Joel Ballivan, Fine-tuning arguments and biological design arguments: can the theist have both?, Religious Studies, 2019 pp. 1-7.
Luke A Barnes, A Reasonable Little Question: A Formulation of the Fine-Tuning Argument, Ergo, An Open Access Journal Of Philosophy, 6 (2019) 1-38.
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Carl Emery, Consciousness or the Physical Universe - Which Came First?, The Heythrop Journal, 60 (2015) 16-28.
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Jonathan J Heckman and Cumrun Vafa, Fine tuning, sequestering, and the swampland, Physics Letters B, 2019 vol. 798 p. 135004.
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Jonathan J Heckman and Cumrun Vafa, Fine Tuning, Sequestering, and the Swampland, Arxiv.Org, 2019 1905.06342v1, hep-th.
We conjecture and present evidence that any effective field theory coupled to gravity in flat space admits at most a finite number of fine tunings, depending on the amount of supersymmetry and spacetime dimension. In particular, this means that there are infinitely many non-trivial correlations between the allowed deformations of a given effective field theory in the gravitational context. Fine tuning of parameters allows us to obtain some consistent CFTs in the IR limit of gravitational theories. Related to finiteness of fine tunings, we conjecture that except for a finite number of CFTs, the rest cannot be consistently coupled to gravity and belong to the swampland. Moreover, we argue that even though matter sectors coupled to gravity may sometimes be partially sequestered, there is an irreducible level of mixing between them, correlating and coupling infinitely many operators between these sectors.
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Timo A Lähde et al., An update on fine-tunings in the triple-alpha process, , 2019.
The triple-alpha process, whereby evolved stars create carbon and oxygen, is believed to be fine-tuned to a high degree. Such fine-tuning is suggested by the unusually strong temperature dependence of the triple-alpha reaction rate at stellar temperatures. This sensitivity is due to the resonant character of the triple-alpha process, which proceeds through the so-called "Hoyle state" of $^{12}$C with spin-parity $0^+$. The question of fine-tuning can be studied within the {\it ab initio} framework of nuclear lattice effective field theory, which makes it possible to relate {\it ad hoc} changes in the energy of the Hoyle state to changes in the fundamental parameters of the nuclear Hamiltonian, which are the light quark mass $m_q$ and the electromagnetic fine-structure constant. Here, we update the effective field theory calculation of the sensitivity of the triple-alpha process to small changes in the fundamental parameters. In particular, we consider recent high-precision lattice QCD calculations of the nucleon axial coupling $g_A$, as well as new and more comprehensive results from stellar simulations of the production of carbon and oxygen. While the updated stellar simulations allow for much larger {\it ad hoc} shifts in the Hoyle state energy than previously thought, recent lattice QCD results for the nucleon S-wave singlet and triplet scattering lengths now disfavor the scenario of no fine-tuning in the light quark mass $m_q$.
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Carlos Outeiral et al., Investigating the potential for a limited quantum speedup on protein lattice problems, Arxiv Preprint, 2020.
Protein folding, the determination of the lowest-energy configuration of a protein, is an unsolved computational problem. If protein folding could be solved, it would lead to significant advances in molecular biology, and technological development in areas such as drug discovery and catalyst design. As a hard combinatorial optimisation problem, protein folding has been studied as a potential target problem for adiabatic quantum computing. Although several experimental implementations have been discussed in the literature, the computational scaling of these approaches has not been elucidated. In this article, we present a numerical study of the (stoquastic) adiabatic quantum algorithm applied to protein lattice folding. Using exact numerical modelling of small systems, we find that the time-to-solution metric scales exponentially with peptide length, even for small peptides. However, comparison with classical heuristics for optimisation indicates a potential limited quantum speedup. Overall, our results suggest that quantum algorithms may well offer improvements for problems in the protein folding and structure prediction realm.
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Steinar Thorvaldsen and Ola Hössjer, Using statistical methods to model the fine-tuning of molecular machines and systems, Journal Of Theoretical Biology, 2020 p. 110352.
Fine-tuning has received much attention in physics, and it states that the fundamental constants of physics are finely tuned to precise values for a rich chemistry and life permittance. It has not yet been applied in a broad manner to molecular biology. However, in this paper we argue that biological systems present fine-tuning at different levels, e.g. functional proteins, complex biochemical machines in living cells, and cellular networks. This paper describes molecular fine-tuning, how it can be used in biology, and how it challenges conventional Darwinian thinking. We also discuss the statistical methods underpinning fine-tuning and present a framework for such analysis
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