Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

A quantum advantage for inferring causal structure

Abstract

The problem of inferring causal relations from observed correlations is relevant to a wide variety of scientific disciplines. Yet given the correlations between just two classical variables, it is impossible to determine whether they arose from a causal influence of one on the other or a common cause influencing both. Only a randomized trial can settle the issue. Here we consider the problem of causal inference for quantum variables. We show that the analogue of a randomized trial, causal tomography, yields a complete solution. We also show that, in contrast to the classical case, one can sometimes infer the causal structure from observations alone. We implement a quantum-optical experiment wherein we control the causal relation between two optical modes, and two measurement schemes—with and without randomization—that extract this relation from the observed correlations. Our results show that entanglement and quantum coherence provide an advantage for causal inference.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1: The quantum causal inference problem.
Figure 2: Two schemes for probing causal relations and experimental set-up.
Figure 3: Reconstruction of the causal map.
Figure 4: Indicators of causal structure determined by interventionist and observational schemes.

Similar content being viewed by others

References

  1. Reichenbach, H. The Direction of Time (Univ. of California Press, 1956).

    Book  Google Scholar 

  2. Pearl, J. Causality: Models, Reasoning and Inference (Cambridge Univ. Press, 2000).

    MATH  Google Scholar 

  3. Spirtes, P., Glymour, C. & Scheines, R. Causation, Prediction, and Search (MIT Press, 2000).

    MATH  Google Scholar 

  4. Mooij, J. M., Peters, J., Janzing, D., Zscheischler, J. & Schölkopf, B. Distinguishing cause from effect using observational data: Methods and benchmarks. Preprint at http://arxiv.org/abs/1412.3773 (2014).

  5. Fitzsimons, J., Jones, J. & Vedral, V. Quantum correlations which imply causation. Preprint at http://arxiv.org/abs/1302.2731 (2013).

  6. Richardson, T. S. & Robins, J. M. Single World Intervention Graphs (SWIGs): A Unification of the Counterfactual and Graphical Approaches to Causality (CSSS, University of Washington, 2013).

    Google Scholar 

  7. Chiribella, G., D’Ariano, G. M. & Perinotti, P. Theoretical framework for quantum networks. Phys. Rev. A 80, 022339 (2009).

    Article  ADS  MathSciNet  Google Scholar 

  8. Hardy, L. The operator tensor formulation of quantum theory. Phil. Trans. R. Soc. A 370, 3385–3417 (2012).

    Article  ADS  MathSciNet  Google Scholar 

  9. Oreshkov, O., Costa, F. & Brukner, C. Quantum correlations with no causal order. Nature Commun. 3, 1092 (2012).

    Article  ADS  Google Scholar 

  10. Leifer, M. & Spekkens, R. W. Towards a formulation of quantum theory as a causally neutral theory of Bayesian inference. Phys. Rev. A 88, 052130 (2013).

    Article  ADS  Google Scholar 

  11. Leifer, M. S. Quantum dynamics as an analog of conditional probability. Phys. Rev. A 74, 042310 (2006).

    Article  ADS  Google Scholar 

  12. Aharonov, Y., Popescu, S., Tollaksen, J. & Vaidman, L. Multiple-time states and multiple-time measurements in quantum mechanics. Phys. Rev. A 79, 052110 (2009).

    Article  ADS  MathSciNet  Google Scholar 

  13. Oeckl, R. A “general boundary” formulation for quantum mechanics and quantum gravity. Phys. Lett. B 575, 318–324 (2003).

    Article  ADS  MathSciNet  Google Scholar 

  14. Choi, M. D. Completely positive linear maps on complex matrices. Linear Algebr. Appl. 10, 285–290 (1975).

    Article  MathSciNet  Google Scholar 

  15. D’Ariano, G. M. & Lo Presti, P. Quantum tomography for measuring experimentally the matrix elements of an arbitrary quantum operation. Phys. Rev. Lett. 86, 4195–4198 (2001).

    Article  ADS  Google Scholar 

  16. Jozsa, R. Fidelity for mixed quantum states. J. Mod. Opt. 41, 2315–2323 (1994).

    Article  ADS  MathSciNet  Google Scholar 

  17. Wolf, M. M., Eisert, J., Cubitt, T. & Cirac, J. Assessing non-Markovian quantum dynamics. Phys. Rev. Lett. 101, 150402 (2008).

    Article  ADS  MathSciNet  Google Scholar 

  18. Laine, E-M., Piilo, J. & Breuer, H-P. Measure for the non-Markovianity of quantum processes. Phys. Rev. A 81, 062115 (2010).

    Article  ADS  Google Scholar 

  19. Rivas, Á., Huelga, S. F. & Plenio, M. B. Quantum non-Markovianity: Characterization, quantification and detection. Rep. Prog. Phys. 77, 094001 (2014).

