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At least 19 records

The coevolution of decimetric millisecond spikes and hard X-ray emission during solar flares

Results are presented of an analysis of a comprehensive data set of 27 solar flares with decimetric millisecond spikes between 1980 and 1989, simultaneously observed with the Zuerich radio spectrometers and the Hard X-ray Burst Spectrometer on the SMM spacecraft. Two contradictory relationships of the coevolution of hard X-ray and spiky radio emissions during flares are found: the temporal evolution of both emissions reveals a close functional dependence, but there is a substantial time delay between the two emissions. Five possible scenarios for the hard-X-ray-associated radio spike emission which may account for both their detailed coevolution and their substantial intervening time delay are discussed. All five scenarios are able to explain both the close coevolution of hard X-ray and radio emission as well as their mutual delay to some degree, but none of them can explain all observational aspects in a simple way.

Aschwanden, Markus J.↗

Coevolution of Machine Learning and Process-Based Modelling to Revolutionize Earth and Environmental Sciences: A Perspective

Machine learning (ML) applications in Earth and environmental sciences (EES) have gained incredible momentum in recent years. However, these ML applications have largely evolved in ‘isolation’ from the mechanistic, process-based modelling (PBM) paradigms, which have historically been the cornerstone of scientific discovery and policy support. In this perspective, we assert that the cultural barriers between the ML and PBM communities limit the potential of ML, and even its ‘hybridization’ with PBM, for EES applications. Fundamental, but often ignored, differences between ML and PBM are discussed as well as their strengths and weaknesses in light of three overarching modelling objectives in EES, (1) nowcasting and prediction, (2) scenario analysis, and (3) diagnostic learning. The paper ponders over a ‘coevolutionary’ approach to model building, shifting away from a borrowing to a co-creation culture, to develop a generation of models that leverage the unique strengths of ML such as scalability to big data and high-dimensional mapping, while remaining faithful to process-based knowledge base and principles of model explainability and interpretability, and therefore, falsifiability.

Saman Razavi↗

An analysis of the metabolic theory of the origin of the genetic code

A computer program was used to test Wong's coevolution theory of the genetic code. The codon correlations between the codons of biosynthetically related amino acids in the universal genetic code and in randomly generated genetic codes were compared. It was determined that many codon correlations are also present within random genetic codes and that among the random codes there are always several which have many more correlations than that found in the universal code. Although the number of correlations depends on the choice of biosynthetically related amino acids, the probability of choosing a random genetic code with the same or greater number of codon correlations as the universal genetic code was found to vary from 0.1% to 34% (with respect to a fairly complete listing of related amino acids). Thus, Wong's theory that the genetic code arose by coevolution with the biosynthetic pathways of amino acids, based on codon correlations between biosynthetically related amino acids, is statistical in nature.

NASA Discipline Exobiology↗

Preparation and characterization of electrodes for the NASA Redox storage system

Electrodes for the Redox energy storage system based on iron and chromium chloride reactants is discussed. The physical properties of several lots of felt were determined. Procedures were developed for evaluating electrode performance in lab scale cells. Experimental procedures for evaluating electrodes by cyclic voltammetry are described which minimize the IR losses due to the high internal resistance in the felt (distributed resistance). Methods to prepare electrodes which reduced the coevolution of hydrogen at the chromium electrode and eleminate the drop in voltage on discharge occasionally seen with previous electrodes were discussed. Single cells of 0.3329 ft area with improved membranes and electrodes are operating at over 80% voltage efficiency and coulombic efficiencies of over 98% at current densities of 16 to 20 amp % ft.

Reid, M. A.↗

Diurnal variations of outgoing longwave radiation and albedo from ERBE scanner data

The scanning instruments of the Earth Radiation Budget Experiment provide measurements of instantaneous broadband albedo and outgoing longwave radiation (OLR) with a spatial resolution of about 50 km. Data from the Earth Radiation Budget Satellite (ERBS), which is in an orbit that precesses through local time at the rate of one hour every three days, can be used to describe the mean, hourly diurnal variations in the distribution of OLR and albedo on this scale. Much of this variation is caused by cloud type and amount changes. Two-dimensional histograms show the coevolution of OLR and albedo with the diurnal cycle, and the distribution of albedo-OLR pairings associated with the cloud distribution in a particular region and season. The albedo-OLR pairing characterizes a cloud type and determines its net effect on the energy balance at the top of the atmosphere. Diurnal variations in cloud type and amount in many regions are sufficient to cause substantial errors in radiation budget quantities and cloud properties estimated from observations taken from a single sun-synchronous orbit. Errors in estimated net radiation can be as large as 50 W/sq m for oceanic stratus regions and for land regions during summer.

