It is possible that quantum algorithms can save time in the calculation of electron dynamics. This is because certain quantum algorithms, such as the quantum phase estimation algorithm and the quantum linear systems algorithm, can solve certain types of problems more efficiently than classical algorithms.
For complicated tasks, quantum computers offer noticeably faster computation speeds. However, there are still just a handful of so-called qubit-constrained quantum computers in existence globally. On ordinary servers, a quantum computer simulator, however, can already perform quantum computer algorithms.
In order to determine the electron orbitals and their dynamic development after a laser pulse excitation, a team at HZB used the example of a tiny molecule. The technique may theoretically be used to investigate bigger molecules that are difficult to calculate.
“These quantum computer algorithms were originally developed in a completely different context. We used them here for the first time to calculate electron densities of molecules, in particular also their dynamic evolution after excitation by a light pulse,” says Annika Bande, who heads a group on theoretical chemistry at HZB. Together with Fabian Langkabel, who is doing his doctorate with Bande, she has now shown in a study how well this works.
Error-free quantum computer
“We developed an algorithm for a fictitious, completely error-free quantum computer and ran it on a classical server simulating a quantum computer of ten Qbits,” says Fabian Langkabel.
These quantum computer algorithms were originally developed in a completely different context. We used them here for the first time to calculate electron densities of molecules, in particular also their dynamic evolution after excitation by a light pulse.
Annika Bande
To make the calculations without a true quantum computer and to compare them to conventional calculations, the researchers restricted their analysis to smaller molecules.
Faster computation
Indeed, the quantum algorithms produced the expected results. In contrast to conventional calculations, however, the quantum algorithms are also suitable for calculating significantly larger molecules with future quantum computers:
“This has to do with the calculation times. They increase with the number of atoms that make up the molecule,” says Langkabel.
Quantum algorithms are substantially faster because, unlike conventional approaches, their computation time does not scale with the number of added atoms.
Photocatalysis, light reception, and more
The study thus demonstrates a novel method for performing in-depth calculations with an extremely high spatial and temporal resolution of electron concentrations and their “response” to excitations with light. For instance, this enables the simulation and comprehension of rapid decay events, which are also essential for the operation of quantum computers composed of so-called quantum dots.
Predictions regarding the physical or chemical behavior of molecules are also conceivable, for instance when light is absorbed and electrical charges are subsequently transferred. This might make it easier to create photocatalysts that use sunlight to produce green hydrogen or to comprehend how the light-sensitive receptor molecules in the eye work.
However, it is important to note that the performance of quantum algorithms can depend on a variety of factors, such as the specific problem being solved and the characteristics of the quantum computer being used, so it is not always possible to say in advance whether a quantum algorithm will offer a significant speedup over classical algorithms.
