Purification-based quantum error mitigation of pair-correlated electron
simulations
- URL: http://arxiv.org/abs/2210.10799v1
- Date: Wed, 19 Oct 2022 18:00:03 GMT
- Title: Purification-based quantum error mitigation of pair-correlated electron
simulations
- Authors: T. E. O'Brien, G. Anselmetti, F. Gkritsis, V. E. Elfving, S. Polla, W.
J. Huggins, O. Oumarou, K. Kechedzhi, D. Abanin, R. Acharya, I. Aleiner, R.
Allen, T. I. Andersen, K. Anderson, M. Ansmann, F. Arute, K. Arya, A. Asfaw,
J. Atalaya, D. Bacon, J. C. Bardin, A. Bengtsson, S. Boixo, G. Bortoli, A.
Bourassa, J. Bovaird, L. Brill, M. Broughton, B. Buckley, D. A. Buell, T.
Burger, B. Burkett, N. Bushnell, J. Campero, Y. Chen, Z. Chen, B. Chiaro, D.
Chik, J. Cogan, R. Collins, P. Conner, W. Courtney, A. L. Crook, B. Curtin,
D. M. Debroy, S. Demura, I. Drozdov, A. Dunsworth, C. Erickson, L. Faoro, E.
Farhi, R. Fatemi, V. S. Ferreira, L. Flores Burgos, E. Forati, A. G. Fowler,
B. Foxen, W. Giang, C. Gidney, D. Gilboa, M. Giustina, R. Gosula, A. Grajales
Dau, J. A. Gross, S. Habegger, M. C. Hamilton, M. Hansen, M. P. Harrigan, S.
D. Harrington, P. Heu, J. Hilton, M. R. Hoffmann, S. Hong, T. Huang, A. Huff,
L. B. Ioffe, S. V. Isakov, J. Iveland, E. Jeffrey, Z. Jiang, C. Jones, P.
Juhas, D. Kafri, J. Kelly, T. Khattar, M. Khezri, M. Kieferov\'a, S. Kim, P.
V. Klimov, A. R. Klots, R. Kothari, A. N. Korotkov, F. Kostritsa, J. M.
Kreikebaum, D. Landhuis, P. Laptev, K. Lau, L. Laws, J. Lee, K. Lee, B. J.
Lester, A. T. Lill, W. Liu, W. P. Livingston, A. Locharla, E. Lucero, F. D.
Malone, S. Mandra, O. Martin, S. Martin, J. R. McClean, T. McCourt, M.
McEwen, A. Megrant, X. Mi, A. Mieszala, K. C. Miao, M. Mohseni, S. Montazeri,
A. Morvan, R. Movassagh, W. Mruczkiewicz, O. Naaman, M. Neeley, C. Neill, A.
Nersisyan, H. Neven, M. Newman, J. H. Ng, A. Nguyen, M. Nguyen, M. Y. Niu, S.
Omonije, A. Opremcak, A. Petukhov, R. Potter, L. P. Pryadko, C. Quintana, C.
Rocque, P. Roushan, N. Saei, D. Sank, K. Sankaragomathi, K. J. Satzinger, H.
F. Schurkus, C. Schuster, M. J. Shearn, A. Shorter, N. Shutty, V. Shvarts, J.
Skruzny, V. Smelyanskiy, W. C. Smith, R. Somma, G. Sterling, D. Strain, M.
Szalay, D. Thor, A. Torres, G. Vidal, B. Villalonga, C. Vollgraff
Heidweiller, T. White, B. W. K. Woo, C. Xing, Z. J. Yao, P. Yeh, J. Yoo, G.
Young, A. Zalcman, Y. Zhang, N. Zhu, N. Zobrist, C. Gogolin, R. Babbush, and
N. C. Rubin
- Abstract summary: We compare the performance of error mitigation based on doubling quantum resources in time (echo verification) or in space (virtual distillation) on up to $20$ qubits of a superconducting qubit quantum processor.
We observe a reduction of error by one to two orders of magnitude below less sophisticated techniques.
We find that, despite the impressive gains from purification-based error mitigation, significant hardware improvements will be required for classically intractable variational chemistry simulations.
- Score: 0.5939007745452041
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: An important measure of the development of quantum computing platforms has
been the simulation of increasingly complex physical systems. Prior to
fault-tolerant quantum computing, robust error mitigation strategies are
necessary to continue this growth. Here, we study physical simulation within
the seniority-zero electron pairing subspace, which affords both a
computational stepping stone to a fully correlated model, and an opportunity to
validate recently introduced ``purification-based'' error-mitigation
strategies. We compare the performance of error mitigation based on doubling
quantum resources in time (echo verification) or in space (virtual
distillation), on up to $20$ qubits of a superconducting qubit quantum
processor. We observe a reduction of error by one to two orders of magnitude
below less sophisticated techniques (e.g. post-selection); the gain from error
mitigation is seen to increase with the system size. Employing these error
mitigation strategies enables the implementation of the largest variational
algorithm for a correlated chemistry system to-date. Extrapolating performance
from these results allows us to estimate minimum requirements for a
beyond-classical simulation of electronic structure. We find that, despite the
impressive gains from purification-based error mitigation, significant hardware
improvements will be required for classically intractable variational chemistry
simulations.
