The net result is a much faster operation that involves many fewer doors. That’s important because errors in quantum hardware increase as a function of both time and the number of operations.
The researchers then used this approach to explore a chemical, MN4EITHER5CA, that plays a key role in photosynthesis. Using this approach, they showed that it is possible to calculate what is called the “spin ladder,” or the list of the lowest energy states that electrons can occupy. The energy differences between these states correspond to the wavelengths of light they can absorb or emit, so this also defines the spectrum of the molecule.
Faster, but not fast enough
We are not ready to run this system on today’s quantum computers, as the error rates are still too high. But because the operations needed to run this type of algorithm can be done so efficiently, error rates don’t have to drop much before the system becomes viable. The main determinant of whether you will encounter an error is how far down the time dimension you run the simulation, plus the number of measurements of the system that takes the most time.
“The algorithm is especially promising for short-term devices that have favorable resource requirements quantified by the number of snapshots (sample complexity) and maximum evolution time (coherence) required for accurate spectral calculation,” the researchers wrote. .
But the work also makes a couple of bigger points. The first is that quantum computers are fundamentally different from other forms of computing that we have developed. They are able to run things that look like traditional algorithms, where operations are performed and an outcome is determined. But they are also quantum systems that are growing in complexity with each new generation of hardware, making them excellent for simulating other quantum systems. And there are a number of hard problems involving quantum systems that we would like to solve.
In some ways, we may only be beginning to scratch the surface of the potential of quantum computers. Until very recently, there were many hypotheticals; Now it looks like we’re on the cusp of using one for some potentially useful calculations. And that means more people will start to think about clever ways we can solve problems with them, including cases like this, where hardware would be used in ways its designers haven’t even considered.
Nature Physics, 2025. Doi: 10.1038/s41567-024-02738-z (about two).