Riverlane

Last week, we announced our milestone Series C fundraise, which will bring us closer to our mission of making quantum computing useful far sooner than previously imaginable. 🎯     As part of this effort, we are introducing various new opportunities across Riverlane, such as hardware and software engineering, quantum scientist positions, and operations roles.      If you’d like to be part of the team at the forefront of the quantum computing revolution, then check out our open roles here: https://lnkd.in/e-r--t_w   (Prior quantum computing knowledge is not necessary❗ ) #quantumcomputingjobs #quantumerrorcorrection #quantumjobs #STEMcareers

Will quantum computing have its 'Sputnik' moment? 🛰️ In light of our $75m Series C raise, our Founder and CEO, Steve Brierley, and VP of Quantum Science, Earl Campbell, recently spoke with James Pheby about the potential of quantum computing and Riverlane's role within the sector as the company taking on the industry's 'error problem'. Speaking about recent industry progress, Steve says, "There's definitely a scrambling to understand what's coming next in technology. It's really important that we learn the lessons from AI, not be surprised by the technology, and think early about what those implications are going to be." 📰 Read the full interview in Fortune here: https://lnkd.in/eFwYhJgj

Riverlane's mission—to make quantum computing useful far sooner than previously imaginable—has remained unchanged since day one.      Today, we're excited to share another milestone on that journey - Riverlane has raised $75 million in Series C funding 🚀      The round was led by Planet First Partners with participation ETF Partners and EDBI Pte Ltd and existing investors Cambridge Innovation Capital, Amadeus Capital Partners, the National Security Strategic Investment Fund (NSSIF) and Altair.       As quantum computers continue to scale, quantum error correction (QEC) will be a critical enabler to unlock the industry's next wave of progress.      This investment will enable Riverlane to expand operations to meet growing demand for QEC technology from hardware companies and governments worldwide.      Thank you to our partners, investors and the incredible Riverlane team who have all made this milestone possible 🙏      For quantum computing, it's now no longer a matter of 𝘪𝘧 but when... 💥 📎 Read more: https://lnkd.in/eppA2BvG #quantumcomputing #quantumerrorcorrection #Riverlane   

“After many years of academic and industrial research, the field is reaching an inflection point. Quantum computing is becoming ‘QEC-ready’." Our VP quantum science, Earl Campbell, spoke to Ray Fernandez from Techopedia about how quantum error correction can help unlock the first useful applications for quantum computers and Riverlane's recently released roadmap for our QEC Stack, Deltaflow. "The QEC stack will be a critical component of every reliable quantum computer, regardless of its manufacturer, operator, and qubit modality." Find out more: https://lnkd.in/eQG7BZbq #quantum | #quantumerrorcorrection |#quantumcomputing

💥 Pow! Our Collision Clustering decoder packs quite the (quantum error-correcting) punch Our staff quantum engineer, Kenton Barnes, explains how the team recently integrated our ‘sliding window’ decoding technique into the proprietary Collision Clustering decoder. This method, essentially, allows arbitrarily long memory experiments to run in a hardware decoder for the first time. The CC decoder is an integral part of the current Deltaflow 1 release of our QEC Stack. It is also available through our software decoder suite QEC Explorer, which provides a range of decoders for offline experiments and simulations to help quantum hardware companies get QEC-ready. 👉 Find out more here: https://lnkd.in/eyvCN8Ew #quantum | #quantumcomputing | #quantumerrorcorrection

🌍 "We must build quantum computers in a way that can help tackle climate change-related problems without releasing excessive additional CO2 into the atmosphere. Any other strategy would be nonsensical." In a recent article for embedded.com, our VP Engineering, Marco Ghibaudi, explains how quantum computers could help tackle climate change-related problems, what the quantum community can learn from AI and how quantum error correction plays a vital role when tackling this important challenge. "The word efficient is key: we want to compute faster and with a lower energy footprint than a classical computer." 👉 Read the full article here: https://lnkd.in/eFG48CZY #quantumcomputing | #quantum | #climatechange

📣 Riverlane and Atlantic Quantum 📣     We're proud to announce a new partnership where we'll work together to advance a range of unique quantum error correction techniques for Atlantic Quantum's superconducting fluxonium-based qubit architecture.     Here's how:  💫 All quantum computers will need QEC to detect and correct the errors that qubits are prone to.     💫 MIT spin-out Atlantic Quantum has already done "excellent work" (according to our CEO Steve Brierley) with its unique qubit architecture, which achieves the lowest error rates for superconducting qubits, exceeding fidelities of 99.9% for two-qubit gates and 99.997% for single-qubit gates.   💫 Riverlane's patented quantum error correction stack ('Deltaflow') turns large numbers of unreliable qubits into smaller numbers of reliable 'logical' qubits, thus enabling the system to decode errors and execute logical operations in real time.     💬 Bharath Kannan, Co-founder & CEO of Atlantic Quantum, said: "Quantum error correction (QEC) is the only way to enable sustained quantum computation and is foundational to all useful applications. We are excited to collaborate with the QEC experts at Riverlane to maximize the potential of our world-class hardware as we scale to larger systems."    📎 Read more about our collaboration in this piece by Linnea Ahlgren (TNW): https://lnkd.in/eA95Egx3 #quantumcomputing #quantumerrorcorrection #quantumpartnerships  

