Plato Data Intelligence.
Vertical Search & Ai.

Mitigation of readout noise in near-term quantum devices by classical post-processing based on detector tomography

Date:


Filip B. Maciejewski1,2,3, Zoltán Zimborás4,5,6, and Michał Oszmaniec2,3

1University of Warsaw, Faculty of Physics, Ludwika Pasteura 5, 02-093 Warszawa, Poland
2International Centre for Theory of Quantum Technologies, University of Gdansk, Wita Stwosza 63, 80-308 Gdansk, Poland
3Center for Theoretical Physics, Polish Academy of Sciences, Al. Lotników 32/46, 02-668 Warszawa, Poland
4Wigner Research Centre for Physics of the Hungarian Academy of Sciences, H-1525 Budapest, P.O.Box 49, Hungary
5BME-MTA Lendület Quantum Information Theory Research Group, Budapest, Hungary
6Mathematical Institute, Budapest University of Technology and Economics, P.O.Box 91, H-1111, Budapest, Hungary

Find this paper interesting or want to discuss? Scite or leave a comment on SciRate.

Abstract

We propose a simple scheme to reduce readout errors in experiments on quantum systems with finite number of measurement outcomes. Our method relies on performing classical post-processing which is preceded by Quantum Detector Tomography, i.e., the reconstruction of a Positive-Operator Valued Measure (POVM) describing the given quantum measurement device. If the measurement device is affected only by an invertible classical noise, it is possible to correct the outcome statistics of future experiments performed on the same device. To support the practical applicability of this scheme for near-term quantum devices, we characterize measurements implemented in IBM’s and Rigetti’s quantum processors. We find that for these devices, based on superconducting transmon qubits, classical noise is indeed the dominant source of readout errors. Moreover, we analyze the influence of the presence of coherent errors and finite statistics on the performance of our error-mitigation procedure. Applying our scheme on the IBM’s 5-qubit device, we observe a significant improvement of the results of a number of single- and two-qubit tasks including Quantum State Tomography (QST), Quantum Process Tomography (QPT), the implementation of non-projective measurements, and certain quantum algorithms (Grover’s search and the Bernstein-Vazirani algorithm). Finally, we present results showing improvement for the implementation of certain probability distributions in the case of five qubits.

Most researchers believe that quantum computing, if ever actually developed, could offer major advances in numerous areas of scientific research. Yet, this technology is currently in its infancy, and the state of the art devices suffer from various problems. One of the most serious obstacles we need to overcome is the noise affecting the qubits. In this context, an important task arises of developing methods to reduce the errors.

In this work, we focus on the noise affecting quantum measurements. We propose a simple procedure to mitigate measurement errors via classical post-processing of the experimental outcome statistics. The procedure works perfectly provided measurement noise is classical and one operates in the infinite-statistics regime. Naturally, neither of those two assumptions is fulfilled exactly in practice, therefore we study the performance of our mitigation scheme in the presence of their violations. Importantly, we show how to validate the model of noise via the procedure known as Quantum Detector Tomography, which allows one to obtain the classical description of the quantum detector.

Our aim is to present a paper exploring the whole procedure of readout error mitigation: from the detailed description of necessary assumptions, through validation of those, finishing at the implementation of presented ideas on the actual quantum hardware from IBM and Rigetti. We believe that such an approach makes the work accessible to readers not necessarily familiar with the formalism of quantum measurements.

To encourage the practical realization of our findings, we developed an open-source GitHub repository implementing the ideas from the paper https://github.com/fbm2718/QREM.

► BibTeX data

► References

[1] J. Preskill “Quantum Computing in the NISQ era and beyond” Quantum 2, 79 (2018).
https:/​/​doi.org/​https:/​/​doi.org/​10.22331/​q-2018-08-06-79

