Citation
Dorn, Evan David (2005) Universal Biosignatures for the Detection of Life. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/08B9-8Q96. https://resolver.caltech.edu/CaltechETD:etd-05272005-071800
Abstract
My goal is to identify processes of life that leave measurable effects on an organism's environment, but which are not tied to any particular biochemistry, in order to build a conceptual framework for the search for extraterrestrial life. To this end, I test a pair of phenomena that appear in both terrestrial (biochemical) life and in digital life. Because these two life forms are different and unrelated, any phenomenon measurable in both is suggested to be universal.
The Monomer Abundance Distribution Biosignature (MADB) is any measurement of the relative concentrations of related chemical compounds that cannot be explained by abiotic processes. I observe that living systems synthesize specific chemical compounds at rates that maximize their fitness. As a result, life-bearing environmental samples exhibit compounds in abundance ratios that are clearly not the result of abiotic synthesis because those ratios belie the formation kinetics and thermodynamics that would constrain abiotic synthesis. Often, biotic samples contain high concentrations of specific large, complex molecules that are never seen in abiotic synthesis and cannot be explained unless highly specific catalysts (i.e., enzymes) are present, and energy is expended to drive thermodynamically unfavorable reactions. I catalog this effect as it appears in terrestrial biochemical systems, including amino acids and carboxylic acids, and demonstrate the universality of selection's action on the monomeric composition of life forms by studying analogous examples in digital life. I suggest how this phenomenon provides a route to the detection of even unusual or unforeseen biochemistries, and give examples of detection methods using pattern-recognition techniques that may allow us to empower an autonomous system with the general ability to detect life forms.
The Layered Trophic Residue Biosignature (LTRB) is any observation of stratification in solute chemistry that indicates metabolic activity by a sequence of diverse communities. When multiple chemical resources are available, natural selection drives adaptive radiation and the formation of specialist phenotypes. Competition ensures that specialists consume resources in decreasing order of energetic potential when resources diffuse through a medium near a boundary. The result is strata of chemicals appearing in order of redox potential, which is best explained by the presence of life.
Item Type: | Thesis (Dissertation (Ph.D.)) | ||||||
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Subject Keywords: | amino acids; artificial life; astrobiology; carboxylic acids; digital life; meteorites; NDLTD Innovative ETD Award 2006; neural networks | ||||||
Degree Grantor: | California Institute of Technology | ||||||
Division: | Engineering and Applied Science | ||||||
Major Option: | Computation and Neural Systems | ||||||
Awards: | Networked Digital Library of Theses and Dissertations Innovative ETD Award, 2006. | ||||||
Thesis Availability: | Public (worldwide access) | ||||||
Research Advisor(s): |
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Thesis Committee: |
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Defense Date: | 11 February 2005 | ||||||
Non-Caltech Author Email: | public (AT) lrdesign.com | ||||||
Record Number: | CaltechETD:etd-05272005-071800 | ||||||
Persistent URL: | https://resolver.caltech.edu/CaltechETD:etd-05272005-071800 | ||||||
DOI: | 10.7907/08B9-8Q96 | ||||||
Related URLs: |
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Default Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | ||||||
ID Code: | 2143 | ||||||
Collection: | CaltechTHESIS | ||||||
Deposited By: | Imported from ETD-db | ||||||
Deposited On: | 02 Jun 2005 | ||||||
Last Modified: | 30 Aug 2022 23:13 |
Thesis Files
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PDF (Thesis-DornED-2005.pdf)
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PDF (README-ListOfFiles.pdf)
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Video (MPEG) (biosignature_movie_1.mpg)
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Video (MPEG) (biosignature_movie_2.mpg)
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Video (MPEG) (LTRB_movie.mpg)
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MS Excel (AminoAcids.xls)
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MS Excel (CarboxylicAcids.xls)
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