Notes: Physics Wanting Something

Chapter notes for “Physics Wanting Something”

Notes

¹ Haldane, J.B.S., Possible Worlds and Other Papers (Chatto & Windus, 1927). The full quote, “the universe is not only queerer than we suppose, but queerer than we can suppose,” appears in the essay “Possible Worlds.”

² Aristotle, Physics II.3 and Metaphysics V.2. Aristotle’s four causes (material, formal, efficient, final) provided the dominant explanatory framework in Western natural philosophy from antiquity through the medieval period.

³ Campbell, John O., “Universal Darwinism as a process of Bayesian inference,” Frontiers in Systems Neuroscience 10 (2016): 49, https://doi.org/10.3389/fnsys.2016.00049. Campbell demonstrates that the Price equation is mathematically isomorphic to Bayesian updating, unifying evolutionary and inferential reasoning.

⁴ England, Jeremy, “Dissipative adaptation in driven self-assembly,” Nature Nanotechnology 10 (2015): 919-923, https://doi.org/10.1038/nnano.2015.250. England’s theoretical framework shows that driven systems will, over time, tend toward configurations that are better at absorbing and dissipating work from external drives.

^4a Vanchurin, Vitaly. “On the emergence of spacetime in learning systems.” Preprint, DOI: 10.13140/RG.2.2.13481.25444 (October 2025).

^4b Gusev, Y. and Vanchurin, V., “Molecular Learning Dynamics,” arXiv:2504.10560 (2025). The paper develops a physics-learning duality: the equations of motion that follow from a molecular system’s Lagrangian also emerge when the particles are treated as agents performing gradient-based optimization. For the water result cited here, the loss functions of oxygen and hydrogen were inferred from a quantum-mechanical (CP2K) simulation; the learning-based run reproduced bond lengths, vibrational spectra and thermal fluctuations while completing 1,000 steps in about 20 seconds against roughly 10 hours for the physics-based simulation, a speedup of about 1,800.

^4c Vanchurin, V., Wolf, Y.I., Katsnelson, M.I. and Koonin, E.V., “Toward a theory of evolution as multilevel learning,” PNAS 119(6): e2120037119 (2022). The paper treats mutation and selection as learning at the genome level, epigenetic modification as learning at the organism level, and cultural transmission as learning at the population level, each with its own trainable variables and its own effective loss function.

^4d Matloff, G., “Can Panpsychism Become an Observational Science?,” Journal of Consciousness Exploration and Research 7(7): 524-543 (2016). See also Haisch, B., The God Theory (Weiser, 2006), for the proto-consciousness field hypothesis.

^4e Vanchurin, V., “Towards a theory of quantum gravity from neural networks,” arXiv:2111.00903v3 (2022). The claim is speculative; the derivation, recovering the Schrödinger equation, Lorentz symmetry, the geodesic equation, and the Einstein field equations from neural network dynamics, is mathematically explicit.

⁵ Wolfram, Stephen, “What Ultimately Is There? Metaphysics and the Ruliad,” Stephen Wolfram Writings (February 4, 2026). Wolfram argues that the ruliad (the entangled limit of all possible computations) is a necessary abstract object, and that observers like us inevitably perceive certain regularities (including physical laws) as a consequence of our computational boundedness.

⁶ Wissner-Gross, A.D. and C.E. Freer, “Causal Entropic Forces,” Physical Review Letters 110 (2013): 168702, https://doi.org/10.1103/PhysRevLett.110.168702. Their simulations showed that a causal entropy maximization principle (maximizing the entropy of future accessible states) spontaneously produces intelligent behavior including tool use and social cooperation.

⁷ Fontenele, Antonio J., et al., “Criticality between Cortical States,” Physical Review Letters 122 (2019): 208101, https://doi.org/10.1103/PhysRevLett.122.208101. The authors demonstrated that cortical dynamics exhibit a genuine phase transition between synchronous and desynchronized states, with the brain operating near this critical point.

⁸ Atasoy, Selen, et al., “Connectome-harmonic decomposition of human brain activity reveals dynamical repertoire re-organization under LSD,” Scientific Reports 7 (2017): 17661, https://doi.org/10.1038/s41598-017-17546-0. Using connectome harmonics, Atasoy et al. showed that LSD expands the repertoire of active brain states, consistent with increased neural entropy.

⁹ Carhart-Harris, Robin L., et al., “The entropic brain: a theory of conscious states informed by neuroimaging research with psychedelic drugs,” Frontiers in Human Neuroscience 8 (2014): 20, https://doi.org/10.3389/fnhum.2014.00020. The entropic brain hypothesis proposes that the quality of conscious states can be indexed by the entropy of spontaneous brain activity, with higher entropy corresponding to richer phenomenal experience.

¹⁰ Parliament of the World’s Religions, “Declaration Toward a Global Ethic” (1993). This declaration, signed by representatives of the world’s major religious and spiritual traditions, identified the Golden Rule (“treat others as you wish to be treated”) as a principle present in virtually every ethical tradition across cultures and centuries.

¹¹ Dalton, Drew M., “The Unbecoming of Being: Thermodynamics and The Metaphysics and Ethics of Entropic Decay,” Technophany 2:2 (2024), https://doi.org/10.54195/technophany.14045. The fullest statement of entropic pessimism. See also Dalton, The Matter of Evil: From Speculative Realism to Ethical Pessimism (Northwestern University Press, 2023) for the book-length development. Dalton draws on Schopenhauer’s The World as Will and Representation (1818/1844), the classical source for metaphysical pessimism.

¹² Kolchinsky, Artemy and David H. Wolpert. “Semantic information, autonomous agency, and nonequilibrium statistical physics.” Interface Focus 8(6): 20180041 (2018), https://doi.org/10.1098/rsfs.2018.0041. They define semantic information as “the syntactic information that a physical system has about its environment which is causally necessary for the system to maintain its own existence.”

¹³ Rovelli, C. “Meaning and Intentionality = Information + Evolution.” In Wandering Towards a Goal, ed. A. Aguirre, B. Foster, and Z. Merali (Springer, 2018). Rovelli frames meaning as arising from the coupling of a physical system with its environment through natural selection.