Author: sglanz

Assembly theory explains and quantifies selection and evolution

Applied to ITC, TMT, EVP
Abhishek Sharma, Dániel Czégel, Michael Lachmann, Christopher P. Kempes, Sara I. Walker & Leroy Cronin Nature volume 622, pages 321–328 (2023)

In this post, I first summarize the source document. Then, I query how the theories contained in that document can be used to pursue TMT (Transmaterialization Technology) research. This also applies to research and development in ITC (Interdimensional Transcommunication) ITC and EVP (Electronic Voice Phenomena). I used Open AI’s Chat GPT4 as an assistant in writing this post.

Source Document:

https://www.nature.com/articles/s41586-023-06600-9

Summary

Understanding and Quantifying Selection and Evolution through Assembly Theory in Biological Systems

Understanding and Quantifying Selection and Evolution through Assembly Theory in Biological Systems

  • Reconciling Biology and Physics:
    • Scientists have struggled to reconcile biological evolution with the laws of physics.
    • Evolutionary theory explains the existence and non-existence of things through selection.
  • Introducing Assembly Theory:
    • Assembly Theory (AT) redefines the concept of an ‘object’ to explain the emergence of diverse forms.
    • AT conceptualizes objects as entities defined by their formation histories and introduces the concept of assembly (A).
  • Understanding Objects in AT:
    • Objects in AT are defined by their possible formation histories.
    • AT allows for the incorporation of novelty generation and selection into the physics of complex objects.
  • The Assembly Space:
    • The assembly space in AT captures the minimal memory necessary to construct observed objects.
    • AT accounts for multiple realizability and modular use of units in the assembly of biological objects.
  • Quantifying Selection and Evolution:
    • AT introduces assembly indices to quantify the degree of selection and evolution in objects.
    • Assembly is a function of copy number and assembly indices, allowing for the measurement of memory required to produce objects.
  • Measuring Complexity and Functionality:
    • The assembly index alone cannot detect selection, but when combined with copy number, it can measure complexity.
    • Complex and functional objects generated by evolution require many steps to make and have many identical copies.
  • The Unification of Physics and Biology:
    • AT provides a powerful interface between physics and biology by reimagining the concept of matter within assembly spaces.
    • It offers a framework to unify descriptions of selection and the generation of novelty across disciplines.
  • A New Aspect of Physics:
    • AT reveals a new aspect of physics emerging at the chemical scale.
    • History and causal contingency influence the existence of objects.
  • Universal Computation for Molecules:
    • Using universal computation to assess molecules adds unrealistic dynamics, making the answer uncomputable.
    • The assembly measure presented here uses realistic dynamics for molecules and is computable for any molecule.
  • Application to Chemical Systems:
    • AT is applied to chemical systems to develop a new understanding of the evolution of complex matter.
    • The assembly index of molecules has a clear physical interpretation and has been validated as evidence of selection.
  • General Applicability:
    • AT can apply to a wide variety of systems including polymers, cell morphology, graphs, images, computer programs, human languages, and memes.
    • The challenge lies in constructing an assembly space with a clear physical meaning for each system.
  • Two Important Features in AT:
    • Objects in the environment constrain the steps to assemble an object in AT.
    • These objects have been selected and retained to physically instantiate the memory needed to build the target object.
    • Importance of Copy Number:
      • Copy number is important for detecting selection in highly complex molecules.
      • High copy numbers indicate non-random processes generating the object.
  • The Assembly Equation:
    • Assembly is quantified using the assembly equation, which combines the assembly index and copy number of objects in an ensemble.
    • Assembly quantifies both the difficulty of discovering new objects and how selection was required to make them.
  • Assembly and Selectivity:
    • Assembly in AT results from increasing copy numbers and assembly indices.
    • High assembly values indicate selection and the presence of a memory-based mechanism for generating specific objects.
  • Assembly Spaces and Selection:
    • Assembly spaces allow us to understand how selection and historical contingency impose constraints on future creations.
    • Combinatorial objects in assembly spaces play a crucial role in describing selection.
  • Assembly observed and assembly universe:
    • Assembly observed (A) captures all histories for the construction of observed objects from elementary building blocks, consistent with physical operations.
    • Assembly universe (A) is an assembly space containing all possible pathways for assembling any object composed of the same building blocks as the target object. It has no rules, leading to a combinatorial explosion.
  • Selection and resource limitation:
    • Selection and resource limitation restrict the size of the space of what can be built.
    • Higher-assembly objects can be built before constructing all possible lower-assembly objects due to memory and resource limitations.
  • Assembly possible and assembly contingent:
    • Assembly possible (A) represents the space of physically possible objects and is described by undirected forward dynamics.
    • Assembly contingent (A) represents the possible space of objects where history and selection matter. The growth of assembly contingent is slower than exponential due to selectivity along specific paths.
  • Exploration and selectivity:
