Tailored Density Cumulant Theory A Novel Theoretical Approach for Strongly Correlated Systems

Electron correlation is an important quantum phenomenon arising from explicit pairwise Coulomb interaction of electrons. Development of theoretical approaches for efficient and accurate description of this phenomenon has always been a driving force for quantum chemistry. In many molecules and materials, electron correlation is weak. In such cases, the electrons are assumed to interact not directly with each other, but through an averaged electric field, hence the name “mean-field approximation”. From the mean-field approximation, many theoretical models are available to efficiently recover the effect of the weak correlation. However, in many new applications such as superconductor, photocatalysts and active sites of enzymes, the mean-field approximation breaks down as electron correlation becomes strong. Although theoretical models capable of describing strong correlation exist, they usually suffer from high computational and memory cost therefore are limited to small systems. Recently, hybrid models are being developed assuming that strong correlation is local, I.e. prominent for only a small subspace of the system. Whereas the strongly correlated subspace is treated extensively, the rest of the system is still modeled under mean-field approximation which makes its treatment very efficient. On the other hand, a balanced description between the strong and weak correlation is crucial for accurate results. In this presentation, I will introduce a new theoretical model termed tailored density cumulant theory (T-DCT) that efficiently describes strong and weak electron correlation in a balanced and consistent manner. Central to this theory is density cumulant, a mathematical object that captures the essence of electron correlation. I will briefly describe the theoretical formulation of T-DCT, my computer implementation, as well as show some preliminary results of the application of this approach to several chemical systems.Academic Major: Chemistr

Simulating X-ray absorption spectra with linear-response density cumulant theory

We present a new approach for simulating X-ray absorption spectra based on linear-response density cumulant theory (LR-DCT) [A. V. Copan and A. Yu. Sokolov, J. Chem. Theory Comput., 2018, 14, 4097 - 4108]. Our new method combines the LR-ODC-12 formulation of LR-DCT with core-valence separation approximation (CVS) that allows to efficiently access high-energy core-excited states. We describe our computer implementation of the CVS-approximated LR-ODC-12 method (CVS-ODC-12) and benchmark its performance by comparing simulated X-ray absorption spectra to those obtained from experiment for several small molecules. Our results demonstrate that the CVS-ODC-12 method shows a good agreement with experiment for relative spacings between transitions and their intensities, but the excitation energies are systematically overestimated. When comparing to results from excited-state coupled cluster methods with single and double excitations, the CVS-ODC-12 method shows a similar performance for intensities and peak separations, while coupled cluster spectra are less shifted, relative to experiment. An important advantage of CVS-ODC-12 is that its excitation energies are computed by diagonalizing a Hermitian matrix, which enables efficient computation of transition intensities

Block2: a comprehensive open source framework to develop and apply state-of-the-art DMRG algorithms in electronic structure and beyond

Block2 is an open source framework to implement and perform density matrix renormalization group and matrix product state algorithms. Out-of-the-box it supports the eigenstate, time-dependent, response, and finite-temperature algorithms. In addition, it carries special optimizations for ab initio electronic structure Hamiltonians and implements many quantum chemistry extensions to the density matrix renormalization group, such as dynamical correlation theories. The code is designed with an emphasis on flexibility, extensibility, and efficiency, and to support integration with external numerical packages. Here we explain the design principles and currently supported features and present numerical examples in a range of applications.Comment: 20 pages, 8 figure

Measures of Adherence to Varenicline: Impact on Smoking Cessation Outcomes

There are currently over one billion tobacco smokers worldwide and tobacco use remains a major contributor to the global disease burden. In addition to prevention, effective treatment for tobacco dependence is necessary to reduce the overall prevalence of smoking and tobacco-related disease. A significant barrier to effective treatment is low medication adherence. While varenicline is the most efficacious smoking cessation pharmacotherapy currently on the market, the impact of adherence on varenicline-assisted cessation has not been fully explored. This thesis investigated the validity of different measures of adherence to varenicline, the impact of adherence on cessation and the underlying factors contributing to low adherence. We found poor associations between self-report pill count (a widely used approach to measure smoking treatment adherence) and salivary varenicline drug concentration [Spearman rho ranges: 0.10-0.15; rate of correct classification (area under the curve ranges: 0.53-0.59)]. Approximately 20% of participants misreported pill counts relative to their varenicline drug concentration. When these individuals were excluded, the associations improved modestly suggesting self-report pill count overestimates adherence and that direct measures of adherence, such as drug concentrations, are superior. In terms of the relationship between adherence and cessation outcomes, we demonstrated that adherence based on varenicline drug concentration was predictive of both early and long-term cessation success (odds ratio ranges: 1.92-3.16), whereas adherence based on self-report pill count was not. Furthermore, a pharmacogenomic biomarker’s impact on cessation (nicotine metabolite ratio by treatment) was strengthened when adherence was confirmed by varenicline drug concentration. As lower adherence was associated with a lower likelihood of cessation success, we explored factors that lowered adherence using mediation modelling. We found that early nausea, a varenicline-related adverse effect, was associated with early-, mid- and long-term cessation success, and that this association was mediated in part by adherence, measured by varenicline concentration. Overall, our findings demonstrate the superiority of varenicline drug concentration in contrast to self-report pill count as a measure of adherence to varenicline, and provide avenues for enhancing cessation rates and reducing smoking-related disease burden.Ph.D

Construction of a virtual reality platform for computer-aided navigation Lingnan bone setting technique

ABSTRACTTo establish a standard Traditional Chinese medicine (TCM) bone setting technique, standardize the operation and inherit the TCM bone setting technique. This project was based on the interactive tracking of bone setting techniques with a dedicated position tracker, the motion tracking of bone setting techniques based on RGBD (Red Green Blue Depth) cameras, the digital analysis of bone setting techniques, and the design of the virtual reality platform for bone setting techniques. These key technical researches were combined to construct an interactive bone setting technique. The virtual simulation system can reproduce the implementation process of the expert’s bone setting technique. The user can observe the implementation of the manipulative technique from multiple angles; through human-computer interaction, the whole process of implementation of the bone setting technique can be simulated, and the movement and reduction of the affected bone can be observed at the same time. It can be used as a teaching and training system for assisting bone setting techniques. Students can use the system to carry out repeated self-training, and can instantly compare with the standard techniques of the expert database, breaking the traditional teaching mode of ‘expected and unspeakable’ and avoid directly using patients. Therefore, this research makes it possible to reduce teaching costs, reduce risks, improve teaching quality, and make up for the lack of teaching conditions. It is very positive for the inheritance of the traditional Chinese ‘intangible culture’ of bone setting techniques, and to promote the digitalization and standardization of bone setting techniques