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Artificial intelligence (AI) is poised to transform healthcare by enabling personalized and efficient care through data-driven insights. Although radiology is at the forefront of AI adoption, in practice, the potential of AI models is often overshadowed by severe failures to generalize: AI models can have performance degradation of up to 20% when transitioning from controlled test environments to clinical use by radiologists. This mismatch raises concerns that radiologists will be misled by incorrect AI predictions in practice and/or grow to distrust AI, rendering these promising technologies practically ineffectual. Exhaustive clinical trials of AI models on abundant and diverse data is thus critical to anticipate AI model degradation when encountering varied data samples. Achieving these goals, however, is challenging due to the high costs of collecting diverse data samples and corresponding annotations. To overcome these limitations, we introduce a novel conditional generative AI model designed for virtual clinical trials (VCTs) of radiology AI, capable of realistically synthesizing full-body CT images of patients with specified attributes. By learning the joint distribution of images and anatomical structures, our model enables precise replication of real-world patient populations with unprecedented detail at this scale. We demonstrate meaningful evaluation of radiology AI models through VCTs powered by our synthetic CT study populations, revealing model degradation and facilitating algorithmic auditing for bias-inducing data attributes. Our generative AI approach to VCTs is a promising avenue towards a scalable solution to assess model robustness, mitigate biases, and safeguard patient care by enabling simpler testing and evaluation of AI models in any desired range of diverse patient populations., Comment: 35 pages

After a Preface written by the Editors, there follow twelve papers submitted by theoretical physicists from Asia, Europe and the USA., Comment: 182 pages. Published by MDPI as a Special Issue (2024). arXiv admin note: substantial text overlap with arXiv:2502.04704, 2409.13776, 2404.05821, 2404.16933, 2402.17859, 2409.18440, 2410.00926, 2410.00926, 2402.04170, 2502.04704, 2404.08999, 2009.04443, 2304.10370

We explore the influence of framing on decision-making, where some products are framed (e.g., displayed, recommended, endorsed, or labeled). We introduce a novel choice function that captures observed variations in framed alternatives. Building on this, we conduct a comprehensive revealed preference analysis, employing the concept of frame-dependent utility using both deterministic and probabilistic data. We demonstrate that simple and intuitive behavioral principles characterize our frame-dependent random utility model (FRUM), which offers testable conditions even with limited data. Finally, we introduce a parametric model to increase the tractability of FRUM. We also discuss how to recover the choice types in our framework.

Cathodoluminescence, i.e. the radiation caused by the interaction of high-energy electron beams with matter, has gained a major interest in the analysis of minerals, semiconductors, and plasmonic resonances in nanoparticles. This radiation can either be coherent or incoherent, depending on the underlying interaction mechanism of electrons with nanostructured matter. Thanks to their high spatial resolution and large spectral excitation bandwidth, the evanescent near-field of a moving electron in a scanning electron microscope is used to probe locally photonic modes at the nanoscale, e.g., exciton or plasmon polaritons. The properties of these excitations can be analyzed through both spectral and temporal statistics of the emitted light. Here, we report on the technical design and implementation of a novel fiber-based cathodoluminescence detector for a scanning electron microscope. Moreover, we present first characterization measurements to prove the ability for raster scanning the cathodoluminescence emission using optical fibers with 3D printed micro-optics. The functionality and flexibility of this fiber-based detector is highlighted by resolving the spatial far-field distribution of the excited light, as well as cathodoluminescence spectroscopy and time-correlated single photon counting. Our findings pave the way for a better understanding of the characteristic of the light emitted from electron beams interacting with nanostructures and two-dimensional materials.

The James Webb Space Telescope, launched in 2021, is an infrared observatory of novel design: deployable, with active optics, fully open to space for radiative cooling and orbiting the Lagrange point no. 2. This article explains the rationale leading to this specific design and describes the various other architectures that were considered along the way: from a monolithic 10-meter telescope in geosynchronous orbit to a 6-meter one in High Earth Orbit, then a 16-meter observatory on the Moon, a 4- or 6-meter one in an elliptical heliocentric orbit, and a segmented 8-meter one passively cooled to 50 K at L2, which was finally descoped to 6.6 meters. It also addresses the optimization for scientific performance, the challenge of dealing with such an ultra-low operating temperature, cost issues, supporting technology, modifications made during final design and, finally, how the architecture performs on orbit., Comment: 36 pages, 37 figures, submitted to Journal of Astronomical Telescopes, Instruments and Systems (JATIS)

