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Raymond J. Spiteri

Publications and source records attributed to Raymond J. Spiteri.

At least 19 recordsLinked to original sources
arXiv2026

Coarse-Graining Agent-Based Models of Bacterial Infections

Agent-based models (ABMs) provide a natural framework for representing cell-level rules and spatial heterogeneity in bacterial infections, but their computational cost limits their use for macroscopic tissue-scale simulations and broad parameter exploration. We derive a deterministic coarse-grained description for a class of bacterial-infection ABMs in which immune cells and extracellular bacteria diffuse, immune cells ingest nearby bacteria, and intracellular bacterial loads evolve through prescribed birth and clearance processes. The first coarse-grained model is a semidiscrete reaction--diffusion system that retains a discrete internal state for each immune-cell bacterial load while representing cell and bacterial populations by continuum concentration fields. The key technical step is the derivation of state-dependent effective ingestion rates from the microscopic ABM parameters: these rates are obtained by solving an auxiliary diffusion problem around a single bacterium and computing the flux of immune cells into the interaction region. We then take a continuum limit in the internal state variable, yielding a state-structured reaction--diffusion system in which intracellular dynamics appear as advection and diffusion in state space. Numerical comparisons with ensemble-averaged ABM simulations show close agreement in biologically motivated parameter regimes. The resulting framework preserves the rule-based structure of the ABM while producing PDE models that are substantially more tractable for large-scale simulation and parameter studies.

q-bio.CB↗
arXiv2026

Learning to Advect: A Neural Semi-Lagrangian Architecture for Weather Forecasting

Recent machine-learning approaches to weather forecasting often employ a monolithic architecture in which distinct physical mechanisms-advection (long-range transport), diffusion-like mixing, thermodynamic processes, and forcing-are represented implicitly within a single large network. This is particularly problematic for advection, where long-range transport typically requires expensive global interaction mechanisms or deep stacks of local convolutional layers. To mitigate this, we present PARADIS, a physics-inspired global weather prediction model that enforces inductive biases on network behavior through a functional decomposition into advection, diffusion, and reaction blocks acting on latent variables. We implement advection through a Neural Semi-Lagrangian operator that performs trajectory-based transport via differentiable interpolation on the sphere, enabling end-to-end learning of both the latent modes to be transported and their characteristic trajectories. Diffusion-like processes are modeled by depthwise-separable spatial mixing, whereas local source terms and vertical interactions are handled via pointwise channel interactions, yielding a physically structured operator decomposition. Evaluated on ERA5 benchmarks, PARADIS achieves competitive deterministic forecast skill, with particularly strong short-lead performance, while preserving substantially better spectral fidelity and forecast activity during medium-range rollouts.

cs.LG↗
arXiv2026

Thermodynamically Constrained Information Geometric Regularization for Compressible Flows

We construct and analyze a thermodynamic extension of the recently proposed information geometric regularization of Cao and Schäfer. The construction extends their shock-mitigating Hessian metric geometry using the Shannon entropy to constrain the regularized motion based on a thermodynamic length. Reformulating the equations in terms of mass and specific entropy explicitly connects the thermodynamic state to a position in the diffeomorphism group, allowing for a derivation of the regularized equations using an information geometric mechanics formalism based on geodesics on a Hessian manifold with a dual affine connection. The dynamics are defined using a pullback geometry for the Levi--Civita connection, describing constrained geodesic motion, and the cubic Amari--Chentsov tensor describing the information geometric correction. This new compressible fluid model introduces an anisotropic stress tensor to the momentum equation that vanishes along isentropic directions and an additional elliptic equation coupled to the barotropic regularization. Numerical simulations in one and two spatial dimensions demonstrate that the geometrically consistent incorporation of a thermodynamic constraint mitigates cusp singularities previously observed in other approaches while still maintaining the benefits of an inviscid regularization.

