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Alumni Spotlight: Ryan Levy

Alumni Spotlight: Ryan Levy Ryan Levy worked at the Center for Computational Quantum Physics (CCQ) at the Simons Foundation’s Flatiron Institute as a research fellow from September 2022 to June 2025. Levy received his Ph.D. in physics from the University of Illinois Urbana-Champaign in 2022, where his work spanned quantum Monte Carlo (QMC) methods, tensor networks and, more recently, quantum computing. We recently caught up with Levy to ask him what he’s been up to as he’s continued his career. The Flatiron Institute works to develop the next generation of computational scientists. Interested in joining us? See our careers page. Flatiron Institute alumni can also keep in touch by joining our alumni network. What are you doing now? I am the applications lead for Fundamental Research at PsiQuantum, where I help develop and guide applications for quantum computing, with a strong focus on lattice models in condensed matter such as the Hubbard model. I get to work both internally, at the intersection of algorithms, business and methodology teams, as well as with external partners (academia, labs, etc.) to explore how fault-tolerant quantum computers can advance basic research. What is one thing that you’ve taken away from your time at the Simons Foundation that helps you in your current role? Being exposed to very diverse scientific audiences, both within CCQ and across the foundation more broadly. It’s sometimes hard to see the scale that state-of-the-art science can achieve outside of your immediate domain, and the variety of speakers the foundation would regularly host really helped showcase this. What is the coolest adventure you’ve been on since you left? For my wife’s birthday, we decided to explore Long Island for a long weekend: hanging out with rescue cows and goats at a farm (we fed them animal crackers, hah!), getting fresh pie

Pangea 5: TotalEnergies unveils AI supercomputer with 6x <b>computing</b> power

Pangea 5: TotalEnergies unveils AI supercomputer with 6x computing power Pangea 5 will multiply TotalEnergies’ computing power sixfold for AI and seismic workloads. French energy major TotalEnergies is building a new high-performance supercomputer called Pangea 5 to expand its artificial intelligence and seismic imaging capabilities for energy exploration and research. The system will be installed at the company’s Jean Féger Scientific and Technical Center in Pau, France, and is expected to go live in 2027. The company said the supercomputer will increase its computing power sixfold compared to current systems. The project is being developed in partnership with Dell Technologies and NVIDIA and represents an investment of more than 100 million euros. Pangea 5 will be used to process complex geological and energy data, including advanced seismic imaging that helps energy companies map underground structures more accurately. TotalEnergies said the added computing power will also support AI-based research and integrated power system modeling. The company plans to use the platform to shorten computing times and improve analysis of complex industrial processes tied to energy production and transition technologies. AI powers energy search “Artificial intelligence and digital technology are strategic drivers of our energy transition. By increasing our computing power sixfold, we are strengthening our leadership in high-performance computing ensuring that our experts teams continue to have the means to push the envelope to support the development of our activities and meet the growing global demand for energy,” said Namita Shah, President, OneTech at TotalEnergies. The company said the system will rely on specialized processors optimized for massively parallel computing tasks. These chips are designed to process large-scale scientific and industrial workloads more efficiently than traditional computing systems. According to TotalEnergies, Pangea 5 will cut energy consumption by around 40 percent at equal performance levels compared to earlier versions. The cooling

<b>Quantum Computers</b> Now Learn From Experiments Far More Efficiently

A new quantum uploading procedure accelerates the processing of data from physical experiments. Ishaan Kannan and colleagues at Harvard University demonstrate exponential speedups in both classical shadow tomography and the estimation of cubic observables, surpassing the performance of non-encoded adaptive strategies. The advance is key because it overcomes the challenge of noise when coupling a quantum processor to an experimental sample, maintaining learning efficiency even with imperfect hardware. The team validated their findings with a simulation of astronomical imaging, showing sharp reductions in the number of measurements needed to detect exoplanets, and establishing the potential of fault-tolerant quantum computation for scientific discovery. Embedding quantum states within error-correcting codes for noise durability Quantum uploading swiftly embeds an unknown quantum system into a protective quantum code; this is a method of protecting quantum information from errors, similar to how redundant data is used in traditional computing to ensure data integrity. This process immediately shields the quantum information, compressing any initial exposure to noise into a single, manageable step before fault-tolerant processing begins. The technique begins with a transduction stage, mapping the physical state from the experiment onto the quantum processor’s memory, followed by injecting that state into an error-correcting code, effectively creating a strong logical state Efficiency gains are substantial when performing learning tasks on this encoded state, circumventing the typical slowdowns caused by accumulating noise during analysis. Embedding a quantum system into an error-correcting code protects information from noise during processing. First, the physical state is transduced onto the quantum processor’s memory, then injected into the code, creating a strong logical state. The chosen approach compresses initial noise exposure into a single step, allowing for fault-tolerant processing and circumventing typical slowdowns; the code distance can be arbitrarily high with constant error overhead. Quantum uploading enhances exoplanet detection and quantum state characterisation

