IP Library Granted Patent US 12,632,756
Granted Patent B2
US 12,632,756 · App. 17/863,787 · Granted May 19, 2026

Efficient quantum simulation with quantum information compression and multiple fermion-to-qubit basis transformations

Inventors: Qingfeng Wang (College Park, MD); Yunseong Nam (North Bethesda, MD)
Assignees: IONQ, INC.; UNIVERSITY OF MARYLAND
G06N10/20G06N10/40
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,632,756
App. No.
17/863,787
Granted
May 19, 2026
Kind
B2
Abstract

Aspects of the present disclosure describe a method including compressing and uncompressing redundant quantum information encoded in quantum computers; processing quantum information in the compressed space; and computing, in response to determining the ansatz terms, a set of optimal transformations.

Claims (51)

1 . A method of using a quantum information processing system comprising a plurality of trapped ions, each trapped ion defining a qubit, the method comprising:

performing a dynamic simulation of a Fermionic system, comprising:

computing, by a processor, first quantum circuits that implement one-body Trotter terms and second quantum circuits that implement two-body Trotter terms of a time evolution operator of the Fermionic system on a plurality of qubits;

compressing, by the processor, the second quantum circuits, each of which implements a two-body Trotter term on a first qubit, a second qubit, a third qubit, and a fourth qubit of the plurality of qubits in a selected state, wherein in the selected state, the first and second qubits are in a first qubit state, and the third and fourth qubits are in a second qubit state;

implementing, by an optical controller, the computed first quantum circuits and the compressed second quantum circuits on the plurality of qubits; and

measuring, by an imaging system, a qubit state of each of the plurality of qubits at a first time; and

outputting, by the processor, an indication of the measured qubit state of each of the plurality of qubits at the first time, the indication illustrating a time evolution of the Fermionic system at the first time.

2 . The method of claim 1 , wherein each of the first quantum circuits comprises a singly-controlled X gate and a controlled-NOT gate on the pair of qubits of the plurality of qubits.

3 . The method of claim 1 , wherein each of the second quantum circuits comprises a triply-controlled-X and controlled-NOT gates on the first, second, third, and fourth qubits.

4 . The method of claim 3 , wherein each of the compressed second quantum circuit comprises a quantum circuit that implements a one-body Trotter term on the first and third qubits, a controlled-NOT gate on the first and second qubits, and a controlled-NOT gate on the second and fourth qubits.

5 . The method of claim 1 , further comprising:

computing, by the processor, third quantum circuits that implement hybrid Trotter terms between one-body Trotter terms and two-body Trotter terms, each of the third quantum circuits comprising a doubly-controlled X gate.

6 . A method of performing an estimation of a ground state energy of a Fermionic system using a quantum information processing system comprising a plurality of trapped ions, each trapped ion defining a qubit, the method comprising:

performing a dynamic simulation of a Fermionic system, comprising:

preparing, by an optical controller, a plurality of qubits in a first ansatz state;

computing, by a processor, first quantum circuits that implement one-body Trotter terms and second quantum circuits that implement two-body Trotter terms of a parametrized unitary ansatz evolution operator of a Fermionic system, on the plurality of qubits;

compressing, by the processor, the second quantum circuits, each of which implements a two-body Trotter term on a first qubit, a second qubit, a third qubit, and a fourth qubit of the plurality of qubits in a selected state, wherein in the selected state, the first and second qubits are in a first qubit state, and the third and fourth qubits are in the same a second qubit state;

implementing, by the optical controller, the computed first quantum circuits and the compressed second quantum circuits on the plurality of qubits; and

measuring, by an imaging system, a qubit state of each of the plurality of qubits; and

outputting, by the processor, an indication of the measured qubit state of each of the plurality of qubits, the indication illustrating a first energy of the Fermionic system.

7 . The method of claim 6 , further comprising:

modifying, by the processor, the parametrized unitary ansatz evolution operator; and

repeating the preparing of the plurality of qubits, the computing of the first quantum circuits and the second quantum circuits, the compressing of the second quantum circuits, the measuring of the qubit state of each of the plurality of qubits, and the outputting of an indication of the measured qubit state of each of the plurality of qubits, the indication illustrating a second energy of the Fermionic system, wherein the second energy is less than the first energy.

