The existence of a weird new phase of hydrogen in solid form has been
discovered by scientists using a computer that can learn a few quantum
tricks. Even though it is still purely theoretical for the time being, the
discovery might be able to shed some light on how matter behaves, from the
smallest scales to the internal workings of the largest planets in the
universe.
Under extreme conditions, the shape of the hydrogen molecules in this newly
discovered solid hydrogen phase, which was discovered by an international
team of researchers, changed from spheres stacked like a pile of oranges to
something that more closely resembled eggs.
In order to solidify, hydrogen often needs both extremely high pressures
and very low temperatures. The researchers discovered the unique chemical
arrangement using a cutting-edge machine learning analysis of this
particular phase shift.
According
to physicist Scott Jensen of the University of Illinois Urbana-Champaign,
"We started with the not-too-ambitious goal of refining the theory of
something we know about."
It was more interesting than that, which is unfortunate or perhaps
fortunate. This brand-new behavior started to emerge. In reality, it was the
predominant behavior at high pressures and temperatures, which prior
theories made no mention of.
An upgraded machine learning method was crucial to the research since it
could simulate the movements of thousands of atoms rather than just the
hundreds that are often used in investigations of quantum phenomena.
The
Quantum Monte Carlo
(QMC) approach, which the researchers enhanced, essentially employs random
sampling and probability theory to figure out how vast groups of atoms are
acting collectively, groupings that would be too challenging to analyze in a
real experiment.
The outcomes were then confirmed using a second computational approach,
which was better equipped to handle more atoms but had lower precision. The
fact that the results were consistent shows that the improved QMC approach
is operating as anticipated.
According to University of Illinois Urbana-Champaign physicist David
Ceperley, "Machine learning turned out to teach us a great deal." Because we
could only accommodate a limited number of atoms in our previous
simulations, we didn't trust the indications of novel behavior.
We could fully utilize the most precise techniques and determine the true
situation thanks to our machine learning model.
To put it simply, the machine learning component increased the precision
and range of the simulations the scientists could conduct by leveraging
pre-existing data and earlier simulations to improve the estimations from
subsequent ones.
In addition to being the most prevalent element in the universe, hydrogen
also has the simplest atomic structure, consisting simply of one proton and
one electron. The rest of physics can therefore be significantly impacted by
new hydrogen-related findings.
It is now too early to determine what this new solid hydrogen phase
entails, and further modeling and testing are needed to examine it in
greater detail. The study of hydrogen-rich planets like Jupiter and Saturn
is simply one use of this additional knowledge, though.
Ceperley asserts, "We should start with systems that we can attack because
we want to understand everything. "It's important to know that we can deal
with hydrogen because it's straightforward."
The research has been published in
Physical Review Letters.
