BlueQubit

📄 New Paper Alert! "Efficient charge-preserving excited state preparation with variational quantum algorithms" 🧑💻 Researchers from NVIDIA, Stony Brook University, and Brookhaven National Laboratory introduce CPVQD (Charge-Preserving Variational Quantum Deflation), a breakthrough algorithm that makes excited state calculations more efficient on quantum computers! Key Results: 🔹 Successfully tested systems up to 24 qubits using GPU-accelerated quantum simulations on NERSC's Perlmutter system 🔹 Achieved 99.7% quantum computation ratio for largest systems (24 qubits) 🔹 Reduced 4-qubit HeH+ ion system from 16 possible states to just 4 states through charge preservation 🔹 Demonstrated successful convergence for Schwinger model calculations at large mass Why It Matters: Understanding excited states of quantum systems is crucial for advancing everything from drug development to new materials design. While classical computers struggle with these calculations due to the exponential scaling of quantum states, quantum computers offer a natural way to simulate these systems - if we can make the algorithms efficient enough for today's noisy quantum hardware. 🎯 Read the full paper here: https://lnkd.in/dKVC_M7q

Why do we use NVIDIA GPUs to accelerate quantum algorithms on the BlueQubit platform? Quantum simulations require massive parallel computations for matrix and tensor operations. While traditional CPU approaches struggle, GPUs can handle thousands of calculations simultaneously, enabling: 🔷 Universal state-vector simulations up to 36 qubits 🔷 Multi-node GPU simulations pushing beyond traditional limits 🔷 Tensor network simulations handling 100+ qubits in some cases While CPUs have to process these sequentially, GPUs can handle thousands of calculations simultaneously - making them perfectly suited for quantum computing problems as a stepping stone to run. Additionally? There's positive environmental impact! 🌱 As researcher Steven Thomson notes in the NVIDIA Developer blog on "Simulating Quantum Dynamics Systems with NVIDIA GPUs": "Without GPUs, simulations would have taken tens or hundreds of times longer to run... [coming] with a huge environmental cost due to the energy required." GPU acceleration enables entirely new areas of quantum research while reducing computational energy costs. ⚡ Sources: 🔷 NVIDIA Developer Blog (October 16, 2024) - https://lnkd.in/dMm783_x 🔷 BlueQubit BlueQubit Offers Managed Quantum Simulators, Powered by NVIDIA Technology Blog (March 18, 2024) - https://lnkd.in/dAFZPEE4

🔬 Quantum Computing Takes On Biological Systems! In this new paper "Quantum Embedding of Non-local Quantum Many-body Interactions in Prototypal Anti-tumor Vaccine Metalloprotein on Near Term Quantum Computing Hardware", researchers from King's College London have demonstrated the first-ever quantum simulation of hemocyanin - a crucial respiratory protein with cancer-fighting potential - marking a significant leap in quantum computing's biological applications! Key Results: 🔹 Achieved a quantum simulation of hemocyanin (Hc) - an important respiratory protein used in cancer vaccines! 🔹 Achieved convergence within 0.485% accuracy on Quantinuum hardware 🔹 Tested multiple simulation configurations up to 14 qubits Technical Achievements: 🔸 Developed quantum embedding method for non-local quantum interactions 🔸 Mapped complex molecule onto Anderson impurity model (AIM) 🔸 Tested different ansatz types (UCCS, UCCSD, Hardware-Efficient) 🔸 Analyzed impact of noise and hardware topology on results This breakthrough demonstrates quantum computing's potential to provide new approaches for understanding complex biological systems, particularly in drug development and cancer therapeutics, by enabling direct quantum mechanical simulations of strongly correlated electron systems. 🧬🚀 Read the full paper here: https://lnkd.in/eVA8BsSw

We're so happy to welcome Jake Malliaros to BlueQubit! Jake joins us as our new Vice President of Business Development, bringing a wealth of experience from his career in quantum computing and tech innovation. Having held pivotal roles at companies like Open Quantum Design and Creative Destruction Lab, Jake has a deep understanding of the quantum landscape. With Jake leading our business development, we’re excited for the new heights BlueQubit will reach. His technical expertise and strategic vision will be invaluable as we work to make enterprise quantum software solutions more accessible and effective. Welcome to the team, Jake!

Thank you, IBM Quantum, for an incredible visit! It was a pleasure diving into quantum algorithms, hardware progress, and the journey toward quantum advantage together. #quantumcomputing #quantum #qml

Join Hrant Gharibyan, PhD, Co-founder and CEO of BlueQubit, and Pero Subasic, Director of Systems Engineering at Honda Research Institute USA, Inc., at Inside Quantum Technology today Oct 30th, 2024 at 4:30 PM to discuss how to supercharge image processing with quantum computing! #quantumcomputing #quantum #quantumcomputers #iqt24 #qml

🚀 BlueQubit team is at the Inside Quantum Technology (Inside Quantum Technology) Conference in New York! If you’re around, come swing by our booth! We’re sharing some exciting insights into our Quantum Algorithms work and can’t wait to connect with others pushing the boundaries of quantum tech. Curious about how BlueQubit is bridging enterprise problems with quantum solutions? Drop by, say hello, and let’s chat about the future of quantum computing together! #IQT2024 #QuantumComputing #Bluequbit

Join Hrant Gharibyan, PhD at Inside Quantum Technology in New York on October 29th-30th, 2024! Hrant will showcase our recent achievements in applying quantum machine learning methods to image processing, discuss experiments conducted on IBM and Quantinuum quantum computers, and dive into the latest trends and opportunities in QML. 📅 October 29th at 2:35 PM: 🔹 Panel Discussion: “Emerging Markets for Quantum Machine Learning” 📅 October 30th at 4:30 PM: 🔹 Presentation: “Supercharge Image Processing with Quantum” Looking forward to seeing you there! #quantumcomputing #quantum #quantumcomputers #iqt24

Ever wondered how quantum computing could revolutionize AI and machine learning? 🚀 🔷 Quantum Machine Learning (QML) combines quantum computing power with ML algorithms 🔷 Hybrid quantum-classical models bridge current technology with quantum capabilities 🔷 Applications are already emerging in finance, healthcare, and transportation Hybrid quantum-classical models optimize different ML tasks depending on what is most efficient on a classical or quantum system. Classical Layers can include: 🔷 Data preprocessing and cleaning 🔷 Feature selection and engineering 🔷 Result post-processing 🔷 Optimization loop management Quantum Layers can include: 🔷 Complex matrix operations 🔷 High-dimensional space exploration 🔷 Probabilistic computations The result is that a task like portfolio optimization that would take classical computers days can be approximated in hours or minutes, while considering exponentially more possible combinations. Want to learn more about quantum machine learning? Read our blog post here: https://lnkd.in/ejdpsEKx #quantumcomputing #qml #ml #machinelearning

🚀 Supercharge Image Processing with Quantum Computing! Interested to learn more about quantum machine learning and BlueQubit’s collaboration with Honda on image processing. Join us at Inside Quantum Technology in New York on October 29th-30th, 2024. 📅 October 29th at 2:35 PM: 🔹 Panel Discussion: “Emerging Markets for Quantum Machine Learning” Join me and industry experts as we delve into the latest trends and opportunities in QML. 📅 October 30th at 4:30 PM: 🔹 Presentation: “Supercharge Image Processing with Quantum” I’ll showcase our recent achievements in applying QML methods to image processing and discuss experiments conducted on IBM and Quantinuum quantum computers. Looking forward to seeing you there! https://lnkd.in/ga74yaXb #quantumcomputing #qml #quantumcomputers