Quantum Annealing: D-Wave Systems & Optimization Applications
Quantum annealing news: D-Wave Advantage systems, optimization problems, hybrid algorithms. QUBO formulations & commercial deployments.
Quantum annealing represents the earliest commercialized form of quantum computing, using quantum fluctuations to find optimal solutions to combinatorial optimization problems. D-Wave Systems has deployed systems with 5,000+ qubits (Advantage processor) accessed via cloud and installed at research institutions, government labs, and corporations.
Unlike gate-based quantum computers that execute algorithmic instructions, quantum annealers solve problems by mapping them onto an Ising model or quadratic unconstrained binary optimization (QUBO) formulation. The quantum processor evolves from a superposition of all possible states toward the ground state of the problem Hamiltonian.
India's Quantum Annealing Landscape
India's enterprise technology sector explores quantum annealing through cloud access to D-Wave systems. The National Quantum Mission focuses primarily on gate-based quantum computing hardware development rather than quantum annealing hardware, but optimization applications using quantum annealing fall under NQM's broader quantum computing applications scope. Tata Consultancy Services (TCS), Infosys, and other IT majors develop quantum optimization solutions for Indian enterprises using hybrid quantum-classical approaches.
Key Advantages
Key advantages include mature commercial technology with 10+ years of cloud availability, massive qubit counts (5,000+), specialization for optimization without requiring full error correction, and established application ecosystems. Limitations include narrow application scope (optimization only), no quantum error correction, and restricted connectivity requiring problem embedding overhead.
Recent Developments
Recent developments include D-Wave's Advantage2 prototype experimenting with higher connectivity (Zephyr topology) and error-reduction techniques.
quantum-computingEntanglement reveals the difficulty of computational problems
Adiabatic quantum computing An example problem represented by an energy landscape. Each point on the landscape represents a candidate solution. The deepest valley represents the actual solution with the lowest energy in dark blue. A difficult problem involves multiple valleys with similar depth and therefore similar energy. Arriving at the solution – the lowest energy valley – requires a large amount of entanglement and time. This is where quantum speed-up can be most crucial. (Courtesy: Einar Gabbassov)"> Adiabatic quantum computing An example problem represented by an energy landscape. Each point on the landscape represents a candidate solution. The deepest valley represents the actual solution with the lowest energy in dark blue. A difficult problem involves multiple valleys with similar depth and therefore similar energy. Arriving at the solution – the lowest energy valley – requires a large amount of entanglement and time. This is where quantum speed-up can be most crucial. (Courtesy: Einar Gabbassov) Entanglement is a key resource for quantum computation and quantum technologies, but it can also tell us much about a computational problem. That is the conclusion of a recent paper by Achim Kempf and Einar Gabbassov – who are applied mathematicians at Canada’s University of Waterloo and are affiliated with Waterloo’s Institute for Quantum Computing and the Perimeter Institute for Theoretical Physics. Writing in Quantum Science and Technology, Gabbassov and Kempf show how entanglement plays a fundamental role in determining both the efficiency and the hardness of quantum computation problems. They considered the role of entanglement in adiabatic quantum computing. This considers a landscape of hills and valleys (the problem) where the shape of the landscape depends on the problem to be solved. A point on the landscape represents a candidate solution to the problem. This could be a configuration of possible states of three qubits, for example, or “a possible
Physics World QuantumLoading...0
Quantum Computers Sidestep Major Flaw, Paving Way for Larger, More Accurate Calculations
Scientists are increasingly exploring variational quantum eigensolvers as practical approaches to prepare ground states, but their potential for quantum advantage remains unclear. Baptiste Anselme Martin from Eviden Quantum Lab and Thomas Ayral from CPHT, CNRS, Ecole Polytechnique, IP Paris, alongside et al., demonstrate a novel method utilising differentiable 2D tensor networks to optimise parameterised circuits for the transverse field Ising model. This research is significant because it enables the preparation of highly accurate ground states for systems exceeding one dimension and crucially, mitigates the detrimental barren plateau issue by identifying enhanced gradient zones that maintain performance as system size increases. By evaluating the classical simulation cost at these optimised starting points, the team delineate regimes where quantum hardware may ultimately outperform tensor network simulations. Tensor network pre-optimisation overcomes barren plateaus in variational quantum circuits by improving initial parameterisation Researchers are pioneering a new approach to harness the power of quantum computing by integrating classical tensor network