Google is all set to dominate the race for quantum supremacy with its Bristlecone chip.
On Monday, tech giant Google introduced to the world its newest quantum processor: the Bristlecone chip. The company is reportedly optimistic that their processor would pave the way for quantum computing to go mainstream.
The processor was presented by the Google Quantum AI Lab at the annual American Physical Society meeting in Los Angeles, California. In a blog post written by Julian Kelly, a research scientist at the Quantum AI Lab, he said:
“Today we presented Bristlecone, our new quantum processor, at the annual American Physical Society meeting in Los Angeles. The purpose of this gate-based superconducting system is to provide a testbed for research into system error rates and scalability of our qubit technology, as well as applications in quantum simulation, optimization, and machine learning.”
The Bristlecone chip reportedly features a 72-qubit gate-based superconducting system. Before its arrival, the most powerful quantum computing chip was the 50-qubit processor developed by IBM. It is now clear that the crown has been snatched away from the latter.
The Bristlecone Chip
In his post, Kelly explained how the Google Quantum AI Lab team developed the Bristlecone chip. The processor was reportedly created by scaling the company’s former 9-qubit system which has a 1 percent low error rate for readout. The new processor uses the same “scheme for coupling, control, and readout, but is scaled to a square array of 72 qubits.”
“Our strategy is to explore near-term applications using systems that are forward compatible to a large-scale universal error-corrected quantum computer,” Kelly further stated.
The Bristlecone chip has outdone its 9-qubit chip predecessor when it comes to quantum error correction, a significant factor that keeps hypersensitive qubits from getting corrupted.
“We are cautiously optimistic that quantum supremacy can be achieved with Bristlecone.” ~ Julian Kelly
According to Kelly, Bristlecone was primarily developed as a testbed for research works involving quantum system error rates, Google qubit technology’s scalability, quantum simulation, optimization, and machine learning.
With the Bristlecone chip’s 72-qubit size, the team aims to demonstrate quantum supremacy in the future, use surface code to investigate first and second order error-correction, and be able to facilitate quantum algorithm development on actual hardware.
However, before investigating specific applications, Kelly pointed out that it is vital to quantify a processor’s capabilities first. For this, Google’s Quantum AI Lab theory team developed a benchmarking tool capable of doing such complicated task.
“We can assign a single system error by applying random quantum circuits to the device and checking the sampled output distribution against a classical simulation,” Kelly went on to say. “We can assign a single system error by applying random quantum circuits to the device and checking the sampled output distribution against a classical simulation.”
While the size of the Bristlecone chip may somehow help mitigate qubit error rates, Google said that quantum computing is not just about qubits.
Apparently, operating devices like the Bristlecone at low system error also requires a balance between a full stack of technology from software and control electronics to the processor itself. This needs careful system engineering over several iterations, Kelly said.
Aside from Google, other companies like IBM and Microsoft have been vocal about their quantum computing efforts. For instance, IBM has reportedly been working on a general-purpose quantum computer for utilization by businesses in the future.
With Google’s latest quantum processor, the race for quantum supremacy has become tighter than ever before.