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quantum-computingIonQ vs. Rigetti: Which Quantum Computing Stock Is a Better Buy in 2026?
The quantum computing race is accelerating as firms move from theoretical models to functional hardware. Is IonQ (IONQ +1.87%) or Rigetti Computing (RGTI +0.61%) the better buy for your portfolio in 2026?Both companies represent a high-stakes bet on the future of high-performance computing. IonQ focuses on trapped-ion technology to build its systems, while Rigetti specializes in superconducting processors. This comparison evaluates their financial health, strategic growth, and unique risks to help you decide which stock is a more compelling opportunity today.CollapseRGTI & IONQ: Performance ComparisonKey Financial MetricsRGTI – Rigetti Computing$14.95+0.61% (+$0.09)IONQ – IonQ$36.44+1.87% (+$0.67)Market Cap$5.0B52wk Range$12.53 - $58.15Gross Margin-5945.49%P/E Ratio-17.23EPS (TTM)$-0.87Market Cap$14B52wk Range$25.89 - $84.64Gross Margin-2879.52%P/E Ratio-212.85EPS (TTM)$-0.17RGTI – Rigetti Computing$14.95+0.61% (+$0.09)Market Cap$5.0B52wk Range$12.53 - $58.15Gross Margin-5945.49%P/E Ratio-17.23EPS (TTM)$-0.87IONQ – IonQ$36.44+1.87% (+$0.67)Market Cap$14B52wk Range$25.89 - $84.64Gross Margin-2879.52%P/E Ratio-212.85EPS (TTM)$-0.17The case for IonQIonQ develops trapped-ion quantum computers and offers cloud access to government, enterprise, and research customers. The company recently completed the acquisition of SkyWater Technology, establishing a domestic semiconductor foundry to bolster its infrastructure. Customer concentration like this adds a layer of risk to the business, as revenue heavily depends on a few government entities and cloud partnerships.In FY 2025, revenue reached nearly $130.0 million, which was a 201.9% increase from the roughly $43.1 million reported in FY 2024. Despite this top-line surge, the company reported a net loss of approximately $510.4 million. The net margin was roughly -392.6%, which measures what percentage of each dollar earned as revenue remains after accounting for all expenses.As of its December 2025 balance sheet, the debt-
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quantum-computingQuantum Computing Weekly Round-Up: Week Ending August 1, 2026
Quantum Computing Weekly Round-Up for the week ending August 1, 2026 delivered hard proof that quantum signals can share live commercial fiber, silicon processors can run their own error correction, and real capital plus telco deals are turning roadmaps into working infrastructure. Northwestern pushed entangled photons 15 miles through Chicago traffic at 94 percent fidelity. ZuriQ raised $25.5 million for its 2D trapped-ion architecture while HRL showed an 18-qubit silicon chip controlling itself inside the cryostat. AT&T expanded its D-Wave footprint and post-quantum authentication reached origin servers. Readers who skip the links will feel the FOMO. The post Quantum Computing Weekly Round-Up: Week Ending August 1, 2026 appeared first on The Qubit Report.
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quantum-computingIonQ vs. D-Wave Quantum: Which Quantum Computing Stock Is a Better Buy in 2026?