math.NA↗
arXiv2025

Analytical solutions for the Extracellular-Membrane-Intracellular model

The Extracellular-Membrane-Intracellular (EMI) model is a novel mathematical framework for cardiac electrophysiology simulations. The EMI model provides a more detailed description of the heart's electrical activity compared to traditional monodomain and bidomain models, potentially making it better-suited for understanding the electrical dynamics of the heart under pathological conditions. In this paper, we derive and verify several analytical solutions for the EMI model. Specifically, we obtain a family of solutions for a single two-dimensional cell in polar coordinates and for a pair of coupled three-dimensional cells in spherical coordinates. We also introduce a manufactured solution for N three-dimensional cells in Cartesian coordinates. To verify the analytical solutions, we conduct numerical experiments using the mortar finite element method combined with operator splitting. The results demonstrate that the analytical solutions are effective for verifying the accuracy of numerical simulations of the EMI model.

math.NA↗
arXiv2025

Non-Linear behavior of the Electron Cyclotron Drift Instability and the Suppression of Anomalous Current

We present results of one-dimensional collisionless simulations of plasma turbulence and related anomalous electron current of the Electron Cyclotron Drift Instability (ECDI). Our highly resolved, long-term simulations of xenon plasma in the magnetic field performed with the WarpX particle-in-cell (PIC) code show several intermediate non-linear stages before the system enters a stationary state with significantly increased electron temperature and a finite level of energy in the electrostatic fluctuations. In early and intermediate non-linear stages, the fluctuations are driven by the electron cyclotron resonances gradually shifting from higher ($m>1$) modes to the fundamental $m=1$ resonance. Enhanced resonant growth is observed from the point when the cyclotron $m=1$ mode coincides with the most unstable ion-acoustic mode. In the final stage, the anomalous electron current existing in intermediate stages is quenched to zero. Following this quenching, our simulations reveal a transition from ECDI-driven dynamics to saturated ion-acoustic turbulence. The modification of the electron and ion distribution functions and their roles in the non-linear developments and saturation of the instability are analyzed at different non-linear stages. The non-linear development of ECDI driven by the $\mathbf{E} \times \mathbf{B}$ electron drift from the applied current and the ECDI driven by the ion beam perpendicular to the magnetic field are compared and characterized as two perspectives of the instability, observed through different Doppler-shifted frames. An extension of this work incorporating full the dynamics of magnetized ions for ECDI driven by a hydrogen ion beam is shown to develop full beam inversion, with the periodic bursts of growth-saturation cycles of ECDI.

physics.plasm-ph↗
arXiv2025

Improving the stability and efficiency of high-order operator-splitting methods

Operator-splitting methods are widely used to solve differential equations, especially those that arise from multi-scale or multi-physics models, because a monolithic (single-method) approach may be inefficient or even infeasible. The most common operator-splitting methods are the first-order Lie--Trotter (or Godunov) and the second-order Strang (Strang--Marchuk) splitting methods. High-order splitting methods with real coefficients require backward-in-time integration in each operator and hence may be adversely impacted by instability for certain operators such as diffusion. However, besides the method coefficients, there are many other ancillary aspects to an overall operator-splitting method that are important but often overlooked. For example, the operator ordering and the choice of sub-integration methods can significantly affect the stability and efficiency of an operator-splitting method. In this paper, we investigate some design principles for the construction of operator-splitting methods, including minimization of local error measure, choice of sub-integration method, maximization of linear stability, and minimization of overall computational cost. We propose a new four-stage, third-order, 2-split operator-splitting method with seven sub-integrations per step and optimized linear stability for a benchmark problem from cardiac electrophysiology. We then propose a general principle to further improve stability and efficiency of such operator-splitting methods by using low-order, explicit sub-integrators for unstable sub-integrations. We demonstrate an almost 30\% improvement in the performance of methods derived from these design principles compared to the best-known third-order methods.

math.NA↗
arXiv2024

pythOS: A Python library for solving IVPs by operator splitting

Operator-splitting methods are widespread in the numerical solution of differential equations, especially the initial-value problems in ordinary differential equations that arise from a method-of-lines discretization of partial differential equations. Such problems can often be solved more effectively by treating the various terms individually with specialized methods rather than simultaneously in a monolithic fashion. This paper describes \pythOS, a Python software library for the systematic solution of differential equations by operator-splitting methods. The functionality of \pythOS\ focuses on fractional-step methods, including those with real and complex coefficients, but it also implements additive Runge--Kutta methods, generalized additive Runge--Kutta methods, and multi-rate, and multi-rate infinitesimal methods. Experimentation with the solution of practical problems is facilitated through an interface to the \Firedrake\ library for the finite element spatial discretization of partial differential equations and further enhanced by the convenient implementation of exponential time-integration methods and fully implicit Runge--Kutta methods available from the \Irksome\ software library. The functionality of \pythOS\ as well as some less generally appreciated aspects of operator-splitting methods are demonstrated by means of examples.

