All-optical reconstruction of three-band transition dipole moments by the crystal harmonic spectrum from a two-color laser pulse.

When a bulk solid is irradiated by an intense laser pulse, transition dipole moments (TDMs) between different energy bands have an important influence on the ultra-fast dynamic process. In this paper, we propose a new all-optical method to reconstruct the k-dependent TDMs between multi-bands using a crystal high-order harmonic generation (HHG). Taking advantage of an obvious separation of bandgaps between three energy bands of an MgO crystal along the <001 > direction, a continuous harmonic spectrum with two plateaus can be generated by a two-color laser pulse. Furthermore, the first harmonic platform is mainly dominated by the polarization between the first conduction band and the valence band, and the second one is largely attributed to the interband HHG from the second conduction band and the valence band. Therefore, the harmonic spectrum from a single quantum trajectory can be adopted to map TDMs between the first, second conduction bands, and the valence one. Our work is of great significance for understanding the instantaneous properties of solid materials in the strong laser field, and will strongly promote the development of the HHG detection technology.

Effect of interband polarization on a solid's high-order-harmonic generation just belowthe band gap.

A series of theoretical and experimental results has proved that harmonics below/above the band gap are produced mainly by the intraband current/interband polarization for solids in strong mid-infrared laser pulses. However, which mechanism dominates the harmonic process is still debated. In this work, based on simulating high-order-harmonic generation from an MgO crystal in a linearly polarized mid-infrared laser by solving semiconductor Bloch equations, we demonstrate that harmonics just below the band gap originate from the interference between intraband and interband currents. Furthermore, it is found that intensities of harmonics just below the band gap are apparently enhanced with an increase in the incident laser's strength. By analyzing the band dispersion and the transition dipole moment of the 001-cut MgO crystal, this can be attributed to the interband polarization between two conduction bands.

All-optical reconstruction of k-dependent transition dipole moment by solid harmonic spectra from ultrashort laser pulses.

Band structure and transition dipole moment play important roles in high-order harmonic generation from solid materials. In this work we provide a new all-optical technique to reconstruct the momentum-dependent transition dipole moment using the harmonic spectrum from MgO crystal driven by an ultrashort mid-infrared laser pulse. Under the influence of the ultrashort laser pulse, the emitted photon energy and the crystal momentum form a one-to-one match, in the same way between the intensity of the harmonic above the minimum bandgap and the square of the amplitude of the transition dipole moment, resulting in a realization of directly probing the transition dipole moment. Our all-optical method paves a way to image the two-dimensional transition dipole moment of crystals with the inversion symmetry.

Mapping Chinese annual gross primary productivity with eddy covariance measurements and machine learning.

Annual gross primary productivity (AGPP) is the basis for grain production and terrestrial carbon sequestration. Mapping regional AGPP from site measurements provides methodological support for analysing AGPP spatiotemporal variations thereby ensures regional food security and mitigates climate change. Based on 641 site-year eddy covariance measuring AGPP from China, we built an AGPP mapping scheme based on its formation and selected the optimal mapping way, which was conducted through analysing the predicting performances of divergent mapping tools, variable combinations, and mapping approaches in predicting observed AGPP variations. The reasonability of the selected optimal scheme was confirmed by assessing the consistency between its generating AGPP and previous products in spatiotemporal variations and total amount. Random forest regression tree explained 85 % of observed AGPP variations, outperforming other machine learning algorithms and classical statistical methods. Variable combinations containing climate, soil, and biological factors showed superior performance to other variable combinations. Mapping AGPP through predicting AGPP per leaf area (PAGPP) explained 86 % of AGPP variations, which was superior to other approaches. The optimal scheme was thus using a random forest regression tree, combining climate, soil, and biological variables, and predicting PAGPP. The optimal scheme generating AGPP of Chinese terrestrial ecosystems decreased from southeast to northwest, which was highly consistent with previous products. The interannual trend and interannual variation of our generating AGPP showed a decreasing trend from east to west and from southeast to northwest, respectively, which was consistent with data-oriented products. The mean total amount of generated AGPP was 7.03 ± 0.45 PgC yr-1 falling into the range of previous works. Considering the consistency between the generated AGPP and previous products, our optimal mapping way was suitable for mapping AGPP from site measurements. Our results provided a methodological support for mapping regional AGPP and other fluxes.