Espartaco

“Is that to say we are against Free Trade? No, we are for Free Trade, because by Free Trade all economical laws, with their most astounding contradictions, will act upon a larger scale, upon the territory of the whole earth; and because from the uniting of all these contradictions in a single group, where they will stand face to face, will result the struggle which will itself eventuate in the emancipation of the proletariat.”

Karl Heinrich Marx · Marx-Engels Collected Works, Vol. VI, p. 290

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Tag: Ecuación de Schrödinger

  • A DIALECTICAL MATERIALIST ANALYSIS ON PATH DEPENDENCE, IRREVERSIBILITY AND TELEOLOGY IN PHYSICAL SYSTEMS

    A DIALECTICAL MATERIALIST ANALYSIS ON PATH DEPENDENCE, IRREVERSIBILITY AND TELEOLOGY IN PHYSICAL SYSTEMS

    Why Broken Eggs Don’t Unbreak — A New Physics of History, Direction, and Purpose
    Physics • Philosophy • Foundations

    Why Broken Eggs Don’t Unbreak

    A philosopher argues that history, not mechanics, is the deepest grammar of the physical world — and that matter itself pursues stability.

    Based on a paper by José Mauricio Gómez Julián ~9 min read

    Why does a broken egg never reassemble itself? Every law governing the motion of its atoms is perfectly reversible — run the film backward and nothing in the mathematics complains. And yet, in the real world, broken eggs stay broken. This gap between what our equations allow and what nature actually does has haunted physics for over a century. A new paper from the University of Costa Rica proposes an answer that is as philosophically bold as it is mathematically precise.

    The Paradox That Won’t Go Away

    In the 1870s, the Austrian physicist Josef Loschmidt challenged Ludwig Boltzmann’s statistical explanation of the second law of thermodynamics. His objection was devastatingly simple: if the equations of motion work the same forwards and backwards in time, how can entropy — disorder — only ever increase? This is Loschmidt’s paradox, and it sits at the intersection of thermodynamics, quantum mechanics, and the philosophy of science.

    Physicists have proposed many partial answers. Some invoke the statistical improbability of reversal (there are astronomically more disordered states than ordered ones). Others appeal to cosmological boundary conditions — the universe simply started in a very special, low-entropy state. More recent work, cited in this paper, turns to information theory and Landauer’s principle (the idea that erasing information has a minimum physical cost).

    But the author — José Mauricio Gómez Julián, writing from the University of Costa Rica — finds all of these solutions insufficient. His central claim is provocative: the paradox is not in nature. It is in our models. We build theories that are fundamentally ahistorical, then act surprised when the real world — which is fundamentally historical — doesn’t obey them. The problem, he argues, is not that reality misbehaves. It is that our theories refuse to remember.

    The Core Move

    Instead of asking “Why is the macroscopic world irreversible?”, the paper reframes the question entirely: “Why do we insist on building reversible models and then call irreversibility a paradox?”

    The Philosophical Engine: Dialectical Materialism

    The paper is grounded in dialectical materialism — a philosophical tradition rooted in Marx and Engels, developed further by Hegel (in its idealist form) and by Soviet physicists like Blokhintsev and Rosental. If that sounds unusual for a physics paper, the author would say: that’s exactly the point.

    Dialectical materialism holds that reality is made of matter in motion, that contradictions are not flaws in our thinking but features of the world, and that quantitative changes eventually produce qualitative leaps. It also insists on a distinction that modern physics has muddled:

    • Epistemology — what we can know and measure (our limitations as observers).
    • Ontology — what actually exists in the world, regardless of our ability to observe it.

    This distinction turns out to be the paper’s sharpest tool. When quantum mechanics says that a particle’s position is “uncertain,” the author asks: is that uncertainty a feature of reality (ontology), or a feature of our knowledge (epistemology)? His answer is nuanced and consequential. The Schrödinger equation itself is fully deterministic — give it an initial state and a Hamiltonian, and it will predict the future wave function with perfect precision. The randomness enters only when we try to measure — when the quantum system meets our macroscopic instruments.

