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clarify the use of LossyDAS

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Clarify that what matters is the false positive threshold, allowing
different sampling strategies as protocol compliant behavior.

Signed-off-by: Csaba Kiraly <csaba.kiraly@gmail.com>
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Csaba Kiraly 2024-05-28 12:24:25 +02:00
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specs/_features/eip7594/das-core.md
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@ -243,6 +243,14 @@ To custody a particular column, a node joins the respective gossip subnet. Verif
At each slot, a node SHOULD select at least `SAMPLES_PER_SLOT` column IDs for sampling. It is recommended to use uniform random selection without replacement based on local randomness. Sampling is considered successful if the node manages to retrieve all selected columns.
Alternatively, a node MAY use LossyDAS selecting more than `SAMPLES_PER_SLOT` columns while allowing some missing, respecting the same target false positive threshold (the probability of successful sampling of an unavailable block) as dictated by `SAMPLES_PER_SLOT`. The table below shows the number of samples and the number of allowed missing columns for this threshold.
| Allowed missing (L) | 0| 1| 2| 3| 4| 5| 6| 7| 8|
|------------------------------- |--|--|--|--|--|--|--|--|--|
| Samples (S) for target threshold 5e-6 |16|20|23|26|29|32|34|37|39|
Sampling is considered successful if any `S - L` columns are retrieved successfully.
### Sample queries
A node SHOULD maintain a diverse set of peers for each column and each slot by verifying responsiveness to sample queries.