Measurement incompatibility and quantum steering via linear programming

Lucas E. A. Porto; Sébastien Designolle; Sebastian Pokutta; Marco Túlio Quintino

doi:10.22331/q-2026-06-19-2141

Measurement incompatibility and quantum steering via linear programming

Lucas E. A. Porto^1,2, Sébastien Designolle^3,4, Sebastian Pokutta^3,5, and Marco Túlio Quintino¹

¹Sorbonne Université, CNRS, LIP6, F-75005 Paris, France
²Instituto de Física Gleb Wataghin, Universidade Estadual de Campinas (Unicamp), Rua Sérgio Buarque de Holanda 777, Campinas, São Paulo 13083-859, Brazil
³Zuse Institute Berlin, Takustraße 7, 14195 Berlin, Germany
⁴Inria, ENS de Lyon, UCBL, LIP, 69342, Lyon Cedex 07, France
⁵Berlin Institute of Technology, 10587 Berlin, Germany

Published:	2026-06-19, volume 10, page 2141
Editor:	Ravi Kunjwal
Eprint:	arXiv:2506.03045v3
Doi:	https://doi.org/10.22331/q-2026-06-19-2141
Citation:	Quantum 10, 2141 (2026).

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Abstract

The problem of deciding whether a set of quantum measurements is jointly measurable is known to be equivalent to determining whether a quantum assemblage is unsteerable. This problem can be formulated as a semidefinite program (SDP). However, the number of variables and constraints in such a formulation grows exponentially with the number of measurements, rendering it intractable for large measurement sets. In this work, we circumvent this problem by transforming the SDP into a hierarchy of linear programs that compute upper and lower bounds on the incompatibility robustness with a complexity that grows polynomially in the number of measurements. The hierarchy is guaranteed to converge and it can be applied to arbitrary measurements – including non-projective POVMs (Positive Operator-Valued Measures) – in arbitrary dimensions. While convergence becomes impractical in high dimensions, in the case of qubits our method reliably provides accurate upper and lower bounds for the incompatibility robustness of sets with several hundred measurements in a short time using a standard laptop. We also apply our methods to qutrits, obtaining non-trivial upper and lower bounds in scenarios that are otherwise intractable using the standard SDP approach, although such bounds are significantly looser than the ones obtained in the qubit case. Finally, we show how our methods can be used to construct local hidden state models for states (i.e., to prove that a state cannot lead to steering under any possible local measurements), or conversely, to certify that a given state exhibits steering; for two-qubit quantum states, our approach is comparable to, and in some cases outperforms, the current best methods.

Featured image: Comparison between computational runtime for quantifying measurement incompatibility using the linear programming approach proposed in this work and the standard semidefinite programming approach.

Popular summary

In the classical world, the properties of any system are always assume to be well defined. A classical particle has, at any moment in time, a well-defined position and a well-defined velocity. Or, by looking at a playing card, one can simultaneously tell its value and its suit. However, this is not true in quantum theory. Heisenberg's uncertainty principle states that if a quantum particle has a well-defined position, it cannot have a well-defined value of velocity. Or, if one were to play cards with a quantum deck, it could be that the value and the suit of any card could not be simultaneously known.

Within quantum theory, this phenomenon can be formalised by the concept of measurement incompatibility. A set of measurements is incompatible if they cannot be jointly performed, that is, if they cannot all be performed at the same time. Deciding whether any given set of measurements is incompatible is a problem that can be cast as a semidefinite program, which can be solved with the aid of a computer. Although this approach works perfectly well for deciding the incompatibility of sets with few measurements, the size of the resulting program grows exponentially with the number of measurements in the set and thus quickly becomes intractable.

In this work, we propose a way to circumvent this scalability problem, that works particularly well for measurements on qubits, i.e., quantum systems of dimension two. The method we propose trades off accuracy for efficiency, and relies on a finite approximation of the space of valid quantum states. Since such a space is particularly simple in dimension two, the method provides remarkably precise answers for sets of more than ~100 measurements, while the standard approach already becomes prohibitive for ~20 measurements. Finally, we also discuss applications of the method for problems related to quantum correlations.

► BibTeX data

@article{Porto2026measurement,
  doi = {10.22331/q-2026-06-19-2141},
  url = {https://doi.org/10.22331/q-2026-06-19-2141},
  title = {Measurement incompatibility and quantum steering via linear programming},
  author = {Porto, Lucas E. A. and Designolle, S{\'{e}}bastien and Pokutta, Sebastian and Quintino, Marco T{\'{u}}lio},
  journal = {{Quantum}},
  issn = {2521-327X},
  publisher = {{Verein zur F{\"{o}}rderung des Open Access Publizierens in den Quantenwissenschaften}},
  volume = {10},
  pages = {2141},
  month = jun,
  year = {2026}
}

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