8 . The method of claim 6 , wherein each of the first quantum circuits comprises a singly-controlled X gate and a controlled-NOT gate on the pair of qubits of the plurality of qubits.

9 . The method of claim 6 , wherein each of the second quantum circuits comprises 13 controlled-NOT gates on the first, second, third, and fourth qubits.

10 . The method of claim 9 , wherein the compressed second quantum circuits comprises a quantum circuit that implements a one-body Trotter term on the first and third qubits, a controlled-NOT gate on the first and second qubits, and a controlled-NOT gate on the second and fourth qubits.

11 . The method of claim 6 , further comprising:

computing, by the processor, third quantum circuits that implement hybrid Trotter terms between one-body Trotter terms and two-body Trotter terms, each of the third quantum circuits comprising 30 controlled-NOT gates; and

compressing, by the processor, the third quantum circuits.

12 . A non-transitory computer readable medium having instructions stored therein that, when executed by a processor, cause the processor to:

simulate a dynamic simulation of a Fermionic system by:

computing, by a processor, first quantum circuits that implement one-body Trotter terms and second quantum circuits that implement two-body Trotter terms of an evolution operator of a Fermionic system, on a plurality of qubits, each qubit comprising a trapped ion;

compressing, by the processor, the second quantum circuits, each of which implements a two-body Trotter term on a first qubit, a second qubit, a third qubit, and a fourth qubit of the plurality of qubits in a selected state, wherein in the selected state, the first and second qubits are in a first qubit state, and the third and fourth qubits are in a second qubit state;

implementing, by an optical controller, the computed first quantum circuits and the compressed second quantum circuits on the plurality of qubits; and

measuring, by an imaging system, a qubit state of each of the plurality of qubits; and

output, by the processor, an indication of the measured qubit state of each of the plurality of qubits.

13 . The non-transitory computer readable medium of claim 12 , wherein

the evolution operator of the Fermionic system is a time evolution operator of the Fermionic system, and

the indication of the measured qubit state of each of the plurality of qubits is a time evolution of the Fermionic system.

14 . The non-transitory computer readable medium of claim 12 , wherein

the evolution operator of the Fermionic system is a parametrized unitary ansatz evolution operator of the Fermionic system, and

the indication of the measured qubit state of each of the plurality of qubits is a first energy of the Fermionic system.

15 . The non-transitory computer readable medium of claim 14 , further comprising instructions for preparing, by the optical controller, the plurality of qubits in a first ansatz state.

16 . The non-transitory computer readable medium of claim 15 , further comprising instructions for

modifying, by the processor, the parametrized unitary ansatz evolution operator; and

repeating the preparing of the plurality of qubits, the computing of the first quantum circuits and the second quantum circuits, the compressing of the second quantum circuits, the measuring of the qubit state of each of the plurality of qubits, and the outputting of an indication of the measured qubit state of each of the plurality of qubits, the indication illustrating a second energy of the Fermionic system, wherein the second energy is less than the first energy.

17 . The non-transitory computer readable medium of claim 12 , wherein each of the first quantum circuits comprises a singly-controlled X gate and a controlled-NOT gate on the pair of qubits of the plurality of qubits.

18 . The non-transitory computer readable medium of claim 12 , wherein each of the second quantum circuits comprises controlled-NOT gates on the first, second, third, and fourth qubits.

19 . The non-transitory computer readable medium of claim 18 , wherein the compressed second quantum circuit comprises a quantum circuit that implements a one-body Trotter term on the first and third qubits, a controlled-NOT gate on the first and second qubits, and a controlled-NOT gate on the second and fourth qubits.

20 . The non-transitory computer readable medium of claim 15 , further comprising instructions for

computing, by the processor, the third quantum circuits.

