975 resultados para Mean-field model
Resumo:
The process of stimulated Raman adiabatic passage (STIRAP) provides a possible route for the generation of a coherent molecular Bose-Einstein condensate (BEC) from an atomic BEC. We analyze this process in a three-dimensional mean-field theory, including atom-atom interactions and nonresonant intermediate levels. We find that the process is feasible, but at larger Rabi frequencies than anticipated from a crude single-mode lossless analysis, due to two-photon dephasing caused by the atomic interactions. We then identify optimal strategies in STIRAP allowing one to maintain high conversion efficiencies with smaller Rabi frequencies and under experimentally less demanding conditions.
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Many images consist of two or more 'phases', where a phase is a collection of homogeneous zones. For example, the phases may represent the presence of different sulphides in an ore sample. Frequently, these phases exhibit very little structure, though all connected components of a given phase may be similar in some sense. As a consequence, random set models are commonly used to model such images. The Boolean model and models derived from the Boolean model are often chosen. An alternative approach to modelling such images is to use the excursion sets of random fields to model each phase. In this paper, the properties of excursion sets will be firstly discussed in terms of modelling binary images. Ways of extending these models to multi-phase images will then be explored. A desirable feature of any model is to be able to fit it to data reasonably well. Different methods for fitting random set models based on excursion sets will be presented and some of the difficulties with these methods will be discussed.
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The new science of nonlinear atom optics and atom lasers is evolving rapidly. There are similarities between many related areas in modern photonic and atom optics, particularly at the mean-field level. In both cases we can often use classical nonlinear wave equations to describe classical solitons, vortices, and other nonlinear structure. Atom-molecular coupling can be used to play the role of second-harmonic generation. This leads to novel types of soliton. In addition, quantum effects at low densities are likely to be readily observable.
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We consider the quantum dynamics of a neutral atom Bose-Einstein condensate in a double-well potential, including many-body hard-sphere interactions. Using a mean-field factorization we show that the coherent oscillations due to tunneling are suppressed when the number of atoms exceeds a critical value. An exact quantum solution, in a two-mode approximation, shows that the mean-field solution is modulated by a quantum collapse and revival sequence.
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A study of spin-orbit mixing and nephelauxetic effects in the electronic spectra of nickel(II)-encapsulating complexes involving mixed nitrogen and sulfur donors is reported. As the number of sulfur donors is systematically varied through the series [Ni(N6-xSx)](2+) (x = 0-6), the spin-forbidden (3)A(2)g --> E-1(g) and (3)A(2g) --> (1)A(1g) transitions undergo a considerable reduction in energy whereas the spin-allowed transitions are relatively unchanged. The [Ni(diAMN(6)sar)](2+) and [Ni(AMN(5)Ssar)](2+) complexes exhibit an unusual band shape for the (3)A(2g) --> T-3(2g) transition which is shown to arise from spin-orbit mixing of the E spin-orbit levels associated with the E-1(g) and T-3(2g) states. A significant differential nephelauxetic effect also arises from the covalency differences between the t(2g) and e(g) orbitals with the result that no single set of Racah B and C interelectron repulsion parameters adequately fit the observed spectra. Using a differential covalency ligand-field model, the spectral transitions are successfully reproduced with three independent variables corresponding to 10Dq and the covalency parameters f(t) and f(e), associated with the t(2g) and e(g) orbitals, respectively. The small decrease in f(t) from unity is largely attributed to central-field covalency effects whereas the dramatic reduction in f(e) with increasing number of sulfur donors is a direct consequence of the increased metal-ligand covalency associated with the sulfur donors. Covalency differences between the t(2g) and e(g) orbitals also result in larger 10Dq values than those obtained simply from the energy of the (3)A(2g) --> T-3(2g) spin-allowed transition.
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Smoothing the potential energy surface for structure optimization is a general and commonly applied strategy. We propose a combination of soft-core potential energy functions and a variation of the diffusion equation method to smooth potential energy surfaces, which is applicable to complex systems such as protein structures; The performance of the method was demonstrated by comparison with simulated annealing using the refinement of the undecapeptide Cyclosporin A as a test case. Simulations were repeated many times using different initial conditions and structures since the methods are heuristic and results are only meaningful in a statistical sense.
