IP Library › Granted Patent US 12,531,116
Granted Patent B2
US 12,531,116 · App. 17/554,994 · Granted Jan 20, 2026

TLS-based optimization of stark tone tuning

Inventors: Takashi Imamichi (Tokyo, JP); Naoki Kanazawa (Yokohama, JP); Sami Rosenblatt (White Plains, NY); Benjamin Fearon (Brooklyn, NY)
Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
G11C11/44G06N10/40
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Quick Facts
Patent No.
US 12,531,116
App. No.
17/554,994
Granted
Jan 20, 2026
Kind
B2
Abstract

Systems and techniques that facilitate TLS-based optimization of Stark tone tuning are provided. In various embodiments, a system can comprise a receiver component that can access a qubit topology. In various aspects, the system can further comprise an optimization component that can identify, based on a set of two-level-system, (TLS) frequency regions of the qubit topology, one or more Stark tone frequencies. In various instances, the system can further comprise an execution component that can apply, to a qubit lattice corresponding to the qubit topology, one or more Stark tones that have the one or more Stark tone frequencies, thereby eliminating frequency collisions in the qubit lattice.

Claims (56)

1 . A system, comprising:

a processor that executes computer-executable components stored in a computer-readable memory, the computer-executable components comprising:

a receiver component that accesses a qubit topology;

an optimization component that identifies, based on a set of two-level-system (TLS) frequency regions of the qubit topology, one or more Stark tone frequencies; and

an execution component that:

applies, to a qubit lattice corresponding to the qubit topology, one or more Stark tones that have the one or more Stark tone frequencies; and

eliminates frequency collisions in the qubit lattice such that Stark tone tuning eliminates direct frequency collisions between neighboring qubits and also eliminates TLS frequency collisions for each individual qubit.

2 . The system of claim 1 , wherein the computer-executable components further comprise:

an execution component that applies, to a qubit lattice corresponding to the qubit topology, one or more Stark tones that have the one or more Stark tone frequencies, thereby eliminating frequency collisions in the qubit lattice.

3 . The system of claim 1 , wherein the computer-executable components further comprise:

a scanning component that identifies, via application of qubit relaxation spectroscopy to a qubit lattice corresponding to the qubit topology, the set of TLS frequency regions.

4 . The system of claim 1 , wherein the optimization component identifies the one or more Stark tone frequencies by executing an optimizer on a set of collision constraints, wherein the set of collision constraints include a set of TLS collision constraints that are based on the set of TLS frequency regions.

5 . The system of claim 4 , wherein the set of collision constraints further include a set of qubit-to-qubit collision constraints and a set of tone-to-qubit collision constraints.

6 . A computer-implemented method, comprising:

accessing, by a device operatively coupled to a processor, a qubit topology;

identifying, by the device and based on a set of two-level-system (TLS) frequency regions of the qubit topology, one or more Stark tone frequencies;

applying, by the device, and to a qubit lattice corresponding to the qubit topology, one or more Stark tones that have the one or more Stark tone frequencies; and

eliminating, by the device, frequency collisions in the qubit lattice such that Stark tone tuning eliminates direct frequency collisions between neighboring qubits and also eliminates TLS frequency collisions for each individual qubit.

7 . The computer-implemented method of claim 6 , further comprising:

identifying, by the device and via application of qubit relaxation spectroscopy to a qubit lattice corresponding to the qubit topology, the set of TLS frequency regions.

8 . The computer-implemented method of claim 6 , wherein the device identifies the one or more Stark tone frequencies by executing an optimizer on a set of collision constraints, wherein the set of collision constraints include a set of TLS collision constraints that are based on the set of TLS frequency regions.

9 . The computer-implemented method of claim 8 , wherein the set of collision constraints further include a set of qubit-to-qubit collision constraints and a set of tone-to-qubit collision constraints.

10 . A computer program product for facilitating TLS-based optimization of Stark tone tuning, the computer program product comprising a non-transitory computer-readable memory having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to:

access a qubit topology;

identify, based on a set of two-level-system (TLS) frequency regions of the qubit topology, one or more Stark tone frequencies;

apply to a qubit lattice corresponding to the qubit topology, one or more Stark tones that have the one or more Stark tone frequencies; and

eliminate frequency collisions in the qubit lattice such that Stark tone tuning eliminates direct frequency collisions between neighboring qubits and also eliminates TLS frequency collisions for each individual qubit.

