H00102--00A, Front mat Genesis

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H00102--00A, Front mat Genesis Page 4

by Charles Baum


  matter, energy, forces, and motions in almost every human experience.

  The power of these laws lies in their universality. Each law can be ex-

  pressed as an equation that applies to an infinite number of events,

  from the interactions of atoms to the formation of galaxies. Armed

  with these laws, scientists and engineers confidently analyze almost any

  physical system, from steam engines to stars.

  So sweeping and inclusive are these natural laws that some schol-

  ars of the late nineteenth century suggested that the entire theoretical

  framework of science had been deduced. All that remained to be dis-

  covered were relatively minor details, like filling in the few remaining

  gaps in a stamp collection. Though this turned out not to be the case—

  modern physics research has revealed new phenomena at the relativis-

  tic scales of the very small, the very fast, and the very massive—the

  classic laws do indeed still hold sway in our everyday lives.

  Yet in spite of centuries of labor by many thousands of scientists,

  we do not fully understand one of nature’s most transforming phe-

  nomena—the emergence of complexity. Systems as a whole do tend to

  become more disordered with time, but at the local scale of a cell, an

  ant colony, or your conscious brain, remarkable complexity emerges.

  In the 1970s, the Russian-born chemist Ilya Prigogine recognized that

  these so-called complex emergent systems arise when energy flows

  through a collection of many interacting particles. The arms of spiral

  galaxies, the rings of Saturn, hurricanes, rainbows, sand dunes, life,

  consciousness, cities, and symphonies all are ordered structures that

  emerge when many interacting particles, or “agents”—be they mol-

  THE MISSING LAW

  13

  ecules, stars, cells, or people—are subjected to a flow of energy. In the

  jargon of thermodynamics, the formation of patterns in these systems

  helps to speed up the dissipation of energy as mandated by the second

  law. Scientists and nonscientists alike tend to value the surprising or-

  der and novelty of such emergent systems.

  The recognition and description of such emergent systems pro-

  vides a foundation for origin-of-life research, for life is the quintessen-

  tial emergent phenomenon. From lifeless molecules emerged the first

  living cell. If we can understand the principles governing such systems,

  we may be able to apply those insights to our experimental programs.

  DESCRIBING EMERGENT SYSTEMS

  If you want to enunciate a law that characterizes emergent systems,

  then the first step is to examine everyday examples. You can observe

  emergent behavior in countless systems all around us, including the

  interactions of atoms, or of automobiles, or of ants. This universal

  tendency for systems to display increased order when lots of objects

  interact, while fully consistent with the first and second laws of ther-

  modynamics, is not addressed explicitly in either of those laws. We

  have yet to discover if all emergent systems possess a unifying math-

  ematical behavior, though our present ignorance should not seem too

  unsettling. It took more than a half-century for each of the first two

  laws of thermodynamics—describing the behavior of energy and en-

  tropy, respectively—to develop from qualitative ideas into quantita-

  tive laws. I suspect that a mathematical formulation of emergence will

  be discovered much sooner than that, perhaps within the next decade

  or two.

  Scientists have already identified key aspects of the problem. Many

  familiar natural systems lie close to equilibrium—that is, they are stable

  and unchanging—and thus they do not display emergent behavior.

  Water gradually cooled to below the freezing point equilibrates to be-

  come a clear chunk of ice. Water gradually heated above the boiling

  point similarly equilibrates by converting to steam. For centuries, sci-

  entists have documented such equilibrium processes in countless care-

  fully controlled scientific studies.

  Away from equilibrium, dramatically different behavior occurs.

  Rapidly boiling water, for example, displays complex, turbulent con-

  vection. Water flowing downhill in the gravitational gradient of a river

  14

  GENESIS

  valley interacts with sediments to produce the emergent landform pat-

  terns of braided streams, meandering rivers, sandbars, and deltas.

  These patterns arise as energetic water moves.

  Emergent systems seem to share this common characteristic: They

  arise away from equilibrium when energy flows through a collection of

  many interacting particles. Such systems of agents tend spontaneously

  to become more ordered and to display new, often surprising behav-

  iors. And as patterns arise, energy is dissipated more efficiently, in ac-

  cord with the second law of thermodynamics. Ultimately, the resulting

  behavior appears to be much more than the sum of the parts.

  Emergent patterns in water and sand may seem a far cry from liv-

  ing organisms, but for scientists studying life’s origins there’s a big pay-

  off in understanding such simple systems: Of all known emergent

  phenomena, none is more dramatic than life, so studies of simpler

  emergence can provide a conceptual basis, a jumping-off point, for

  origin-of-life research.