Assignments (3)
CONFIRMATORY LICENSE Recorded Feb 26, 2025
From: UNIV OF MARYLAND, COLLEGE PARK
To: NATIONAL SCIENCE FOUNDATION
Reel/Frame 070333/0439 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 1, 2023
From: WANG, QINGFENG
To: UNIVERSITY OF MARYLAND, COLLEGE PARK
Reel/Frame 063833/0457 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 1, 2022
From: NAM, YUNSEONG
To: IONQ, INC.
Reel/Frame 061610/0430 →
Continuity (2)
Provisional Application 63221717 · Jul 14, 2021
Related Publication 20230042892A1 · Feb 9, 2023
References Cited (51)
US 10637480B1 · Hu · 2020 [cited by examiner]
US 10776544B2 · Delaney · 2020 [cited by examiner]
US 20200184024A1 · Nam et al. · 2020 [cited by applicant]
US 20210264309A1 · Wang et al. · 2021 [cited by applicant]
US 20210374550A1 · Cao · 2021 [cited by examiner]
Boyyajian et al, Matchgate circuits and compressed quantum computation, pp. 1-187, 2015 (Year: 2015). [cited by examiner]
Y. Nam, J. Chen, N. Pisenti, K. Wright, C. Delaney, D. Maslov, K. R. Brown, S. Allen, J. M. Amini, J. Apisdorf, K. M. Beck, A. Blinov, V. Chaplin, M. Chmielewski, . . . “Ground-state energy estimation of the water molec… [cited by examiner]
“PSI41.1:An Open-Source Electronic Structure Program Emphasizing Automation, Advanced Libraries, and Interoperability” R. M. Parrish, L. A. Bums, D. G.A. Smith, A. C. Simmonett, A. E. DePrince, E. G. Hohenstein, U.Bozka… [cited by examiner]
Rodney J. Bartlett, Stanislaw A. Kucharski, and Jozef Noga. Alternative coupled-cluster ansätze ii. the unitary coupled-cluster method. Chemical Physics Letters, 155 (1): 133-140, 1989. [cited by applicant]
Mark R. Hoffmann and Jack Simons. A unitary multiconfigurational coupled cluster method: Theory and applications. The Journal of Chemical Physics, 88 (2): 993-1002, 1988. [cited by applicant]
James Kennedy and Russell C Eberhart. A discrete binary version of the particle swarm algorithm. In 1997 IEEE International conference on systems, man, and cybernetics. Computational cybernetics and simulation, vol. 5, … [cited by applicant]
Ryan Babbush, Jarrod McClean, Dave Wecker, Alan Aspuru-Guzik, and Nathan Wiebe. Chemical basis of trotter-suzuki errors in quantum chemistry simulation. Physical Review A, 91 (2), Feb. 2015. [cited by applicant]
Dominic W. Berry, Graeme Ahokas, Richard Cleve, and Barry C. Sanders. Efficient quantum algorithms for simulating sparse hamiltonians. Communications in Mathematical Physics, 270 (2): 359-371, 2007. [cited by applicant]
Alex Bocharov, Martin Roetteler, and Krysta M. Svore. Efficient synthesis of universal repeat-until-success quantum circuits. Physical Review Letters, 114: 080502, Feb. 2015. [cited by applicant]
Sergey B. Bravyi and Alexei Yu. Kitaev. Fermionic quantum computation. Annals of Physics, 298 (1):210-226, 2002. [cited by applicant]
Andrew M. Childs, Dmitri Maslov, Yunseong Nam, Neil J. Ross, and Yuan Su. Toward the first quantum simulation with quantum speedup. Proceedings of the National Academy of Sciences, 115 (38): 9456-9461, 2018. ISSN 0027-8… [cited by applicant]
J. I. Cirac and P. Zoller. Quantum computations with cold trapped ions. Physical Review Letters, 74: 4091-4094, May 1995. [cited by applicant]
E. F. Dumitrescu, A. J. McCaskey, G. Hagen, G. R. Jansen, T. D. Morris, T. Papenbrock, R. C. Pooser, D. J. Dean, and P. Lougovski. Cloud quantum computing of an atomic nucleus. Physical Review Letters, 120: 210501, May … [cited by applicant]