The quantum computing race is intensifying as companies transition from laboratory experiments to commercial applications. Choosing between IonQ (IONQ +1.87%) and D-Wave Quantum (QBTS +0.56%) requires you to decide which specialized hardware approach will win.IonQ focuses on trapped-ion technology to build scalable quantum systems for enterprise use. D-Wave specializes in quantum annealing, a different method optimized for solving complex business calculations. Both companies are high-risk investments that aim to revolutionize computing as we know it today.The case for IonQIonQ utilizes trapped-ion technology to develop quantum platforms for diverse fields like drug discovery and financial modeling. The company is a notable player among quantum computing stocks that focus on specialized hardware. It maintains commercial agreements with the likes of Amazon for its cloud-based offerings. Following its July 2026 acquisition of SkyWater Technology, the company now operates its own domestic foundry to serve a broader range of customers.In its 2025 fiscal year (FY), revenue reached $130.0 million, representing a year-over-year increase of 201.9%. The company reported a net loss of $510.4 million for the same period. This resulted in a net margin of -392.6%, which measures the total loss generated for every dollar of revenue.As of its December 2025 balance sheet, IonQ reported a debt-to-equity ratio of zero. This ratio shows total debt relative to shareholder equity, indicating the company has no traditional debt on its books. The current ratio of 15.5x is high, indicating the company has ample assets to cover short-term bills, though it generated a negative free cash flow of $299.6 million. Free cash flow is the cash a business generates after paying for its operations and equipment.The case for D-Wave QuantumD-Wave Quantum focuses on quantum annealing systems designed to solve complex optimization problems for more than 100 organizations. Its customer list includes globa
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quantum-computingBigBear.ai vs. D-Wave Quantum: Which Technology Stock Is a Better Buy in 2026?
Investors seeking exposure to cutting-edge computing technologies often weigh the merits of artificial intelligence against quantum breakthroughs. Choosing between BigBear.ai (BBAI -1.41%) and D-Wave Quantum (QBTS +0.56%) requires balancing government-focused growth with commercial innovation.BigBear.ai specializes in decision intelligence for defense and logistics, while D-Wave Quantum provides cloud-based quantum computing services. While both companies operate in the high-stakes world of advanced technology, their paths to profitability and market niches differ significantly. This comparison examines their financials, risks, and valuations to help you decide which stock fits your strategy.CollapseBBAI & QBTS: Performance ComparisonKey Financial MetricsBBAI – BigBear.ai$2.79–1.41% (-$0.04)QBTS – D-Wave Quantum$18.08+0.56% (+$0.10)Market Cap$1.3B52wk Range$2.59 - $9.39Gross Margin27.92%P/E Ratio-12.80EPS (TTM)$-0.22Market Cap$6.7B52wk Range$12.75 - $46.75Gross Margin32.92%P/E Ratio-15.96EPS (TTM)$-1.13BBAI – BigBear.ai$2.79–1.41% (-$0.04)Market Cap$1.3B52wk Range$2.59 - $9.39Gross Margin27.92%P/E Ratio-12.80EPS (TTM)$-0.22QBTS – D-Wave Quantum$18.08+0.56% (+$0.10)Market Cap$6.7B52wk Range$12.75 - $46.75Gross Margin32.92%P/E Ratio-15.96EPS (TTM)$-1.13The case for BigBear.aiBigBear.ai is a prominent name among tech stocks that provide decision intelligence solutions for supply chains and autonomous systems. The company serves the U.S. Intelligence Community and the Department of Defense alongside commercial manufacturing clients. Customer concentration like this adds a layer of risk to the business, as a few large contracts account for over half of total revenue.In FY 2025, revenue reached nearly $127.7 million, representing a decline of approximately 19.3% compared to the previous year. The company reported a net loss of roughly $293.9 million for the period, which resulted in a net margin of nearly 230.2%. Net margin measures how much of every dollar in revenue
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quantum-computingBlueQubit, IBM, and RIKEN Demonstrate Quantum R&D Potential
BlueQubit, alongside Qedma, IBM, and RIKEN, reports demonstrating a performance advantage for quantum computing by successfully predicting complex material behaviors where classical simulations failed. RIKEN expended over 500,000 CPU-core hours on the Fugaku supercomputer attempting to model sub-atomic oscillations, a task ultimately achieved with an error-mitigated quantum processor. This achievement suggests that practical quantum applications may arrive sooner than the previously expected timeframe of five to ten years, indicating that a quantum advantage is attainable now. “Proving true quantum advantage requires rigorous verification against the uppermost limits of classical computing,” said Hayk Tepanyan, BlueQubit co-founder and CTO. Floquet Ising Magnet Simulations Demonstrate Quantum