    In other words, probability in quantum mechanics is an epistemological resource — a powerful tool for managing complexity and incomplete knowledge — not a statement that reality itself is fundamentally random. This does not mean quantum mechanics is wrong. It means that its probabilistic character tells us about us, not about the universe.

    The author is careful, however, to distinguish this from classical Laplacian determinism. Heisenberg’s uncertainty principle, he argues, is ontological — it reflects genuine structural features of reality (the complementarity between position and momentum). So the world is deterministic in a deep sense, but not in the naive clockwork sense. It is deterministic in the way a complex, path-dependent system is deterministic: constrained, structured, lawful — but too intricate for any observer to fully predict.

    When the terrain disagrees with the map, trust the terrain

    Path Dependence: History Before Time

    Here is where the paper makes its most original conceptual move. The author argues that path dependence is more fundamental than time itself.

    What does this mean? In complex systems — economies, ecosystems, living organisms — the current state depends not just on the present conditions but on the entire sequence of events that led there. An economy with the same GDP, population, and technology as another can behave very differently because its institutions, crises, and policy choices followed a different historical path. The paper claims this is not just a feature of complex systems. It is a feature of all physical reality, at every scale.

    In this framework, time is reimagined. It is not a background parameter through which things happen (as in Newtonian mechanics), nor a dimension woven into spacetime (as in relativity), but rather a structure that records material transformations — a kind of universal memory. Space and time co-emerge as the necessary fabric for matter to develop and preserve its evolutionary trajectory.

    The author traces this insight back to Hegel’s philosophy of nature (published decades before Einstein’s relativity), where place, space, and time are understood as a unity — and where motion (and therefore matter) arises from their contradiction. The passage is striking:

    Place is spatial singularity… This perishing and regenerating of space in time and of time in space… is movement. This becoming… is the immediate, identical and existing unity of space and time: it is matter.
    — Hegel, Encyclopaedia of the Philosophical Sciences

    If path dependence is fundamental, then irreversibility is not something to be explained — it is something to be assumed, just as mathematicians assume the existence of natural numbers rather than proving it. Every broken egg, every aging star, every evolved species is evidence that the universe remembers its own history.

    A New Equation for a Remembering Universe

    The author doesn’t stop at philosophy. He proposes a concrete mathematical reformulation of the Schrödinger equation — the foundational equation of quantum mechanics — to make path dependence explicit.

    Standard quantum mechanics writes:

    Standard Form

    iℏ ∂ψ/∂t = Ĥ ψ

    where the Hamiltonian Ĥ describes the system’s energy at a given instant.

    The paper’s reformulation introduces a history-dependent Hamiltonian:

    Path-Dependent Form

    iℏ ∂ψ/∂t = Ĥ(t) ψ

    where Ĥ(t) = Ĥ₀ + ∫ K(t, t′) ψ(t′) dt′

    Here, t is not clock time but an interaction index — an ordering of how physical interactions emerged. The kernel K(t, t′) encodes how every prior interaction influences the current one.

    This is a bold move. It says: the state of a quantum system at any moment is shaped by the entire chain of interactions that brought it there — not just by its instantaneous configuration. The author also defines a metric on this “interaction space,” capturing the distance between interactions in terms of both complexity and energy change, and proves it satisfies the standard properties of a mathematical metric (nonnegativity, symmetry, triangle inequality).

    The elegance of this formulation is that it reproduces known physics as special cases:

    • Classical regime (low energy, macroscopic): the metric reduces to ordinary Euclidean geometry.
    • Relativistic regime (high velocity): it reproduces the Minkowski spacetime interval.
    • Quantum regime (entanglement, superposition): the metric captures quantum correlations through entanglement entropy.

    Entanglement Without Spookiness

    The path-dependent framework also offers a fresh take on quantum entanglement — Einstein’s famous “spooky action at a distance.” In the standard picture, measuring one entangled particle seems to instantaneously affect its partner, no matter how far away. In the author’s framework, entangled particles don’t communicate across space. They share a common interaction history. They are “close” in interaction space even when they are far apart in physical space — much like two points on a folded piece of paper that look distant but are actually adjacent when the paper is unfolded.