Richard P. Feynman. Simulating physics with computers. International Journal of Theoretical Physics, 21 (6): 467-488, 1982. ISSN 1572-9575. [cited by applicant]
Craig Gidney. Halving the cost of quantum addition. Quantum, 2: 74, Jun. 2018. ISSN 2521-327X. [cited by applicant]
Pranav Gokhale, Olivia Angiuli, Yongshan Ding, Kaiwen Gui, Teague Tomesh, Martin Suchara, Margaret Martonosi, and Frederic T Chong. Minimizing state preparations in variational quantum eigensolver by partitioning into c… [cited by applicant]
Harper R. Grimsley, Sophia E. Economou, Edwin Barnes, and Nicholas J. Mayhall. An adaptive variational algorithm for exact molecular simulations on a quantum computer. Nature Communications, 10 (1): 3007, Jul. 2019. ISS… [cited by applicant]
Matthew B. Hastings, Dave Wecker, Bela Bauer, and Matthias Troyer. Improving quantum algorithms for quantum chemistry. Quantum Info. Comput., 15 (1-2): 1-21, Jan. 2015. ISSN 1533-7146. [cited by applicant]
Cornelius Hempel, Christine Maier, Jonathan Romero, Jarrod McClean, Thomas Monz, Heng Shen, Petar Jurcevic, Ben P. Lanyon, Peter Love, Ryan Babbush, Alan Aspuru-Guzik, Rainer Blatt, and Christian F. Roos. Quantum chemis… [cited by applicant]
Zhang Jiang, Kevin J. Sung, Kostyantyn Kechedzhi, Vadim N. Smelyanskiy, and Sergio Boixo. Quantum algorithms to simulate many-body physics of correlated fermions. Physical Review Applied, 9 (4), Apr. 2018. [cited by applicant]
Abhinav Kandala, Antonio Mezzacapo, Kristan Temme, Maika Takita, Markus Brink, Jerry M. Chow, and Jay M. Gambetta. Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets. Nature, 549(… [cited by applicant]
Ian D. Kivlichan, Craig Gidney, Dominic W. Berry, Nathan Wiebe, Jarrod McClean, Wei Sun, Zhang Jiang, Nicholas Rubin, Austin Fowler, Alan Aspuru-Guzik, and et al. Improved fault-tolerant quantum simulation of condensed-… [cited by applicant]
Joonho Lee, William J. Huggins, Martin Head-Gordon, and K. Birgitta Whaley. Generalized unitary coupled cluster wave functions for quantum computation. Journal of Chemical Theory and Computation, 15 (1): 311-324, Jan. 2… [cited by applicant]
Seth Lloyd. Universal quantum simulators. Science, 273 (5278): 1073-1078, 1996. [cited by applicant]
Guang Hao Low and Isaac L. Chuang. Optimal hamiltonian simulation by quantum signal processing. Physical Review Letters, 118: 010501, Jan. 2017. [cited by applicant]
Guang Hao Low and Isaac L. Chuang. Hamiltonian Simulation by Qubitization. Quantum, 3: 163, Jul. 2019. [cited by applicant]
D. Maslov, Y. Nam, and J. Kim. An outlook for quantum computing [point of view]. Proceedings of the IEEE, 107 (1): 5-10, Jan. 2019. [cited by applicant]
Dmitri Maslov. Advantages of using relative-phase toffoli gates with an application to multiple control toffoli optimization. Physical Review A, 93: 022311, Feb. 2016. [cited by applicant]
Dmitri Maslov and Yunseong Nam. Use of global interactions in efficient quantum circuit constructions. New Journal of Physics, 20 (3): 033018, Mar. 2018. [cited by applicant]
Yunseong Nam and Dmitri Maslov. Low-cost quantum circuits for classically intractable instances of the hamiltonian dynamics simulation problem. npj Quantum Information, 5 (1): 44, 2019. [cited by applicant]
Yunseong Nam, Neil J. Ross, Yuan Su, Andrew M. Childs, and Dmitri Maslov. Automated optimization of large quantum circuits with continuous parameters. npj Quantum Information, 4 (1): 23, 2018. [cited by applicant]
