arXiv subjects

J. Wilkinson

Publications and source records attributed to J. Wilkinson.

4 recordsLinked to original sources

arXiv2025

Observation of a gapped phase in the one-dimensional $S = {\frac{1}{2}}$ Heisenberg antiferromagnetic chain Cu(Ampy)ClBr

Spin-1/2 Heisenberg antiferromagnetic frustrated spin chain systems display exotic ground states with unconventional excitations and distinct quantum phase transitions as the ratio of next-nearest-neighbor to nearest-neighbor coupling is tuned. We present a comprehensive investigation of the structural, magnetic, and thermodynamics properties of the spin-1/2 compound, Cu(Ampy)ClBr (Ampy= C$_6$H$_8$N$_2$ = 2-(Aminomethyl)pyridine) via x-ray diffraction, magnetization, specific heat, $^1$H nuclear magnetic resonance (NMR), electron spin resonance (ESR), and muon spin relaxation ($\mu$SR) techniques. The crystal structure features an anisotropic triangular chain lattice of magnetic Cu$^{2+}$ ions. Our bulk and local probe experiments detect neither long-range magnetic ordering nor spin freezing down to 0.06 K despite the presence of moderate antiferromagnetic interaction between Cu$^{2+}$ spins as reflected by a Curie-Weiss temperature of about $-9$ K from the bulk susceptibility data. A broad maximum is observed at about 9 K in magnetic susceptibility and specific heat data, indicating the onset of short-range spin correlations. At low temperatures, the zero-field magnetic specific heat and the $^1$H NMR spin-lattice relaxation rate follow an exponential temperature dependence, indicating the presence of gapped magnetic excitations. Furthermore, persistent spin dynamics down to 0.088 K observed by zero-field $\mu$SR evidences lack of any static magnetism.

cond-mat.str-el↗

arXiv2024

Muon spectroscopy investigation of anomalous dynamic magnetism in NiI$_2$

We present the results of muon-spin relaxation ($\mu^{+}$SR) measurements of the van der Waals magnet NiI$_2$, which probe magnetic phase transitions at $T_{\mathrm{N1}}=73$~K and $T_{\mathrm{N2}}=60$~K. Supporting density functional theory (DFT) calculations allow the determination of a single muon stopping site whose magnetic environment is consistent with the proposed ground-state magnetic structure. $\mu^{+}$SR measurements of the dynamics reveal behavior consistent with spin-wave excitations below $T_{\mathrm{N2}}$. In the region $T_{\mathrm{N2}}<T<T_{\mathrm{N1}}$ the character of the dynamics changes qualitatively, resulting in an unusual region of temperature-independent fluctuations.

cond-mat.str-el↗

arXiv2022

How do dataset characteristics affect the performance of propensity score methods and regression for controlling confounding in observational studies? A simulation study

In observational studies, researchers must select a method to control for confounding. Options include propensity score methods and regression. It remains unclear how dataset characteristics (size, overlap in propensity scores, exposure prevalence) influence the relative performance of the methods, making it difficult to select the best method for a particular dataset. A simulation study to evaluate the role of dataset characteristics on the performance of propensity score methods, compared to logistic regression, for estimating a marginal odds ratio in the presence of confounding was conducted. Outcomes were simulated from logistic and complementary log-log models, and size, overlap in propensity scores, and prevalence of the exposure were varied. Regression showed poor coverage for small sample sizes, but with large sample sizes it was more robust to imbalance in propensity scores and low exposure prevalence than were propensity score methods. Propensity score methods frequently displayed suboptimal coverage, particularly as overlap in propensity scores decreased. These problems were exacerbated at larger sample sizes. Power of matching methods was particularly affected by lack of overlap, low prevalence of exposure, and small sample size. Performance of inverse probability of treatment weighting depended heavily on dataset characteristics, with poor coverage and bias with low overlap. The advantage of regression for large data size was less clear in sensitivity analysis with a complementary log-log outcome generation mechanism and unmeasured confounding, with superior bias and error but lower coverage than nearest neighbour and caliper matching.

stat.ME↗

arXiv2021

Justification for the use of Markovian Langevin statistics in the modelling of activated surface diffusion

Low temperature surface diffusion is driven by the thermally activated hopping of adatoms between adsorption sites. Helium spin-echo techniques, capable of measuring the sub-picosecond motion of individual adatoms, have enabled the bench-marking of many important adsorbate-substrate properties. The well-known Markovian Langevin equation has emerged as the standard tool for the interpretation of such experimental data, replacing adatom-substrate interactions with stochastic white noise and linear friction. However, the consequences of ignoring the colored noise spectrum and non-linearities inherent to surface systems are not known. Through the computational study of three alternative models of adatom motion, we show that the hopping rate and jump distributions of an adatom are fixed to within a few percent by the potential energy surface and a new generalized energy exchange rate parameter alone, independent of the model used. This result justifies the use of the Markovian Langevin equation, regardless of the true statistical nature of adatom forces, provided results are quoted in terms of the new energy exchange rate parameter. Moreover, numerous mechanisms for the effect of noise correlations and non-linear friction on the energy exchange rate are proposed which likely contribute to activated surface diffusion and activated processes more generally.

cond-mat.stat-mech↗