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<b>Quantum</b> Risk Explained

Quantum Risk Explained: What, When, How? Summary - Quantum computing is moving from theory toward early practical use, with direct implications for encryption, authentication, and long-term data confidentiality. - The primary risk is the eventual emergence of cryptographically relevant quantum computers (CRQCs), which would break today’s public-key cryptography and undermine encryption, digital identity, and software trust at scale. - Quantum risk is already present: “harvest now, decrypt later” activity exposes long-lived sensitive data today, regardless of when CRQCs ultimately arrive. - Regulatory mandates and procurement standards are accelerating post-quantum cryptography (PQC) adoption, making quantum readiness a multi-year compliance and resilience priority. - Organizations that delay preparation beyond 2026 are likely to face compressed migration timelines, higher transition costs, and increased operational disruption. Quantum Computing Explained Quantum computing applies principles of physics to solve certain complex problems far more efficiently than classical computers. Its security relevance lies primarily in cryptanalysis and optimization: A sufficiently powerful quantum computer will reduce the calculations required to protect today's public-key encryption from thousands of years to hours or less. Researchers have used the term “Q-Day” to refer to the hypothetical point at which quantum computers will be powerful enough to break encryption. Quantum computing is now moving from theory toward early practical use, bringing “Q-Day” closer to reality. Industry estimates suggest quantum computing alone could generate up to $1.3 trillion in value by 2035. Major cloud providers, including IBM, Google, and Microsoft, are expanding their quantum services, while specialised firms such as Quantinuum and PsiQuantum continue to improve system stability and error correction. While these advances are not yet transformative, they are consistent with the early stages of commercial adoption. Alongside its potential benefits across finance, pharmaceuticals, defense, and other sectors, quantum computing introduces four key security risks. Risk 1: Breaking Public-Key Encryption The most

America 250: Learning from World War II in today's race for <b>quantum</b> security

As the United States marks its 250th anniversary, WTOP presents “250 Years of America,” a multipart series examining the innovations, breakthroughs and pivotal moments that have shaped the nation since 1776. Knox Systems is proud to partner with WTOP to bring you this series. When Allied codebreakers cracked encrypted messages during World War II, the course of the conflict shifted dramatically — but those victories were years in the making. The Allies gained a decisive edge by reading German military communications very early in the war. That advantage didn’t happen overnight. It was the result of years of work by Polish and British mathematicians, who laid the groundwork for breaking the complex codes used by the German military. Their efforts, along with the work of cryptanalysts who broke Japanese codes, gave the Allies access to information that would prove critical in major battles and strategic decisions. By late 1940, U.S. Army and Navy teams were able to read Japanese diplomatic traffic between Tokyo and its embassies in major cities. This ability to intercept and understand enemy communications allowed Allied leaders to anticipate moves, plan counterattacks and avoid deadly traps. According to the National Museum of the U.S. Air Force, these breakthroughs saved countless lives and may have shortened the war by as much as two years. The story of World War II code breaking isn’t just a tale of secret rooms and mysterious machines — it’s a lesson in the importance of preparation and innovation. The nations that invested early in cryptography and code breaking technology held the advantage when it mattered most. The Allies’ readiness to tackle encrypted messages gave them a head start that paid off in the heat of battle. Fast forward to today, and some experts see a parallel in the race for quantum computing. Quantum

Cleveland Clinic Releases New National Report on the State of Women's Health in the U.S.

