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Joseph Bates

Publications and source records attributed to Joseph Bates.

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The Dyson Minds 2025 Workshop: SETI around Black Holes

The Dyson Minds 2025 Workshop, held at the Center for Brains, Minds & Machines at MIT and organized by Penn State, MIT, and The Ultraintelligence Foundation, brought together researchers in astrophysics, engineering, artificial intelligence, computer science, and philosophy to examine "Dyson Minds" -- large-scale post-biological intelligences powered by energy harvested from supermassive black holes (SMBHs). Building on the ideas of F. J. Dyson (1960, 1966) and I. J. Good (1966), participants explored the physical, engineering, behavioral, and observational consequences of civilizations embodied as machinery operating near the universe's most powerful energy sources. The workshop aimed to develop new observational strategies capable of detecting signatures of such systems. Despite the highly cross-disciplinary scope, discussions centered on how a Dyson Mind might be constructed, how it might behave, and how those factors would shape strategies for the search for extraterrestrial intelligence. Key themes included the thermodynamic, mechanical, and stability limits of Dyson swarms; the trade-offs between power availability and communication latency in distributed minds; and how observability changes depending on whether Dyson Minds act as coherent entities or as loosely coordinated collectives. Across these topics, the consensus was that details of architecture and behavior strongly influence observational signatures. A major recommendation was to apply anomaly-detection methods to archival datasets, including those from WISE, JWST, and the Event Horizon Telescope, to identify unusual sources potentially overlooked by standard reduction pipelines. By integrating insights from multiple disciplines, the meeting advanced concrete, observation-focused strategies for future technosignature searches around SMBHs.

astro-ph.GA

Toward Lattice QCD On Billion Core Approximate Computers

We present evidence of the feasibility of using billion core approximate computers to run simple U(1) sigma models, and discuss how the approach might be extended to Lattice Quantum Chromodynamics (LQCD) models. This work is motivated by the extreme time, power, and cost needed to run LQCD on current computing hardware. We show that, using massively parallel approximate hardware, at least some models can run with great speed and power efficiency without sacrificing accuracy. As a test of accuracy, a 32 x 32 x 32 U(1) sigma model yielded similar results using floating point and approximate representations for the spins. A 20 million point 3D model, run on a 34,000-core single-board prototype approximate computer, showed encouraging accuracy with a ~750 times improvement in speed and ~2500 times improvement in speed/watt compared to a traditional CPU. These results suggest there is value in future research to determine whether similar speed-ups and accuracies are possible running full LQCD on the compact billion-core approximate computing systems that are now practical.

hep-lat