    Bell’s theorem — which proved that no local realistic theory can reproduce all quantum predictions — is not violated but reinterpreted: the “nonlocality” is real in emergent spacetime but disappears when you consider the deeper interaction space. Locality is preserved at the fundamental level; it only appears broken in the effective spacetime we observe.

    Why Does Matter Seek Stability?

    IV

    The paper’s second major argument is about teleology — the idea that natural processes are directed toward ends or purposes. This is a concept that modern science has largely banished (with some notable exceptions in biology). The author argues it should be restored — but in a materialist, not a mystical, form.

    The claim: physical systems universally tend toward maximum achievable stability within their material constraints. This is not an external force or an intelligent design. It is an inherent property of matter itself, arising from the internal contradictions within material systems.

    The evidence spans every scale of reality:

    • Cosmological: The universe’s laws appear “fine-tuned” for structure and complexity. Cyclic cosmological models suggest a drive to preserve laws conducive to stability.
    • Stellar: Stars burn through nuclear fuel, then transform — into white dwarfs, neutron stars, or supernovae — each outcome representing a reorganization toward the next achievable stable state.
    • Chemical: The pressure-induced transformation of graphite to diamond. Autocatalytic systems that reorganize when reactants deplete.
    • Biological: DNA’s role as a stable transcription template. Gould’s punctuated equilibria — long periods of stasis followed by rapid change. Insect metamorphosis.
    • Neural: The brain reorganizing through neuroplasticity after injury or during learning.
    • Social: Revolutions occurring when existing structures of production become incompatible with productive forces.

    In each case, the pattern is the same: systems seek stability, achieve it temporarily, exhaust the conditions that made it possible, undergo a qualitative transformation, and resume the search in a new configuration. Stability is the attractor; transformation is the mechanism.

    Least Action and Ground States

    The author connects this teleological perspective to two pillars of physics:

    The principle of least action — the mathematical rule that physical systems follow paths that extremize (usually minimize) the “action” functional. This is usually treated as a computational tool. The paper reinterprets it as a teleological law: systems select trajectories in service of their drive toward stability, and the path of least action is the one that best serves this purpose. Sometimes, the system does not take the absolute minimum energy path — because the absolute minimum may not serve the broader goal of sustained stability.

    The ground state tendency — quantum systems’ natural inclination to settle into their lowest energy configuration. The author, drawing on Solovej’s work on the stability of matter, argues this is not merely a mechanical outcome but an expression of matter’s fundamental need for stabilization. Electrons don’t “accidentally” fall into lower energy levels. They are driven there by the internal logic of material reality.

    Key Insight

    Teleology here is not purpose in the human sense — no intentions, no intelligence. It is the tendency of matter to resolve its own internal contradictions by seeking the most stable configuration available. Purpose arises from the inherent contradictions of matter, not from any external guide.

    The Arrow of Time, Revisited

    With path dependence as the foundation, the arrow of time becomes almost trivial to explain. Time flows in one direction because systems are historical. The future depends not only on the present state but on the entire trajectory that led to it. Irreversibility is not a statistical accident or a cosmological boundary condition — it is a structural feature of reality, as basic as the existence of natural numbers in mathematics.

    The author draws an analogy to the Cosmic Microwave Background (CMB) — the faint radiation left over from the early universe, which provides a natural “preferred frame” for cosmic observations without violating relativity. Similarly, the paper proposes that a preferred temporal direction can emerge from path dependence without requiring absolute time. Each observer may have their own “proper time,” but the causal structure — the chain of dependencies — is invariant and objective across all reference frames.

    This bridges a gap between quantum mechanics and general relativity. Quantum theory works with a notion of time closer to the classical (absolute) picture, while relativity treats time as relative and observer-dependent. The path-dependence framework offers a way to reconcile both: the ordering of interactions is fundamental and observer-independent; the measurement of time is relative.

    Testable Predictions

    The paper does not remain in the realm of philosophy. It proposes four concrete experimental protocols:

    • Decoherence studies: Prepare identical quantum systems, give them different interaction histories, and measure whether their decoherence rates differ. The paper predicts they will.
    • Entanglement analysis: Generate entangled photon pairs, expose them to different interaction histories, and check whether entanglement strength decays exponentially with “interaction distance” as the metric predicts.
    • Modified double-slit experiment: Introduce controlled interaction histories before particles reach the slits and look for history-dependent deviations in the interference pattern.
    • Time emergence clocks: Prepare identical atomic clocks with different interaction histories and compare their temporal evolution rates.

