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Yelyzaveta Satynska

Publications and source records attributed to Yelyzaveta Satynska.

2 recordsLinked to original sources

Dynamic Phase Transitions in Mean-Field Ginzburg-Landau Models: Conjugate Fields and Fourier-Mode Scaling

Dynamic phase transitions of periodically forced mean-field ferromagnets are often described by a single order parameter and a scalar conjugate field. Building from previous work, we show that, at the critical period $P_c$ of the mean-field Ginzburg-Landau (MFGL) dynamics with energy $F(m)=am^2+bm^4-hm$, the correct conjugate field is the entire even-Fourier component part of the applied field. The correct order parameter is $z_k=\sqrt{\bigl|\,m_k^2-|m_{k,c}|^2\,\bigr|}$, where $m_k$ is the $k^{th}$ Fourier component of the magnetization m(t), and $m_{k,c}$ is the $k^{th}$ Fourier component at the critical period. Using high-accuracy limit-cycle integration and Fourier analysis, we first confirm that, for periodic fields that contain only odd components, the symmetry-broken branch below $P_c$ exhibits $z_k \propto \varepsilon^{1/2}$ (computationally tested for modes $k\le30$), where $\varepsilon=(P_c-P)/P_c$. This provides strong evidence that the 1/2 scaling holds for all Fourier modes. We then find three robust facts: (1) Exactly at $P_c$, adding a small perturbation composed of even Fourier components with an overall field multiplier $h_{mult}$ yields $z_k \propto h_{mult}^{1/3}$ across many $k$. (2) Mode-resolved deviations obey a parity rule: $|δm_{2n}| \propto h_{mult}^{1/3}$ and $|δm_{2n+1}| \propto h_{mult}^{2/3}$. (3) These scalings persist in two MFGL models with higher-order nonlinearities.

cond-mat.stat-mech↗

Darts Analysis

In this paper we examine the effectiveness of five mathematical models used to predict the outcomes of amateur darts games. These models not only predict the outcomes at the start of the game, but also update their estimations as the game score changes. The models were trained and tested on a dataset consisting of games played by amateur players involving students, faculty, and staff at Roanoke College. The five models are: the null model, which is based only on the live scores, a logistic regression model, a basic simulation model, a time-adjusted simulation model, and a new variation of the Massey model which updates based on the current score. We evaluate these models using two approaches. First, we compare their Brier scores. Second, we conduct head-to-head comparisons in a betting game in which one model sets the betting odds while the other places bets. In both cases, model performance is assessed not only at the start of the game but also at the start of each round. Across both evaluation methods, the score-dependent Massey model performs the best. We conclude by illustrating how this score-dependent Massey model framework can be adapted to other competitive settings beyond darts.

stat.AP↗