Single Asset Pools | Provide Liquidity | Earn Rewards
Limit the risks of impermanent loss while providing liquidity
Overview
On Delta, each Liquidity Pool in a Chain Path requires liquidity to facilitate swaps. Adding liquidity to one side of the Chain Path creates a mirrored amount on the other side, with both pools maintaining a record of their counterpart's liquidity.
Similar to Automated Market Maker (AMM) liquidity pools, adding liquidity on Delta generates corresponding LP Tokens. These LP Tokens can be used to reclaim liquidity or participate in Delta staking. Note: LP Tokens are redeemable from either liquidity pool, but cross-chain token redemption is only permitted if there is insufficient liquidity on the executing chain. This mechanism ensures that users can always reclaim their liquidity.
Example: Add ETH liquidity and stake your LP Tokens to earn Delta rewards.
The HUB
Instead of using unified liquidity pools, Delta employs separate liquidity pools for each Chain Path, making each path independent. This approach enhances resilience to chain outages, as only the specific liquidity pool pair involved would be affected, rather than the entire system.
To manage the dispersed liquidity across all Chain Paths, Delta uses a HUB. Each Chain Path connects to the HUB through one liquidity pool. If two chains are not directly connected to the HUB, users can always route through the HUB to reach their desired destination.
Example: Connecting chains A, B, C, D, and E for a single asset involves a separate liquidity pool for each connection. Adding a new chain to the HUB increases the number of liquidity pools by +2, compared to +1 with unified liquidity pools, leading to an exponential increase in the number of fractionalized liquidity pools: nΓ(nβ1)n \times (n - 1)nΓ(nβ1), where nnn represents the number of chains.
HUB: One liquidity pool for each Chain Path connected to the HUB chain (8).
Deltaβs HUB-based approach ensures efficient, decentralized, and resilient cross-chain connectivity while managing liquidity across multiple paths effectively.
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