Findings show many women are more concerned about affording care than developing serious diseases — with gaps in prevention and clear information shaping their decisions Content is property of Cleveland Clinic and for news media use only. Maria Shriver (left) and Beri Ridgeway, M.D., at the Global Women’s Health + WAM Forum on May 7. A new national report from Cleveland Clinic’s Women’s Comprehensive Health and Research Center highlights gaps in how women across generations understand, access and manage their health. The findings show that financial concerns, inconsistent engagement with preventive care and limited access to clear, credible information are influencing health decisions at every stage of life. For many women, these challenges are not abstract — they are shaping real decisions about when and how to seek care. Based on a survey of 2,000 women ages 18 and older, the report finds that while many women are taking steps to support their health, several challenges continue to affect how and when they seek care. Nearly half of women (45%) say their biggest concern as they age is not having enough money to take care of their health — more than those who cite serious conditions like cancer, heart disease or Alzheimer’s disease as their primary concern. “This report makes one thing clear: women’s health is in crisis with persistent and consequential gaps in how women understand and manage their health across the lifespan,” said Maria Shriver, founder of the Women’s Alzheimer’s Movement (WAM) at Cleveland Clinic and co‑founder of the Cleveland Clinic Women’s Comprehensive Health and Research Center. “Too many women lack clear information about their health risks, and too many are unsure whether they can afford the care they need. By addressing these gaps in knowledge, access, and affordability, we have a meaningful opportunity to improve health outcomes

From Theory to Impact: Real-World Results in <b>Quantum</b> Machine Learning

About the research collaboration This research was conducted through a collaboration between KPMG Quantum Research, IBM, and Kipu Quantum, combining enterprise problem framing, quantum algorithm design, and execution on leading quantum hardware platforms. The work focuses on translating cutting‑edge quantum science into practical, enterprise‑ready machine‑learning applications—grounded in measurable outcomes rather than theoretical benchmarks. All findings were developed and authored by human researchers using established classical and quantum machine learning methodologies.

<b>Quantum</b> Motion Secures $160M Series C to Scale Silicon Spin QPUs

Quantum Motion, a developer of silicon transistor-based quantum computers, has closed a $160 million Series C funding round. The investment was co-led by DCVC and Kembara (the deep-tech fund of Mundi Ventures), with significant new participation from the British Business Bank and Firgun. The round also saw full support from existing investors, including Oxford Science Enterprises, Inkef, Bosch Ventures, Porsche Automobil Holding SE, and Parkwalk Advisors. This financing positions Quantum Motion as the UK’s best-funded quantum computing company and is intended to accelerate the commercialization of utility-scale systems that utilize existing CMOS manufacturing processes. The Silicon Transistor Advantage Quantum Motion’s architecture is built on the premise that quantum information can be processed using the same silicon transistor technology found in modern smartphones and laptops. By utilizing quantum dots to trap single electron spins, the company can manufacture qubits within standard semiconductor foundries. This approach offers a significant reduction in physical and resource overhead compared to other modalities; the company reports a 100-fold reduction in cost and space requirements and a 1,000-fold reduction in energy consumption relative to industrial-scale architectures that require bespoke, multi-megawatt facilities. Deployment and Manufacturing Integration The Series C follows the 2025 deployment of a full-stack silicon CMOS quantum computer at the UK National Quantum Computing Centre (NQCC). This system demonstrated single and two-qubit gates, entanglement, and reliable measurement within a footprint of only three standard server racks. To ensure a scalable supply chain, Quantum Motion has deepened its manufacturing partnership with GlobalFoundries, allowing its roadmap to integrate directly into commercial 300mm wafer production lines. This strategy aims to deliver “utility-scale” processors that fit within existing data center racks rather than requiring dedicated buildings. International Expansion and Talent Growth Since 2023, Quantum Motion has expanded its global operations, opening new laboratories and offices in Spain and Australia to

