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Standard Formalization

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Abstract

A standard formalization of a scientific theory is a system of axioms for that theory in a first-order language (possibly many-sorted; possibly with the membership primitive \(\in\)). Suppes (in: Carvallo M (ed) Nature, cognition and system II. Kluwer, Dordrecht, 1992) expressed skepticism about whether there is a “simple or elegant method” for presenting mathematicized scientific theories in such a standard formalization, because they “assume a great deal of mathematics as part of their substructure”. The major difficulties amount to these. First, as the theories of interest are mathematicized, one must specify the underlying applied mathematics base theory, which the physical axioms live on top of. Second, such theories are typically geometric, concerning quantities or trajectories in space/time: so, one must specify the underlying physical geometry. Third, the differential equations involved generally refer to coordinate representations of these physical quantities with respect to some implicit coordinate chart, not to the original quantities. These issues may be resolved. Once this is done, constructing standard formalizations is not so difficult—at least for the theories where the mathematics has been worked out rigorously. Here we give what may be claimed to be a simple and elegant means of doing that. This is for mathematicized scientific theories comprising differential equations for \(\mathbb{R}\)-valued quantities Q (that is, scalar fields), defined on n (“spatial” or “temporal”) dimensions, taken to be isomorphic to the usual Euclidean space \(\mathbb{R}^n\). For illustration, I give standard (in a sense, “text-book”) formalizations: for the simple harmonic oscillator equation in one-dimension and for the Laplace equation in two dimensions.

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Notes

  1. There is a vast literature on differential equations in mathematical physics. Classics are Sommerfeld (1964), Courant and Hilbert (1924) and Jeffreys and Jeffreys (1966), and Arnold (1989). There are many standard undergraduate level texts, which I would recommend: e.g, Arfken and Weber (2005) for physicists and Olver (2014) for mathematicians. There exist very good advanced undergraduate/graduate level texts which develop the framework of differential geometry: e.g., Schutz (1980); and the quite advanced Frankel (2011). Additionally, there are “differential equation solvers” for software packages (e.g., Matlab, Mathematica and R). I use one of these below in Sect. 7.2 to compare an analytic solution of Laplace’s equation to a numerically integrated one. The interested reader who knows R programming might consult the book Soetaert et al. (2012).

  2. Nice explanations of differential geometry may be found in, say, Schutz (1980), Wald (1984), Frankel (2011), or Robin and Salamon (2012).

  3. Epistemologically, perhaps not so trivial, I need to add: as, in their own ways, Hume, Popper, Hempel and Goodman have all pointed out.

  4. Here I use type/sort notation: \((\forall x: \mathbb{R})\). It’s equivalent to \((\forall x \in \mathbb{R})\).

  5. On the usual reduction of reals to sets, each real lives inside \(V_{\omega +1}\) (which is, more or less, \(\mathcal{P}( \mathbb{N})\)), where the \(V_{\alpha }\)’s are “the von Neumann levels” in the hierarchy of pure (well-founded) sets. \(V_0\) is defined to be \(\varnothing\); and, for any ordinal \(\alpha\), \(V_{\alpha + 1}\) is defined to be \(P(V_{\alpha })\) (i.e., the power set of \(V_{\alpha }\)); and, if \(\lambda\) is a limit ordinal (i.e., \(\lambda\) is not equal to \(\alpha + 1\), for any ordinal \(\alpha\)), then \(V_{\lambda }\) is defined to be the union of all the \(V_{\alpha }\)’s with \(\alpha < \lambda\). This is the definition of the von Neumann hierarchy. It is analogous to defining the factorial function by, \(F(0) = 1\) and \(F(n+1) = (n+1)F(n)\), except that it uses ordinals instead of numbers and it has a special “infinity clause”. So, since \(\omega\) is the smallest infinite ordinal, \(V_{\omega }\) is the smallest infinite level: it is the set of all well-founded finite pure sets. From the definition, \(V_{\omega +1}\) is \(P(V_{\omega })\). There are several ways to encode \(\mathbb{N}\) into \(V_{\omega }\) (including a bijective way, called the Ackermann encoding; computer scientists call it the BIT predicate). And there are ways to encode each real number as a subset \(X \subseteq \mathbb{N}\), and conversely too, and indeed bijectively. So, one can think of \(V_{\omega +1}\) as (encoding) the set of reals. Each function \(F: \mathbb{R}\rightarrow \mathbb{R}\) lives inside \(V_{\omega +2}\); and thus a class of such functions lives inside \(V_{\omega + 3}\). Somewhat loosely speaking, the arena of almost all theoretical physics—the function spaces, Lie groups & algebras, topological spaces, manifolds, distribution spaces, bundles, etc.—is \(V_{\omega + n}\), for some smallish n. This material is explained in a set theory textbook, such as Jech (2002), Potter (2004), or Enderton (1977).

