arXiv subjects

Erik Jansson

Publications and source records attributed to Erik Jansson.

17 recordsLinked to original sources

arXiv2026

Learning piecewise-smooth dynamical systems

Discovering dynamical systems from trajectory data is a central problem in applied mathematics and engineering. Whilst recent advances in machine learning have led to strong progress in data-driven system identification, much less attention has been given to systems with discontinuous dynamics. These systems are nevertheless highly relevant in applications, including climate dynamics and mechanical systems with friction. In this work, we consider the problem of identifying piecewise-smooth dynamical systems directly from trajectory data. Compared with the smooth setting, this requires recovering the governing equations and detecting the switching hyperplanes that separate different dynamical regimes and characterising their behaviour, such as sliding motion. We present a modular framework for discovering such systems by first estimating switching hyperplanes from data and then learning smooth dynamics within each region using geometry-constrained neural networks. The geometry-learning phase is studied from a statistical perspective, analysing the identifiability of the discontinuities and the robustness of the procedure. We also introduce a novel neural network architecture with a prescribed discontinuity set, and provide a theoretical analysis of its approximation properties. The approach is tested on low-dimensional benchmark problems, including dry-friction oscillators and the PP04 climate model for the ice ages.

math.DS↗

arXiv2026

Recovering protein conformations from single-particle cryo-EM data via indirect shape matching gradient flows

Single-particle cryo-electron microscopy images a macromolecule as many noisy tomographic projections of its electrostatic potential. We reconstruct the protein backbone directly from such projections, as an atomic point cloud, without the intermediate step of reconstructing the 3D electrostatic potential map. We formulate this as an indirect shape matching problem: a point-cloud template of the backbone is deformed until its simulated projections agree with the data, with the structure observed only through the imaging operator. The deformation is computed via a gradient flow on a Lie group, and we derive the resulting framework in a general geometric setting before adapting it for single-particle cryo-electron microscopy. On synthetic data, we recover single- and multichain proteins and capture conformational transitions.

q-bio.BM↗

arXiv2026

Research Assistant: AstraZeneca's Agentic System for R&D

We describe Research Assistant, an internal LLM-based system developed at AstraZeneca to help scientists and clinicians explore biomedical questions across a broad range of data sources. The system provides a chat-style interface that brings together evidence from scientific literature, knowledge graphs, chemistry, clinical trials, safety resources, expression data, and internal experimental systems. It supports both a fast mode for direct question answering and a multi-step mode for more complex research tasks. Responses are grounded in retrieved evidence and linked back to the original sources, allowing users to review and further explore the underlying data. In this technical note, we outline the system architecture, the main design choices behind the product, and lessons learned from deploying it at scale to support day-to-day R&D workflows across AstraZeneca.

cs.AI↗

arXiv2026

Minimum-enstrophy solutions in topographic quasi-geostrophic flow on the rotating sphere

The minimum-enstrophy theory of Bretherton and Haidvogel postulates that two-dimensional turbulent systems evolve to a state that minimises enstrophy at a fixed energy level. We extend this to the rotating spherical quasi-geostrophic setting, accounting for bottom topography and the fully nonlinear Coriolis effect, resulting in latitude-dependent effects not present in planar approximations. We prove existence and nonlinear stability of minimum-enstrophy solutions and describe analytically asymptotic regimes for certain rates of rotation, topography scales, and energy values. We compute the minimum-enstrophy solutions by a structure-preserving method for the quasi-geostrophic equations on the sphere. We apply the method to a range of parameter values, including those describing Jupiter's atmosphere. The results reveal a distinct latitude dependence of the flow, with a tendency for topographical trapping near the poles and zonal flow near the equator, depending on the chosen parameters. The predicted nonlinear stability is confirmed numerically by integrating perturbed solutions using a structure-preserving time discretisation.

physics.flu-dyn↗

arXiv2025

An exponential map free implicit midpoint method for stochastic Lie-Poisson systems

An integrator for a class of stochastic Lie-Poisson systems driven by Stratonovich noise is developed. The integrator is suited for Lie-Poisson systems that also admit an isospectral formulation, which enables scalability to high-dimensional systems. Its derivation follows from discrete Lie-Poisson reduction of the symplectic midpoint scheme for stochastic Hamiltonian systems. We prove almost sure preservation of Casimir functions and coadjoint orbits under the numerical flow and provide strong and weak convergence rates of the proposed method. The scalability, structure-conservation, and convergence rates are illustrated numerically for the (generalized) rigid body, point vortex dynamics, and the two-dimensional Euler equations on the sphere.