    Article  ADS  MathSciNet  Google Scholar 

  20. Rivas, Á., Huelga, S. F. & Plenio, M. B. Entanglement and non-Markovianity of quantum evolutions. Phys. Rev. Lett. 105, 050403 (2010).

    Article  ADS  MathSciNet  Google Scholar 

  21. Lu, X-M., Wang, X. & Sun, C. Quantum Fisher information flow and non-Markovian processes of open systems. Phys. Rev. A 82, 042103 (2010).

    Article  ADS  Google Scholar 

  22. Liu, B-H. et al. Experimental control of the transition from Markovian to non-Markovian dynamics of open quantum systems. Nature Phys. 7, 931–934 (2011).

    Article  ADS  Google Scholar 

  23. Tang, J-S. et al. Measuring non-Markovianity of processes with controllable system-environment interaction. Europhys. Lett. 97, 10002 (2012).

    Article  ADS  Google Scholar 

  24. Wallman, J., Flammia, S., Barnhill, M. & Emerson, J. Simpler, faster, better: Robust randomized benchmarking tests for non-unitality and non-Markovianity in quantum devices. Bull. Am. Phys. Soc. 77 (2014).

  25. Pechukas, P. Reduced dynamics need not be completely positive. Phys. Rev. Lett. 73, 1060–1062 (1994).

    Article  ADS  MathSciNet  Google Scholar 

  26. Altepeter, J. B. et al. Ancilla-assisted quantum process tomography. Phys. Rev. Lett. 90, 193601 (2003).

    Article  ADS  Google Scholar 

  27. Boulant, N., Emerson, J., Havel, T. F., Cory, D. G. & Furuta, S. Incoherent noise and quantum information processing. J. Chem. Phys. 121, 2955–2961 (2004).

    Article  ADS  Google Scholar 

  28. Weinstein, Y. S. et al. Quantum process tomography of the quantum Fourier transform. J. Chem. Phys. 121, 6117–6133 (2004).

    Article  ADS  Google Scholar 

  29. Howard, M. et al. Quantum process tomography and Lindblad estimation of a solid-state qubit. New J. Phys. 8, 33 (2006).

    Article  ADS  Google Scholar 

  30. Carteret, H., Terno, D. R. & Zyczkowski, K. Physical accessibility of non-completely positive maps. Phys. Rev. A 77, 042113 (2008).

    Article  ADS  MathSciNet  Google Scholar 

  31. Kim, T., Fiorentino, M. & Wong, F. N. C. Phase-stable source of polarization-entangled photons using a polarization Sagnac interferometer. Phys. Rev. A 73, 012316 (2006).

    Article  ADS  Google Scholar 

  32. Fedrizzi, A., Herbst, T., Poppe, A., Jennewein, T. & Zeilinger, A. A wavelength-tunable fiber-coupled source of narrowband entangled photons. Opt. Express 15, 15377–15386 (2007).

    Article  ADS  Google Scholar 

  33. Biggerstaff, D. N. et al. Cluster-state quantum computing enhanced by high-Fidelity generalized measurements. Phys. Rev. Lett. 103, 240504 (2009).

    Article  ADS  Google Scholar 

  34. Kwiat, P. G., Mitchell, J. R., Schwindt, P. D. D. & White, A. G. Grover’s search algorithm: An optical approach. J. Mod. Opt. 47, 257–266 (2000).

    Article  ADS  MathSciNet  Google Scholar 

  35. Nagata, T., Okamoto, R., O’Brien, J. L., Sasaki, K. & Takeuchi, S. Beating the standard quantum limit with four-entangled photons. Science 316, 726–729 (2007).

    Article  ADS  Google Scholar 

Download references

Acknowledgements

We thank J. M. Donohue and J. Lavoie for valuable discussions, and M. Mazurek for his assistance in preparing the figures. This research was supported in part by the Natural Sciences and Engineering Research Council of Canada (NSERC), Canada Research Chairs, Industry Canada and the Canada Foundation for Innovation (CFI). Research at Perimeter Institute is supported by the Government of Canada through Industry Canada and by the Province of Ontario through the Ministry of Research and Innovation.

Author information

Authors and Affiliations

Authors

Contributions

D.J. and R.W.S. conceived the original idea for the project. K.R. and R.W.S. developed the project and the theory. M.A. and K.J.R. designed the experiment. M.A. and L.V. performed the experiment. M.A., K.R. and K.J.R. performed the numerical calculations. M.A., K.R., K.J.R. and R.W.S. analysed the results. K.R., M.A. and R.W.S. wrote the first draft of the paper and all authors contributed to the final version.

Corresponding author

Correspondence to Katja Ried.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Information

Supplementary Information (PDF 1018 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ried, K., Agnew, M., Vermeyden, L. et al. A quantum advantage for inferring causal structure. Nature Phys 11, 414–420 (2015). https://doi.org/10.1038/nphys3266

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nphys3266

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing