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Large-scale silicon quantum photonics implementing arbitrary two-qubit processing


Photonics is a promising platform for implementing universal quantum information processing. Its main challenges include precise control of massive circuits of linear optical components and effective implementation of entangling operations on photons. By using large-scale silicon photonic circuits to implement an extension of the linear combination of quantum operators scheme, we realize a fully programmable two-qubit quantum processor, enabling universal two-qubit quantum information processing in optics. The quantum processor is fabricated with mature CMOS-compatible processing and comprises more than 200 photonic components. We programmed the device to implement 98 different two-qubit unitary operations (with an average quantum process fidelity of 93.2 ± 4.5%), a two-qubit quantum approximate optimization algorithm, and efficient simulation of Szegedy directed quantum walks. This fosters further use of the linear-combination architecture with silicon photonics for future photonic quantum processors.

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Fig. 1: Quantum information processing circuits and schematic of the experimental set-up.
Fig. 2: Experimental realization of arbitrary two-qubit gates.
Fig. 3: Experimental realization of a two-qubit quantum approximate optimization algorithm.
Fig. 4: Experimental quantum simulation of Szegedy directed quantum walks.


  1. Ladd, T. D. et al. Quantum computers. Nature 464, 45–53 (2010).

    Article  ADS  Google Scholar 

  2. Silverstone, J. W., Bonneau, D., O’Brien, J. L. & Thompson, M. G. Silicon quantum photonics. IEEE J. Sel. Top. Quantum Electron. 22, 390–402 (2016).

    Article  ADS  Google Scholar 

  3. O’Brien, J. L., Furusawa, A. & Vučković, J. Photonic quantum technologies. Nat. Photon. 3, 687–695 (2009).

    Article  ADS  Google Scholar 

  4. Wilkes, C. M. et al. 60 dB high-extinction auto-configured Mach–Zehnder interferometer. Opt. Lett. 41, 5318–5321 (2016).

    Article  ADS  Google Scholar 

  5. Sun, J., Timurdogan, E., Yaacobi, A., Hosseini, E. S. & Watts, M. R. Large-scale nanophotonic phased array. Nature 493, 195–199 (2013).

    Article  ADS  Google Scholar 

  6. Harris, N. C. et al. Quantum transport simulations in a programmable nanophotonic processor. Nat. Photon. 11, 447–452 (2017).

    Article  ADS  Google Scholar 

  7. Knill, E., Laflamme, R. & Milburn, G. J. A scheme for efficient quantum computation with linear optics. Nature 409, 46–52 (2001).

    Article  ADS  Google Scholar 

  8. Zhou, X. Q. et al. Adding control to arbitrary unknown quantum operations. Nat. Commun. 2, 413 (2011).

    Article  Google Scholar 

  9. Long, G. L. General quantum interference principle and duality computer. Commun. Theor. Phys. 45, 825–844 (2006).

    Article  ADS  MathSciNet  Google Scholar 

  10. Politi, A., Cryan, M. J., Rarity, J. G., Yu, S. & O’Brien, J. L. Silica-on-silicon waveguide quantum circuits. Science 320, 646–649 (2008).

    Article  ADS  Google Scholar 

  11. Peruzzo, A. et al. Quantum walks of correlated photons. Science 329, 1500–1503 (2010).

    Article  ADS  Google Scholar 

  12. Spring, J. B. et al. Boson sampling on a photonic chip. Science 339, 798–801 (2013).

    Article  ADS  Google Scholar 

  13. Tillmann, M. et al. Experimental boson sampling. Nat. Photon. 7, 540–544 (2013).

    Article  ADS  Google Scholar 

  14. Crespi, A. et al. Integrated multimode interferometers with arbitrary designs for photonic boson sampling. Nat. Photon. 7, 545–549 (2013).

    Article  ADS  Google Scholar 

  15. Wang, J. et al. Multidimensional quantum entanglement with large-scale integrated optics. Science 360, 285–291 (2018).

    Article  ADS  MathSciNet  Google Scholar 

  16. Carolan, J. et al. Universal linear optics. Science 349, 711–716 (2015).

    Article  MathSciNet  MATH  Google Scholar 

  17. Sharping, J. E. et al. Generation of correlated photons in nanoscale silicon waveguides. Opt. Express 14, 12388–12393 (2006).

