IBM and RPI collaborate on quantum-centric supercomputing tools

🚀 Call for Papers: Special Issue on "Software Frameworks and Workload Management on Quantum and HPC Ecosystems" 🧠 This Special Issue focuses on the development of software frameworks and workload management strategies that are crucial for Quantum-HPC (Q-HPC) ecosystems. As quantum computing progresses, integrating quantum processors with HPC systems presents significant opportunities to tackle complex, large-scale problems. Experts from academia, industry, and national labs will discuss the challenges of managing hybrid resources, along with cutting-edge research on middleware, scheduling algorithms, decomposition strategies, and benchmarking methodologies for Q-HPC systems. 📚 Guest Editors: Dr. Esam El-Araby, Dr. Naveed Mahmud and Dr. In-Saeng Suh 🔍 Explore the full details and submission guidelines here: https://lnkd.in/gVW7pME9 MDPI The University of Kansas Florida Institute of Technology Oak Ridge National Laboratory #QuantumHPC #QHPC #workflowmanagement #quantumprogramming #optimizationalgorithms #resourceallocation #CallForPapers

At Georgia Institute of Technology's Partner for an Advanced Computing Environment (PACE), improving how researchers use and develop software in high-performance computing (HPC) environments is at the forefront of our decisions. Last week at USRSE'25 in Philadelphia, Fang (Cherry) Liu, PhD presented our poster on the Research Computing Accounting Management System (RCAMS) — a project that I have been contributing to over the past 10 months, building on earlier work led by Alan Tao. This effort represents the combined expertise of multiple Research Scientists and Research Software Engineers (RSEs) at PACE. By applying human-centered design (HCD) principles, our goal has been to make RCAMS not just a management platform, but a system built around real-world workflows and needs of both researchers and HPC environments. I’m excited to see this collaborative work continue to shape the future of research computing at Georgia Tech. #USRSE25 #GeorgiaTech #PACE #RSE #HCD #HPC #opensource #innersource #conference

Researchers at the Technical University of Munich (TUM) have created a tool that enables seamless interaction between quantum computers and existing supercomputers, addressing the integration challenges posed by their differing architectures and interfaces. This hybrid tool, named sys-sage, has been demonstrated in collaboration with the Leibniz Supercomputing Centre (LRZ).

The NQCC Quantum Computing Access Programme is now open for academic proposals! We’re excited to announce that UK researchers can now apply to access cutting-edge quantum computing resources through the Quantum Computing Access Programme – empowering the next wave of discovery and innovation. This initiative is designed to: - Accelerate quantum computing research - Build skills for the next generation of quantum experts - Drive application discovery across diverse domains Academic users are invited to apply for access to QC resources in Q4 2025. The programme is part of the NQCC’s wider SparQ initiative, supporting the UK’s journey toward quantum readiness. Learn more and apply here: https://lnkd.in/eAhwb2FU #QuantumComputing #Research #QuantumInnovation #SparQ #QuantumReadiness UK Research and Innovation EPSRC STFC Quantum Software Lab

For 20 years, LLNL’s Computing Grand Challenge Program has accelerated scientific discovery with unclassified supercomputing resources. In the latest issue of the Science &Technology Review, explore how supercomputing rises to grand scientific challenges: https://str.llnl.gov/

⚡🤝 Day 18 – Variational Quantum Algorithms (VQAs) Day 18 of my QuCode 21 Days Quantum Computing Challenge – Cohort 3! If the past few days were about quantum’s theoretical breakthroughs (Shor, Grover), today was about its practical survival strategy in the NISQ era: V Variational Quantum Algorithms (VQAs). 🔹 The Hybrid Loop A VQA is not fully quantum — it’s a dance between quantum and classical worlds: A parameterized quantum circuit (PQC) encodes candidate solutions. Measurements extract expectation values. A classical optimizer updates the parameters. The loop repeats, steadily converging toward an answer. 🔹 Why it Matters VQE (Variational Quantum Eigensolver) estimates molecular ground states, crucial for chemistry and materials science. QAOA (Quantum Approximate Optimization Algorithm) tackles combinatorial optimization, from logistics to finance. Hybrid design makes VQAs robust to noise and feasible on today’s shallow circuits. 🔹 Challenges & Insights Smart choice of ansatz (hardware-efficient vs problem-inspired) is critical. Barren plateaus and noise can stall progress, but clever optimizers (SPSA, COBYLA) keep the loop alive. Most importantly, the same framework flexibly adapts to chemistry, ML, and optimization tasks. ✨ Takeaway VQAs show that the future of quantum won’t be purely quantum — it will be hybrid. They remind me that innovation often means compromise: not waiting for perfect hardware, but building algorithms that thrive within constraints. The beauty of VQAs is simple — they don’t just open the quantum door, they hold it open long enough for us to walk through. 🚀 #Day18 #QuCodeChallenge #QuantumComputing #VQE #QAOA #HybridComputing #FutureOfTech #LearningJourney