math.NA↗
arXiv2024

A pair of Second-order complex-valued, N-split operator-splitting methods

The use of operator-splitting methods to solve differential equations is widespread, but the methods are generally only defined for a given number of operators, most commonly two. Most operator-splitting methods are not generalizable to problems with $N$ operators for arbitrary $N$. In fact, there are only two known methods that can be applied to general $N$-split problems: the first-order Lie--Trotter (or Godunov) method and the second-order Strang (or Strang--Marchuk) method. In this paper, we derive two second-order operator-splitting methods that also generalize to $N$-split problems. These methods are complex valued but have positive real parts, giving them favorable stability properties, and require few sub-integrations per stage, making them computationally inexpensive. They can also be used as base methods from which to construct higher-order $N$-split operator-splitting methods with positive real parts. We verify the orders of accuracy of these new $N$-split methods and demonstrate their favorable efficiency properties against well-known real-valued operator-splitting methods on both real-valued and complex-valued differential equations.

math.NA↗
arXiv2023

A complementary experimental study of epitaxial La0.67Sr0.33MnO3 to identify morphological and chemical disorder

Gaining insight into the characteristics of epitaxial complex oxide films is essential to control the behavior of devices and catalytic processes. It is known that substrate induced strain, doping, and layer growth can affect the electronic and magnetic properties of the film's bulk. In this study, we demonstrate a clear distinction between the bulk and surface of thin films of La0.67Sr0.33MnO3 in terms of chemical composition, electronic disorder, and surface morphology. We employed a combined experimental approach of X-ray based characterization methods and scanning probe microscopy. X-ray diffraction and resonant X-ray reflectivity revealed surface non-stochiometry in the strontium and lanthanum, as well as an accumulation of oxygen vacancies. Scanning tunneling microscopy showed a staggered growth surface morphology accompanied by an electronic phase separation (EPS) related to this non-stochiometry. The EPS is likely responsible for the temperature-dependent resistivity transition and is a cause of a proposed mixed-phase ferromagnetic and paramagnetic state near room temperature in these thin films.

cond-mat.mtrl-sci↗
arXiv2023

Beyond domain alignment: Revealing the effect of intrinsic magnetic order on electrochemical water splitting

To reach a long term viable green hydrogen economy, rational design of active oxygen evolution reaction (OER) catalysts is critical. An important hurdle in this reaction originates from the fact that the reactants are singlet molecules, whereas the oxygen molecule has a triplet ground state with parallel spin alignment, implying that magnetic order in the catalyst is essential. Accordingly, multiple experimentalists reported a positive effect of external magnetic fields on OER activity of ferromagnetic catalysts. However, it remains a challenge to investigate the influence of the intrinsic magnetic order on catalytic activity. Here, we tuned the intrinsic magnetic order of epitaxial La$_{0.67}$Sr$_{0.33}$MnO$_{3}$ thin film model catalysts from ferro- to paramagnetic by changing the temperature in-situ during water electrolysis. Using this strategy, we show that ferromagnetic ordering below the Curie temperature enhances OER activity. Moreover, we show a slight current density enhancement upon application of an external magnetic field and find that the dependence of magnetic field direction correlates with the magnetic anisotropy in the catalyst film. Our work thus suggests that both the intrinsic magnetic order in La$_{0.67}$Sr$_{0.33}$MnO$_{3}$ films and magnetic domain alignment increase their catalytic activity. We observe no long-range magnetic order at the catalytic surface, implying that the OER enhancement is connected to the magnetic order of the bulk catalyst. Combining the effects found with existing literature, we propose a unifying picture for the spin-polarized enhancement in magnetic oxide catalysts.