algorithms with parameterized quantum circuits. This work details the use of differentiable two-dimensional tensor networks to optimize circuits designed to prepare the ground state of the transverse field Ising model, achieving high energy accuracy even for complex systems exceeding one-dimensional limitations. The study demonstrates that pre-optimization using tensor networks effectively mitigates the barren plateau issue, a significant obstacle in quantum computation, by unlocking enhanced gradient zones that maintain their size even as system complexity increases. Specifically, the research focuses on optimizing quantum circuits using projected entangled pair states, a type of two-dimensional tensor network, combined with automatic differentiation techniques. This method allows for the efficient preparation
Quantum ZeitgeistLoading...0
quantum-computingFlynn Zito Dumps 100,000 D-Wave Quantum Shares Worth $2.9 Million
Specializing in quantum computing hardware and cloud services, D-Wave Quantum serves enterprise clients across diverse industries.On February 5, 2026, Flynn Zito Capital Management disclosed in an SEC filing that it sold 100,000 shares of D-Wave Quantum (QBTS +2.37%).What happenedAccording to a SEC filing dated February 5, 2026, Flynn Zito Capital Management reduced its stake by 100,000 shares in D-Wave Quantum during the fourth quarter of 2025. The estimated value of shares sold, calculated using the average closing price for the quarter, was $2.91 million. The fund’s position value in D-Wave Quantum declined by $2.41 million over the quarter, a figure that includes both trading and price movements.What else to knowThis was a sell, leaving the D-Wave Quantum position at 0.37% of the fund’s 13F AUM after the transaction.Top five holdings after the filing:NYSEMKT: HFXI: $20,609,453 (7.4% of AUM)NYSEMKT: PRF: $20,383,474 (7.3% of AUM)NASDAQ: AAPL: $20,002,736 (7.1% of AUM)NYSEMKT: IWF: $18,790,446 (6.7% of AUM)NYSEMKT: FLQM: $17,814,776 (6.4% of AUM)As of February 5, 2026, shares of D-Wave Quantum were priced at $17.21, up 174.9% over the past year with one-year alpha of 162.76 percentage points versus the S&P 500.Company overviewMetricValuePrice (as of market close February 5, 2026)$17.21Market capitalization$6.31 billionRevenue (TTM)$24,144,000Net income (TTM)($398,813,000)Company snapshotProvides quantum computing systems, cloud-based quantum access, professional onboarding services, and open-source software tools.Generates revenue through hardware sales, cloud subscriptions, and enterprise quantum consulting and deployment services.Targets manufacturing, logistics, financial services, life sciences, and other sectors seeking advanced computational solutions.D-Wave Quantum is a technology company specializing in the development and commercialization of quantum computing hardware, software, and cloud-based services. The company leverages its proprietary quantum
The Motley FoolLoading...0
quantum-computingBoca Raton Lures Quantum Computing Firm D-Wave From Silicon Valley - The Capitolist
Boca Raton Lures Quantum Computing Firm D-Wave From Silicon Valley The Capitolist
Google News – Quantum ComputingLoading...0
quantum-computingQuantum Chaos Simulations Boosted by Algorithm with a Cubic Scaling Advantage
Researchers are continually seeking efficient methods to generate the random thermal states essential for investigating thermalisation, chaos, and phase transitions in complex quantum systems. Jiyu Jiang, Mingrui Jing, and Jizhe Lai, from the Thrust of Artificial Intelligence, Information Hub at The Hong Kong University of Science and Technology (Guangzhou), alongside Xin Wang and Lei Zhang et al., have developed a novel approach called thermal-drift sampling to address the computational cost of preparing these states individually. Their work introduces a measurement-based operation and algorithm that generates thermal states alongside Hamiltonian labels, scaling favourably with system size and offering a trade-off between accuracy and range. Validated through simulations on a 2D Heisenberg model, this technique provides a practical and scalable pathway for chaos diagnostics, demonstrated by the successful application to a 2D transverse-field Ising model and its alignment with Wigner, Dyson predictions, potentially advancing studies on near-term quantum hardware. Scientists introduce the thermal-drift channel, a measurement-based operation that implements a tunable nonunitary drift along a chosen Pauli term. Based on this channel, they present a measurement-controlled sampling algorithm that generates thermal states together with their Hamiltonian “labels” for general physical models. They prove that the total gate count of their algorithm scales cubically with system size, quadratically with inverse temperature, and as the inverse error tolerance to the two-thirds power, with logarithmic dependence on the allowed failure probability. Furthermore, they show that the induced label distribution approaches a normal distribution reweighted by the. Haar and Thermal State Generation for Quantum System Characterisation Scientists are investigating the generation of random quantum states, offering a resource analogous to random numbers in classical stochastic theories. Ense
Quantum ZeitgeistLoading...0
quantum-computingBuy These 2 Quantum Stocks Now For Up to 5,233% Gains by 2035.
