Papers

The electron-positron stage of the Future Circular Collider (FCC-ee) provides exciting opportunities that are enabled by next generation particle physics detectors. This contribution presents IDEA, a detector concept optimised for FCC-ee and composed of a vertex detector based on MAPS, a very light drift chamber, a silicon wrapper, a high resolution dual-readout crystal electromagnetic calorimeter, an HTS based superconducting solenoid, a dual-readout fibre calorimeter, and three layers of muon chambers embedded in the magnet flux return yoke. In particular, the physics requirements and the technical solutions chosen in the various sub-systems to address them are discussed. This is followed by a description of the detector R&D currently in progress, test-beam results, and the expected performance on some key physics benchmarks.

Reactive flows in confined spaces involve complex flame-wall interaction (FWI). This work aims to gain more insights into the physics of the premixed near-wall flame and the wall heat flux as an important engineering relevant quantity. Two different flame configurations have been studied, including the normal flushing flame and inclined sweeping flame. By introducing the skin friction vector defined second-order tensor, direct numerical simulation (DNS) results of these two configurations show consistently that larger flame curvatures are associated with small vorticity magnitude under the influence of the vortex pair structure. Correlation of both the flame normal and tangential strain rates with the flame curvature has also been quantified. Alignment of the progress variable gradient with the most compressive eigenvector on the wall is similar to the boundary free behavior. To characterize the flame ordered structure, especially in the near-wall region, a species alignment index is proposed. The big difference in this index for flames in different regions suggests distinct flame structures. Building upon these fundamental insights, a predictive model for wall heat flux is proposed. For the purpose of applicability, realistic turbulent combustion situations need to be taken into account, for instance, flames with finite thickness, complex chemical kinetics, non-negligible near-wall reactions, and variable flame orientation relative to the wall. The model is first tested in an one-dimensional laminar flame and then validated against DNS datasets, justifying the model performance with satisfying agreement.

We demonstrate substantial field enhancement in plasma nanoshells through high-order Mie resonances using combined Mie theory and particle-in-cell simulations. Optimal shell geometries yield approximately threefold electric field enhancement for 800 nm irradiation, with transient buildup times of tens of femtoseconds before plasma expansion disrupts resonance. Few-cycle pulses produce reduced enhancement due to insufficient resonance establishment. These findings enable optimized laser-plasma interactions for applications including diagnostics of laser-cluster interaction and energetic ion production from engineered core-shell targets, highlighting the critical role of temporal dynamics in nanoplasma resonances.

Langmuir probe diagnostics are a cornerstone of plasma characterization, providing critical measurements of electron temperature, electron density, and plasma potential. However, conventional swept Langmuir probes and other traditional electrostatic probes often lack the temporal resolution necessary to capture transient plasma behavior in dynamic environments. This paper presents the design and implementation of a fast-sweeping Langmuir probe system that is open-source, low-cost, and adaptable for a wide range of plasma applications. The probe system incorporates voltage sweeping to resolve rapid fluctuations in plasma parameters at a temporal resolution of up to 200 kHz. To validate its performance, the system was implemented in the 30 kW miniature Arc jet Research Chamber (mARC II), a high-enthalpy DC arc jet facility designed for prototype testing and development. Experimental results demonstrate the probe's capability to operate in extreme aerothermal conditions, providing time-resolved electron temperature and density along the flow's radial profile. This work establishes a robust and accessible Langmuir diagnostic solution for researchers studying transient plasma behavior in high-enthalpy environments.

An attempt to construct a phenomenological theory of earthquakes is being undertaken by a small research team, which includes the author. We have only taken the first steps towards goal, but the results already obtained convincingly demonstrate the feasibility of the project. This paper is a kind of commentary on the path taken. The paper explains the essence and character of phenomenological theory. It also contains critical comments on alternative approaches to describing earthquakes. The theory is based on the concept of an earthquake source as a dynamic system, the state of which is described by a small number of phenomenological parameters. Within the framework of elementary theory, the source is described by one parameter, called the deactivation coefficient. The most important concept of the proper time of the source has been introduced, the course of which, generally speaking, differs from the course of world time. Dynamic equations describing the evolution of the source are given. The inverse problem of the source is posed, the essence of which is to calculate the phenomenological parameters based on earthquake observation data. Elementary phenomenological theory has already become a practical tool for the experimenter studying specific earthquake time series. The Appendix provides a list of previously unknown properties and patterns of earthquakes that we discovered within the framework of elementary theory. At the same time, it is noted that phenomenology itself does not lead us to a deep understanding of the essence of earthquakes. Sooner or later, the results of a complex of geophysical and physical-mathematical disciplines will lead to such an understanding. We place particular hopes on the theory of phase transitions and the mathematical theory of catastrophes.

