IonQ has announced its financial results for the first quarter ended March 31, 2026, marking the largest quarter in the company’s history. The company reported triple-digit revenue growth and unveiled its 6th-generation chip-based architecture. The table below summarizes key GAAP financial metrics for Q1 2026 compared with the prior quarter (Q4 2025) and the year-ago quarter (Q1 2025). | Amounts in $M | Q1’2026 | Q4’2025 | Q1’2025 | % vs Q4’2025 | % vs Q1’2025 | | Revenue | $64.7 | $61.9 | $7.6 | +4.5% | +751.3% | | Operating Expenses | $336.2 | $290.5 | $83.2 | +15.7% | +304.1% | | Operating Loss | ($271.5) | ($228.6) | ($75.7) | +18.8% | +258.7% | | Net Income (Loss) | $805.4 | $753.7 | ($32.3) | +6.9% | +2,593.5% | | Cash and Investments | $3,100.0 | $3,300.0 | $697.1 | -6.1% | +344.7% | Financial and Strategic Overview IonQ delivered record GAAP revenue of $64.7 million, representing a staggering 755% increase year-over-year. The result exceeded the midpoint of the company’s guidance by 30%, driven by global system sales and strong commercial demand. Notably, 60% of revenue came from commercial customers, and one-third of total revenue was derived from multi-product sales spanning computing, networking, and sensing. The company reported GAAP Net Income of $805.4 million, which was primarily due to a $1.06 billion non-cash gain related to the change in fair value of warrant liabilities. On an adjusted basis, the company reported an Adjusted EPS of ($0.34). Backlog momentum reached a historic high, with Remaining Performance Obligations (RPOs) growing 554% year-on-year to $470 million. With a liquidity position of $3.1 billion, IonQ remains the best-capitalized player in the sector, providing ample runway to close its pending acquisition of SkyWater Technology (expected in Q2 or Q3 2026) and
May 7, 2026 · via quantumcomputingreport.com
Qubitcore raises $9.6M to advance ion-trap quantum computing With this latest round, the Japanese startup will accelerate R&D and commercialization of a quantum optical interconnect interface based on micro-optical cavities and a distributed ion-trap quantum computing architecture, building on research outcomes from OIST. Qubitcore, an ion-trap quantum computing startup spun out of Japan’s Okinawa Institute of Science and Technology (OIST), has announced that it has completed a JPY 1.53 billion (approximately USD 9.6 million) seed round through a third-party allotment of preferred shares. The round was led by SBI Investment, with participation from 12 investors. Participating investors include SBI Investment as lead investor, Abies Ventures, Nissay Capital, Lifetime Ventures, Dual Bridge Capital, Daiwa House Ventures, Yanmar Ventures, Mitsubishi UFJ Capital, Blue Lab, SMBC Venture Capital, Bank of the Ryukyus, and Canal Ventures, according to a media release. With this latest round, the company will accelerate the R&D and commercialization of a quantum optical interconnect interface based on micro-optical cavities and a distributed ion-trap quantum computing architecture, building on research outcomes from OIST. Qubitcore aims to develop fault-tolerant universal quantum computers, or FTQC, for computational challenges that are difficult for conventional computers, including drug discovery, materials and energy materials design, climate-related simulation, and high-speed, energy-efficient AI model training, the media release said. “We see this seed round as a strong vote of confidence from a diverse group of investors,” said Ryuta Watanuki, Founder & CEO of Qubitcore. “Together with the R&D team led by Co-Founder & CSO Hiroki Takahashi, we will accelerate research and development, business development, and hiring as we work to build a quantum computing company from Japan.” “It is deeply meaningful to see our research on ion-trap quantum optical interconnects at OIST evolve, through Qubitcore, into concrete initiatives toward an actual quantum computer system,” said Hiroki Takahashi, Co-Founder
May 7, 2026 · via evertiq.com
Revenue Exceeds Midpoint of Guidance Range by 30% - Reported Record GAAP Revenues of $64.7 Million, Representing 755% Year-On-Year Growth, Fueled by Quantum Computing Growth and Expansion of the Quantum Platform - Raises Full Year Guidance to be between $260 and $270 Million as Remaining Performance Obligations grow 554% year-on-year to $470 Million - Continued to Drive Commercial Momentum with Approximately 60% of Revenue from Commercial Customers, 35% of Revenue from International Customers, and 35% of Revenue from Multi-Product Customers - Sold IonQ’s First 6th-Generation, Chip-Based, 256-Qubit System, Anchored by a Secure Quantum Network and Broad IP-Generation Partnership Spanning Computing, Networking, Sensing, and Security. Demand for Fifth-Generation Tempo Remains Strong - Selected for DARPA’s HARQ Program, Reflecting IonQ’s Leadership in Modular Quantum Computing and Scalable Networking Architectures Using Quantum Interconnects - Published World’s First Definitive and Detailed Architectural Blueprint For Fault-Tolerant Quantum Computing, Setting a New Standard for Technical Specificity and Transparency COLLEGE PARK, Md.