By Keithen Drury – Feb 8, 2026 at 2:10PM ESTKey PointsIonQ and D-Wave Quantum are taking different approaches to quantum computing. Their risks of failure are much higher than their chances of success.We’re bullish on these 10 stocks ›NYSE: IONQIonQMarket Cap$12BToday's Changeangle-down(14.98%) $4.56Current Price$34.99Price as of February 6, 2026 at 4:00 PM ETThe quantum computing market could be worth as much as $72 billion annually by 2035.Quantum computing is an emerging industry that is viewed as having massive potential. Although commercial applications for quantum computing haven't arrived yet, that's more to do with the current capabilities of the technology than the workloads. If a company could create a viable quantum computer, that company would instantly be worth hundreds of billions of dollars. But that's not where we are yet. We're still some distance from quantum computing becoming mainstream, but we're getting closer. Two stocks that often get discussed as great quantum computing investment options are IonQ (IONQ +14.98%) and D-Wave Quantum (QBTS +20.19%). Each of these companies is taking a different approach to the technology, and each has a viable path ahead. If everything works out, each stock could deliver 1,000% or greater gains, but they have steep hills to climb to get there. Image source: Getty Images. IonQ and D-Wave have different technologies There are numerous techniques that can be employed to create the qubits that sit at the heart of every quantum computer. IonQ uses the trapped ion approach, which uses lasers to cool isolated individual atoms to near absolute zero -- conditions that cause their behavior to be governed by quantum mechanical principles, allowing them to be harnessed to process data in ways that classical computers can't. ExpandNYSE: IONQIonQToday's Change(14.98%) $4.56Current Price$34.99Key Data PointsMarket Cap$12BDay's Range$31.34 - $36.1052wk Range$17.88 - $84.64Volume33MAvg Vol21MGross Margin-747.41% D-Wav
The Motley FoolLoading...0
quantum-computingD-Wave Quantum Shares Crashed in January. Is it Time to Buy?
Are quantum computing stocks in a bubble or about to take off?D-Wave Quantum (QBTS +20.39%) wants to lead the development of quantum computing with a unique, dual-platform approach. The month of January included several steps to accomplish that goal. Yet rather than sending shares higher, D-Wave stock lost 18.9% last month, according to data provided by S&P Global Market Intelligence. That makes it a good time to take another look at the investing thesis. Image source: Getty Images. Game-changing potential Quantum computing could be a powerful game changer in many areas. It possesses enormous, transformative potential across industries such as pharmaceuticals, materials science, finance, and cybersecurity by tackling problems that classical computers cannot solve. 2025 was a somewhat breakthrough year as quantum sensing technology advanced beyond foundational research. The emphasis has shifted to production and deployment with quantum computing processing. Companies are taking varied approaches, leaving investors to decide which, if any, quantum computing stocks to include in their portfolios. D-Wave was primarily known for its leading quantum annealing system, which is already commercially available. It's an energy-efficient system designed to help enterprises speed up decision-making, optimize operations, and respond to disruptions. Last month, however, the company completed what could be a somewhat transformational acquisition. D-Wave brought Quantum Circuits Inc. (QCI) into its fold. That company creates full-stack superconducting gate-model quantum computing systems engineered for commercial scalability. The combination gives D-Wave a balance between its commercial annealing quantum systems and a path to develop gate-model quantum computers at scale for general-purpose, fault-tolerant computing. Investors should keep eyes wide open D-Wave didn't break the bank with the acquisition. The price to acquire QCI was $550 million, consisting of a combination of $3
The Motley FoolLoading...0
quantum-computing2 Quantum Computing Stocks That Could Make You a Millionaire