An optimized stellarator at finite plasma beta is realized by single-stage optimization of simply modifying the coil currents of the Compact Stellarator with Simple Coils (CSSC)[Yu et al., J. Plasma Physics 88,905880306 (2022)]. The CSSC is an optimized stellarator obtained by direct optimization via coil shapes, with its coil topology similar to that of the Columbia Non-neutral Torus (CNT) [Pederson et al., Phys. Rev. Lett. 88, 205002 (2002)]. Due to its vacuum-based optimization, the CSSC exhibits detrimental finite beta effects on neoclassical confinement. The results of optimization show that the finite beta effects can be largely mitigated by reducing the coil currents of CSSC.

Molecular dynamics simulations for tripeptides in the gas phase and in solution using empirical and machine-learned energy functions are presented. For cationic AAA a machine-learned potential energy surface (ML-PES) trained on MP2 reference data yields quantitative agreement with measured splittings of the amide-I vibrations. Experimental spectroscopy in solution reports a splitting of 25 cm-1 which compares with 20 cm-1 from ML/MM-MD simulations of AAA in explicit solvent. For the AMA tripeptide a ML-PES describing both, the zwitterionic and neutral form is trained and used to map out the accessible conformational space. Due to cyclization and H-bonding between the termini in neutral AMA the NH- and OH-stretch spectra are strongly red-shifted below 3000 cm-1. The present work demonstrates that meaningful MD simulations on the nanosecond time scale are feasible and provides insight into experiments.

The relationship between the spatiotemporal distribution of oxygen transport and blood flow dynamics, accounting for the motion and deformation of individual red blood cells (RBCs), is of fundamental importance for understanding microcirculation systems. Three-dimensional (3D) modeling is indispensable for addressing complex oxygen transport and cellular behaviors in capillary networks; however, the computational approach is formidable for enforcing interface (or jump) conditions on largely moving and deforming interfaces. In this paper, we propose a diffuse interface approach for the oxygen transport using a mixture formulation. We formulate oxygen transport using an advection-diffusion-reaction equation and rewrite all governing equations in mixture forms using phase indicator functions, where all the interface conditions are included in the governing equations. This innovation avoids the complexity associated with discontinuities for largely moving interfaces in highly dense RBC conditions. We model cellular flow as a fluid-membrane interaction problem using the immersed boundary method (IBM). The method allows the seamless calculation of coupling problems for cellular flows and oxygen transports in the cytoplasm (internal fluid) of the RBC, plasma (external fluid), and tissue regions using a fixed Cartesian coordinate mesh. The proposed method accurately captures the analytical solution for spherically symmetric diffusion, and successfully demonstrates oxygen transport in both straight capillaries and their networks. These rigorous analyses suggest that RBCs can autonomously regulate the oxygen supply to tissues in response to the local tissue oxygenation level, resulting in the establishment of homogeneous tissue oxygenation.

ABET accreditation is an increasingly prominent system of global accreditation of engineering programs, and the assessment requires programs to demonstrate that they meet the needs of the program's stakeholders, typically industrial potential employers of graduates. To obtain these inputs, programs are required to assemble an advisory committee board. The views of the advisory board on the relevance of the degree outcomes are an essential part of this process. The purpose of this qualitative research study is to explore the viewpoints that industry stakeholders have on this type of process. The context for the study was an Ecuadorian engineering program which had successfully achieved the ABET accreditation. The study drew on interviews undertaken with industry members who were part of the advisory board. This study focuses on how they perceive the process and the accreditation awarded, analyzing their views of its usefulness, especially in relation to the employability of graduates. Based on the findings, we offer critical insights into this accreditation process when it takes place in contexts beyond highly industrialized countries.