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We consider a two-component Bose-Einstein condensate in two spatially localized modes of a double-well potential, with periodic modulation of the tunnel coupling between the two modes. We treat the driven quantum field using a two-mode expansion and define the quantum dynamics in terms of the Floquet Operator for the time periodic Hamiltonian of the system. It has been shown that the corresponding semiclassical mean-field dynamics can exhibit regions of regular and chaotic motion. We show here that the quantum dynamics can exhibit dynamical tunneling between regions of regular motion, centered on fixed points (resonances) of the semiclassical dynamics.
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As determined by X-ray crystallography, Meldrum's acid derivatives 8–19 feature dihedral angles around the central CC double bonds between 3 and 83°. Hydrogen bonds between substituents RHN and the carbonyl groups favour near-planarity. Sterically demanding substituents favour large dihedral angles and zwitterionic structures as in formula 20. AM1 calculations of the structures are in excellent agreement with the experimental X-ray data, provided a dielectric field is incorporated (?= 40). This can be ascribed to the highly polar (zwitterionic) nature of the molecules. It is further predicted that all these molecules, including those that are stabilised in a planar form by intramolecular hydrogen bonds, undergo rapid rotation about the central CC bonds at room temperature. DFT calculations incorporating a dielectric field model (PCM) are in excellent agreement with the near-perpendicular arrangement of the alkene moiety in 19.
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The exact description of the thermodynamics of solutions has been used to describe, without approximation, the distribution of all the components of an incompressible solution in a centrifuge cell at sedimentation equilibrium. Thermodynamic parameters describing the interactions between solute components of known molar mass can be obtained by direct analysis of the experimental data. Interpretation of the measured thermodynamic parameters in terms of molecular interactions requires that an arbitrary distinction be made between nonassociative forces, like hard-sphere volume-exclusion and mean-field electrostatic repulsion or attraction, and specific short-range forces of association that give rise to the formation of molecular aggregates. Provided the former can be accounted for adequately, the effects of the latter can be elucidated in the form of good estimates of the equilibrium constants for the reactions of aggregation.
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In this work the critical indices β, γ , and ν for a three-dimensional (3D) hardcore cylinder composite system with short-range interaction have been obtained. In contrast to the 2D stick system and the 3D hardcore cylinder system, the determined critical exponents do not belong to the same universality class as the lattice percolation,although they obey the common hyperscaling relation for a 3D system. It is observed that the value of the correlation length exponent is compatible with the predictions of the mean field theory. It is also shown that, by using the Alexander-Orbach conjuncture, the relation between the conductivity and the correlation length critical exponents has a typical value for a 3D lattice system.
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The scope of this paper is to adapt the standard mean-variance model of Henry Markowitz theory, creating a simulation tool to find the optimal configuration of the portfolio aggregator, calculate its profitability and risk. Currently, there is a deep discussion going on among the power system society about the structure and architecture of the future electric system. In this environment, policy makers and electric utilities find new approaches to access the electricity market; this configures new challenging positions in order to find innovative strategies and methodologies. Decentralized power generation is gaining relevance in liberalized markets, and small and medium size electricity consumers are also become producers (“prosumers”). In this scenario an electric aggregator is an entity that joins a group of electric clients, customers, producers, “prosumers” together as a single purchasing unit to negotiate the purchase and sale of electricity. The aggregator conducts research on electricity prices, contract terms and conditions in order to promote better energy prices for their clients and allows small and medium customers to benefit improved market prices.
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This work is divided into two distinct parts. The first part consists of the study of the metal organic framework UiO-66Zr, where the aim was to determine the force field that best describes the adsorption equilibrium properties of two different gases, methane and carbon dioxide. The other part of the work focuses on the study of the single wall carbon nanotube topology for ethane adsorption; the aim was to simplify as much as possible the solid-fluid force field model to increase the computational efficiency of the Monte Carlo simulations. The choice of both adsorbents relies on their potential use in adsorption processes, such as the capture and storage of carbon dioxide, natural gas storage, separation of components of biogas, and olefin/paraffin separations. The adsorption studies on the two porous materials were performed by molecular simulation using the grand canonical Monte Carlo (μ,V,T) method, over the temperature range of 298-343 K and pressure range 0.06-70 bar. The calibration curves of pressure and density as a function of chemical potential and temperature for the three adsorbates under study, were obtained Monte Carlo simulation in the canonical ensemble (N,V,T); polynomial fit and interpolation of the obtained data allowed to determine the pressure and gas density at any chemical potential. The adsorption equilibria of methane and carbon dioxide in UiO-66Zr were simulated and compared with the experimental data obtained by Jasmina H. Cavka et al. The results show that the best force field for both gases is a chargeless united-atom force field based on the TraPPE model. Using this validated force field it was possible to estimate the isosteric heats of adsorption and the Henry constants. In the Grand-Canonical Monte Carlo simulations of carbon nanotubes, we conclude that the fastest type of run is obtained with a force field that approximates the nanotube as a smooth cylinder; this approximation gives execution times that are 1.6 times faster than the typical atomistic runs.