    These are technically demanding experiments — requiring millikelvin temperatures, ultra-high vacuum, single-photon detection, and high-fidelity quantum tomography — but they are within reach of current laboratory capabilities. The predictions are specific enough to be falsified, which is exactly what good science requires.

    Why This Matters Beyond Physics

    FOR THE NON-PHYSICIST

    If you are an economist, a political scientist, or simply someone who thinks about how societies change, this paper’s conceptual framework should feel familiar — and provocative.

    The concept of path dependence is already central to institutional economics (think of Douglass North or Paul David’s QWERTY keyboard). The idea that history matters — that you cannot understand a system’s current state without knowing how it got there — is a staple of comparative politics and historical sociology. What this paper does is argue that path dependence is not just a useful metaphor borrowed from physics. It is a fundamental feature of physical reality itself.

    Similarly, the paper’s concept of teleology without intention — systems pursuing stability through the internal logic of their own contradictions — resonates powerfully with Marx’s theory of historical materialism, where modes of production develop, exhaust their potential, and undergo revolutionary transformation. The author draws this connection explicitly, noting that revolutions occur “when existing relations of production become incompatible with developing productive forces.”

    And the distinction between epistemology and ontology — between what we can model and what actually exists — is a question every social scientist should take seriously. When our econometric models fail to predict a financial crisis, is the crisis a “black swan” (an anomaly), or is it evidence that our models are too ahistorical to capture reality?

    The problem is not that reality “contradicts” theory but that theory is a limited abstraction of reality, creating tension when attempting to make reality fit the model instead of developing models that capture reality’s historical-contextual nature.
    — José Mauricio Gómez Julián

    A Bridge Between Worlds

    This is not a paper that will convince everyone. Its philosophical framework — dialectical materialism — is unfamiliar and, for some, politically charged. Its mathematical proposals, while rigorous, are exploratory and await experimental confirmation. Its claim that teleology is a fundamental feature of matter will strike many physicists as a step backward toward pre-modern thinking.

    But that is precisely what makes it worth reading. In a landscape where theoretical physics has fragmented into string theory, loop quantum gravity, and various interpretations of quantum mechanics that all reproduce the same experimental results, a paper that asks “What if we’re starting from the wrong assumptions?” is exactly the kind of provocation that science needs.

    The paper’s deepest contribution may be methodological: a demonstration that philosophy and physics can inform each other without either colonizing the other. The philosophical framework provides the conceptual clarity to ask better questions. The physics provides the experimental discipline to test whether those questions have real answers.

    Whether or not its specific proposals survive experimental scrutiny, the paper succeeds in something more modest but no less important: it makes you see the broken egg differently. Not as a problem to be explained away, but as evidence of a universe that remembers — and that, in remembering, moves irreversibly forward.

    Original paper: “A Dialectical Materialist Analysis on Path Dependence, Irreversibility and Teleology in Physical Systems” by José Mauricio Gómez Julián, University of Costa Rica.

    Available as a preprint: OSF Preprints

    This post is an explanatory summary and does not represent the views of the author or any institution. Errors in interpretation are the blogger’s own.

  • Outlining a Dialectical Hypothesis On The C-Value Paradox In The Light of Quantum Chemistry

    Outlining a Dialectical Hypothesis On The C-Value Paradox In The Light of Quantum Chemistry

    Why an Amoeba Has 200 Times More DNA Than You — A Philosophical Take on the C-Value Paradox
    Explainers · Philosophy of Science · Molecular Biology

    The C-Value Paradox:

    Why an Amoeba Has 200 Times More DNA Than You?

    A philosopher argues that the way we count genes is broken — and proposes a dialectical, quantum-informed fix.