The evolution of global income distribution from 1988 to 2018 is analyzed using purchasing power parity exchange rates and well-established statistical distributions. This research proposes the use of two separate distributions to more accurately represent the overall data, rather than relying on a single distribution. The global income distribution was fitted to log-normal and gamma functions, which are standard tools in econophysics. Despite limitations in data completeness during the early years, the available information covered the vast majority of the world's population. Probability density function (PDF) curves enabled the identification of key peaks in the distribution, while complementary cumulative distribution function (CCDF) curves highlighted general trends in inequality. Initially, the global income distribution exhibited a bimodal pattern; however, the growth of middle classes in highly populated countries such as China and India has driven the transition to a unimodal distribution in recent years. While single-function fits with gamma or log-normal distributions provided reasonable accuracy, the bimodal approach constructed as a sum of log-normal distributions yielded near-perfect fits.

Accurate prediction of the radar cross section (RCS) of chaff clouds requires careful consideration of aerodynamic effects, as the orientation and spatial distribution of individual chaff elements evolve significantly after deployment. Building upon conventional six-degree-of-freedom (6-DoF) formulations for chaff aerodynamic analysis-which assumed straight or two-dimensionally bent geometries-we extend the framework to incorporate arbitrarily curved three-dimensional chaff geometries. This extension enables accurate modeling of both flattened and helical dynamics induced by aerodynamic moments acting along the roll, pitch, and yaw directions, thereby providing a more comprehensive and realistic description of chaff motion. We then finally develop a coupled aerodynamic-electromagnetic framework that integrates the extended aerodynamic model with our recently developed fast method-of-moments solver, which is optimized for efficiently estimating the RCS of million-scale chaff clouds. The proposed multiphysics coupled framework allows real-time, first-principles prediction of the monostatic and bistatic RCS of large-scale chaff clouds with arbitrary geometries, orientations, and lengths, accurately incorporating their time-varying aerodynamic evolution. Simulation results confirm that the monostatic RCS is strongly influenced by aerodynamic effects, with the coexistence of flattened and helical motions playing a critical role in determining the overall scattering response. The proposed framework thus provides a physically grounded and computationally efficient approach for predicting the RCS of large-scale chaff clouds. Furthermore, it can be directly extended to radar signal processing applications by utilizing multi-frequency complex-valued far-field responses, thereby enabling the reconstruction of Range-Doppler, Range-Angle, and Doppler-Angle maps.

It is well-established that human activity is driving extreme weather patterns, and that these extreme events influence human behaviour. However, few models allow for human behaviours and the climate to dynamically interact. The models presented in this paper expand on previous work and serve as an initial framework to extend current models by using a dynamic social-climate feedback loop. First, we introduce a social model to determine the conditions under which a committed minority can overturn a pre-established social convention. Second, we modify an existing climate model to include climatic variability. Lastly, we formulate a social-climate feedback model to study the interplay between human behaviour and the climate. Our results demonstrate that the social-climate feedback loop may be important in accurately predicting future temperatures, in contrast to the standard approach where human behaviour is a priori. Additionally, we find that a committed minority plays a vital role in shifting public opinion towards climate action and that the time at which the social convention of climate inaction is overturned has a large impact on future temperatures.

Accurate position reconstruction in noble-element time-projection chambers (TPCs) is critical for rare-event searches in astroparticle physics, yet is systematically limited by electric field distortions arising from charge accumulation on detector surfaces. Conventional data-driven field corrections suffer from three fundamental limitations: discretization artifacts that break smoothness and differentiability, lack of guaranteed consistency with Maxwell's equations, and statistical requirements of $\mathcal{O}(10^7)$ calibration events. We introduce a physics-informed continuous normalizing flow architecture that learns the electric field transformation directly from calibration data while enforcing the constraint of field conservativity through the model structure itself. Applied to simulated $^{83\mathrm{m}}$Kr calibration data in an XLZD-like dual-phase xenon TPC, our method achieves superior reconstruction accuracy compared to histogram-based corrections when trained on identical datasets, demonstrating viable performance with only $6\times10^5$ events$\unicode{x2013}$an order of magnitude reduction in calibration requirements. This approach enables practical monthly field monitoring campaigns, propagation of position uncertainties through differentiable transformations, and enhanced background discrimination in next-generation rare-event searches.