math.NA↗

arXiv2025

Rebalancing Markov jump processes for non-reversible continuous-time sampling

Markov chain Monte Carlo methods are central in computational statistics, and typically rely on detailed balance to ensure invariance with respect to a target distribution. Although straightforward to construct by Metropolization, this can induce diffusion-like exploration of the sample space, requiring careful tuning of parameters such as step size. We introduce a general mechanism for constructing non-reversible continuous-time samplers, without requiring detailed balance. Our approach transforms jump processes satisfying a skew-detailed balance condition for a reference measure into processes sampling a target measure absolutely continuous with respect to it. Unbounded balancing functions allow such samplers to dynamically select favourable transitions. We establish invariance under weak criteria and demonstrate how to verify geometric ergodicity. Numerical experiments demonstrate that the resulting samplers are more robust to parameter tuning.

math.ST↗

arXiv2025

Diffusive behavior of transport noise on $\mathbb{S}^2$

We investigate theoretically and numerically transport noise-induced diffusion in flows on the sphere. Previous analysis on the torus demonstrated that suitably chosen transport noise in the Euler equations leads to diffusive behavior resembling the Navier--Stokes equations. Here, we analyze dynamics on the sphere with noise-induced differential elliptic operator dissipation and characterize their energy and enstrophy decay properties. Through structure-preserving numerical simulations with the Zeitlin discretization, we demonstrate that appropriately scaled transport noise induces energy dissipation while preserving enstrophy and coadjoint orbits. The presented analysis lays a groundwork for further theoretical investigation of transport noise and supports the calibration of transport noise models as a parametrization for unresolved processes in geophysical fluid simulations.

math.NA↗

arXiv2025

Scalable chip-based 3D ion traps

Ion traps are used for a wide range of applications from metrology to quantum simulations and quantum information processing. Microfabricated chip-based 3D ion traps are scalable to store many ions for the realization of a large number of qubits, provide deep trapping potentials compared to surface traps, and very good shielding from external electric fields. In this work, we give an overview of our recent developments on chip-based 3D ion traps. Different types of chip materials, the integration of electronic filter components on-chip and compact electrical connections in vacuum are discussed. Further, based on finite element method (FEM) simulations, we discuss how integrating micro-optics in 3D ion traps is possible without disturbing the trapped ions.

quant-ph↗

arXiv2025

On spectral scaling laws for averaged turbulence on the sphere

Spectral analysis for a class of Lagrangian-averaged Navier--Stokes (LANS) equations on the sphere is carried out. The equations arise from the Navier--Stokes equations by applying a Helmholtz filter of width $α$ to the advecting velocity $β$ times. Power laws for the energy spectrum are derived and indicate a $β$-dependent scaling at wave numbers $l$ with $αl\gg 1$. The energy and enstrophy transfer rates distinctly depend on the averaging, allowing control over the energy flux and the enstrophy flux separately through the choice of averaging operator. A necessary condition on the averaging operator is derived for the existence of the inverse cascade in two-dimensional turbulence. Numerical experiments with a structure-preserving integrator confirm the expected energy spectrum scalings and the robustness of the double cascade under choices of the averaging operator.

physics.flu-dyn↗

arXiv2024

On the numerical signature of blow-up in hydrodynamic equations

The phenomenon of finite time blow-up in hydrodynamic partial differential equations is central in analysis and mathematical physics. While numerical studies have guided theoretical breakthroughs, it is challenging to determine if the observed computational results are genuine or mere numerical artifacts. Here we identify numerical signatures of blow-up. Our study is based on the complexified Euler equations in two dimensions, where instant blow-up is expected. Via a geometrically consistent spatiotemporal discretization, we perform several numerical experiments and verify their computational stability. We then identify a signature of blow-up based on the growth rates of the supremum norm of the vorticity with increasing spatial resolution. The study aims to be a guide for cross-checking the validity for future numerical experiments of suspected blow-up in equations where the analysis is not yet resolved.

math.NA↗

arXiv2024

Indium tin oxide combined with anti-reflective coatings with high transmittance for wavelengths < 400 nm

