Fidelity; Matrix completion; NISQ; Pauli operators; Quantum state tomography; Singular value decomposition; Benchmarking tools; Low-rank matrix completions; Post-processing; Quantum device; Quantum state; Quantum Information
Abstract :
[en] This paper introduces a novel and efficient technique for quantum state estimation, coined as low-rank matrix-completion quantum state tomography for characterizing pure quantum states, as it requires only non-entangling bases and 2n+1 local Pauli operators. This significantly reduces the complexity of the process and increases the accuracy of the state estimation, as it eliminates the need for the entangling bases, which are experimentally difficult to implement on quantum devices. The required minimal post-processing, improved accuracy and efficacy of this matrix-completion-based method make it an ideal benchmarking tool for investigating the properties of quantum systems, enabling researchers to verify the accuracy of quantum devices, characterize their performance, and explore the underlying physics of quantum phenomena. Our numerical results demonstrate that this method outperforms contemporary techniques in its ability to accurately reconstruct multi-qubit quantum states on real quantum devices, making it an invaluable contribution to the field of quantum state characterization and an essential step toward the reliable deployment of intermediate- and large-scale quantum devices.
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Tariq, Shehbaz; Department of Electronics and Information Convergence Engineering, Kyung Hee University, Yongin-si, South Korea
Farooq, Ahmad; Department of Electronics and Information Convergence Engineering, Kyung Hee University, Yongin-si, South Korea ; Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland
UR REHMAN, Junaid ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom
Duong, Trung Q.; Department of Electrical and Computer Engineering, Memorial University of Newfoundland, St. John’s, Canada
Shin, Hyundong; Department of Electronics and Information Convergence Engineering, Kyung Hee University, Yongin-si, South Korea
External co-authors :
yes
Language :
English
Title :
Efficient quantum state estimation with low-rank matrix completion
Publication date :
August 2024
Journal title :
EPJ Quantum Technology
eISSN :
2196-0763
Publisher :
Springer Science and Business Media Deutschland GmbH
National Research Foundation of Korea Institute for Information & Communications Technology Planning & Evaluation
Funding text :
We acknowledge the use of the IBM Q for this work. The views expressed are those of the authors and do not reflect the official policy or position of IBM or the IBM Quantum team.This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2022R1A4A3033401) and by the MSIT (Ministry of Science and ICT), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2021-0-02046) supervised by the IITP (Institute for Information & Communications Technology Planning & Evaluation).
J. Preskill Quantum computing in the NISQ era and beyond Quantum 2018 2 10.22331/q-2018-08-06-79
A. Kandala A. Mezzacapo K. Temme M. Takita M. Brink J.M. Chow J.M. Gambetta Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets Nature 2017 549 7671 242 246 2017Natur.549.242K 10.1038/nature23879
J. Zhang G. Pagano P.W. Hess A. Kyprianidis P. Becker H. Kaplan A.V. Gorshkov Z.-X. Gong C. Monroe Observation of a many-body dynamical phase transition with a 53-qubit quantum simulator Nature 2017 551 7682 601 604 2017Natur.551.601Z 10.1038/nature24654
D. Loss D.P. DiVincenzo Quantum computation with quantum dots Phys Rev A 1998 57 120 126 1998PhRvA.57.120L 10.1103/PhysRevA.57.120
H. Bernien S. Schwartz A. Keesling H. Levine A. Omran H. Pichler S. Choi A.S. Zibrov M. Endres M. Greine et al. Probing many-body dynamics on a 51-atom quantum simulator Nature 2017 551 7682 579 584 2017Natur.551.579B 10.1038/nature24622
M. Reck A. Zeilinger H.J. Bernstein P. Bertani Experimental realization of any discrete unitary operator Phys Rev Lett 1994 73 58 61 1994PhRvL.73..58R 10.1103/PhysRevLett.73.58
B.M. Terhal Quantum supremacy, here we come Nat Phys 2018 14 6 530 531 10.1038/s41567-018-0131-y
L.S. Madsen F. Laudenbach M.F. Askarani F. Rortais T. Vincent J.F. Bulmer F.M. Miatto L. Neuhaus L.G. Helt M.J. Collins et al. Quantum computational advantage with a programmable photonic processor Nature 2022 606 7912 75 81 2022Natur.606..75M 10.1038/s41586-022-04725-x
F. Arute K. Arya R. Babbush D. Bacon J.C. Bardin R. Barends R. Biswas S. Boixo F.G. Brandao D.A. Buell et al. Quantum supremacy using a programmable superconducting processor Nature 2019 574 7779 505 510 2019Natur.574.505A 10.1038/s41586-019-1666-5
J. Eisert D. Hangleiter N. Walk I. Roth D. Markham R. Parekh U. Chabaud E. Kashefi Quantum certification and benchmarking Nat Rev Phys 2020 2 7 382 390 10.1038/s42254-020-0186-4
