arXiv subjects

Michael Cecil

Publications and source records attributed to Michael Cecil.

6 recordsLinked to original sources

arXiv2026

MRI-triggered instability at the inner dead zone edge: disc evolution and burst modes tied to magnetic field strengths

The inner edge of the dead zone (DZIE) in protoplanetary discs is prone to episodic instability caused by the activation of the magneto-rotational instability (MRI) in the weakly turbulent regions. We show how different magnetic field configurations set the inner disc structure and regulate the morphologies of instability cycles. We performed 2D and 3D radiation hydrodynamic simulations of the regions around the DZIE of a Class II disc over a thousand-year timescale. We implemented MRI activation criteria based on ambipolar and Ohmic diffusion coupled to magnetic field strength profiles comprising stellar and disc components. The properties and consequences of the episodic accretion events are highly sensitive to the magnetic field strength. We recover previously reported behaviour by considering relatively strongly magnetised discs. A new burst mode is revealed, in which the midplane MRI activity is restricted to small radii in the presence of weak magnetic fields. In this narrow mode, the pressure bump at the DZIE does not remain static even during quiescence. A distinct dichotomy between the wide and narrow modes is established by the hydrodynamic (in)stability of the ionisation front. Both modes are additionally separated into a reflaring and a non-reflaring version. Our setup does not lead to the classical thermal instability by hydrogen ionisation. In quiescence, the MRI active region shows a layered structure that converges towards the midplane near the star. Our 3D model reveals the breaking of density features produced in the narrow mode, leading to vortices at radii smaller than 0.5 AU. Coupling MRI activity directly to different magnetic field strengths, rather than using simple temperature thresholds, enables a variety of burst modes. Each mode exhibits characteristic accretion burst signatures and has different consequences for planet formation and migration conditions.

astro-ph.EP↗

arXiv2026

Planet formation at the inner edge of the dead zone I. the interplay between accretion outbursts and dust growth

The inner edge of the dead zone in protoplanetary disks has been shown to periodically go unstable, leading to accretion outbursts and annular substructure within the dead zone. While dust opacities play a key role in this process, the thermal and dynamical effects of dust drift and growth have not been fully explored. We investigate the evolution of accretion outbursts in the inner disk and their impact on the formation of dust-rich substructure with a fully dynamic dust model. In doing so, we aim to highlight the importance and limitations of dust growth in forming planets in this region. We carry out radiation hydrodynamics simulations of a protoplanetary disk including prescriptions for the structure of the inner edge of the dead zone, viscous and irradiation heating, radiative cooling, dust-gas dynamics, and dust evolution. We find that accretion outbursts at the inner disk edge can lead to the formation of multiple dust rings that extend deep inside the dead zone (~1 au) and diffuse on viscous timescales (~10 kyr for alpha=1e-4). The rings contain dust masses of up to ~1.6 Earth masses, possibly kickstarting planet formation. Dynamic modeling of dust fragmentation enhances the total opacity during the burst, yielding more intense outbursts that penetrate deeper into the dead zone. Our results highlight the thermal and dynamical importance of treating dust dynamics self-consistently in models of accretion outbursts. Additional modeling is needed to characterize the inevitable nonaxisymmetric structures arising from accretion outbursts and their observational prospects.

astro-ph.EP↗

arXiv2026

The role of detailed gas and dust opacities in shaping the evolution of the inner disc edge subject to episodic accretion

We investigate the effects of different dust and gas opacity descriptions on the structure and evolution of the inner regions of protoplanetary discs. The influence on the episodic instability of the inner rim is hereby of central interest. 2D axisymmetric radiation hydrodynamic models are employed to simulate the evolution of the inner disc over several thousand years. Our simulations greatly expand on previous models by implementing detailed opacity descriptions in terms of their mean and frequency-dependent values, allowing us to also consider binned frequency-dependent irradiation. The adaptive opacity description significantly affects the structure of the inner disc rim, with gas opacities exerting the greatest influence. The resulting effects include shifts in the position of both the dust sublimation front and the dead zone inner edge, a significantly altered temperature in the dust-free region and the manifestation of an equilibrium temperature degeneracy as a sharp temperature transition. The episodic instability due to MRI activation in the dead zone still occurs, but at lower inner disc densities. While the gas opacities set the initial conditions for the instability, the evolution of the outburst itself is mainly governed by the dust opacities. The analysis of criteria for non-axisymmetric instabilities reveals possible breaking of the density peaks produced by the burst. However, due to the periodicity of the instability, the inner edge itself may remain stable throughout quiescent phases according to linear criteria. Although the thermal structure of the inner disc is crucially affected by different opacity descriptions, the mechanism of the periodic instability of the DZIE remains active and is only marginally influenced by gas opacities. The observational consequences of the severely altered temperatures may be significant and require further investigation.

