People of ACM - Fred Chong

March 24, 2026

Many say we are on the cusp of a "quantum revolution." What have been the key advances in the last 5-10 years that have gotten us to this point?

For the first time, we have quantum hardware of non-trivial size (100+ physical quantum bits—qubits) and, more importantly, demonstrations of quantum error correction on these machines which have shown that we can reduce the raw error rate. We have multiple technologies that have line-of-sight to scale to 1000s or more qubits, with many companies pursuing aggressive machine roadmaps over the next few years. Once these physical qubits can implement 100s of reliable logical qubits, quantum advantage on a range of applications will be enabled.

A stated goal of the EPiQC project is to "reduce the current gap between theoretical algorithms and quantum computing architectures." What has been one of the longstanding challenges here?

The biggest challenges have been errors when operating on qubits, especially operations between two or more qubits. Qubits are engineered to maintain their state and to isolate from the external environment, but operations on qubits are deliberately controlled  from the outside by the user. EPiQC developed many software techniques to minimize the number of operations needed for an application and to create more reliable operations by tailoring to the physics of each machine. The combination of these techniques can save many orders of magnitude in the operations and qubits needed to run an application. Such savings is equivalent to years of hardware improvements, dramatically shortening the timeline to practical applications.

While quantum technology has been improving rapidly, classical high-performance computers (HPC) are also steadily becoming more powerful and can now perform a mind-boggling number of calculations per second. How will the quantum and HPC fields interact going forward?

HPC is critical to solving real applications with quantum computers. That is because there are a limited number of quantum algorithms that give quantum computers an advantage over classical machines. The key is to build an application around one or more of these quantum kernels. For example, we are working on cancer biomarker identification for a research program called Q4Bio which is funded by Wellcome Leap, and we find that the best classical solvers start to produce suboptimal solutions when examining 100 to 200 candidate biomarkers. We use a quantum algorithm that does a good job of reducing larger problems until they are small enough for the classical machines to start doing a good job again. 

There has been much public discussion about how the latest technologies (especially the data centers needed to run AI applications) require a great deal of energy. How will the continued growth of quantum computing impact the environment?

Assuming we are successful in building quantum computers that can solve problems that are very hard for classical machines, quantum computing could reduce the environmental impact of solving many HPC problems. A small quantum computer could solve portions of problems that would require substantial runtime from a large datacenter. From a sustainability perspective, room-temperature technologies (neutral atoms and ions) would have some advantages over cryogenic technologies (superconductors) that use a lot of energy for their dilution refrigerators. Greater efficiency in solving important problems, however, can lead to more demand and the conundrum of the Jevons Paradox, such as when efficient steam engines led to greater demand for coal.

Ten years from now, how will quantum computers be reshaping the tech landscape?

Quantum computers will most likely not replace classical computing but serve as special-purpose accelerators (quantum processing units or QPUs) which can efficiently solve certain subproblems that are intractable for classical machines. Solving these problems could lead to a number of societal benefits, including improvements in materials, batteries, medical treatment, medicines, and agriculture.