Capacitive loading has emerged as a major obstacle to scaling fluxonium qubits from one-dimensional to highly connected two-dimensional (2D) architectures, yet its physical origin remainspoorly understood. We derive an analytical relation between the qubit capacitance budget and the achievable capacitive coupling to external circuit elements, identifying the parasitic capacitances of Josephson junctions and Josephson junction arrays as the dominant source of capacitive loading while showing that the qubit-pad geometry can instead be engineered to mitigate it. Building on these insights, we formulate practical design principles and numerically demonstrate ultrafast, high-fidelity two-qubit gates in 2D fluxonium architectures. Our results reveal that capacitive loading does not constitute a fundamental limit for 2D fluxonium quantum processors.
Fluxonium qubits combine long coherence times with strong anharmonicity, making them a promising platform for scalable superconducting quantum processors. Recent experiments have demonstratedhigh-fidelity operations in multi-qubit processors while suppressing stray qubit interactions using fluxonium-transmon-fluxonium (FTF) architectures. However, scaling such systems to larger arrays is constrained by a trade-off between achievable coupling strength, crosstalk suppression and qubit-qubit spacing required for wiring in a two-dimensional architecture. Multimode couplers, such as the double-transmon coupler (DTC), provide a promising pathway to overcome this limitation by enabling stronger interactions without compromising qubit spacing and isolation. Here, we develop a quantitative design framework for fluxonium-based quantum processors employing DTCs. Central to this work is a frequency-partitioned architecture that places qubit transitions, tunable-coupler excitations, and resonator modes in well-separated spectral regions. This structured allocation reduces parameter interdependence and enables the concurrent optimization of gate operations, readout, and qubit reset. By formulating device design as a multi-objective optimization problem under realistic experimental constraints and fabrication-induced disorder, we develop a tractable sequential workflow and determine a feasible parameter regime that simultaneously supports high-fidelity single- and two-qubit gates, fast qubit reset, and robust dispersive readout. These results establish a system-level architectural methodology that links circuit parameters to processor-level performance, and provide an experimentally actionable pathway toward scalable fluxonium quantum processors.