It is always hard to publish negative results, but is actually really important to keep our scientific estimates rigorous and honest. So I wanted to highlight the paper "Recent quantum runtime (dis)advantages" by J. Tuziemski, J. Pawłowski, P. Tarasiuk, Ł. Pawela, B. Gardas As they state in the abstract: "We scrutinize two important milestones: (1) quantum annealing for approximate QUBO, which uses a sensible time-to-ϵ metric but proxies runtime by the annealing time (non-measurable); (2) a restricted Simon's problem, whose advantageous scaling in oracle calls is undisputed; yet, as we demonstrate, estimated runtime of the quantum experiment is ∼100× slower than a tuned classical baseline. Finally, we show that recently claimed "runtime advantage" of the BF-DCQO hybrid algorithm (arXiv:2505.08663) does not withstand rigorous benchmarking." https://lnkd.in/esX6Vjyx

Researchers from Vanguard and IBM introduce a new paper investigating the value of quantum computing for portfolio optimization—one of the most computationally challenging problems in finance: https://ibm.co/6045BJeBP The collaborative research underscores the growing promise of quantum optimization workflows—combining the natural ability of quantum circuits to explore high-dimensional solution spaces with sophisticated classical algorithms that refine and validate results. More importantly, it’s an exciting example of how leading financial services organizations are exploring quantum as a potential source of meaningful advantages in valuable applications like portfolio construction.

💡 Quantum Meets Asset Management Excited to see how IBM and Vanguard are pushing the boundaries of finance and technology. In their latest research, they explore variational quantum algorithms (VQAs) to tackle portfolio optimization problems that classical approaches struggle with. IBM 🔍 Some highlights: They combine quantum sampling with classical local search to navigate complex, constrained investment landscapes. The hybrid workflow showed optimization gaps within industry-acceptable ranges, even when compared with traditional classical solvers. The study used 109 qubits on IBM’s hardware and still showed robustness in noisy environments 🔗 Read more: https://lnkd.in/ewKB_Q79 #QuantumComputing #FinanceInnovation #IBM #Vanguard #PortfolioOptimization

A quantum leap in finance is here. The question is: who will be ready for it? This new research from IBM and Vanguard on quantum portfolio optimization is a landmark moment. It's a powerful signal that we're moving from theoretical quantum problems to real-world, high-impact financial applications. The core challenge they're tackling is the sheer complexity of financial modeling—a 'combinatorial explosion' that strains even classical supercomputers. This is where quantum algorithms are set to revolutionize the industry. But this raises a critical question: As quantum applications become a reality, how do we equip the next wave of developers, analysts, and researchers with the necessary skills and tools? That's the question we're tackling head-on at QuantumLings (quantumlings.com/). To meet this future, I'm excited to share our own strategic roadmap, which is focused on two core pillars: 1. Guided Learning Paths: To provide a clear, structured journey from quantum basics to the advanced algorithms being used by companies like IBM. 2. An Enhanced Qiskit Playground: To offer a powerful, intuitive tool with the stunning visibility needed to truly understand how these quantum circuits work. We are building the platform where you can learn the skills to be a part of this new era. If this future excites you, join the conversation and follow our journey at Quantumlings. #QuantumComputing #FinTech #Finance #IBM #Vanguard #Roadmap #EdTech #Quantumlings #Qiskit #FutureOfWork #Innovation