cond-mat.mtrl-sci↗
arXiv2023

Beyond Strang: A practical assessment of some second-order 3-splitting methods

Operator splitting is a popular divide-and-conquer strategy for solving differential equations. Typically, the right-hand side of the differential equation is split into a number of parts that are then integrated separately. Many methods are known that split the right-hand side into two parts. This approach is limiting, however, and there are situations when 3-splitting is more natural and ultimately more advantageous. The second-order Strang operator-splitting method readily generalizes to a right-hand side splitting into any number of operators. It is arguably the most popular method for 3-splitting because of its efficiency, ease of implementation, and intuitive nature. Other 3-splitting methods exist, but they are less well-known, and \rev{analysis and} evaluation of their performance in practice are scarce. We demonstrate the effectiveness of some alternative 3-split, second-order methods to Strang splitting on two problems: the reaction-diffusion Brusselator, which can be split into three parts that each have closed-form solutions, and the kinetic Vlasov--Poisson equations that is used in semi-Lagrangian plasma simulations. We find alternative second-order 3-operator-splitting methods that realize efficiency gains of 10\%--20\% over traditional Strang splitting. Our analysis for the practical assessment of efficiency of operator-splitting methods includes the computational cost of the integrators and can be used in method design.

math.NA↗
arXiv2023

Physiological accuracy in simulating refractory cardiac tissue: the volume-averaged bidomain model vs. the cell-based EMI model

The refractory period of cardiac tissue can be quantitatively described using strength-interval (SI) curves. The information captured in SI curves is pertinent to the design of anti-arrhythmic devices including pacemakers and implantable cardioverter defibrillators. As computational cardiac modelling becomes more prevalent, it is feasible to consider the generation of computationally derived SI curves as a supplement or precursor to curves that are experimentally derived. It is beneficial, therefore, to examine the profiles of the SI curves produced by different cardiac tissue models to determine whether some models capture the refractory period more accurately than others. In this study, we compare the unipolar SI curves of two tissue models: the current state-of-the-art bidomain model and the recently developed extracellular-membrane-intracellular (EMI) model. The EMI model's resolution of individual cell structure makes it a more detailed model than the bidomain model, which forgoes the structure of individual cardiac cells in favour of treating them homogeneously as a continuum. We find that the resulting SI curves elucidate differences between the models, including that the behaviour of the EMI model is noticeably closer to the refractory behaviour of experimental data compared to that of the bidomain model. These results hold implications for future computational pacemaker simulations and shed light on the predicted refractory properties of cardiac tissue from each model.

math.NA↗
arXiv2023

The electron cyclotron drift instability: a comparison of particle-in-cell and continuum Vlasov simulations

The linear and nonlinear characteristics of the electron cyclotron drift instability (ECDI) have been studied through the particle-in-cell (PIC) and continuum Vlasov simulation methods in connection with the effects of the azimuthal length (in the $E \times B$ direction) on the simulations. Simulation results for a long azimuthal length (17.82 cm $= 627\;v_d/ω_{ce}$, where $ω_{ce}$ is the electron cyclotron frequency and $v_d$ is the $E\times B$ drift of the electrons) are reported, for which a high resolution is achieved in Fourier space. For simulations with a long azimuthal length, the linear growth rates of the PIC simulations show a considerable discrepancy with the theory, whereas the linear growth rate of the Vlasov simulations remains close to the theory. In the nonlinear regime, the inverse cascade is shown in both PIC and Vlasov simulations with a sufficiently large azimuthal length. In simulations with a short azimuthal length, however, the inverse cascade is barely observed. Instead, the PIC simulations with a short azimuthal length (0.5625 cm $=19.8\;v_d/ω_{ce}$) show an essentially continuous nonlinear dispersion, similar to what is predicted by the ion-sound turbulence theory. It is shown that, in the PIC and Vlasov simulations, the inverse cascade coincides with the formation and merging of electron structures in phase space. This process, however, terminates differently in the PIC simulations compared with the Vlasov simulations. Larger amplitudes of ECDI fluctuations are observed in the PIC simulations compared with the Vlasov simulations, leading to an intensified electron heating and anomalous current. This suggests that the statistical noise of PIC simulations might contribute to the extreme electron heating that has been observed in previous studies.

physics.plasm-ph↗
arXiv2022

Fractional-Step Runge--Kutta Methods: Representation and Linear Stability Analysis