By Keithen Drury – Feb 7, 2026 at 4:07PM ESTKey PointsIonQ's trapped-ion quantum computers currently have an accuracy advantage over the competition.D-Wave Quantum's niche approach makes it a worthy investment. We’re bullish on these 10 stocks ›NYSE: IONQIonQMarket Cap$12BToday's Changeangle-down(14.98%) $4.56Current Price$34.99Price as of February 6, 2026 at 4:00 PM ETIonQ and D-Wave Quantum are great long-shot bets in this space.The quantum computing space is full of companies that have millionaire-maker potential. The difficulty lies in sorting out ahead of time which ones are most likely to actually deliver on that potential. Developing this nascent technology remains a high-risk, high-potential-reward endeavor, and many companies pursuing it are likely to go bankrupt or be bought out before reaching a point where they can offer a commercially viable quantum computing product. In my view, these two stocks could deliver incredible returns, but there is no guarantee that either will actually do so. Image source: Getty Images. 1. IonQ IonQ (IONQ +14.98%) is my top pick in this space, at least among the pure plays. Among the leading challenges in quantum computing right now are error reduction and error mitigation. The qubits that sit at the heart of all of these machines are incredibly sensitive, and that leads to an unacceptably high level of errors in their results. An inaccurate computing solution is basically worthless, so every company in the quantum computing space is looking to develop systems that will drastically reduce their error rates and allow them to correct those that do occur. IonQ is the current leader on that front, and by a fairly meaningful margin. It gained this advantage due in part to the particular approach it's taking to quantum computing. While IonQ's trapped ion qubits have given it an accuracy advantage, the processing speeds of this type of system are slower than those of more widely pursued types of quantum computers. This co
The Motley FoolLoading...0
quantum-computingPrediction: The Quantum Stock Could Surge 78% in 2026
By Rick Orford – Feb 7, 2026 at 11:00AM ESTNYSE: QBTSD-Wave QuantumMarket Cap$7.7BToday's Changeangle-down(20.19%) $3.48Current Price$20.68Price as of February 6, 2026 at 3:58 PM ETIs this the quantum computing stock that finally turns promise into profits or is the market getting ahead of itself?D-Wave Quantum (QBTS +20.19%) is making a bold move that could redefine its future and unlock massive upside for investors willing to embrace volatility. This video breaks down the catalyst, the risks, and what needs to happen next. Stock prices used were the market prices of Jan. 27, 2026. The video was published on Feb. 5, 2026. Read NextFeb 6, 2026 •By Keith NoonanD-Wave Quantum Skyrocketed Today -- Is the Stock a Buy Right Now?Feb 6, 2026 •By Chris NeigerWarning: This Skyrocketing Stock Has a Hidden RiskFeb 5, 2026 •By Robert IzquierdoIs D-Wave Quantum Stock a Buy Now?Feb 4, 2026 •By Rick OrfordShould You Buy D-Wave Stock Before Its Next Breakout?Feb 4, 2026 •By Leo Sun2 Quantum Computing Stocks to Buy Hand Over Fist in FebruaryFeb 4, 2026 •By John BromelsIs D-Wave Quantum (QBTS) Stock a Buy Now?About the AuthorRick is a Wall Street Journal best-selling author with over 20 years of experience trading stocks and options. The most authoritative publications, including Good Morning America, Washington Post, Yahoo Finance, MSN, Business Insider, NBC, FOX, CBS, and ABC News, cover his work. His passion is business, and he works tirelessly to deliver content in an easy-to-understand manner. In 2018, Rick wrote The Financially Independent Millennial to inspire his readers with his story about becoming financially independent at age 35 despite not learning about money when he was younger. His books are easy to read and often refer to key points that “He would tell his younger self.” When not thinking about business, Rick writes (mainly about cruise ship travel) for his travel blog and is an enthusiast of fast cars, technology, & cooking.CMFrickorfordStocks Mention
The Motley FoolLoading...0
quantum-computingWhere Will Rigetti Computing Go Next?
By Anders Bylund – Feb 6, 2026 at 7:09PM ESTKey PointsRigetti shares have gained 1,420% in 15 months, outpacing IonQ but trailing D-Wave.The stock trades at 757 times sales, making even its high-flying peers look cheap.Cash-burning companies don't always survive long waits for profitability.These 10 Stocks Could Mint the Next Wave of Millionaires ›NASDAQ: RGTIRigetti ComputingMarket Cap$4.9BToday's Changeangle-down(17.96%) $2.69Current Price$17.66Price as of February 6, 2026 at 3:58 PM ETWhere is Rigetti stock headed next? The answer depends on which question you're really asking.Like its pure-play quantum computing peers, Rigetti Computing (RGTI +17.96%) has seen incredible stock returns recently. As of this writing on Feb. 4, 2026, share prices are up by 1,420% in the past 15 months. The jump is a few steps behind D-Wave Quantum (QBTS +20.19%) gaining 1,910% over the same period, but far ahead of IonQ's (IONQ +14.98%) 770% rise. Rigetti investors expect quantum computing to disrupt many industries in the long run. From encryption and genetic analysis to financial forecasting, quantum's probabilistic calculations should eventually run circles around today's digital computers. And Rigetti isn't laser-focused on a single aspect of this opportunity. Instead, it wants to offer a full stack of quantum computing solutions, from hardware manufacturing and system design to management software and cloud-based service delivery. Presenting the whole package as a unit could make Rigetti popular with deep-pocketed enterprise customers. ExpandNASDAQ: RGTIRigetti ComputingToday's Change(17.96%) $2.69Current Price$17.66Key Data PointsMarket Cap$4.9BDay's Range$15.34 - $17.7352wk Range$6.86 - $58.15Volume1.4MAvg Vol37MGross Margin-6849.48% But what about the stock? You weren't asking about Rigetti's business ambitions, though. You want to know where the stock is going next. Honestly, Rigetti can go wherever quantum hype takes it. I thought it would cool down in 2025 after