[2] H. Abraham, I. Y. Akhalwaya, G. Aleksandrowicz, T. Alexander, G. Alexandrowics, E. Arbel, A. Asfaw, C. Azaustre, AzizNgoueya, P. Barkoutsos, G. Barron, L. Bello, Y. Ben-Haim, D. Bevenius, L. S. Bishop, S. Bosch, S. Bravyi, D. Bucher, F. Cabrera, P. Calpin, L. Capelluto, J. Carballo, G. Carrascal, A. Chen, C.-F. Chen, R. Chen, J. M. Chow, C. Claus, C. Clauss, A. J. Cross, A. W. Cross, S. Cross, J. Cruz-Benito, C. Culver, A. D. Córcoles-Gonzales, S. Dague, T. E. Dandachi, M. Dartiailh, DavideFrr, A. R. Davila, D. Ding, J. Doi, E. Drechsler, Drew, E. Dumitrescu, K. Dumon, I. Duran, K. EL-Safty, E. Eastman, P. Eendebak, D. Egger, M. Everitt, P. M. Fernández, A. H. Ferrera, A. Frisch, A. Fuhrer, M. GEORGE, J. Gacon, Gadi, B. G. Gago, J. M. Gambetta, A. Gammanpila, L. Garcia, S. Garion, J. Gomez-Mosquera, S. Puente González, I. Gould, D. Greenberg, D. Grinko, W. Guan, J. A. Gunnels, I. Haide, I. Hamamura, V. Havlicek, J. Hellmers, Ł. Herok, S. Hillmich, H. Horii, C. Howington, S. Hu, W. Hu, H. Imai, T. Imamichi, K. Ishizaki, R. Iten, T. Itoko, A. Javadi-Abhari, Jessica, K. Johns, T. Kachmann, N. Kanazawa, Kang-Bae, A. Karazeev, P. Kassebaum, S. King, Knabberjoe, A. Kovyrshin, V. Krishnan, K. Krsulich, G. Kus, R. LaRose, R. Lambert, J. Latone, S. Lawrence, D. Liu, P. Liu, Y. Maeng, A. Malyshev, J. Marecek, M. Marques, D. Mathews, A. Matsuo, D. T. McClure, C. McGarry, D. McKay, D. McPherson, S. Meesala, M. Mevissen, A. Mezzacapo, R. Midha, Z. Minev, A. Mitchell, N. Moll, M. D. Mooring, R. Morales, N. Moran, P. Murali, J. Müggenburg, D. Nadlinger, G. Nannicini, P. Nation, Y. Naveh, P. Neuweiler, P. Niroula, H. Norlen, L. J. O’Riordan, O. Ogunbayo, P. Ollitrault, S. Oud, D. Padilha, H. Paik, S. Perriello, A. Phan, M. Pistoia, A. Pozas-iKerstjens, V. Prutyanov, D. Puzzuoli, J. Pérez, Quintiii, R. Raymond, R. M.-C. Redondo, M. Reuter, J. Rice, D. M. Rodríguez, M. Rossmannek, M. Ryu, T. SAPV, SamFerracin, M. Sandberg, N. Sathaye, B. Schmitt, C. Schnabel, Z. Schoenfeld, T. L. Scholten, E. Schoute, J. Schwarm, I. F. Sertage, K. Setia, N. Shammah, Y. Shi, A. Silva, A. Simonetto, N. Singstock, Y. Siraichi, I. Sitdikov, S. Sivarajah, M. B. Sletfjerding, J. A. Smolin, M. Soeken, I. O. Sokolov, SooluThomas, D. Steenken, M. Stypulkoski, J. Suen, H. Takahashi, I. Tavernelli, C. Taylor, P. Taylour, S. Thomas, M. Tillet, M. Tod, E. Torre, K. Trabing, M. Treinish, TrishaPe, W. Turner, Y. Vaknin, C. R. Valcarce, F. Varchon, A. C. Vazquez, D. Vogt-Lee, C. Vuillot, J. Weaver, R. Wieczorek, J. A. Wildstrom, R. Wille, E. Winston, J. J. Woehr, S. Woerner, R. Woo, C. J. Wood, R. Wood, S. Wood, J. Wootton, D. Yeralin, R. Young, J. Yu, C. Zachow, L. Zdanski, C. Zoufal, Zoufalc, azulehner, bcamorrison, brandhsn, zz, dan1pal, dime10, drholmie, elfrocampeador, faisaldebouni, fanizzamarco, gruu, kanejess, klinvill, kurarrr, lerongil, ma5x, aharoni, ordmoj, sethmerkel, strickroman, sumitpuri, tigerjack, toural, vvilpas, welien, willhbang, yang.luh, yelojakit, and yotamvakninibm, “Qiskit: An Open-source Framework for Quantum Computing” (2019).
https:/​/​doi.org/​10.5281/​zenodo.2562110

[3] IBM “https:/​/​quantumexperience.ng.bluemix.net/​qx/​” (Access: 2018.12.28).
https:/​/​quantumexperience.ng.bluemix.net/​qx/​