Elucidating the factors limiting quantum coherence in real materials is essential to the development of quantum technologies. Here we report a strategic approach to determine the effect of lattice dynamics on spin coherence lifetimes using oxygen deficient double perovskites as host materials. In addition to obtaining millisecond $T_1$ spin-lattice lifetimes at T ~ 10 K, measurable quantum superpositions were observed up to room temperature. We determine that $T_2$ enhancement in $Sr_2CaWO_{6-\delta}$ over previously studied $Ba_2CaWO_{6-\delta}$ is caused by a dynamically-driven increase in effective site symmetry around the dominant paramagnetic site, assigned as $W^{5+}$ via electron paramagnetic resonance spectroscopy. Further, a combination of experimental and computational techniques enabled quantification of the relative strength of spin-phonon coupling of each phonon mode. This analysis demonstrates the effect of thermodynamics and site symmetry on the spin lifetimes of $W^{5+}$ paramagnetic defects, an important step in the process of reducing decoherence to produce longer-lived qubits., Comment: 25 pages, 7 figures submitted to npj Quantum Materials (revised version). Please contact corresponding author for supplementary information, data, or code requests

Many supervised machine learning methods have revolutionised the empirical modelling of complex systems. These empirical models, however, are usually "black boxes" and provide only limited physical explanations about the underlying systems. Instead, so-called "knowledge discovery" methods can be used to explore the governing equations that describe observed phenomena. This paper focuses on how we can use such methods to explore underlying physics and also model a commonly observed yet not fully understood phenomenon - the breaking of ocean waves. In our work, we use symbolic regression to explore the equation that describes wave-breaking evolution from a dataset of in silico waves generated using expensive numerical methods. Our work discovers a new boundary equation that provides a reduced-order description of how the surface elevation (i.e., the water-air interface) evolves forward in time, including the instances when the wave breaks - a problem that has defied traditional approaches. Compared to the existing empirical models, the unique equation-based nature of our model allows further mathematical interpretation, which provides an opportunity to explore the fundamentals of breaking waves. Further expert-AI collaborative research reveals the physical meaning of each term of the discovered equation, which suggests a new characteristic of breaking waves in deep water - a decoupling between the water-air interface and the fluid velocities. This novel reduced-order model also hints at computationally efficient ways to simulate breaking waves for engineering applications., Comment: \keywords{Symbolic Regression, Wave Breaking, Knowledge Discovery, Symbolic Classification}

The quasiharmonic approximation is the most common method for modeling the specific heat of solids; however, it fails to capture the effects of intrinsic anharmonicity in phonons. In this study, we introduce the "elastic softening approximation," an alternative approach to modelling intrinsic anharmonic effects on thermodynamic quantities which is grounded in Wallace's thermodynamic framework (Thermodynamics of Crystals, 1972) and focused on tracking entropy changes due to the continuous softening of phonons as a function of temperature. A key finding of our study is a direct correlation between Poisson's ratio and the differential rate of phonon softening at finite frequencies, compared to lower frequencies relevant to elastic moduli measurements. We observe that elemental solids such as alpha-Be, diamond, Al, Cu, In, W, Au, and Pb, which span a wide range of Poisson's ratios and exhibit varying degrees of intrinsic anharmonicity, consistently follow this trend. When applied to alpha-U, alpha-Pu, and delta-Pu, our method reveals unusually large anharmonic phonon contributions at elevated temperatures across all three light actinide metals. These findings are attributed to the unique combination of enhanced covalency and softer elastic moduli inherent in the actinides, potentially influenced by their 5f-electron bonding., Comment: 18 pages with 13 figures

We use helicity-resolved ultrafast transient absorption spectroscopy to study spin-valley polarization dynamics in a vertically stacked MoSe$_{2}$/WSe$_{2}$ heterostructure. The experimental findings reveal details of interlayer charge transfer on ultrafast timescales, showing that the spin-valley polarized state of photoexcited carriers is conserved during the charge transfer and formation of interlayer excitons. Our results confirm that phonon scattering mediates the interlayer charge transfer process, while a high phonon population at elevated temperatures causes a significant decrease in spin-valley selective charge transfer. Moreover, the experimental findings demonstrate the possibility that interlayer excitons and their spin-valley polarization can be probed in the optical response of intralayer excitons. These findings pave the way for ultrafast detection, control, and manipulation of spin-valley polarized excitons in transition metal dichalcogenide-based 2D heterostructures.