The transparent and conductive properties of indium tin oxide (ITO) thin films, make them an attractive coating for optically integrated ion traps. However, the relatively low transmittance for wavelengths $<$ 400 nm, high scattering and high production temperature limits the usability in trapped-ion-based quantum technologies. Here we present ITO coatings and a combined ITO + anti-reflective (AR) coating system optimized for an ion trap applied using ion beam sputtering (IBS). The coatings feature a high transmittance for wavelengths $<$ 400 nm and additional wavelengths up to 1000 nm, low scattering and low production temperature $<$ 150 $^{\circ}$C. The transmission, reflection and absorption spectra are simulated and the resistance, transmittance and scattering at 370 nm are measured for different ITO coating thicknesses and the ITO + AR coating system. For the ITO + AR coating system a resistance of 115 $\pm$ 5 $Ω/\Box$, transmittance of 80$\%$ and scattering of 0.012 $\pm$ 0.002$\%$ at 370 nm is achieved.

physics.optics↗

arXiv2024

Geometric shape matching for recovering protein conformations from single-particle Cryo-EM data

We address recovery of the three-dimensional backbone structure of single polypeptide proteins from single-particle cryo-electron microscopy (Cryo-SPA) data. Cryo-SPA produces noisy tomographic projections of electrostatic potentials of macromolecules. From these projections, we use methods from shape analysis to recover the three-dimensional backbone structure. Thus, we view the reconstruction problem as an indirect matching problem, where a point cloud representation of the protein backbone is deformed to match 2D tomography data. The deformations are obtained via the action of a matrix Lie group. By selecting a deformation energy, the optimality conditions are obtained, which lead to computational algorithms for optimal deformations. We showcase our approach on synthetic data, for which we recover the three-dimensional structure of the backbone.

q-bio.BM↗

arXiv2024

Non-stationary Gaussian random fields on hypersurfaces: Sampling and strong error analysis

A flexible model for non-stationary Gaussian random fields on hypersurfaces is introduced. The class of random fields on curves and surfaces is characterized by an amplitude spectral density of a second order elliptic differential operator. Sampling is done by a Galerkin--Chebyshev approximation based on the surface finite element method and Chebyshev polynomials. Strong error bounds are shown with convergence rates depending on the smoothness of the approximated random field. Numerical experiments that confirm the convergence rates are presented.

math.NA↗

arXiv2024

Sub-Riemannian Landmark Matching and its interpretation as residual neural networks

The problem of finding a time-dependent vector field which warps an initial set of points to a target set is common in shape analysis. It is an example of a problem in the diffeomorphic shape matching regime, and can be thought of as a spatial discretization of diffeomorphic image matching. In this paper, we consider landmark matching modified by restricting the set of available vector fields in the sense that vector fields are parametrized by a set of controls. We determine the geometric setting of the problem, referred to as sub-Riemannian landmark matching, and derive the equations of motion for the controls. We provide two computational algorithms and demonstrate them in numerical examples. In particular, the experiments highlight the importance of the regularization term. A strong motivation is that sub-Riemannian landmark matching have connections with neural networks, in particular the interpretation of residual neural networks as time discretizations of continuous control problems. It allows shape analysis practitioners to think about neural networks in terms of diffeomorphic landmark matching, thereby providing a bridge between the two fields.

math.OC↗

arXiv2023

Convergence of the vertical Gradient flow for the Gaussian Monge problem

We investigate a matrix dynamical system related to optimal mass transport in the linear category, namely, the problem of finding an optimal invertible matrix by which two covariance matrices are congruent. We first review the differential geometric structure of the problem in terms of a principal fiber bundle. The dynamical system is a gradient flow restricted to the fibers of the bundle. We prove global existence of solutions to the flow, with convergence to the polar decomposition of the matrix given as initial data. The convergence is illustrated in a numerical example.

math.OC↗

arXiv2021

Surface finite element approximation of spherical Whittle--Matérn Gaussian random fields

Spherical Whittle--Matérn Gaussian random fields are considered as solutions to fractional elliptic stochastic partial differential equations on the sphere. Approximation is done with surface finite elements. While the non-fractional part of the operator is solved by a recursive scheme, a quadrature of the Dunford--Taylor integral representation is employed for the fractional part. Strong error analysis is performed, and the computational complexity is bounded in terms of the accuracy. Numerical experiments for different choices of parameters confirm the theoretical findings.

math.NA↗

arXiv2020

Observation of effects due to an atom's electric quadrupole polarizability

The response of matter to fields underlies the physical sciences, from particle physics to astrophysics, and from chemistry to biophysics. We observe an atom's response to an electric quadrupole field to second- and higher orders; this arises from the atom's electric quadrupole polarizability and hyperpolarizabilities. We probe a single atomic ion which is excited to Rydberg states and confined in the electric fields of a Paul trap. The quadrupolar trapping fields cause atomic energy level shifts and give rise to spectral sidebands. The observed effects are described well by theory calculations.

physics.atom-ph↗