66 research outputs found
Exciton-phonon information flow in the energy transfer process of photosynthetic complexes
Non-Markovian and non-equilibrium phonon effects are believed to be key
ingredients in the energy transfer in photosynthetic complexes, especially in
complexes which exhibit a regime of intermediate exciton-phonon coupling. In
this work, we utilize a recently-developed measure for non-Markovianity to
elucidate the exciton-phonon dynamics in terms of the information flow between
electronic and vibrational degrees of freedom. We study the measure in the
hierarchical equation of motion approach which captures strong system-bath
coupling effects and non-equilibrium molecular reorganization. We propose an
additional trace-distance measure for the information flow that could be
extended to other master equations. We find that for a model dimer system and
the Fenna-Matthews-Olson complex that non-Markovianity is significant under
physiological conditions.Comment: 4 pages, 2 figure
Quantum Hopfield neural network
Quantum computing allows for the potential of significant advancements in
both the speed and the capacity of widely used machine learning techniques.
Here we employ quantum algorithms for the Hopfield network, which can be used
for pattern recognition, reconstruction, and optimization as a realization of a
content-addressable memory system. We show that an exponentially large network
can be stored in a polynomial number of quantum bits by encoding the network
into the amplitudes of quantum states. By introducing a classical technique for
operating the Hopfield network, we can leverage quantum algorithms to obtain a
quantum computational complexity that is logarithmic in the dimension of the
data. We also present an application of our method as a genetic sequence
recognizer.Comment: 13 pages, 3 figures, final versio
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