Lessons about quantum computing

12-06-2024 | Posted by Joaquín Martí

Computación cuántica

At Principia, our expertise lies in tackling continuum mechanics problems, for which we usually enlist the aid of classical computers, those which operate using bits that can be either 0 or 1. However, as forward-thinking consultants, we recognize the importance of staying abreast of emerging technologies. With an eye towards the future, we recently commissioned a course for all our technical staff on quantum computing led by Javier Machín and Carmen Pellicer.

It has been a rewarding experience, as the learning curve is always steep at the beginning and only levels off when one starts to become more competent. We have learned about qubits, and about the superposition and entanglement that distinguish quantum systems from classical ones. And we know that we must measure only at the end, lest the wave function collapses too early and loses its magic.

We now understand how to operate on the qubits with gates and circuits in a universal quantum gate computer; this is the more flexible type of quantum computer, but one that is hard to build and to maintain the stability of qubits. We also understand how a quantum annealer operates; this type of computer is essentially oriented to solving problems that can be framed as energy minimisation tasks, but it is easier to build a stable quantum annealing processor and qubits.

Amidst our exploration, we couldn’t help but ponder the fate of quantum computing’s promise. There is a longstanding jest among physicists about fusion energy always being 20 years away, suggesting an eternal promise yet to be fulfilled. On the other hand, artificial intelligence (AI) has in recent years gone from uncertain promise to delivering a wealth of goods

computación cuánticaIn this context the trajectory of quantum computing prompts reflection. After all, Shor’s algorithm, hailed as a potential game-changer for its ability to factorise large numbers efficiently and threaten RSA encryption, has been around for three decades; yet its tangible achievements are modest, the largest number factorised using it was 21 in 2012. Similarly, Grover’s algorithm, designed for searching unsorted databases, is nearly as old and has yet to showcase transformative breakthroughs. And those are the two more famous algorithms aiming to provide quantum advantage.

Admittedly, the problem lies with the hardware, not the algorithms. But the comparison begs the question: Will quantum computing suffer a fate of perpetual postponement, as fusion energy has so far? Or are we on the brink of a breakthrough that, as is occurring with AI, will revolutionise the field? As consultants navigating the frontier of technological advancement, these questions spur us to delve deeper, to anticipate the possibilities and the challenges that lie ahead in realising the full potential of quantum computing. A number of major corporations are certainly investing in the concept, see Project CUCO in Spain as an example.

As a byproduct of our course, we are now capable of maintaining a meaningful discourse about Schrödinger´s cat and the basics of quantum computing, an undeniable improvement compared to the previous state of affairs.

It may interest you