Even with more than 1 prefix, we will always have the chance that the target will be the first one we find, but at 65%.How did you arrive at 65%? To me, it would be based on how many prefixes are in the range, unless you are just doing an average. If there are: 4 prefixes = 25% 3 prefixes = 33% 2 prefixes = 50% So I would say on average a 36% we find the target hash, if there are more than 1 prefixes in a subrange. It would jump to 42% if there were never 4 prefixes in a subrange, but we can't conclude that 100%. Exactly, I just misspelled what I meant to say, which was this: We would need to run tests to see if it's more cost-effective to choose fixed blocks or to do it adaptively, but if you saw that you were finding more prefixes, it's a good indication that it's worth comparing both strategies using unique targets for both tests since you were achieving a more efficient coverage density by finding fewer empty blocks. Similarly, it could be used for creating vanity addresses; if you find more fast prefixes, you'll create the vanity faster. But that's another topic for now. update: I asked the AI ​​to make the modification to the code for the comparison you mentioned. I chose a 30% jump after the prefix, but the results, although you need more checks on average, are more promising. So far 1000 simulations. 10,000 simulations In my opinion, without going into too much detail, adaptive hopping is an upgrade to the fixed-block method, although it forces a single path, so if the target is at the end, it will always take longer than with a randomized-block method. However, randomizing the fixed block would also send the target to the last blocks. But what if we randomized every time a block is scanned when using fixed blocks? .... The benefit of adaptive hopping is clear in comparison.
Even with more than 1 prefix, we will always have the chance that the target will be the first one we find, but at 65%.How did you arrive at 65%? To me, it would be based on how many prefixes are in the range, unless you are just doing an average. If there are: 4 prefixes = 25% 3 prefixes = 33% 2 prefixes = 50% So I would say on average a 36% we find the target hash, if there are more than 1 prefixes in a subrange. It would jump to 42% if there were never 4 prefixes in a subrange, but we can't conclude that 100%. Exactly, I just misspelled what I meant to say, which was this: We would need to run tests to see if it's more cost-effective to choose fixed blocks or to do it adaptively, but if you saw that you were finding more prefixes, it's a good indication that it's worth comparing both strategies using unique targets for both tests since you were achieving a more efficient coverage density by finding fewer empty blocks. Similarly, it could be used for creating vanity addresses; if you find more fast prefixes, you'll create the vanity faster. But that's another topic for now. update: I asked the AI ​​to make the modification to the code for the comparison you mentioned. I chose a 30% jump after the prefix, but the results, although you need more checks on average, are more promising. So far 1000 simulations. 10,000 simulations In my opinion, without going into too much detail, adaptive hopping is an upgrade to the fixed-block method, although it forces a single path, so if the target is at the end, it will always take longer than with a randomized-block method. However, randomizing the fixed block would also send the target to the last blocks. But what if we randomized every time a block is scanned when using fixed blocks? .... The benefit of adaptive hopping is clear in comparison.

Even with more than 1 prefix, we will always have the chance that the target will be the first one we find, but at 65%.How did you arrive at 65%? To me, it would be based on how many prefixes are in the range, unless you are just doing an average. If there are: 4 prefixes = 25% 3 prefixes = 33% 2 prefixes = 50% So I would say on average a 36% we find the target hash, if there are more than 1 prefixes in a subrange. It would jump to 42% if there were never 4 prefixes in a subrange, but we can't conclude that 100%. Exactly, I just misspelled what I meant to say, which was this: We would need to run tests to see if it's more cost-effective to choose fixed blocks or to do it adaptively, but if you saw that you were finding more prefixes, it's a good indication that it's worth comparing both strategies using unique targets for both tests since you were achieving a more efficient coverage density by finding fewer empty blocks. Similarly, it could be used for creating vanity addresses; if you find more fast prefixes, you'll create the vanity faster. But that's another topic for now. update: I asked the AI ​​to make the modification to the code for the comparison you mentioned. I chose a 30% jump after the prefix, but the results, although you need more checks on average, are more promising. So far 1000 simulations. 10,000 simulations In my opinion, without going into too much detail, adaptive hopping is an upgrade to the fixed-block method, although it forces a single path, so if the target is at the end, it will always take longer than with a randomized-block method. However, randomizing the fixed block would also send the target to the last blocks. But what if we randomized every time a block is scanned when using fixed blocks? .... The benefit of adaptive hopping is clear in comparison.

Even with more than 1 prefix, we will always have the chance that the target will be the first one we find, but at 65%.How did you arrive at 65%? To me, it would be based on how many prefixes are in the range, unless you are just doing an average. If there are: 4 prefixes = 25% 3 prefixes = 33% 2 prefixes = 50% So I would say on average a 36% we find the target hash, if there are more than 1 prefixes in a subrange. It would jump to 42% if there were never 4 prefixes in a subrange, but we can't conclude that 100%. Exactly, I just misspelled what I meant to say, which was this: We would need to run tests to see if it's more cost-effective to choose fixed blocks or to do it adaptively, but if you saw that you were finding more prefixes, it's a good indication that it's worth comparing both strategies using unique targets for both tests since you were achieving a more efficient coverage density by finding fewer empty blocks. Similarly, it could be used for creating vanity addresses; if you find more fast prefixes, you'll create the vanity faster. But that's another topic for now. update: I asked the AI ​​to make the modification to the code for the comparison you mentioned. I chose a 30% jump after the prefix, but the results, although you need more checks on average, are more promising. So far 1000 simulations. 10,000 simulations In my opinion, without going into too much detail, adaptive hopping is an upgrade to the fixed-block method, although it forces a single path, so if the target is at the end, it will always take longer than with a randomized-block method. However, randomizing the fixed block would also send the target to the last blocks. But what if we randomized every time a block is scanned when using fixed blocks? .... The benefit of adaptive hopping is clear in comparison.