<b>Quantum</b> Motion Secures $160M Series C to Scale Silicon Spin QPUs

Quantum Motion, a developer of silicon transistor-based quantum computers, has closed a $160 million Series C funding round. The investment was co-led by DCVC and Kembara (the deep-tech fund of Mundi Ventures), with significant new participation from the British Business Bank and Firgun. The round also saw full support from existing investors, including Oxford Science Enterprises, Inkef, Bosch Ventures, Porsche Automobil Holding SE, and Parkwalk Advisors. This financing positions Quantum Motion as the UK’s best-funded quantum computing company and is intended to accelerate the commercialization of utility-scale systems that utilize existing CMOS manufacturing processes. The Silicon Transistor Advantage Quantum Motion’s architecture is built on the premise that quantum information can be processed using the same silicon transistor technology found in modern smartphones and laptops. By utilizing quantum dots to trap single electron spins, the company can manufacture qubits within standard semiconductor foundries. This approach offers a significant reduction in physical and resource overhead compared to other modalities; the company reports a 100-fold reduction in cost and space requirements and a 1,000-fold reduction in energy consumption relative to industrial-scale architectures that require bespoke, multi-megawatt facilities. Deployment and Manufacturing Integration The Series C follows the 2025 deployment of a full-stack silicon CMOS quantum computer at the UK National Quantum Computing Centre (NQCC). This system demonstrated single and two-qubit gates, entanglement, and reliable measurement within a footprint of only three standard server racks. To ensure a scalable supply chain, Quantum Motion has deepened its manufacturing partnership with GlobalFoundries, allowing its roadmap to integrate directly into commercial 300mm wafer production lines. This strategy aims to deliver “utility-scale” processors that fit within existing data center racks rather than requiring dedicated buildings. International Expansion and Talent Growth Since 2023, Quantum Motion has expanded its global operations, opening new laboratories and offices in Spain and Australia to

Qutwo Raises €25M ($29.4M USD) Angel Round to Bridge Enterprise AI and <b>Quantum Computing</b>

Qutwo, a Helsinki-based AI and quantum software startup, has secured €25 million ($29.4 million USD) in an angel funding round, reaching a valuation of €325 million ($382.2 million). Founded by Peter Sarlin, formerly the CEO of Silo AI (acquired by AMD for $665 million in 2024), the company operates as an “AI lab for the quantum era.” The investment features a group of high-profile backers, including Yuri Milner, Xavier Niel, Niklas Zennström, and the founders of category-defining European companies such as Hugging Face, Supercell, and Wolt. Orchestrating the Next Paradigm: Qutwo OS The company’s core product, Qutwo OS, is an orchestration layer designed to manage AI workloads across classical, quantum-inspired, and emerging quantum hardware. Rather than focusing solely on future quantum processors, Qutwo emphasizes “quantum-inspired” computing, which utilizes classical high-performance chips (including NVIDIA, AMD, and Google TPUs) to simulate quantum behaviors for complex optimization and modeling tasks. This approach allows enterprises to achieve performance gains on reliable hardware today while preparing their R&D pipelines for the eventual arrival of utility-scale quantum machines. Commercial Traction and Industry Partnerships Within two months of its February 2026 launch, Qutwo secured over €20 million in contracted revenue through strategic design partnerships. Notable collaborations include: - Zalando: Development of “lifestyle agents” and advanced AI assistants for retail. - OP Pohjola: Implementation of financial modeling and risk management tools for the banking sector. - Open-Source Innovation: The company is developing Miles, an open-source tool for large-scale reinforcement learning, intended to enhance model performance after initial training. Interdisciplinary Leadership and Scientific Depth Qutwo’s team of over 50 scientists and engineers combines expertise from both the AI and quantum hardware sectors. The founding team includes Kaj-Mikael Björk (Silo AI co-founder) and Kuan Yen Tan (co-founder of IQM Quantum Computers). The company’s board of directors includes Pekka Lundmark, the

A grapefruit-sized <b>quantum</b> device mapped Earth's magnetic field from space