    Article  ADS  Google Scholar 

  18. Najafi, F. et al. On-chip detection of entangled photons by scalable integration of single-photon detectors. Nat. Commun. 6, 5873 (2014).

    Article  Google Scholar 

  19. Debnath, S. et al. Demonstration of a small programmable quantum computer with atomic qubits. Nature 536, 63–66 (2016).

    Article  ADS  Google Scholar 

  20. Vandersypen, L. M. K. et al. Experimental realization of Shor’s quantum factoring algorithm using nuclear magnetic resonance. Nature 414, 883–887 (2001).

    Article  ADS  Google Scholar 

  21. Song, C. et al. 10-qubit entanglement and parallel logic operations with a superconducting circuit. Phys. Rev. Lett. 119, 180511 (2017).

    Article  ADS  Google Scholar 

  22. Martn-López, E. et al. Experimental realization of Shor’s quantum factoring algorithm using qubit recycling. Nat. Photon. 6, 773–776 (2012).

    Article  ADS  Google Scholar 

  23. Barz, S. et al. A two-qubit photonic quantum processor and its application to solving systems of linear equations. Sci. Rep. 4, 6115 (2014).

    Article  Google Scholar 

  24. Wang, J. et al. Experimental quantum Hamiltonian learning. Nat. Phys. 13, 551–555 (2017).

    Article  Google Scholar 

  25. Santagati, R. et al. Silicon photonic processor of two-qubit entangling quantum logic. J. Opt. 19, 114006 (2017).

    Article  ADS  Google Scholar 

  26. Hanneke, D. et al. Realization of a programmable two-qubit quantum processor. Nat. Phys. 6, 13–16 (2010).

    Article  Google Scholar 

  27. Farhi, E., Goldstone, J. & Gutmann, S. A quantum approximate optimization algorithm. Preprint at (2014).

  28. Farhi, E., Goldstone, J. & Gutmann, S. A quantum approximate optimization algorithm applied to a bounded occurrence constraint problem. Preprint at (2014).

  29. Szegedy, M. Spectra of quantized walks and a \(\sqrt {{\rm{\delta}}{\rm{\varepsilon}}}\) rule. Preprint at (2004).

  30. Szegedy, M. in Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science 32–41 (IEEE, 2004).

  31. Childs, A. M. & Wiebe, N. Hamiltonian simulation using linear combinations of unitary operations. Quantum Inform. Comput. 12, 901–924 (2012).

    MathSciNet  MATH  Google Scholar 

  32. Childs, A. M., Kothari, R. & Somma, R. D. Quantum algorithm for systems of linear equations with exponentially improved dependence on precision. SIAM J. Comput. 46, 1920–1950 (2017).

    Article  MathSciNet  MATH  Google Scholar 

  33. Patel, R. B., Ho, J., Ferreyrol, F., Ralph, T. C. & Pryde, G. J. A quantum Fredkin gate. Sci. Adv. 2, e1501531 (2016).

    Article  ADS  Google Scholar 

  34. Wei, S. J., Ruan, D. & Long, G. L. Duality quantum algorithm efficiently simulates open quantum systems. Sci. Rep. 6, 30727 (2016).

    Article  ADS  Google Scholar 

  35. Qiang, X., Zhou, X., Aungskunsiri, K., Cable, H. & O’Brien, J. L. Quantum processing by remote quantum control. Quantum Sci. Technol. 2, 045002 (2017).

    Article  ADS  Google Scholar 

  36. Silverstone, J. W. et al. On-chip quantum interference between silicon photon-pair sources. Nat. Photon. 8, 104–108 (2014).

    Article  ADS  Google Scholar 

  37. Raussendorf, R. & Briegel, H. J. A one-way quantum computer. Phys. Rev. Lett. 86, 5188–5191 (2001).

    Article  ADS  Google Scholar 

  38. Okamoto, R. et al. An entanglement filter. Science 323, 483–485 (2009).

    Article  ADS  Google Scholar 

  39. Farhi, E. & Harrow, A. W. Quantum supremacy through the quantum approximate optimization algorithm. Preprint at (2016).

  40. Childs, A. M., Gosset, D. & Webb, Z. Universal computation by multiparticle quantum walk. Science 339, 791–794 (2013).

