I see how my post might’ve come across as redundant or not directly helpful to the discussion for that i apologize. I’m still learning a lot as I go, and just trying to better understand the mechanics behind narrowing the keyspace and how people like RetiredCoder were able to approach these high-bit puzzles. I’ll aim to keep future posts more focused and relevant. i do have a something about puzzle 135 on my rtx 3050 ti (i know its not great and part 3 of the research was intended with a 4090 im going to rent out a 4090 when the research is concluded) i get 7,000 days do i narrow down the keyspace width to like 35bits instead of the full 135 to search smaller areas first is that incorrect? at times i do get a collision error but one of my colleagues said that even with 35 bits there's a possibility it wont be there and im just wasting my time. 

Hi RetiredCoder,

I've been researching the Bitcoin puzzle challenges and was especially intrigued by your successful solution to Puzzle #130. I'm reaching out as part of a small group analyzing these puzzles in-depth, trying to understand the methods that could realistically lead to a solve beyond brute force or Pollard's Kangaroo — both of which we've tested extensively without success.

Here’s what we’ve uncovered so far:

The puzzles all use shared private keys across chains (BTC, BCH, DOGE, ETH, DASH, etc.).

We've confirmed there's no r reuse in BTC or BCH signatures for puzzle #130.

Pollard's Kangaroo returns impractical solve times.

Your side-puzzle for BCH related to #130 shows transactions with shared TXIDs and structure, suggesting that BCH (or another altchain) played a role.

We're considering the possibility of a cross-chain signature comparison or vulnerability — possibly a reused r or signature weakness on a chain like DOGE, DASH, or CLAMS.

If you're willing to share any insights — even general direction or confirmation of our reasoning — it would be greatly appreciated. We’re not seeking the key itself, just a better understanding of how the solve was approached, and what kind of cross-chain data analysis might be most productive.

Thanks for your time and for pushing the boundaries of what’s possible in crypto research.