--(BUSINESS WIRE)-- IonQ (NYSE: IONQ), the world’s only full-stack quantum platform company, today announced financial results for the quarter ending March 31, 2026. “I am pleased to share that IonQ has begun 2026 with strong momentum, delivering our fourth consecutive quarter of record-breaking results and the biggest quarter in our company's history - thus far. With $64.7 million in revenue, we have once again significantly outperformed our guidance range, exceeding the midpoint by 30%,” said Niccolo de Masi, Chairman and CEO. “As a result, we are raising our revenue expectations for the full year to $270 million at the high end, based upon the strong and growing demand for our leading quantum computers, as well as the commercial impact of our entire quantum platform.” “Securing our first 256-qubit system sale and receiving our first ion trap chip samples back from the fab this quarter marks a
May 7, 2026 · via investors.ionq.com
Quantum algorithms for estimating Gibbs expectations now achieve a computational complexity of $\widetilde{\mathcal{O}}(ε^{-1})$ for estimating these expectations within a specified error margin, ε. This is a sharp improvement over classical multilevel Monte Carlo methods, which require $\widetilde{\mathcal{O}}(ε^{-2})$, and overcomes biases present in existing quantum approaches. The work provides a framework for unbiased quantum sampling and estimation, even for complex, heavy-tailed distributions. Xinmiao Li and Jin-Peng Liu from Tsinghua University have created a new quantum algorithm for statistical computation that improves upon both traditional and existing quantum techniques. This algorithm offers unbiased estimation, a key feature for accurate results, while reducing the computational effort required for complex calculations. The advance addresses limitations in quantum Monte Carlo methods, used to model probabilities, and broadens the scope of quantum computing to include challenging statistical problems. A new quantum algorithm improves the efficiency of statistical calculations, surpassing both classical and existing quantum methods, according to work by Xinmiao Li and Jin-Peng Liu at Tsinghua University. This advancement tackles a long-standing challenge in modelling probabilities, offering a way to calculate the average value of a quantity in a statistical system, with greater speed and accuracy. The new approach achieves a computational complexity scaling inversely with error, a substantial improvement over classical techniques which scale inversely with the square of the error. A key innovation lies in the algorithm’s ability to handle complex, ‘heavy-tailed’ distributions, and it employs a mathematical set of tools called Radon-Nikodym derivatives to refine its estimations. Unbiased Gibbs expectation estimation via optimised quantum complexity A quantum complexity of $\widetilde{\mathcal{O}}(ε^{-1})$ has been achieved for estimating Gibbs expectations, representing a marked improvement over the $\widetilde{\mathcal{O}}(ε^{-2})$ required by classical multilevel Monte Carlo methods. This breakthrough surpasses a critical threshold, enabling unbiased quantum sampling and estimation, unlike previous quantum algorithms that produced biased results or demanded
May 7, 2026 · via quantumzeitgeist.com
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May 6, 2026 · via facebook.com
Bitcoin’s post-quantum migration will be harder than Taproot and needs to start now, Project Eleven CEO says Alex Pruden said the asymmetry between acting on a post-quantum signature scheme today and waiting for certainty about quantum-computing hardware timelines means Bitcoin developers should move from research into production. What to know: - Project Eleven CEO Alex Pruden told CoinDesk’s Consensus Miami conference Wednesday that Bitcoin’s developer community should move from research into production on a post-quantum signature option rather than waiting for certainty about quantum-computer timelines. - He said the migration will be substantially harder than Taproot, which took roughly five years and remained opt-in, because every bitcoin user, wallet and exchange will need to participate in a post-quantum migration to stay secure. - Asked for his personal view, Pruden said recycling dormant quantum-vulnerable coins back into Bitcoin’s supply curve would put him “overall” on the confiscation side, though he stressed the community and market would ultimately decide. Bitcoin’s developer community should stop waiting for certainty about quantum-computing timelines and focus on getting a post-quantum signature scheme into production, Alex Pruden, CEO of Project Eleven, told CoinDesk’s Consensus Miami conference on Wednesday. Pruden said the asymmetry between acting now and waiting favors action. “We added some new cryptography, we kind of built in this optionality, it turns out we didn’t need quite yet, but at least we have it,” he said, describing the worst case of moving early. The worst case of moving late is far worse: a sufficiently capable quantum computer could derive private keys from any exposed public key using Shor’s algorithm, the 1994 algorithm that remains the canonical example of what a quantum machine can do that a classical one cannot. Pruden valued the asset at stake at roughly $2.3 trillion. “In a very real sense, someone with
