George Montañez, Assistant Professor in the Computer Sciences Department\ at Harvey Mudd College, has just published a unified model of specified complexity:

Abstract:

A mathematical theory of complex specified information is introduced which unifies several prior methods of computing specified complexity. Similar to how the exponential family of probability distributions have dissimilar surface forms yet share a common underlying mathematical identity, we define a model that allows us to cast Dembski’s semiotic specified complexity, Ewert et al.’s algorithmic specified complexity, Hazen et al.’s functional information, and Behe’s irreducible complexity into a common mathematical form. Adding additional constraints, we introduce canonical specified complexity models, for which one-sided conservation bounds are given, showing that large specified complexity values are unlikely under any given continuous or discrete distribution and that canonical models can be used to form statistical hypothesis tests, by bounding tail probabilities for arbitrary distributions. Montanez GD (2018) A Unified Model of Complex Specified Information. BIO-Complexity 2018 (4):1- ˜ 26. doi:10.5048/BIO-C.2018.4

We are told to expect a lay-friendly version of the model soon as well.

*See also:* How can we measure specified complexity

and

Bill Dembski: Specification: The Pattern That Signifies Intelligence

Kirk K Durston et al. Measuring the functional sequence complexity of proteins

Winston Ewert at Evolutionary Informatics

Robert M. Hazen et al. Functional information and the emergence of biocomplexity (public access) A friend notes, “Functional information, as outlined by Hazen et al., can be a measure of specified complexity, where the specificity supplies the functional constraint.”

Robert M. Hazen et al. Functional Information and the Emergence of Biocomplexity pdf (book)

Could a signature of specified complexity help us find alien life?

and

A Tutorial on Specified Complexity

This seems very interesting, although I will have to try to understand it! 🙂

However, this is apparently the core of the problem:

I think that describes exactly what happens with proteins. And it’s, I believe, the essence of my answer to the “many possible solutions” argument, so often raised by our kind interlocutors.

There can be many possible solutions, but not so many as to be practically relevant, when those solutions are all highly specified (complex).

What’s going on with the discussion between GP and professor JF of TSZ ?

Whose court is the ball in now?

jawa:

I don’t know.

I am not aware of any true answer from JF, except for the following (I am of course intepreting him):

a) He (that would be me) has not demonstrated that NS cannot do it, that it is logically impossible. (But I have nevere even tried to do that: it is not necessary at all).

b) If I (that would be JF) define fitness as the function, then changes that happen anywhere in the genome can contribute to it (which is true, but only because fitness is a vague definition, that includes any possible function, most of them extremely simple, that give some reproductive advantage in some environment. For all more specific definitions of function, that are related to functonal complexity, JF’s statement is simply wrong, and changes have to occur in some specific site).

c) His (that would be my) arguments would not impress evolutionary biologists. True. And so? If my arguments are true (and they are), that is a problem of evolutionary biologists, I suppose.

Has he offered any other argument? I suppose he has acknowledged, in a way, that my thief argument is formally correct. Of course he does not agree that it is absolutely pertinent to what happens in the biological world (in principle: of course it does not model exactly the biological space, but the basic idea is valid for it as much as for the safes). But I am not aware that he has explained why, except of course for the above mentioned “arguments”, which are only distractions and do not address the real point.

The real point, of course, is that many simple solutions, each of them contributing to fitness, do not make one complex solution. And the example of the thief clearly shows that.

But, of course, at some point I have stopped checking the debate at TSZ. For obvious reasons.

George, well done. KF

PS: Best wishes to the living proof that there is a God!

gpuccio,

your arguments are clear enough to be understood by anyone who wants to understand them. Your point is sufficiently convincing to any open-minded person. Further discussion in this case would have been a waste of time. Well done.

Thanks.

Appears to be an excellent foundational theorem. Congratulations.

For the converse new foundational theorem see

Basener & Sanford on genetic entropy.

“Fisher’s Famous Theorem Has Been “Flipped””

“Fisher had claimed that his theorem was a mathematical proof of evolution — making the continuous increase in fitness a universal and mathematically certain natural law. The corrected theorem shows that just the opposite is true — fitness must very consistently degenerate — making macroevolution impossible.”

http://www.geneticentropy.org/latest-development

Basener, W.F. and Sanford, J.C., 2018. The fundamental theorem of natural selection with mutations. Journal of mathematical biology, pp.1-34.