The Motley FoolLoading...0
quantum-computingQuantum Error Fix Cuts Processing Time for Complex Problems Significantly
Scientists are increasingly focused on benchmarking noisy intermediate-scale quantum devices, and a new study details a method for data-driven evaluation of quantum annealing experiments. Juyoung Park, Junwoo Jung, and Jaewook Ahn, all from the Department of Physics at KAIST, alongside et al., present a deterministic error mitigation (DEM) procedure that improves inference from noisy measurements on Rydberg arrays. This research is significant because it establishes a framework for comparing the performance of quantum devices with classical algorithms based on both solution quality and computational cost. By applying DEM to the -independent set problem on neutral atom arrays, the team demonstrate a reduction in postprocessing overhead and predict a scaling that allows for a direct cost-based comparison between quantum experiments and their classical counterparts. These experiments often yield measurement outcomes deviating from ideal distributions, hindering accurate performance assessment. DEM is a shot-level inference procedure that leverages experimentally characterised noise to enable data-driven benchmarking, considering both solution quality and the classical computational cost of processing noisy measurements. The work demonstrates this approach using the decision version of the k-independent set problem, a computationally demanding task. Within a Hamming-shell framework, the volume of candidate solutions explored by DEM is governed by the binary entropy of the bit-flip error rate, resulting in a classical postprocessing cost directly controlled by this entropy. Experimental data reveals that DEM reduces postprocessing overhead when compared to conventional classical inference baselines. Numerical simulations and experimental results obtained from neutral atom devices validate the predicted scaling behaviour with both system size and error rate. These established scalings indicate that one hour of classical computation performed on an Intel i9 processor is eq
Quantum ZeitgeistLoading...0
quantum-computingLight Transforms Magnetic Material into Exotic ‘Chern Insulator’ State
Researchers have demonstrated that altermagnets exhibit unusual thermoelectric and thermal Hall effects following irradiation with light. Fang Qin from Jiangsu University of Science and Technology, alongside Xiao-Bin Qiang from Southern University of Science and Technology, and colleagues, reveal how elliptically polarised light transforms an altermagnet into a Chern insulator, subsequently inducing these effects. This work is significant because it establishes a novel method for probing both the electronic bandwidth and topological properties of materials via measurements of thermoelectric and thermal Hall conductivities at extremely low temperatures. Specifically, the observed linear temperature dependence and eventual quantisation of these conductivities offer a new pathway for characterising complex quantum states within irradiated altermagnets. Light-induced topological phase transition in d-wave altermagnets generates anomalous Hall effects Researchers have demonstrated a pathway to transform a d-wave altermagnet into a Chern insulator using elliptically polarized light, opening possibilities for advanced electronic technologies. This breakthrough centers on manipulating material states with light, specifically inducing a topological phase transition within the altermagnet. The study details how irradiation with a high-frequency photon beam fundamentally alters the material’s electronic structure, creating conditions for novel thermoelectric and thermal transport properties. Specifically, the research reveals that exposing the d-wave altermagnet to elliptically polarized light generates a gap within its electronic band structure, a crucial step towards realizing the Chern insulating state. This light-induced transformation activates intrinsic anomalous thermoelectric and thermal Hall effects, previously suppressed in the material. At extremely low temperatures, the thermoelectric Hall coefficient vanishes within this newly formed energy gap, but exhibits disti
Quantum ZeitgeistLoading...0
quantum-computingD-Wave Quantum Skyrocketed Today -- Is the Stock a Buy Right Now?