We discuss extension of the electroweak gauge group to $SU(3)_L \times SU(3)_R \times U(1)_{XL} \times U(1)_{XR}$. This adds new leptons to the familiar 331-model. The explanation for three light quark-lepton families remains but new particles are introduced which have no TeV scale upper limit on their masses., Comment: 7 pages LaTeX. Improved wording of Abstract. Added Acknowledgements. Added references

This paper investigates properties of concatenated polar codes and their potential applications. We start with reviewing previous work on stopping set analysis for conventional polar codes, which we extend in this paper to concatenated architectures. Specifically, we present a stopping set analysis for the factor graph of concatenated polar codes, deriving an upper bound on the size of the minimum stopping set. To achieve this bound, we propose new bounds on the size of the minimum stopping set for conventional polar code factor graphs. The tightness of these proposed bounds is investigated empirically and analytically. We show that, in some special cases, the exact value of the minimum stopping set can be determined with a time complexity of $O(N)$, where $N$ is the codeword length. The stopping set analysis motivates a novel construction method for concatenated polar codes. This method is used to design outer polar codes for two previously proposed concatenated polar code architectures: augmented polar codes and local-global polar codes. Simulation results demonstrate the advantage of the proposed codes over previously proposed constructions based on density evolution (DE)., Comment: Submitted to IEEE Transactions on Communications. arXiv admin note: substantial text overlap with arXiv:2402.04486

We discuss a cosmological model first proposed in 2022 in which the accelerated rate of expansion is attributed to repulsive electromagnetic forces between like-sign charged PEMNSs (= Primordial Extremely Massive Naked Singularities)., Comment: 17 pages LaTeX. Talk on July 9th 2024 at the 17th Marcel Grossmann Meeting in Pescara, Italy. To appear in the Proceedings. arXiv admin note: substantial text overlap with arXiv:2404.08999

Spatialized vibrotactile feedback systems deliver tactile information by placing multiple vibrotactile actuators on the body. As increasing numbers of actuators are required to adequately convey information in complicated applications, haptic designers find it difficult to create such systems due to limited scalability of existing toolkits. We propose VibraForge, an open-source vibrotactile toolkit that supports up to 128 vibrotactile actuators. Each actuator is encapsulated within a self-contained vibration unit and driven by its own microcontroller. By leveraging a chain-connection method, each unit receives independent vibration commands from a control unit, with fine-grained control over intensity and frequency. We also designed a GUI Editor to expedite the authoring of spatial vibrotactile patterns. Technical evaluation showed that vibration units reliably reproduced audio waveforms with low-latency and high-bandwidth data communication. Case studies of a phonemic tactile display, virtual reality fitness training, and drone teleoperation demonstrated the potential usage of VibraForge within different domains. A usability study with non-expert users highlighted the low technical barrier and customizability of the toolkit.

High-velocity outflows are ubiquitous in compact, massive (M$_* \sim$ 10$^{11}$ M$_{\odot}$), z $\sim$ 0.5 galaxies with extreme star formation surface densities ($\Sigma_{SFR} \sim$ 2000 M$_{\odot}$ yr$^{-1}$ kpc$^{-2}$). We have previously detected and characterized these outflows using MgII absorption lines. To probe their full extent, we present Keck/KCWI integral field spectroscopy of the [OII] and MgII emission nebulae surrounding all of the 12 galaxies in this study. We find that [OII] is more effective than MgII in tracing low surface brightness, extended emission in these galaxies. The [OII] nebulae are spatially extended beyond the stars, with radial extent R$_{90}$ between 10 and 40 kpc. The nebulae exhibit non-gravitational motions, indicating galactic outflows with maximum blueshifted velocities ranging from -335 to -1920 km s$^{-1}$. The outflow kinematics correlate with the bursty star formation histories of these galaxies. Galaxies with the most recent bursts of star formation (within the last $<$ 3 Myr) exhibit the highest central velocity dispersions ($\sigma >$ 400 km s$^{-1}$), while the oldest bursts have the lowest-velocity outflows. Many galaxies exhibit both high-velocity cores and more extended, slower-moving gas indicative of multiple outflow episodes. The slower, larger outflows occurred earlier and have decelerated as they propagate into the CGM and mix on timescales $>$ 50 Myr., Comment: Accepted for publication in The Astrophysical Journal

