Classiq and ParityQC Partner to Improve Quantum Circuit Execution Across Hardware

Classiq and ParityQC have announced a partnership to integrate ParityQC’s Parity Twine technology with Classiq’s quantum software engineering platform. This collaboration is intended to create a more direct path from high-level algorithm design to execution on quantum hardware.

This addresses one of the more persistent challenges in quantum computing, which is translating an algorithm into a circuit that can run efficiently on hardware where qubits cannot all interact directly with one another.

Most quantum processors have limited connectivity, meaning information must be moved between qubits before an operation can be performed. This movement is usually done through SWAP gates, which increase circuit depth, execution time and exposure to noise. On current quantum systems, where errors accumulate quickly, inefficient routing can determine whether an experiment produces a meaningful result at all.

Classiq and ParityQC plan to combine Classiq’s universal optimization protocols with ParityQC’s algorithm-aware optimization methods. The goal is to reduce circuit complexity and the number of SWAP operations required when mapping quantum programs onto physical devices.

“Quantum computing will only become practical at scale if the software layer can automatically bridge the gap between algorithmic intent and the constraints of real machines,” said Nir Minerbi, co-founder and CEO of Classiq.

Classiq’s platform uses a model-first approach, allowing developers to define the function and constraints of a quantum program before the platform synthesizes an optimized circuit. ParityQC’s technology introduces additional hardware-aware methods for representing and distributing quantum information across a processor’s connectivity layout.

The integration is intended to place these architecture-specific considerations directly within a higher-level development workflow. Rather than requiring developers to manually redesign algorithms for each processor, the combinatio could automate more of the optimization process while preserving portability across different hardware systems.

This is increasingly important as the quantum hardware market becomes more diverse. Superconducting, trapped-ion, neutral-atom, photonic and other architectures each have distinct connectivity, control and compilation requirements. Software that can retain a degree of hardware independence while still accounting for the physical characteristics of individual devices may become a critical layer of the emerging quantum stack.

The collaboration will target both current noisy quantum processors and future fault-tolerant systems. The companies also indicated that the partnership could extend beyond product integration into academic research, workforce development, benchmarking and future quantum software standards.

The project is supported by Germany’s Federal Ministry for Economic Affairs and Energy following a decision by the German Bundestag.