Algorithms on the Path to Quantum Advantage

Quantum algorithm company Phasecraft is partnering with Google, IBM and Rigetti to reduce the timescale for quantum advantage in several sectors by developing efficient algorithms. The company aims to get the most out of near-term quantum computers and inform the development of next-generation hardware.

U.K. Research and Innovation (UKRI) recently awarded Phasecraft two grants: funding a collaboration between Phasecraft, Rigetti, and BT Group and one supporting a collaboration between University College London and Oxford PV to research the development of near-term quantum computing for photovoltaic materials modeling.

Phasecraft director and cofounder Ashley Montanaro discusses the importance of government funding for quantum, collaborations with end users and hardware manufacturers, and the need to be realistic about the expectations of quantum computing.

Enter Quantum: What are Phasecraft’s aims?

Ashley Montanaro: Phasecraft is a quantum algorithms company. We’re trying to enable some of the applications of quantum computing to solve important problems, such as modeling materials, which are beyond the capacity of classical computing technologies.

We're aiming to get the most out of the near-term quantum computers that we have now, or that we might have in the next few years, as opposed to quantum computers that will exist in 20 or 30 years. But to make these applications happen, we need to think hard about how to squeeze all the performance that we can out of these devices because they're still very limited compared with how quantum computers will be in the long term.

What use cases are you working on?

We've got several collaborations going on with companies in areas where we think that quantum computing is going to be particularly important. We feel that one of the most important application domains for quantum computing in the near future is going to be the simulation of quantum mechanical systems. These are inherently tough to solve for standard computers, but also important to solve because quantum mechanics underpins our universe.

We are interested in the simulation of material systems, and we think that two of the most important applications within that are simulating batteries and simulating solar cells. That's why we've set up partnerships with Johnson Matthey, experts in battery materials and design, and Oxford PV, experts in solar cells, and photovoltaics. We're working with them to understand the best applications in these areas for quantum computers.

We also have an upcoming partnership with BT where we're going to be using Rigetti quantum computers to solve hard optimization problems that are relevant to the telecoms industry and elsewhere, which we also think is an interesting application domain.

You recently received funding from UKRI for these two projects. Why is government funding important for companies trying to commercialize quantum?

We've been successful in five grant applications through UKRI. For us, the thing that is incredibly important about these schemes is as well as the financial support, they enable collaboration with companies. They provide a vehicle for us to work with some top-notch end users and hardware companies.

The project with Rigetti and BT combines a hardware company, the end user and Phasecraft as the algorithms company. How do you work together and what is the goal?

The goal here is to understand the potential of quantum computing to solve hard optimization problems including new algorithm design. We recently showed substantial performance improvements using quantum computing to solve this fundamental problem called Boolean satisfiability, which is a very hard optimization problem to solve.

It's going to be both new algorithmic developments like that and implementing proof of principle experiments on quantum hardware provided by Rigetti. And that's all sort of tied together with a focus on real-world applications provided by BT who are experts in telecommunications networks and have a lot of hard and interesting optimization problems to solve in that domain.

The second project is with UCL and Oxford PV. How do quantum computers solve quantum physics problems better than classical computers?

Quantum mechanics is inherently difficult to solve on a normal computer because if you want to write down a quantum state of end particles, the amount of information you need grows exponentially with the number of particles. Quantum computers on the other hand can represent these sorts of systems natively so we would expect that this could enable us to get a significant performance enhancement for simulating these systems.

When we have a physical system, like a solar cell or maybe a battery, if you want to simulate this accurately, if you want to understand the physics, the quantum effects, of what's going on in that system. You might attempt to come up with a rough model classically, but what the expert end users tell us is that this is not sufficient for the problems that they want to solve.

Some experiments still need to be done in the lab rather than within the computer because the classical simulation technology is just not sufficiently accurate, and that's what we would like to enable on a quantum computer for end users like Oxford PV.

What is your advice for a company considering adopting quantum?

We need to be realistic about the promise and expectations of quantum computing. We believe quantum computers have not delivered significant commercial value in the sense of solving a problem that is beyond the capability of what businesses can do now.

However, now is the time for companies to get into understanding quantum computing and to work with experts, perhaps like us, who are trying to make these applications happen. The point where quantum computing is solving practical, important problems is very nearby.

If you look at the hardware roadmaps from companies like Google and IBM, they have some impressive plans for the coming few years. If these are realized, then we really will be at the point where companies are going to have to sit up and take notice of quantum computers that are useful to them.

Now's the time for them to get involved, to shape this transition and to be ahead of the curve rather than a few months or years behind it.