[4] Rigetti “https:/​/​www.rigetti.com/​forest” (Access: 2018.12.28).
https:/​/​www.rigetti.com/​forest

[5] D-Wave “https:/​/​cloud.dwavesys.com/​qubist/​”.
https:/​/​cloud.dwavesys.com/​qubist/​

[6] M. A. Nielsenand I. L. Chuang “Quantum Computation and Quantum Information: 10th Anniversary Edition” Cambridge University Press (2010).
https:/​/​doi.org/​10.1017/​CBO9780511976667

[7] I. M. Georgescu, S. Ashhab, and F. Nori, “Quantum simulation” Reviews of Modern Physics 86, 153-185 (2014).
https:/​/​doi.org/​10.1103/​RevModPhys.86.153
arXiv:1308.6253

[8] K. Tamuraand Y. Shikano “Quantum Random Numbers generated by the Cloud Superconducting Quantum Computer” (2019).
arXiv:1906.04410

[9] Y. Liand S. C. Benjamin “Efficient variational quantum simulator incorporating active error minimisation” Phys Rev X 7, 021050 (2017).
https:/​/​doi.org/​https:/​/​doi.org/​10.1103/​PhysRevX.7.021050
arXiv:1611.09301

[10] A. Kandala, A. Mezzacapo, K. Temme, M. Takita, M. Brink, J. M. Chow, and J. M. Gambetta, “Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets” Nature 549, 242-246 (2017).
https:/​/​doi.org/​10.1038/​nature23879
arXiv:1704.05018

[11] A. Kandala, K. Temme, A. D. Corcoles, A. Mezzacapo, J. M. Chow, and J. M. Gambetta, “Extending the computational reach of a noisy superconducting quantum processor” Nature 567, 491 (2019).
https:/​/​doi.org/​https:/​/​doi.org/​10.1038/​s41586-019-1040-7
arXiv:1805.04492

[12] K. Temme, S. Bravyi, and J. M. Gambetta, “Error Mitigation for Short-Depth Quantum Circuits” Phys. Rev. Lett. 119, 180509 (2017).
https:/​/​doi.org/​10.1103/​PhysRevLett.119.180509
arXiv:1612.02058

[13] S. Endo, S. C. Benjamin, and Y. Li, “Practical Quantum Error Mitigation for Near-Future Applications” Physical Review X 8, 031027 (2018).
https:/​/​doi.org/​10.1103/​PhysRevX.8.031027
arXiv:1712.09271

[14] V. N. Premakumarand R. Joynt “Error Mitigation in Quantum Computers subject to Spatially Correlated Noise” arXiv e-prints arXiv:1812.07076 (2018).
arXiv:1812.07076

[15] X. Bonet-Monroig, R. Sagastizabal, M. Singh, and T. E. O’Brien, “Low-cost error mitigation by symmetry verification” Phys. Rev. A 98, 062339 (2018).
https:/​/​doi.org/​10.1103/​PhysRevA.98.062339
arXiv:1807.10050

[16] J. Combes, C. Granade, C. Ferrie, and S. T. Flammia, “Logical Randomized Benchmarking” arXiv e-prints (2017).
arXiv:1702.03688

[17] M. Sunand M. R. Geller “Efficient characterization of correlated SPAM errors” arXiv e-prints (2018).
arXiv:1810.10523

[18] J. S. Lundeen, A. Feito, H. Coldenstrodt-Ronge, K. L. Pregnell, C. Silberhorn, T. C. Ralph, J. Eisert, M. B. Plenio, and I. A. Walmsley, “Tomography of quantum detectors” Nature Physics 5, 27 (2008).
https:/​/​doi.org/​10.1038/​nphys1133

[19] L. Zhang, H. B. Coldenstrodt-Ronge, A. Datta, G. Puentes, J. S. Lundeen, X.-M. Jin, B. J. Smith, M. B. Plenio, and I. A. Walmsley, “Mapping coherence in measurement via full quantum tomography of a hybrid optical detector” Nature Photonics 6, 364 (2012).
https:/​/​doi.org/​10.1038/​nphoton.2012.107

[20] L. Zhang, A. Datta, H. B. Coldenstrodt-Ronge, X.-M. Jin, J. Eisert, M. B. Plenio, and I. A. Walmsley, “Recursive quantum detector tomography” New Journal of Physics 14, 115005 (2012).
https:/​/​doi.org/​10.1088/​1367-2630/​14/​11/​115005
arXiv:1207.3501