This study investigates the 5$f$-electron-conduction electron hybridization process in the heavy fermion superconductor UPd$_2$Al$_3$ using a combination of angle-resolved photoemission spectroscopy (ARPES) and time-resolved photoemission spectroscopy (tr-PES). ARPES measurements reveal the formation of a hybridization gap at a temperature of approximately 75 K, which becomes more pronounced as the temperature decreases. Notably, the persistence of a flat U 5$f$ band at temperatures well above the hybridization onset challenges conventional understanding. Our findings demonstrate a non-monotonic temperature dependence of the quasiparticle relaxation time, with an anomalous decrease at 20 K, suggesting complex electronic and magnetic interactions. These findings provide detailed insights into the 5$f$-electron hybridization process in UPd$_2$Al$_3$, with significant implications for the understanding of heavy fermion superconductivity and the role of 5$f$-electron hybridization in uranium-based materials., Comment: 5 pages, 4 figures

Competing risks models can involve more than one time scale. A relevant example is the study of mortality after a cancer diagnosis, where time since diagnosis but also age may jointly determine the hazards of death due to different causes. Multiple time scales have rarely been explored in the context of competing events. Here, we propose a model in which the cause-specific hazards vary smoothly over two times scales. It is estimated by two-dimensional $P$-splines, exploiting the equivalence between hazard smoothing and Poisson regression. The data are arranged on a grid so that we can make use of generalized linear array models for efficient computations. The R-package TwoTimeScales implements the model. As a motivating example we analyse mortality after diagnosis of breast cancer and we distinguish between death due to breast cancer and all other causes of death. The time scales are age and time since diagnosis. We use data from the Surveillance, Epidemiology and End Results (SEER) program. In the SEER data, age at diagnosis is provided with a last open-ended category, leading to coarsely grouped data. We use the two-dimensional penalised composite link model to ungroup the data before applying the competing risks model with two time scales., Comment: 36 pages, 9 figures, 2 tables

The Linac Coherent Light Source (LCLS) is the world's first x-ray free electron laser. It is a scientific user facility operated by the SLAC National Accelerator Laboratory, at Stanford, for the U.S. Department of Energy. As beam time at LCLS is extremely valuable and limited, experimental efficiency -- getting the most high quality data in the least time -- is critical. Our overall project employs cognitive engineering methodologies with the goal of improving experimental efficiency and increasing scientific productivity at LCLS by refining experimental interfaces and workflows, simplifying tasks, reducing errors, and improving operator safety and stress. Here we describe a multi-agent, multi-scale computational cognitive interaction model of instrument operations at LCLS. Our model simulates aspects of human cognition at multiple cognitive and temporal scales, ranging from seconds to hours, and among agents playing multiple roles, including instrument operator, real time data analyst, and experiment manager. The model can roughly predict impacts stemming from proposed changes to operational interfaces and workflows. Example results demonstrate the model's potential in guiding modifications to improve operational efficiency. We discuss the implications of our effort for cognitive engineering in complex experimental settings, and outline future directions for research. The model is open source and supplementary videos provide extensive detail., Comment: Under review. Supplemental videos: https://www.youtube.com/playlist?list=PLI13S4Z1cbXggy98pDXjqnVnnoekohF2f

In quantum electrodynamics, Schwinger showed in 1951 that in a uniform electric field the vacuum may spontaneously produce electron-positron pairs. For this to occur, the required electric field is exceptionally large, $\sim 10^{18}$ N/C. In the Electromagnetically Accelerating Universe (EAU) model, such an electric field would be undesirable because it discharges the Primoridal Extemely Massive Naked Singularities (PEMNSs) whose mutual repulsion causes the acceleration. This leads to a constraints on the charges and masses of the PEMNSs which must be satisfied in an EAU model., Comment: 9 pages LaTeX. Additional material on time dependence of cosmological constant

The interaction of terahertz (THz) radiation with high-frequency spin resonances in complex magnetic materials is central for modern ultrafast magnonics. Here we demonstrate strong variations of the excitation efficiency of the sub-THz exchange magnon in a single crystal ferrimagnet (Gd,Bi)$_3$Fe$_5$O$_{12}$. An enhancement of the exchange magnon amplitude is observed when its frequency matches an eigenmode of the cavity created by the sample interfaces. Moreover, this enhancement is accompanied by a 5-fold decrease in effective damping of the exchange mode. The THz-exchange magnon interaction in the cavity is analyzed within the developed Landau-Lifshitz-Gilbert formalism for three coupled magnetization sublattices and cavity-enhanced THz field. This work presents a novel approach for the THz excitation of spin dynamics in ferrimagnets and outlines promising pathways for the controlled optimization of light-spin coupling in single crystals.

