IBM Quantum

Nominations for the Richard Feynman Prize in Quantum Computing, sponsored by Abdus Salam International Centre for Theoretical Physics (ICTP) and IBM, are now open: https://ibm.co/6049Bzpyx Named after Nobel laureate and American physicist Richard Feynman—renowned for his work in quantum electrodynamics—this new, annual prize recognizes significant contributions to the field of quantum computing, including algorithms, applications, and simulations. Nominations close 30 November 2025. Self-nominations not accepted.

A few months ago, we shared with you our progress on developing novel decoding algorithms for qLDPC codes. That effort resulted in the Relay-BP algorithm (https://lnkd.in/eFbWNFeU), which surpassed prior state-of-the-art qLDPC decoders in terms of logical error rate while simultaneously removing barriers toward real-time implementation. In particular, we showed that a novel variation of the belief propagation (BP) algorithm was sufficient for accurate decoding of our gross code without the need of an expensive second-stage decoder to fix cases where BP failed to converge. I’m excited to tell you about some of the progress we’ve made on taking the first steps towards implementing a real-time decoder in hardware (https://lnkd.in/e8CShTmT). Our initial effort has focused on FPGAs because they are very flexible and allow for very low-latency integration into our quantum control system. FPGAs’ flexibility in supporting custom logic and user-defined numerical formats allowed us to evaluate the performance of Relay-BP across a range of floating-point, fixed-point, and integer precisions. Encouragingly, we observe a high tolerance to reduced precision. Our experiments show that even 6-bit arithmetic is sufficient to maintain decoding performance. We explored the speed limits of an FPGA Relay-BP implementation in a maximally-parallel computational architecture. Like traditional BP, the Relay-BP algorithm is a message-passing algorithm where messages are exchanged between nodes on a decoding graph. Our maximally parallel implementation assigns a unique compute resource to every node in this graph, allowing a full BP iteration to be computed on every clock cycle. This decoder architecture is resource-intensive, but we succeeded in building a Relay-BP decoder for the gross code and fit it within a single AMD VU19P FPGA. Our implementation is limited to split X/Z decoding of the gross code syndrome cycle (we decode windows of 12 cycles), a simpler implementation than we’d need for Starling. That being said, it is extremely fast, an absolute requirement for practical implementation. In fact, we can execute a Relay-BP iteration in 24ns. As physical error rates drop below 1e-3, Relay-BP typically converges in less than 20 iterations. This means we can complete the decoding task in about 480ns. This is significantly faster than what is possible with NVIDIA’s DGX-Quantum solution, which requires a 4000ns start-up cost before decoding begins. The figure below compares the logical error performance versus physical error rate of our FPGA implementation compared to a floating-point software implementation for memory experiments of the size of Loon and Kookaburra on our Innovation roadmap. This and further data shows that the reduced precision arithmetic in the FPGA matches the accuracy of a software model, while simultaneously running dramatically faster. Further details are in the pre-print: https://lnkd.in/e8CShTmT

Registration is now open for our upcoming expert-led quantum industry session: https://ibm.co/6045BK5g5 As quantum computing rapidly advances, it’s critical for finance organizations to invest in internal capabilities and evaluate emerging use cases—such as portfolio optimization, risk exposure estimation, quantum-safe cryptography, and more—to capture value in the quantum era. Join Vincent J. Beltrani, along with our consulting partners from EY, KPMG, and LTIMindtree, for a conversation on how we’re helping banking and insurance organizations explore the potential of quantum computing to solve some of the most complex computational problems in finance. Speakers: Evangelos Thomas Karamatskos, Dr. Aaron C. Kemp - CISSP, IBM Champion, and Indranil Mitra 👆 Sign up at the link above.

A new paper, now published in Nature Computational Science, introduces "Quantum Approximate Multi-Objective Optimization," a breakthrough from researchers at IBM, Los Alamos National Laboratory, and Zuse Institute Berlin. This work represents one of the most promising proposals for near-term demonstrations of quantum advantage in combinatorial optimization, with enormous relevance across industry and science: https://lnkd.in/ew7Pe2K5 Multi-objective optimization is a branch of mathematical optimization that deals with problems involving multiple often conflicting goals—e.g., constructing financial portfolios that minimize risk while maximizing returns. These problems can be extremely challenging for classical methods as the number of objective functions increases, even in cases where the single-objective version of the problem is easily solvable. The study demonstrates how quantum computers can approximate the optimal Pareto front, i.e., the set of all optimal trade-offs between conflicting objectives, showing better scaling than classical algorithms. Sampling good solutions from vast solution spaces is a task at which quantum computers excel, and the researchers take full advantage of that in their work. This marks an important step toward practical quantum advantage in optimization, and shows the value of exploring quantum capabilities beyond conventional problem classes. The paper is the latest outcome from our quantum optimization technical working group, and I encourage you to have a look.

