Witnessing quantum memory in non-Markovian processes

Christina Giarmatzi1,2 and Fabio Costa1

1Centre for Engineered Quantum Systems, School of Mathematics and Physics, University of Queensland, QLD 4072 Australia
2University of Technology Sydney, Centre for Quantum Software and Information, Ultimo NSW 2007, Australia

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Abstract

We present a method to detect quantum memory in a non-Markovian process. We call a process Markovian when the environment does not provide a memory that retains correlations across different system-environment interactions. We define two types of non-Markovian processes, depending on the required memory being classical or quantum. We formalise this distinction using the process matrix formalism, through which a process is represented as a multipartite state. Within this formalism, a test for entanglement in a state can be mapped to a test for quantum memory in the corresponding process. This allows us to apply separability criteria and entanglement witnesses to the detection of quantum memory. We demonstrate the method in a simple model where both system and environment are single interacting qubits and map the parameters that lead to quantum memory. As with entanglement witnesses, our method of witnessing quantum memory provides a versatile experimental tool for open quantum systems.

The study of open quantum systems is a vast field within quantum physics that concerns the interaction between some system and its environment. Its great importance lies on the fact that every experimental realization of a quantum process faces the possibility of noise coming from the environment. Although in small quantum devices the noise is assumed to be uncorrelated (Markovian) this assumption fails as the size and complexity increases, and the various system-environment interactions become correlated (non-Markovian). These non-Markovian processes can be simulated only by adding an external memory that carries the correlations across the different interactions. The memory required to reproduce the process can be quantum or classical, and being able to distinguish between the two types of non-Markovian noise would lead to different ways of finding its source or correcting for it. Therefore, it is desirable to have efficient methods to decide whether an environment carries a classical or quantum memory.

In this work, we provide a first rigorous definition of classical memory in a non-Markovian process and we present a method that detects that a process is non-Markovian with quantum memory. We do this by mapping our problem to the well known problem of entanglement. We apply our method to an example of a non-Markovian process and present our results of detecting a quantum memory.

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► References

[1] H. P. Breuer and F. Petruccione, Oxford University Press, Oxford (2002).
https:/​/​doi.org/​10.1093/​acprof:oso/​9780199213900.001.0001

[2] F. Arute, K. Arya, R. Babbush et al., Nature 574, 505 (2019).
https:/​/​doi.org/​10.1038/​s41586-019-1666-5

[3] J. Preskill, Quantum 2, 79 (2018).
https:/​/​doi.org/​10.22331/​q-2018-08-06-79

[4] J. Morris, F. A. Pollock and K. Modi, Non-markovian memory in ibmqx4, (2019), arXiv:1902.07980 [quant-ph].
arXiv:1902.07980

[5] J. Piilo, S. Maniscalco, K. Härkönen et al., Phys. Rev. Lett. 100, 180402 (2008).
https:/​/​doi.org/​10.1103/​PhysRevLett.100.180402

[6] M. M. Wolf and J. I. Cirac, Communications in Mathematical Physics 279, 147 (2008).
https:/​/​doi.org/​10.1007/​s00220-008-0411-y

[7] H.-P. Breuer, E.-M. Laine and J. Piilo, Phys. Rev. Lett. 103, 210401 (2009).
https:/​/​doi.org/​10.1103/​PhysRevLett.103.210401

[8] A. Rivas, S. F. Huelga and M. B. Plenio, Phys. Rev. Lett. 105, 050403 (2010).
https:/​/​doi.org/​10.1103/​PhysRevLett.105.050403

[9] S. C. Hou, X. X. Yi, S. X. Yu et al., Phys. Rev. A 83, 062115 (2011).
https:/​/​doi.org/​10.1103/​PhysRevA.83.062115

[10] D. Chruściński and S. Maniscalco, Phys. Rev. Lett. 112, 120404 (2014).
https:/​/​doi.org/​10.1103/​PhysRevLett.112.120404

[11] Á. Rivas, S. F. Huelga and M. B. Plenio, Reports on Progress in Physics 77, 094001 (2014).
https:/​/​doi.org/​10.1088/​0034-4885/​77/​9/​094001
http:/​/​stacks.iop.org/​0034-4885/​77/​i=9/​a=094001