astro-ph.EP↗

arXiv2024

Variability of the inner dead zone edge in 2D radiation hydrodynamic simulations

The inner regions of protoplanetary disks are prone to thermal instability (TI), which can significantly impact the thermal and dynamic evolution of planet-forming regions. Observable as episodic accretion outbursts, such periodic disturbances shape the disk's vertical and radial structure. We investigate the stability of the inner disk edge around a Class II T Tauri star and analyse the consequences of TI on the inner disk's evolution in both the vertical and radial dimensions. A particular focus is laid on the emergence and destruction of solid-trapping pressure maxima. Our 2D axisymmetric radiation hydrodynamic models include the transition to the dead zone from a highly turbulent inner disk, heating by both stellar irradiation and viscous dissipation, vertical and radial radiative transport and an adaptive dust-to-gas mass ratio. The simulated time frames include both the TI- and quiescent phases. We track the TI on S-curves of thermal stability. The TI in our models can develop in disks with moderate accretion rates and results from the activation of the magnetorotational instability (MRI) in the dead zone. The TI creates an extensive MRI active region around the midplane and disrupts the stable pebble- and migration trap at the inner edge of the dead zone. Our simulations consistently show the occurrence of TI-reflares, which, together with the initial TI, produce pressure maxima in the inner disk within 1 AU, possibly providing favourable conditions for streaming instability. On a timescale of a few thousand years, TI regularly disrupts the disk's radial and vertical structure within 1 AU. While several pressure maxima are created, stable migration traps are destroyed and reinstated after the TI phase. Our models provide a foundation for more detailed investigations into phenomena such as short-term variability of accretion rates.

astro-ph.EP↗

arXiv2024

Seeing Through the Clouds: Cloud Gap Imputation with Prithvi Foundation Model

Filling cloudy pixels in multispectral satellite imagery is essential for accurate data analysis and downstream applications, especially for tasks which require time series data. To address this issue, we compare the performance of a foundational Vision Transformer (ViT) model with a baseline Conditional Generative Adversarial Network (CGAN) model for missing value imputation in time series of multispectral satellite imagery. We randomly mask time series of satellite images using real-world cloud masks and train each model to reconstruct the missing pixels. The ViT model is fine-tuned from a pretrained model, while the CGAN is trained from scratch. Using quantitative evaluation metrics such as structural similarity index and mean absolute error as well as qualitative visual analysis, we assess imputation accuracy and contextual preservation.

cs.CV↗

arXiv2023

Foundation Models for Generalist Geospatial Artificial Intelligence

Significant progress in the development of highly adaptable and reusable Artificial Intelligence (AI) models is expected to have a significant impact on Earth science and remote sensing. Foundation models are pre-trained on large unlabeled datasets through self-supervision, and then fine-tuned for various downstream tasks with small labeled datasets. This paper introduces a first-of-a-kind framework for the efficient pre-training and fine-tuning of foundational models on extensive geospatial data. We have utilized this framework to create Prithvi, a transformer-based geospatial foundational model pre-trained on more than 1TB of multispectral satellite imagery from the Harmonized Landsat-Sentinel 2 (HLS) dataset. Our study demonstrates the efficacy of our framework in successfully fine-tuning Prithvi to a range of Earth observation tasks that have not been tackled by previous work on foundation models involving multi-temporal cloud gap imputation, flood mapping, wildfire scar segmentation, and multi-temporal crop segmentation. Our experiments show that the pre-trained model accelerates the fine-tuning process compared to leveraging randomly initialized weights. In addition, pre-trained Prithvi compares well against the state-of-the-art, e.g., outperforming a conditional GAN model in multi-temporal cloud imputation by up to 5pp (or 5.7%) in the structural similarity index. Finally, due to the limited availability of labeled data in the field of Earth observation, we gradually reduce the quantity of available labeled data for refining the model to evaluate data efficiency and demonstrate that data can be decreased significantly without affecting the model's accuracy. The pre-trained 100 million parameter model and corresponding fine-tuning workflows have been released publicly as open source contributions to the global Earth sciences community through Hugging Face.

cs.CV↗