    • Exploration ratio quantifies the degree of exploration at a given assembly step.
    • Directed exploration with selection leads to a lower exploration ratio and higher complexity compared to undirected exploration, indicating the presence of selectivity.
    • Historical contingency leads to the exploration of higher-assembly objects before exhausting lower-assembly objects.
  • Assembly dynamics and selection:
    • The ‘more assembled’ an ensemble of objects, the more selection is required for it to come into existence.
    • Assembly physics includes an explicit arrow of time intrinsic to the structure of objects.
    • Early selection events lead to symmetry breaking along historically contingent paths.
  • Assembly in the real universe:
    • Objects in the real universe can only be built from existing parts, making the discovery of new objects historically contingent.
    • The rate of discovery of new objects is defined by the expansion rate, introducing a characteristic timescale.
  • Discovery and reproduction dynamics in assembly theory:
    • Discovery dynamics (τd) represents the time it takes to discover a new object in the assembly process.
    • Reproduction dynamics (τp) represents the time it takes to reproduce a specific object in the assembly process.
  • Impact of copy number on assembly dynamics:
    • For fast discovery and slow reproduction (τp/τd >> 1), the assembly space expands too quickly and objects have low copy numbers.
    • For fast reproduction and slow discovery (τp/τd << 1), resources are primarily consumed in producing copies of existing objects.
  • Conditions for selection and evolution to emerge:
    • Selection and evolution emerge in the transition regime where there is a small separation in the timescales of discovery and reproduction.
    • This regime is located between τd << τp and τd >> τp.
  • Integrating discovery and production kinetics:
    • Mass action kinetics can be used to describe the simultaneous dynamics of discovery and reproduction.
    • Assembly can be used to quantify the degree of selection and measure the production of selected objects over time.
  • Unifying selection across physics and biology:
    • Assembly theory provides a unified language for describing selection and generating novelty.
    • It quantifies the discovery and production of selected objects in a forward process described by mass action kinetics.
  • Implications for studying molecules:
    • Computing the assembly index is not necessary for molecules, as it can be probed directly experimentally with spectroscopy techniques.
    • The assembly index can provide information about the number of objects, their assembly index, and copy number as a function of time.
  • Advantages of assembly theory:
    • Assembly theory allows the quantification of selection and the generation of novelty in an ensemble of evolved objects.
    • It provides a framework to unify descriptions of selection across physics and biology.
  • Availability of data and research design:
    • All calculations were performed using Mathematica 13.
    • Mathematica Notebooks and the string assembly calculator used in the calculations are available on GitHub and Zenodo repositories.
  • Resource Competition and Community Structure:
    • Tilman, D. Resource Competition and Community Structure. (MPB-17) Vol. 17 (Princeton Univ. Press, 2020).
    • Elena, S. F., Cooper, V. S. & Lenski, R. E. Punctuated evolution caused by selection of rare beneficial mutations. Science 272, 1802–1804 (1996).
  • Power-law tail distributions and nonergodicity:
    • Lutz, E. Power-law tail distributions and nonergodicity. Phys. Rev. Lett. 93, 190602 (2004).The TAP equation: evaluating combinatorial innovation in biocosmology:
      • Cortês, M., Kauffman, S. A., Liddle, A. R. & Smolin, L. The TAP equation: evaluating combinatorial innovation in biocosmology. Preprint at http://arxiv.org/abs/2204.14115 (2023).
      • Fontana, W. & Buss, L. W. in Boundaries and Barriers (eds Casti, J. & Karlqvist, A.) 56–116 (Addison-Wesley, 1996).
      • Marshall, S. M., Murray, A. R. G. & Cronin, L. A probabilistic framework for identifying biosignatures using Pathway Complexity. Philos. Trans. R. Soc. Math. Phys. Eng. Sci. 375, 20160342 (2017).
  • Formalising the pathways to life using assembly spaces:
    • Marshall, S. M., Moore, D. G., Murray, A. R. G., Walker, S. I. & Cronin, L. Formalising the pathways to life using assembly spaces. Entropy 24, 884 (2022).
  • Exploring and mapping chemical space with molecular assembly trees:
    • Liu, Y. et al. Exploring and mapping chemical space with molecular assembly trees. Sci. Adv. 7, eabj2465 (2021).
  • Top-down causation and emergence: some comments on mechanisms:
    • Ellis, G. F. R. Top-down causation and emergence: some comments on mechanisms. Interface Focus 2, 126–140 (2012).
  • Multiple realizability as a design heuristic in biological engineering:
    • Koskinen, R. Multiple realizability as a design heuristic in biological engineering. Eur. J. Philos. Sci. 9, 15 (2019).
  • Identifying molecules as biosignatures with assembly theory and mass spectrometry:
    • Marshall, S. M. et al. Identifying molecules as biosignatures with assembly theory and mass spectrometry. Nat. Commun. 12, 3033 (2021).
  • Assembly theory explains and quantifies selection and evolution:
    • The article discusses the concept of assembly theory and its application in explaining and quantifying selection and evolution in biological systems.
    • It provides insights into the mechanisms by which organisms adapt and evolve in response to environmental changes.
  • Relevant supplementary information available:
    • Supplementary information containing details of the mathematical models, simulations, and examples used in the manuscript is provided.
    • It also includes supplementary sections, figures, and references that further support the main findings of the article.
    •  

