http://hdl.handle.net/10453/37629 2026-11-03T09:00:20Z http://hdl.handle.net/10453/197284 Title: A comprehensive Hirshfeld and iterative-Hirshfeld dataset for 5080 inorganic materials from first-principles calculations Authors: Su, T; Li, M; Wang, X; Hu, S; Zhang, TY Abstract: Atomic charge descriptors are widely used to interpret chemical bonding, quantify charge transfer, and construct data-driven models for inorganic materials. This data article describes a first-principles dataset containing Hirshfeld and iterative-Hirshfeld outputs for 5080 inorganic materials, corresponding to 31,288 atomic sites and 77 chemical elements. For each material, the database stores the atomic structure, Materials Project identifier, calculation metadata, standard Hirshfeld charges, iterative Hirshfeld charges, Hirshfeld relative volumes, and iterative-Hirshfeld relative volumes. The data were generated using density-functional theory calculations in VASP with a consistent local-density-approximation setup, a 500 eV plane-wave cutoff, 0.25 inverse angstrom k-point spacing, and an electronic convergence threshold of 1e-6 eV. The dataset is distributed as an ASE database with accompanying JSON statistics, analysis scripts, figures, and a Flask-based web interface. It can support charge-transfer analysis, benchmarking of charge-partitioning methods, and charge-informed machine-learning workflows in which atomic populations, charge-transfer magnitudes, or volume descriptors are used as features for materials-property prediction. 2026-08-01T00:00:00Z http://hdl.handle.net/10453/197193 Title: A Branch Group With Unsolvable Conjugacy Problem Authors: Bishop, A; Schesler, E Abstract: Abstract We prove that every finitely generated residually finite group $G$ can be embedded in a finitely generated branch group $\Gamma $ such that two elements in $G$ are conjugate in $G$ if and only if they are conjugate in $\Gamma $. As an application we construct a finitely generated branch group with solvable word problem and unsolvable conjugacy problem and thereby answer a question of Bartholdi, Grigorchuk, and Šuniḱ. 2026-04-01T00:00:00Z http://hdl.handle.net/10453/196919 Title: Information-Theoretic Approach to Financial Market Modeling Authors: Platen, E Abstract: The paper treats the financial market as a communication system, using four information-theoretic assumptions to derive an idealized model with only one parameter. State variables are scalar stationary diffusions. The model maximizes the surprisal of the market and minimizes the Kullback–Leibler divergence between the benchmark-neutral pricing measure and the real-world probability measure. The state variables, their sums, and the growth optimal portfolio of the stocks evolve as squared radial Ornstein-Uhlenbeck processes in respective activity times. 2026-01-01T00:00:00Z http://hdl.handle.net/10453/196849 Title: Age-Dependent Multi-Cohort Affine Mortality Models with Cohort Correlation Authors: Zhou, Y; Garces, LP; Shen, Y; Sherris, M; Ziveyi, J Abstract: Continuous-time affine mortality models are useful in the analysis of age-cohort mortality rates as they yield a closed-form expression for survival curves, which are consistent with the dynamics of latent factors driving mortality and are well-suited for finance and insurance applications. We extend and improve these mortality models by introducing age dependence of mortality rates and correlation between cohorts. We propose and compare two classes of age-dependent mortality models, namely the age-dependent coefficient model and the age-dependent factor model. Specifically, we assess both Gaussian and Cox–Ingersoll–Ross (CIR)–type models for each category of age-dependent models. Both categories of age-dependent models involve age and calendar time, which in turn specify the cohort. Thus, our models admit an analytical form for the instantaneous correlation between mortality rates of different cohorts. Moreover, we propose two improvements to the parameter estimation process. First, to improve the estimation of cohort correlations, we regularize the parameter estimation by adding a penalty term which penalizes larger differences between empirical and estimated correlations. Second, we develop and assess a method to include incomplete cohorts into the Kalman filtering algorithm for parameter estimation. By incorporating age dependence and using incomplete cohort mortality data, we improve the goodness of fit and produce more reasonable out-of-sample forecasts of survival probabilities. We also show that regularization produces more realistic correlations between cohorts for varying age differences. Our results show that, under most circumstances, the correlation between cohorts decreases as the age difference increases. 2026-01-01T00:00:00Z