11 . The computer program product of claim 10 , wherein the program instructions are further executable to cause the processor to:

identify, via application of qubit relaxation spectroscopy to a qubit lattice corresponding to the qubit topology, the set of TLS frequency regions.

12 . The computer program product of claim 10 , wherein the processor identifies the one or more Stark tone frequencies by executing an optimizer on a set of collision constraints, wherein the set of collision constraints include a set of TLS collision constraints that are based on the set of TLS frequency regions.

13 . The computer program product of claim 12 , wherein the set of collision constraints further include a set of qubit-to-qubit collision constraints and a set of tone-to-qubit collision constraints.

14 . A device, comprising:

a processor that executes computer-executable components stored in a computer-readable memory, the computer-executable components comprising:

a scanning component that identifies, via qubit relaxation spectroscopy, a plurality of two-level-system (TLS) frequency regions associated with a qubit lattice, wherein the scanning component performs steps comprising:

sweeping operational frequency values of a defined qubit through a defined range of values, by applying one or more Stark tone frequencies to the defined qubit with varying amplitudes or varying durations, and the relaxation time of the defined qubit is measured and probed for one or more of the operational frequency values;

identifying one or more operational frequency intervals or ranges that cause the relaxation time of the defined qubit to decrease by a defined margin, wherein the relaxation time is decreased compared to another relaxation time prior to the identifying the one or more operational frequency intervals or ranges; and

marking such identified ones of the one or more operational frequency intervals or ranges as one or more TLS frequency regions of the defined qubit, wherein the one or more TLS frequency regions is comprised within a set of TLS frequency regions; and

an optimization component that calculates, based on the plurality of TLS frequency regions, at least one Stark tone frequency that prevents frequency collisions of the qubit lattice such that Stark tone tuning eliminates direct frequency collisions between neighboring qubits and also eliminates TLS frequency collisions for each individual qubit.

15 . The device of claim 14 , wherein the optimization component identifies at least one Stark shift that corresponds to the at least one Stark tone frequency, and wherein the computer-executable components further comprise:

an amplitude component that estimates at least one Stark tone amplitude that, in combination with the at least one Stark tone frequency, causes the at least one Stark shift.

16 . The device of claim 15 , wherein the computer-executable components further comprise:

an execution component that applies at least one Stark tone to the qubit lattice, according to the at least one Stark tone frequency and the at least one Stark tone amplitude.

17 . The device of claim 15 , wherein the optimization component calculates the at least one Stark tone frequency and the at least one Stark shift via an optimization engine that operates according to a plurality of collision constraints, wherein the plurality of collision constraints are based on the plurality of TLS frequency regions.

18 . The device of claim 17 , wherein the optimization engine implements mixed integer linear programming or mixed integer quadratic programming.

19 . A computer-implemented method, comprising:

identifying, by a system operatively coupled to a processor and via qubit relaxation spectroscopy, a plurality of two-level-system (TLS) frequency regions associated with a qubit lattice;

sweeping, by the system, operational frequency values of a defined qubit through a defined range of values, by applying one or more Stark tone frequencies to the defined qubit with varying amplitudes or varying durations, and the relaxation time of the defined qubit is measured and probed for one or more of the operational frequency values;

identifying, by the system, one or more operational frequency intervals or ranges that cause the relaxation time of the defined qubit to decrease by a defined margin, wherein the relaxation time is decreased compared to another relaxation time prior to the identifying the one or more operational frequency intervals or ranges;

mark such identified ones of the one or more operational frequency intervals or ranges as one or more TLS frequency regions of the defined qubit, wherein the one or more TLS frequency regions is comprised within a set of TLS frequency regions; and

calculate, based on the plurality of TLS frequency regions, at least one Stark tone frequency that prevents frequency collisions of the qubit lattice such that Stark tone tuning eliminates direct frequency collisions between neighboring qubits and also eliminates TLS frequency collisions for each individual qubit.

20 . The computer-implemented method of claim 19 , wherein the at least one Stark tone frequency corresponds to at least one Stark shift, and further comprising:

estimating, by the system, at least one Stark tone amplitude that, in combination with the at least one Stark tone frequency, causes the at least one Stark shift.