Is D-Wave stock worth buying after its rebound rally?D-Wave Quantum (QBTS +20.19%) stock posted massive gains in Friday's trading. The quantum computing company's share price surged more than 20% in a day of trading that saw the S&P 500 gain 2% and and the Nasdaq Composite surge 2.2% higher. After some big sell-offs earlier in the week, D-Wave and other growth stocks came roaring back in today's trading. The company's rally was aided in part by Amazon's announcement that it plans to spend $200 billion this year building out its artificial intelligence (AI) data-center infrastructure and pursuing other growth projects. Image source: Getty Images. Amazon's huge capital expenditures forecast helped restore confidence in the AI trade -- and the bullish momentum extended to D-Wave and other quantum-computing stocks. Despite the rally today, D-Wave stock is still down 53.5% from its lifetime high. Is D-Wave stock a buy right now? D-Wave appears to have solid early positioning in the quantum-computing market. The company's annealing approach to quantum tech is yielding commercialization opportunities, and its bets on gate-model tech could wind up powering even bigger growth over the long term. ExpandNYSE: QBTSD-Wave QuantumToday's Change(20.19%) $3.48Current Price$20.68Key Data PointsMarket Cap$6.4BDay's Range$17.85 - $20.9852wk Range$4.45 - $46.75Volume1.4MAvg Vol36MGross Margin82.82% On the other hand, D-Wave's outlook is highly speculative -- and the potential for big upside with the stock comes with a lot of risk. For long-term investors, D-Wave stock may be looking at a binary outcome. While shares could go on to deliver multibagger returns, there is also a big risk that shareholders could lose most or all of their investment. Read NextFeb 6, 2026 •By Chris NeigerWarning: This Skyrocketing Stock Has a Hidden RiskFeb 5, 2026 •By Robert IzquierdoIs D-Wave Quantum Stock a Buy Now?Feb 4, 2026 •By Rick OrfordShould You Buy D-Wave Stock Before Its Next Breakout?Feb 4, 2
The Motley FoolLoading...0
quantum-computingQuantum Circuits Unlock New Ways To Simulate Complex Magnetic Materials - Quantum Zeitgeist
Researchers are increasingly exploring the connections between bosonic counting problems and the simulation of complex quantum systems. Minhyeok Kang from SKKU Advanced Institute of Nanotechnology, Gwonhak Lee from the same institution, and Youngrong Lim from Chungbuk National University, alongside Joonsuk Huh et al., demonstrate a significant advance in this field by extending the established link between Ising model interactions and matrix functions to encompass arbitrary network topologies. Their work reveals that transition amplitudes within the Ising Hamiltonian correlate directly with the hafnian and loop-hafnian, functions previously associated with classical computational hardness. Importantly, this research establishes a unified framework connecting single photons, Gaussian states, and spin dynamics, potentially unlocking new applications for quantum circuit models and highlighting previously unrecognised classically intractable problems. This work extends the Ising model construction to arbitrary interaction networks, demonstrating that transition amplitudes of the Ising Hamiltonian are proportional to the hafnian and the loop-hafnian. These matrix functions, including the permanent, hafnian, and loop-hafnian, are central to bosonic counting problems and arise naturally in spin models like the Ising and Heisenberg models. The correspondence between these seemingly disparate areas has implications for understanding the classical hardness of simulating interacting spin systems, relating their output distributions to computationally challenging #P-hard quantities. Previous investigations largely focused on bipartite spin interactions, where transition amplitudes were proportional to the permanent. This research broadens this scope by showing that arbitrary interaction networks within the Ising model yield transition amplitudes proportional to both the hafnian and the loop-hafnian. The loop-hafnian, a generalization of both the permanent and hafnian, introduce
Google News – Quantum ComputingLoading...0
quantum-computingQuantum Computing’s ‘barren Plateaus’ Overcome with Extra Circuit Parameters
Variational Quantum Algorithms (VQAs) represent a promising avenue for near-term quantum computing, but optimisation performance can be severely limited by fundamental issues such as barren plateaus and overparametrisation. Himuro Hashimoto, Akio Nakabayashi, and Lento Nagano, from Yokogawa Electric Corporation and The University of Tokyo, with colleagues including Yutaro Iiyama, Ryu Sawada, and Junichi Tanaka, present a comprehensive numerical study investigating both barren plateaus and overparametrisation within VQA optimisation. Their work significantly advances understanding by quantitatively evaluating the impacts of these phenomena, and their interplay, using a one-dimensional transverse and longitudinal field Ising model. This research offers a crucial framework for designing more effective VQAs and ansatzes, providing theoretical support for parameter optimisation behaviours in practical applications. These algorithms, reliant on parametrised quantum circuits, frequently encounter difficulties stemming from vanishing gradients known as barren plateaus and the presence of undesirable local minima within the cost function landscape. Numerical investigations have indicated that increasing the number of parameters in a circuit, a state termed overparametrisation, can significantly reduce the likelihood of becoming trapped in these local minima. While theoretical understanding of both barren plateaus and overparametrisation has progressed, a comprehensive study examining both phenomena concurrently has remained elusive. This work presents a detailed numerical analysis of VQAs, quantitatively assessing the impacts of barren plateaus and overparametrisation, and their combined influence on circuit optimisation. The research employs concrete implementations of the one-dimensional transverse and longitudinal field Ising model to evaluate performance. Numerical results are then carefully compared against established theoretical diagnostics for both barren plateaus an