Our latest IBM Institute for Business Value report — “Secure the post-quantum future” — reveals that 73% of organizations say business and technology leaders are collaborating on their quantum-safe strategy: https://ibm.co/6043Bz865 Cryptography underpins our digital world, but as quantum computers scale, many current encryption methods will become vulnerable. This shift highlights the urgent need for quantum-safe solutions. Yet despite growing awareness, action lags. Skills shortages and the belief that “vendors will handle it” (held by 62% of respondents) contribute to a risky sense of complacency. Quantum Safe isn’t just an IT issue—it’s a business-wide resilience challenge. Learn how to protect trust, compliance, and competitiveness in the quantum era in the link above.

🚀 QuARC 2025! 🚀 Learn about NISQ and Fault-Tolerant Quantum Algorithms! Dive deep on Quantum Error Correction methods and how they are compiled on hardware! Join us for QuARC 2025 with the world's leading experts from industry and academia coming to Los Angeles. ✅ Hands-On Workshops on Quantum Algorithms and Quantum Error Correction from Google, IBM and more ✅ Networking Sessions with industry professionals ✅ Win Prizes ✅ Learn marketable skills 🌟 Whether you’re just beginning or an expert, QuARC is the perfect place for you to level up in quantum algorithms. 📅 When & Where? 📍 November 10-12, 2025 | 9:00 AM – 5:00 PM | UCLA James West Alumni Center 🌏 Can't join in person? Participate online from anywhere in the world and get access to all materials! 🔗 Learn more and register: https://lnkd.in/dwd8VqXK 🍕 Breakfast & lunch provided We thank our sponsors Google, IBM, Alice & Bob, BlueQubit, Qblox , Fetchai Foundation, Quantum Elements and Aqora for making this event possible. Come, connect, collaborate, and push the boundaries of quantum technology with us at QuARC 2025!

Our quarterly update, “What’s New at IBM Quantum”, is now live: https://ibm.co/6041BK7TL Revisit the latest updates, releases, and resources from IBM Quantum and Qiskit in this convenient one-pager designed to help you and your team dive into new capabilities right away. Highlights include, but are not limited to: 🧰 Key features from Qiskit 2.2 SDK launch 📊 New quantum + HPC workflow demo 🪶 Heron Revision 3 QPU, ibm_pittsburgh 💻 Qiskit v2.X developer certification

We’ve reached an important milestone on the journey to realizing our vision of quantum-centric supercomputing: a new demo showcasing how Qiskit’s C API now enables end-to-end compiled-language quantum + HPC workflows. Learn more on the IBM Quantum blog (https://lnkd.in/eN-g9nuA) or explore the demo on GitHub (https://lnkd.in/eZHcbduA). Progress toward quantum advantage is accelerating and the first demonstrations of it will likely leverage quantum to accelerate classical HPC. To cross that finish line, and facilitate our collaboration with the HPC community, we need to enable full quantum workflows in compiled languages like C++ and Fortran, which power the lion’s share of today’s HPC data centers. This new demo is the result of incredible collaboration both across IBM and with our partners in the IBM Quantum Network. It would not be possible without the work we’ve done on the recent Qiskit SDK v2.2 release, which introduces a new standalone C API transpiler (https://lnkd.in/eGcCu45a), a key ingredient in our compiled-language workflows. The demo also leverages capabilities from open-source projects like the SBD eigensolver built by our partners at Japanese national laboratory RIKEN (https://lnkd.in/e8Gg7mJx), Qiskit C++ (https://lnkd.in/eKYS5yK8), the quantum resource management interface or QRMI (https://lnkd.in/eBa39cX2), the qiskit-ibm-runtime C client (https://lnkd.in/exXZgByC), and the new HPC-ready version of Qiskit’s SQD addon (https://lnkd.in/e2KC5niH). Together, these capabilities allow you to compile a hybrid QCSC workflow into a single binary executable that uses MPI in a way that is native for a broad cross-section of HPC environments—a remarkable achievement given that our C API is less than a year old. I hope you’ll explore the resources and GitHub repos linked above to test drive the QCSC workflows of the future, and to see how you can contribute to these open-source community efforts. 

Applications for IBM Quantum 2026 Internships are now open! https://ibm.co/6040BK2Xn Quantum interns at IBM will have the opportunity to research quantum applications, design hardware, develop open-source projects with Qiskit, and collaborate directly with the researchers, developers, and business experts who are pushing quantum computing forward. If you’re interested in quantum computing and are currently a student, we encourage you to apply through the link above. This is an excellent opportunity for students to gain valuable experience in an emerging field.