Theory of magneto-optics and circular magnetic x-ray dichroism

This thesis contains three parts. In the first part, before getting into the discussion of magneto-optical properties for the systems under study, the author reviews some background subjects, such as the energy-band theory within the framework of density functional theory, the multiple scattering approach to the solution of band problem and its relation with the LMTO method, an account of the tight-binding LMTO method which we use exclusively in our calculations, the linear response theory and its application to the quantum theory of dielectric constants. In the second part, circular magnetic x-ray dichroism, as a powerful and newly developed experimental technique for quantitative study of the magnetic properties of different materials, is discussed. In the last part, the detailed study of the magneto-optical properties of some transition metals and the so-called half metallic Heusler alloys is presented

Spin symmetry and spin current of helicity eigenstates of the Luttinger Hamiltonian

A general spin symmetry argument is proposed for spin currents in semiconductors. In particular, due to the symmetry with respect to spin polarization of the helicity eigenstates of the Luttinger Hamiltonian for a hole-doped semiconductor, the spin polarized flux from a single helicity eigenstate induced by an external electric field, is canceled exactly when all such contributions from eigenstates that are degenerate in energy are summed. Thus, the net spin current predicted by Murakami et al, Science 301, 1348 (2003), cannot be produced by such a Hamiltonian. Possible symmetry breaking mechanisms which may generate a spin current are discussed

LDA-Based Topic Strength Analysis

Topic strength is an important hotspot in topic research. The evolution of topic strength not only indicates emerging new topics, but also helps us to determine whether a topic will produce some fluctuation of topic strength over time. Thus, topic strength analysis can provide significant findings in public opinion monitoring and user personalization. In this paper, we present an LDA-based topic strength analysis approach. We take topic quality into our topic strength consideration by combining local LDA and global LDA. For empirical studies, we use three data sets in real applications: film critic data of "A Chinese Odyssey" in Douban Movies, corruption news data in Sina News, and public paper data. Compared to existing approaches, experimental results show that our proposed approach can obtain better results of topic strength analysis in detecting the time of event topic occurrences and distinguishing different types of topics, and it can be used to monitor the occurrences of public opinions and the changes of public concerns

Unifying Large Language Models and Knowledge Graphs: A Roadmap

Large language models (LLMs), such as ChatGPT and GPT4, are making new waves in the field of natural language processing and artificial intelligence, due to their emergent ability and generalizability. However, LLMs are black-box models, which often fall short of capturing and accessing factual knowledge. In contrast, Knowledge Graphs (KGs), Wikipedia and Huapu for example, are structured knowledge models that explicitly store rich factual knowledge. KGs can enhance LLMs by providing external knowledge for inference and interpretability. Meanwhile, KGs are difficult to construct and evolving by nature, which challenges the existing methods in KGs to generate new facts and represent unseen knowledge. Therefore, it is complementary to unify LLMs and KGs together and simultaneously leverage their advantages. In this article, we present a forward-looking roadmap for the unification of LLMs and KGs. Our roadmap consists of three general frameworks, namely, 1) KG-enhanced LLMs, which incorporate KGs during the pre-training and inference phases of LLMs, or for the purpose of enhancing understanding of the knowledge learned by LLMs; 2) LLM-augmented KGs, that leverage LLMs for different KG tasks such as embedding, completion, construction, graph-to-text generation, and question answering; and 3) Synergized LLMs + KGs, in which LLMs and KGs play equal roles and work in a mutually beneficial way to enhance both LLMs and KGs for bidirectional reasoning driven by both data and knowledge. We review and summarize existing efforts within these three frameworks in our roadmap and pinpoint their future research directions.Comment: 29 pages, 25 figure

A Strategy for Prompt Phase Transfer of Upconverting Nanoparticles Through Surface Oleate-Mediated Supramolecular Assembly of Amino-β-Cyclodextrin

Lanthanide-doped upconverting nanoparticles (UCNPs) are promising for applications as wide as biosensing, bioimaging, controlled drug release, and cancer therapy. These applications require surface engineering of as-prepared nanocrystals, commonly coated with hydrophobic ligand of oleic acid, to enable an aqueous dispersion. However, literature-reported approaches often require a long time and/or multiple step treatment, along with several fold upconversion luminescence (UCL) intensity decrease. Here, we describe a strategy allowing oleate-capped UCNPs to become water-soluble and open-modified, with almost undiminished UCL, through ultrasonication of minutes. The prompt phase transfer was enabled by oleate-mediated supramolecular self-assembly of amino modified β-cyclodextrin (amino-β-CD) onto UCNPs surface. We showed that this method is valid for a wide range of UCNPs with quite different sizes (6–400 nm), various dopant types (Er, Tm, and Ho), and hierarchical structures (core, core-shell). Importantly, the amino group of amino-β-CD on the surface of treated UCNPs provide possibilities to introduce entities for biotargeting or functionalization, as exemplified here, a carboxylic-containing near infrared dye (Cy 7.5) that sensitizes UCNPs to enhance their UCL by ~4,820 fold when excited at ~808 nm. The described method has implications for all types of oleate-capped inorganic nanocrystals, facilitating their myriad bioapplications