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Jie Long

Publications and source records attributed to Jie Long.

3 recordsLinked to original sources

High-purity valley-polarized currents induced by bichromatic optical fields in two-dimensional materials

Producing currents predominantly from a single valley, namely valley-polarized currents, at optical-cycle timescales is an important aspect of the petahertz valleytronics, yet it remains less developed. This work exhibits the feasibility of achieving this goal using bichromatic optical fields, which allow for the precise control of sub-cycle electron dynamics. The combined effect of the helical and asymmetric waveforms of the optical fields leads to highly asymmetric excitation at different valleys and displacement of the excited electrons concurrently, thereby inducing valley-polarized currents with high valley purity, on the sub-optical-cycle timescale. Inherently, the purity of the currents built up from the optical approach remains high even for materials with short decoherence time. Moreover, the direction of the currents can be precisely controlled by adjusting the relative phase of the bichromatic components. Our work offers a promising avenue for generating and modulating high-purity valley-polarized currents at the femtosecond timescale, facilitating the development of petahertz valleytronics.

physics.optics

Efficient spectral broadening and few-cycle pulse generation with multiple thin water films

High-energy, few-cycle laser pulses are essential for numerous applications in the fields of ultrafast optics and strong-field physics, due to their ultrafast temporal resolution and high peak intensity. In this work, different from the traditional hollow-core fibers and multiple thin solid plates, we represent the first demonstration of the octave-spanning supercontinuum broadening by utilizing multiple ultrathin liquid films (MTLFs) as the nonlinear media. The continuum covers a range from 380 to 1050 nm, corresponding to a Fourier transform limit pulse width of 2.5 fs, when 35 fs Ti:sapphire laser pulse is applied on the MTLFs. The output pulses are compressed to 3.9 fs by employing chirped mirrors. Furthermore, a continuous high-order harmonic spectrum up to the 33rd order is realized by subjecting the compressed laser pulses to interact with Kr gas. The utilization of flowing water films eliminates permanent optical damage and enables wider and stronger spectrum broadening. Therefore, this MTLFs scheme provides new solutions for the generation of highly efficient femtosecond supercontinuum and nonlinear pulse compression, with potential applications in the fields of strong-field physics and attosecond science.

physics.optics

Identification and prediction of time-varying parameters of COVID-19 model: a data-driven deep learning approach

Data-driven deep learning provides efficient algorithms for parameter identification of epidemiology models. Unlike the constant parameters, the complexity of identifying time-varying parameters is largely increased. In this paper, a variant of physics-informed neural network (PINN) is adopted to identify the time-varying parameters of the Susceptible-Infectious-Recovered-Deceased model for the spread of COVID-19 by fitting daily reported cases. The learned parameters are verified by utilizing an ordinary differential equation solver to compute the corresponding solutions of this compartmental model. The effective reproduction number based on these parameters is calculated. Long Short-Term Memory (LSTM) neural network is employed to predict the future weekly time-varying parameters. The numerical simulations demonstrate that PINN combined with LSTM yields accurate and effective results.

math.DS