This week, IBM Quantum partners are traveling from all over the world to convene in London, England for IBM Quantum Partner Forum 2025. The annual event invites partners to hear from IBM leadership and researchers about the latest in quantum hardware, quantum algorithm discovery, and the powerful new software tools that are making it easier than ever to take full advantage of the quantum stack.
As part of this year’s Partner Forum program, we are proud to introduce two brand new application functions debuting today on the Qiskit Functions Catalog: the QUICK-PDE function by French quantum startup ColibriTD, and the Quantum Portfolio Optimizer by Spanish startup Global Data Quantum. The new functions bring an even greater diversity of use cases to our roster of application functions, which are designed to help you harness the full power of utility-scale quantum computers in researching and developing new quantum use cases.
Application functions provide you with a full, ready-made quantum pipeline so you don’t have to build one yourself. Users who access IBM quantum computers through our Premium Plan, Dedicated Service, or the recently introduced Flex Plan can explore these powerful workflows for themselves by requesting a free trial through the Qiskit Functions Catalog homepage.
Below, we’ll provide a brief overview of these two new application functions, and some of the others that have joined the Qiskit Functions Catalog over the past year. Before we do that, let’s take a moment to refresh our understanding of what application functions are, and how they make the power of utility-scale quantum computing more accessible.
What are application functions?
Qiskit application functions are services that abstract away the complexities of the quantum workflow to accelerate quantum algorithm discovery and application prototyping. They take the same classical inputs you would use in your typical classical workflow — training data, molecular definition graphs, etc. — and return domain-familiar classical outputs, making it easy to integrate quantum methods into pre-existing application workflows.
Behind the scenes, the function handles all the details of the typical quantum workflow. It maps classical input data to quantum circuits, optimizes circuits for specific quantum hardware, executes the circuits on quantum hardware, post-processes the results, and translates those results into usable outputs.
This means enterprise developers, data scientists, and others with valuable domain expertise can use application functions to explore problems which are challenging to solve with classical solvers such as CPLEX, Gurobi or Pyscf running on personal computers.
Classical methods require high-performance computing (HPC) resources to solve problems at these scales. As the hunt for quantum advantage progresses, we believe more and more researchers will use application functions to tackle problems that are challenging or impossible for the most powerful HPC systems.
New application functions tackle valuable use cases
Today, we’re adding two brand new application functions to the Qiskit Functions Catalog:
QUICK-PDE by ColibriTD allows users to solve certain differential equations for material deformation and computational fluid dynamics problems. For example, one team of researchers has already begun using the QUICK-PDE function to study the dynamics of novel reactive fluids developed to transfer heat more efficiently in a type of nuclear reactor known as Small Modular Reactors.
Quantum Portfolio Optimizer by Global Quantum Data enables quantitative finance researchers to backtest portfolio optimization strategies. Running at 100Q+, this function calculates a portfolio’s sharpe ratio vs. return across a specified time period. Early users are exploring the optimizer’s ability to evaluate historical performance of an investment strategy and to enable comparisons of different portfolios under similar conditions.
QUICK-PDE and the Quantum Portfolio Optimizer aren’t the only application functions that have joined the Qiskit Functions Catalog since the catalog’s initial launch in 2024:
Iskay Quantum Optimizer by Kipu Quantum is designed to tackle a variety of combinatorial optimization problems, but performs particularly well for higher-order binary optimization tasks, where the objective function is a polynomial with binary variables. Researchers have found that the Iskay optimizer outperforms popular classical optimization solvers in financial use cases such as portfolio optimization, in one case using just 156 variables for a problem that would require 1,000+ variables when mapped to typical classical optimization solvers.
HI-VQE Chemistry by Qunova Computing allows computational chemists to tackle approximate molecular ground state quantum chemistry problems involving 16-22 orbitals modeled on 32-44 qubits. By contrast, popular classical tools for solving the same problems — Pyscf, MOLPRO, Q-Chem, ORCA, etc. — can typically handle no more than 36-qubit problems on a desktop computer, and would require HPC resources for anything more.
The Singularity Machine Learning function by Multiverse Computing addresses classification problems that benefit from ensemble learning and complex model optimization. Today, you can use classical tools like AdaBoost, Random Forests, or stacked ensemble methods to handle similar problems, but without HPC resources, these methods quickly become a bottleneck. Leveraging IBM QPUs, users can train large ensembles and perform global optimization of ensemble configurations using QAOA-based quantum optimization, beyond the feasible memory and compute power of local machines.
Making it easier to run, debug, and analyze Qiskit Functions
Qiskit Functions are constantly improving to reflect your feedback. Since launch, our partners have improved performance, added new features, and implemented a number of upgrades that make it easier to run, debug, and analyze workloads.
In addition to the new functions we’re announcing, today’s launch brings a new round of improvements — with clearer error messaging to help you troubleshoot independently when experiments don’t run as expected, detailed status updates for realtime insight into your workload, and resource summaries to help you analyze performance.
The new QUICK-PDE and Quantum Portfolio functions already incorporate all three of these improvements, and you’ll be able to use this information across more functions over the coming weeks.
Get started today
Interested in giving Qiskit Functions a try? Each of our third party functions providers offers a free trial for Premium Plan, Dedicated Service, and Flex Plan users who would like to see for themselves how functions can help accelerate their research. Visit the Qiskit Functions Catalog today and click on the function of your choice to find links for requesting your free trial.
For those with more experience designing quantum workflows, you may be wondering how you can get started building your own function. If you’re a Premium Plan, Dedicated Service, or Flex Plan user with a quantum workflow that you would like to turn into a Qiskit function, you can get started with function templates, starter kits that demonstrate essential best practices and which are deployable with Qiskit Serverless.
Whether you’re using functions or building them, we hope you’ll join our growing ecosystem and help us push forward to quantum advantage and truly useful quantum computing.
