IBM is accelerating the pursuit of quantum advantage with significant updates to its Qiskit Functions, empowering researchers to tackle complex challenges without requiring deep quantum expertise. Launched in 2024, and expanded in 2025, Qiskit Functions now boast a broadened catalog of nearly a dozen pre-built software services designed to automate key portions of quantum workflows—spanning chemistry, optimization, and machine learning. These “abstractions” allow scientists to focus on application value rather than deployment intricacies, and are already enabling teams to scale experiments to record qubit and gate counts. As Sanket Panda and Robert Davis explain, the goal is to make large-scale quantum experimentation accessible: “Qiskit Functions make it easier than ever for researchers to run large‑scale quantum experiments without deep quantum expertise.” Premium and Flex Plan users can request free trials starting today, with eligible organizations able to secure a free one-year license until March 31st.
Qiskit Functions Catalog Enables Scalable Quantum Workflows
Nearly a dozen pre-built functions are now available to streamline quantum experimentation, allowing researchers to scale to record qubit counts without requiring specialized quantum expertise. The Qiskit Functions Catalog, launched in 2024—a year ahead of schedule according to initial IBM Quantum Roadmaps—is rapidly evolving into a central resource for accelerating quantum applications research. This collection of “abstractions” developed by partners within the IBM Quantum ecosystem automates crucial steps in quantum workflows, freeing researchers to concentrate on application value.
The catalog currently boasts almost a dozen functions addressing key areas like quantum error-handling, partial differential equations, chemistry simulation, optimization, and machine learning. These functions are categorized as either ‘Application functions’ or ‘Circuit functions’, catering to varying levels of quantum computing experience. Application functions accept classical inputs, automatically mapping problems to quantum circuits and executing them at full system scale. Conversely, circuit functions are designed for those directly working with quantum circuits, offering optimized execution and post-processing with customizable trade-offs between time and accuracy.
Premium and Flex Plan users can immediately explore these capabilities by requesting a free trial for any function within the catalog. Furthermore, organizations with the IBM Quantum Premium Plan can request a free one-year license until 31 March. Recent enhancements focus on improving the user experience throughout the experimental process. Researchers can now run up to four concurrent experiments, gaining detailed visibility into each stage—from mapping and hardware optimization to QPU execution and post-processing. Detailed resource insights are also provided, revealing CPU, GPU, and QPU usage throughout the workflow.
This data, accessible via a single line of code job.result()['metadata']['resource_usage']allows for informed decisions regarding classical versus quantum resource allocation. An example workload summary might reveal that “RUNNING: EXECUTING_QPU” consumed 159.0 units of QPU time. Real-time log access with enriched metadata is planned for future release, alongside clearer error messages for faster debugging. The impact of Qiskit Functions is already demonstrable across academic and industrial settings.
Researchers at Yonsei University are utilising Qunova’s HI-VQE function to scale molecular simulations, achieving experiments with up to 44 qubits and over 96 two-qubit CNOT gates. “The HI-VQE method successfully produces smooth and stable potential energy curves, demonstrating its scalability and reliability for systems beyond the reach of classical and other sample-based quantum algorithms,” notes the Yonsei team in recent research. Similarly, University of Tokyo researchers leveraged Qedma’s QESEM function to scale experiments studying quantum many-body scars to 25 qubits and 480 two-qubit gates.
Enterprise teams at E.ON, SoftBank, Mitsubishi Chemical, and Qubit Pharmaceuticals have also seen success with Q-CTRL’s Performance Management and Optimisation Solver functions, achieving improved results and scaling beyond previous limitations. ColibriTD, a startup partner, scaled its QUICK-PDE application function to 144 qubits and improved accuracy by 61% using Q-CTRL’s Performance Management circuit function. According to IBM, these examples “highlight how Qiskit Functions are enabling industry and academic researchers to dive into utility-scale quantum experiments.”
Application & Circuit Functions Accelerate Research
The landscape of quantum computing is rapidly evolving, shifting from foundational hardware development toward practical application exploration. While achieving fault-tolerant, universal quantum computers remains a long-term goal, researchers are increasingly focused on leveraging near-term devices to tackle complex problems. A key enabler of this transition is the emergence of pre-built software services, known as Qiskit Functions, designed to streamline the process of running large-scale quantum experiments without requiring extensive quantum expertise. This allows researchers to dedicate more time to problem-solving and less to the intricacies of quantum workload deployment.
These functions aren’t merely theoretical tools; they are driving tangible results across diverse fields. Beyond academia, enterprise organisations are also realising significant benefits. Mitsubishi Chemical, for instance, extended Quantum Phase Estimation circuits to “a scale of up to 52 qubits and 5,000+ two-qubit gates,” a new world record. Qubit Pharmaceuticals recently executed a drug-discovery workload at “up to 123 qubits and 2,000 two-qubit gates,” achieving classical precision in hydration-site prediction.
Concurrent Experiments & Enhanced Resource Insights
Researchers are increasingly leveraging parallel processing to accelerate quantum experimentation, and IBM’s Qiskit Functions are at the forefront of this trend. Beyond simply adding new functions to its catalog, the platform is delivering tools designed to maximize efficiency and provide granular insight into resource allocation, allowing scientists to push the boundaries of quantum computation. Improvements now permit users to run “up to 4 concurrent experiments to speed up your research iterations,” a significant leap forward for iterative development and testing.
This isn’t merely about speed; detailed visibility into each experiment’s state – encompassing mapping, hardware optimization, QPU execution, and post-processing – provides a level of control previously unavailable. This enhanced control extends to a deeper understanding of computational resources.
Future updates promise even greater granularity, with the imminent arrival of real-time logs enriched with metadata like two-qubit reduction after transpilation, and clearer error messages to facilitate rapid debugging and restarts. The impact of these tools is already being felt across multiple disciplines.
HI-VQE & QESEM Functions Scale to 44 Qubits
Researchers are achieving unprecedented scale in quantum simulations thanks to advancements in pre-built software components known as Qiskit Functions, with recent experiments pushing the boundaries to 44 qubits and beyond. These “abstractions” are enabling teams to tackle increasingly complex problems in fields ranging from materials science to drug discovery, accelerating the timeline towards practical quantum applications. The Qiskit Functions Catalog, launched in 2024, provides readily available tools that automate key aspects of quantum workflows, allowing scientists to concentrate on problem-solving rather than the intricacies of quantum hardware.
The impact of these functions is becoming increasingly apparent in academic and industrial settings. This scalability is particularly significant, as it allows for the investigation of more complex molecular systems previously inaccessible to quantum simulation. Parallel progress is being made with the QESEM function, developed by Qedma. This achievement highlights the function’s effectiveness in tackling problems in condensed matter physics, where understanding the behavior of interacting quantum particles is paramount. Beyond academia, several enterprise teams are also realizing benefits from Qiskit Functions. These advancements collectively signal a shift towards more practical and impactful quantum computing research.
These abstractions—the Qiskit Functions—are pre-built software services that automate key portions of the typical quantum workflow.
