Although no one has achieved this goal yet, we calculate quantum supremacy can be comfortably demonstrated with 49 qubits, a circuit depth exceeding 40, and a two-qubit error below 0.5%. These random circuits must be large in both number of qubits as well as computational length (depth).

If a quantum processor can be operated with low enough error, it would be able to outperform a classical supercomputer on a well-defined computer science problem, an achievement known as quantum supremacy. 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. Our theory team has developed a benchmarking tool for exactly this task. The intended research direction of the Quantum AI Lab is shown in red, where we hope to access near-term applications on the road to building an error corrected quantum computer.Д«efore investigating specific applications, it is important to quantify a quantum processorвЂ™s capabilities. We chose a device of this size to be able to demonstrate quantum supremacy in the future, investigate first and second order error-correction using the surface code, and to facilitate quantum algorithm development on actual hardware.ДўD conceptual chart showing the relationship between error rate and number of qubits. This device uses the same scheme for coupling, control, and readout, but is scaled to a square array of 72 qubits. The guiding design principle for this device is to preserve the underlying physics of our previous 9-qubit linear array technology 1, 2, which demonstrated low error rates for readout (1%), single-qubit gates (0.1%) and most importantly two-qubit gates (0.6%) as our best result. On the right is a cartoon of the device: each вЂњXвЂќ represents a qubit, with nearest neighbor connectivity. 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.Д«ristlecone is GoogleвЂ™s newest quantum processor (left). Today we presented Bristlecone, our new quantum processor, at the annual American Physical Society meeting in Los Angeles. Crucially, the processor must also have low error rates on readout and logical operations, such as single and two-qubit gates. In order for a quantum processor to be able to run algorithms beyond the scope of classical simulations, it requires not only a large number of qubits. Our strategy is to explore near-term applications using systems that are forward compatible to a large-scale universal error-corrected quantum computer. The goal of the Google Quantum AI lab is to build a quantum computer that can be used to solve real-world problems. Posted by Julian Kelly, Research Scientist, Quantum AI Lab

Netop vision pro 9 license key