Enhanced dissociation of H2+ into highly excited states via laser-induced sequential resonant excitation

We study the dissociation of H$_2$$^+$ in uv laser pulses by solving the non-Born-Oppenheimer time-dependent Schr\"{o}dinger equation as a function of the photon energy $\omega$ of the pulse. Significant enhancements of the dissociation into highly excited electronic states are observed at critical $\omega$. This is found to be attributed to a sequential resonant excitation mechanism where the population is firstly transferred to the first excited state by absorbing one photon and sequentially to higher states by absorbing another one or more photons at the same internuclear distance. We have substantiated the underlying dynamics by separately calculating the nuclear kinetic energy spectra for individual dissociation pathways through different electronic states

Anomalous isotopic effect on electron-directed reactivity by a 3-{\mu}m midinfrared pulse

We have theoretically studied the effect of nuclear mass on electron localization in dissociating H_2^+ and its isotopes subjected to a few-cycle 3-{\mu}m laser pulse. Compared to the isotopic trend in the near-infrared regime, our results reveal an inverse isotopic effect in which the degree of electron-directed reactivity is even higher for heavier isotopes. With the semi-classical analysis, we find, for the first time, the pronounced electron localization is established by the interferences through different channels of one- and, more importantly, higher-order photon coupling. Interestingly, due to the enhanced high-order above-threshold dissociation of heavier isotopes, the interference maxima gradually become in phase with growing mass and ultimately lead to the anomalous isotopic behavior of the electron localization. This indicates that the multi-photon coupling channels will play an important role in controlling the dissociation of larger molecules with midinfrared pulses.Comment: 5 pages, 4 figure

Revealing Correlated Electron-Nuclear Dynamics in Molecules with Energy-Resolved Population Image

We explore a new fashion, named energy-resolved population image (EPI), to represent on an equal footing the temporary electronic transition and nuclear motion during laser-molecular interaction. By using the EPI we have intuitively demonstrated the population transfer in vibrational H$_2^+$ exposed to extreme ultraviolet pulses, revealing the energy sharing rule for the correlated electron and nuclei. We further show that the EPI can be extended to uncover the origins of the distinct energy sharing mechanisms in multi-photon and tunneling regimes. The present study has clarified a long-standing issue about the dissociative ionization of H$_2^+$ and paves the way to identify instantaneous molecular dynamics in strong fields

Isolated sub-100-attosecond pulse generation via controlling electron dynamics

A new method to coherently control the electron dynamics is proposed using a few-cycle laser pulse in combination with a controlling field. It is shown that this method not only broadens the attosecond pulse bandwidth, but also reduces the chirp, then an isolated 80-as pulse is straightforwardly obtained and even shorter pulse is achievable by increasing the intensity of the controlling field. Such ultrashort pulses allow one to investigate ultrafast electronic processes which have never be achieved before. In addition, the few-cycle synthesized pulse is expected to manipulate a wide range of laser-atom interactions.Comment: 11 pages, 4 figure

Revisiting the tunnelling site of electrons in strong field enhanced ionization of molecules

We investigated electron emissions in strong field enhanced ionization of asymmetric diatomic molecules by quantum calculations. It is demonstrated that the widely-used intuitive physical pic- ture, i.e., electron wave packet direct ionization from the up-field site (DIU), is incomplete. Besides DIU, we find another two new ionization channels, the field-induced excitation with subsequent ionization from the down-field site (ESID), and the up-field site (ESIU). The contributions from these channels depend on the molecular asymmetry and internuclear distance. Our work provides a more comprehensive physical picture for the long-standing issue about enhanced ionization of diatomic molecules

Molecular orbital tomography beyond the plane wave approximation

The use of plane wave approximation in molecular orbital tomography via high-order harmonic generation has been questioned since it was proposed, owing to the fact that it ignores the essential property of the continuum wave function. To address this problem, we develop a theory to retrieve the valence molecular orbital directly utilizing molecular continuum wave function which takes into account the influence of the parent ion field on the continuum electrons. By transforming this wave function into momentum space, we show that the mapping from the relevant molecular orbital to the high-order harmonic spectra is still invertible. As an example, the highest orbital of $\mathrm{N_2}$ is successfully reconstructed and it shows good agreement with the \emph{ab initio} orbital. Our work clarifies the long-standing controversy and strengthens the theoretical basis of molecular orbital tomography

View Adaptive Recurrent Neural Networks for High Performance Human Action Recognition from Skeleton Data

Skeleton-based human action recognition has recently attracted increasing attention due to the popularity of 3D skeleton data. One main challenge lies in the large view variations in captured human actions. We propose a novel view adaptation scheme to automatically regulate observation viewpoints during the occurrence of an action. Rather than re-positioning the skeletons based on a human defined prior criterion, we design a view adaptive recurrent neural network (RNN) with LSTM architecture, which enables the network itself to adapt to the most suitable observation viewpoints from end to end. Extensive experiment analyses show that the proposed view adaptive RNN model strives to (1) transform the skeletons of various views to much more consistent viewpoints and (2) maintain the continuity of the action rather than transforming every frame to the same position with the same body orientation. Our model achieves significant improvement over the state-of-the-art approaches on three benchmark datasets.Comment: ICCV201

Interference of high-order harmonics generated from molecules at different alignment angles

We theoretically investigate the interference effect of high-order harmonics generated from molecules at different alignment angles. It is shown that the interference of the harmonic emissions from molecules aligned at different angles can significantly modulate the spectra and result in the anomalous harmonic cutoffs observed in a recent experiment [ Nature Phys. 7, 822 (2011) ]. The shift of the spectral minimum position with decreasing the degree of alignment is also explained by the interference effect of the harmonic emissions.Comment: 6 pages,5 figures,journa

Probing rotational wave-packet dynamics with the structural minimum in high-order harmonic spectra

We investigate the alignment-dependent high-order harmonic spectrum generated from nonadiabatically aligned molecules around the first half rotational revival. It is found that the evolution of the molecular alignment is encoded in the structural minima. To reveal the relation between the molecular alignment and the structural minimum in the high-order harmonic spectrum, we perform an analysis based on the two-center interference model. Our analysis shows that the structural minimum position depends linearly on the inverse of the alignment parameter $$. This linear relation indicates the possibility of probing the rotational wave-packet dynamics by measuring the spectral minima

Semantics-Guided Neural Networks for Efficient Skeleton-Based Human Action Recognition

Skeleton-based human action recognition has attracted great interest thanks to the easy accessibility of the human skeleton data. Recently, there is a trend of using very deep feedforward neural networks to model the 3D coordinates of joints without considering the computational efficiency. In this paper, we propose a simple yet effective semantics-guided neural network (SGN) for skeleton-based action recognition. We explicitly introduce the high level semantics of joints (joint type and frame index) into the network to enhance the feature representation capability. In addition, we exploit the relationship of joints hierarchically through two modules, i.e., a joint-level module for modeling the correlations of joints in the same frame and a framelevel module for modeling the dependencies of frames by taking the joints in the same frame as a whole. A strong baseline is proposed to facilitate the study of this field. With an order of magnitude smaller model size than most previous works, SGN achieves the state-of-the-art performance on the NTU60, NTU120, and SYSU datasets. The source code is available at https://github.com/microsoft/SGN.Comment: Accepted by CVPR2020. The source code is available at https://github.com/microsoft/SG