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Largest
simulation an entire gene of DNA, LANL image.
Given just
how important genes are, it’s somewhat surprising that we have very little
direct imagery of them functioning. The problem is that genes are so small and
work so quickly that taking any photos or videos of them is nearly impossible.
That’s why a group of researchers at Los Alamos National Laboratory turned to a
computer simulation as the next best thing.
Using the Trinity supercomputer at Los Alamos, the researchers
created a simulation of a single nanosecond of a gene. If one nanosecond sounds
short to you—that’s about a billionth of a second—remember that the simulation
contains over a billion atoms. For the researchers to simulate this gene, they
have to not only simulate those individual atoms but also the electrical and
chemical interactions between each pair of them. That’s an enormous amount of
calculation. (Full story)
LANL
researchers simulate billion-atom biomolecule
HPCwire
Detail
of the billion atom DNA model, LANL image.
Researchers
from Los Alamos National Laboratory, RIKEN Center for Computational Science in
Japan, the New Mexico Consortium, and New York University have successfully
created the first billion-atom simulation of an entire gene using a new
approach they devised that reduces computational costs for such large
simulations.
“It is important to understand DNA at this level of detail
because we want to understand precisely how genes turn on and off,” said
Karissa Sanbonmatsu, a structural biologist at Los Alamos and author of the
paper. “Knowing how this happens could unlock the secrets to how many diseases
occur.” It’s worth noting there is enough DNA in the human body to wrap around
the earth 2.5 million times, which means it is compacted in a very precise and
organized way. (Full story)
See the video
Also from United Press International and PhysOrg
The
hidden seismic symphony in earthquake signals
Many of the
recent headline-grabbing developments in machine learning hinge on an approach
called deep neural networks. Yet a simpler and more transparent form of machine
learning called decision trees is unlocking impressive new scientific
discoveries. In the case of our earthquake research at Los Alamos National
Laboratory, a machine-learning process involving decision trees has revealed
previously unsuspected physics principles that a deep neural network would have
obscured and humans poring over data sets probably never would have noticed. To
our surprise—and delight—this approach has led to a breakthrough in probing the
mechanics of earthquakes, which will certainly advance our pursuit of the holy
grail of geoscience: earthquake forecasting. (Full story)
Could
machine learning be the key to earthquake prediction?
Earthquakes
of magnitude 7.0 or higher between
1900 and
2013, USGS image.
Five years
ago, Paul Johnson wouldn’t have thought predicting earthquakes would ever be
possible. Now, he isn’t so certain. “I can’t say we will, but I’m much more
hopeful we’re going to make a lot of progress within decades,” the Los Alamos
National Laboratory seismologist says. “I’m more hopeful now than I’ve ever
been.”
The main reason for that new hope is a technology Johnson
started looking into about four years ago: machine learning. Many of the sounds
and small movements along tectonic fault lines where earthquakes occur have
long been thought to be meaningless. But machine learning—training computer
algorithms to analyze large amounts of data to look for patterns or signals—suggests
that some of the small seismic signals might matter after all. (Full story)
Seeing
the quantum
Light
generated by spontaneous parametric
down-conversion,
from Aeon.
I spent a
lot of time in the dark in graduate school. Not just because I was learning the
field of quantum optics – where we usually deal with one particle of light or
photon at a time – but because my research used my own eyes as a measurement
tool. I was studying how humans perceive the smallest amounts of light, and I
was the first test subject every time. Author Rebecca Holmes is a physicist and
staff scientist at Los Alamos National Laboratory. (Full story)
SuperCam developed in Los Alamos to be used on rover in 2020 mission to Mars
SuperCam
undergoing final preperations.
On Monday,
a camera developed here in New Mexico makes its first stop on its mission to
Mars. Researchers at the Los Alamos National Laboratory say the SuperCam will
be a key feature on the 2020 Mars rover. It will be attached to the rover
currently at NASA's Jet Propulsion Laboratory in Pasadena, Calif. before
heading to space next year.
"SuperCam is like a geological observatory on Mars,"
said Roger Wiens, principal investigator on the SuperCam at Los Alamos National
Laboratory. The future of space exploration is in the works -- and it's
happening right here in New Mexico with the development of the SuperCam. (Full story)
In
the Lab: Building the next generation of experts
John
Kramer, LANL photo.
In a woodsy
part of the Los Alamos National Laboratory where elk linger outside his
building, John Kramer is guiding the next generations of high explosives
experts.
The lab’s esteemed explosives enclave has been Kramer’s turf
since he was 19, mopping up water in big bays and growing accustomed to the
shaking, rumbling world around him. Now, 37 years later, Kramer is a revered
R&D engineer who holds two patents and keeps the lab’s detonator powder
production plant humming to meet growing demands. (Full story)
