Abstract
Materials improvement is a powerful approach to reducing loss and decoherence in superconducting qubits, because such improvements can be readily translated to large-scale processors. Recent work improved transmon coherence by using tantalum as a base layer and sapphire as a substrate1. The losses in these devices are dominated by two-level systems with comparable contributions from both the surface and bulk dielectrics2, indicating that both must be tackled to achieve substantial improvements in the state of the art. Here we show that replacing the substrate with high-resistivity silicon markedly decreases the bulk substrate loss, enabling 2D transmons with time-averaged quality factors (Qavg) of 9.7 × 106 across 45 qubits. For our best qubit, we achieve a Qavg of 1.5 × 107, reaching a maximum Q of 2.5 × 107, corresponding to a lifetime (T1) up to 1.68 ms. This low loss also allows us to observe decoherence effects related to the Josephson junction, and we use an improved, low-contamination junction deposition to achieve Hahn echo coherence times (T2E) exceeding T1. We achieve these materials improvements without any modifications to the qubit architecture, allowing us to readily incorporate standard quantum control gates. We demonstrate single-qubit gates with 99.994% fidelity. The tantalum-on-silicon platform comprises a simple material stack that can potentially be fabricated at the wafer scale and therefore can be readily translated to large-scale quantum processors.
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Data availability
The data that support the findings of this study are available from the corresponding authors on request.
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The code related to the data analysis of this study is available from the corresponding authors on request.
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Acknowledgements
We acknowledge helpful conversations with M. Devoret, Y. Chen, A. Opremcak, G. Sterling, M. Reagor, L. Ioffe, L. Faoro, J. Thompson, J. Rovny, L. Krayzman, P. Jatakia, J. Bryon and K. D. Crowley. We also acknowledge E. Umbarkar and M. Lin for initial work on Ta deposition on Si. This work was primarily supported by the US Department of Energy, Office of Science, National Quantum Information Science Research Centers, Co-design Center for Quantum Advantage (C2QA) under contract no. DESC0012704. This research was partially supported by Google Quantum AI. Interface characterization and fabrication optimization were supported by the Microelectronics Commons programme, a DoD initiative, under award number N00164-23-9-G061. M.P.B. and E.H. were also supported by the National Science Foundation Graduate Research Fellowship Program (NSF-GRFP) under grant no. DGE-2444107. We acknowledge the use of Princeton’s Imaging and Analysis Center (IAC), which is partially supported by the Princeton Center for Complex Materials (PCCM), a National Science Foundation (NSF) Materials Research Science and Engineering Center (MRSEC; DMR-2011750), as well as the Princeton Micro/Nano Fabrication Laboratory. We also acknowledge MIT Lincoln Labs for supplying a travelling-wave parametric amplifier.
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Contributions
M.P.B. and F.B. conducted the principal qubit and resonator fabrication, measurements and analysis. J.G.C.M. performed qubit measurements and conducted the CPMG experiments. P.H.P. conducted the RB single-qubit measurements. M.P.B. optimized device parameters. F.B. and M.P.B. optimized the Ta film growth conditions. B.M.S. assisted with the qubit design. F.B. and E.H. performed material characterization. A. Joshi, E.H., A.C.P.-T., S.K., A. Jindal, R.D.C. and A.Y. helped with device fabrication and cryogenic measurements. G.C. and N.Y. performed TEM measurements. R.J.C., N.P.d.L. and A.A.H. conceived and supervised the project. N.P.d.L. and A.A.H. designed the experiments and analysed data. M.P.B., F.B., J.G.C.M., P.H.P., B.M.S., A.Y., N.P.d.L. and A.A.H. wrote the manuscript, with input from all authors.
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A.A.H., Princeton University professor, is also a consultant for Quantum Circuits, Inc. (QCI). As a result of his income from QCI, Princeton University has a management plan in place to mitigate a potential conflict of interest that could affect the design, conduct and reporting of this research. N.P.d.L., Princeton University professor, is a visiting faculty researcher with Google Quantum AI. As a result of her income from Google, Princeton University has a management plan in place to mitigate a potential conflict of interest that could affect the design, conduct and reporting of this research. Her academic group also has a sponsored research contract with Google Quantum AI. A.A.H., N.P.d.L., R.J.C. and B.M.S. hold a patent relevant to the work (patent no. WO2021096955) and A.A.H., N.P.d.L., F.B., M.B., A.J., and B.M.S. have also filed provisional patents directly arising from the results detailed in this manuscript.
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Extended data figures and tables
Extended Data Fig. 1 Cross-sectional EDS elemental mapping.
The EDS scan for Ta (blue), Si (orange) and O (red) confirms the absence of intermixing between Ta and Si at the metal–substrate interface, as well as the absence of O. Furthermore, the HAADF image is plotted on a combined cross-sectional EDS map (far left) to demonstrate the clean separation between Ta and Si.
