Algorithmiq

The Wellcome Leap Quantum for Bio program shares our vision about the potential of #quantumcomputing applications in health and life sciences, and this is why we decided to apply to the #Q4Bio Supported Challenge Program. 🤩 It is, therefore, even more exciting to share that we have moved to Phase 2 of the program together with Frederic T. Chong from Infleqtion, Jonathan Hirst from University of Nottingham, Kanav Setia from qBraid, Matthias Christandl from University of Copenhagen, Mikhail Lukin from Harvard University, Grant M. Rotskoff from Stanford University, and Sergii Strelchuk from University of Cambridge. 💫 During Phase 2, the focus will be on large-scale simulations of the algorithms developed in Phase 1 using classical high-performance computing (HPC). The goal is to develop biology and health applications that will benefit from near-term quantum computers and that will successfully address human health challenges. Wellcome Leap builds programs that “aim to deliver breakthroughs in human health over 5 – 10 years and demonstrate seemingly impossible results on seemingly impossible timelines”. We are ready to take on the challenge. 🚀 #wellcomeleap

Why is everyone so excited about #quantumcomputers? 👉 Quantum computers have the potential to solve much more complex problems than computers available today, including supercomputers. But why is this so hard to achieve? 👉 Quantum computers are susceptible to errors, partly due to external factors like noise or interference. You might think that we are forced to wait until fault-tolerant quantum computers become possible, but that is a common misconception 🤔. In fact, by using techniques that effectively reduce noise, called quantum error mitigation, we can still get answers to problems we couldn't otherwise solve. To make a simple analogy, even the best noise-cancelling headphones available today can't filter out all background noise, but there's no doubt that this technology allows us to enjoy a much higher quality music listening experience 🎧. Why #Algorithmiq’s Tensor-network Error Mitigation (TEM) method is so interesting: 😈 It is optimal; of all existing methods, it requires the smallest number of additional measurements for successful noise mitigation. 😈 It works entirely in post-processing without needing extra circuits, which means lower costs and fewer errors. 😈 It makes quantum algorithms more reliable and precise. #TEM is now available on IBM's Qiskit Functions Catalog! ⚡ Are you curious to know how it works in practice? Head over to Algorithmiq’s blog to learn more 👇. https://lnkd.in/dzsY4r7C

Our team members Martina Stella, Elsi-Mari Borrelli, and Fabijan Pavosevic joined the Nordic Quantum Life Sciences Round Table 2024 together with our collaborator from Cleveland Clinic, Vijay Krishna, and all we got is the picture below 🥺 (we were hoping for some Norwegian cookies 🤭). You might remember that Algorithmiq hosted last year’s edition in Helsinki, and this year we shared our strategy towards accurate #quantum simulations for drug discovery. 🧪 We also took part in the panel "From Theory to Reality: Quantum Hardware Needs for Life Science Applications". With a focus on interdisciplinary collaboration and on exploring the possibilities of #quantumtechnologies for healthcare and life sciences, we are looking forward to next year’s round table in Sweden. 🇸🇪 Thanks to the organizers: Ebba Carbonnier, Morten Bache, Sabrina Maniscalco, Pedro G. Lind, and Daniel Lundqvist! Hopefully, next time our team will also bring back some cinnamon buns! 🍪

🇨🇭 At the Quantum Industry Day in QuantumBasel our co-founder Boris Sokolov shared our latest results on the collaboration with Cleveland Clinic and the application of TEM and treespilation on near-term devices for industry-relevant use cases. #QIDIS2024

Karl Freund has covered the announcement of Algorithmiq’s Tensor-Network Error Mitigation algorithm, #TEM, on IBM’s Qiskit Function Catalog and you can read the full article on Forbes 👁️🗨. This is what our CEO Sabrina Maniscalco had to say about the potential impact of TEM on #quantumcomputing: “The immediate future of quantum computing relies heavily on effective error mitigation techniques. Through the power of TEM error mitigation running on IBM quantum hardware, we can push the boundaries of what near-term quantum devices can achieve, bringing us closer to practical and advantageous quantum computations”. ⚡