Abstract

“The mutation–selection process is the most fundamental mechanism of evolution. In 1935, R. A. Fisher proved his fundamental theorem of natural selection, providing a model in which the rate of change of mean fitness is equal to the genetic variance of a species. Fisher did not include mutations in his model, but believed that mutations would provide a continual supply of variance resulting in perpetual increase in mean fitness, thus providing a foundation for neo-Darwinian theory. In this paper we re-examine Fisher’s Theorem, showing that because it disregards mutations, and because it is invalid beyond one instant in time, it has limited biological relevance. We build a differential equations model from Fisher’s first principles with mutations added, and prove a revised theorem showing the rate of change in mean fitness is equal to genetic variance plus a mutational effects term. We refer to our revised theorem as the fundamental theorem of natural selection with mutations. Our expanded theorem, and our associated analyses (analytic computation, numerical simulation, and visualization), provide a clearer understanding of the mutation–selection process, and allow application of biologically realistic parameters such as mutational effects. The expanded theorem has biological implications significantly different from what Fisher had envisioned.”

https://link.springer.com/article/10.1007/s00285-017-1190-x

Together these two theories provide a foundation for intelligent design and constrain evolution to decreasing fitness.

I liked Dr. Marks’ quip about the typical response from Darwinists that they give when they are informed about the extreme, (‘needle in a universe wide haystack’) rarity of functional sequences in sequence space:

Besides Darwinists being purposely ignorant and obtuse, at the other end of the spectrum there is another detail that gets, inadvertently, lost in this debate.

It seems to me that in the fleshing out of the technical mathematical details of Conservation of Information, that an important scientific detail is constantly being overlooked by leading Intelligent Design proponents in their quest to build a more rigid mathematical foundation for Intelligent Design.

That important scientific detail, that is left on the cutting room floor by leading ID proponents, is the scientific detail of mathematically, and empirically, fleshing out the precise physical relationship between immaterial information and matter-energy.

Moreover, without a rigorous mathematical and physical definition of Information, that physically distinguishes information from matter-energy, it seems to me Darwinists can forever play their games pretending that, no matter how improbable it is shown to be for them, information is somehow ’emergent’ from a matter-energy basis.

To be sure, it is certainly not an easy task to map out this relationship, (shoot, for all I know it could well be intractable), but I have seen no effort whatsoever, (save for some nascent work by Dr. Andy McIntosh in thermodynamics), by leading ID proponents to even try to address this issue from an ID perspective.

To be sure, the field is still extremely young, and I am certainly no expert in it, but perhaps its time for some of ID’s brightest minds, (Dembski, Marks, Ewert, Durston, Montañez, Sternberg, Axe, etc.., etc..), to finally have a mathematical go at building at least a rough preliminary mathematical foundation towards the question of precisely how immaterial information and matter-energy physically interact within biological life?

As far how physical science is usually formulated and practiced, with its emphasis of how a mathematical theory might experimentally interact with the physical world, it would seem to be a VERY important scientific detail to finally look into.

Thermodynamics seems to be a promising avenue for mathematically addressing this question,

The information content of a ‘simple’ bacterial cell, when working from the thermodynamic perspective, has been calculated to be approx. 10^12 bits:

To put 10^12 bits in perspective,

And as mentioned previously, Dr. Andy McIntosh has, from a thermodynamic perspective, done some nascent work in this area.

Specifically, Dr. McIntosh holds that regarding information as independent of energy and matter ‘resolves the thermodynamic issues and invokes the correct paradigm for understanding the vital area of thermodynamic/organisational interactions’.

And in support of Dr. McIntosh’s contention that it must be non-material information which constrains biological life to be so far out of thermodynamic equilibrium, information has now been experimentally shown to have a ‘thermodynamic content’:

This work on elucidating the precise relationship between information and thermodynamics, has now been extended:

A surprising detail, (a detail that I have still not completely wrapped my mind around), is revealed in the following article

In the following article a Professor is quoted as saying, “Now in information theory, we wouldn’t say entropy is a property of a system, but a property of an observer who describes a system.”,,,”

To reiterate, “Entropy,,, is a property of an observer who describes a system.” ???