😲 "Error-correcting a quantum computer can mean processing 100TB every second." John Timmer from Ars Technica dives into Riverlane's technology, our roadmap and how many start-ups are targeting the hard problems in quantum. 📣 For Riverlane, we're targeting quantum error correction, aka "the huge amount of classical computations that are going to be necessary to make the quantum hardware work," according to John. "Regardless of the physics involved in controlling the qubits, everybody borrowed the same hardware from a different field [...] That makes it relatively easy to integrate Riverlane's hardware with a variety of systems." 📣 Our CEO Steve Brierley also gave a personal insight into why he's so passionate about QEC as the key to unlocking useful quantum computing, explaining to John why he's optimistic about the Riverlane roadmap and broader future of quantum computing. "I think we'll see the first long-lived logical qubit in the next 12 months, and we'll quickly get to hundreds of logical qubits in two to three years," Steve told Ars. 👉 Find out more here: https://lnkd.in/ess9ZFwT

🚀 Introducing Riverlane’s Quantum Error Correction roadmap     We’ve set ourselves the goal of building the first prototype of a MegaQuOp-scale QEC Stack by the end of 2026. We are calling the final product Deltaflow Mega, with intermediate releases every year.     At a MegaQuOp (million error-free quantum operations), a quantum computer can run simulations that no supercomputer can.  Today's machines are capable of a few hundred QuOps. ⏩ Now: Deltaflow 1 - Fast decoding In 2023, Riverlane released the first generation of its Quantum Error Correction Stack, Deltaflow 1, demonstrating that decoding can be scaled to an arbitrarily long sequence of gates [1].  ⏰ 2024: Deltaflow 2 - Streaming, high-fidelity memory We will extend the memory functionalities in time. Deltaflow 2 will support a streaming high-fidelity memory, i.e., a single logical qubit as a memory experiment in real time. Essentially, DF2 allows us to keep the qubits alive “forever”, meaning for as long we want. 💡2025: Deltaflow 3 – Streaming logic Deltaflow 3 will support a broad set of operations belonging to the so-called Clifford gate set. It will support Clifford operations with a few (2-4) logical qubits, and up to 1,000 physical qubits. 📈2026: Deltaflow Mega – Logic at scale Deltaflow Mega will constitute a significant milestone for the quantum computing industry. It will take the quantum industry into the realm of the first operations that cannot be efficiently classically simulated, by supporting non-Clifford logic and fast feedback for the first time. 🚀 Beyond 2027: Pushing to the GigaQuOp, then TeraQuOp The MegaQuOp is a critical milestone, but it's just the first step on the journey to full fault tolerant quantum computing. Some projections estimate we’ll need a trillion error-free quantum operations (‘TeraQuOp’) and millions of physical qubits to unlock the higher value applications of quantum computing.    So, the fundamentals of Deltaflow are founded on scalable principles to take us there in the long run. As the ecosystem continues to pull together and quantum computers mature, so will Deltaflow. For the next few years, we’ll sprint with our eyes firmly fixed one prize: building a Quantum Error Correction Stack capable of delivering a million error-free quantum operations across every major qubit platform. We’re already working with quantum computing’s top hardware companies to achieve this. We hope you’ll join us on this exciting journey. 👉 Find out more from our VP quantum science Earl Campbell and VP product and partnerships Maria Maragkou here: https://lnkd.in/gvUaZJaX #quantumcomputing | #quantum | #quantumerrorcorrection | #QuOp | #MegaQuOp [1] https://lnkd.in/eHZSuwxx 

🌎 ⚡ Can quantum computing learn sustainability lessons from AI?     In a recent Q&A with Berenice Baker (IoT World Today), our VP of Engineering, Marco Ghibaudi discussed quantum computing’s potential to combat climate change by creating energy savings.    In the interview, Marco emphasises the importance of building sustainability and energy efficiency into the development of quantum computing from the outset, learning from the energy challenges faced by the AI industry.    He encourages players across the quantum computing field to prioritise power-efficient design and join initiatives like the Quantum Energy Initiative to collaboratively address these challenges.    🔗 Read the full Q&A to learn more about Marco’s thoughts on this topic and how it informs the engineering approach of our QEC Stack: https://lnkd.in/eibEacwN