Extended Data Fig. 2 DC resistivity.
Resistivity as a function of temperature for Ta-on-Si films at zero applied magnetic field. Error bars represent s.d. arising from instrumental noise. The transition temperature is 4.2 ± 0.1 K, consistent with α-phase Ta. Error in the transition temperature is the step size of the resistivity measurement.
Extended Data Fig. 3 Ta–air and Ta–Si interfaces.
Left, the cross-sectional STEM image of the Ta–air interface. The native oxide layer on the Ta thin films, which corresponds to the darker grey region near the top of the Ta, is estimated to be about 2.7–3.0 nm thick. Right, the cross-sectional STEM image of the Ta–Si interface. The blurry area at the Ta–Si interface is amorphous Ta resulting from the lattice mismatch between Ta and Si. EDS in Fig. 1b and Extended Data Fig. 1 confirm the absence of amorphous TaSix or oxides at this interface. The thickness of this region is estimated to be about 4 nm.
Extended Data Fig. 4 Qubit patterns.
Optical images without (a) and with (b) drive lines. Each 7 × 7-mm pattern comprises six transmons, each capacitively coupled to a readout resonator that is inductively coupled to a central feedline that also acts as a Purcell filter. The measured device parameters for these qubits are shown in Extended Data Table 3, with a simulated T1 owing to Purcell decay (T1,p) exceeding 10 ms. The qubit parameters were designed in AWR Microwave Office. Scale bars, 1 mm.
Extended Data Fig. 5 Resonator patterns.
Optical images of coplanar waveguide (a) and lumped element resonators (b,c). Scale bars, 1 mm (a,b), 0.3 mm (c). The coplanar waveguides have resonance frequencies between 5.5 and 8.0 GHz with gaps ranging from 2 to 16 μm, corresponding to pMS between 1.5 × 10−3 and 2 × 10−4 and external coupling (Qc) around 1 million. The lumped elements have resonance frequencies between 4 and 5 GHz and gaps ranging from 2 to 100 μm, corresponding to pMS between 6 × 10−3 and 7 × 10−5 and Qc around 10 million.
Extended Data Fig. 6 Quality factors for transmon qubits.
Comparison of Q for 45 transmon qubits across nine chips. Boxes mark the 25th and 75th quartiles and coloured lines mark the medians of the dataset. Qubits fabricated on the same chip are grouped by colour. The numbers on the x-axis correspond to the same qubits as in Extended Data Table 1.
Extended Data Fig. 7 SiOx regrowth after 65 days.
Si2p XPS spectrum showing a pair of spin–orbit split peaks corresponding to bulk Si (Si0) and a broad feature around 103 eV associated with the oxide. The difference between the SiOx thicknesses is clear from the two XPS spectra. The Si2p spectra for the device before (a) and after (b) 65 days show a large difference in the intensity of the oxide peaks, confirming a substantial amount of SiOx regrowth. The error bars on each data point represent the shot noise normalized to intensity.
Extended Data Fig. 8 Transmon dephasing times.
Tϕ calculated using \({T}_{1}^{{\rm{avg}}}\) and \({T}_{2{\rm{E}}}^{{\rm{avg}}}\) for each qubit. We observe an increase in Tϕ for qubits with UHV-deposited junctions (purple) with a median Tϕ of 2.0 ms compared with qubits with HV-deposited junctions (orange) with a median Tϕ of 0.22 ms. Note that qubit 39 approaches the T2E = 2T1 limit and has a Tϕ of 40 ms. Errors are propagated from the standard error of the T1 and T2E data for each qubit.
Extended Data Fig. 9 Quality factor comparison between HV and UHV qubits.
Distribution in quality factors for transmons with HV-deposited (orange) and UHV-deposited (purple) junctions. The average and s.d. of Qavg for the HV and UHV qubits are (9.67 ± 2.29) × 106 and (9.87 ± 1.93) × 106, respectively.
Extended Data Fig. 10 Trench profile in etched devices.
Scanning electron microscope images of Ta-on-Si devices after chlorine reactive ion etch for 1 min and 45 s (a,b) and 1 min (c,d). The etch chemistry also etches Si, resulting in a trench profile, which reduces the SPR. Resonator trench depths varied from 50 to 1,000 nm, whereas qubit trench depths varied from 50 to 100 nm.
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Bland, M.P., Bahrami, F., Martinez, J.G.C. et al. Millisecond lifetimes and coherence times in 2D transmon qubits. Nature 647, 343–348 (2025). https://doi.org/10.1038/s41586-025-09687-4
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DOI: https://doi.org/10.1038/s41586-025-09687-4
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