We present force characterizations of two newly developed insect-scale propulsors–one single-tailed and one double-tailed–for microrobotic swimmers that leverage fluid-structure interaction (FSI) to generate thrust. The designs of these two devices were inspired by anguilliform swimming and are driven by soft tails excited by high-work-density (HWD) actuators powered by shape-memory alloy (SMA) wires. While these propulsors have been demonstrated to be suitable for microrobotic aquatic locomotion and controllable with simple architectures for trajectory tracking in the two-dimensional (2D) space, the characteristics and magnitudes of the associated forces have not been studied systematically. In the research presented here, we adopted a theoretical framework based on the notion of reactive forces and obtained experimental data for characterization using a custom-built micro-N-resolution force sensor. We measured maximum and cycle-averaged force values with multi-test means of respectively 0.45 mN and 2.97 micro-N, for the tested single-tail propulsor. For the dual-tail propulsor, we measured maximum and cycle-averaged force values with multi-test means of 0.61 mN and 22.6 micro-N, respectively. These results represent the first measurements of the instantaneous thrust generated by insect-scale propulsors of this type and provide insights into FSI for efficient microrobotic propulsion.

We present a path-integral Monte Carlo estimator for calculating the dipole polarizability of interacting Coulomb plasma in the long-wavelength limit, i.e., the optical region. We present comprehensive details and method validation studies for our approach based on both collective and one-particle dipole autocorrelation functions in the imaginary time. The simulation of thermal equilibrium in imaginary time has exact Coulomb interactions and Boltzmann quantum statistics. For reference, we use analytically continued Drude model as the long-wavelength limit of the Lindhard response. Our collective response shows perfect match to the analytical reference. The one-particle response is used in systematic studies of physical and numerical parameters, and to discuss the phenomenological Drude scattering model.

Illusion effects-where one object appears as another-arise from the non-uniqueness of physical systems, in which different material configurations yield identical external responses. Conventional approaches, such as coordinate transformation, map equivalent configurations but provide only specific solutions, while analytical or numerical optimization methods extend these designs by minimizing scattering yet remain constrained by model assumptions and computational cost. Here, we exploit this non-uniqueness through a data-driven framework that uses a variational autoencoder to compress high-dimensional thermal-field data into a compact latent space capturing geometrical relations between configurations and observations. In this latent space, thermal illusion corresponds to finding configurations that minimize geometric distance to a target configuration, with thermal cloaking as a special case where the target is free space. Specifically, we demonstrate the concept in a cylindrical shell with anisotropic thermal conductivities enclosing a core of arbitrary conductivity, achieving robust thermal illusion and cloaking using only positive conductivities. Such a latent-space distance approach provides a refreshed perspective for achieving illusion and can be applied to inverse-design problems in other classical wave systems.

We study the influence of perturbations in the three dimensional isotropic harmonic oscillator problem considering different perturbing force laws and apply our results in the context of celestial mechanics, particularly in the movement of stars in stellar clusters. We use a method based on the Runge-Lenz tensor, so that our results are valid for any eccentricity of the unperturbed orbits of the oscillator. To establish basic concepts, we start by considering two cases, namely: a Larmor and a keplerian perturbation; and show that, in both cases, the perturbed orbits will precess. After that, we consider the more general problem of a central perturbation with any power-law dependence, that also only causes precession. Then, we consider precessionless perturbations caused by an Euler force and by the non-central dragging forces of the form $\boldsymbol{\delta F}=-\gamma_nv^{n-1}\boldsymbol{v}$, where $\boldsymbol{v}$ is the velocity of the particle and $\gamma_n\geq0$. We demonstrate that, in the case of a linear drag $(n=1)$, the orbits eccentricities remains constant. In contrast to what occurs in the well-known Kepler problem, for $n>1$ the orbit becomes increasingly eccentric. In the case $n=-3$, where the force is interpreted as a Chandrasekhar friction, we show that the eccentricity diminishes over time. We finish this work by making a few comments about the relevance of the main results.