21 . The computer-implemented method of claim 20 , further comprising:

applying, by the system, at least one Stark tone to the qubit lattice, according to the at least one Stark tone frequency and the at least one Stark tone amplitude.

22 . The computer-implemented method of claim 20 , wherein the system calculates the at least one Stark tone frequency and the at least one Stark shift via an optimization engine that operates according to a plurality of collision constraints, wherein the plurality of collision constraints are based on the plurality of TLS frequency regions.

23 . The computer-implemented method of claim 22 , wherein the optimization engine implements mixed integer linear programming or mixed integer quadratic programming.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 17, 2021
From: IMAMICHI, TAKASHI; KANAZAWA, NAOKI; ROSENBLATT, SAMI; FEARON, BENJAMIN
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 058422/0423 →
Continuity (1)
Related Publication 20230197147A1 · Jun 22, 2023
References Cited (58)
US 7847615B2 · Yorozu et al. · 2010 [cited by applicant]
US 9432024B2 · Chow et al. · 2016 [cited by applicant]
US 10282675B2 · Bloom et al. · 2019 [cited by applicant]
US 10366340B2 · Przybysz · 2019 [cited by applicant]
US 10467544B2 · Filipp et al. · 2019 [cited by applicant]
US 10622536B2 · Chow et al. · 2020 [cited by applicant]
US 10755193B2 · Kandala et al. · 2020 [cited by applicant]
US 10833680B2 · Mckay et al. · 2020 [cited by applicant]
US 10892398B2 · Pollanen et al. · 2021 [cited by applicant]
US 10900998B1 · Sandberg et al. · 2021 [cited by applicant]
US 10924095B1 · Mckay et al. · 2021 [cited by applicant]
US 11004009B2 · Monroe et al. · 2021 [cited by applicant]
US 11017310B2 · Chu et al. · 2021 [cited by applicant]
US 11244241B1 · Gambetta · 2022 [cited by examiner]
US 11681016B1 · Bohaichuk et al. · 2023 [cited by applicant]
US 20190165244A1 · Hertzenberg et al. · 2019 [cited by applicant]
US 20200274703A1 · Lukens et al. · 2020 [cited by applicant]
US 20210036206A1 · Neill et al. · 2021 [cited by applicant]
US 20210049494A1 · King et al. · 2021 [cited by applicant]
US 20210182096A1 · Walker et al. · 2021 [cited by applicant]
US 20210208231A1 · Lachance-Quirion et al. · 2021 [cited by applicant]
US 20210272001A1 · Smelyanskiy et al. · 2021 [cited by applicant]
US 20210334689A1 · Klimov et al. · 2021 [cited by applicant]
US 20220196716A1 · Anderson et al. · 2022 [cited by applicant]
US 20230169252A1 · Stehlik et al. · 2023 [cited by applicant]
US 20230176935A1 · Earnest-Noble et al. · 2023 [cited by applicant]
US 20230289400A1 · Carroll et al. · 2023 [cited by applicant]
CN 112215360A · 2021 [cited by applicant]
CN 112444714A · 2021 [cited by applicant]
WO 2018063168A1 · 2018 [cited by applicant]
WO 2020263255A1 · 2020 [cited by applicant]
WO 2021170164A1 · 2021 [cited by applicant]
Chang et al “On Quantum Computing for Mixed-Integer Programming”, retrieved from https://arxiv.org/pdf/2010.07852v1 and dated Oct. 15, 2020 (Year: 2020). [cited by examiner]
Li, G et al. | “Towards Efficient Superconducting Quantum Processor Architecture Design”. ASPLOS'20, Mar. 16-20, 2020, Lausanne, Switzerland, 15 pages. [cited by applicant]
IBM | “IBM ILOG CPLEX Optimizer”. Webpage https://www.ibm.com/analytics/cplex-optimizer, last accessed Nov. 24, 2021, 7 pages. [cited by applicant]
Hertzberg, J.B. et al. | “Laser-annealing Josephson junctions for yielding scaled-up superconducting quantum processors”. arXiv:2009.00781v4 [quant-ph] Sep. 23, 2020, 16 pages. [cited by applicant]
