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Tianyuan Cai

Publications and source records attributed to Tianyuan Cai.

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Massless Majorana spinors in the Kerr spacetime

In this paper, we show that massive Majorana spinors \eqref{1.2} do not exist if they are $t$-dependent or $ϕ$-dependent in Kerr, or Kerr-(A)dS spacetimes. For massless Majorana spinors in the non-extreme Kerr spacetime, the Dirac equation can be separated into radial and angular equations, parameterized by two complex constants $ε_1$, $ε_2$. If at least one of $ε_1$, $ε_2$ is zero, massless Majorana spinors can be solved explicitly. If $ε_1$, $ε_2$ are nonzero, we prove the nonexistence of massless time-periodic Majorana spinors in the non-extreme Kerr spacetime which are $L^p$ outside the event horizon for $ 0<p\le\frac{6}{|ε_1|+|ε_2| +2}$. We then provide the Hamiltonian formulation for massless Majorana spinors and prove that the self-adjointness of the Hamiltonian leads to the angular momentum $a=0$ and spacetime reduces to the Schwarzschild spacetime, moreover, the massless Majorana spinor must be $ϕ$-independent. Finally, we show that, in the Schwarzschild spacetime, for initial data with $L^2$ decay at infinity, the probability of the massless Majorana spinors to be in any compact region of space tends to zero as time tends to infinity.

gr-qc

THERIF: A Pipeline for Generating Themes for Readability with Iterative Feedback

Digital reading applications give readers the ability to customize fonts, sizes, and spacings, all of which have been shown to improve the reading experience for readers from different demographics. However, tweaking these text features can be challenging, especially given their interactions on the final look and feel of the text. Our solution is to offer readers preset combinations of font, character, word and line spacing, which we bundle together into reading themes. To arrive at a recommended set of reading themes, we present our THERIF pipeline, which combines crowdsourced text adjustments, ML-driven clustering of text formats, and design sessions. We show that after four iterations of our pipeline, we converge on a set of three COR themes (Compact, Open, and Relaxed) that meet diverse readers' preferences, when evaluating the reading speeds, comprehension scores, and preferences of hundreds of readers with and without dyslexia, using crowdsourced experiments.

cs.HC

Readability Research: An Interdisciplinary Approach

Readability is on the cusp of a revolution. Fixed text is becoming fluid as a proliferation of digital reading devices rewrite what a document can do. As past constraints make way for more flexible opportunities, there is great need to understand how reading formats can be tuned to the situation and the individual. We aim to provide a firm foundation for readability research, a comprehensive framework for modern, multi-disciplinary readability research. Readability refers to aspects of visual information design which impact information flow from the page to the reader. Readability can be enhanced by changes to the set of typographical characteristics of a text. These aspects can be modified on-demand, instantly improving the ease with which a reader can process and derive meaning from text. We call on a multi-disciplinary research community to take up these challenges to elevate reading outcomes and provide the tools to do so effectively.

cs.HC