  6. A sketch of the construction of the formula \(\Phi _{\text{C}^2( \mathbb{R})}(F)\) is given below, in Sect. 5, Example 3.

  7. In data science, to “smooth” a dataset (usually a time series), one interpolates a smooth curve between the datapoints, usually not lying on those points, but rather averages. For example, the usual visualizations for the global temperature time series are smoothed using a moving average. A “low pass filter” is also a special kind of smoothing function (which eliminates high frequencies). Likewise, image processing filters.

  8. A real-valued Bessel function (on the reals) is a function \(F: \mathbb{R}\rightarrow \mathbb{R}\) satisfying:

    $$\begin{aligned} x^{2}{\frac{d^{2}F}{dx^{2}}}+x{\frac{dF}{dx}}+\left( x^{2}-\alpha ^{2}\right) F=0 \end{aligned}$$
    (19)

    for some constant \(\alpha\). Such functions turn up in many applications involving waves.

  9. Feynman’s puzzle here corresponds to what Hartry Field calls “Heavy Duty Platonism”. See Field (1989): 186–200. The rejection of Heavy Duty Platonism plays a central role also in Field’s main anti-nominalist arguments in Field (1980). See also Knowles (2015) for a recent discussion of this. Knowles defines it as “the view that physical magnitudes, such as mass and temperature, are cases of physical objects being related to numbers”.

  10. I allude here to the Quine–Putnam Indispensability Argument (see Colyvan (2019)). Quine’s views on this are scattered across several decades (e.g., Quine (1948, 1986)). Putnam’s canonical formulations are given in Putnam (1971, 1975).

  11. For details, see, for example, Bennett (1995), Theorem 1, p. 72.

  12. I must stress that the claim that the points of space do indeed carry such relations is an approximation. Yet it holds to an extremely good approximation.

  13. The reason for this is that when \(\mathsf{PA}_2\) is treated as a two-sorted first-order theory, one may use The Completeness Theorem—Henkin’s Completeness Theorem (Henkin 1950)—to transfer between model-theoretic and proof-theoretic results.

  14. See, e.g., Halbach (2014) or Cieśliński (2017).

  15. I have seen it remarked that a formalized theory, in particular for scientific theories, must always be stated directly in machine code. This is incorrect. The requirement is only that it uses predicates and function symbols which are definable. Axioms “higher-up”, so to speak, are stated using these defined predicates. \(\textsf{CT}1\)-\(\textsf{CT}4\) above are examples. But there are many others, well-known in mathematical logic.

  16. One example is the following: Georg Kreisel conjectured that if there is some fixed k such that, for all \(n \in \mathbb{N}\), \(\mathsf{PA}\) proves \(\phi (S^n(0))\) in at most k steps, then \(\mathsf{PA}\) proves \(\forall x \phi (x)\). Does Kreisel’s Conjecture (KC) hold for Peano arithmetic? It turns out to be implementation dependent. Parikh (1973) showed that KC holds for an implementation called \(\mathsf{PA}^{*}\), where the function symbols \(+\), \(\cdot\) are replaced by appropriate predicates, say, A(xyz) and M(xyz), with suitable axioms stating existence and uniqueness. The proof of this is quite difficult. But, cleverly choosing \(\phi (x)\), it is easy to give a formulation \(\mathsf{PA}^{\phi }\) of \(\mathsf{PA}\), in the same language \(L(0,S,+, \cdot )\) and with the same theorems as standard \(\mathsf{PA}\), such that KC does not hold. See Cavagnetto (2009), Proposition 1.2 (we choose \(\phi (x)\) to be any formula witnessing \(\omega\)-incompleteness).

