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 en

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