May 6, 2026 · via coindesk.com
Drug resistance is a major biomedical challenge that undermines treatments for infectious diseases, cancer, and viral infections worldwide. Classical computational models fail to capture the full molecular complexity underlying these processes due to inherent approximations and computational constraints. Quantum models offer a computationally advanced framework, enabling more accurate simulation of molecular interactions and improved understanding of drug-target binding and resistance mechanisms. Image Credit: Saiful52/Shutterstock.com Why Is It Difficult to Model Drug Resistance? Drug resistance represents an adaptive biological response in which cells, pathogens, or organisms lose sensitivity to therapeutic agents that were previously effective, driven by evolutionary selection that favors survival of resistant variants under drug pressure. At the molecular level, this resistance arises through multiple mechanisms, including enzymatic drug inactivation, reduced intracellular accumulation via decreased uptake or active efflux, and structural modification of drug targets that lowers binding affinity while preserving biological function. Additional pathways include target overproduction, metabolic bypass mechanisms that circumvent inhibited steps, and target mimicry that sequesters drugs away from their intended binding sites. These mechanisms frequently act in combination, producing robust and multifactorial resistance phenotypes that reduce therapeutic efficacy and complicate long-term disease management across infectious diseases, oncology, and other biological systems.1,2 Limitations in Modeling Modeling drug resistance presents significant challenges due to the dynamic, heterogeneous, and multiscale nature of biological systems, combined with fundamental limitations of classical computational approaches. Biological populations evolve continuously under therapeutic pressure, while rare mutations in a small subset of cells can rapidly dominate a population. This dynamic adaptive behavior introduces significant stochasticity, making resistance trajectories difficult to predict using deterministic models alone. Limitations in experimental data, particularly the absence of real-time, patient-specific measurements, further reduce model reliability, making drug resistance modeling a problem that requires integrating evolutionary biology, multiscale modeling, and quantum-level accuracy.3,4 What Can Quantum Models do Against
May 6, 2026 · via azoquantum.com
Key Points Nvidia is building a quantum computing infrastructure layer to support the development of the technology. IonQ is emerging as a key hardware partner within Nvidia’s growing quantum computing ecosystem. Nvidia’s hybrid quantum-AI approach could accelerate real-world adoption of IonQ's systems. Artificial intelligence (AI) has dominated the attention of U.S. equity markets since 2023. However, quantum computing is emerging as a potential trend on Wall Street. 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 » In April, Nvidia(NASDAQ: NVDA) expanded its quantum computing footprint with the launch of the Ising AI model family, designed to improve how quantum computers are calibrated and how they correct their errors. Because the qubits at the heart of any quantum computer are so delicate and sensitive, they can be interfered with by even tiny external forces. The result of such interference: errors in the results of the calculations. Reducing those high error rates and finding effective ways to correct those that do occur are among the biggest challenges in quantum computing. And in that context, incremental improvements could significantly increase real-world adoption of this technology. Nvidia asserts that its Ising models perform their error-correcting processes about 3 times more accurately than traditional open-source tools, and up to 2.5 times faster. CEO Jensen Huang has highlighted Nvidia's strategy of focusing on building a software and infrastructure stack to support quantum computing use cases, rather than building quantum computers or hardware itself. Here's how IonQ(NYSE: IONQ) stands to benefit from Nvidia's advances in quantum computing. IonQ's growth strategy IonQ is building quantum computing hardware using trapped-ion qubits, an approach to the technology that is known for its better precision and stability.
