Honeywell has upgraded the commercial trapped ion quantum computer System Model H1 and achieved a quantum volume of 512. This is four times higher than when it was released in September 2020 with a quantum volume of 128. This is the highest measured on a commercial quantum computer to date. It is the third time in nine months Honeywell has set a record for quantum volume on one of its systems.
This high performance, combined with low error mid-circuit measurement, provides unique capabilities with which quantum algorithm developers can innovate.
The average single-qubit gate fidelity for this milestone was 99.991(8)%, the average two-qubit gate fidelity was 99.76(3)% with fully-connected qubits, and measurement fidelity was 99.75(3)%. We ran 300 circuits with 20 shots each, using standard QV optimization techniques to yield an average of 76.82 two-qubit gates per circuit.
The System Model H1 successfully passed the quantum volume 512 benchmark, outputting heavy outcomes 73.32% of the time, which is above the 2/3 threshold with 99.54% confidence.
Honeywell has claimed they will improve Quantum Volume to 640,000 Path by 2025. IBM was talking QV 100,000 by 2030.
Algorithm and hardware improvements will enable software and hardware quantum simulations (not quantum machines but regular computers running the quantum problems) to achieve QV 4096 and possibly far beyond. This means non-quantum systems can continue to compete against quantum computers. There is no hard line where regular computers get beat by quantum systems. There is a significant race to improve the science and algorithms in all areas.
Quantum volume measures the number of qubits, stability of the qubits, connectedness and several other characteristics that affect what can be solved.
In 2018, Alibaba and the University of Michigan published “Classical Simulation of Intermediate-Size Quantum Circuits”.
Computing a single amplitude of an 8 × 8 qubit circuit with depth 40 was previously beyond the reach of supercomputers. Their algorithm can compute this within 2 minutes using a small portion (≈ 14% of the nodes) of the cluster.
They successfully simulating quantum supremacy circuits of sizes
9×9×40 (QV 512),
10×10×35 (QV 1024),
11 × 11 × 31 (QV2048), and
12 × 12 × 27 (QV4096).
They did that using 131072 processors and 1 petabyte of memory.
Quantum Computing Reports explains the problem with Quantum Volume:
1. The test is all based upon a square circuit configuration, but very few quantum programs really have a square configuration. Some of the algorithms being developed for NISQ computers such as VQE and QAOA, are wide and shallow. They use a larger number of qubits but only a few levels of gate depth. Other algorithms may use a much larger number of gate operations versus the numbers of qubits. For example, Shor’s algorithm to factor 2048 bit number using about 4100 logical qubits but needs 8.6 billion gate operations. (Note that is based upon logical or error-free qubits and not physical qubits).
2. The measurement distorts how fast power is increasing. If the square circuits were solving an office space problem. QV64 Honeywell is with 6×6 circuit solution is about 44% more valuable (36/25) than the QV32 (5×5) and not 100%.
3. The focus for anyone developing a quantum computer should be how to make it achieve quantum advantage and solve problems better than a classical computer. Since classical computers are error-free, the equivalent quantum volume for a quantum program running on a quantum simulator on a classical computer can be very high. In 2019, Google ran a quantum benchmark on the Summit supercomputer at the Oak Ridge National Lab that successfully calculated the results of a 49×40 circuit. So the equivalent QV for Summit would be 240 or about 1.1 trillion.
Written By Brian Wang, Nextbigfuture.com
Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
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