🇬🇧 Last week, Sabrina Maniscalco, Elsi-Mari Borrelli and Stefan Knecht presented our latest advances towards using the power of near-term quantum computers to optimize drugs for photodynamic cancer therapy at the Q4Bio - Quantum for Bio Wellcome Leap meeting in Ascot. 💫 This work is a joint effort with the teams of Vijay Krishna, Cleveland Clinic and Ivano Tavernelli, IBM Quantum Zürich and the meeting marked the end of Phase 1 of the Q4Bio Wellcome Leap Program. 💬 We were particularly excited to share our one-year progress with our fellow Q4Bio competitors and discuss advances, challenges and synergies with the other teams. 💡 Photodynamic cancer therapy is a targeted, spatially and temporarily controlled cancer therapy which relies on an efficient light-to-chemical energy conversion driven by a photosensitiser drug molecule. In our Q4Bio project, we developed throughout Phase 1 an end-to-end quantum algorithms software framework which allowed us to perform the first, successful photochemistry quantum simulations on IBM system one at Cleveland Clinic for a clinically relevant photosensitiser drug molecule. 🙏 A huge thanks to the Q4Bio Wellcome Leap Director, Shihan Sajeed and the Q4Bio Wellcome Leap Program Coordinator, Nate Smith for making this wonderful event possible. 👇For more info, check out the comments

🇨🇦 If you are at #IEEE Quantum Week, you might have already heard that today, we have some big news to share! 🚀 Together, with our partner IBM, we have launched our Tensor-Network Error Mitigation algorithm, #TEM on IBM’s Qiskit Function Catalog! 🚀 💫 Our breakthrough error mitigation algorithm will enable to run quantum simulations and computations previously unattainable. What does it mean in practice? One of the biggest obstacles to achieving true quantum advantage (the potential of #quantum computers to solve currently unsolvable problems) is device noise, which introduces unwanted errors into a quantum computer’s calculations and results. This is why it’s essential to apply error mitigation strategies when working with current near-term devices. 👥 Since the inception of #algorithmiq, our incredible team of researchers has worked on a better solution to this problem. Our efforts has culminated in the release of TEM, which has previously achieved unprecedented error mitigation without the need for additional quantum circuits. 💥 TEM is now available on IBM’s Qiskit Functions Catalog for all customers in IBM’s Quantum Network. 🔊 As Jay Gambetta, VP of IBM Quantum comments: “As we move along the IBM Quantum roadmap towards ever larger quantum systems, Qiskit Functions incorporating error mitigation services such as Algorithmiq’s TEM will help extend the boundaries of what today’s systems can explore. Together with our partners, we look forward to using techniques such as TEM to discover quantum algorithms that will unlock new computational territory and push towards quantum advantage”. ➡ Share the news with your colleagues working with #quantumalgorithms. We are looking forward to seeing what results can be achieved with TEM, available only on IBM’s new Qiskit Functions Catalog!

🔜 Hold tight for next week’s big announcement! Summer has been very busy as we prepare for an exciting release… 🔊One of the biggest obstacles to realizing the promise of current quantum computing is the errors that occur in existing quantum computation. While fault-tolerant quantum computing is still a long way off, powerful error mitigation strategies are essential to derive value from current near-term quantum computing. 🌠 This is one of our areas of expertise. #Algorithmiq’s Tensor Network Error Mitigation (TEM) method has been proven to be optimal in increasing the accuracy and precision at utility-scale using tensor-networks in post-processing, while also reducing the amount of additional measurements required to bring down the noise. Next week will mark the launch of months of a collaboration announced at #IEEE Conference that aims to extend the boundaries of what today’s quantum systems can explore. This launch will move us along the roadmap towards ever larger quantum systems that will unlock new computational territory, pushing toward quantum advantage. 🔜 Stay tuned!

🇩🇪Today, Aaron Miller, one of our talented young researchers, presented our Treespilation algorithm at the 6th International Workshop on Quantum Compilation in Berlin. 🌳The algorithm chooses a way of translating fermionic problem that aims to reduce the cost of implementing circuits on a quantum machines. This is an important step forward to a faithful quantum hardware utilisation. 🔎 Details on our algorithms can be found in https://lnkd.in/dNzbfQ4v Adam Glos

On September 10th, you will be able to listen to some of the world’s most interesting discussions at The Hudson Forum, including a session on #quantumcomputing with our CEO Sabrina Maniscalco. Starting at 9:00, Jerry M. Chow, Sarah Sheldon, Michael Biercuk, Travis Humble and Sabrina will discuss quantum utility, #artificialintelligence, and commercial use cases for quantum algorithms. Here are some of the questions that will be discussed (but you are welcome to ask more): 🔎 Is quantum advantage possible without fault-tolerant quantum computers? 🔎 Why is noise such a problem for quantum computers, and how can it be managed? 🔎 What is possible with the current hardware and error mitigation? 🔎 How can quantum algorithms be used for the development of healthcare and life sciences? If you are attending The Hudson Forum, make sure to get your questions ready, or you can leave us a comment below👇. We will do our best to ensure your question gets answered during the panel.