May 6, 2026 · via theglobeandmail.com
IonQ Announces First Quarter 2026 Financial Results Revenue Exceeds Midpoint of Guidance Range by 30% - Reported Record GAAP Revenues of $64.7 Million, Representing 755% Year-On-Year Growth, Fueled by Quantum Computing Growth and Expansion of the Quantum Platform - Raises Full Year Guidance to be between $260 and $270 Million as Remaining Performance Obligations grow 554% year-on-year to $470 Million - Continued to Drive Commercial Momentum with Approximately 60% of Revenue from Commercial Customers, 35% of Revenue from International Customers, and 35% of Revenue from Multi-Product Customers - Sold IonQ’s First 6th-Generation, Chip-Based, 256-Qubit System, Anchored by a Secure Quantum Network and Broad IP-Generation Partnership Spanning Computing, Networking, Sensing, and Security. Demand for Fifth-Generation Tempo Remains Strong - Selected for DARPA’s HARQ Program, Reflecting IonQ’s Leadership in Modular Quantum Computing and Scalable Networking Architectures Using Quantum Interconnects - Published World’s First Definitive and Detailed Architectural Blueprint For Fault-Tolerant Quantum Computing, Setting a New Standard for Technical Specificity and Transparency COLLEGE PARK, Md.--(BUSINESS WIRE)-- IonQ (NYSE: IONQ), the world’s only full-stack quantum platform company, today announced financial results for the quarter ending March 31, 2026. “I am pleased to share that IonQ has begun 2026 with strong momentum, delivering our fourth consecutive quarter of record-breaking results and the biggest quarter in our company's history - thus far. With $64.7 million in revenue, we have once again significantly outperformed our guidance range, exceeding the midpoint by 30%,” said Niccolo de Masi, Chairman and CEO. “As a result, we are raising our revenue expectations for the full year to $270 million at the high end, based upon the strong and growing demand for our leading quantum computers, as well as the commercial impact of our entire quantum platform.” “Securing our first 256-qubit system sale and receiving our first ion trap chip samples back
May 6, 2026 · via ionq.com
IonQ delivers huge Q1 sales beat, hikes full-year revenue guidance
Trapped-ion quantum computing company IonQ just posted a very impressive set of Q1 sales, sending shares higher in postmarket trading.
In Q1, the largest quantum computing company by market cap and sales reported:
Revenue of $64.7 million (compared to analyst estimates of $49.7 million and guidance for $48 million to $51 million).
An adjusted loss per share of $0.34 (estimate: a $0.24 loss).
Management expects Q2 sales between $65 million and $68 million (estimate: $54.9 million), and raised its full-year sales guidance by $25 million to a range of $260 million to $270 million.
The quantum computing space has gotten its mojo back as of late as speculative appetite returned in April after the US and Iran agreed to a ceasefire, with the cohort later turbocharged after Nvidia unveiled a suite of open models designed to leverage AI to improve calibration and error correction for quantum computers.
