AI summary · arXiv: 2611.01434v1 · quant-ph
Boson sampling is fragile to loss
The essentials
Fixed nonzero uniform photon loss makes the specified boson-sampling distributions efficiently classically approximable on average, even when detected photon numbers grow linearly with system size.
Based on the abstract only: check the details in the original paper.
Question
Does the computational hardness of boson sampling survive photon loss as the system grows? The paper asks whether small but fixed uniform loss allows efficient classical sampling.
Method
The authors use loss-induced suppression of correlations involving many photons to approximate the output distribution using only low correlation orders. They establish polynomial-time sampling in system size and inverse total variation error, with error averaged over Haar-random interferometers, for Fock-state sampling with single photons in distinct inputs and arbitrary extra vacuum inputs, and for Gaussian boson sampling with equal, bounded-strength squeezing.
Findings
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Result
Any fixed, nonzero uniform loss rate permits efficient classical sampling in the average case as the system grows.
See the passage in the paper
We show that even an arbitrarily small nonzero uniform loss rate permits efficient classical sampling in the average case when the rate remains fixed as the system grows.
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Authors’ interpretation
The approximation works by retaining low-order correlations because loss suppresses correlations involving many photons.
See the passage in the paper
We exploit how loss suppresses correlations involving many photons to approximate the full output distribution using low correlation orders.
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Result
The resulting samplers have runtime polynomial in system size and inverse total variation error, with the guarantee averaged over Haar-random interferometers.
See the passage in the paper
The resulting samplers run in time polynomial in system size and inverse total variation error, with the error averaged over Haar random interferometers.
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Authors’ interpretation
Large detected photon counts alone do not guarantee computational hardness under the stated loss conditions.
See the passage in the paper
Classical sampling is efficient even when the mean detected photon number grows linearly with system size, showing that large photon counts alone do not ensure computational hardness.
Limitations
- The stated results cover specific input families and loss conditions, so the abstract does not establish the same conclusion for other boson-sampling setups.
See the passage in the paper
The results apply to Fock state boson sampling with single-photon states in distinct input modes and arbitrary additional vacuum inputs, and to Gaussian boson sampling with equal squeezing of bounded strength in every input mode.
Why it matters
The authors argue that even small fixed uniform loss can undermine the computational-hardness motivation for boson-sampling experiments. In particular, scaling the mean detected photon number linearly with system size is not sufficient, by itself, to establish hardness.
Written by AI from the paper. Passages are checked word for word against the text we analysed; the rest may contain errors.
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Abstract
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