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Efficient Tomography of Non-Interacting Fermion States
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abstract
We give an efficient algorithm that learns a non-interacting fermion state, given copies of the state. For a system of $n$ non-interacting fermions and $m$ modes, we show that $O(m^3 n^2 \log(1/\delta) / \epsilon^4)$ copies of the input state and $O(m^4 n^2 \log(1/\delta)/ \epsilon^4)$ time are sufficient to learn the state to trace distance at most $\epsilon$ with probability at least $1 - \delta$. Our algorithm empirically estimates one-mode correlations in $O(m)$ different measurement bases and uses them to reconstruct a succinct description of the entire state efficiently.
Forward citations
Cited by 2 Pith papers
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The symplectic rank of non-Gaussian quantum states
The number of symplectic eigenvalues above the vacuum value defines a computable non-Gaussianity monotone that governs compression, tomography, simulation, and irreversibility under Gaussian operations.
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Efficient Noisy Quantum State and Process Tomography
The paper proposes tomography by estimating only low-weight Pauli coefficients of noisy random-circuit states and processes, with claimed complexity independent of depth and noise strength — but the supporting path-co...
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