In certain applications, pressure transducers may be exposed to high pressures either deliberately or accidentally, raising concerns about their functionality afterwards. We compared the performance of two MKS Granville-Phillips 390 Micro-Ion Gauges against each other, one that had been exposed to 10,000 Torr and the other had never been exposed to pressures above 1000 Torr. Our results show that the differences in the readings between the gauges were within the range of uncertainty specified by the manufacturer indicating negligible impact due to the exposure to high pressure. Additionally, the high pressure exposure did not compromise the leak integrity of the gauge.

A self-consistent model is presented for the formation and propagation of kinetic Alfvén (KA) solitons in mass-loaded filaments within the pulsar wind, where a magnetized electron–positron–ion plasma flows along open magnetic field lines beyond the light cylinder. Using a reductive perturbation approach, we derive a Korteweg–de Vries (KdV) equation governing the nonlinear evolution of KA solitons in this environment. The soliton amplitude and width depend sensitively on key pulsar observables, including spin period, spin-down rate, and pair multiplicity, as well as on plasma composition and suprathermal particle distributions. Heavy ion species such as Fe$^{26+}$ produce significantly broader solitons through enhanced inertia and dispersion, while increasing pair multiplicity leads to smaller solitons through stronger screening. More oblique propagation (larger $\theta$) yields wider but lower-amplitude solitons, whereas more thermalized pair plasmas (higher $\kappa$) support taller and broader structures. A population-level analysis of 1174 pulsars quantifies the physical scales of these nonlinear structures, showing that millisecond pulsars host the most compact solitons, whereas slower pulsars support broader structures. Within the adopted admissible finite-$\beta$ regime, this work links soliton properties to measurable pulsar parameters and provides a self-consistent framework for characterizing localized nonlinear plasma structures in finite-magnetization regions of pulsar winds and for assessing their role in modulating the local plasma environment.

Tritium plays a critical role in nuclear fusion power plant designs and dryer beds are an essential tool for managing tritiated water vapor. A series of tests were performed to investigate the ability of a saturated dryer to preferentially adsorb heavy water vapor. The design of passive tritiated control systems is feasible by utilizing a dryer's ability to preferentially trap heavier isotopologues of water. This work investigates this displacement phenomenon and the effect of the heavy water humidity on the dryers performance. Significant displacement was observed when a humid stream of heavy water was diverted through a dryer pre-saturated with light water, as indicated by changes in the partial pressures of $D_2O$ and $H_2O$. After the capture of heavy water in the bed, the subsequent rise in $D_2O$ partial pressure depended on the humidity of heavy water in the gas stream. Higher humidity values lead to faster and steeper mass transfer profiles in the dryer, which could be empirically fit with sigmoid curves.

Purpose: To develop a virtual reality simulator for high dose rate prostate brachytherapy and to test whether participation is associated with immediate gains in self-reported confidence across predefined procedural domains in two cohorts. Methods: Two modules were developed and implemented using Unreal Engine: patient preparation and template guided needle insertion. Oncology staff and trainees completed pre and post surveys that assessed confidence for recalling steps, explaining steps, identifying equipment, and explaining equipment function. Studies were conducted at the Hands On Brachytherapy Workshop (HOWBT) in London, Ontario, and at Sunnybrook Odette Cancer Centre in Toronto, Ontario. Paired Wilcoxon signed rank tests with two-sided p values compared before and after scores within each module. Results: Patient preparation (N=11) confidence increased for recalling steps (W=65, p=0.002), explaining steps (W=51, p = 0.023), identifying equipment (W=65, p=0.002), and explaining equipment function (W=60, p=0.0078). Needle insertion (N=27) confidence increased for recalling steps (W=292, p<0.001), explaining steps (W=347, p<0.001), identifying equipment (W=355, p<0.001), and explaining equipment function (W=354, p<0.001). Conclusion: The simulator was feasible to deploy and was associated with higher self-reported confidence across key domains immediately after training. Findings may inform future curriculum design and implementation work.

