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Classical shadows of fermions with particle number symmetry

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arxiv 2208.08964 v2 pith:XFYJ75DU submitted 2022-08-18 quant-ph

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keywords epsilonfracclassicalcomplexitymathcalbinomdensitymatrices
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abstract

We consider classical shadows of fermion wavefunctions with $\eta$ particles occupying $n$ modes. We prove that all $k$-Reduced Density Matrices (RDMs) may be simultaneously estimated to an average variance of $\epsilon^{2}$ using at most $\binom{\eta}{k}\big(1-\frac{\eta-k}{n}\big)^{k}\frac{1+n}{1+n-k}/\epsilon^{2}$ measurements in random single-particle bases that conserve particle number, and provide an estimator for any $k$-RDM with $\mathcal{O}(k^2\eta)$ classical complexity. Our sample complexity is a super-exponential improvement over the $\mathcal{O}(\binom{n}{k}\frac{\sqrt{k}}{\epsilon^{2}})$ scaling of prior approaches as $n$ can be arbitrarily larger than $\eta$, which is common in natural problems. Our method, in the worst-case of half-filling, still provides a factor of $4^{k}$ advantage in sample complexity, and also estimates all $\eta$-reduced density matrices, applicable to estimating overlaps with all single Slater determinants, with at most $\mathcal{O}(\frac{1}{\epsilon^{2}})$ samples, which is additionally independent of $\eta$.

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Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. OpenAlex reports about 18 citations worldwide. Full citation record

  1. Classical shadows for sample-efficient measurements of gauge-invariant observables

    quant-ph 2025-11 conditional novelty 7.0 of 10

    Using the Z2 lattice-gauge-theory/Ising duality, symmetry-aware classical shadow protocols estimate gauge-invariant observables with exponentially fewer samples than symmetry-blind protocols, at the cost of deeper circuits.

  2. Adaptive-depth randomized measurement for fermionic observables

    quant-ph 2025-01 conditional novelty 7.0 of 10

    A depth-adaptive fermionic classical shadow protocol achieves polynomial sample complexity at depth max{d_int^2/log n, d_int}, where d_int is the observable's interaction distance.

  3. Programming optical-lattice Fermi-Hubbard quantum simulators

    quant-ph 2025-02 conditional novelty 6.0 of 10

    Pre-compiled variational and imaginary-time circuits built from native optical-lattice Fermi-Hubbard dynamics prepare ground states of local and extended Hubbard models on ladders with high fidelity in shorter times t...

  4. Quantum Measurement for Quantum Chemistry on a Quantum Computer

    quant-ph 2025-01 accept novelty 3.0 of 10

    This review organizes quantum measurement techniques for quantum chemistry into three cost categories: VQE-era Hamiltonian partitioning, classical shadows, POVM-based schemes, and quantum phase estimation inspired met...

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