  QUANTIFYING THE COMPLEXITY OF

  EMERGENT SYSTEMS

  Even though emergent systems surround us, a rigorous definition

  (much less a precise mathematical formulation) remains elusive. If we

  are to discover a natural law that describes the behavior of emergent

  systems, then we must first identify the essential properties of such

  systems. But what characteristics distinguish emergent systems from

  other less interesting collections of interacting objects?

  All emergent systems display the rather subjective characteristic of

  “complexity” —a property that thus far lacks a precise quantitative defi-

  nition. In a colloquial sense, a complex system has an intricate or pat-

  terned structure, as in a complex piece of machinery or a Bach fugue.

  “Complexity” may also refer to information content: An advanced text-

  book contains more detailed information, and is thus more complex,

  than an elementary one. In this sense, the interactions of ants in an ant

  colony or neurons in the human brain are vastly more complex than

  the behavior of a pile of sand or a box of Cheerios.

  Such complexity is the hallmark of every emergent system. What

  scientists hope to find, therefore, is an equation that relates the proper-

  ties of a system on the one hand (its temperature or pressure, for ex-

  ample, expressed in numbers), to the resultant complexity of the

  THE MISSING LAW

  15

  system (also expressed as a number) on the other. Such an equation

  would in fact be the missing “law of emergence.” But before that is

  possible we need an unambiguous, quantitative definition of the com-

  plexity of a physical system. How to proceed?

  A small band of scientists, many of them associated with the Santa

  Fe Institut
e in New Mexico, have thought long and hard about com-

  plex systems and ways to model them mathematically. But their efforts

  yield surprisingly diverse (some would say divergent) views on how to

  approach the subject.

  John Holland, an ace at computer algorithms and a revered

  founder of the field of emergence, models emergent systems as com-

  puter programs with a fixed set of operating instructions. He suspects

  that any emergent phenomenon, including sand ripples, ant colonies,

  the conscious brain, and more, can be reduced to a set of selection

  rules. Holland and his followers have made great strides in mimicking

  natural phenomena with a few lines of computer code. Indeed, for

  Holland and his followers the complexity of a system is closely related

  to the minimum number of lines of computer code required to mimic

  that system’s behavior.

  A delightful example of this approach is BOIDS, a simple program

  written by California programmer Craig Reynolds that duplicates the

  movements of flocking birds, schooling fish, swarming insects, and

  other collective animal behaviors with astonishing accuracy. (To check

  it out on the Internet, just Google “BOIDS.”) Lest you think that this

  effort is idle play, remember that computer programmers of video

  games and Hollywood special effects have made a bundle on this type

  of simulated emergent behavior. Think of BOIDS the next time you

  watch dinosaur herds on the run in Jurassic Park, swarming locusts in

  The Mummy, or schools of fish in Finding Nemo.

  Physicist Stephen Wolfram, a mathematical prodigy who made

  millions in his twenties from the elegant, indispensable computer pack-

  age Mathematica, provides a complementary vision of emergent com-

  plexity from simple rules. Like Holland, Wolfram was captivated by

  the power of simple instructions to generate complex visual patterns.

  Sensing a new paradigm for the description and analysis of the natural

  world, he has spent the past 20 years developing what he calls “a new

  kind of science” (NKS for short). A mammoth tome by that title pub-

  lished in 2002 and an elaborate Web site (www.wolframscience.com)

  illustrate some of the stunning ways whereby geometric complexity

  16

  GENESIS

  may arise from simple rules. Perhaps, Wolfram argues, the complex

  evolution of the physical universe and all it contains can be modeled as

  a set of sequential instructions.

  Many other ways to view complex systems have been proposed.

  The late Danish physicist Per Bak described complex systems in terms

  of a mathematical characteristic called “self-criticality.” These systems

  evolve by repeatedly achieving a critical point at which they falter and

  regroup, like a growing pile of sand that avalanches over and over again

  as new grains are added. Santa Fe theorist Stuart Kauffman proposes

  another tack, focusing on the emergence of chemical complexity via

  competitive “autocatalytic networks,” by which collections of chemi-

  cal compounds catalyze their own formation. And Nobel laureate

  Murray Gell-Mann, who also works at the Santa Fe Institute, has re-

  cently introduced a new parameter he calls “nonextensive entropy”—

  a measure of the intrinsic complexity of a system—as a path to

  understanding complex systems.

  All these approaches and more inform the search for a law of emer-

  gence; all provide a glimpse of the answer. Yet each seems too abstract

  to apply to benchtop chemical experiments on the origin of life. An

  experimentalist needs to decide on the nitty-gritty details: What should

  be the starting chemicals at what concentrations; how acidic or basic

  the solution; what run temperatures, pressures, and times? Is there any

  way that the ideas of emergence can help?

  A classic scientific approach to discovering general principles and

  laws is to examine the behavior of specific systems. The study of simple

  systems that display emergent behavior may well point to physical fac-

  tors that lead to patterning in much more complex systems, including

  life. We can hope that observations of specific systems will eventually

  point to more general rules.

