Please also take a look at "Applying Private Information Retrieval to
Lightweight Bitcoin Clients" Scaling Bitcoin talk. The academics were not
aware of BIP158 at all, yet came up with a similar scheme independently.

On Sat, Sep 21, 2019 at 11:40 PM Tamas Blummer via bitcoin-dev <
bitcoin-dev@lists.linuxfoundation.org> wrote:

> Hi Aleksey,
>
> Yes, BIP158 uses the block hash to seed the hash function, which makes
> distinct block filters non-aggregatable
> for common values. Aggregate fiters on ranges of blocks would have to use
> some other seed and then
> achive significant savings using the same design.
>
> I think that the most likely use of filters is to decide if a newly
> announced block should be downloaded and
> not scanning over the entire chain, where aggregate filters would help. I
> also suspect that whole chain
> scans would be better served with plain sequential reads in map-reduce
> style.
>
> Typical clients do not care of filters for blocks before the birth date of
> their wallet’s keys, so they skip over the
> majority of history which is a bigger saving than any aggregate filter.
>
> I wish we get a filter committed as commitment would unlock more utility
> than any marginal savings through
> more elaborate design.
>
> Tamas Blummer
>
> On Sep 19, 2019, at 19:20, admin--- via bitcoin-dev <
> bitcoin-dev@lists.linuxfoundation.org> wrote:
>
> Hello list,
>
> Here is a link for a draft of a BIP for  compact probabilistic block
> filters alternative of BIP 158
>
>
> https://docs.google.com/document/d/1jH9tEUyb9w2OZd4-kxfGuyNIIZzmgkEb_z0qSxv80ik/edit?usp=sharing
>
> Summary:
>
>  - BIP 158  false positive rate is low, we can achieve lower bandwidth
> with higher false positive rate filter while sync blockchain
>
>  - BIP 158 not do not support filter batching by design of used parameters
> for siphash and Golomb coding optimal parameters
>
>  - Alternative compression with delta coding and splitting data to 2 bit
> string  sequences. First for data without prefixes, second one for
> information about  bit length written to first sequence.
>    Second sequence have a lot of duplicates,  compressed with 2 round of
> Huffman algorithm. (Effectivity about 98% vs Golomb with optimal parameters)
>
>  - Block filters batching reduce filter size significantly
>
> - Separation of filters by address type allows lite client not to download
> redundant information without compromising privacy.
>
> - Lite client filters download strategy: get biggest filter (smallest
> blocks/size rate) for blocks range, in case positive test  -> get medium
> filters to reduce blocks range ->  get block filters for affected range ->
> download affected blocks over TOR
>
> Implementation (python):
> https://github.com/bitaps-com/pybtc/blob/bugfix/pybtc/functions/filters.py#L172
>
> Exactly information from mainnet  about size for separated filters by
> address types and batch size will be added within few days.
>
> Thanks for any feedback.
>       Aleksey Karpov
>
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-- 
Best,
Ádám