    Article  ADS  MathSciNet  MATH  Google Scholar 

  41. Childs, A. M. & Goldstone, J. Spatial search by quantum walk. Phys. Rev. A 70, 022314 (2004).

    Article  ADS  Google Scholar 

  42. Paparo, G. D. & Martin-Delgado, M. A. Google in a quantum network. Sci. Rep. 2, 444 (2012).

    Article  ADS  Google Scholar 

  43. Paparo, G. D., Müller, M., Comellas, F. & Martin-Delgado, M. A. Quantum Google in a complex network. Sci. Rep. 3, 2773 (2013).

    Article  ADS  Google Scholar 

  44. Loke, T., Tang, J. W., Rodriguez, J., Small, M. & Wang, J. B. Comparing classical and quantum pageranks. Quantum Inf. Process. 16, 25 (2017).

    Article  ADS  MATH  Google Scholar 

  45. Chiang, C.-F., Nagaj, D. & Wocjan, P. Efficient circuits for quantum walks. Quantum Inform. Comput. 10, 420–434 (2010).

    MathSciNet  MATH  Google Scholar 

  46. Loke, T. & Wang, J. B. Efficient quantum circuits for Szegedy quantum walks. Ann. Phys. 382, 64–84 (2017).

    Article  ADS  MathSciNet  MATH  Google Scholar 

  47. Highchi, Y., Konno, N., Sato, I. & Segawa, E. Periodicity of the discrete-time quantum walk on a finite graph. Interdiscip. Inform. Sci. 23, 75–86 (2017).

    MathSciNet  Google Scholar 

  48. Collins, M. J. et al. Integrated spatial multiplexing of heralded single-photon sources. Nat. Commun. 4, 2582 (2013).

    Article  Google Scholar 

  49. Khasminskaya, S. et al. Fully integrated quantum photonic circuit with an electrically driven light source. Nat. Photon. 10, 727–732 (2016).

    Article  ADS  Google Scholar 

  50. Gimeno-Segovia, M., Shadbolt, P. J., Browne, D. E. & Ruddolph, T. From three-photon Greenberger–Horne–Zeilinger states to ballistic universal quantum computation. Phys. Rev. Lett. 115, 020502 (2015).

    Article  ADS  Google Scholar 

  51. Qiang, X. et al. Underpinning data for ‘Large-scale silicon quantum photonics implementing arbitrary two-qubit processing.’ (2018).

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The authors thank S. Paesani, J. Silverstone, G. Sinclair, K. Aungskunsiri and C. Sparrow for helpful discussions and A. Murray and M. Loutit for assistance with wire-bonding the device. This work was supported by EPSRC programme grant EP/L024020/1, US Army Research Office (ARO) grant no. W911NF-14-1-0133, US Air Force Office of Scientific Research (AFOSR) and the Centre for Nanoscience and Quantum Information (NSQI). X.Q. acknowledges support from the China Scholarship Council and the National Natural Science Foundation of China (NSFC no. 61632021). X.Z. acknowledges support from the National Key Research and Development Program (2017YFA0305200 and 2016YFA0301700), the National Young 1000 Talents Plan, and the Natural Science Foundation of Guangdong (2016A030312012). J.W. acknowledges support from the National Young 1000 Talents Plan. T.C.R. acknowledges support from the Australian Research Council Centre of Excellence for Quantum Computation and Communication Technology (project no. CE170100012). J.L.O.B. acknowledges a Royal Society Wolfson Merit Award and a Royal Academy of Engineering Chair in Emerging Technologies. M.G.T. acknowledges support from the ERC starter grant ERC-2014-STG 640079 and an EPSRC Early Career Fellowship EP/K033085/1. J.C.F.M acknowledges support from EPSRC Early Career Fellowship EP/M024385/1.

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Authors and Affiliations



X.Z., X.Q., T.C.R., J.L.O.B. and J.C.F.M. conceived and designed the project. X.Z. and X.Q. designed the device. X.Q., J.W., C.M.W., L.K., G.D.M. and R.S. built the experimental set-up and carried out the experiments. X.Q., X.Z., T.L., S.O.G., J.B.W. and J.C.F.M. performed the theoretical analysis. X.Z., J.L.O.B., M.G.T. and J.C.F.M. managed the project. All authors discussed the results and contributed to writing the manuscript.

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Correspondence to Xiaoqi Zhou or Jonathan C. F. Matthews.

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Qiang, X., Zhou, X., Wang, J. et al. Large-scale silicon quantum photonics implementing arbitrary two-qubit processing. Nature Photon 12, 534–539 (2018).

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