistic interpretation of the Master Equation, than identifying the most general set of assumptions under which our claims are true