Isotope shift of the D-Lines of 20Na

Coolen, F.C.M.; Schaik, N. van

doi:10.1016/0378-4363(78)90133-x

Cited by 30 publications

(77 citation statements)

References 2 publications

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“…It is clear that the depopulation effect increases with the laser intensity. The shape of the curves are in good agreement with those measured and calculated by COOLEN [19]. We have measured (Fig.…”

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confidence: 89%

Investigations on Afterglows of Neon Gas Discharges

Steenhuijsen

1981

Contrib Plasma Phys

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We report on the experimental and numerical investigations on afterglows of neon gas discharges, which are performed at the Eindhoven University of Technology.The studied gas pressure range extends from 1 to 100 torr, the discharge current from 1 to 100 mA. The densities of the 1s‐levels are measured with the help of the selective excitation spectroscopy (fluorescence technique). In this way a great number of decay curves of the 1s‐densities have been measured in the afterglow of neon gas discharges. From these curves the diffusion coefficient of the metastable 1s‐atoms, the coefficients of atomic collisional transfer between the 1s5‐ and 1s4‐level, as well as the three body collision coefficient between metastable 1s5‐atoms and neon ground state atoms have been determined.Besides these experiments a numerical model of the neon afterglows has been developed. With this model the afterglow phenomena can be simulated and the influence of the particular processes on the whole afterglow can be studied conveniently. Comparison is made between the experimentally and numerically obtained decay curves.For the application of the numerical model a number of starting conditions, such as radial density profiles, gas temperature, (relative) densities of the 1s‐levels, have been measured. Results of these measurements are presented.Also with the help of the selective excitation spectroscopy the coefficients of atomic collisional transfer between the 2p‐levels have been measured in the afterglow. From these results, together with the measured (relative) intensities of the neon spectral lines in the afterglow the partial recombination coefficients for the 2p‐levels were calculated.

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confidence: 89%

Investigations on Afterglows of Neon Gas Discharges

Steenhuijsen

1981

Contrib Plasma Phys

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“…The temperature has been set equal to 1, since any effects of changing the temperature can be realized by changing the coupling parameter g and the field strengths. Even for time-independent field and in a steady state, this system is not in a Gibbs equilibrium [10]. However, we show that, like its equilibrium counterpart, the nonequilibrium inverse problem for this model can be solved using a gradient descent method and also via systematic approximate inferences derived using dynamical versions of naive mean-field (nMF) and Thouless-Anderson-Palmer (TAP) equations.…”

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confidence: 96%

“…There has also been work [6], closely connected to (1), in which s i (t+1) depends on linear combinations of h(t ′ ) and s(t ′ ), for t ′ ≤ t. Given the advantage of these nonequilibrium models over the equilibrium ones for describing spike train statistics, a meanfield theory for inferring their parameters would be of great theoretical and practical benefit. For such models, we expect that it will be possible to use the techqniues in [8] or [10,16] to derive dynamical nMF and TAP equations. Employing the approach developed here one can then build approximate mean field inversion techniques based on these equations.…”

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confidence: 99%

Mean Field Theory for Nonequilibrium Network Reconstruction

Roudi

Hertz²

2011

Phys. Rev. Lett.

135

225

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There has been recent progress on inferring the structure of interactions in complex networks when they are in stationary states satisfying detailed balance, but little has been done for nonequilibrium systems. Here we introduce an approach to this problem, considering, as an example, the question of recovering the interactions in an asymmetrically-coupled, synchronously-updated Sherrington-Kirkpatrick model. We derive an exact iterative inversion algorithm and develop efficient approximations based on dynamical mean-field and Thouless-Anderson-Palmer equations that express the interactions in terms of equal-time and one time step-delayed correlation functions. Introduction.-Finding the connectivity in complex networks is crucial for understanding how they operate. Gene and multi-electrode microarrays have recently made the type of data required for this purpose available. What is needed now is appropriate theoretical tools for analyzing these data and extracting the connectivity.In much recent work on this subject [1-3], the problem has been posed as that of inferring the parameters of a stationary Gibbs distribution modeling the system. While satisfied in many applications, the assumption of Gibbs equilibrium is unlikely to hold for many biological systems since they are usually driven by time-dependent external fields, their interactions may not satisfy detailed balance, or they may only be observed while the transients dominate the dynamics. Applying the equilibrium approach to such cases usually yields effective interactions that do not bear an obvious relationship to the real ones [3]. Kinetic and nonequilibrium models provide a much richer platform for studying such systems [4][5][6].Whereas for equilibrium models the development of systematic mean field inference methods [7] has led to great practical and conceptual advancements, a mean field theory for nonequilibrium network reconstruction is still lacking. In this paper, we show how a mean field theory for inference can also be developed for a nonequilibrium system. We consider this problem for a particular simple nonequilibrium model: a kinetic Ising model with random asymmetric interactions (J ji independent of J ij ), in an external field which may be time-dependent. This is a discrete-time, synchronously updated model composed of N spins s i = ±1 with transition probability

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“…During pattern retrieval of this model, spin neurons exhibit periodic oscillation, reproducing phase differences of the encoded periodic patterns. To investigate this nonequilibrium nature of the asymmetric neural network, we analyze the system by path integral methods [8][9][10][11][17][18][19][20][21]. Path integral methods can deal with the asymmetric Ising-spin system, such as the asymmetrically modified Sherrington-Kirkpatrick model [10,21].…”

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confidence: 99%

“…DOI Measurements of neural activity in a rat's brain have offered a clue to memory representation in the real nervous system [1][2][3]. These studies have shown that a single neural circuit is capable of storing a number of memories, and the mechanism of this multiple-pattern learning has been explained by multiple attractors in associative memory neural network models [4][5][6][7][8][9][10][11][12][13][14][15][16]. It is then an interesting problem to clarify how many memories or attractors can be memorized in one neural network.…”

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confidence: 99%

Learning of Spatiotemporal Patterns in Ising-Spin Neural Networks: Analysis of Storage Capacity by Path Integral Methods

Yoshioka

2009

Phys. Rev. Lett.

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We encode periodic spatiotemporal patterns in Ising-spin neural networks, using the simple learning rule inspired by the spike-timing-dependent synaptic plasticity. It is then found that periodically oscillating spin neurons successfully reproduce phase differences of the encoded periodic patterns. The storage capacity of this associative memory neural network is enhanced with an adequate level of asymmetry in synapse connections. To understand the properties of these nonequilibrium retrieval states of the neural network, we carry out an analysis based on a path integral method. The relation of a dynamic crosstalk term to time-persistent oscillation of a correlation function well explains the enhancement of the storage capacity in spite of our approximation on nonpersistent terms. We investigate the accuracy of this approximation further by detailed comparison with numerical simulations.

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Isotope shift of the D-Lines of 20Na

Cited by 30 publications

References 2 publications

Investigations on Afterglows of Neon Gas Discharges

Investigations on Afterglows of Neon Gas Discharges

Mean Field Theory for Nonequilibrium Network Reconstruction

Learning of Spatiotemporal Patterns in Ising-Spin Neural Networks: Analysis of Storage Capacity by Path Integral Methods

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