Suppressing Errors Enables the Next-Generation Quantum Computing Hardware
Quantum computing holds extraordinary promise, but before quantum computers can be commercialized there are challenges to be resolved. One of the most important is finding ways to identify and correct errors in quantum computer hardware. Q-CTRL aims to solve the fundamental problems facing quantum technology, improving hardware performance and accelerating pathways to useful quantum computers and other technologies. In an interview with EE times, Michael J. Biercuk, Founder & CEO, Q-CTRL, discussed why quantum error correction (QEC) algorithms and their links to low-level quantum control are critical.
Quantum computing is a new way of storing and processing information using the rules of quantum physics. When we do this, problems that are impossible to solve even on the new generation of exascale supercomputers should become easy. Right now, in laboratories all over the world, real quantum computers are in operation and under development. But these face problems related to noise and hardware instability.
Today’s machines tend to suffer hardware failures — errors in their digital components, which are called qubits — in times much shorter than a second. Companies building quantum computers such as IBM and Google have pointed out that the use of quantum error correction is crucial as we move to machines with 1,000 qubits or more.
“Quantum computing has seen tremendous strides over the last 20 years — we are now routinely seeing systems at the scale of 50 qubits being operated and industry roadmaps are planning for 1,000-qubit devices in just the next few years,” said Biercuk. He added, “but lurking quietly behind all of quantum computing’s progress remains the Achilles heel of the field — the fragility of quantum computing hardware and its susceptibility to failure. For comparison, the probability of error for a conventional transistor in a single clock cycle is something like 10-24 or lower. For the quantum analog of a transistor — the qubit — the best teams are achieving about 10-4. That’s 20 orders of magnitude worse!”
Quantum error correction is one approach that promises to help quantum technology. “It’s real and has seen many partial demonstrations in laboratories around the world, and these first steps make it clear it’s a potentially viable approach. Moving forward, our key driver must be to transform QEC from an abstract mathematical concept underpinning quantum computer science into a practically relevant routine that ultimately helps us move closer to what we actually want – real quantum computers with far fewer errors,” said Biercuk.
Noise and errors are inevitable in any quantum computer. Commonly occurring errors are due to noise in the physical qubits causing logical bit flip or phase flip errors. There is, therefore, a postulated need to employ QEC in every future implementation of a large-scale system to ensure robustness.
Quantum error correction
QEC is an algorithm involving a series of mathematical operations to identify and correct errors in quantum computers. Many experiments have taken place over time. According to leading experts in the field, 2021 could be the year in which it is convincingly demonstrated that QEC provides a net benefit in real quantum computing hardware.
“Because QEC is so foundational to the field, it has featured prominently in research and engineering in hardware as well as quantum information theory. In QEC one ‘encodes’ the information of a quantum bit across many physical systems, prompting many teams to look at how the necessary inter-qubit connectivity can be ‘hard-wired’ in circuit architecture. Similarly, the need for fast local processing and actuation has driven a new generation of custom classical electronics platforms targeting QEC – even extending to cryogenic FPGAs,” said Biercuk.
He added, “But as special as QEC is for abstract quantum computing mathematically, in practice it’s really just a form of feedback stabilization using a clever measurement scheme that identifies errors without ‘exposing’ the encoded quantum information to degradation. This realization opens new opportunities to attack the problem of error in quantum computing holistically. Instead of only researching the encoding scheme itself, we are now exploring how to merge device-level dynamic stabilization via quantum firmware with QEC, or how to leverage smart filtering algorithms in the QEC feedback loop. As in most circumstances where we are seeking to stabilize an unstable system, quite a lot can be achieved at the software layer. This is Q-CTRL’s primary area of focus, leveraging quantum control to accelerate quantum computer performance, including through increased QEC efficiency.”
Fault-tolerant QEC allows — in principle — the construction of an arbitrarily large quantum computer capable of arbitrarily long calculations. Research on QEC has made great strides in recent years by introducing mathematical tricks that lighten the workload. There is still much to be done to validate the efficiency of QEC. A major public sector research program run by the US intelligence community has spent the last four years trying to finally pass the ‘break-even’ point in experimental hardware for a single logic qubit. QEC can be described as a feedback stabilization, the same used to regulate speed while with cruise control, or to prevent walking robots from tipping over.
The challenge comes when we look at the implementation of QEC in practice. The algorithm by which QEC is performed itself consumes resources — more qubits and many operations. “Returning to the promise of 1,000-qubit machines in industry, so many resources might be required that those 1,000 qubits only yield, say five useful QEC-protected qubits. Even worse, the amount of extra work that must be done to apply QEC currently introduces more error than the benefits afforded in identifying and correcting them. Despite huge progress reducing these burdens, the most advanced experimental demonstrations show it’s still better to do nothing than to apply QEC in most cases,” said Biercuk.
He added, “Crossing the ’breakeven point’ and achieving useful, functioning QEC doesn’t mean we suddenly enter an era with no hardware errors; it just means we have fewer. QEC only totally suppresses errors if we dedicate infinite resources to the process, an obviously untenable proposition. Moreover, even forgetting those theoretical limits, QEC is imperfect and relies on many assumptions about the properties of the errors it’s tasked with correcting. Small deviations from these mathematical models (which happen all the time in real labs) can reduce QEC’s effectiveness further. This again is where a holistic approach to dealing with error in quantum computers can deliver big improvements.”
The efficient manipulation of coherent quantum hardware is a major challenge due to a variety of sources including hardware fabrication imperfections, ambient environmental noise, and even the influence of cosmic rays as shown recently by a team at MIT. As system sizes have grown from a few to a few dozen qubits, the need for new approaches to suppress the influence of these processes have grown as well.
As the complexity of quantum applications increases, there is a need for ever longer coherence times. Longer coherence times offer higher performance and higher fidelity of quantum operations, which is extremely important for quantum computing. Quantum control techniques will aid the characterization and fine-tuning of the hardware. Quantum physicists need new approaches to prevent decoherence due to noise and losses, and to error suppression. This is referred to as quantum coherence, which is at the heart of quantum information technology. To this end, quantum error correction is an essential element.
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