arXiv subjects

David M. Hall

Publications and source records attributed to David M. Hall.

6 recordsLinked to original sources

arXiv2025

Climate in a Bottle: Towards a Generative Foundation Model for the Kilometer-Scale Global Atmosphere

Climate modeling is reaching unprecedented resolution, producing petabytes of data. AI climate model emulators offer a path to computationally cheap analysis, enabling new scientific insight and scenario planning. Recent advances show promise in faithfully emulating climate data. However, prevailing auto-regressive paradigms are difficult to train on climate time horizons due to drifts, instabilities, and component-coupling challenges. They are hard to scale to high resolution and require sifting through troves of output to identify rare extremes of interest. We present Climate in a Bottle (cBottle), a generative diffusion-based framework emulating global 5 km climate simulations and reanalysis on the HEALPix grid. cBottle samples directly from the full distribution of atmospheric states, avoiding auto-regressive rollout, and is the first to reach this 12.5M-pixel global resolution. It consists of two stages: a coarse-resolution generator conditioned on sea surface temperatures and solar position, followed by a patch-based 16x super-resolution stage. cBottle passes a battery of tests, including diurnal-to-seasonal variability, large-scale modes of variability, tropical cyclone statistics, and trends of climate change and weather extremes. It is a step toward a foundation model: bridging data modalities (reanalysis and simulation), enabling zero-shot bias correction, downscaling, and data infilling. It also enables new interactivity via guided diffusion. For example, we train a tropical cyclone (TC) classifier alongside the generator, guide towards TC states, and obtain physically credible samples. This opens the door to guidance methods for a wide array of user queries and new ways of interacting with climate data.

physics.ao-ph↗

arXiv2023

Developing Digital Twins for Earth Systems: Purpose, Requisites, and Benefits

The accelerated change in our planet due to human activities has led to grand societal challenges including health crises, intensified extreme weather events, food security, environmental injustice, etc. Digital twin systems combined with emerging technologies such as artificial intelligence and edge computing provide opportunities to support planning and decision-making to address these challenges. Digital twins for Earth systems (DT4ESs) are defined as the digital representation of the complex integrated Earth system including both natural processes and human activities. They have the potential to enable a diverse range of users to explore what-if scenarios across spatial and temporal scales to improve our understanding, prediction, mitigation, and adaptation to grand societal challenges. The 4th NOAA AI Workshop convened around 100 members who are developing or interested in participating in the development of DT4ES to discuss a shared community vision and path forward on fostering a future ecosystem of interoperable DT4ES. This paper summarizes the workshop discussions around DT4ES. We first defined the foundational features of a viable digital twins for Earth system that can be used to guide the development of various use cases of DT4ES. Finally, we made practical recommendations for the community on different aspects of collaboration in order to enable a future ecosystem of interoperable DT4ES, including equity-centered use case development, community-driven investigation of interoperability for DT4ES, trust-oriented co-development, and developing a community of practice.

physics.soc-ph↗

arXiv2013

Time to Extinction in Subcritical Two-Sex Branching Processes

Lower and upper bounds for the cumulative distribution function (cdf) of the time to extinction in a subcritical two-sex branching process are derived. A recursive procedure for approximating this cdf is also utilized. The results are illustrated with some simulations.

math.PR↗

arXiv2006

Numerical Method for Hydrodynamic Transport of Inhomogeneous Polymer Melts

We introduce a mesoscale method for simulating hydrodynamic transport and self assembly of inhomogeneous polymer melts in pressure driven and drag induced flows. This method extends dynamic self consistent field theory (DSCFT) into the hydrodynamic regime where bulk material transport and viscoelastic effects play a significant role. The method combines four distinct components as a single coupled system, including (1) non-equilibrium self consistent field theory describing block copolymer self-assembly, (2) multi-fluid Navier-Stokes type hydrodynamics for tracking material transport, (3) constitutive equations modeling viscoelastic phase separation, and (4) rigid wall fields which represent moving channel boundaries, machine components, and nano-particulate fillers. We also present an efficient, pseudospectral implementation for this set of coupled equations which enables practical application of the model in periodic domains. We validate the model by reproducing well known phenomena including equilibrium diblock meso-phases, analytic Stokes flows, and viscoelastic phase separation of glassy/elastic polymer melts. We also demonstrate the stability and accuracy of the numerical implementation by examining its convergence under grid-size refinement.

cond-mat.soft↗

arXiv2006

Hydrodynamic Self-Consistent Field Theory for Inhomogeneous Polymer Melts

We introduce a mesoscale technique for simulating the structure and rheology of block copolymer melts and blends in hydrodynamic flows. The technique couples dynamic self consistent field theory (DSCFT) with continuum hydrodynamics and flow penalization to simulate polymeric fluid flows in channels of arbitrary geometry. We demonstrate the method by studying phase separation of an ABC triblock copolymer melt in a sub-micron channel with neutral wall wetting conditions. We find that surface wetting effects and shear effects compete, producing wall-perpendicular lamellae in the absence of flow, and wall-parallel lamellae in cases where the shear rate exceeds some critical Weissenberg number.

cond-mat.soft↗

arXiv2001

Gravitational Settling of 22Ne in Liquid White Dwarf Interiors

The nuclear reactions that occur in the stellar progenitors of white dwarfs (WDs) lead to an internal composition of 12C, 16O, and a ``contaminant'' nucleus, 22Ne. The 22Ne is produced by helium captures on 14N left from hydrogen burning via the CNO cycle. By virtue of its two excess neutrons (relative to the predominant A=2Z nuclei), a downward force of 2m_pg is exerted on 22Ne in the WD interior. This biases its diffusive equilibrium, forcing 22Ne to settle towards the center of the WD. We discuss the physics of the gravitational settling when the WD is in the liquid state and the luminosity generated by it. This modifies the cooling of WD's with masses in excess of a solar mass. The current uncertainties in the microphysics even allow for solutions where a 1.2M_\odot WD remains mostly liquid for a few Gyrs due to the internal heating from 22Ne sedimentation. This highlights the need for an accurate calculation of the inter-diffusion coefficient, especially in the quantum liquid regime relevant for high mass WD's. There is also time in old, liquid WD's (such as those found in cataclysmic variables and possibly in accreting Type Ia progenitors) for partial settling.

astro-ph↗