[21] J. J. Renema, G. Frucci, Z. Zhou, F. Mattioli, A. Gaggero, R. Leoni, Dood, A. Fiore, and M. P. Exter, “Modified detector tomography technique applied to a superconducting multiphoton nanodetector” Opt. Express 20, 2806-2813 (2012).
https:/​/​doi.org/​10.1364/​OE.20.002806
http:/​/​www.opticsexpress.org/​abstract.cfm?URI=oe-20-3-2806

[22] J. Z. Blumoff, K. Chou, C. Shen, M. Reagor, C. Axline, R. T. Brierley, M. P. Silveri, C. Wang, B. Vlastakis, S. E. Nigg, L. Frunzio, M. H. Devoret, L. Jiang, S. M. Girvin, and R. J. Schoelkopf, “Implementing and Characterizing Precise Multiqubit Measurements” Phys. Rev. X 6, 031041 (2016).
https:/​/​doi.org/​10.1103/​PhysRevX.6.031041

[23] J. Koch, T. M. Yu, J. Gambetta, A. A. Houck, D. I. Schuster, J. Majer, A. Blais, M. H. Devoret, S. M. Girvin, and R. J. Schoelkopf, “Charge-insensitive qubit design derived from the Cooper pair box” Phys. Rev. A 76, 042319 (2007).
https:/​/​doi.org/​10.1103/​PhysRevA.76.042319

[24] M. Oszmaniec, F. B. Maciejewski, and Z. Puchała, “Simulating all quantum measurements using only projective measurements and postselection” Physical Review A 100 (2019).
https:/​/​doi.org/​10.1103/​physreva.100.012351

[25] L. K. Grover “A fast quantum mechanical algorithm for database search” arXiv e-prints quant-ph/​9605043 (1996).
arXiv:quant-ph/9605043

[26] E. Bernsteinand U. Vazirani “Quantum complexity theory” Proc. of the Twenty-Fifth Annual ACM Symposium on Theory of Computing (STOC ’93) 11–20 (1993).
https:/​/​doi.org/​DOI:10.1145/​167088.167097

[27] A. Peres “Quantum theory: Concepts and methods” Springer Science & Business Media (2006).
https:/​/​doi.org/​https:/​/​doi.org/​10.1007/​0-306-47120-5

[28] Z. Hradil, J. Řeháček, J. Fiurášek, and M. Ježek, “3 Maximum-Likelihood Methods in Quantum Mechanics” Springer Berlin Heidelberg (2004).
https:/​/​doi.org/​10.1007/​978-3-540-44481-7_3

[29] J. Fiurášek “Maximum-likelihood estimation of quantum measurement” Physical Review A 64, 024102 (2001).
https:/​/​doi.org/​10.1103/​PhysRevA.64.024102
arXiv:quant-ph/0101027

[30] A. W. Harrowand A. Montanaro “Quantum computational supremacy” Nature 549, 203-209 (2017).
https:/​/​doi.org/​10.1038/​nature23458
arXiv:1809.07442

[31] H. Pashayan, S. D. Bartlett, and D. Gross, “From estimation of quantum probabilities to simulation of quantum circuits” Quantum 4, 223 (2020).
https:/​/​doi.org/​10.22331/​q-2020-01-13-223

[32] M. Navascuésand S. Popescu “How Energy Conservation Limits Our Measurements” Phys. Rev. Lett. 112, 140502 (2014).
https:/​/​doi.org/​10.1103/​PhysRevLett.112.140502
arXiv:1211.2101

[33] Z. Puchała, Ł. Pawela, A. Krawiec, and R. Kukulski, “Strategies for optimal single-shot discrimination of quantum measurements” Phys. Rev. A 98, 042103 (2018).
https:/​/​doi.org/​10.1103/​PhysRevA.98.042103
arXiv:1804.05856

[34] Z. Puchała, Ł. Pawela, A. r. Krawiec, R. Kukulski, and M. Oszmaniec, “Multiple-shot and unambiguous discrimination of von Neumann measurements” arXiv e-prints arXiv:1810.05122 (2018).
arXiv:1810.05122

[35] J. Watrous “The Theory of Quantum Information” Cambridge University Press (2018).
https:/​/​doi.org/​10.1017/​9781316848142

[36] E. Haapasalo, T. Heinosaari, and J.-P. Pellonpaa, “Quantum measurements on finite dimensional systems: relabeling and mixing” Quant. Inf. Process. 11, 1751-1763 (2012).
https:/​/​doi.org/​10.1007/​s11128-011-0330-2

