Project summary

This project analyzes the historical development of general relativistic magnetohydrodynamics (GRMHD) simulations as a case study in scientific and technological progress. GRMHD has become a central tool in astrophysics, enabling modeling of black hole accretion, jets, and high-energy phenomena. However, the field’s progress has been uneven and driven by a combination of algorithmic innovation, computational scaling, and conceptual breakthroughs.

This project aims to systematically document and analyze these drivers of progress, producing a detailed account of how GRMHD simulations evolved and what factors most strongly influenced their advancement.

The final output will be a long-form research essay suitable for publication on platforms such as LessWrong and arXiv, targeting both academic and meta-science audiences.

What are this project's goals? How will you achieve them?

Goals:

• Identify key inflection points in the development of GRMHD simulations

• Quantify the relative importance of:

  • algorithmic improvements

  • increased computational power

  • theoretical insights

• Understand bottlenecks that slowed progress

• Extract general lessons about how computational science advances

Approach:

• Literature review of GRMHD papers over the past ~20–30 years

• Categorization of advances (e.g., numerical schemes, resolution, hardware scaling)

• Timeline construction of major breakthroughs

• Analysis of trends (e.g., performance vs. compute, method adoption)

• Synthesis into a structured “progress model” for the field

How will this funding be used?

My PhD program no longer has the funds to provide me a stipend, so this would serve in its place and allow me to complete this project at the intersection of physics and progress studies as the final piece of my dissertation.

Who is on your team? What's your track record on similar projects?

I am nearly done with a first-author technical paper on original GRMHD simulations that will be submitted to ApJ.

What are the most likely causes and outcomes if this project fails?

What are the most likely causes and outcomes if this project fails?

Risks:

• Difficulty obtaining consistent or comparable historical benchmarks

• Overly qualitative conclusions if quantitative data is limited

• Scope creep (field is broad and technically complex)

Mitigations:

• Focus on well-documented milestones and widely used codes

• Combine qualitative and quantitative analysis

• Maintain a tightly scoped case study

Failure outcome:

• A less rigorous or less generalizable analysis, but still a useful descriptive overview of the field’s development

How much money have you raised in the last 12 months, and from where?

$0