Caltech's Bren Professor of Chemistry, Garnet K Chan is on a mission to develop new algorithms that'll take quantum computing one step further.
Caltech's Bren Professor of Chemistry, Garnet K Chan is on a mission to develop new algorithms that'll take quantum computing one step further.

Researchers at Caltech develop new algorithm to make quantum computers more efficient

ANI | Updated: Dec 29, 2019 18:39 IST

California [USA], Dec 29 (ANI): Quantum computers aren't that different from classical computers in the sense that just like their older siblings their functioning is dependent on the instructions we give them.
This new milestone in computing opens endless prospects for the future but the instructions and algorithms that are necessary to run them are still in their infancy and not advanced enough to be of any substantial use.
Caltech's Bren Professor of Chemistry, Garnet K Chan is on a mission to develop new algorithms that will take quantum computing one step further.
In an interview on Caltech's (California Institute of Technology) website, Chen talked about the new research paper he published recently, that proposes a new algorithm, which will enable quantum computers to carry out simulations in physical sciences.
This study has been co-authored by his colleagues Fernando Brandao, Bren Professor of Theoretical Physics, and Austin Minnich, professor of mechanical engineering and applied physics.
This new algorithm is an evolution of a pre-existing one that is already used in classical computing. The older algorithm -- imaginary time evolution -- has now been re-tailored to run on quantum computers and is rather appropriately termed as 'quantum imaginary time evolution.'
Chen explains that Quantum computing has a vast potential in terms of its application in physical sciences. Scientists in this field are eager to find a means to simulate the ground states of molecules and materials.
"Our new paper proposes a way to calculate ground states of Hamiltonians that runs on near-term quantum computers with very few resources."
Hamiltonian depicts the energy state of a system and the most stable state of the problem exists at the ground state of the Hamiltonian. A majority of physical systems under normal conditions exist closer to the ground state.
For instance, water prefers to exist in a liquid state instead of in the form of plasma. Hence plasma is not the ground state of water.
The study of ground states is of great relevance if one wishes to understand the world in its ordinary form.
The problem with quantum computers is that they decohere after a short period of time and have to be recalibrated so that calculations can be performed again. So, a way had to be figured out to execute calculations efficiently enough so that the required solution is quickly acquired before the computer decoheres.
Explaining how his algorithm solves this problem, Chen says: "There have been many proposals for how to obtain ground states on quantum computers. One of the first was by Alexei Kitaev [Caltech's Ronald and Maxine Linde Professor of Theoretical Physics and Mathematics], but unfortunately, that algorithm, known as phase estimation, requires too many instructions and cannot be implemented before current quantum computers decohere. Another way, called the variational approach, is very simple to implement but in practice turns out not to be so accurate. We wanted to find a way that could be potentially as accurate as phase estimation but which could also be practically programmed on today's quantum computers."
Chen believes that we still don't know exactly where quantum computers find their best use but this can change with further research and innovation
"Because we can barely use them right now, part of the answer lies in developing efficient programs that can be run on them in very little time. Our work provides a basis for assessing the capabilities of quantum computers as they are now, which will help tell us what we can expect in the future." (ANI)

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