Ultrafast Electron Microscopy with Relativistic Femtosecond Electron Pulses

An ultrafast electron microscope (UEM) with a femtosecond temporal resolution is a “dream machine” desired for studies of ultrafast structural dynamics in materials. In this chapter, we present a brief overview of the historical development of current UEMs with nonrelativistic electron pulses to illustrate the need for relativistic-energy electron pulses. We then describe the concept and development of a UEM with relativistic femtosecond electron pulses generated by a radio frequency (RF) acceleration-based photoemission gun. The technique of RF electron gun and physical characteristics of the relativistic electron pulses are described. Demonstrations of UEM images acquired using approximately 100 fs long electron pulses with energies of 3 MeV are presented. Finally, we report a single-shot diffraction imaging methodology in the UEM with a relativistic femtosecond electron pulse for studies of laser-induced ultrafast phenomena in crystalline materials

Femtosecond Electron Diffraction Using Relativistic Electron Pulses

Observation of atomic-scale structural motion in matter with femtosecond temporal resolution is of considerable interest to scientists and paves the way for new science and applications. For this purpose, ultrafast electron diffraction (UED) imaging using femtosecond electron pulses is a very promising technique, as electrons have a larger elastic scattering cross section as compared to photons or X-rays and can be easily focused in observation with high spatial resolution. In this chapter, we first give an overview of the historical development of current nonrelativistic UEDs and discuss the potentials of UEDs with relativistic electron pulses. Second, we describe the concept and development of relativistic UED with femtosecond electron pulses generated by a radio-frequency acceleration-based photoemission gun. Some demonstrations of diffraction imaging of crystalline materials using 3-MeV electron pulses with durations of ∼100 fs are presented. Finally, we report a methodology of single-shot time-resolved diffraction imaging for the study of ultrafast dynamics of photo-induced irreversible phase transitions

Multi-Perspective Relevance Matching with Hierarchical ConvNets for Social Media Search

Despite substantial interest in applications of neural networks to information retrieval, neural ranking models have only been applied to standard ad hoc retrieval tasks over web pages and newswire documents. This paper proposes MP-HCNN (Multi-Perspective Hierarchical Convolutional Neural Network) a novel neural ranking model specifically designed for ranking short social media posts. We identify document length, informal language, and heterogeneous relevance signals as features that distinguish documents in our domain, and present a model specifically designed with these characteristics in mind. Our model uses hierarchical convolutional layers to learn latent semantic soft-match relevance signals at the character, word, and phrase levels. A pooling-based similarity measurement layer integrates evidence from multiple types of matches between the query, the social media post, as well as URLs contained in the post. Extensive experiments using Twitter data from the TREC Microblog Tracks 2011--2014 show that our model significantly outperforms prior feature-based as well and existing neural ranking models. To our best knowledge, this paper presents the first substantial work tackling search over social media posts using neural ranking models.Comment: AAAI 2019, 10 page

Time lapsed AVAZ seismic modeling research on CO2 storage monitoring

CCUS (Carbon Capture, Utilization and Storage) now is a lead way to reduce greenhouse effect such as carbon dioxide emission in the world. This paper presents an integrated overview of seismic monitoring technology when CO2 injection process. Mainly is time-lapse seismic method .Time-lapse seismic method is a feasible way to monitor CO2 injection process when CO2 interaction with minerals, which is proved an effective method in CCUS experiments. AVAZ (Amplitude versus Azimuth) seismic method is proved a useful tool to indentify CO2 injection process, which can detect fluid-induced seismic anisotropic response and locating where CO2 flow to in reservoirs, therefore, it’s an effective way to monitor CO2 flow in CO2 monitoring process. Since we develop AVAZ modelling experiment base on rock physics theory to modeling the time-lapse AVAZ seismic reservoir response. The research show fluid saturation and pressure behave two main factors influence modeling seismic AVAZ response. Meanwhile the AVAZ response can also be detect by seismic AVAZ data