In a step toward practical quantum computing, researchers have designed a system that can verify when quantum chips have accurately performed complex computations that classical computers can’t.
Quantum chips perform computations using quantum bits (qubits) that can represent the two states corresponding to classic binary bits — a 0 or 1 — or a “quantum superposition” of both states simultaneously. The unique superposition state can enable quantum computers to solve problems that are practically impossible for classical computers.
Full-scale quantum computers will require millions of qubits, which isn’t yet feasible. In the past few years, researchers have started developing Noisy Intermediate Scale Quantum (NISQ) chips that contain around 50 to 100 qubits. That’s just enough to demonstrate “quantum advantage,” meaning the NISQ chip can solve certain algorithms that are intractable for classical computers. Verifying that the chips performed operations as expected, however, can be very inefficient. The chip’s outputs can look entirely random, so it takes a long time to simulate steps to determine if everything went according to plan.
The novel protocol efficiently verifies that an NISQ chip has performed all the right quantum operations. The work traces an output quantum state generated by the quantum circuit back to a known input state. Doing so reveals which circuit operations were performed on the input to produce the output. Those operations should always match what was programmed. If not, the information can be used to pinpoint where things went wrong on the chip.
At the core of the new protocol, called Variational Quantum Unsampling, the output quantum state is broken into chunks, unscrambling layer by layer. For this, the researchers took inspiration from neural networks — which solve problems through many layers of computation — to build a quantum neural network (QNN) where each layer represents a set of quantum operations.
To run the QNN, they used traditional silicon fabrication techniques to build a 2 × 5-millimeter NISQ chip with more than 170 control parameters — tunable circuit components that make manipulating the photon path easier. Pairs of photons are generated at specific wavelengths from an external component and injected into the chip. The photons travel through the chip’s phase shifters — which change the path of the photons — interfering with each other. This produces a random quantum output state that represents what would happen during computation. The output is measured by an array of external photodetector sensors.
That output is sent to the QNN. The first layer uses complex optimization techniques to dig through the noisy output to pinpoint the signature of a single photon among all those scrambled together. Then, it unscrambles that single photon from the group to identify what circuit operations return it to its known input state. Those operations should match exactly the circuit’s specific design for the task. All subsequent layers do the same computation — removing from the equation any previously unscrambled photons — until all photons are unscrambled.