It looks like Elasticsearch is currently missing support for concurrent searching and that this is a major prospective optimization to reduce latency.

Digression: this is not the topic at hand but I personally consider the fork OpenSearch to be an historical tragedy of duplication of work and a segregation of improvements. What would be even more anti-utilitarist would be to blindly *ignore* each other advances towards making better search.

Lucene concurrent search APIs are probably among the most important feature/optimization currently not leveraged by Elasticsearch.
The fork OpenSearch has a [pull request](https://github.com/opensearch-project/OpenSearch/pull/1500) implementing support for it.

See also the [corresponding issue](https://github.com/opensearch-project/OpenSearch/issues/1286) 

I believe it would be great for end users if you could take inspiration from the PR and work on this feature.

Great blog about the Lucene feature:
https://blog.mikemccandless.com/2019/10/concurrent-query-execution-in-apache.html?m=1
See also those performance results:
https://engineeringblog.yelp.com/2021/09/nrtsearch-yelps-fast-scalable-and-cost-effective-search-engine.html
server/src/main/java/org/elasticsearch/search/SearchService.java
}
    }
    /**
     * Shortcut ids to load, we load only "from" and up to "size". The phase controller
     * handles this as well since the result is always size * shards for Q_T_F
     */
    private static void shortcutDocIdsToLoad(SearchContext context) {
        final int[] docIdsToLoad;
        int docsOffset = 0;
        final Suggest suggest = context.queryResult().suggest();
        int numSuggestDocs = 0;
        final List<CompletionSuggestion> completionSuggestions;
        if (suggest != null && suggest.hasScoreDocs()) {
            completionSuggestions = suggest.filter(CompletionSuggestion.class);
            for (CompletionSuggestion completionSuggestion : completionSuggestions) {
                numSuggestDocs += completionSuggestion.getOptions().size();
            }
        } else {
            completionSuggestions = Collections.emptyList();
        }
        if (context.request().scroll() != null) {
            TopDocs topDocs = context.queryResult().topDocs().topDocs;
            docIdsToLoad = new int[topDocs.scoreDocs.length + numSuggestDocs];
            for (int i = 0; i < topDocs.scoreDocs.length; i++) {
                docIdsToLoad[docsOffset++] = topDocs.scoreDocs[i].doc;
            }
        } else {
            TopDocs topDocs = context.queryResult().topDocs().topDocs;
            if (topDocs.scoreDocs.length < context.from()) {