Hartmann, Dennis L.↗

Unnatural selection in chemical systems

The theory of evolution through natural selection was proposed by Darwin and Wallace to explain how the characteristics of populations of animals change with time. An examination of their assumptions shows that the theory has much broader application than they originally envisaged. We now know that in appropriate environments RNA molecules or computer viruses, for example, can evolve. The adventure with which we are concerned is the quest for chemical systems that undergo processes analogous to Darwinian selection in the test tube. The search is not restricted to systems that are closely related to nucleic acids, although most of the available experimental evidence concerns such systems. A population of molecules satisfies all the requirements of the theory is there are different kinds of molecules in the population and if each individual molecule can direct the formation of copies of itself, then a population of molecules will adapt to a varying environment by changing its composition so as to maintain as high as possible a rate of replication. Sol Spiegelman is the inventor of 'unnatural selection'. He showed clearly that populations of RNA molecules evolve when replicated repeatedly by Q beta RNA polymerase under a chosen set of adverse reaction conditions. In the systems that he studied, the initial population was fairly homogeneous and much of the variation was created during the course of the experiment by mutation, that is, error of replication. The term 'unnatural selection' will be used loosely to describe evolution of nucleic acids or other replicatable polymers in vitro. The term 'Natural Selection' will be reserved for the evolution of living organisms and their viruses. Natural Section usually involves the coevolution of nucleic acids and proteins, while 'unnatural selection', as practiced so far, allows replicating nucleic acids to evolve but hold constant the enzymes that catalyze replication. It is widely believed that biology based on DNA, RNA, and proteins was preceded by the biology of an 'RNA world' in which enzymes were composed of RNA alone. The origin of RNA replication is thus the central puzzle of the origins of life. Consequently, RNA-catalyzed RNA replication is presently one of the main goals of experimental work on unnatural selection. However, there is also a more distant goal, namely, to achieve replication and selection in systems unrelated to RNA. These different systems are discussed in this article.

Orgel, Leslie E.↗

Towards Evolving Electronic Circuits for Autonomous Space Applications

The relatively new field of Evolvable Hardware studies how simulated evolution can reconfigure, adapt, and design hardware structures in an automated manner. Space applications, especially those requiring autonomy, are potential beneficiaries of evolvable hardware. For example, robotic drilling from a mobile platform requires high-bandwidth controller circuits that are difficult to design. In this paper, we present automated design techniques based on evolutionary search that could potentially be used in such applications. First, we present a method of automatically generating analog circuit designs using evolutionary search and a circuit construction language. Our system allows circuit size (number of devices), circuit topology, and device values to be evolved. Using a parallel genetic algorithm, we present experimental results for five design tasks. Second, we investigate the use of coevolution in automated circuit design. We examine fitness evaluation by comparing the effectiveness of four fitness schedules. The results indicate that solution quality is highest with static and co-evolving fitness schedules as compared to the other two dynamic schedules. We discuss these results and offer two possible explanations for the observed behavior: retention of useful information, and alignment of problem difficulty with circuit proficiency.

Lohn, Jason D.↗

Comparing a Coevolutionary Genetic Algorithm for Multiobjective Optimization

We present results from a study comparing a recently developed coevolutionary genetic algorithm (CGA) against a set of evolutionary algorithms using a suite of multiobjective optimization benchmarks. The CGA embodies competitive coevolution and employs a simple, straightforward target population representation and fitness calculation based on developmental theory of learning. Because of these properties, setting up the additional population is trivial making implementation no more difficult than using a standard GA. Empirical results using a suite of two-objective test functions indicate that this CGA performs well at finding solutions on convex, nonconvex, discrete, and deceptive Pareto-optimal fronts, while giving respectable results on a nonuniform optimization. On a multimodal Pareto front, the CGA finds a solution that dominates solutions produced by eight other algorithms, yet the CGA has poor coverage across the Pareto front.