Advantage Floquet Ising magnet simulations have revealed a demonstrable performance advantage for quantum computing, challenging expectations of a five-to-ten year timeline before practical applications emerge. Researchers from BlueQubit, Qedma, IBM, and RIKEN successfully predicted the behavior of these complex materials using error-mitigated quantum processors, a feat unattainable with current classical supercomputers. The study focused on the sub-atomic oscillations within Floquet Ising magnets, materials crucial for developing technologies such as room-temperature superconductors and improved electric vehicle batteries. These materials rely on a “prethermal” barrier to maintain stable oscillations, a property proving difficult to model accurately with classical methods. Despite these substantial efforts, classical approaches failed to consistently and reliably predict the material’s behavior. Qedma then deployed its QESEM error-mitigation software on IBM’s 156-qubit Heron processor, and independently validated the results using trapped-ion systems from Quantinuum, achieving percent-level accuracy without requiring millions of qubits or full error correction. This success hi
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quantum-computingQuantum Computing Stocks To Keep An Eye On - August 1st - MarketBeat
Quantum Computing Stocks To Keep An Eye On - August 1st Written by MarketBeatAugust 1, 2026 ShareLink copied to clipboard. Image from MarketBeat Media, LLC. Key Points IonQ, D-Wave Quantum, Quantum Computing Inc., Quantinuum, and Horizon Quantum Computing are highlighted as quantum-computing stocks drawing significant recent trading interest. The companies span quantum-computing systems, cloud access, software, photonics, cybersecurity, sensing, and related technologies, reflecting the sector’s movement from research toward early commercial adoption. Investors should note the industry’s high volatility, uncertain profitability, and substantial technological risk, despite its long-term growth potential driven partly by rising demand for computing power from applications such as artificial intelligence. MarketBeat previews the top five stocks to own by September 1st. Quantum Earnings Could Decide Whether the Sector’s Sell-Off Has Gone Too FarIonQ, D-Wave Quantum, Quantum Computing, Quantinuum, and Horizon Quantum Computing Pte. are the seven Quantum Computing stocks to watch today, according to MarketBeat's stock screener tool. Quantum computing stocks are shares of publicly traded companies involved in developing quantum computers, quantum software, related hardware, or supporting technologies. For investors, these stocks represent exposure to a developing industry with potentially significant long-term growth, but they may also carry high volatility, uncertain profitability, and substantial technological risk. These companies had the highest dollar trading volume of any Quantum Computing stocks within the last several days. Get IonQ alerts:Sign UpIonQ (IONQ)IonQ, Inc. engages in the development of general-purpose quantum computing systems in the United States. It sells access to quantum computers of various qubit capacities. The company makes access to its quantum computers through cloud platforms, such as Amazon Web Services (AWS) Amazon Braket, Microsoft's Azure Q
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quantum-computingINQA 2026 conference
INQA 2026 conference Dates: Monday, November 2, 2026 to Wednesday, November 4, 2026Web page: INQA 2026Registration deadline: Friday, September 25, 2026Submission deadline: Tuesday, September 8, 2026Tags: quantum computinganalog quantum computingquantum simulationadiabatic quantum computingquantum optimizationquantum annealingquantum computation in continuous TimeINQA Conference 2026 | International Network on Quantum Annealing | Quantum Simulation and Quantum Computation in Continuous Time Abstract submission deadline (oral & poster) September 8, 2026 Registration deadline September 25, 2026 ABOUT THE CONFERENCE Analog Quantum Computation: From Annealing to Simulation Quantum annealing is a method of quantum computation for solving combinatorial optimisation problems operating in continuous time, a feature that is shared with various methods of analog quantum simulation. The International Network on Quantum Annealing (INQA) 2026 conference aims to bring together leading experts in analog quantum computation and simulation to share and discuss their latest results. Theoretical, numerical and experimental works are welcome, as well as contributions within the theme from related fields. This year’s conference of INQA will be held in Bled, Slovenia, from November 2 – 4, 2026. This is the 5th instalment of this conference series, which previously took place in London (2022), Innsbruck (2023), Tokyo (2024) and Barcelona (2025). Log in or register to post comments
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quantum-computingNSF Awards UC San Diego $18 Million MRSEC Grant for Quantum Materials Development in $108 Million National Materials Initiative