Related papers
- Efficient Learning for Linear Properties of Bounded-Gate Quantum Circuits [63.733312560668274]
Given a quantum circuit containing d tunable RZ gates and G-d Clifford gates, can a learner perform purely classical inference to efficiently predict its linear properties?
We prove that the sample complexity scaling linearly in d is necessary and sufficient to achieve a small prediction error, while the corresponding computational complexity may scale exponentially in d.
We devise a kernel-based learning model capable of trading off prediction error and computational complexity, transitioning from exponential to scaling in many practical settings.
arXiv Detail & Related papers (2024-08-22T08:21:28Z) - Near-Term Distributed Quantum Computation using Mean-Field Corrections
and Auxiliary Qubits [77.04894470683776]
We propose near-term distributed quantum computing that involve limited information transfer and conservative entanglement production.
We build upon these concepts to produce an approximate circuit-cutting technique for the fragmented pre-training of variational quantum algorithms.
arXiv Detail & Related papers (2023-09-11T18:00:00Z) - Compilation of a simple chemistry application to quantum error correction primitives [44.99833362998488]
We estimate the resources required to fault-tolerantly perform quantum phase estimation on a minimal chemical example.
We find that implementing even a simple chemistry circuit requires 1,000 qubits and 2,300 quantum error correction rounds.
arXiv Detail & Related papers (2023-07-06T18:00:10Z) - Classical-to-Quantum Transfer Learning Facilitates Machine Learning with Variational Quantum Circuit [62.55763504085508]
We prove that a classical-to-quantum transfer learning architecture using a Variational Quantum Circuit (VQC) improves the representation and generalization (estimation error) capabilities of the VQC model.
We show that the architecture of classical-to-quantum transfer learning leverages pre-trained classical generative AI models, making it easier to find the optimal parameters for the VQC in the training stage.
arXiv Detail & Related papers (2023-05-18T03:08:18Z) - Experimental quantum computational chemistry with optimised unitary coupled cluster ansatz [23.6818896497932]
Experimental realisation of scalable and high-precision quantum chemistry simulation remains elusive.
We push forward the limit of experimental quantum computational chemistry and successfully scale up the implementation of VQE with an optimised unitary coupled-cluster ansatz to 12 qubits.
arXiv Detail & Related papers (2022-12-15T18:04:28Z) - Analytical and experimental study of center line miscalibrations in M\o
lmer-S\o rensen gates [51.93099889384597]
We study a systematic perturbative expansion in miscalibrated parameters of the Molmer-Sorensen entangling gate.
We compute the gate evolution operator which allows us to obtain relevant key properties.
We verify the predictions from our model by benchmarking them against measurements in a trapped-ion quantum processor.
arXiv Detail & Related papers (2021-12-10T10:56:16Z) - Hardware-Efficient, Fault-Tolerant Quantum Computation with Rydberg
Atoms [55.41644538483948]
We provide the first complete characterization of sources of error in a neutral-atom quantum computer.
We develop a novel and distinctly efficient method to address the most important errors associated with the decay of atomic qubits to states outside of the computational subspace.
Our protocols can be implemented in the near-term using state-of-the-art neutral atom platforms with qubits encoded in both alkali and alkaline-earth atoms.
arXiv Detail & Related papers (2021-05-27T23:29:53Z) - Improving readout in quantum simulations with repetition codes [0.0]
We use repetition codes as scalable schemes with the potential to provide more accurate solutions to problems of interest in quantum chemistry and physics.
We showcase our approach in multiple IBM Quantum devices and validate our results using a simplified theoretical noise model.
arXiv Detail & Related papers (2021-05-27T18:01:05Z) - Enhancing quantum models of stochastic processes with error mitigation [0.0]
We bridge the gap between theoretical quantum models and practical use with the inclusion of error mitigation methods.
It is observed that error mitigation is successful in improving the resultant expectation values.
While our results indicate that error mitigation work, we show that its methodology is ultimately constrained by hardware limitations in these quantum computers.
arXiv Detail & Related papers (2021-05-13T17:45:34Z) - As Accurate as Needed, as Efficient as Possible: Approximations in
DD-based Quantum Circuit Simulation [5.119310422637946]
Decision Diagrams (DDs) have previously shown to reduce the required memory in many important cases by exploiting redundancies in the quantum state.
We show that this reduction can be amplified by exploiting the probabilistic nature of quantum computers to achieve even more compact representations.
Specifically, we propose two new DD-based simulation strategies that approximate the quantum states to attain more compact representations.
arXiv Detail & Related papers (2020-12-10T12:02:03Z) - Benchmarking adaptive variational quantum eigensolvers [63.277656713454284]
We benchmark the accuracy of VQE and ADAPT-VQE to calculate the electronic ground states and potential energy curves.
We find both methods provide good estimates of the energy and ground state.
gradient-based optimization is more economical and delivers superior performance than analogous simulations carried out with gradient-frees.
arXiv Detail & Related papers (2020-11-02T19:52:04Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.