May 6, 2026 · via sherwood.news
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May 6, 2026 · via youtube.com
Catalyst Professorship fosters collaboration with the private sector New part-time role allows leading faculty to pursue industry employment alongside academic work Seeking to enhance relationships between academia and industry, the Office of the Provost in 2024 introduced the Catalyst Professorship: a distinguished senior faculty role aimed at fostering collaboration with the private sector. Three prominent Harvard faculty have now been appointed Catalyst Professors: Doug Melton, a stem cell scientist; Boaz Barak, a theoretical computer physicist; and Michael Brenner, a scholar of applied mathematics. “The Catalyst Professorships offer an important new approach to supporting academic excellence,” said President Alan M. Garber. “They acknowledge the ambitions of outstanding faculty who seek to drive progress across many fronts as they contribute to the fulfillment of our mission. Doug, Boaz, and Michael are distinguished teachers and researchers who have long inspired Harvard students and scientists. I am eager to see what they achieve in their new roles.” “The Catalyst Professorship provides a terrific, innovative model for making our research ecosystem more porous and collaborative,” said provost John F. Manning. “The three distinguished inaugural professors provide an extraordinary proof of concept.” “As the first opportunity of its kind at Harvard, the Catalyst Professorship offers a unique arrangement for exceptionally distinguished faculty to engage in external opportunities while maintaining their teaching commitments and contributions to Harvard’s academic mission,” said Judy Singer, senior vice provost for faculty. The professorship is open to individuals of the highest academic distinction who have demonstrated excellence, experience, and integrity as researchers, teachers, mentors, and University contributors. It is open to all disciplines, including emerging areas such as artificial intelligence, biotechnology, renewable energy, and quantum technologies, where alliances between academia and industry are especially critical for advancing research and addressing global challenges. Catalyst Professors will not only further scientific exploration but also
May 6, 2026 · via news.harvard.edu
Abstract The scalability and power of quantum computing architectures depend critically on high-fidelity operations and robust and flexible qubit connectivity1,2,3. In this respect, mobile qubits are particularly attractive as they enable dynamic and reconfigurable qubit arrays. This approach allows quantum processors to adapt their connectivity patterns during operation, implement different quantum error correction codes on the same hardware and optimize resource use through dedicated functional zones for specific operations such as measurement or entanglement generation4,5,6,7. Such flexibility also relieves architectural constraints, as recently demonstrated in atomic systems based on trapped ions4,5 and neutral atoms manipulated with optical tweezers6,7. In solid-state platforms, highly coherent shuttling of electron spins was recently reported8,9. A key outstanding question is whether it may be possible to perform quantum gates directly on the mobile spins. Here we demonstrate two-qubit operations between two electron spins carried towards each other in separate travelling potential minima in a semiconductor device. We find that the interaction strength is highly tunable by their spatial separation. When we shuttle the two spins towards the centre by 120 nm each for a total displacement of 240 nm, we achieve an average two-qubit gate fidelity of about 99%. Furthermore, we implement conditional post-selected quantum state teleportation between qubits separated by 320 nm with an average gate fidelity of 87%, showcasing the potential of mobile spin qubits for non-local quantum information processing. We expect that operations on mobile qubits will become a universal feature of future large-scale semiconductor quantum processors. Similar content being viewed by others Main Quantum computing offers the promise to solve complex problems that are intractable for classical computers. As quantum processors scale up, maintaining high connectivity between qubits becomes crucial for implementing effective error correction schemes1,2,3. However, traditional architectures are often restricted to interactions between nearest neighbours, constraining the options for
May 6, 2026 · via nature.com
How a Convening at UC San Diego Could Help Shape California’s Quantum Future Published Date Article Content Key Takeaways - California is shaping its quantum future. The San Diego convening will gather leaders from industry, academia and government to inform the state’s strategy. - Quantum computing could unlock powerful new tools. Promising uses include designing materials, preparing cybersecurity for quantum-era risks and improving complex logistics. - A major challenge is scaling by design. Quantum computers need to become larger and more reliable, with hardware and algorithms developed together. The University of California San Diego Qualcomm Institute (QI) will host an invitation-only Quantum San Diego Convening on May 18–19, bringing together approximately 200 leaders from industry, academia, national laboratories and government to help the state shape its future in quantum. Here, QI Research Specialist Riley Need, one of the event