Hybridlane: A Software Development Kit for Hybrid Continuous-Discrete Variable Quantum Computing

TL;DR

Hybridlane is an open-source SDK that enables unified development and validation of hybrid quantum circuits combining discrete qubits and continuous variables, supporting multiple backends and improving scalability.

Contribution

It introduces automatic wire type inference, a comprehensive hybrid gate library, and backend support, addressing fragmentation and scalability issues in hybrid quantum software.

Findings

Supports hybrid quantum circuit validation and compilation.

Demonstrates applications in bosonic phase estimation and ion trap calibration.

Enables scalable hybrid quantum programming without simulation overhead.

Abstract

Hybrid quantum computing systems that combine discrete-variable qubits with continuous-variable qumodes offer promising advantages for quantum simulation, error correction, and sensing applications. However, existing quantum software frameworks lack native support for expressing and manipulating hybrid circuits, forcing developers to work with fragmented toolchains or rely on simulation-coupled representations that limit scalability. We present Hybridlane, an open-source software development kit providing a unified frontend for hybrid continuous-discrete variable quantum computing. Hybridlane introduces automatic wire type inference to distinguish qubits from qumodes without manual annotations, enabling compile-time validation of circuit correctness. By decoupling gate semantics from matrix representations, Hybridlane can describe wide and deep circuits with minimal memory consumption and without requiring simulation. The framework implements a comprehensive library of hybrid gates and decompositions following established instruction set architectures, while remaining compatible with PennyLane's extensive qubit algorithm library. Furthermore, it supports multiple backends including classical simulation with Bosonic Qiskit and hardware compilation to Sandia National Laboratories' QSCOUT ion trap. We demonstrate Hybridlane's capabilities through bosonic quantum phase estimation and ion trap calibration workflows.