What structure does MD6 utilize to handle long input messages?

MD6 utilizes a Merkle-tree-like structure to handle long input messages, which is essential for efficiently processing and hashing large amounts of data. This approach allows MD6 to break down the input data into manageable pieces, each represented as a leaf node in the Merkle tree. These leaf nodes are combined through a series of hashing operations to form the parent nodes, ultimately resulting in a single hash that encapsulates the entirety of the original input.

The Merkle-tree structure is particularly advantageous for handling long inputs because it enables parallel processing of the leaves, which can significantly enhance performance, especially for larger datasets. It also provides a way to verify the integrity of data without needing to hash the entire input again, making it suitable for applications that require data integrity verification.

In contrast, structures like a linear queue or a circular buffer do not inherently provide the same level of efficiency or the ability to create a cumulative hash representation for long inputs. A chain of hashes could be used but lacks the structured efficiency and verification benefits found in a Merkle tree. Thus, the Merkle-tree-like structure is the most appropriate and advantageous choice for handling long input messages in MD6.