  17. The theories of Russell and Zermelo included atoms (Zermelo (1908), Russell (1903), Russell (1908)) as did Church’s type theory (Church 1940). Recent examples are: Mendelson (2010) (§4.6.5); Jech (2002) (p. 250 ff.); Potter (2004). A detailed exposition of many-sorted logic appears in Manzano (1996) and recent applications to questions concerning theory formalization in Halvorson (2019).

  18. So \(v_i = v_j\) and \(v_i \in v_j\) are well-formed primitive formulas irrespective of the sorts of the variables \(v_i, v_j\).

  19. See, e.g., Jech (2002) or Enderton (1977) for a detailed exposition of these axioms.

  20. So, what is called “\(\mathsf{ZCA}_{\sigma }\)” below is, strictly speaking, a definitional extension of the given axioms.

  21. An interesting discussion of the mathematical needs of scientifically applicable mathematics is Feferman (1992), in which Feferman discusses a predicative system W (descended from that set out by Hermann Weyl in Weyl (1918)) which is proof-theoretically conservative over \(\mathsf{PA}\). However, this all seems besides the central point, which derives from Quine and Putnam: physical quantities, fields, and so on, are themselves mixed functions and impure structures. It seems irrelevant then whether the set theory one uses, say, is conservative over \(\mathsf{PA}\) or not. Even if it is, these physical, mixed quantities exist (and their values, etc.) and that contradicts nominalism. The realism of Quine and Putnam in question concerns these physical, mixed quantities.

  22. See Hawking and Ellis (1973), Ch. 7, especially pp. 249–251; see Wald (1984), Theorem 10.2.2, p. 264.

  23. Note that, using numerical integration, one may also model geometry on a discrete grid. An example of this is briefly explained in Sect. 7.2, where we look at the analytic solution for Laplace equation in 2 dimensions (with Dirichlet boundary conditions on a unit square) and compare that with the numerical solution obtained using a software partial differential equation solver.

  24. To obtain \(L_2(\sigma )\), we add second-order variables \(X_i^{(j)}\) (i.e., the \(i\hbox{th}\) variable for j-place relations), and atomic formulas \(X_i^{(j)}(p_1, \dots , p_j)\) (and equations \(X_i^{(j)} = X_k^{(j)}\)), and corresponding second-order quantifiers. In a clear sense, one can interpret \(L_2(\sigma )\) into the full set-theoretic extended language \(L(\sigma _{\in })\). For the set-theoretic translation \((X_i^{(j)}(p_1, \dots , p_j))^{\circ }\) of an atomic formula \(X_i^{(j)}(p_1, \dots , p_j)\) is given as: \((p_1, \dots , p_j) \in X_i^{(j)}\), using pairing.

  25. I conflate the function symbol \(\textsf{B}\) and the set constant \(\textsf{B}\) naming its extension; likewise \(\equiv\). But this conflation is harmless, since context always disambiguates.

  26. This is analogous to the fact that one can prove a Representation Theorem for second-order Peano arithmetic \(\mathsf{PA}_2\) inside set theory: any (full) model \(M \models \mathsf{PA}_2\) is isomorphic to \((\omega , \varnothing , (.)^{+}, +_{\omega }, \cdot _{\omega })\).

  27. See also Väänänen and Wang (2015), Button and Walsh (2018) (pp. 223–250), Ketland (2021).

  28. For us, it is important that \(\textsf{EG}^{(n)}\) be expressed as a single axiom, and one can do this because the Continuity Axiom is a single second-order sentence quantifying over sets of points.