    Blog Post 2025
    ~ 9 min read

    Imagine you are handed two books. One is a slim novella; the other is an encyclopedia the size of a suitcase. Intuitively, you’d guess the encyclopedia contains more information. Now imagine that the novella turns out to encode the instructions for building an entire human being, while the suitcase-sized volume merely describes how to be a single-celled amoeba. Welcome to the C-value paradox — one of the most stubborn puzzles in modern biology — and to a recent paper that proposes a genuinely unusual way of thinking about it.

    The article in question is “Outlining a Dialectical Hypothesis on the C-Value Paradox in the Light of Quantum Chemistry” by the philosopher José Mauricio Gómez Julián, published in the Pitt Philosophy of Science archive (available here). It is not a typical biology paper. It moves fluidly between Hegelian logic, quantum mechanics, selfish genetic elements, and the mathematics of how we measure sets. If that sounds intimidating, don’t worry: by the end of this post, you’ll see why the argument matters — even if you’ve never opened a biology textbook.

    1. The Puzzle: More DNA, But Not More Complexity

    Let’s start with the basics. Every living cell carries a complete copy of the organism’s DNA — its genome. Biologists measure genome size in base pairs (bp) or, for convenience, in megabases (Mb), where 1 Mb = one million base pairs. This measurement is called the C-value.

    In prokaryotes (bacteria and archaea — the simplest forms of life, without a cell nucleus), the relationship is fairly intuitive: bigger genome, more genes, somewhat more complex organism. But when we turn to eukaryotes (everything from yeast to humans, with cells that contain a nucleus), the intuition collapses.

    A Few Striking Numbers
    Organism Genome Size (Mb) Gene Count (approx.)
    Yeast12~6,000
    Fruit fly180~14,000
    Human3,400~20,000–25,000
    Onion18,000
    Amoeba (A. dubia)686,000

    Sources: Latorre & Silva (2013); Pray (2022).

    A single-celled amoeba carries roughly 200 times more DNA than a human being. An onion needs about five times more DNA than we do. Amphibians, as a group, show genome-size variations of up to 91-fold. As the paper notes, citing Latorre and Silva, “it is hard to believe that this may reflect variations of nearly 100 times the number of genes necessary to give rise to the corresponding amphibians.”

    Nor is it simply a matter of how many genes there are. Even the raw count of protein-coding genes doesn’t track complexity well: a pufferfish has roughly the same number as a human (~35,000), and the rice plant has more (~51,000). The disconnect between genome size, gene number, and organismal complexity is the C-value paradox.

    2. Why Should Anyone Outside Biology Care?

    If you’re an economist, a political scientist, or a mathematician, you might be wondering what amoebae have to do with your work. The answer lies not in the biological details but in the type of reasoning the paper employs. Gómez Julián is making an argument about how we measure complexity — and specifically, why our standard tools for counting and measuring break down when the system we’re studying is fundamentally nonlinear.

    This is a problem that recurs everywhere: in financial markets (where small shocks cascade unpredictably), in political systems (where a single event can reshape an entire order), and in ecology (where species interact in webs, not chains). The C-value paradox is, at its core, a case study of what happens when you try to impose a linear accounting framework on a nonlinear reality.

    3. The Philosophy: What Does “Dialectical” Mean Here?

    The paper’s philosophical backbone comes from dialectical materialism — a tradition rooted in Hegel and adapted by Marx, Engels, and later Soviet philosophers. For readers unfamiliar with the term, here is the essence in plain language:

    Things are not only what they are in terms of their current state of development, but also their potential.

    In this framework, reality is a totality: not just what currently exists, but what could exist, what is coming into being, and what is being annihilated. The concept of “contradiction” is central — but not in the colloquial sense of a logical error. A dialectical contradiction means that any complex thing contains opposing developmental tendencies that are simultaneously complementary and mutually exclusive. These tendencies can be nonantagonistic (stable, coexisting) or antagonistic (destabilizing, eventually forcing the system to transform into something qualitatively new).

    Gómez Julián draws an explicit parallel between this philosophical notion and Bohr’s complementarity principle in quantum mechanics: to understand a quantum phenomenon fully, you need both the wave description and the particle description, even though they are mutually exclusive. The paper argues that this isn’t merely an analogy — it reflects a deeper logical structure shared across physics, chemistry, and biology.