Quantum ZeitgeistLoading...0
quantum-computingWarning: This Skyrocketing Stock Has a Hidden Risk
D-Wave shareholders are betting on a company that has very little sales and that operates in an unproven market.It's hard to ignore the long list of quantum computing stocks that have been on a tear over the past few years. One company that's benefited from all of the quantum computing hype -- because a lot of it is hype -- is D-Wave Quantum (QBTS 14.45%). D-Wave's returns of 1,600% over the past three years are hard to ignore. But I think the recent gains are masking a significant risk for investors. Here's why. Image source: Getty Images. Significant quantum computing sales are years away When a company's share price is rocketing so high and so fast, some investors don't want to look at the hard truths about the company or the market it's competing in. In this case, the risk many people are ignoring is the fact that D-Wave generates hardly any revenue, and it could be years before quantum computing companies see any meaningful sales. D-Wave recently reported its third-quarter results, and the company had just $3.7 million in sales. That's obviously a very small amount, but it looks even worse when we put it into the context of D-Wave's net loss of $140 million under generally accepted accounting principles (GAAP). This means that the gap between D-Wave's revenue and losses is very significant, and it could be years before it comes close to closing it. While there are plenty of optimistic investors who believe that quantum computing sales will catch up with spending soon, I'm not so sure. Even big tech players like Alphabet -- which has developed its own quantum computing processor and made breakthroughs in quantum algorithms -- believe that significant commercial sales are still five to 10 years away. And management at Rigetti Computing has said that the company won't have commercial sales for three to five years. ExpandNYSE: QBTSD-Wave QuantumToday's Change(-14.45%) $-2.90Current Price$17.20Key Data PointsMarket Cap$6.4BDay's Range$16.91 - $19.6152wk Range$4.45 -
The Motley FoolLoading...0
quantum-computingFlorida’s Emerging Role in the Quantum Economy
Insider Brief Florida crossed a structural inflection point in quantum development as coordinated corporate moves, academic investments, workforce initiatives, and capital alignment converged within a single week. IonQ’s planned acquisition of SkyWater Technology, D-Wave’s headquarters relocation and R&D expansion in Boca Raton, and Florida Atlantic University’s $20 million on-site quantum system collectively anchored both commercial and institutional quantum capacity in the state. Workforce programs led by Palm Beach State College, combined with Palm Beach County’s proven economic development framework and growing focus on advanced computing investment, signal a deliberate shift from quantum ambition to execution. PRESS RELEASE — Last week marked a quiet but consequential inflection point for quantum activity in Florida. Not through a single announcement or headline-grabbing pledge, but through a sequence of coordinated moves – corporate, academic, and institutional – that together signal a region moving from aspiration to structure. The signal came early in the week. IonQ announced its intention to acquire SkyWater Technology, a deal set to create one of the most vertically integrated quantum platforms in the industry. While national in scope, the transaction carries specific relevance for Florida: SkyWater maintains operations in the state, placing Florida directly within IonQ’s evolving hardware and manufacturing footprint. At a moment when quantum supply chains are still forming, the deal reinforces Florida’s role as part of that emerging industrial base. That context mattered, because what followed was distinctly local. On January 27, D-Wave announced it will relocate its corporate headquarters and establish a major U.S. research and development facility in Boca Raton. The decision represents more than a headquarters move. It anchors commercial quantum activity in South Florida and reflects confidence that the region can support sustained R&D, ta
Quantum DailyLoading...0
quantum-computingQuantum Algorithm Swiftly Unlocks Energy States for Next-Generation Technologies