Lohn, Jason D.↗

Coevolutionary Free Lunches

Recent work on the foundations of optimization has begun to uncover its underlying rich structure. In particular, the "No Free Lunch" (NFL) theorems [WM97] state that any two algorithms are equivalent when their performance is averaged across all possible problems. This highlights the need for exploiting problem-specific knowledge to achieve better than random performance. In this paper we present a general framework covering most search scenarios. In addition to the optimization scenarios addressed in the NFL results, this framework covers multi-armed bandit problems and evolution of multiple co-evolving agents. As a particular instance of the latter, it covers "self-play" problems. In these problems the agents work together to produce a champion, who then engages one or more antagonists in a subsequent multi-player game In contrast to the traditional optimization case where the NFL results hold, we show that in self-play there are free lunches: in coevolution some algorithms have better performance than other algorithms, averaged across all possible problems. However in the typical coevolutionary scenarios encountered in biology, where there is no champion, NFL still holds.

Wolpert, David H.↗

Coevolutionary Free Lunches

Recent work on the mathematical foundations of optimization has begun to uncover its rich structure. In particular, the "No Free Lunch" (NFL) theorems state that any two algorithms are equivalent when their performance is averaged across all possible problems. This highlights the need for exploiting problem-specific knowledge to achieve better than random performance. In this paper we present a general framework covering more search scenarios. In addition to the optimization scenarios addressed in the NFL results, this framework covers multi-armed bandit problems and evolution of multiple co-evolving players. As a particular instance of the latter, it covers "self-play" problems. In these problems the set of players work together to produce a champion, who then engages one or more antagonists in a subsequent multi-player game. In contrast to the traditional optimization case where the NFL results hold, we show that in self-play there are free lunches: in coevolution some algorithms have better performance than other algorithms, averaged across all possible problems. We consider the implications of these results to biology where there is no champion.

Wolpert, David H.↗

Comparison Between GOES-12 Overshooting-Top Detections, WSR-88D Radar Reflectivity, and Severe Storm Reports

Studies have found that convective storms with overshooting-top (OT) signatures in weather satellite imagery are often associated with hazardous weather, such as heavy rainfall, tornadoes, damaging winds, and large hail. An objective satellite-based OT detection product has been developed using 11-micrometer infrared window (IRW) channel brightness temperatures (BTs) for the upcoming R series of the Geostationary Operational Environmental Satellite (GOES-R) Advanced Baseline Imager. In this study, this method is applied to GOES-12 IRW data and the OT detections are compared with radar data, severe storm reports, and severe weather warnings over the eastern United States. The goals of this study are to 1) improve forecaster understanding of satellite OT signatures relative to commonly available radar products, 2) assess OT detection product accuracy, and 3) evaluate the utility of an OT detection product for diagnosing hazardous convective storms. The coevolution of radar-derived products and satellite OT signatures indicates that an OT often corresponds with the highest radar echo top and reflectivity maximum aloft. Validation of OT detections relative to composite reflectivity indicates an algorithm false-alarm ratio of 16%, with OTs within the coldest IRW BT range (less than 200 K) being the most accurate. A significant IRW BT minimum typically present with an OT is more often associated with heavy precipitation than a region with a spatially uniform BT. Severe weather was often associated with OT detections during the warm season (April September) and over the southern United States. The severe weather to OT relationship increased by 15% when GOES operated in rapid-scan mode, showing the importance of high temporal resolution for observing and detecting rapidly evolving cloud-top features. Comparison of the earliest OT detection associated with a severe weather report showed that 75% of the cases occur before severe weather and that 42% of collocated severe weather reports had either an OT detected before a severe weather warning or no warning issued at all. The relationships between satellite OT signatures, severe weather, and heavy rainfall shown in this paper suggest that 1) when an OT is detected, the particular storm is likely producing heavy rainfall and/or possibly severe weather; 2) an objective OT detection product can be used to increase situational awareness and forecaster confidence that a given storm is severe; and 3) this product may be particularly useful in regions with insufficient radar coverage.

