theoretical-computer-science / Information theory; average-case complexity

Polynomial-Time MIMO Detection at the ML Threshold

An average-case claim about the Gaussian model, not a contradiction of the worst-case NP-hardness of integer least squares. If it holds, no computational-statistical gap separates polynomial-time detection from exhaustive maximum likelihood at first order in this model.

18Significance / 100
1Frontier events
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theoretical-computer-scienceAug 8, 2026Significance 18/100Registry: unreviewed

Polynomial-Time MIMO Detection at the ML Threshold

Prior state unknown→proved

An average-case claim about the Gaussian model, not a contradiction of the worst-case NP-hardness of integer least squares. If it holds, no computational-statistical gap separates polynomial-time detection from exhaustive maximum likelihood at first order in this model.

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An average-case claim about the Gaussian model, not a contradiction of the worst-case NP-hardness of integer least squares. If it holds, no computational-statistical gap separates polynomial-time detection from exhaustive maximum likelihood at first order in this model.

An average-case claim about the Gaussian model, not a contradiction of the worst-case NP-hardness of integer least squares. If it holds, no computational-statistical gap separates polynomial-time detection from exhaustive maximum likelihood at first order in this model.

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Polynomial-Time MIMO Detection at the ML Threshold — Mathematical Frontier Network