At the recent Q2B conference it was emphasized that qubit quality is a very important factor in creating a viable quantum computer. So kudos to IBM and Rigetti for documenting the specifications of their respective 20 qubit and 19 qubit chips. However, they are using different formats making it difficult to compare so we decided to put them into a common format. These parameters are shown below in the three tables below. Table 1 shows the qubit count, qubit connectivity, T1 and T2 or T2* times. Table 2 shows the single qubit gate fidelity, the two qubit gate fidelity and the readout fidelities. And Table 3 shows the sources of the data for the first two tables. Note that all of this data is for physical qubits without any error correction.
Although we don’t have complete data for Google’s implementations, they recently provided some information at the Adiabatic Quantum Computing Conference (AQC 2018) where they compared metrics from their 5 and 9 qubit test chips with IBM’s 20 qubit implementation. In the presentation Google indicated that their T1 times are roughly 2-4X worse than IBM’s, but that their single and two qubit gate fidelities are 2-10X better, and their measurement fidelities are roughly 10X better. They also gave their opinion that gate fidelities are a more realistic measure than coherence times and that they expect their forthcoming 49 qubit chip will show similar results as their 5 and 9 qubit chips. You can view Google’s complete presentation at AQC 2018 here.
We encourage anyone else who has data on other implementations to contact us at info@quantumcomputingreport.com so we can include your data into these tables. Please see the notes at the end of this page that provides additional details of how these tables were generated.
Qubit Connectivity | T1 (µsec) | T2 (µsec) | ||||||||
Computer | Qubit Count | Min | Max | Ave | Min | Max | Ave | Min | Max | Ave |
IBM Q5 Tenerife |
5 |
2 |
4 |
2.4 |
41.2 |
53.0 |
48.4 |
11.2 |
36.4 |
20.1 |
IBM Q16 Melbourne |
14 |
2 |
3 |
2.71 |
24.5 |
110.0 |
58.7 |
17.0 |
155.7 |
71.5 |
IBM Q16 Rueschlikon |
16 |
2 |
3 |
2.75 |
22.4 |
68.2 |
41.4 |
21.4 |
104.4 |
61.0 |
IBM Q20 Tokyo |
20 |
2 |
6 |
3.9 |
N/A |
N/A |
78.3 |
N/A |
N/A |
56.2 |
Rigetti 8Q |
8 |
2 |
2 |
2 |
10.0 |
15.5 |
13.4 |
9.2 |
26.2 |
15.1 |
Rigetti 19Q |
19 |
1 |
3 |
2.21 |
8.2 |
31.0 |
20.3 |
4.9 |
26.8 |
10.9 |
1-Qubit Gate Fidelity | 2-Qubit Gate Fidelity | Read Out Fidelity | |||||||
Computer | Min | Max | Ave | Min | Max | Ave | Min | Max | Ave |
IBM Q5 Tenerife |
99.16% |
99.91% |
99.73% |
94.05% |
97.34% |
95.81% |
91.80% |
96.80% |
94.46% |
IBM Q16 Melbourne |
99.11% |
99.87% |
99.68% |
69.86% |
96.81% |
92.84% |
81.87% |
97.41% |
93.02% |
IBM Q16 Rueschlikon |
99.35% |
99.90% |
99.74% |
91.65% |
97.50% |
95.65% |
82.92% |
96.51% |
92.74% |
IBM Q20 Tokyo |
N/A |
N/A |
99.85% |
N/A |
N/A |
95.33% |
N/A |
N/A |
91.72% |
Rigetti 8Q |
93.20% |
98.20% |
96.15% |
67.00% |
93.00% |
87.00% |
67.80% |
94.30% |
83.84% |
Rigetti 19Q |
94.96% |
99.42% |
98.63% |
79.00% |
93.60% |
87.50% |
84.00% |
97.00% |
93.30% |
Computer | Reference | Date |
IBM Q5 Tenerife |
https://quantumexperience.ng.bluemix.net/qx/devices |
10/8/2018 |
IBM Q16 Melbourne |
https://quantumexperience.ng.bluemix.net/qx/devices |
10/8/2018 |
IBM Q16 Rueschlikon |
https://quantumexperience.ng.bluemix.net/qx/devices |
9/26/2018 |
IBM Q20 Tokyo |
https://quantumexperience.ng.bluemix.net/qx/devices |
10/7/2018 |
Rigetti 8Q |
https://pyquil.readthedocs.io/en/stable/qpu.html |
10/8/2018 |
Rigetti 19Q |
No Longer On-Line |
12/18/2017 |
Notes
Besides this overview of the quality of IBM and Rigetti qubits, I believe adding overviews comparing different technology types (e.g. arXiv:1610.02208 or, a little older, arXiv:quant-ph/0607065 chapter 4.2.1) can be helpful to get a general understanding the pros-and-cons of different qubit types
We have also been looking for some good comparisons of the different implementation technologies. The best concise comparison we could find is an article published in Science Magazine written by Gabriel Popkin. It briefly summarizes the major technologies with the exception of photonics. You can find it at http://www.sciencemag.org/news/2016/12/scientists-are-close-building-quantum-computer-can-beat-conventional-one,
Hi,
I have seen various parameters but I am a little confused by the relations of them (coherence time/T1/T2, fidelity, connectivity, error rate)? Is error rate resulted by the other three parameters?)
Can I generally say:
Power of a quantum computer=Quality of qubits (connectivity x error rate) x Number of qubits = Number of logical qubits?
Thank you!
Eric
There is no simple agreed upon formula that fully describes the power of a quantum computer. All that can be said is that the higher the qubit count, quality level, and connectivity, the better. The number of logical qubits is a function of the specific error correction algorithm that is used with the physical qubits. It is not directly related to the qubit quality. However, the lower the qubit quality, the more error correction you may want to put in. Describing the details of the different error types can get a little complicated and I would refer you to a quantum computing textbook to get a more complete description.
Doug Finke
Managing Editor