[37] M. Oszmaniec, L. Guerini, P. Wittek, and A. Acín, “Simulating Positive-Operator-Valued Measures with Projective Measurements” Physical Review Letters 119, 190501 (2017).
https:/​/​doi.org/​10.1103/​PhysRevLett.119.190501
arXiv:1609.06139

[38] L. Guerini, J. Bavaresco, M. Terra Cunha, and A. Acín, “Operational framework for quantum measurement simulability” Journal of Mathematical Physics 58, 092102 (2017).
https:/​/​doi.org/​10.1063/​1.4994303
arXiv:1705.06343

[39] E. Knill, D. Leibfried, R. Reichle, J. Britton, R. B. Blakestad, J. D. Jost, C. Langer, R. Ozeri, S. Seidelin, and D. J. Wineland, “Randomized benchmarking of quantum gates” Physical Review A 77, 012307 (2008).
https:/​/​doi.org/​10.1103/​PhysRevA.77.012307
arXiv:0707.0963

[40] J. M. Gambetta, A. D. Córcoles, S. T. Merkel, B. R. Johnson, J. A. Smolin, J. M. Chow, C. A. Ryan, C. Rigetti, S. Poletto, T. A. Ohki, M. B. Ketchen, and M. Steffen, “Characterization of Addressability by Simultaneous Randomized Benchmarking” Phys. Rev. Lett. 109, 240504 (2012).
https:/​/​doi.org/​10.1103/​PhysRevLett.109.240504
arXiv:1204.6308

[41] M. Guta, J. Kahn, R. Kueng, and J. A. Tropp, “Fast state tomography with optimal error bounds” arXiv e-prints arXiv:1809.11162 (2018).
arXiv:1809.11162

[42] T. Weissman, E. Ordentlich, G. Seroussi, S. Verdul, and M. J. Weinberger, “Inequalities for the L1 Deviation of the Empirical Distribution” Technical Report HPL-2003-97R1, Hewlett-Packard Labs (2003).

[43] M. S. Andersen, J. Dahl, and L. Vandenberghe, “CVXOPT: A Python package for convex optimization, version 1.2” (2019).
https:/​/​cvxopt.org/​

[44] IBM “Qiskit Github repository” (Access: 2019.07.09).

[45] R. Blume-Kohout, J. King Gamble, E. Nielsen, J. Mizrahi, J. D. Sterk, and P. Maunz, “Robust, self-consistent, closed-form tomography of quantum logic gates on a trapped ion qubit” arXiv e-prints arXiv:1310.4492 (2013).
arXiv:1310.4492

[46] S. T. Merkel, J. M. Gambetta, J. A. Smolin, S. Poletto, A. D. Córcoles, B. R. Johnson, C. A. Ryan, and M. Steffen, “Self-consistent quantum process tomography” Phys. Rev. A 87, 062119 (2013).
https:/​/​doi.org/​10.1103/​PhysRevA.87.062119
arXiv:1211.0322

[47] M. D. Mazurek, M. F. Pusey, K. J. Resch, and R. W. Spekkens, “Experimentally bounding deviations from quantum theory in the landscape of generalized probabilistic theories” arXiv e-prints arXiv:1710.05948 (2017).
arXiv:1710.05948

[48] E. Farhi, J. Goldstone, and S. Gutmann, “A Quantum Approximate Optimization Algorithm” arXiv e-prints arXiv:1411.4028 (2014).
arXiv:1411.4028

[49] J. A. Smolin, J. M. Gambetta, and G. Smith, “Maximum Likelihood, Minimum Effort” Phys. Rev. Lett 108, 070502 (2012).
https:/​/​doi.org/​10.1103/​PhysRevLett.108.070502
arXiv:1106.5458

[50] B. Schumacher “Sending quantum entanglement through noisy channels” arXiv e-prints quant-ph/​9604023 (1996).
arXiv:quant-ph/9604023

[51] P. Horodecki, M. Horodecki, and R. Horodecki, “General teleportation channel, singlet fraction and quasi-distillation” arXiv e-prints quant-ph/​9807091 (1998).
arXiv:quant-ph/9807091

[52] A. Chefles “Unambiguous discrimination between linearly independent quantum states” Physics Letters A 239, 339-347 (1998).
https:/​/​doi.org/​10.1016/​S0375-9601(98)00064-4
arXiv:quant-ph/9807022

