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World models have emerged as a unifying paradigm for learning latent dynamics, simulating counterfactual futures, and supporting planning under uncertainty. In this paper, we argue that computational epidemiology is a natural and underdeveloped setting for world models. This is because epidemic decision-making requires reasoning about latent disease burden, imperfect and policy-dependent surveillance signals, and intervention effects are mediated by adaptive human behavior. We introduce a conceptual framework for epidemiological world models, formulating epidemics as controlled, partially observed dynamical systems in which (i) the true epidemic state is latent, (ii) observations are noisy and endogenous to policy, and (iii) interventions act as sequential actions whose effects propagate through behavioral and social feedback. We present three case studies that illustrate why explicit world modeling is necessary for policy-relevant reasoning: strategic misreporting in behavioral surveillance, systematic delays in time-lagged signals such as hospitalizations and deaths, and counterfactual intervention analysis where identical histories diverge under alternative action sequences. 

Abstract With the advent of Ulysses measurements during the solar minima of Solar Cycles 23 and 24, the heliospheric magnetic field and the solar wind were observed to behave much differently than expected. In particular, previous studies showed that the magnetic open flux of the Sun, calculated as the product of the radial component of the Sun’s magnetic field and the squared radial distance from the Sun, was observed to have decreased along with observed changes in solar-wind streams, such as solar wind proton density. This was in contrast to the standing theory, prior to the measurements made by Ulysses, that the “baseline” of the magnetic open flux should remain constant across the minima. Studies conducted after these measurements accounted for the discrepancies by showing that the Total Open Magnetic Flux (TOMF), the total amount of open flux outside the streamer belt, is a conserved “baseline” quantity from solar minimum to minimum. In this work, we examine a range of solar-wind parameters across five solar minima in Cycles 21, 22, 23, 24, and 25. Using measurements of the heliospheric magnetic field, dynamic solar wind, and heavy ion composition from multiple spacecraft, we investigate the width of the Heliospheric Current Sheet (HCS) streamer belt in the recent Solar Cycle 25 solar minimum using Advanced Composition Explorer (ACE) Solar Wind Ion Composition Spectrometer (SWICS) (1.1 and 2.0) and Solar Wind Electron, Proton and Alpha Monitor (SWEPAM) data. We also investigate the width of the HCS-streamer belt for the Solar Cycle 22 minimum using a newly proposed entropy methodology. With this analysis, we show continued validation of the conservation theory for the TOMF at solar minimum for Solar Cycles 22 and 25. 

Abstract Applying full-waveform methods to image small-scale structures of geophysical interest buried within the Earth requires the computation of the seismic wavefield over large distances compared to the target wavelengths. This represents a considerable computational cost when using state-of-the-art numerical integration of the equations of motion in three-dimensional earth models. “Box Tomography” is a hybrid method that breaks up the wavefield computation into three parts, only one of which needs to be iterated for each model update, significantly saving computational time. To deploy this method in remote regions containing a fluid-solid boundary, one needs to construct artificial sources that confine the seismic wavefield within a small region that straddles this boundary. The difficulty arises from the need to combine the solid-fluid coupling with a hybrid numerical simulation in this region. Here, we report a reconciliation of different displacement potential expressions used for solving the acoustic wave equation and propose a unified framework for hybrid simulations. This represents a significant step towards applying ’Box Tomography’ in arbitrary regions inside the Earth, achieving a thousand-fold computational cost reduction compared to standard approaches without compromising accuracy. We also present examples of benchmarks of the hybrid simulations in the case of target regions at the ocean floor and the core-mantle boundary.