Quantum Energy Teleportation Between Spin Particles in a Gibbs State

Energy in a multipartite quantum system appears from an operational perspective to be distributed to some extent non-locally because of correlations extant among the system's components. This non-locality allows users to transfer, in effect, locally accessible energy between sites of different system components by local operations and classical communication (LOCC). Quantum energy teleportation is a three-step LOCC protocol, accomplished without an external energy carrier, for effectively transferring energy between two physically separated, but correlated, sites. We apply this LOCC teleportation protocol to a model Heisenberg spin particle pair initially in a quantum thermal Gibbs state, making temperature an explicit parameter. We find in this setting that energy teleportation is possible at any temperature, even at temperatures above the threshold where the particles' entanglement vanishes. This shows for Gibbs spin states that entanglement is not fundamentally necessary for energy teleportation; correlation other than entanglement can suffice. Dissonance-quantum correlation in separable states-is in this regard shown to be a quantum resource for energy teleportation, more dissonance being consistently associated with greater energy yield. We compare energy teleportation from particle A to B in Gibbs states with direct local energy extraction by a general quantum operation on B and find a temperature threshold below which energy extraction by a local operation is impossible. This threshold delineates essentially two regimes: a high temperature regime where entanglement vanishes and the teleportation generated by other quantum correlations yields only vanishingly little energy relative to local extraction and a second low-temperature teleportation regime where energy is available at B only by teleportation.

Advanced morphological 3D magnetic resonance observation of cartilage repair tissue (MOCART) scoring using a new isotropic 3D proton-density, turbo spin echo sequence with variable flip angle distribution (PD-SPACE) compared to an isotropic 3D steady-state free precession sequence (True-FISP) and standard 2D sequences

To evaluate a new isotropic 3D proton-density, turbo-spin-echo sequence with variable flip-angle distribution (PD-SPACE) sequence compared to an isotropic 3D true-fast-imaging with steady-state-precession (True-FISP) sequence and 2D standard MR sequences with regard to the new 3D magnetic resonance observation of cartilage repair tissue (MOCART) score.

Theta burst TMS increases cerebral blood flow in the primary motor cortex during motor performance as assessed by arterial spin labeling (ASL)

Theta burst stimulation (TBS) is a novel variant of repetitive transcranial magnetic stimulation (rTMS), which induces changes in neuronal excitability persisting up to 1h. When elicited in the primary motor cortex, such physiological modulations might also have an impact on motor behavior. In the present study, we applied TBS in combination with pseudo continuous arterial spin labeling (pCASL) in order to address the question of whether TBS effects are measurable by means of changes in physiological parameters such as cerebral blood flow (CBF) and if TBS-induced plasticity can modify motor behavior. Twelve right-handed healthy subjects were stimulated using an inhibitory TBS protocol at subthreshold stimulation intensity targeted over the right motor cortex. The control condition consisted of within-subject Sham treatment in a crossover design. PCASL was performed before (pre TBS/pre Sham) and immediately after treatment (post TBS/post Sham). During the pCASL runs, the subjects performed a sequential fingertapping task with the left hand at individual maximum speed. There was a significant increase of CBF in the primary motor cortex after TBS, but not after Sham. It is assumed that inhibitory TBS induced a "local virtual lesion" which leads to the mobilization of more neuronal resources. There was no TBS-specific modulation in motor behavior, which might indicate that acute changes in brain plasticity caused by TBS are immediately compensated. This compensatory reaction seems to be observable at the metabolic, but not at the behavioral level.

Varying spin state composition by the choice of capping ligand in a family of molecular chains: detailed analysis of magnetic properties of chromium(III) horseshoes

We report a detailed physical analysis on a family of isolated, antiferro-magnetically (AF) coupled, chromium(III) finite chains, of general formula (Cr(RCO(2))(2)F)(n) where the chain length n = 6 or 7. Additionally, the chains are capped with a selection of possible terminating ligands, including hfac (= 1,1,1,5,5,5-hexafluoropentane-2,4-dionate(1-)), acac (= pentane-2,4-dionate(1-)) or (F)(3). Measurements by inelastic neutron scattering (INS), magnetometery and electron paramagnetic resonance (EPR) spectroscopy have been used to study how the electronic properties are affected by n and capping ligand type. These comparisons allowed the subtle electronic effects the choice of capping ligand makes for odd member spin 3/2 ground state and even membered spin 0 ground state chains to be investigated. For this investigation full characterisation of physical properties have been performed with spin Hamiltonian parameterisation, including the determination of Heisenberg exchange coupling constants and single ion axial and rhombic anisotropy. We reveal how the quantum spin energy levels of odd or even membered chains can be modified by the type of capping ligand terminating the chain. Choice of capping ligands enables Cr-Cr exchange coupling to be adjusted by 0, 4 or 24%, relative to Cr-Cr exchange coupling within the body of the chain, by the substitution of hfac, acac or (F)(3) capping ligands to the ends of the chain, respectively. The manipulation of quantum spin levels via ligands which play no role in super-exchange, is of general interest to the practise of spin Hamilton modelling, where such second order effects are generally not considered of relevance to magnetic properties.

Spike-based decision learning of nash equilibria in two-player games

Humans and animals face decision tasks in an uncertain multi-agent environment where an agent's strategy may change in time due to the co-adaptation of others strategies. The neuronal substrate and the computational algorithms underlying such adaptive decision making, however, is largely unknown. We propose a population coding model of spiking neurons with a policy gradient procedure that successfully acquires optimal strategies for classical game-theoretical tasks. The suggested population reinforcement learning reproduces data from human behavioral experiments for the blackjack and the inspector game. It performs optimally according to a pure (deterministic) and mixed (stochastic) Nash equilibrium, respectively. In contrast, temporal-difference(TD)-learning, covariance-learning, and basic reinforcement learning fail to perform optimally for the stochastic strategy. Spike-based population reinforcement learning, shown to follow the stochastic reward gradient, is therefore a viable candidate to explain automated decision learning of a Nash equilibrium in two-player games.

The Choice of Expedient Regulatory Controls on Housing Market Using Short-Term Equilibria Model

Khutoretsky dealt with the problem of maximising a linear utility function (MUF) over the set of short-term equilibria in a housing market by reducing it to a linear programming problem, and suggested a combinatorial algorithm for this problem. Two approaches to the market adjustment were considered: the funding of housing construction and the granting of housing allowances. In both cases, locally optimal regulatory measures can be developed using the corresponding dual prices. The optimal effects (with the regulation expenditures restricted by an amount K) can be found using specialised models based on MUF: a model M1 for choice of the optimum structure of investment in housing construction, and a model M2 for optimum distribution of housing allowances. The linear integer optimisation problems corresponding to these models are initially difficult but can be solved after slight modifications of the parameters. In particular, the necessary modification of K does not exceed the maximum construction cost of one dwelling (for M1) or the maximum size of one housing allowance (for M2). The result is particularly useful since slight modification of K is not essential in practice.