organizers, discusses the gathering and its goals in the context of the rapidly developing field. (This interview is edited for length and clarity.) Qualcomm Institute: What is the backstory of this event? Riley Need: Late last year, California Governor Gavin Newsom announced the statewide Quantum California initiative, a public-private initiative meant to solidify California as a global leader in quantum computing, sensing, networking and materials. Related state legislation (AB 940) instructed the California Governor’s Office of Business and Economic Development (GO-Biz) to put together a strategic framework to help policy makers understand the California quantum ecosystem: What are our strengths? What are our weaknesses? What are our opportunities? What should state legislators focus on in terms of funding or legislation that will help the state not only be part of the quantum revolution, but a leader nationally and globally? A convening was held at UC Berkeley to kick off Quantum California and have discussions that would contribute to this report. The
May 6, 2026 · via today.ucsd.edu
Cleveland Clinic, RIKEN, and IBM Model a 12,635-Atom Protein – the Largest Known to Be Simulated with Quantum Computers Milestone simulation of biologically meaningful molecules expands quantum-centric supercomputing’s role as a scientific tool YORKTOWN HEIGHTS, N.Y. and CLEVELAND, May 5, 2026 /PRNewswire/ — Scientists at Cleveland Clinic, RIKEN, and IBM (NYSE: IBM) have used IBM quantum computers and two of the world’s most powerful supercomputers to simulate protein complexes spanning up to 12,635 atoms. These are the largest-known simulations of biologically meaningful molecules performed with quantum hardware yet, and signal that quantum computers are maturing into useful scientific tools which can help solve fundamental problems in biology, chemistry, and life sciences. Researchers at IBM, Cleveland Clinic, and RIKEN used quantum-centric supercomputing to model the protein trypsin, a 12,635-atom protein and the largest known to be simulated with quantum computers. (Credit: IBM, Cleveland Clinic, and RIKEN) The results were achieved in part by an innovative algorithm that optimizes how quantum and classical computers can work together, a framework known as quantum-centric supercomputing. Using this approach, the team captured the behavior of two biochemically relevant proteins that are roughly 40 times larger than what this same method could initially achieve just six months ago. Additionally, the accuracy of the simulations in a key step of the workflow improved by up to 210 times over this same period. The decision to explore if quantum computers could offer value in the simulation of protein complexes was motivated by challenges faced today by researchers when studying how a drug candidate could bind to a protein. This can be one of the most difficult and expensive problems in life sciences research, and one that today’s existing computational methods have struggled to exactly solve as molecules increase in size. Doing so accurately and early in the discovery
May 5, 2026 · via technode.global
Morgan Stanley raised its price target on IonQ (NYSE:IONQ | IONQ Price Prediction) to $47 from $37, while keeping an Equal Weight rating. The call arrived as part of a preview note covering another week of earnings from the semiconductors and quantum group on Monday, May 4. The price target raised signals growing Wall Street confidence in IonQ’s commercial trajectory, even as Morgan Stanley stays neutral on near-term valuation. For prudent investors, the revised IonQ stock outlook lands just two days before the Q1 2026 results. | Ticker | Company | Firm | Action | Old Rating | New Rating | Old Target | New Target | |---|---|---|---|---|---|---|---| | IONQ | IonQ | Morgan Stanley | Price Target Raised | Equal Weight | Equal Weight | $37 | $47 | The Analyst’s Case The Equal Weight stance reflects a balanced read on IonQ stock: bullish on the long-term quantum opportunity, neutral on the current valuation. The new $47 target sits well below the broader analyst consensus of $64.56, suggesting a more conservative posture even after the upward revision. Morgan Stanley’s preview frames quantum computing as a category transitioning from research into early commercial deployments. IonQ sits at the center of that shift, with hyperscaler technology partnerships and government customers that have repeatedly re-rated the shares higher with each design win. Company Snapshot IonQ is the first public quantum computing company to exceed $100M in annual GAAP revenue. Q4 2025 revenue hit $61.89M, up 429% year over year (YoY), beating consensus of $40.26M. Full-year 2025 revenue reached $130.02M, up 202% YoY. IonQ CEO Niccolo de Masi guided for FY2026 revenue of $225M to $245M, alongside an adjusted EBITDA loss of ($330M) to ($310M). Strategic milestones for IonQ include a pending SkyWater Technology acquisition, an expanded QuantumBasel contract exceeding $60M over four
May 5, 2026 · via 247wallst.com