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There is currently an increasing demand for robots able to acquire the sequential organization of tasks from social learning interactions with ordinary people. Interactive learning-by-demonstration and communication is a promising research topic in current robotics research. However, the efficient acquisition of generalized task representations that allow the robot to adapt to different users and contexts is a major challenge. In this paper, we present a dynamic neural field (DNF) model that is inspired by the hypothesis that the nervous system uses the off-line re-activation of initial memory traces to incrementally incorporate new information into structured knowledge. To achieve this, the model combines fast activation-based learning to robustly represent sequential information from single task demonstrations with slower, weight-based learning during internal simulations to establish longer-term associations between neural populations representing individual subtasks. The efficiency of the learning process is tested in an assembly paradigm in which the humanoid robot ARoS learns to construct a toy vehicle from its parts. User demonstrations with different serial orders together with the correction of initial prediction errors allow the robot to acquire generalized task knowledge about possible serial orders and the longer term dependencies between subgoals in very few social learning interactions. This success is shown in a joint action scenario in which ARoS uses the newly acquired assembly plan to construct the toy together with a human partner.
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Per a determinar la dinàmica espai-temporal completa d’un sistema quàntic tridimensional de N partícules cal integrar l’equació d’Schrödinger en 3N dimensions. La capacitat dels ordinadors actuals permet fer-ho com a molt en 3 dimensions. Amb l’objectiu de disminuir el temps de càlcul necessari per a integrar l’equació d’Schrödinger multidimensional, es realitzen usualment una sèrie d’aproximacions, com l’aproximació de Born–Oppenheimer o la de camp mig. En general, el preu que es paga en realitzar aquestes aproximacions és la pèrdua de les correlacions quàntiques (o entrellaçament). Per tant, és necessari desenvolupar mètodes numèrics que permetin integrar i estudiar la dinàmica de sistemes mesoscòpics (sistemes d’entre tres i unes deu partícules) i en els que es tinguin en compte, encara que sigui de forma aproximada, les correlacions quàntiques entre partícules. Recentment, en el context de la propagació d’electrons per efecte túnel en materials semiconductors, X. Oriols ha desenvolupat un nou mètode [Phys. Rev. Lett. 98, 066803 (2007)] per al tractament de les correlacions quàntiques en sistemes mesoscòpics. Aquesta nova proposta es fonamenta en la formulació de la mecànica quàntica de de Broglie– Bohm. Així, volem fer notar que l’enfoc del problema que realitza X. Oriols i que pretenem aquí seguir no es realitza a fi de comptar amb una eina interpretativa, sinó per a obtenir una eina de càlcul numèric amb la que integrar de manera més eficient l’equació d’Schrödinger corresponent a sistemes quàntics de poques partícules. En el marc del present projecte de tesi doctoral es pretén estendre els algorismes desenvolupats per X. Oriols a sistemes quàntics constituïts tant per fermions com per bosons, i aplicar aquests algorismes a diferents sistemes quàntics mesoscòpics on les correlacions quàntiques juguen un paper important. De forma específica, els problemes a estudiar són els següents: (i) Fotoionització de l’àtom d’heli i de l’àtom de liti mitjançant un làser intens. (ii) Estudi de la relació entre la formulació de X. Oriols amb la aproximació de Born–Oppenheimer. (iii) Estudi de les correlacions quàntiques en sistemes bi- i tripartits en l’espai de configuració de les partícules mitjançant la formulació de de Broglie–Bohm.
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This paper presents 3-D brain tissue classificationschemes using three recent promising energy minimizationmethods for Markov random fields: graph cuts, loopybelief propagation and tree-reweighted message passing.The classification is performed using the well knownfinite Gaussian mixture Markov Random Field model.Results from the above methods are compared with widelyused iterative conditional modes algorithm. Theevaluation is performed on a dataset containing simulatedT1-weighted MR brain volumes with varying noise andintensity non-uniformities. The comparisons are performedin terms of energies as well as based on ground truthsegmentations, using various quantitative metrics.