Anyways, leaving that tantalizing tidbit aside for the moment, and of related interest to immaterial information having a ‘thermodynamic content’, classical digital information was found to be a subset of ‘non-local’, (i.e. beyond space and time), quantum entanglement/information by the following method which removed heat from a computer by the deletion of data:

In the following article, (in direct contradiction to the reductive materialistic claims of Darwinian evolution), Dr. Vaccaro states in regards to the preceding thought experiment that “Landauer said that information is physical because it takes energy to erase it. We are saying that the reason it (information) is physical has a broader context than that.”,

Although the preceding is certainly very strong evidence for the physical reality of immaterial information, the coup de grace for demonstrating that immaterial information is its own distinct physical entity, separate from matter and energy, is Quantum Teleportation:

Moreover, this ‘physically real’ quantum information is also found to be ‘conserved’ (as in it cannot be created nor destroyed).

Moreover, this physically real quantum information can perform a number of tasks that are impossible for classical information. And indeed these ‘impossible tasks’ that quantum information is able to perform, provides the motivation for trying to build quantum computers.

As well this physically real quantum information, which cannot be created or destroyed, (and of which classical information is a subset), is also now found in molecular biology on a massive scale. In every DNA and protein molecule:

Moreover, this Quantum Information in molecular biology, since it can perform computational tasks that are impossible for classical information, provides coherent solutions for the protein folding enigma, DNA search problems, and for exactly why life is so far out of thermodynamic equilibrium in the first place.

Besides providing direct empirical falsification of Landauer’s claim, and neo-Darwinian claims in general, claims that say immaterial information does not exist apart from its representation on a physical medium, the implication of finding ‘non-local’, beyond space and time, and ‘conserved’, quantum information in molecular biology on such a massive scale, in every DNA and protein molecule, is fairly, and pleasantly, obvious.

That pleasant implication, or course, being the fact that we now have very strong physical evidence directly implying that we do indeed have an immaterial, and eternal, soul that is very well capable of living beyond the death of our material bodies.

As Stuart Hameroff states in the following video, ‘the quantum information,, isn’t destroyed. It can’t be destroyed,,, it’s possible that this quantum information can exist outside the body. Perhaps indefinitely as a soul.”

Verse and video:

Thus in conclusion, there is much evidence establishing the independent physical reality of immaterial information apart from matter-energy, but as hopefully some can see by now, there is still much ‘mathematical work’ left to be done elucidating precisely how all this will fit into the Intelligent Design perspective.

of related note to giving ID a more ‘physical’ scientific basis, instead of ID just having an essentially mathematical, theoretical, basis, Gödel’s incompleteness theorem has, finally, been extended, from just theoretical mathematics, into physics.

In the following article entitled ‘Quantum physics problem proved unsolvable: Godel and Turing enter quantum physics’, which studied the derivation of macroscopic properties from a complete microscopic description, the researchers remark that even a perfect and complete description of the microscopic properties of a material is not enough to predict its macroscopic behaviour.,,, The researchers further commented that their findings challenge the reductionists’ point of view, as the insurmountable difficulty lies precisely in the derivation of macroscopic properties from a microscopic description.”

How Gödel’s incompleteness theorem may mathematically (and now physically) relate to ID was touched upon in the following articles:

Another thing that often gets missed in all the discussion about macro-evolution being mathematically impossible is the fact that devolution isn’t. John Sanford’s

Genetic Entropyis a horrifying look into the genetic decay of a fallen world.Very interesting.

Folks, let’s note that this is a case of the fourth generation of ID-friendly scholarship emerging. Emerging, in fact from one of UD’s own circle of commenters. That should be recognised as a milestone in its own right. This paper marks a key proposed synthesis and thus unified view of “the property of an object being both unlikely and structurally organized,” where as the headlined quote from Glieck who in turn cites: ““Life must depend on a higher level of complexity, structure without predictable repetition . . .” KF

KF,

Good observation.

A very interesting read, but I will have to work hard at this to fully comprehend it. This is due to my limitations, not the author’s.

The paper is very interesting in that it shows the independent derivations of specified complexity are all talking about the same quantity. Sort of like how multiple derivations of the same groundbreaking idea tend to show up at the same time.

So much for evolution by intelligent design.

So genetic algorithms don’t work?

@ET

>So genetic algorithms don’t work?

Not very well.

“I have never encountered any problem where genetic algorithms seemed to me the right way to attack it. Further, I have never seen any computational results reported using genetic algorithms that have favorably impressed me. Stick to simulated annealing for your heuristic search voodoo needs.”

— Steven Skiena, Algorithm Design Manual

I guess except for the many that have worked very well.

I wonder how Steven would have approached the antenna issue…