Carroll, M. et al. | “Dynamics of superconducting qubit relaxation times”. arXiv:2105.15201v1 [quant-ph] May 31, 2021, 10 pages. [cited by applicant]
Abdurakhimov, L.V. et al. | “Driven-state relaxation of a coupled qubit-defect system in spin-locking measurements”. Phys. Rev. B 102, 100502(R)—Published Sep. 3, 2020, 5 pages. [cited by applicant]
Jurcevic, P. et al. | “Demonstration of quantum vol. 64 on a superconducting quantum computing system”. arXiv:2008.08571v2 [quant-ph] Sep. 4, 2020, 7 pages. [cited by applicant]
Lisenfeld, J. et al. | “Electric field spectroscopy of material defects in transmon qubits”. npj Quantum Information (2019) 5:105 ; https://doi.org/10.1038/s41534-019-0224-1, 6 pages. [cited by applicant]
Burnett, J.J. et al. | “Decoherence benchmarking of superconducting qubits”. npj Quantum Information (2019) 5:54 ; https://doi.org/10.1038/s41534-019-0168-5, 8 pages. [cited by applicant]
Zhang, E.J. et al. | “High-fidelity superconducting quantum processors via laser-annealing of transmon qubits”. arXiv:2012.08475v1 [quant-ph] Dec. 15, 2020, 9 pages. [cited by applicant]
Morvan, A. et al. | “Optimizing frequency allocation for fixed-frequency superconducting quantum processors”. arXiv:2112.01634v1 [quant-ph] Dec. 2, 2021, 11 pages. [cited by applicant]
Li, G. et al. | “Towards Efficient Superconducting Quantum Processor Architecture Design”. arXiv:1911.12879v1 [quant-ph] Nov. 28, 2019, 15 pages. [cited by applicant]
Mell et al., “The NIST Definition of Cloud Computing,” Recommendations of the National Institute of Standards and Technology, NIST Special Publication 800-145, Sep. 2011, 7 pages. [cited by applicant]
International Search Report and Written Opinion received for PCT Application Serial No. PCT/E P2022/086455 dated Mar. 14, 2023, 15 pages. [cited by applicant]
Wei, K.X. et al. | “Quantum crosstalk cancellation for fast entangling gates and improved multi-qubit performance”, arxiv.org, Cornell University Library, 201 Olin Library Cornell University Ithaca, NY 14853, Jun. 1, 20… [cited by applicant]
Magnard et al., “Fast and Unconditional All-Microwave Reset of a Superconducting Qubit”, https://arxiv.org/abs/1801.07689, Jan. 23, 2018, 9 pages. [cited by applicant]
Egger et al., “Pulsed Reset Protocol for Fixed-Frequency Superconducting Qubits”, https://doi.org/10.1103/PhysRevApplied.10.044030, Apr. 1, 2019, 7 pages. [cited by applicant]
Klimov et al., “Fluctuations of Energy-Relaxation Times in Superconducting Qubits”, https://doi.org/10.48550/arXiv.1809.01043, Mar. 2, 2022, 21 pages. [cited by applicant]
Mcrae et al., “Reproducible Coherence Characterization of Superconducting Quantum Devices”, Appl. Phys. Lett., vol. 119, No. 100501, 2021, 13 pages. [cited by applicant]
List of IBM Patents and Patent Applications Treated as Related. [cited by applicant]
Notice of Allowance and Fees Due (PTOL-85) Mailed on Nov. 13, 2024 for U.S. Appl. No. 17/694,051, 8 page(s). [cited by applicant]
Notice of Allowance and Fees Due (PTOL-85) Mailed on Oct. 21, 2024 for U.S. Appl. No. 17/694,051, 9 page(s). [cited by applicant]
Non-Final Rejection Mailed on Jun. 30, 2025 for U.S. Appl. No. 17/936,262, 17 page(s). [cited by applicant]
Coherent Josephson qubit suitable for scalable quantum integrated circuits, Barend et al, 2013 (Year: 2013). [cited by applicant]
Non-Final Rejection Mailed on Sep. 15, 2025 for U.S. Appl. No. 17/694,063, 12 page(s). [cited by applicant]
Notice of Allowance for U.S. Appl. No. 17/936,262 dated Oct. 14, 2025. [cited by applicant]