A grapefruit-sized quantum device mapped Earth’s magnetic field from space A diamond sensor in the cube showcases quantum magnetometers’ potential An imperfect diamond is perfect for sensing Earth’s magnetic field from space. A quantum device used a diamond’s defects to map Earth’s magnetic field from the International Space Station. Just 10 centimeters on a side, OSCAR-QUBE reveals the potential of the technology. It performed consistently over 10 months of data taking in 2021 and 2022, and its measurements agreed with a previous estimate of the magnetic field, engineer Jaroslav Hruby and colleagues report in a paper published May 7 in Physical Review Applied. Space-based measurements of Earth’s magnetic field typically require bulky satellites. Quantum sensors can be smaller, while also being more sensitive and operating more stably, among other benefits. OSCAR-QUBE’s sensor is made of a lentil-sized piece of diamond with defects in its lattice of carbon atoms, in which a carbon atom is missing and a neighboring carbon is replaced by a nitrogen. The defects act like quantum particles, with energy levels similar to an atom’s. Magnetic fields alter the energy levels of the defects. That means variations in the strength of the Earth’s magnetic field from place to place can be detected by measuring the light emitted when the diamond is hit with laser light and microwaves. “Earth’s magnetic field is actually very fascinating to measure, because it contains a lot of information,” says Hruby, of Hasselt University in Belgium. Motions within Earth’s molten outer core, the rocks in the crust, space weather and ocean tides all affect the magnetic field. Maps of the magnetic field can even be used to navigate, for example, when GPS is not available. The device’s performance didn’t yet beat out the most advanced conventional magnetometers. But a future mission will have upgraded

Buying D-Wave <b>Quantum</b> Stock? 3 Things You Should Know First.

Key Points D-Wave's sales can swing wildly quarter to quarter depending on whether a big hardware deal closes. The company is winning meaningful contracts but still reported a $355 million loss in 2025. Big share price swings and a hefty price tag mean D-Wave's shares aren't for the faint of heart. D-Wave Quantum(NYSE: QBTS) is one of the most popular quantum computing stocks, with a stunning 4,900% gain over the past three years. As one of only a handful of publicly traded quantum computing pure plays, D-Wave may seem like a sure-fire way to gain exposure to a market that McKinsey & Co. thinks could be worth $2.7 trillion by 2035. But there are three critical things investors should know before they buy D-Wave stock. Will AI create the world's first trillionaire? Our team just released a report on the one little-known company, called an "Indispensable Monopoly" providing the critical technology Nvidia and Intel both need. Continue » 1. D-Wave's business is inherently lumpy D-Wave specializes in selling quantum computers to its customers and quantum computing cloud services. The latter is a fairly consistent revenue stream, but when D-Wave sells a quantum computer to a big client, the revenue from that sale isn't as consistent as the cloud sales. For example, D-Wave had $15 million in sales in the first quarter of 2025 and a loss of $0.02 per share. Part of that revenue came from the company selling its first Advantage quantum computer system to a research center. Large sales like this are great when they happen, but they don't happen in every quarter. In Q1 2026, consensus estimates for D-Wave's sales are just $4.1 million, and the company is expected to post a loss of $0.08 per share. For most companies, that decline would be a big red

Intel, behind in AI chips, bets on <b>quantum</b> and neuromorphic processors | Network World

Intel is looking beyond the current AI hardware boom to what comes next. Intel for years chopped critical products including CPUs, GPUs and networking gear to cut corporate fat and get back into shape. Many cuts pre-date the appointment last year of Lip-Bu Tan as CEO. Now, Tan is placing a long-term bet beyond the current crop of AI chips and doubling down on quantum processors and neuromorphic chips, which survived Intel’s earlier product cuts. Tan has now tapped company veteran Pushkar Ranade to be Intel’s new chief technology officer, with a mission to drive developments in “quantum computing, neuromorphic computing, photonics, and novel materials,” the chipmaker announced this week. The move is a longer-term bet, according to Dylan Patel, CEO of semiconductor research firm SemiAnalysis. “It’s a bit further out stuff he is doing, so it wouldn’t help with the next two years of products,” he said, adding that Ranade is an excellent choice for Intel’s move into future computing models. Multiple analysts said Intel’s quantum group has been hindered by limited funding and resources and hurt by staff turnover. Former CEO Pat Gelsinger and CTO Greg Lavender departed the company last year. Quantum uncertainty There’s very little known about Intel’s quantum computing efforts. The company’s most recent quantum chip, Tunnel Falls, was announced back in 2023. But there’s leadership continuity, with quantum hardware leader James Clarke and quantum systems and software leader Anne Matsuura still at the company. “Maybe this means Lip-Bu wants to [reorient] Intel’s focus and investment in quantum computing,” said Jim McGregor, principal analyst at Tirias Research. Intel has a solid record of success with technology moonshots, and its neuromorphic chip development is the best in the business, said Ian Cutress, chief analyst at semiconductor consulting firm More Than Moore. “Intel’s [quantum] approach, since [former