## DAG Ledger Structure: - Transaction 1 (A -> B) is recorded and validated independently. - Transaction 2 (B -> C) is another independent record that may confirm or validate a prior transaction. - Transaction 3 (C -> A) also gets recorded, and it confirms the previous transactions. ### Example: Transaction 1: Wallet A -> Wallet B Transaction 2: Wallet B -> Wallet C Transaction 3: Wallet C -> Wallet A In a DAG ledger, each transaction is a node, and the edges represent validations or approvals. For example, **Transaction 3** (C -> A) may validate **Transaction 1** (A -> B) and **Transaction 2** (B -> C), but not in a cyclic manner—each transaction points to earlier transactions without creating a loop back to itself. How It Remains Acyclic: **Sequential Validation:** Each transaction validates previous transactions without forming a closed loop. **Forward Movement:** In the ledger, the sequence moves forward in time and dependencies—no transaction points back to itself or creates a closed cycle in the validation structure. This is why, even though tokens can circulate among wallets in any pattern, the underlying transaction confirmations and dependencies in the ledger form a DAG without cycles. The key is to differentiate between **the flow of assets** and the **structural dependencies of the transactions themselves**. Reference: https://en.wikipedia.org/wiki/Directed_acyclic_graph // * Node: Each transaction is a node. While tokens can circulate among // * accounts in any pattern (including returning to the origin), the // * transaction confirmations in a DAG structure always move forward // * without creating cycles. // // * Edges: Edges represent validations or approvals. Transaction dependencies // * do not create cycles, meaning a new transaction cannot be dependent // * on itself, either directly or indirectly. // // * Graphs: The graph represents how transactions are connected and validated // * rather than direct token exchanges between accounts.