In this study, the capabilities of the Physics-Informed Neural Network (PINN) method are investigated for three major tasks: modeling, simulation, and optimization in the context of the heat conduction problem. In the modeling phase, the governing equation of heat transfer by conduction is reconstructed through equation discovery using fractional-order derivatives, enabling the identification of the fractional derivative order that best describes the physical behavior. In the simulation phase, the thermal conductivity is treated as a physical parameter, and a parametric simulation is performed to analyze its influence on the temperature field. In the optimization phase, the focus is placed on the inverse problem, where the goal is to infer unknown physical properties from observed data. The effectiveness of the PINN approach is evaluated across these three fundamental engineering problem types and compared against conventional numerical methods. The results demonstrate that although PINNs may not yet outperform traditional numerical solvers in terms of speed and accuracy for forward problems, they offer a powerful and flexible framework for parametric simulation, optimization, and equation discovery, making them highly valuable for inverse and data-driven modeling applications.

Arrays of semiconductor quantum dots provide a powerful platform to design correlated quantum matter from the bottom up. We establish a predictive framework for engineering local electron pairing in these artificial molecules by systematically deploying three control levers: lattice geometry, orbital hybridization, and external electric fields. Using Hartree-Fock simulations on canonical 3D clusters from the tetrahedron (Z = 3) to the FCC lattice (Z = 12), at and near half-filling, we uncover three fundamental design principles. (i) Geometric Hierarchy: The resilience to Coulomb repulsion U is dictated by the coordination number Z, which controls kinetic delocalization. (ii) Orbital Hybridization: Counter-intuitively, inter-orbital hopping t_orb acts not as a simple suppressor of pairing, but as a sophisticated control knob that enhances double occupancy at moderate U by engineering the on-site energy landscape. (iii) Field Squeezing: An electric field robustly induces pairing by forcing charge localization, an effect most potent in low-connectivity clusters. These principles form a blueprint for deterministically targeting charge and spin correlations in quantum-dot-based quantum hardware.

The main ideas behind a research plan to use the Wigner formulation as a bridge between classical and quantum probabilistic algorithms are presented, focusing on a particular case: the Quantum analog of Stochastic Gradient Descent in its continuous-time limit based on the Wigner formulation of Open Quantum Systems.

This study proposes a quantitative framework to enhance curriculum coherence through the systematic alignment of Course Learning Outcomes (CLOs) and Program Learning Outcomes (PLOs), contributing to continuous improvement in outcome-based education. Grounded in accreditation standards such as ABET and NCAAA, the model introduces mathematical tools that map exercises, assessment questions, teaching units (TUs), and student assessment components (SACs) to CLOs and PLOs. This dual-layer approach-combining micro-level analysis of assessment elements with macro-level curriculum evaluation-enables detailed tracking of learning outcomes and helps identify misalignments between instructional delivery, assessment strategies, and program objectives. The framework incorporates alignment matrices, weighted relationships, and practical indicators to quantify coherence and evaluate course or program performance. Application of this model reveals gaps in outcome coverage and underscores the importance of realignment, especially when specific PLOs are underrepresented or CLOs are not adequately supported by assessments. The proposed model is practical, adaptable, and scalable, making it suitable for academic programs. Its systematic structure supports institutions in implementing evidence-based curriculum improvements and provides a reliable mechanism for aligning teaching practices with desired learning outcomes. Ultimately, this framework offers a valuable tool for closing the feedback loop between instructional design, assessment execution, and learning outcomes, thus promoting greater transparency, accountability, and educational effectiveness. Institutions that adopt this model can expect to strengthen their quality assurance processes and help ensure that students graduate with the competencies required by academic standards and professional expectations.

Parametric excitation in coupled mechanical systems has enabled advances in sensing, computation, and phonon control. The function of distinct phase modes using parametric driving remains insufficiently explored. Here, we investigate the nonlinear and parametric response of degenerate phase modes in a Double Ended Tuning Fork (DETF) resonator. Our measurements reveal pronounced nonlinearity and parametric amplification in the out-phase mode, attributed to the dominant contribution of the coupling beam, while the in-phase mode remains predominantly linear. Uniquely, we demonstrate parametric excitation through the coupling spring, enabling selective amplification and de-amplification controlled via the relative phase between harmonic and parametric drives. A parametric gain of $\sim$13 dB is achieved in the out-phase mode, with phase-dependent modulation of amplification, indicating its suitability for signal processing, logic operations, and memory elements based on degenerate modes. These results establish a new approach to exploiting mode-specific nonlinear dynamics in coupled resonators for emerging applications in sensing and phononic control.