Scientists are continually seeking more efficient methods for computing the electronic structures of complex systems, a crucial task for advances in photonics, solid-state physics and related technologies. Shaobo Zhang from The University of Melbourne, Akib Karim from Data61, CSIRO, and Harry M. Quiney, also from The University of Melbourne, alongside Muhammad Usman, present a novel approach with the Quantum Jacobi-Davidson (QJD) method and its Sample-Based variant, demonstrating markedly faster convergence for ground state energy estimation. Their research assesses the performance of these methods using simulations on systems ranging from 8-qubit matrices to a 10-qubit water molecule Hamiltonian, revealing significant improvements in convergence speed and reduced requirements for Pauli measurements compared to existing Davidson methods. These findings establish the QJD framework as a powerful, general-purpose technique with considerable potential for sparse Hamiltonian calculations on future quantum hardware. These new algorithms address a critical challenge in simulating quantum systems: the computational expense and convergence issues inherent in traditional iterative methods for finding energy eigenstates of a Hamiltonian. The work details the development and implementation of QJD and SBQJD, showcasing their performance through rigorous numerical simulations. Researchers assessed the intrinsic algorithmic efficiency of these methods across diverse quantum systems, including 8-qubit diagonally dominant matrices, 12-qubit one-dimensional Ising models, and a 10-qubit Hamiltonian representing a water molecule. Both QJD and SBQJD consistently outperformed the recently reported Quantum Davidson method, requiring fewer Pauli measurements to achieve comparable results. SBQJD further enhanced performance through optimized preparation of the initial reference state. These findings establish the QJD framework as a versatile and efficient subspace-based technique for solvin
Quantum ZeitgeistLoading...0
quantum-computingWhy IonQ Stock Keeps Going Down
By Rich Smith – Feb 5, 2026 at 1:16PM ESTKey PointsWolfpack Research published a "short" report on IonQ yesterday.Wolfpack believes IonQ has lost its biggest defense contracts in Congress.These 10 Stocks Could Mint the Next Wave of Millionaires ›NYSE: IONQIonQMarket Cap$13BToday's Changeangle-down(-11.26%) $3.98Current Price$31.36Price as of February 5, 2026 at 2:00 PM ETIonQ lost $1.5 billion last year. Now, even its ability to grow revenues looks questionable.IonQ (IONQ 11.26%) stock is in a tailspin. Down six trading sessions in a row, shares of the biggest name in quantum computing (IonQ is valued at $14 billion, more than Rigetti (RGTI 10.79%) and D-Wave (QBTS 11.24%) combined) added 8.8% to their losses Thursday. That's the tally as of 12:45 p.m. ET -- and IonQ stock is still going down. You can blame Wolfpack Research for that. Image source: Getty Images. Wolfpack shorts IonQ Wolfpack is a short seller, so it's perhaps unsurprising to learn that yesterday it published a report urging investors to sell IonQ stock short. Why? IonQ exploded in popularity on the back of massive revenue growth. Five years ago, IonQ did barely $2 million a year in sales, but from 2022 to 2024, sales soared to $11 million, $22 million, then $43 million! (At last report, sales were on course to double again in 2025.) But Wolfpack explains in its 33-page short report that "up to 86%" of IonQ's 2022-2024 revenue came from Pentagon contracts that Congress is no longer funding; its largest contract was "completely" stripped from the fiscal 2026 defense budget. This creates "a $54.6 million black hole in [IonQ's] expected quantum computing revenues," warns Wolfpack. The analyst says revenues have not taken an obvious hit yet, only because IonQ has been replacing the canceled government contracts with revenue from "subpar non-quantum computing companies" that IonQ has been acquiring. ExpandNYSE: IONQIonQToday's Change(-11.26%) $-3.98Current Price$31.36Key Data PointsMarket Cap$13
The Motley FoolLoading...0
quantum-computingNew Magnetic States Discovered across All 2D Materials Could Transform Data Storage
Scientists are increasingly recognising Van Hove singularities as key drivers of novel phase transitions in materials. Chen Lu and Lun-Hui Hu, from their respective institutions, alongside colleagues, demonstrate that these singularities within multi-orbital systems can stabilise diverse and competing magnetic orders, including a previously unobserved form of intrinsic altermagnetism arising from spontaneous orbital antiferromagnetism. This research is significant because it reveals that intrinsic altermagnetism, where antiparallel spins occupy separate orbitals, can be realised across all two-dimensional crystal structures, offering a generic route to this phenomenon in correlated materials and potentially paving the way for new spintronic technologies. They map several magnetic transitions via Hubbard model phase diagrams, linking these behaviours to specific electronic conditions near Van Hove singularities. This work demonstrates that VHSs within multi-orbital systems can stabilize a variety of competing magnetic orders, notably including an intrinsic altermagnetism originating from spontaneous orbital antiferromagnetism. This intrinsic phase, characterized by antiparallel spins residing on distinct orbitals, is remarkably realized across all four two-dimensional Bravais lattices. The emergence of this phase is driven by orbital-resolved spin fluctuations, enhanced by inter-orbital hopping, and favored by suppressed Hund’s coupling, strong inter-orbital hybridization, and electronic filling near a VHS arising from quadratic band touching. Researchers mapped several magnetic phase transitions through Hubbard-U, JH phase diagrams, specifically observing transitions from ferrimagnet to d-wave extrinsic altermagnet, from d-wave intrinsic altermagnet to ferromagnet, and from g-wave extrinsic altermagnet to either d-wave extrinsic altermagnet or ferromagnet. These findings establish a clear connection between VHSs and the stabilization of altermagnetism in correlated
Quantum ZeitgeistLoading...0