[12] H.-P. Breuer, E.-M. Laine, J. Piilo et al., Rev. Mod. Phys. 88, 021002 (2016).
https:/​/​doi.org/​10.1103/​RevModPhys.88.021002

[13] L. Li, M. J. Hall and H. M. Wiseman, Physics Reports 759, 1 (2018).
https:/​/​doi.org/​10.1016/​j.physrep.2018.07.001

[14] I. de Vega and D. Alonso, Reviews of Modern Physics 89, 015001 (2017).
https:/​/​doi.org/​10.1103/​RevModPhys.89.015001

[15] J. H. Shapiro, G. Saplakoglu, S.-T. Ho et al., J. Opt. Soc. Am. B 4, 1604 (1987).
https:/​/​doi.org/​10.1364/​JOSAB.4.001604

[16] C. M. Caves and G. J. Milburn, Phys. Rev. A 36, 5543 (1987).
https:/​/​doi.org/​10.1103/​PhysRevA.36.5543

[17] H. M. Wiseman and G. J. Milburn, Phys. Rev. Lett. 70, 548 (1993).
https:/​/​doi.org/​10.1103/​PhysRevLett.70.548

[18] A. A. Budini, Phys. Rev. A 64, 052110 (2001).
https:/​/​doi.org/​10.1103/​PhysRevA.64.052110

[19] D. Zhou, A. Lang and R. Joynt, Quantum Inf. Process. 9, 727 (2010).
https:/​/​doi.org/​10.1007/​s11128-010-0165-2

[20] P. Bordone, F. Buscemi and C. Benedetti, Fluctuation Noise Lett. 11, 1242003 (2012).
https:/​/​doi.org/​10.1142/​S0219477512420035

[21] A. Bodor, L. Diósi, Z. Kallus et al., Phys. Rev. A 87, 052113 (2013).
https:/​/​doi.org/​10.1103/​PhysRevA.87.052113

[22] J.-S. Xu, K. Sun, C.-F. Li et al., Nature Communications 4, 2851 (2013).
https:/​/​doi.org/​10.1038/​ncomms3851

[23] B. Vacchini, Phys. Rev. A 87, 030101 (2013).
https:/​/​doi.org/​10.1103/​PhysRevA.87.030101

[24] A. A. Budini, Phys. Rev. A 97, 052133 (2018).
https:/​/​doi.org/​10.1103/​PhysRevA.97.052133

[25] A. Shaji and E. Sudarshan, Physics Letters A 341, 48 (2005).
https:/​/​doi.org/​10.1016/​j.physleta.2005.04.029

[26] P. Pechukas, Phys. Rev. Lett. 73, 1060 (1994).
https:/​/​doi.org/​10.1103/​PhysRevLett.73.1060

[27] P. Štelmachovičand V. Bužek, Phys. Rev. A 64, 062106 (2001).
https:/​/​doi.org/​10.1103/​PhysRevA.64.062106

[28] D. Schmid, K. Ried and R. W. Spekkens, Phys. Rev. A 100, 022112 (2019).
https:/​/​doi.org/​10.1103/​PhysRevA.100.022112

[29] G. Lindblad, Comm. Math. Phys. 65, 281 (1979).
https:/​/​projecteuclid.org:443/​euclid.cmp/​1103904877

[30] L. Accardi, A. Frigerio and J. T. Lewis, Publications of the Research Institute for Mathematical Sciences 18, 97 (1982).
https:/​/​doi.org/​10.2977/​prims/​1195184017

[31] G. Chiribella, G. M. D'Ariano and P. Perinotti, Phys. Rev. A 80, 022339 (2009).
https:/​/​doi.org/​10.1103/​PhysRevA.80.022339

[32] F. A. Pollock, C. Rodríguez-Rosario, T. Frauenheim et al., Physical Review A 97, 012127 (2018a).
https:/​/​doi.org/​10.1103/​PhysRevA.97.012127

