Transcript Computational and biological analogies for understanding the fine tuning of parameters in physics. Clément Vidal Center Leo Apostel (CLEA) Evolution Complexity and Cognition (ECCO) [email protected].

Computational and biological
analogies
for understanding the fine tuning
of parameters in physics.
Clément Vidal
Center Leo Apostel (CLEA)
Evolution Complexity and Cognition (ECCO)
[email protected]
Outline
1.
2.
3.
4.
5.
Introduction
Physical constants and initial conditions
Analogies for scientific purposes
The computational universe
The biological universe
1. Introduction
The worldview questions.
(Apostel, Van der Veken 1991); (Vidal 2007, 2008b)
Question
Philosophical Domain
1. What is?
4. What is good and what is evil?
Ontology
(model of the present)
Explanation
(model of the past)
Prediction
(model of the future, futurology)
Axiology (theory of values)
5. How should we act?
Praxeology (theory of action)
6. What is true and what is false?
Epistemology
(theory of knowledge)
2. Where does it all come from?
3. Where are we going?
The worldview questions.
(Apostel, Van der Veken 1991); (Vidal 2007, 2008b)
Question
Philosophical Domain
1. What is?
4. What is good and what is evil?
Ontology
(model of the present)
Explanation
(model of the past)
Prediction
(model of the future, futurology)
Axiology (theory of values)
5. How should we act?
Praxeology (theory of action)
6. What is true and what is false?
Epistemology
(theory of knowledge)
2. Where does it all come from?
3. Where are we going?
Gap in scientific explanation
God explained the “laws of Nature”
 Science developed, and God was put aside
 Laws are given, brute facts.

Immense progress in Big History
 Gap in scientific explanation for the origin.

(Davies 1998)
The Fine-Tuning (FT) Problem

if a number of physical parameters had
been slightly different, no life or more
generally no complexity would have
emerged. (e.g. Leslie 1989, Rees 2000, etc.).

Two sets of fine-tuned parameters:
Physical constants model of particle physics.
 Initial conditions in cosmological models

2. Physical constants and
initial conditions
Levy-Leblond’s (1979)
Classification of constants

A. Properties of physical objects
(masses of "elementary particles", etc.)

B. Classes of physical phenomenas
coupling constants of the various fundamental
interactions (nuclear, strong and weak, electromagnetic
and gravitational)

C. Universal constants
constants applicable in principle to any physical
phenomenon; (Planck constant ħ is a typical example.
Fine Tuning of dimensionless
coupling constants
α electromagnetism
 α gravity
 α weak nuclear force
 α strong nuclear force.

G
W
s

E.g. nucleosynthesis, the condition
α < α 4 must be fulfilled,
else all hydrogen goes to helium.
G
W
(Carr 2007)
The fate of
dimensionful constants

Distinction between:



Historically, Type-C dimensionful constants fade
away




Dimensionless constants
Dimensionful constants (c, G, ħ )
(i) modern
conceptual role dominant (e.g. ħ, c)
(ii) classical
conversion factors (e.g. thermodynamical constants k, J)
(iii) archaic
invisible (e.g. areas are square of lengths)
(Duff 2002): 0 dimensionful constants!
0 dimensionless constants as well?
Type-A (properties) constants
 Type-B coupling constants


All explained by a future cosmological
model?


To be discussed!
If so, FT would be reduced to initial
conditions of this model.
3. Analogies for scientific
purposes
What is an analogy?

“a mapping of knowledge from one domain
(the base) into another (the target) such
that a system of relations that holds
among the base objects also holds among
the target objects.” (Gentner and Jeziorski 1993, 448-449).
E.g. Cloud and sponge
 Basic cognitive tool (problem solving, etc.)

Good analogical reasoning

positive
what is analogous?
 negative
what is disanalogous?
 neutral
are the two domains analogous?
(Hesse 1966)
4. The computational
universe
AIT, laws and initial conditions

AIT: Algorithmic Information Theory (Chaitin)


Laws


Studies the complexity of strings
Information which can be compressed
Initial conditions

Information which cannot compressed
Cognitive point of view

Laws :


Initial conditions


Information our theories are able to compress
Information our theories can’t compress
Scientific progress:

Less initial conditions (hypotheses) and more
compressing laws?
Simulating universes

To understand initial conditions of the Big Bang

FT arguments vary one single parameter
Simulations are needed to vary more
parameters (see Vidal 2008a for more details)

MonkeyGod
Victor Stenger (1995, 2000) simulated
other possible universes.
 Variation of 4 parameters

Mass of the electron
 Mass of the proton
 α electromagnetism
 α strong nuclear force.

s

Many of them generate long-lived stars
Limitations

(AIT) Initial conditions of cosmological
models are not “incompressible”

Search new theories to explain them

Computation assumes Newtonian space
and time

Everything is set up with laws and initial
conditions
4. The biological universe
Evo Devo Universe

My focus: Lee Smolin’s
Cosmological Natural Selection (CNS)

Extension of CNS
(Crane 1994; Harrison 1995; Gardner 2000; 2003; Baláz 2005; Smart 2008;
Vidal 2008)
Lee Smolin’s Cosmological
Natural Selection (CNS)
The situation of nowadays physics is analogous to
the biologists’ before Lamarck and Darwin.
Biology (yesterday)
(1) Why are the different species as they are ?
(2) Species are timeless categories.
Physics
(nowadays)
Lee Smolin’s Cosmological
Natural Selection (CNS)
The situation of nowadays physics is analogous to
the biologists’ before Lamarck and Darwin.
Biology (yesterday)
Physics (nowadays)
(1) Why are the different species as
they are ?
(1) Why are constants as they are ?
(2) Species are timeless categories.
(2) Constants are timeless.
Components
Description
BIOLOGY
(cell)
COSMOLOGY
(universe)
Blueprint
Plan for the
The information
construction of the contained in the
offspring
DNA
Physical
constants and
initial conditions
Factory
Carries out the
construction
Cell
Physical laws and
the universe at
large
Controller
Ensures the
factory follows the
plan
The regulatory
mechanisms of
the mitosis
CNS:?
Duplicating
machine
Transmits a copy
of the blueprint to
the offspring
The reproduction
of the DNA
CNS:?
Components
Description
BIOLOGY
(cell)
COSMOLOGY
(universe)
Blueprint
Plan for the
The information
construction of the contained in the
offspring
DNA
Physical constants
and initial conditions
Factory
Carries out the
construction
Cell
Physical laws and
the universe at large
Controller
Ensures the
factory follows the
plan
The regulatory
mechanisms of
the mitosis
A cosmic process,
aiming at universe
reproduction
Duplicating
machine
Transmits a copy
of the blueprint to
the offspring
The
reproduction of
the DNA
Highly evolved
intelligence
Next talks
James Gardner: String theory
 John Smart: Biological analogy (development)
 John Stewart: Cosmos and human values

5. Conclusion
Summary

Fine tuning arguments reduced to initial
conditions of a future cosmological model?

Careful analogical reasoning

Simulations to explore other possible universes

Completing CNS with a role for intelligent life
(Gardner, Smart, Stewart…)
Thank you for your
attention !
Questions, criticisms are welcome now or later
[email protected]
References (1)
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Apostel, L., and Van der Veken. 1991. Wereldbeelden. Van fragmentering naar
integratie. DNB/Pelckmans. English translation: Aerts, D., L. Apostel, Bart De Moor, et
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http://www.vub.ac.be/CLEA/pub/books/worldviews.pdf.
Baláz, BA. 2005. The Cosmological Replication Cycle, the Extraterrestrial Paradigm
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http://astro.elte.hu/~bab/seti/IACP12z.htm.
Carr, B., ed. 2007. Universe or multiverse. Ed. B. Carr. Cambridge University Press.
Crane, L. 1994. Possible Implications of the Quantum Theory of Gravity: An
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Davies, P. C. W. 1998. Our Place in the Universe. In Modern cosmology & philosophy,
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Duff, M. J., L. B. Okun, and G. Veneziano. 2002. Trialogue on the number of
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http://arxiv.org/abs/physics/0110060.
Gardner, J. N. 2000. The Selfish Biocosm: complexity as cosmology. Complexity 5, no.
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---. 2003. Biocosm. The New Scientific Theory of Evolution: Intelligent Life is the
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Gentner, D., and M. Jeziorski. 1993. The shift from metaphor to analogy in Western
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References (2)
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Harrison, E. R. 1995. The Natural Selection of Universes Containing
Intelligent Life. Quarterly Journal of the Royal Astronomical Society
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http://adsabs.harvard.edu/full/1996QJRAS..37..369B .
Hesse, M. 1966. Models and analogies in science. Notre Dame, IN:
Notre Dame University Press.
Leslie, J. 1989. Universes. Routledge.
Levy-Leblond, J. M. 1979. The importance of being (a) constant.
Problems in the foundations of physics, Enrico Fermi School LXXII,
G. Torraldi ed.,(North Holland): 237.
Rees, M. 2000. Just Six Numbers: The Deep Forces that Shape the
Universe. New York: Basic Books.
Smart, J. 2008. Evo Devo Universe? A Framework for Speculations
on Cosmic Culture. In Cosmos and Culture, ed. S. J. Dick. To
appear.
http://accelerating.org/downloads/SmartEvoDevoUniv2008.pdf.
References (3)
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Stenger, V. J. 2000. Natural Explanations for the Anthropic
Coincidences. Philo 3, no. 2: 50-67.
Stenger, Victor J. 1995. The Unconscious Quantum Metaphysics in
Modern Physics and Cosmology. Amherst, N.Y: Prometheus Books.
Vidal, C. 2007. An Enduring Philosophical Agenda. Worldview
Construction as a Philosophical Method. Submitted for publication.
http://cogprints.org/6048/.
---. 2008a. The Future of Scientific Simulations:
from Artificial Life to Artificial Cosmogenesis. In Death And AntiDeath, Volume 6: Thirty Years After Kurt Gödel (1906-1978). In
press., ed. Charles Tandy. http://arxiv.org/abs/0803.1087.
---. 2008b. What is a worldview? Published in Dutch as: "Wat is een
wereldbeeld?". In Nieuwheid Denken. De Wetenschappen En Het
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