The Classical Advances Needed to Make Quantum Computers Tick

Quantum computers promise to one day solve problems beyond the most powerful supercomputers imaginable. But it’s often underappreciated how much classical computing it takes just to operate these machines. As qubit counts rise, innovations in this supporting infrastructure will be essential if they’re to live up to their promise. To prepare for the scale of quantum computers the industry is working towards, many companies are also gearing up the classical hardware, and software, required to support them. In April, Nvidia announced new AI-based software to accelerate the classical tasks that enable quantum computers. Sydney-based quantum software company Q-CTRL has developed an automatic calibration algorithm for quantum computers, and is now leveraging Nvidia’s agent-based system. Other companies, including IBM Quantum , Cambridge, UK-based which develops quantum-error correction company Riverlane , and Google Quantum AI , are developing similar tools. The role of classical in quantum Digital computer chips are marvels of engineering, operating flawlessly out of the box and capable of trillions of operations without error. The quantum bits, or qubits, at the heart of a quantum computer, by contrast, are temperamental and unreliable, requiring regular calibration and complex error-correcting schemes to keep them on track. Calibration and error-correction are fundamentally classical, not quantum, problems, and they require dedicated classical hardware to solve. As quantum computers get bigger the scale of those resources will need to rise in lockstep. That means that for the foreseeable future, quantum computers are going to be hybrid devices with a healthy dose of classical computing on the side. “The cheapest and fastest way to execute most computer programs is to run them on a classical computer – even if a quantum computer is available,” says Adam Zalcman , a quantum software engineer at Google Quantum AI. “This is true of most of the information processing involved in running a quantum computer itself...therefore, I expect that every practical and efficient quantum computer architecture will incorporate fast classical devices.” Tuning quantum hardware While the transistor has cemented its place as the foundational component of classical chips, the qubits at the heart of a quantum computer come in many flavors – superconducting circuits, trapped ions , neutral atoms , even individual photons . Using them for computation requires a painstaking calibration process to turn the “bare metal” of the underlying hardware into a qubit that can be controlled to run quantum circuits, says Jay Guilmart , lead product manager at Q-CTRL. Calibration has two stages. The first, known as “bring up”, determines the frequency at which each qubit resonates, how long it holds its quantum state, its sensitivity to control pulses, and the strength of its interactions with neighboring qubits. All of these factors determine its error propensity and response to control signals. Done by hand, the process still requires someone with a PhD, and can take days or even weeks, says Guilmart. This isn’t a scalable solution and so there’s a growing drive to automate the process. This is challenging because every step relies on results from the previous step. So rather than relying on a predefined script, Q-CTRL has therefore built intelligent calibration software that examines the result of each measurement, diagnoses failures, and adjusts the approach before retrying. “After each step, we analyze that data and we say, are we okay to proceed to the next step? Do we have to go back to the previous step? Do we have to re-recreate this step?” says Guilmart. Calibration is also not a one-and-done process: key parameters drift over time, gradually degrading performance. Q-CTRL’s software performs “runtime recalibration” to nudge things back into place, but there’s a limit to how much on-the-fly adjustment is practical. “If I’m running a recalibration, I’m not running a circuit,” he says. “Even though I’m maintaining some high system state and high fidelities, if it takes all of my uptime it’s worthless.” Decoding errors in real-time Even a well-calibrated quantum computer remains fault-prone, which is why companies are investing heavily in quantum error correction (QEC). This typically involves encoding quantum information across large numbers of physical qubits in their shared state—a “ logical qubit “—so that errors in individual qubits can be detected and compensated for without destroying the encoded information. Because measuring a qubit directly collapses its quantum state, errors are detected via “parity checks” that query whether pairs of qubits share the same state. This produces a series of measurements known as a “syndrome”, which classical algorithms called decoders analyze to locate errors. The process must happen extremely quickly.