Yunseong Nam, Yuan Su, and Dmitri Maslov. Approximate quantum fourier transform with o(n log(n)) t gates. npj Quantum Information, 6 (1), Mar. 2020b. ISSN 2056-6387. [cited by applicant]
P. J. J. O'Malley, R. Babbush, I. D. Kivlichan, J. Romero, J. R. McClean, R. Barends, J. Kelly, P. Roushan, A. Tranter, N. Ding, B. Campbell, Y. Chen, Z. Chen, B. Chiaro, A. Dunsworth, A. G. Fowler, E. Jeffrey, E. Lucer… [cited by applicant]
Ketan N. Patel, Igor L. Markov, and John P. Hayes. Optimal synthesis of linear reversible circuits. Quantum Info. Comput., 8 (3): 282-294, Mar. 2008. ISSN 1533-7146. [cited by applicant]
Alberto Peruzzo, Jarrod McClean, Peter Shadbolt, Man-Hong Yung, Xiao-Qi Zhou, Peter J. Love, Alan Aspuru-Guzik, and Jeremy L. O'Brien. A variational eigenvalue solver on a photonic quantum processor. Nature Communicatio… [cited by applicant]
David Poulin, Matthew B. Hastings, Dave Wecker, Nathan Wiebe, Andrew C. Doberty, and Matthias Troyer. The trotter step size required for accurate quantum simulation of quantum chemistry. Quantum Info. Comput., 15 (5-6):… [cited by applicant]
Markus Reiher, Nathan Wiebe, Krysta M. Svore, Dave Wecker, and Matthias Troyer. Elucidating reaction mechanisms on quantum computers. Proceedings of the National Academy of Sciences, 2017. [cited by applicant]
Jonathan Romero, Ryan Babbush, Jarrod R McClean, Cornelius Hempel, Peter J Love, and Alan Aspuru-Guzik. Strategies for quantum computing molecular energies using the unitary coupled cluster ansatz. Quantum Science and T… [cited by applicant]
Jacob T. Seeley, Martin J. Richard, and Peter J. Love. The bravyi-kitaev transformation for quantum computation of electronic structure. The Journal of Chemical Physics, 137 (22): 224109, 2012. [cited by applicant]
O. Shehab, K. Landsman, Y. Nam, D. Zhu, N. M. Linke, M. Keesan, R. C. Pooser, and C. Monroe. Toward convergence of effective-field-theory simulations on digital quantum computers. Physical Review A, 100: 062319, Dec. 20… [cited by applicant]
Mark Steudtner and Stephanie Wehner. Fermion-to-qubit mappings with varying resource requirements for quantum simulation. New Journal of Physics, 20 (6): 063010, Jun. 2018. [cited by applicant]
Masuo Suzuki. General theory of fractal path integrals with applications to many?body theories and statistical physics. Journal of Mathematical Physics, 32 (2): 400-407, 1991. [cited by applicant]
Andrew Tranter, Peter J. Love, Florian Mintert, Nathan Wiebe, and Peter V. Coveney. Ordering of trotterization: Impact on errors in quantum simulation of electronic structure. Entropy, 21 (12): 1218, Dec. 2019. [cited by applicant]
Dave Wecker, Bela Bauer, Bryan K. Clark, Matthew B. Hastings, and Matthias Troyer. Gate-count estimates for performing quantum chemistry on small quantum computers. Physical Review A, 90 (2), Aug. 2014. ISSN 1094-1622. … [cited by applicant]
James D. Whitfield, Jacob Biamonte, and Alan Aspuru-Guzik. Simulation of electronic structure hamiltonians using quantum computers. Molecular Physics, 109 (5): 735-750, 2011. [cited by applicant]
Ciyou Zhu, Richard H Byrd, Peihuang Lu, and Jorge Nocedal. Algorithm 778: L-bfgs-b: Fortran subroutines for large-scale bound-constrained optimization. ACM Transactions on mathematical software (TOMS), 23 (4): 550-560, … [cited by applicant]