  29. Strictly speaking, this is a bit sloppy as I have not defined the product sort \(\mathbb{R}^n\). In our setting, with the given basic sorts, the correct sort of \(\varphi\) is \(\mathbb{P} \Rightarrow \mathbb{S}\); but we add a new axiom (called a codomain axiom in Ketland (2021)): \((\forall p \in \mathbb{P})(\varphi (p) \in \mathbb{R}^n)\).

  30. One may then regard the symbol “\(\varphi\)” as a skolem constant for the existential quantifier in “\((\exists \varphi : \mathbb{P} \rightarrow \mathbb{R}^n) \ (P_{\textsf{geom}} \overset{\varphi }{\cong }\mathbb{E}^{n})\)”.

  31. Strictly speaking, again, the sort declaration given for \(Q_i\) is a bit sloppy as I have not defined the relevant sort \(\mathbb{V}\) (i.e., elements of some vector space). In our setting, with the given basic sorts, the correct sort of \(Q_i\) is \(\mathbb{P} \Rightarrow \mathbb{S}\); but, for each \(Q_i\), we add a new codomain axiom: \((\forall p \in \mathbb{P})(Q_i(p) \in \mathbb{V})\), where \(X \in \mathbb{V}\) is the \(L_{\in }\)-formula defining \(\mathbb{V}\) (e.g., \(\mathbb{R}\) or \(\mathbb{C}\), ...).

  32. Henceforth I shall suppress reference to explicit definitions such as \(\textsf{Dfn}(Q^{\varphi })\): one might consider them absorbed into a definitional extension of \(\mathsf{ZCA}_{\sigma }\).

  33. It seems fairly clear that much the same can be done for General Relativity, where the geometric axiom will be: \((\mathbb{P}, \texttt{chart}, \texttt{metric}) \text{ is a relativistic spacetime}\).

  34. As I noted above, I have also deliberately ignored singularities and distributions. There are ways to handle these, but they introduce orthogonal and, in a sense, “higher-level” complexities not relevant to the current level of analysis: i.e., geometric structure and point fields on the geometry satisfying some differential equation.

  35. This is taught to first-year undergraduates, as how to solve the differential equation \((\partial _{xx} + k^2) F = 0\), though not quite in the way we describe it here!

  36. E.g., for the quantum harmonic oscillator, these additional parameters are m, \(\hbar\), \(\omega\), E.

  37. The first four are: \(H_0(x) = 1\); \(H_1(x) = 2x\); \(H_2(x) = 4x^2-2\); \(H_3(x) = 8x^3-12x\); ...

  38. These methods are described in any textbook on differential equations. See, for example, Arfken and Weber (2005), Ch. 9, §9.4 (p. 554), for explanation of separation of variables.

  39. Though it is clear that this is so, it is certainly not easily so—I do not volunteer to specify every detail and lemma. One could, in principle, formalize all this in a theorem-proving assistant like Isabelle, Lean and so on. But it would be something like a year-long MSc research project for a mathematics or computer science student.

  40. In this case, the Axiom of Choice isn’t needed. As I have tried to stress above, such metatheoretic conclusions will be largely invariant with respect the choice of foundational system, so long as it is not too weak. For example, I am reasonably certain this could be formalized inside the HOL/Isabelle theorem-proving assistant, or within Mizar, Coq or Lean.

  41. The numerical solution was worked out using the package ReacTran (for the programming language \(\texttt{R}\)), based on modifying code provided in Soetaert et al. (2012) (Ch. 9, “Solving Partial Differential Equations in R”, p. 167).

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Funding was supported by Narodowe Centrum Nauki (Grant Nos. 2018/29/B/HS1/01832, 2020/39/B/HS1/02020).

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Ketland, J. Standard Formalization. Axiomathes 32 (Suppl 3), 711–748 (2022). https://doi.org/10.1007/s10516-022-09625-3

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