Classiq and ParityQC Combine to Cut Quantum Circuit Complexity

A Germany-Israel collaboration is targeting a critical obstacle in quantum computing: translating complex algorithms into circuits that can run efficiently on existing hardware. Classiq and ParityQC are integrating ParityQC’s technology with Classiq’s quantum software engineering platform to reduce the number of costly SWAP operations that slow down program execution. The companies report that a combined implementation on an IBM Quantum Heron processor achieved a new benchmark for QFT, nearly doubling the previous result. “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, as the partnership aims to build scalable software infrastructure for both current and future quantum systems. Classiq and ParityQC Integrate for Optimized Quantum Execution The pursuit of practical quantum computation received a boost as Classiq and ParityQC announced a collaborative effort to streamline the translation of complex algorithms into executable quantum circuits. This partnership directly addresses a critical bottleneck in the field: efficiently mapping high-level quantum applications onto hardware constrained by limited qubit connectivity. ParityQC’s specialized technology is now being integrated with Classiq’s quantum software engineering platform, aiming to significantly reduce the complexity of quantum programs before they reach the physical hardware. A key focus of this integration is minimizing SWAP operations, which frequently impede quantum program execution by introducing errors and increasing processing time; the combined methodology of Classiq’s optimization protocol and ParityQC’s algorithm-aware techniques are designed to substantially lower their occurrence. This advancement highlights the potential for tangible improvements in quantum algorithm efficiency through coordinated software and architectural innovation. This cross-border initiative, spanning Germany and Israel, underscores a growing trend toward international collaboration in quantum technology. The partnership focuses not only on near-term noisy intermediate-scale quantum (NISQ) devices, but also anticipates the requirements of future fault-tolerant systems, signaling a long-term commitment to scalable quantum software infrastructure. Wolfgang Lechner, Co-CEO of ParityQC, added that integrating the Parity Tools with Classiq’s platform brings hardware-aware compilation directly into high-level development workflows, lowering the barrier to create useful quantum applications. Magdalena Hauser, also Co-CEO of ParityQC, emphasized the importance of collaborative progress, stating, “Meaningful progress in quantum computing is built on collaboration, and bringing our complementary strengths together is what moves the whole field forward.” The companies intend to expand this collaboration beyond technology integration, exploring academic research, workforce development, and the establishment of industry standards, ultimately aiming to accelerate the transition from theoretical promise to deployable quantum reality. 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. Nir Minerbi, co-founder and CEO of Classiq Source: https://www.globenewswire.com/news-release/2026/07/15/3327449/0/en/classiq-and-parityqc-partner-to-optimize-and-streamline-quantum-execution.html Stay currentSee today’s quantum computing news on Quantum Zeitgeist for the latest breakthroughs in qubits, hardware, algorithms, and industry deals. Tags: Ivy Delaney Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing.

For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release. Latest Posts by Ivy Delaney: Rydberg Polaritons Gain Coherence Via Velocity-Memory Scheme July 15, 2026 Quantum Programs Verified With New Runtime Analysis Framework July 15, 2026 Subspace Restart Drives Quantum Walks Into Drifted-Diffusion Regime July 15, 2026