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papers/lp-308-quantum-amm/sections/03-mixed-ft-nft-liquidity-pools.tex
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\section{Mixed FT/NFT Liquidity Pools}
\subsection{Pool Types}
QuantumSwap supports three pool configurations:
\begin{center}
\begin{tabular}{lll}
\toprule
\textbf{Type} & \textbf{Assets} & \textbf{Use Case} \\
\midrule
FT/FT & Two ERC-20 tokens & Standard AMM \\
FT/NFT & ERC-20 + ERC-721 & RWA token trading \\
NFT/NFT & Two ERC-721 collections & Cross-collection swaps \\
\bottomrule
\end{tabular}
\end{center}
\subsection{FT/NFT Mechanics}
In an FT/NFT pool, the NFT side is treated as a discrete quantity
while the FT side is continuous. The bonding curve operates on the
NFT count, producing FT prices. This enables trade sequences like:
\[
\text{FT} \xrightarrow{\text{Pool A}} \text{NFT}_1
\xrightarrow{\text{Pool B}} \text{NFT}_2
\xrightarrow{\text{Pool C}} \text{FT}'
\]
Each hop uses the bonding curve of the respective pool. The router
contract finds the optimal path across available pools.
\subsection{Capital Efficiency}
Concentrated liquidity in QuantumSwap achieves up to $4000\times$
capital efficiency over Uniswap V2's uniform distribution, consistent
with the analysis in Adams et al.~\cite{uniswapv3}. The improvement
comes from restricting liquidity to a narrow price range rather than
distributing it uniformly from zero to infinity.
\begin{remark}
The $4000\times$ figure is a theoretical maximum for a single tick
range. Practical improvement depends on the LP's price range selection
relative to realized volatility. Empirical data from Uniswap V3
shows typical improvements of $4\times$ to $8\times$ for actively
managed positions.
\end{remark}
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