A ψ_transformation is a way of talking about what happens when our understanding shifts into a new pattern of intelligibility. It names the movement of consciousness when we are no longer satisfied with a partial or fragmented grasp of things, and we integrate those fragments into a new, higher viewpoint.
Lonergan often describes how insights don’t just accumulate; they can reorganise our whole horizon. A ψ_transformation is that reorganising shift: the point where our questioning, insights, and judgements come together in a fresh unity of meaning.
One analogy is a “phase change.” Just as water doesn’t gradually turn into ice molecule by molecule, but shifts state at a threshold, so too our understanding sometimes reorganises itself all at once. Another analogy is moving from a local puzzle-piece to seeing how the whole puzzle fits together.
So, ψ_transformation is not a technical algorithm, but a name for the inner dynamic of consciousness: the leap from the local to the global, from fragments to a whole. It’s part of how insight grows into understanding, and how understanding develops into wisdom.
On 1 Sep 2025, at 07:34, 'John Raymaker' via Lonergan_L <loner...@googlegroups.com> wrote:
--• The following article isOpen accessDAvid, your comments on Ψ -transformations are quite technical and interesting. I am trying to understand what you wrote. Could you elaborate a bit more as to how Ψ -transformations can be part of an overal solution, JohnDPaper • The following article isOpen accessApplication of Ψ -transformation to the search for continuous function’s global extremum on simplex
A Sizikov
Published under licence by IOP Publishing Ltd
Journal of Physics: Conference Series, Volume 1203, International Conference "Applied Mathematics, Computational Science and Mechanics: Current Problems" 17–19 December 2018, Voronezh State University, Voronezh, Russian FederationCitation A Sizikov 2019 J. Phys.: Conf. Ser. 1203 012073DOI 10.1088/1742-6596/1203/1/012073Abstract
A nonconvex problem of mathematical programming, the acceptance region of which is simplex. A two-stage algorthm is suggested to solve the problem. At the first stage, the global optimum region is determined; at the second stage, local clean-up of the solution is carried out. The first stage is realized by the Ψ -transformation method, which is an alternative to direct random search techniques. The method is to build and use Ψ -function. Ψ -function is built emperically based on statistic tests. To perform the tests, the generator of random points evenly distributed in simplex is used. Even distribution in simplex is achieved through affine and linear transformations of points evenly distributed in a unit hypercube. For refinement of the approximate solution obtained at the first stage, the method of regular simplex reflection is used. Examples are discussed. The example of algorthm usage to optimize the hydrocarbon mixture make-up is presented.
Application of
to the search for continuous function’s global extremum on simplexPaper • The following article isOpen accessApplication of Ψ -transformation to the search for continuous function’s global extremum on simplex
A Sizikov
Published under licence by IOP Publishing Ltd
Journal of Physics: Conference Series, Volume 1203, International Conference "Applied Mathematics, Computational Science and Mechanics: Current Problems" 17–19 December 2018, Voronezh State University, Voronezh, Russian FederationCitation A Sizikov 2019 J. Phys.: Conf. Ser. 1203 012073DOI 10.1088/1742-6596/1203/1/012073Abstract
A nonconvex problem of mathematical programming, the acceptance region of which is simplex. A two-stage algorthm is suggested to solve the problem. At the first stage, the global optimum region is determined; at the second stage, local clean-up of the solution is carried out. The first stage is realized by the Ψ -transformation method, which is an alternative to direct random search techniques. The method is to build and use Ψ -function. Ψ -function is built emperically based on statistic tests. To perform the tests, the generator of random points evenly distributed in simplex is used. Even distribution in simplex is achieved through affine and linear transformations of points evenly distributed in a unit hypercube. For refinement of the approximate solution obtained at the first stage, the method of regular simplex reflection is used. Examples are discussed. The example of algorthm usage to optimize the hydrocarbon mixture make-up is presented.
A Sizikov
Published under licence by IOP Publishing Ltd
Journal of Physics: Conference Series, Volume 1203, International Conference "Applied Mathematics, Computational Science and Mechanics: Current Problems" 17–19 December 2018, Voronezh State University, Voronezh, Russian FederationCitation A Sizikov 2019 J. Phys.: Conf. Ser. 1203 012073DOI 10.1088/1742-6596/1203/1/012073Abstract
A nonconvex problem of mathematical programming, the acceptance region of which is simplex. A two-stage algorthm is suggested to solve the problem. At the first stage, the global optimum region is determined; at the second stage, local clean-up of the solution is carried out. The first stage is realized by the Ψ -transformation method, which is an alternative to direct random search techniques. The method is to build and use Ψ -function. Ψ -function is built emperically based on statistic tests. To perform the tests, the generator of random points evenly distributed in simplex is used. Even distribution in simplex is achieved through affine and linear transformations of points evenly distributed in a unit hypercube. For refinement of the approximate solution obtained at the first stage, the method of regular simplex reflection is used. Examples are discussed. The example of algorthm usage to optimize the hydrocarbon mixture make-up is presented.
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On 3 Sep 2025, at 15:03, 'PIERRE WHALON' via Lonergan_L <loner...@googlegroups.com> wrote:
Or a rose by any other name… how about vertical shift in horizon, à la MiT?
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