In ferromagnetic oxide epitaxial multilayers, magnetic properties and interlayer coupling are determined by a variety of factors. Beyond the contribution of interlayer exchange coupling, strain and interfacial effects, such as structural reconstructions or charge transfer, play significant roles, resulting in complex magnetic behaviour. In this study the interlayer coupling of ferromagnetic La0.7Sr0.3Mn0.95Ru0.05O3 (LSMRO) layers (8 nm thick) was investigated, when separated by epitaxial spacers of paramagnetic metallic LaNiO3 (LNO), in stacks exhibiting perpendicular magnetic anisotropy. By varying the thickness of the spacer, it was found that the coupling between two LSMRO layers changes from antiferromagnetic (with a 4 unit cell thick LNO spacer) to ferromagnetic (with a 6 unit cells thick LNO spacer). For multilayers comprising five LSMRO layers and a 4 unit cell thick LNO spacer, the antiferromagnetic coupling was preserved. However, the effective magnetic anisotropy changed, causing the magnetization to cant more towards the in-plane direction. This behavior was corroborated by X-ray magnetic circular dichroism (XMCD) investigations at the Mn and Ni L3-edges. The XMCD results indicated that the 4 unit cells thick LNO spacer in the multilayer become magnetically ordered, closely following the magnetization of adjacent LSMRO layers.

P-splines are appealing for smoothing Poisson distributed counts. They provide a flexible setting for modeling nonlinear model components based on a discretized penalty structure with a relatively simple computational backbone. Under a Bayesian inferential process relying on Markov chain Monte Carlo, estimates of spline coefficients are typically obtained by means of Metropolis-type algorithms, which may suffer from convergence issues if the proposal distribution is not properly chosen. To avoid such a sensitive calibration choice, we extend the Griddy-Gibbs sampler to Bayesian P-splines models with a Poisson response variable. In this model class, conditional posterior distributions of spline components are shown to have attractive mathematical properties. Despite their non-conjugate nature, conditional posteriors of spline coefficients can be efficiently explored with a Gibbs sampling scheme by relying on grid-based approximations. The proposed Griddy-Gibbs sampler for Bayesian P-splines (GGSBPS) algorithm is an interesting calibration-free tool for density estimation and histogram smoothing that is made available in a compact and user-friendly routine. The performance of our approach is assessed in different simulation settings and the GGSBPS algorithm is illustrated on two real datasets., Comment: 25 pages, 3 figures, 1 table

Plutonium's phase diagram is host to complex structures and interactions that make the description of its ground state properties elusive. Using all-electron density functional theory, we study the thermodynamic properties of $\alpha$-Pu. To do this, we build on recent work in the literature by introducing a novel noncollinear magnetic ansatz for $\alpha$-Pu's ground state. The noncollinear ansatz accurately recovers the experimental phonon density of states, heat capacity, and thermal expansion. These new results on $\alpha$-Pu along with recent results on $\delta$-Pu demonstrate the efficacy of noncollinear ansatzes for the description of plutonium.

We report a comprehensive Raman study of the phonon behaviour in PdSe$_2$ in the temperature range of 5 K to 300 K. A remarkable change in the Raman spectrum is observed at 120 K: a significant enhancement of the out-of-plane phonon A$^{1}_{g}$ mode, accompanied by a suppression of the in-plane A$^{2}_{g}$ and B$^{2}_{1g}$ modes. This intriguing behavior is attributed to a temperature-dependent resonant excitation effect. The results are supported by density functional theory (DFT) calculations, which demonstrate that the electron-phonon coupling for the phonon modes varies and is strongly associated with the relevant electronic states. Furthermore, nonlinear frequency shifts are identified in all modes, indicating the decay of an optical phonon into multiple acoustic phonons. The study of Raman emission reported here, complemented by linear optical spectroscopy, reveals an unexpected scenario for the vibrational properties of PdSe$_2$ that holds substantial promise for future applications in PdSe$_2$-based optoelectronics.

