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About this paper
Kuan Cheng, Ruiyang Wu
The authors construct explicit strong matrix samplers by connecting operator-norm estimation with quantum-proof randomness extraction. For fixed α>0 and 0<δ≤ε≤1/2, the sampler uses m+Oα(log(D/δ)) random bits and the stated near-optimal sample bound, with each sample computable in polynomial time. Its randomness overhead matches the lower bound up to constants; its sample bound retains α-dependent and logarithmic losses.
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