[33] O. Oreshkov, F. Costa and Č. Brukner, Nat. Commun. 3, 1092 (2012), arXiv:1105.4464 [quant-ph].
https:/​/​doi.org/​10.1038/​ncomms2076
arXiv:1105.4464

[34] O. Oreshkov and C. Giarmatzi, New Journal of Physics 18, 093020 (2016).
https:/​/​doi.org/​10.1088/​1367-2630/​18/​9/​093020
http:/​/​stacks.iop.org/​1367-2630/​18/​i=9/​a=093020

[35] A. Peres, Physical Review Letters 77, 1413 (1996).
https:/​/​doi.org/​10.1103/​PhysRevLett.77.1413

[36] A. C. Doherty, P. A. Parrilo and F. M. Spedalieri, Physical Review A 69, 022308 (2004).
https:/​/​doi.org/​10.1103/​PhysRevA.69.022308

[37] Y. Nesterov and A. Nemirovskii, Interior Point Polynomial Algorithms in Convex Programming, Studies in Applied Mathematics (Society for Industrial and Applied Mathematics, 1987).

[38] E. Davies and J. Lewis, Comm. Math. Phys. 17, 239 (1970).
https:/​/​doi.org/​10.1007/​BF01647093

[39] A. Jamiołkowski, Rep. Math. Phys 3, 275 (1972).
https:/​/​doi.org/​10.1016/​0034-4877(72)90011-0

[40] M.-D. Choi, Linear Algebra Appl. 10, 285 (1975).
https:/​/​doi.org/​10.1016/​0024-3795(75)90075-0

[41] D. Kretschmann and R. F. Werner, Phys. Rev. A 72, 062323 (2005).
https:/​/​doi.org/​10.1103/​PhysRevA.72.062323

[42] F. Costa and S. Shrapnel, New Journal of Physics 18, 063032 (2016).
https:/​/​doi.org/​10.1088/​1367-2630/​18/​6/​063032

[43] C. Giarmatzi and F. Costa, npj Quantum Information 4, 17 (2018).
https:/​/​doi.org/​10.1038/​s41534-018-0062-6

[44] F. A. Pollock, C. Rodríguez-Rosario, T. Frauenheim et al., Physical Review Letters 120, 040405 (2018b).
https:/​/​doi.org/​10.1103/​PhysRevLett.120.040405

[45] J. Kołodyński, S. Rana and A. Streltsov, Physical Review A 101, 020303 (2020).
https:/​/​doi.org/​10.1103/​PhysRevA.101.020303

[46] D. Chruściński and S. Maniscalco, Physical Review Letters 112, 120404 (2014).
https:/​/​doi.org/​10.1103/​PhysRevLett.112.120404

[47] M. Araújo, C. Branciard, F. Costa et al., New J. Phys. 17, 102001 (2015).
https:/​/​doi.org/​10.1088/​1367-2630/​17/​10/​102001

[48] E. M. Rains, arXiv:9707002 [quant-ph].
arXiv:quant-ph/9707002

[49] V. Vedral and M. B. Plenio, Phys. Rev. A 57, 1619 (1998).
https:/​/​doi.org/​10.1103/​PhysRevA.57.1619

[50] C. H. Bennett, D. P. DiVincenzo, C. A. Fuchs et al., Phys. Rev. A 59, 1070 (1999).
https:/​/​doi.org/​10.1103/​PhysRevA.59.1070

[51] M. Nery and M. T. Quintino and P. A. Guérin and T. O. Maciel and R. O. Vianna arXiv:2101.11630 [quant-ph].
arXiv:2101.11630

[52] G. Rubino, L. A. Rozema, A. Feix et al., Science Advances 3 (2017), 10.1126/​sciadv.1602589.
https:/​/​doi.org/​10.1126/​sciadv.1602589

[53] K. Goswami, C. Giarmatzi, M. Kewming et al., Phys. Rev. Lett. 121, 090503 (2018).
https:/​/​doi.org/​10.1103/​PhysRevLett.121.090503

[54] I. Ernst, Z. Physik 31, 253 (1925).

