BitVM Paper Announces Bitcoin Contracts That Are Similar to Ethereum
In order to enable more sophisticated off-chain smart contracts on the Bitcoin network without necessitating a soft fork, a developer by the name of Robin Linus has developed a new technique.
The project lead at ZeroSync, Robin Linus, introduced a system called BitVM in a white paper titled “BitVM: Compute Anything on Bitcoin,” which was published on October 9. Without altering Bitcoin’s core consensus rules, BitVM enables the creation of Bitcoin contracts that are capable of doing Turing-complete computations.
Any computational problem can theoretically be solved by a Turing Complete system. BitVM is a system created for Bitcoin contracts, and it works somewhat similarly to optimistic rollups in Ethereum, where the contract’s logic operates off the Bitcoin network but is confirmed on Bitcoin.
BitVM employs a challenge-response methodology and a structure based on fraud proofs. In this structure, a “prover” makes assertions regarding the contract, and a “verifier” verifies those assertions using fraud-proof techniques to sanction the power if incorrect assertions are found.
Bitcoin can only currently support simple functions like signatures, timelocks, and hashlocks, according to Linus, the creator of BitVM. However, a variety of intriguing applications may now be carried out on the Bitcoin network thanks to BitVM. The model has some restrictions, according to Linus. It mostly functions in situations where there are two parties one prover and one verifier involved. A significant amount of computation and communication off the primary network is also necessary for program execution.
Linus also discussed their forthcoming objectives. They want to completely implement BitVM, which was made possible by the November 2021 Taproot soft fork. They are also developing Tree++, a high-level programming language for building and debugging Bitcoin contracts, in tandem with this.
Linus also noted the impact of studies on optimistic rollups from Ethereum and a study on Merkle Trees. Their eight-page white paper was developed in part thanks to these sources.
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