    For those with an economics background, the parallel to dialectical reasoning in political economy is direct. Just as a commodity is simultaneously a use-value and an exchange-value — and you cannot understand the commodity by examining only one aspect — so a gene is simultaneously a physical structure (DNA sequence) and a functional agent (information carrier, regulatory element, or “selfish” replicator). Reducing it to just one dimension is precisely what creates the paradox.

    4. The Mathematical Core: Why Linear Counting Fails

    Now we arrive at what will interest the mathematicians and econometricians. The paper makes a precise mathematical claim: the tools we use to count genes assume linearity, but the genetic system is nonlinear.

    Formally, a function φ is called sigma-additive (or countably additive) if the measure of a union of disjoint sets equals the sum of the measures of each set. This is the standard foundation of probability theory and measure theory — the Kolmogorov axioms that every statistician and econometrician relies on.

    A subadditive function, by contrast, only requires that the measure of the union be less than or equal to the sum of the parts. Additive functions are a special case of subadditive ones. In genetics, if you use an additive model, you are assuming a perfect linear relationship between the number of allele copies and the organism’s traits — no dominance, no interaction, no epistasis. As Huang and Mackay (2016) showed, this assumption is empirically inadequate for most quantitative traits.

    Gómez Julián’s argument is that counting genes with sigma-additive functions implicitly treats the genome as a linear system: more genes = proportionally more complexity. But the evidence shows this is false. The complexity emerges from how genes interact, not from how many there are. Therefore, the counting function itself must change.

    5. What Actually Generates Complexity? Eight Factors

    The paper proposes that any meaningful relationship between gene count and organismal complexity must account for eight key aspects of the underlying molecular processes. Here they are, translated into plain terms:

    1. What kind of information is encoded? — Not all genes carry the same type of instruction. Some code for structural proteins; others regulate when and where those proteins are made.
    2. What encoding system is used? — The “language” of the genome is not uniform; different regions operate under different coding rules.
    3. Should we weight protein-coding genes more heavily? — Protein-coding genes make up only about 1.5% of the human genome. Should the other 98.5% count equally?
    4. What type of transcription occurs? — Through alternative splicing, a single gene can produce multiple different proteins. Humans may produce over 500,000 distinct proteins from only ~20,000 genes. The process is not one-to-one.
    5. DNA is a nonlinear dynamical system. — The double helix doesn’t behave like a simple linear chain. Researchers have modeled it using nonlinear Hamiltonians since at least the 1980s, and solitary conformational waves (solitons) can propagate along the strand.
    6. What type of gene is involved? — There are protein-coding genes, RNA genes, regulatory sequences, transposable elements, and more. They don’t all contribute to “complexity” in the same way.
    7. What role do “negative genes” play? — This is one of the paper’s most distinctive contributions. Gómez Julián renames so-called “selfish genes” as “negative genes” — borrowing the concept of negativity from dialectical philosophy. These are genetic elements (like transposons) that replicate for their own benefit, even if they are harmful or neutral to the organism. They exist in a state of unity and struggle with the organism’s “ordinary” genes, and this conflict is, according to Werren (2011), “an important driver of evolutionary change and innovation.”
    8. What happens during and around transcription? — This is when the DNA double helix unwinds and single strands are exposed. It is the moment of maximum vulnerability and maximum creative potential: DNA editing, trans-splicing, and tandem chimerism all occur here. The source of nonlinear complexity, the paper argues, is concentrated in this phase.

    If these eight factors could be incorporated into a new kind of counting function — one that captures nonlinear interactions, gene regulation, and the dialectical interplay between “positive” and “negative” genes — the paradox might dissolve. Genome size and gene number would, at least approximately, map onto organismal complexity.

    6. Quantum Chemistry Enters the Picture

    You might wonder: where does quantum mechanics fit into all of this? The paper’s answer is that the covalent bonds holding DNA together are quantum-mechanical phenomena. As early as the 1920s, Heitler and London showed that covalent bonds can be understood through the Schrödinger equation. The nucleotides in each DNA strand are linked by strong covalent bonds, so the strand’s dynamics — its rigidity, its unwinding, its conformational changes — are ultimately governed by quantum mechanics.