    • Query – Applied to ITC

      Based on this theory, imagine that there is non-physical forms and energies in the universe that can assemble into entities that resemble biological forms in terms of action, consciousness, and communication. Designate some of those forms and energies, apply assembly theory to them, and describe them. Then, describe how physical beings might be able to communicate with them through technological means.

      Assembly Theory (AT), as described, concerns itself with the quantification and understanding of complexity in physical objects through their possible formation histories, assembly space, and the indices which measure selection and evolution. It applies to a wide variety of systems including, but not limited to, polymers, cell morphology, and chemical systems. However, AT, as it is described in the context provided, refers to physical objects and systems.

      Extending AT to non-physical forms and energies requires a theoretical stretch beyond its current scope since AT relies on the fundamental concept of objects being assembled from physical building blocks within the realms of physics and chemistry. Non-physical entities, by definition, do not interact with physical forces or components in a measurable way, rendering the core principles of AT inapplicable.

      However, if we were to imagine a hypothetical universe where non-physical forms and energies operate on principles analogous to physical assembly, we could conceptualize these entities using similar language provided by AT. Let’s designate these hypothetical non-physical forms as “Ethereal Assemblies” and the energies as “Spectral Forces”.

      Ethereal Assemblies could be characterized by an “Ethereal Assembly Index,” which measures the hypothetical complexity and history of their formation in non-physical space. Spectral Forces would equate to the fundamental interactions that govern the assembly and disassembly of Ethereal Assemblies. Both would exist in some kind of “Ethereal Assembly Space,” which represents all possible configurations and transformations of these non-physical forms and energies.

      Applying AT principles to these hypothetical constructs might look like this:

      • Ethereal Objects Definition:Non-physical entities are defined by their “Ethereal Formation Histories”, the sequence of steps taken to “assemble” them from their basic constituents within the Ethereal Assembly Space.
      • Quantifying Non-Physical Selection and Evolution:Ethereal Assembly Indices could be imagined to quantify the degree of selection and evolution, assuming there are analogous processes for non-physical forms that resemble biological selection.
      • Measuring Complexity:Ethereal complexities might be measured using an index similar to the assembly index, combined with a frequency or prevalence value similar to the copy number applied to non-physical entities.

      Since these Ethereal Assemblies are non-physical, conventional communication as we understand it would not be possible. However, if technological means were to be conceived, they would likely involve:

      Detection Instruments: Devices or sensors attuned to the existence and properties of non-physical forms of energy, perhaps through a hypothesized interaction with the physical world that we have yet to understand or detect.