Scientists just created exotic new forms of matter that shouldnât exist - Date: - May 4, 2026 - Source: - California Polytechnic State University - Summary: - A new quantum physics study reveals that simply changing a magnetic field over time can unlock entirely new forms of matter that donât exist under normal conditions. By carefully âdrivingâ materials with timed magnetic shifts, researchers created exotic quantum states that could be far more stable and resistant to errorsâone of the biggest challenges in quantum computing. This breakthrough suggests that the future of quantum technology may depend not just on what materials are made of, but how theyâre manipulated in time. - Share: Quantum technology is widely expected to transform how large and complex data sets are processed. Although it is currently used mostly in laboratories and research environments, the field is steadily moving toward real-world applications across a range of industries. In a recent study exploring the fundamentals of quantum physics, researchers examined how matter behaves at extremely small scales, including atoms, electrons, and photons. The work, led by Cal Poly Physics Department Lecturer Ian Powell, focused on how varying a magnetic field over time can cause matter to exhibit unusual and previously unseen properties. Powell and student researcher Louis Buchalter, who earned a Cal Poly bachelor's degree in physics in 2025, published their findings in Physical Review B in a paper titled "Flux-Switching Floquet Engineering." Their research shows that when magnetic fields are changed in a controlled, time-dependent way, they can generate quantum states that do not exist in materials that remain unchanged over time (remaining in the same state as time elapses). "On a big-picture level, I would describe this as an advance in our understanding of how time-dependent control can create and organize new forms of quantum matter,"
May 5, 2026 · via sciencedaily.com
One of the most promising uses for quantum computers is to simulate proteins that could help us discover new drugs, but these devices are currently too error-prone for the task. However, two quantum computers have now broken a simulation record – determining the properties of a molecule with 12,635 atoms – with some help from supercomputers. To understand the behaviour of drug molecules, we need to pin down the quantum states and energies of their electrons, which is a quantum problem that can often be solved only approximately on conventional computers. Advertisement A collaboration between researchers at the Cleveland Clinic in Ohio, the US tech firm IBM and the Japanese scientific institute RIKEN has instead turned to quantum computers, which “speak” quantum physics by default. They developed a hybrid approach that combines quantum computers and conventional supercomputers and used it to simulate two unprecedentedly large molecules, with one about 40 times bigger than the past largest molecule simulated using a quantum computer. “This has been a dream of mine, and here we are,” says team member Kenneth Merz at the Cleveland Clinic. The researchers used two IBM Heron quantum computers, one located at RIKEN and one at the Cleveland Clinic, and two supercomputers called Fugaku and Miyabi-G, which are among the most powerful in the world. For the molecules, the team chose two combinations of a protein and a small molecule, or “protein-ligand complexes”, that Merz says are well studied and popular as fundamental examples in biomedical sciences. The team also simulated them in a layer of water, bringing the results closer to mimicking how researchers work with the molecules in the lab. Free newsletter Sign up to The Daily The latest on what’s new in science and why it matters each day. Quantum computers alone currently have limited usefulness
May 5, 2026 · via newscientist.com
Milestone simulation of biologically meaningful molecules expands quantum-centric supercomputing's role as a scientific tool YORKTOWN HEIGHTS, N.Y. and CLEVELAND, May 5, 2026 /PRNewswire/ -- Scientists at Cleveland Clinic, RIKEN, and IBM (NYSE: IBM) have used IBM quantum computers and two of the world's most powerful supercomputers to simulate protein complexes spanning up to 12,635 atoms. These are the largest-known simulations of biologically meaningful molecules performed with quantum hardware yet, and signal that quantum computers are maturing into useful scientific tools which can help solve fundamental problems in biology, chemistry, and life sciences. The results were achieved in part by an innovative algorithm that optimizes how quantum and classical computers can work together, a framework known as quantum-centric supercomputing. Using this approach, the team captured the behavior of two biochemically relevant proteins that are roughly 40 times larger than what this same method could initially achieve just six months ago. Additionally, the accuracy of the simulations in a key step of the workflow improved by up to 210 times over this same period. The decision to explore if quantum computers could offer value in the simulation of protein complexes was motivated by challenges faced today by researchers when studying how a drug candidate could bind to a protein. This can be one of the most difficult and expensive problems in life sciences research, and one that today's existing computational methods have struggled to exactly solve as molecules increase in size. Doing so accurately and early in the discovery process could meaningfully shorten drug development timelines that currently can stretch over a decade and require substantial investment to produce a single medicine. "This work marks an important advance and underscores quantum computing's emerging role on systems of relevance to drug discovery," said Kenneth Merz, Ph.D., lead author of the study and staff
May 5, 2026 · via prnewswire.com
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May 5, 2026 · via youtube.com