NSF Awards UC San Diego $18 Million MRSEC Grant for Quantum Materials Development in $108 Million National Materials Initiative The U.S. National Science Foundation (NSF) has awarded the University of California San Diego (UC San Diego) an $18 million, six-year grant (NSF Award #2614051) to fund a Materials Research Science and Engineering Center (MRSEC) dedicated to developing advanced quantum materials. The award is part of a broader $108 million NSF deployment funding six national MRSEC research centers across the United States—including Princeton University, Harvard University, Columbia University, MIT, and the University of Nebraska–Lincoln—to advance frontier research in quantum metamaterials, soft matter, and microelectronics. At UC San Diego, the 2026–2032 grant represents a competitive renewal of the campus’s initial 2020 MRSEC award, pivoting the center’s core mission from bio-materials and polymer chemistry to fundamental quantum technology hardware. Jointly led by the Jacobs School of Engineering and the School of Physical Sciences—alongside regional collaborators at UC Irvine, UCLA, and UC Santa Barbara—the center structures its experimental and computational research around two primary thrusts: [ UC San Diego MRSEC Hardware Thrusts ] │ ┌──────────────────────────────────────┴──────────────────────────────────────┐ ▼ ▼ Thrust 1: Quantum Metamaterials Thrust 2: Chemically Tailored 2D Superlattices • Bottom-up nanoscale optical self-assembly. • Atomically thin sheet-like structures. • Hybrid light-matter interaction & ultrafast conversion. • Order-imposed electron transport control. • Direct all-optical & quantum computing platforms. • Topological insulators, superconductors, & 2D logic. Thrust 1: Quantum Metamaterials for All-Optical Processing Co-led by Electrical and Computer Engineering Professor Zhaowei Liu and Physics Professor Richard Averitt, the Quantum Metamaterials group focuses on nanometer-scale engineered structures that move bey
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quantum-computingGil Kalai (Hebrew University / Reichman University): Why noise may doom quantum computers - The Quantum Insider
Yuval Boger interviews mathematician Gil Kalai about his long-standing skepticism regarding scalable quantum computing. Kalai explains two main arguments behind his theory: correlated noise that may defeat quantum error correction and complexity-based limits on NISQ devices achieving quantum supremacy. They discuss experimental claims such as Google’s 2019 result, potential tests of Kalai’s conjectures, and the implications for the future of quantum research. The conversation also explores how Kalai hopes the community will evaluate bold claims and what scientific insights could emerge if quantum computing ultimately fails.
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quantum-computingNIST Finalizes Three Post-Quantum Encryption Standards for Secure Data
Sufficiently powerful quantum computers could expose personal information, financial transactions, and business and government secrets. NIST researcher Andrew Regenscheid is working to address this emerging threat, as today’s cryptography, mathematical problems acting as a “lock” to protect data, becomes increasingly vulnerable. The risk is that someone may develop a quantum computer that can reveal sensitive information sent online, Regenscheid explains, emphasizing the urgent need to update encryption and secure computers, information, and internet traffic with post-quantum cryptography. Cryptography Vulnerability from Quantum Computers Present-day cryptography relies on mathematical problems so complex that conventional computers struggle to solve them, effectively “locking” sensitive data from unauthorized access. However, the emergence of quantum computing introduces a shift, potentially rendering these established cryptographic methods obsolete. NIST researcher Andrew Regenscheid is proactively addressing this risk. The core challenge lies in the unique capabilities of quantum computers, which leverage principles of quantum mechanics to perform calculations beyond the reach of classical machines. Regenscheid explains that “computers we have now can’t easily do those math problems to break the encrypted algorithms, but in the future, quantum computers will likely be able to crack these codes.” This potential necessitates a move towards post-quantum cryptography (PQC), a new generation of encryption designed to withstand attacks from quantum computers. The goal, according to the National Institute of Standards and Technology, is to create mathematical problems so challenging that even a quantum computer cannot solve them. This urgency stems not only from progress in quantum computing but also from a tactic known as “harvest now, decrypt later.” An adversary doesn’t require a functioning quantum computer to begin compromising data; they can intercept and store en
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quantum-computingWhere Will IonQ Be in 1 Year?
