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This research establishes tight sample complexity bounds for property testing specific classes of Gaussian quantum states, proving that constant-sized samples suffice rather than scaling with system size. By optimizing the projection onto irreducible representations, the study achieves optimality for fermionic and bosonic states, advancing the theoretical efficiency of verifying quantum resources without full tomography.
Optimal testing of fermionic and bosonic Gaussian states
arXiv:2609.39113v1 Announce Type: new Abstract: We study the problem of property testing quantum states: given a pure state $|\psi\rangle$ that either (A) belongs to some class $C$ of pure states, or (B) is $\varepsilon$-far in trace distance from all states in $C$, determine which is the case with high probability. It is known that there exists classes $C$ for which the sample complexity of property testing necessarily scales with the size of the system. In this work, we identify classes for which testing only requires a size-independent number of samples. We prove a tight sample complexity of $\Theta(1/\varepsilon^2)$ for the property testing of five important classes of Gaussian quantum states: 1) Fermionic Gaussian states, 2) Slater determinants, 3) bosonic Gaussian states, 4) zero-mean bosonic Gaussian states, and 5) bosonic coherent states. While property testers for some of these classes have been studied previously, those analyses only gave upper bounds scaling polynomially in the number of modes. In each case, our tester is the projection onto the ``top'' irrep of two or three copies. We get to constant sample complexity by lower bounding how quickly the rejection probability increases with distance from the class; the main technical component involves bounding the spectral gap of symmetric extension of the test projector. We then establish optimality by proving matching lower bounds based on binary state discrimination for each class. Our testers and optimality claims also extend to the tolerant setting, wherein $\psi$ may be $O(\varepsilon)$-close to $C$ in case (A), rather than lying exactly inside.
Abstract:We study the problem of property testing quantum states: given a pure state $|\psi\rangle$ that either (A) belongs to some class $C$ of pure states, or (B) is $\varepsilon$-far in trace distance from all states in $C$, determine which is the case with high probability. It is known that there exists classes $C$ for which the sample complexity of property testing necessarily scales with the size of the system. In this work, we identify classes for which testing only requires a size-independent number of samples. We prove a tight sample complexity of $\Theta(1/\varepsilon^2)$ for the property testing of five important classes of Gaussian quantum states: 1) Fermionic Gaussian states, 2) Slater determinants, 3) bosonic Gaussian states, 4) zero-mean bosonic Gaussian states, and 5) bosonic coherent states. While property testers for some of these classes have been studied previously, those analyses only gave upper bounds scaling polynomially in the number of modes. In each case, our tester is the projection onto the ``top'' irrep of two or three copies. We get to constant sample complexity by lower bounding how quickly the rejection probability increases with distance from the class; the main technical component involves bounding the spectral gap of symmetric extension of the test projector. We then establish optimality by proving matching lower bounds based on binary state discrimination for each class. Our testers and optimality claims also extend to the tolerant setting, wherein $\psi$ may be $O(\varepsilon)$-close to $C$ in case (A), rather than lying exactly inside.
arXiv:2609.39113 [quant-ph]
(or arXiv:2609.39113v1 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2609.39113 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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