Fractional-step methods are a popular and powerful divide-and-conquer approach for the numerical solution of differential equations. When the integrators of the fractional steps are Runge--Kutta methods, such methods can be written as generalized additive Runge--Kutta (GARK) methods, and thus the representation and analysis of such methods can be done through the GARK framework. We show how the general Butcher tableau representation and linear stability of such methods are related to the coefficients of the splitting method, the individual sub-integrators, and the order in which they are applied. We use this framework to explain some observations in the literature about fractional-step methods such as the choice of sub-integrators, the order in which they are applied, and the role played by negative splitting coefficients in the stability of the method.

math.NA↗
arXiv2022

Nonlinear regimes of the electron cyclotron drift instability in Vlasov simulations

We report on a novel investigation of the nonlinear regime of the electron cyclotron drift instability, using a grid-based Vlasov simulation. It is shown that the instability occurs as a series of cyclotron resonances with the electron beam mode due to the $E\times B$ drift. In the nonlinear regime, we observe condensation of fluctuations energy toward the lowest resonance mode and below, i.e., an inverse energy cascade. It is shown that the characteristics of the nonlinear saturation state remain far from the ion-sound regime.

physics.plasm-ph↗
arXiv2021

Backward waves in the nonlinear regime of the Buneman instability

Observation of low- and high-frequency backward waves in the nonlinear regime of the Buneman instability is reported. Intense low-frequency backward waves propagating in the direction opposite to the electron drift (with respect to the ion population) of ions and electrons are found. The excitation of these waves is explained based on the linear theory for the stability of the electron velocity distribution function that is modified by nonlinear effects. In the nonlinear regime, the electron distribution exhibits a wide plateau formed by electron hole trapping and extends into the negative velocity region. It is shown that within the linear approach, the backward waves correspond to the weakly unstable or marginally stable modes generated by the large population of particles with negative velocities.

physics.plasm-ph↗
arXiv2021

The role of noise in PIC and Vlasov simulations of the Buneman instability

The effects of noise in particle-in-cell (PIC) and Vlasov simulations of the Buneman instability in unmagnetized plasmas are studied. It is found that, in the regime of low drift velocity, the linear stage of the instability in PIC simulations differs significantly from the theoretical predictions, whereas in the Vlasov simulations it does not. A series of highly resolved PIC simulations with increasingly large numbers of macroparticles per cell is performed using a number of different PIC codes. All the simulations predict highly similar growth rates that are several times larger than those calculated from the linear theory. As a result, we find that the true convergence of the PIC simulations in the linear regime is elusive to achieve in practice and can easily be misidentified. The discrepancy between the theoretical and observed growth rates is attributed to the initial noise inherently present in PIC simulations, but not in Vlasov simulations, that causes particle trapping even though the fraction of trapped particles is low. We show analytically that even weak distortions of the electron velocity distribution function (such as flattening due to particle trapping) result in significant modifications of the growth rates. It is also found that the common quiet-start method for PIC simulations leads to more accurate growth rates but only if the maximum growth rate mode is perturbed initially. We demonstrate that the quiet-start method does not completely remedy the noise problem because the simulations generally exhibit inconsistencies with the linear theory.

physics.plasm-ph↗
arXiv2021

Inherent Structure Landscape of Hard Spheres Confined to Narrow Cylindrical Channels

The inherent structure landscape for a system of hard spheres confined to a hard cylindrical channel, such that spheres can only contact their first and second neighbours, is studied using an analytical model that extends previous results [Phys. Rev. Lett. 115, 025702 (2015)] to provide a comprehensive picture of jammed packings over a range of packing densities. In the model, a packing is described as an arrangement of $k$ helical sections, separated by defects, that have alternating helical twist directions and where all spheres satisfy local jamming constraints. The structure of each helical section is determined by a single helical twist angle, and a jammed packing is obtained by minimizing the length of the channel per particle with respect to the $k$ helical section angles. An analysis of a small system of $N=20$ spheres shows that the basins on the inherent structure landscape associated with these helical arrangements split into a number of distinct jammed states separated by low barriers giving rise to a degree of hierarchical organization. The model accurately predicts the geometric properties of packings generated using the Lubachevsky and Stillinger compression scheme ($N=10^4$) and provides insight into the nature of the probability distribution of helical section lengths.

cond-mat.soft↗