Browsing by Author "Bao, Jie"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Developing a Model Chemistry for Multiconfiguration Pair-Density Functional Theory to Study Photochemistry and Molecular Interactions
    (2021-01) Bao, Jie
    Photochemical reaction, which starts by exciting a system into an electronically excited state, is ubiquitous, for example, in the atmosphere. This has made photochemical reactions a very interesting topic. Multiconfigurational pair-density functional theory (MC-PDFT) is a powerful and efficient method for studying photochemical processes. This method has proved very efficient compared with other wave function methods, such as multi-state complete active space second order perturbation theory (MS-CASPT2), especially for large systems. Successful as MC-PDFT is, there are some limitations that stop MC-PDFT from being applied to studying photochemistry problems. The first limitation is that, like other multireference methods, the performance of MC-PDFT depends on the quality of the reference wave function, which by convention is optimized by an active-space method, such as complete active space self-consistent field (CASSCF). The second limitation is that MC-PDFT is a single-state method that does not include state interaction between reference states. This means that MC-PDFT gives wrong topologies of potential energy surfaces, which are important in studying photochemical reactions. My work is focused on resolving these two limitations. We proposed the ABC scheme and the ABC2 scheme to automatically generate the active space that gives good-quality reference wave functions thus successfully reproducing vertical excitation energies obtained from experiments or high-level calculations. We proposed the extended multi-state PDFT (XMS-PDFT) and compressed-state multi-state PDFT (CMS-PDFT) as two options to introduce state-interaction in pair-density functional theory. Among two methods, XMS-PDFT is more efficient, while CMS-PDFT is more robust. Both methods proved successful in providing correct topologies of potential energy surfaces for a variety of systems.
  • Thumbnail Image
    Item
    Towards location-aware news feed and recommendations
    (2014-06) Bao, Jie
    With the advances in positioning techniques, such as GPS, cell-towers and WiFi, users can enjoy location-based services more easily than ever before, e.g., on their smart phones and GPS devices. However, with the popularity of recommendation (e.g., Amazon \& Netflix) and socialization (like Facebook and Twitter) functionalities in the web services, users of location-based services are no longer satisfied with the static results returned from a spatial database. At the same time, more and more spatial information, such as geo-tagged photos and check-ins are generated in the traditional social networking services. As a result, users are calling for the next generation of location-based service, i.e., location aware news feed and recommendations, which can provide the user with the more personalized and socialized services.In this thesis, I present my vision of the next generation of location-aware service, which enables the social networking services with location awareness. First of all, in this thesis, I present the unique properties that location information brings to the traditional social networking and recommendation services. After that, I summarize the potential challenges in building efficient and effective location-aware news feed and recommendation services from both the system and user's perspectives. Then, I present a prototype system, (i.e., Sindbad, a location-aware social networking system), to demonstrate three main services provided in the system, as: 1) location-aware news feed service, which efficiently returns the user with spatial-aware messages from her subscribed friends. 2)~location-aware news ranking services, which provide a set of efficient news ranking and message updating algorithms for the user to get more relevant news, based on her social-spatial preferences. And 3)~location-aware recommendations, which provides suggestions based on the social knowledge from the local experts and the preferences mined from a user's location history. Finally, the thesis is concluded with the overall contributions and some potential further research directions.