[53] S. M. Barnettand S. Croke “Quantum state discrimination” Advances in Optics and Photonics 1, 238 (2009).
https:/​/​doi.org/​10.1364/​AOP.1.000238
arXiv:0810.1970

[54] J. M. Renes, R. Blume-Kohout, A. J. Scott, and C. M. Caves, “Symmetric informationally complete quantum measurements” Journal of Mathematical Physics 45, 2171-2180 (2004).
https:/​/​doi.org/​10.1063/​1.1737053
arXiv:quant-ph/0310075

[55] S. Ishizakaand T. Hiroshima “Asymptotic Teleportation Scheme as a Universal Programmable Quantum Processor” Phys. Rev. Lett. 101, 240501 (2008).
https:/​/​doi.org/​10.1103/​PhysRevLett.101.240501
arXiv:0807.4568

[56] A. M. Childsand W. Dam “Quantum algorithms for algebraic problems” Rev. Mod. Phys. 82, 1-52 (2010).
https:/​/​doi.org/​10.1103/​RevModPhys.82.1

[57] J. Preskill “Quantum computing and the entanglement frontier” arXiv e-prints (2012).
arXiv:1203.5813

[58] P. J. Coles, S. Eidenbenz, S. Pakin, A. Adedoyin, J. Ambrosiano, P. Anisimov, W. Casper, G. Chennupati, C. Coffrin, H. Djidjev, D. Gunter, S. Karra, N. Lemons, S. Lin, A. Lokhov, A. Malyzhenkov, D. Mascarenas, S. Mniszewski, B. Nadiga, D. O’Malley, D. Oyen, L. Prasad, R. Roberts, P. Romero, N. Santhi, N. Sinitsyn, P. Swart, M. Vuffray, J. Wendelberger, B. Yoon, R. Zamora, and W. Zhu, “Quantum Algorithm Implementations for Beginners” arXiv e-prints (2018).
arXiv:1804.03719

[59] .

[60] N. Moll, P. Barkoutsos, L. S. Bishop, J. M. Chow, A. Cross, D. J. Egger, S. Filipp, A. Fuhrer, J. M. Gambetta, and M. Ganzhorn, “Quantum optimization using variational algorithms on near-term quantum devices” Quantum Science and Technology 3, 030503 (2018).
https:/​/​doi.org/​10.1088/​2058-9565/​aab822
arXiv:1710.01022

[61] J. Wang, V. B. Scholz, and R. Renner, “Confidence Polytopes in Quantum State Tomography” Phys. Rev. Lett. 122, 190401 (2019).
https:/​/​doi.org/​10.1103/​PhysRevLett.122.190401
arXiv:1808.09988

[62] Y. Chen, M. Farahzad, S. Yoo, and T.-C. Wei, “Detector tomography on IBM quantum computers and mitigation of an imperfect measurement” Physical Review A 100 (2019).
https:/​/​doi.org/​10.1103/​physreva.100.052315

Cited by

[1] E. O. Kiktenko, A. O. Malyshev, A. S. Mastiukova, V. I. Man’ko, A. K. Fedorov, and D. Chruściński, “Probability representation of quantum dynamics using pseudostochastic maps”, arXiv:1908.03404, Physical Review A 101 5, 052320 (2020).

[2] Benjamin Nachman, Miroslav Urbanek, Wibe A. de Jong, and Christian W. Bauer, “Unfolding Quantum Computer Readout Noise”, arXiv:1910.01969.

[3] Hyeokjea Kwon and Joonwoo Bae, “A hybrid quantum-classical approach to mitigating measurement errors”, arXiv:2003.12314.

[4] Megan N. Lilly and Travis S. Humble, “Modeling Noisy Quantum Circuits Using Experimental Characterization”, arXiv:2001.08653.

[5] Pranav Gokhale, Ali Javadi-Abhari, Nathan Earnest, Yunong Shi, and Frederic T. Chong, “Optimized Quantum Compilation for Near-Term Algorithms with OpenPulse”, arXiv:2004.11205.

The above citations are from Crossref’s cited-by service (last updated successfully 2020-06-04 00:01:08) and SAO/NASA ADS (last updated successfully 2020-06-04 00:01:09). The list may be incomplete as not all publishers provide suitable and complete citation data.

Source: https://quantum-journal.org/papers/q-2020-04-24-257/

spot_img

Latest Intelligence

spot_img

Chat with us

Hi there! How can I help you?