Quantum machine learning (QML) has the potential for improving the multi-label classification of rare, albeit critical, diseases in large-scale chest x-ray (CXR) datasets due to theoretical quantum advantages over classical machine learning (CML) in sample efficiency and generalizability. While prior literature has explored QML with CXRs, it has focused on binary classification tasks with small datasets due to limited access to quantum hardware and computationally expensive simulations. To that end, we implemented a Jax-based framework that enables the simulation of medium-sized qubit architectures with significant improvements in wall-clock time over current software offerings. We evaluated the performance of our Jax-based framework in terms of efficiency and performance for hybrid quantum transfer learning for long-tailed classification across 8, 14, and 19 disease labels using large-scale CXR datasets. The Jax-based framework resulted in up to a 58% and 95% speed-up compared to PyTorch and TensorFlow implementations, respectively. However, compared to CML, QML demonstrated slower convergence and an average AUROC of 0.70, 0.73, and 0.74 for the classification of 8, 14, and 19 CXR disease labels. In comparison, the CML models had an average AUROC of 0.77, 0.78, and 0.80 respectively. In conclusion, our work presents an accessible implementation of hybrid quantum transfer learning for long-tailed CXR classification with a computationally efficient Jax-based framework., Comment: 11 pages, 13 figures, 3 tables

Using heterodyne transient grating spectroscopy, we observe a significant enhancement of exciton diffusion within a monolayer WSe$_2$ stacked on top of graphene. We further demonstrate that the diffusion dynamics can be optically tuned on the ultrafast time scale (i.e. a few picoseconds) by altering the photoexcited charge carrier density in graphene. The results reveal that, on a time scale of a few picoseconds, the effective diffusion constant in the WSe$_2$/graphene heterostructure is approximately 40 cm$^2 $/s, representing a substantial improvement over the 2 cm$^2 $/s typical for an isolated monolayer of WSe$_2$. The enhanced diffusion can be understood in terms of a transient screening of impurities, charge traps, and defect states in WSe$_2$ by photoexcited charge carriers in graphene. Furthermore, we observe that the diffusion within WSe$_2$ is affected by interlayer interactions, like charge transfer, exhibiting different dynamic states depending on the incident excitation fluence. These findings underscore the dynamic nature of screening and diffusion processes in heterostructures of 2D semiconductors and graphene and provide valuable insights for future applications of these systems in ultrafast optoelectronic devices.

To describe the dark side of the Universe, we adopt a novel approach where dark energy is explained as an electrically charged majority of dark matter. Dark energy, as such, does not exist. The Friedmann equation at the present time coincides with that in a conventional approach, although the cosmological "constant" in the Electromagnetic Accelerating Universe (EAU) Model shares a time dependence with the matter component. Its equation of state is $\omega \equiv P/\rho \equiv -1$ within observational accuracy., Comment: 26 pages LaTeX Submitted to {\it Particle Theory and Theoretical Cosmology}, Festschrift for 80th anniversary of P.H. Frampton. To appear in {\it Entropy} journal, and Special Edition, MDPI Books (2024). arXiv admin note: substantial text overlap with arXiv:1511.08801, arXiv:2304.10370

Generative Adversarial Network (GAN)-based synthesis of fat suppressed (FS) MRIs from non-FS proton density sequences has the potential to accelerate acquisition of knee MRIs. However, GANs trained on single-site data have poor generalizability to external data. We show that federated learning can improve multi-center generalizability of GANs for synthesizing FS MRIs, while facilitating privacy-preserving multi-institutional collaborations., Comment: 5 pages, 2 figures

Domain Specific Languages (DSLs) increase programmer productivity and provide high performance. Their targeted abstractions allow scientists to express problems at a high level, providing rich details that optimizing compilers can exploit to target current- and next-generation supercomputers. The convenience and performance of DSLs come with significant development and maintenance costs. The siloed design of DSL compilers and the resulting inability to benefit from shared infrastructure cause uncertainties around longevity and the adoption of DSLs at scale. By tailoring the broadly-adopted MLIR compiler framework to HPC, we bring the same synergies that the machine learning community already exploits across their DSLs (e.g. Tensorflow, PyTorch) to the finite-difference stencil HPC community. We introduce new HPC-specific abstractions for message passing targeting distributed stencil computations. We demonstrate the sharing of common components across three distinct HPC stencil-DSL compilers: Devito, PSyclone, and the Open Earth Compiler, showing that our framework generates high-performance executables based upon a shared compiler ecosystem.