  PATTERNS IN THE SAND

  You don’t need a laboratory to observe emergent phenomena. In fact,

  you can’t go on a hike without seeing dozens of examples of emer-

  gence in action. Among my favorite emergent phenomena are inter-

  actions of water and sand, which provide a convenient and compre-

  hensible example of structures arising from the energetic interactions

  of lots of agents (not to mention a great excuse to spend the day at the

  shore). When moving water (or wind, for that matter) flows across a

  THE MISSING LAW

  17

  flat layer of sand, new patterns arise. Periodic sand ripples appear, as

  sand grains are sorted by size, shape, and density. The system thus

  becomes more orderly and patterned as energy—the flow of wind or

  water—dissipates.

  My favorite emergent sandy system lies at the base of the fossil-

  rich hundred-foot-tall cliffs that border the Chesapeake Bay’s western

  shore in Calvert County, Maryland. Fifteen-million-year-old whale

  bones, razor-sharp sharks’ teeth, branching bleached corals, and ro-

  bust fist-sized clamshells abound in the wash zone, where waves con-

  stantly wear away the soft sediments. Walks along those majestic

  formations often lead to thoughts about the factors that contribute to

  complexity.

  At times of unusually low tide, especially near a new moon in the

  cold clear winter months, receding waters expose a gently sloping pave-

  ment of ancient sediments below the base of the cliff—a formation

  called blue marl. Treacherously slippery when wet, this firm flat sur-

  face commonly accumulates a thin layer of sand—particles that dis-

  play emergent patterns when subjected to the wash of shallow water.

  Over the years, I’ve noticed four distinct factors that contribute to the

  emergence of complex sand patterning.

  Factor 1: The Concentration of Agents

  The first obvious factor in achieving a patterned, complex system is

  simply the density of sand grains—that is, the number of interacting

  particles per square centimeter of the blue marl’s surface. It’s easy to

  estimate this number by collecting almost every grain of sand from an

  area 10 centimeters square, about the size of a small paper napkin. I

  collect the sand in a plastic bag or bottle, take it back to the lab, dry it,

  and weigh the sample. Using a microscope, I count out 100 grains from

  the sample and then weigh that batch. As it turns out, the total number

  of grains per square centimeter is approximately equal to the total

  weight of sand from the 100 square-centimeter (10 × 10) area divided

  by the weight of 100 sand grains.

  I find that with fewer than about 100 sand grains per square centi-

  meter, the dusting of particles is too sparse for any noticeable patterns

  to emerge. Given the minute size of the average sand grain, typically

  less than half a millimeter in diameter, 100 grains per square
centime-

  ter provides a sparse coverage over less than 10 percent of the smooth

  18

  GENESIS

  A

  B

  C

  Patterns in sand grains emerge as the concentration of grains increases. At about a thousand grains per square centimeter (A) small, black-topped piles are observed; at a few thousand grains per square centimeter (B) discontinuous bands arise; and

  above 10,000 grains per square centimeter (C) continuous ripples cover the surface.

  blue marl surface. Increase the sand concentration to about 1,000

  grains per square centimeter, however, and an intriguing pattern of

  regularly spaced sand piles, each a centimeter or two across, appears

  on the hard blue surface. What’s more, a small circle of darker sand

  grains typically crowns each little tan pile. Evidently a minimum con-

  centration of several hundred grains per square centimeter is required

  to initiate patterning in sand.

  Increase the sand concentration slightly to a few thousand grains

  per square centimeter and you get discontinuous short bands of sand

  at right angles to the gentle back-and-forth wave motion of the shal-

  low water. As with the mini-sandpiles, each tan band is topped by a

  line of darker grains. And as sand concentration exceeds 10,000 grains

  per square centimeter, continuous, evenly spaced, black-capped ripples

  form across the hard pavement. I’ve seen this classic rippled surface

  cover hundreds of square meters of shallow water in patterns so hyp-

  notically regular that I hesitated to disturb the symmetry by walking

  on it.

  THE MISSING LAW

  19

  And that’s it. Higher concentrations of sand simply provide a

  deeper base for the regular ripples. Buried sand grains don’t partici-

  pate in the process so no new structures arise beyond the elegant, wave-

  like, periodic forms on the surface.

  This systematic behavior suggests that the concentration of inter-

  acting agents plays a fundamental role in the emergent complexity of a

  system. Below a critical threshold, no patterns are seen. As particle con-

  centrations increase, so too does complexity, but only to a point. Above

  a critical saturation of agents, we find no new behaviors.

  Similar observations have been made about other emergent sys-

  tems. One ant species— Eciton burchelli, the army ant—stays close to

 

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