3,013 research outputs found
Geometry-induced memory effects in isolated quantum systems: Observations and applications
Memory effects can lead to history-dependent behavior of a system, and they
are ubiquitous in our daily life and have broad applications. Here we explore
possibilities of generating memory effects in simple isolated quantum systems.
By utilizing geometrical effects from a class of lattices supporting flat-bands
consisting of localized states, memory effects could be observed in ultracold
atoms in optical lattices. As the optical lattice continuously transforms from
a triangular lattice into a kagome lattice with a flat band, history-dependent
density distributions manifest quantum memory effects even in noninteracting
systems, including fermionic as well as bosonic systems in the proper ranges of
temperatures. Rapid growth in ultracold technology predicts a bright future for
quantum memory-effect systems, and here two prototypical applications of
geometry-induced quantum memory effects are proposed: An accelerometer
recording the mechanical change rate in a coupled system and a rate-controlled
memvalve where the rate of ramping the lattice potential acts as a control of
the remnant density in the lattice.Comment: 13 pages, 11 figures, update figures and references. We provided one
more application - quantum memory effects atomic memory (QMEAM
Tunable current circulation in triangular quantum-dot metastructures
Advances in fabrication and control of quantum dots allow the realization of
metastructures that may exhibit novel electrical transport phenomena. Here, we
investigate the electrical current passing through one such metastructure, a
system composed of quantum dots placed at the vertices of a triangle. The wave
natural of quantum particles leads to internal current circulation within the
metastructure in the absence of any external magnetic field. We uncover the
relation between its steady-state total current and the internal circulation.
By calculating the electronic correlations in quantum transport exactly, we
present phase diagrams showing where different types of current circulation can
be found as a function of the correlation strength and the coupling between the
quantum dots. Finally, we show that the regimes of current circulation can be
further enhanced or reduced depending on the local spatial distribution of the
interactions, suggesting a single-particle scattering mechanism is at play even
in the strongly-correlated regime. We suggest experimental realizations of
actual quantum-dot metastructures where our predictions can be directly tested.Comment: 5 pages, 4 figures, the Supplemental Information is attached at the
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Design of Deep Learning Acoustic Sonar Receiver with Temporal/ Spatial Underwater Channel Feature Extraction Capability
In this study, deep learning network technology is employed to solve the problem of rapid changes in underwater channels. The modulation techniques employed are frequency-shift keying (FSK) and the BELLHOP module of MATLAB; they are used to create water with multipath, Doppler shifts, and additive Gaussian white noise such that underwater acoustic receiving signals simulating the actual ocean environment can be obtained. The southwest coastal area of Taiwan is simulated in the manuscript. The results reveal that optimizing the environment by using the virtual time reversal mirror (VTRM) technique can generally mitigate the bit error rates (BERs) of the deep learning network’s model receiver and traditional demodulation receiver. Lastly, seven deep learning networks are deployed to demodulate the FSK signals, and these approaches are compared with traditional demodulation techniques to determine the deep learning network techniques that are most suitable for marine environments
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