[55] V. Vedral, Reviews of Modern Physics 74, 197 (2002).
https:/​/​doi.org/​10.1103/​RevModPhys.74.197

[56] S. Milz, M. S. Kim, F. A. Pollock et al., Phys. Rev. Lett. 123, 040401 (2019).
https:/​/​doi.org/​10.1103/​PhysRevLett.123.040401

[57] S. Milz, F. Sakuldee, F. A. Pollock et al., Quantum 4, 255 (2020).
https:/​/​doi.org/​10.22331/​q-2020-04-20-255

[58] D. Chruściński, A. Kossakowski and A. Rivas, Phys. Rev. A 83, 052128 (2011).
https:/​/​doi.org/​10.1103/​PhysRevA.83.052128

[59] C. Giarmatzi, Github page.
http:/​/​github.com/​Christina-Giar/​SDP2_non_markov

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[1] Joshua Morris, Felix A. Pollock, and Kavan Modi, "Quantifying non-Markovian Memory in a Superconducting Quantum Computer", Open Systems & Information Dynamics 29 02, 2250007 (2022).

[2] Varun Srivastava, Abhinash Kumar Roy, Soumik Mahanti, Jasleen Kaur, Salini Karuvade, and Alexei Gilchrist, "Blind spots of randomized benchmarking under temporal correlations", Physical Review Research 8 2, 023258 (2026).

[3] Huan-Yu Ku, Hao-Cheng Weng, Yen-An Shih, Po-Chen Kuo, Neill Lambert, Franco Nori, Chih-Sung Chuu, and Yueh-Nan Chen, "Hidden nonmacrorealism: Reviving the Leggett-Garg inequality with stochastic operations", Physical Review Research 3 4, 043083 (2021).

[4] Gregory A. L. White, Felix A. Pollock, Lloyd C. L. Hollenberg, Charles D. Hill, and Kavan Modi, "What can unitary sequences tell us about multi-time physics?", Quantum 9, 1695 (2025).

[5] K. Goswami, C. Giarmatzi, C. Monterola, S. Shrapnel, J. Romero, and F. Costa, "Experimental characterization of a non-Markovian quantum process", Physical Review A 104 2, 022432 (2021).

[6] Bassano Vacchini, Graduate Texts in Physics 355 (2024) ISBN:978-3-031-58217-2.

[7] U. Shrikant and Prabha Mandayam, "Quantum non-Markovianity: Overview and recent developments", Frontiers in Quantum Science and Technology 2, 1134583 (2023).

[8] Abhinash Kumar Roy, Varun Srivastava, Soumik Mahanti, Christina Giarmatzi, and Alexei Gilchrist, "Semi-device-independent certification of quantum non-Markovianity using sequential random access codes", Physical Review A 110 1, 012608 (2024).

[9] Prateek Chawla, Shrikant Utagi, and C. M. Chandrashekar, "Quantum Walks under Superposition of Causal Order", International Journal of Theoretical Physics 64 3, 68 (2025).

[10] Philip Taranto, Marco Túlio Quintino, Mio Murao, and Simon Milz, "Characterising the Hierarchy of Multi-time Quantum Processes with Classical Memory", Quantum 8, 1328 (2024).

[11] Lucas B. Vieira, Huan-Yu Ku, and Costantino Budroni, "Entanglement-breaking channels are a quantum memory resource", Physical Review Research 7 4, 043281 (2025).

[12] Stefano Martina, Stefano Gherardini, and Filippo Caruso, "Machine learning classification of non-Markovian noise disturbing quantum dynamics", Physica Scripta 98 3, 035104 (2023).

[13] Marcello Nery, Marco Túlio Quintino, Philippe Allard Guérin, Thiago O. Maciel, and Reinaldo O. Vianna, "Simple and maximally robust processes with no classical common-cause or direct-cause explanation", Quantum 5, 538 (2021).

[14] Lucas B. Vieira, Simon Milz, Giuseppe Vitagliano, and Costantino Budroni, "Witnessing environment dimension through temporal correlations", Quantum 8, 1224 (2024).

[15] Guilherme Zambon and Gerardo Adesso, "Quantum Processes as Thermodynamic Resources: The Role of Non-Markovianity", Physical Review Letters 134 20, 200401 (2025).