Dworak, Richard↗

Constraining the Climate and Ocean PH of the Early Earth with a Geological Carbon Cycle Model

The early Earth's environment is controversial. Climatic estimates range from hot to glacial, and inferred marine pH spans strongly alkaline to acidic. Better understanding of early climate and ocean chemistry would improve our knowledge of the origin of life and its coevolution with the environment. Here, we use a geological carbon cycle model with ocean chemistry to calculate self-consistent histories of climate and ocean pH. Our carbon cycle model includes an empirically justified temperature and pH dependence of seafloor weathering, allowing the relative importance of continental and seafloor weathering to be evaluated. We find that the Archean climate was likely temperate (0-50deg C) due to the combined negative feedbacks of continental and seafloor weathering. Ocean pH evolves monotonically from 6.6(sup + 0.6) (sub -0.4) (2 sigma) at 4.0 Ga to 7.0(sup +0.7) (sub-0.5) (2 sigma) at the Archean-Proterozoic boundary, and to 7.9(sup +0.1) (sub -0.2) (2 sigma) at the Proterozoic-Phanerozoic boundary. This evolution is driven by the secular decline of pCO2, which in turn is a consequence of increasing solar luminosity, but is moderated by carbonate alkalinity delivered from continental and seafloor weathering. Archean seafloor weathering may have been a comparable carbon sink to continental weathering, but is less dominant than previously assumed, and would not have induced global glaciation. We show how these conclusions are robust to a wide range of scenarios for continental growth, internal heat flow evolution and outgassing history, greenhouse gas abundances, and changes in the biotic enhancement of weathering.

Krissansen-Totton, Joshua↗

Exoplanet Biosignatures: Understanding Oxygen as a Biosignature in the Context of Its Environment

Here we review how environmental context can be used to interpret whether O 2 is a biosignature in extrasolar planetary observations. This paper builds on the overview of current biosignature research discussed in Schwieterman et al. (2017), and provides an in-depth, interdisciplinary example of biosignature identification and observation that serves as a basis for the development of the general framework for biosignature assessment described in Catling et al., (2017). O 2 is a potentially strong biosignature that was originally thought to be an unambiguous indicator for life at high-abundance. In exploring O 2 as a biosignature, we describe the coevolution of life with the early Earth's environment, and how the interplay of sources and sinks in the planetary environment may have resulted in suppression of O 2 release into the atmosphere for several billion years, a false negative for biologically generated O 2 . False positives may also be possible, with recent research showing potential mechanisms in exoplanet environments that may generate relatively high abundances of atmospheric O 2 without a biosphere being present. These studies suggest that planetary characteristics that may enhance false negatives should be considered when selecting targets for biosignature searches. Similarly our ability to interpret O 2 observed in an exoplanetary atmosphere is also crucially dependent on environmental context to rule out false positive mechanisms. We describe future photometric, spectroscopic and time-dependent observations of O 2 and the planetary environment that could increase our confidence that any observed O 2 is a biosignature, and help discriminate it from potential false positives. The rich, interdisciplinary study of O 2 illustrates how a synthesis of our understanding of life's evolution and the early Earth, scientific computer modeling of star-planet interactions and predictive observations can enhance our understanding of biosignatures and guide and inform the development of next-generation planet detection and characterization missions. By observing and understanding O 2 in its planetary context we can increase our confidence in the remote detection of life, and provide a model for biosignature development for other proposed biosignatures.

Victoria S Meadows↗

Serious Gaming for Building a Basis of Certification via Trust and Trustworthiness of Autonomous Systems

Autonomous systems governed by a variety of adaptive and nondeterministic algorithms are being planned for inclusion into safety-critical environments, such as unmanned aircraft and space systems in both civilian and military applications. However, until autonomous systems are proven and perceived to be capable and resilient in the face of unanticipated conditions, humans will be reluctant or unable to delegate authority, remaining in control aided by machine-based information and decision support. Proving capability, or trustworthiness, is a necessary component of certification. Perceived capability is a component of trust. Trustworthiness is an attribute of a cyber-physical system that requires context-driven metrics to prove and certify. Trust is an attribute of the agents participating in the system and is gained over time and multiple interactions through trustworthy behavior and transparency. Historically, artificial intelligence and machine learning systems provide answers without explanation - without a rationale or insight into the machine “thinking”. In order to function as trusted teammates, machines must be able to explain their decisions and actions. This transparency is a product of both content and communication. NASA’s Autonomy Teaming & TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR) project seeks to build a basis for certification of autonomous systems via establishing metrics for trustworthiness and trust in multi-agent team interactions, using AI (Artificial Intelligence) explainability and persistent modeling and simulation, in the context of mission planning and execution, with analyzable trajectories. Inspired by Massively Multiplayer Online Role Playing Games (MMORPG) and Serious Gaming, the proposed ATTRACTOR modeling and simulation environment is similar to online gaming environments in which player (aka agent) participants interact with each other, affect their environment, and expect the simulation to persist and change regardless of any individual agent’s active participation. This persistent simulation environment will accommodate individual agents, groups of self-organizing agents, and large-scale infrastructure behavior. The effects of the emerging adaptation and coevolution can be observed and measured to building a basis of measurable trustworthiness and trust, toward certification of safety-critical autonomous systems.

Allen, B. Danette↗

JWST/MIRI Simulated Imaging: Insights into Obscured Star Formation and AGNs for Distant Galaxies in Deep Surveys

The James Webb Space Telescope MIRI instrument will revolutionize extragalactic astronomy with unprecedentedsensitivity and angular resolution in mid-IR. Here we assess the potential of MIRI photometry to constrain galaxyproperties in the Cosmic Evolution Early Release Science(CEERS)survey. We derive estimated MIRIfluxes fromthe spectral energy distributions(SEDs)of real sources that fall in a planned MIRI pointing. We also obtain MIRIfluxes for hypothetical active galactic nucleus(AGN)–galaxy mixed models varying the AGN fractionalcontribution to the total IR luminosity(fracAGN). Based on these modelfluxes, we simulate CEERS imaging(3.6 hrexposure)in six bands from F770W to F2100W usingMIRISIMand reduce these data usingJWST PIPELINE.Weperform point-spread-function-matched photometry withTPHOTandfit the source SEDs withX-CIGALE,simultaneously modeling photometric redshift and other physical properties. Adding the MIRI data, the accuracyof both redshift and fracAGNis generally improved by factors of2 for all sources atz3. Notably, for pure-galaxy inputs(fracAGN=0), the accuracy of fracAGNis improved by∼100 times thanks to MIRI. The simulatedCEERS MIRI data are slightly more sensitive to AGN detections than the deepest X-ray survey, based on theempiricalLX–L6μmrelation. Like X-ray observations, MIRI can also be used to constrain the AGN accretionpower(accuracy≈0.3 dex). Our work demonstrates that MIRI will be able to place strong constraints on the mid-IR luminosities from star formation and AGNs and thereby facilitate studies of the galaxy/AGN coevolution.

G Yang↗

Exploring Carbon Mineral Systems: Recent Advances in C Mineral Evolution, Mineral Ecology, and Network Analysis

Large and growing data resources on the spatial and temporal diversity and distribution of the more than 400 carbon-bearing mineral species reveal patterns of mineral evolution and ecology. Recent advances in analytical and visualization techniques leverage these data and are propelling mineralogy from a largely descriptive field into one of prediction within complex, integrated, multidimensional systems. These discoveries include: (1) systematic changes in the character of carbon minerals and their networks of coexisting species through deep time; (2) improved statistical predictions of the number and types of carbon minerals that occur on Earth but are yet to be discovered and described; and (3) a range of proposed and ongoing studies related to the quantification of network structures and trends, relation of mineral “natural kinds” to their genetic environments, prediction of the location of mineral species across the globe, examination of the tectonic drivers of mineralization through deep time, quantification of preservational and sampling bias in the mineralogical record, and characterization of feedback relationships between minerals and geochemical environments with microbial populations. These aspects of Earth’s carbon mineralogy underscore the complex coevolution of the geosphere and biosphere and highlight the possibility for scientific discovery in Earth and planetary systems.

Carbon↗