      Translational Interfaces: Machines that could interpret changes in the non-physical assembly space and translate them into physical phenomena, such as electromagnetic signals, that could be understood by physical beings.

      Indirect Interference: Techniques that manipulate physical conditions in a way that is hypothesized to affect non-physical forms, perhaps by causing ripples in the Ethereal Assembly Space that Ethereal Assemblies could detect and respond to.

      The communication would be less direct and could involve a form of “translation” of intent, message, and response between physical and non-physical means. Pursuing such communication might involve a field akin to non-physical informatics, combining principles of theoretical physics, metaphysics, and information science.

      However, it’s crucial to recognize that this discussion is speculative and ventures into science fiction, as it surpasses the bounds of AT’s original domain that is rooted in observable and measurable physical phenomena.

      Query 2 – Applied to ITC

      Assume that quantum mechanics are a common property of physical and non physical space. In other words, ethereal space is comprised of quantum waves and/or particles. Please describe the detection, translation and communication between physical space and ethereal space.

      If we assume that both physical and ethereal spaces share properties of quantum mechanics, wherein ethereal space is also composed of some form of quantum waves and/or particles, it opens up intriguing possibilities. Let’s explore these in the context of detection, translation, and communication between physical and ethereal space.

      Detection: Quantum Entanglement and Superposition

      The prerequisite for detection would be identifying a shared quantum property or interaction that bridges both spaces. Quantum entanglement may serve as such a bridge, where a paired state in physical space could have a corresponding entangled state in ethereal space. Detecting a change in state in physical space could thus indicate a change in the ethereal counterpart.

      Similarly, superposition might allow an ethereal quantum state to influence or be influenced by a physical system. Precise quantum measurements in physical space might reveal interference patterns or probabilities influenced by ethereal states, even if the latter cannot be directly observed.

      Translation: Quantum Information Theory

      Translating between physical and ethereal quantum states would require a system operating under Quantum Information Theory. Quantum bits or qubits, unlike classical bits, can exist in multiple states simultaneously thanks to superposition. A qubit in ethereal space could be correlated with a qubit in physical space, serving as a translation mechanism. Data from ethereal qubits could then be “read” via their entangled counterparts in physical space.

      Changes in quantum states, detected through phenomena like wave function collapse or entanglement disentanglement, could provide information about events or conditions in ethereal space. The translation process would involve converting these quantum disturbances into classical information that can be interpreted by humans.

      Communication: Quantum Channels

      Communication might leverage something akin to quantum channels, which are used in quantum communication to transfer quantum states from one place to another. If ethereal quantum states can influence or be represented within physical quantum states, creating a sustained communication channel would require maintaining a controlled entangled state or sequence of states.

      Quantum teleportation, which can transmit quantum information over arbitrary distances, could be theoretically extended to ethereal space if quantum mechanics indeed apply there. Information about ethereal events or states could be encoded onto quantum states and “teleported” to physical space through a controlled entanglement.

      Potential Technologies for Interaction:

      • Quantum Sensors: These would be highly sensitive to the entanglement and superposition states indicative of interactions with ethereal particles or waves.
      • Quantum Computers: Could serve as an interface, manipulating and interpreting qubits that represent the entangled states spanning physical and ethereal spaces.
      • Quantum Repeaters: Like those proposed for long-distance quantum communication networks, could facilitate stronger and more reliable quantum links between the two spaces.

Challenges and Considerations:

  • Decoherence: Quantum states are extremely fragile, and interactions with the environment lead to decoherence, which would be a significant challenge in maintaining a stable communication link.
  • Controlled Entanglement: Creating and maintaining a stable, controlled entanglement between physical and ethereal quantum states would require overcoming unknowns about how ethereal quantum mechanics operate.

This elaboration still remains within the theoretical and speculative domain since our understanding of quantum mechanics in the context of non-physical spaces is purely hypothetical. In practice, working within such a framework would entail pioneering new physics and advanced technologies that are currently beyond our capability. Nevertheless, a common quantum mechanical foundation does provide a tantalizing framework for hypothesizing about potentially universal principles that might apply across vastly different realms of existence.

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