[16] Leonardo S. V. Santos, Zhen-Peng Xu, Jyrki Piilo, and Otfried Gühne, "Quantifying information flow in quantum processes", Physical Review A 112 2, 022201 (2025).

[17] Fabio Costa, "A no-go theorem for superpositions of causal orders", Quantum 6, 663 (2022).

[18] Matheus Capela, Lucas C. Céleri, Rafael Chaves, and Kavan Modi, "Quantum Markov monogamy inequalities", Physical Review A 106 2, 022218 (2022).

[19] Christina Giarmatzi, Tyler Jones, Alexei Gilchrist, Prasanna Pakkiam, Arkady Fedorov, and Fabio Costa, "Multi-time quantum process tomography on a superconducting qubit", Quantum 9, 1952 (2025).

[20] Fabio Costa, Jonathan Barrett, and Sally Shrapnel, "A de Finetti theorem for quantum causal structures", Quantum 9, 1628 (2025).

[21] Kaumudibikash Goswami, Abhinash Kumar Roy, Varun Srivastava, Barr Perez, Christina Giarmatzi, Alexei Gilchrist, and Fabio Costa, "Hamiltonian characterization of multi-time processes with classical memory", New Journal of Physics 27 11, 114515 (2025).

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[23] Francesco Buscemi, Rajeev Gangwar, Kaumudibikash Goswami, Himanshu Badhani, Tanmoy Pandit, Brij Mohan, Siddhartha Das, and Manabendra Nath Bera, "Causal and Noncausal Revivals of Information: A New Regime of Non-Markovianity in Quantum Stochastic Processes", PRX Quantum 6 2, 020316 (2025).

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[27] Nina Megier, Manuel Ponzi, Andrea Smirne, and Bassano Vacchini, "Memory Effects in Quantum Dynamics Modelled by Quantum Renewal Processes", Entropy 23 7, 905 (2021).

[28] Guilherme Zambon and Diogo O. Soares-Pinto, "Relations between Markovian and non-Markovian correlations in multitime quantum processes", Physical Review A 109 6, 062401 (2024).

[29] Simon Milz, Cornelia Spee, Zhen-Peng Xu, Felix Pollock, Kavan Modi, and Otfried Gühne, "Genuine multipartite entanglement in time", SciPost Physics 10 6, 141 (2021).

[30] Matheus Capela, Harshit Verma, Fabio Costa, and Lucas C. Céleri, "Reassessing thermodynamic advantage from indefinite causal order", Physical Review A 107 6, 062208 (2023).

[31] Charlotte Bäcker, Krishna Palaparthy, and Walter T Strunz, "Revealing the quantum nature of memory in non-Markovian dynamics on IBM quantum", New Journal of Physics 28 4, 044512 (2026).

[32] Charlotte Bäcker, Konstantin Beyer, and Walter T. Strunz, "Entropic witness for quantum memory in open system dynamics", Physical Review Research 7 3, 033256 (2025).

[33] Vishal Anand, Ananda G. Maity, Subhadip Mitra, and Samyadeb Bhattacharya, "Emergent non-Markovianity and dynamical quantification of the quantum switch", Physical Review A 111 3, 032428 (2025).

[34] Pedro Figueroa–Romero, Felix A. Pollock, and Kavan Modi, "Markovianization with approximate unitary designs", Communications Physics 4 1, 127 (2021).

[35] Graeme D. Berk, Simon Milz, Felix A. Pollock, and Kavan Modi, "Extracting quantum dynamical resources: consumption of non-Markovianity for noise reduction", npj Quantum Information 9 1, 104 (2023).

[36] Aditya Banerjee, "Quantum scarring enhances non-Markovianity of subsystem dynamics", New Journal of Physics 28 5, 054502 (2026).

[37] Amith Mathew, Ranjith Babu, Jayesh V Patil, and H Aswath Babu, 2025 IEEE International Conference on Recent Advances in Systems Science and Engineering (RASSE) 1 (2025) ISBN:979-8-3315-4435-5.

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