    In practice, solving the full Schrödinger equation for a molecule as large as DNA is computationally staggering. But progress is being made. The paper points to three recent advances:

    Computational Progress

    Analytical and numerical solutions of the Peyrard-Bishop DNA model (a nonlinear model of DNA dynamics) now show strong convergence (Al et al., 2020). Kink and localized solutions for the helicoidal version of the same model have been found and could serve as tools for modeling DNA-to-RNA transcription (Zdravković et al., 2019). And quantum annealing has been applied to de novo genome assembly — solving the combinatorial problem of stitching DNA fragments together using quantum and quantum-inspired optimization (Boev et al., 2021).

    These are early steps, but they suggest that the computational barriers to modeling DNA as a quantum-mechanical, nonlinear system are not permanent. Quantum computing may eventually make the Schrödinger-based analysis of large molecules feasible.

    7. The Bigger Picture: A Self-Teaching Universe

    At this point, the paper makes its most ambitious philosophical move. Drawing on research by Alexander et al. (2021), Gómez Julián describes a universe that is self-organized, deterministic, historically determined, and autodidactic — one that “evolves learning in an autodidactic way its own laws,” applying a process physically equivalent to biological natural selection at a cosmological scale. The universe, in this view, is a system that adds new nonlinearities to itself over time — a kind of spontaneous increase in complexity.

    This is linked to the concept of emergence: the spontaneous appearance of new information (new structures, new behaviors) as a result of a system’s internal dynamics. The laws of physics may themselves be subject to higher-order laws, just as a logic of a certain order is subject to the rules of a higher-order logic.

    For the C-value paradox, the implication is this: you cannot understand the parts (genes) without understanding the whole (the organism and its evolutionary history), and you cannot understand the whole without understanding how it emerged from the parts. The truth, as Hegel would say, is in the totality.

    · · ·

    8. So What Would a Solution Actually Look Like?

    Gómez Julián is careful to say that his paper is a guide, not a solution. He proposes the construction of a “paradox-free gene counting function” (PFGCF) — a new mathematical object that would replace simple sigma-additive counting with something capable of capturing:

    • Nonlinear gene interactions
    • The role of alternative splicing and regulatory elements
    • The dialectical interplay between ordinary genes and “negative” (selfish) genes
    • Quantum-mechanical properties of DNA structure
    • What happens during and around transcription

    This function might not even be a single function at all, but rather a family of functions, each capturing different aspects of genomic complexity. The construction will require, the paper argues, “philosophers, chemists, geneticists, and physicists, as well as the use of high-capacity computational equipment.”

    It is, in the author’s own words, a “legitimate speculation” — grounded in established science but not yet experimentally verified. The value of the paper lies in its identification of which factors matter and what kind of mathematics is needed, rather than in providing a finished model.

    9. Why This Paper Matters (Even If You’re Not a Biologist)

    Let’s return to the question of why a non-biologist should care. Here are three reasons:

    The whole is more than the sum of its parts — and the tools we use to count the parts must reflect that.

    First, the paper is a case study in interdisciplinary thinking. It weaves together philosophy, mathematics, chemistry, and biology in a way that is rare in any field. Whether or not you agree with its dialectical-materialist framework, the attempt to build a bridge between Hegel and quantum chemistry is intellectually stimulating.

    Second, it highlights a general methodological problem: when linear tools fail, what replaces them? Economists face this when GDP doesn’t capture well-being; political scientists face it when vote counts don’t capture democratic health; mathematicians face it whenever measure theory meets real-world complexity. The paper’s call for new counting functions is, at bottom, a call for new mathematics.

    Third, it reminds us that paradoxes are productive. The C-value paradox has been around for decades and hasn’t been solved — but it has forced biologists to discover alternative splicing, transposable elements, non-coding RNA, and epigenetic regulation. The paradox was never a dead end; it was a signpost pointing toward deeper truths. That’s a lesson every discipline can take to heart.

    · · ·

    You can read the full paper by José Mauricio Gómez Julián at the PhilSci Archive: https://philsci-archive.pitt.edu/24513/