G. Torlai R.G. Melko Machine-learning quantum states in the NISQ era Annu Rev Condens Matter Phys 2020 11 1 325 344 2020ARCMP.11.325T 10.1146/annurev-conmatphys-031119-050651
A. Shabani R.L. Kosut M. Mohseni H. Rabitz M.A. Broome M.P. Almeida A. Fedrizzi A.G. White Efficient measurement of quantum dynamics via compressive sensing Phys Rev Lett 2011 106 2011PhRvL.106j0401S 10.1103/PhysRevLett.106.100401
S. Lloyd M. Mohseni P. Rebentrost Quantum principal component analysis Nat Phys 2014 10 9 631 633 10.1038/nphys3029
K. Banaszek G.M. D’Ariano M.G.A. Paris M.F. Sacchi Maximum-likelihood estimation of the density matrix Phys Rev A 1999 61 1999PhRvA.61a0304B 10.1103/PhysRevA.61.010304
T. Opatrný D.-G. Welsch W. Vogel Least-squares inversion for density-matrix reconstruction Phys Rev A 1997 56 1788 1799 1997PhRvA.56.1788O 10.1103/PhysRevA.56.1788
B. Qi Z. Hou L. Li D. Dongi G. Xiang G. Guo Quantum state tomography via linear regression estimation Sci Rep 2013 3 2013NatSR..3E3496Q 10.1038/srep03496
R. Blume-Kohout Optimal, reliable estimation of quantum states New J Phys 2010 12 4 10.1088/1367-2630/12/4/043034
V.V. Dodonov V.I. Man’ko Positive distribution description for spin states Phys Lett A 1997 229 6 335 339 1997PhLA.229.335D 1455834 10.1016/S0375-9601(97)00199-0
J.-P. Amiet S. Weigert Reconstructing a pure state of a spinsthrough three Stern-Gerlach measurements J Phys A, Math Gen 1999 32 15 2777 2784 1999JPhA..32.2777A 10.1088/0305-4470/32/15/006
A. Steffens C.A. Riofrío W. McCutcheon I. Roth B.A. Bell A. McMillan M.S. Tame J.G. Rarity J. Eisert Experimentally exploring compressed sensing quantum tomography Quantum Sci Technol 2017 2 2 2017QS&T..2b5005S 10.1088/2058-9565/aa6ae2
R. Kueng H. Rauhut U. Terstiege Low rank matrix recovery from rank one measurements Appl Comput Harmon Anal 2017 42 1 88 116 3574562 10.1016/j.acha.2015.07.007
E. Bolduc G.C. Knee E.M. Gauger J. Leach Projected gradient descent algorithms for quantum state tomography npj Quantum Inf 2017 3 1 1 9 10.1038/s41534-017-0043-1
W.K. Wootters B.D. Fields Optimal state-determination by mutually unbiased measurements Ann Phys 1989 191 2 363 381 1989AnPhy.191.363W 1003014 10.1016/0003-4916(89)90322-9
R.B.A. Adamson A.M. Steinberg Improving quantum state estimation with mutually unbiased bases Phys Rev Lett 2010 105 2010PhRvL.105c0406A 10.1103/PhysRevLett.105.030406
M. Cramer M.B. Plenio S.T. Flammia R. Somma D. Gross S.D. Bartlett O. Landon-Cardinal D. Poulin Y.-K. Liu Efficient quantum state tomography Nat Commun 2010 1 1 1 7 10.1038/ncomms1147
G. Tóth W. Wieczorek D. Gross R. Krischek C. Schwemmer H. Weinfurter Permutationally invariant quantum tomography Phys Rev Lett 2010 105 2010PhRvL.105y0403T 10.1103/PhysRevLett.105.250403
D. Goyeneche G. Cańas S. Etcheverry E.S. Gómez G.B. Xavier G. Lima A. Delgado Five measurement bases determine pure quantum states on any dimension Phys Rev Lett 2015 115 2015PhRvL.115i0401G 10.1103/PhysRevLett.115.090401
C. Carmeli T. Heinosaari M. Kech J. Schultz A. Toigo Stable pure state quantum tomography from five orthonormal bases Europhys Lett 2016 115 3 2016EL..11530001C 10.1209/0295-5075/115/30001
L. Zambrano L. Pereira D. Martínez G. Cańas G. Lima A. Delgado Estimation of pure states using three measurement bases Phys Rev Appl 2020 14 2020PhRvP.14f4004Z 10.1103/PhysRevApplied.14.064004
M. Rambach M. Qaryan M. Kewming C. Ferrie A.G. White J. Romero Robust and efficient high-dimensional quantum state tomography Phys Rev Lett 2021 126 2021PhRvL.126j0402R 10.1103/PhysRevLett.126.100402
C. Ferrie Self-guided quantum tomography Phys Rev Lett 2014 113 2014PhRvL.113s0404F 10.1103/PhysRevLett.113.190404
R.J. Chapman C. Ferrie A. Peruzzo Experimental demonstration of self-guided quantum tomography Phys Rev Lett 2016 117 2016PhRvL.117d0402C 10.1103/PhysRevLett.117.040402
L. Pereira L. Zambrano A. Delgado Scalable estimation of pure multi-qubit states npj Quantum Inf 2022 8 1 1 12 10.1038/s41534-022-00565-9
G. Strang Linear algebra and learning from data 2019 413 428 1(1)
C. Eckart G. Young The approximation of one matrix by another of lower rank Psychometrika 1936 1 3 211 218 10.1007/BF02288367
N.K. Kumar J. Schneider Literature survey on low rank approximation of matrices Linear Multilinear Algebra 2017 65 11 2212 2244 3740692 10.1080/03081087.2016.1267104
O. Troyanskaya M. Cantor G. Sherlock P. Brown T. Hastie R. Tibshirani D. Botstein R.B. Altman Missing value estimation methods for DNA microarrays Bioinformatics 2001 17 6 520 525 10.1093/bioinformatics/17.6.520
Cho M. Imputation of missing values by low rank matrix approximation. US Bureau of Labor Statistics 2021.
J.-F. Cai E.J. Cand‘es Z. Shen A singular value thresholding algorithm for matrix completion SIAM J Optim 2010 20 4 1956 1982 2600248 10.1137/080738970
7-qubit backend: IBM Q team, IBM Q 7 Jakarta backend specification v1.2.5. (Accessed: Jan 2023).