of the greatest challenges in all of science is to understand
life. How does it arise? How does it evolve and change over
time? How does it work?
The answers are proving to be complex in the extreme, because
life does nothing in a simple way. But then, that may be
why more and more physicists are
being drawn to this challenge: they can bring with them decades
of experience in understanding complex systems generally.
Even leaving life aside, after all, the world is rife with complex
systems. Examples range from turbulence in fluids to
the interaction of particles within atoms, and from economic
markets to the origins of the large-scale structure of
the universe. Much of physicists’ insight into this
kind of complexity has come—of course—through
rapid advances in computer simulation. But just as important
has been their deeper understanding of the nonlinear
mathematics that describe complex systems. The hallmark
equations is that they are (usually) simple to write
down but can have surprising and unexpected results. For
example, a nonlinear system may suddenly go from apparent
stability to completely chaotic behavior—one reason
why nonlinear mathematics is often referred to in the popular
media as chaos
The physicists’ work, in turn, is part of a much
broader effort to understand complexity that cuts across
a wide variety of disciplines, from mathematics and computer
science to economics and anthropology. NSF has been a major
supporter of this effort over the years—perhaps most
famously for its early backing of the independent Santa
Fe Institute in New Mexico, but also through its many
grants to individual academic researchers, as well as through
its creation of centers for complexity research at Northwestern
University, the University
of Illinois and elsewhere.
To see how these techniques might apply to life, consider
the human genome—or
for that matter, any of the dozens of other
genomes that are now being sequenced, from chimp to mouse
to mustard weed. The problem is that a genome by itself is
just a blueprint, a parts list, a set of instructions for
building the zillions
of protein molecules that actually do most of the work
in the cell. What’s missing is a deep understanding
of how these components go together to create a working system.
And the reason it’s missing is complexity. Even the
simplest chemical process in the cell may involve dozens
of proteins made by dozens of genes, each of which is regulated
many other genes.
Thus the opening for physicists. The hope is that by applying
a combination of computer modeling and complexity analysis
to these multiple interactions, they can help shed light
on some key questions. For example, what cellular conditions
cause viruses to replicate and infest their host or instead,
lie dormant to wait for conditions to improve?
Complexity analysis may also explain how organisms manage
to survive even though the precise genetic blueprint varies
from one individual to the next. Rather than the
tightly controlled chemistry of a test-tube experiment, organisms
from bacteria to humans may have evolved complex networks
of reactions that get the job done, despite a wide range
of individual variation.
Similar nonlinear interactions exist in ecology, and the
physics of complex systems may help unravel the principles
that govern how populations vary over time. Species thrive
or decline depending on complex interactions among individuals,
competition from other species and environmental conditions
beyond their control, ranging from the phase of the moon
to the harshness of the weather.
At the farthest frontier of complexity research, physicists
are also contemplating the physical laws from which human consciousness emerges.
Competing theories abound. Perhaps consciousness emerges
from the biochemical pathways of intertwined neurons once
brain-size passes a certain threshold. Or perhaps the brain
uses microscopic structures within neurons to create a highly
advanced quantum computer, able to perform complex calculations,
such as those needed to talk, catch a ball or ponder the
meaning of life.
Pushing physics advances in modeling complex systems toward
better understanding of how life works will be a major research
challenge for the 21 st century.
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