93,797 research outputs found
Through a Lattice Darkly -- Shedding Light on Electron-Phonon Coupling in the High T Cuprates
With its central role in conventional BCS superconductivity, electron-phonon
coupling has appeared to play a more subtle role in the phase diagram of the
high temperature superconducting cuprates. The added complexity of the cuprates
with potentially numerous competing phases including charge, spin, orbital, and
lattice ordering, makes teasing out any unique phenomena challenging. In this
review, we present our work using angle resolved photoemission spectroscopy
(ARPES) to explore the role of the lattice and its effect on the valence band
electronic structure in the cuprates. We provide an introduction to the ARPES
technique and its unique ability to the probe the effect of bosonic
renormalization (or "kink") on the near-E band structure. Our survey begins
with the establishment of the ubiquitous nodal cuprate kink leading to the way
isotope substitution has shed a critical new perspective on the role and
strength of electron-phonon coupling. We continue with recently published work
on the connection between the phonon dispersion as seen with inelastic x-ray
scattering (IXS) and the location of the kink as observed by ARPES near the
nodal point. Finally, we present very recent and ongoing ARPES work examining
how induced strain through chemical pressure provides a potentially promising
avenue for understanding the broader role of the lattice to the superconducting
phase and larger cuprate phase diagram.Comment: 17 pages, 20 figures, Review Articl
Stochastic mean field formulation of the dynamics of diluted neural networks
We consider pulse-coupled Leaky Integrate-and-Fire neural networks with
randomly distributed synaptic couplings. This random dilution induces
fluctuations in the evolution of the macroscopic variables and deterministic
chaos at the microscopic level. Our main aim is to mimic the effect of the
dilution as a noise source acting on the dynamics of a globally coupled
non-chaotic system. Indeed, the evolution of a diluted neural network can be
well approximated as a fully pulse coupled network, where each neuron is driven
by a mean synaptic current plus additive noise. These terms represent the
average and the fluctuations of the synaptic currents acting on the single
neurons in the diluted system. The main microscopic and macroscopic dynamical
features can be retrieved with this stochastic approximation. Furthermore, the
microscopic stability of the diluted network can be also reproduced, as
demonstrated from the almost coincidence of the measured Lyapunov exponents in
the deterministic and stochastic cases for an ample range of system sizes. Our
results strongly suggest that the fluctuations in the synaptic currents are
responsible for the emergence of chaos in this class of pulse coupled networks.Comment: 12 Pages, 4 Figure
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