We present an enhanced immersed interface method for simulating incompressible fluid flows in thin gaps between closely spaced immersed boundaries. This regime, common in engineered structures such as including tribological interfaces and bearing assemblies, poses significant computational challenges because of limitations in grid resolution and the prohibitive cost of mesh refinement near contact. The immersed interface method imposes jump conditions that capture stress discontinuities generated by forces that are concentrated along immersed boundaries. Our approach introduces a bilinear velocity interpolation operator that incorporates jump conditions from multiple nearby interfaces when they occupy the same interpolation stencil. Numerical results demonstrate substantial improvements in both interface and Eulerian velocity accuracy compared to lubrication-based immersed boundary and immersed interface methods. The proposed method improves upon previous interpolation schemes, and eliminates the need for prior knowledge of interface orientation or geometry. This makes it broadly applicable to a wide range of fluid–structure interaction problems involving near-contact dynamics.

We employ real-space, real-time time-dependent density functional theory (TDDFT) combined with Ehrenfest dynamics to investigate ultrafast intermolecular relaxation following inner-valence ionization in hydrated pyrrole. This time-dependent approach treats electronic and nuclear motions simultaneously, allowing the description of electronic excitation, charge transfer, ionization, and nuclear motion.When the initial vacancy in the O 2s 1 state is created on the water molecule, the system predominantly undergoes intermolecular Coulombic decay (ICD) and electron-transfer mediated decay (ETMD), accompanied by pronounced charge transfer between pyrrole and water. In contrast, ionization of the pyrrole site for N 2s electron leads to both ICD and Auger decay channels. These results demonstrate that the decay dynamics are strongly governed by the initial vacancy location, offering microscopic insight into intermolecular energy-transfer mechanisms in hydrated molecular systems.

We present the implementation of an anisotropic viscosity solver within the magnetohydrodynamics (MHD) framework of the TreeSPH code OpenGadget3. The solver models anisotropic viscous transport along magnetic field lines following the Braginskii formulation and includes physically motivated limiters based on the mirror and firehose instability thresholds, which constrain the viscous stress in weakly collisional plasmas. To validate the implementation, we performed a suite of standard test problems – including two variants of the sound wave test, circularly and linearly polarized Alfven waves, fast magnetosonic wave, and the Kelvin-Helmholtz instability – both with and without the plasma-instability limiters. The results show excellent agreement with the AREPO implementation of a similar anisotropic viscosity model, confirming the accuracy and robustness of our method. Our formulation integrates seamlessly within the individual adaptive timestepping framework of OpenGadget3, avoiding the need for subcycling. This provides efficient and stable time integration while maintaining physical consistency. Finally, we applied the new solver to a cosmological zoom-in simulation of a galaxy cluster as a proof-of-concept application, demonstrating its capability to model anisotropic transport and plasma microphysics in realistic large-scale environments. Our implementation offers a versatile and computationally efficient tool for studying anisotropic viscosity in magnetized astrophysical systems.

Solving inverse and optimization problems over solutions of nonlinear partial differential equations (PDEs) on complex spatial domains is a long-standing challenge. Here we introduce a method that parameterizes the solution using spectral bases on arbitrary spatiotemporal domains, whereby the basis is defined on a hyperrectangle containing the true domain. We find the coefficients of the basis expansion by solving an optimization problem whereby both the equations, the boundary conditions and any optimization targets are enforced by a loss function, building on a key idea from Physics-Informed Neural Networks (PINNs). Since the representation of the function natively has exponential convergence, so does the solution of the optimization problem, as long as it can be solved efficiently. We find empirically that the optimization protocols developed for machine learning find solutions with exponential convergence on a wide range of equations. The method naturally allows for the incorporation of data assimilation by including additional terms in the loss function, and for the efficient solution of optimization problems over the PDE solutions.