IonQ (IONQ +0.98%) just received final regulatory approval for one of its most important deals to date: the acquisition of SkyWater Technology. SkyWater is the largest exclusively U.S.-based semiconductor foundry and is recognized by the Department of Defense as a trusted foundry. The deal gives IonQ full control of its supply chain. It now has a factory to manufacture its chips, eliminating the need to rely on outside suppliers. In light of this acquisition, it's a good time to consider where IonQ will be in a year. Image source: The Motley Fool. The numbers are trending up Financially, IonQ stands out among pure-play quantum computing companies. Revenue growth is accelerating, as IonQ reported sales of $64.7 million in the first quarter of 2026, a year-over-year increase of 755%. Its remaining performance obligations, meaning future contracted revenue not yet recorded on an income statement, hit a record $470 million. The results were good enough for IonQ to raise full-year revenue guidance to between $260 million and $270 million. That's a stark difference from IonQ's main competitors: D-Wave Quantum, Rigetti Computing, and Quantum Computing. They all had revenue of less than $5 million in their most recent reported quarters. Multiple companies are dedicated to quantum computing systems, but only IonQ has achieved commercial success to date. IonQ also has a solid balance sheet, with $3.1 billion in cash, cash equivalents, and investments. With plenty of cash reserves, substantial revenue growth, and now a major acquisition, IonQ has a strong bull case over the next year. The risk could impact IonQ's upside While there's a lot to like about IonQ, it's still a high-risk investment. It's burning cash: Operating cash flow was negative $151 million in the first quarter, and management is guiding for a full-year adjusted EBITDA loss of $310 million to $330 million. The cash reserves give it a long runway, but this is a company that has had to spend heavily to keep scal
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quantum-computingFlow-Based Modeling Reconstructs Quantum States From Fewer Measurements
Researchers at the Massachusetts Institute of Technology, Stanford University, Tufts University, the University of California, Los Angeles, and Tsinghua University have developed QST-Flow, a new quantum state tomography framework that moves beyond traditional methods of modeling quantum information. QST-Flow represents data using “normalized, samplable neural densities” instead of a truncated density matrix, enabling more efficient processing of complex quantum states. The framework features two variants, QST-QFlow and QST-WFlow, which model the positive Husimi function and sign-changing Wigner functions, respectively, as trainable densities. This construction preserves quasiprobability normalization and enables exact density evaluation and direct sampling, along with importance-sampled learning from finite phase-space measurements without a fixed grid. Benchmarks using states like cat, binomial, and Gottesman-Kitaev-Preskill states demonstrate that QST-WFlow achieves improved reconstruction error compared with QST-CGAN, suggesting a quantifiable advancement in scalable, measurement-efficient phase-space tomography of nonclassical bosonic systems. QST-Flow Framework for Continuous-Variable State Tomography A new approach to quantum state tomography leverages machine learning to map complex quantum states with increased efficiency. This shift in modeling allows for more streamlined data processing crucial for understanding and manipulating quantum systems. QST-Flow distinguishes itself through two variants, QST-QFlow and QST-WFlow, each designed to handle different aspects of quantum behavior. QST-QFlow specifically models positive Husimi functions using a single normalizing flow, while QST-WFlow employs a “trainable difference of two normalized flows” to accurately represent sign-changing Wigner functions. This construction fundamentally preserves quasiprobability normalization, enabling exact density evaluation, direct sampling, and learning from limited phase-spac
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