Quantum Computing Applications

🧨 New record challenging lattice-based #PQC 🧨 A research team led by Professor Jintai Ding (Xi'an Jiaotong-Liverpool University) set a new code-breaking world record for the Lattice Shortest Vector Problem (SVP) in the International Open Darmstadt SVP Challenge. Professor Ding's team has successfully solved the SVP for 200 dimensions, the highest dimension currently supported for submission on the SVP Challenge website. 😱 Don't panic! PQC is not broken yet: Current cryptographic standards would become vulnerable if SVP problems of around 400 dimensions could be solved. However, it shows that there is an algorithmic evolution in tackling SVP problems beyond the advancements in computing power. "Each additional 10 dimensions increases the computational difficulty by roughly an order of magnitude," says Professor Ding. "A decade ago, the record stood at about 130 dimensions and reaching 200 dimensions seemed almost impossible. Yet today, we've solved it with relatively modest academic computing resources." 👉 This record provides a reference to inform cybersecurity agencies and PQC standarization bodies. It also reinforces the importance of cryptoagility, since there seems to be room for research in SVP cryptanalysis. This reminds the importance of the recent announcement from National Institute of Standards and Technology (NIST) to standardize HQC as a non-lattice-based KEM. https://lnkd.in/diBftdHw #postquantum #cryptography

𝗞𝗲𝘆𝗻𝗼𝘁𝗲 𝗦𝗽𝗲𝗮𝗸𝗲𝗿 𝗳𝗼𝗿 𝗜𝗕𝗠 𝗘𝗠𝗘𝗔 𝗶𝗻 𝗠𝗮𝗱𝗿𝗶𝗱: 𝗧𝗿𝗮𝗻𝘀𝗹𝗮𝘁𝗶𝗻𝗴 𝗤𝘂𝗮𝗻𝘁𝘂𝗺 𝗳𝗼𝗿 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 🤍 [𝗔𝗱] Hola from IBM in Madrid! Yesterday I’m was speaking to an exclusive C-suite audience about why technologies like Quantum & AI must be translated – not just developed. According to the latest research from the IBM Institute for Business Value, quantum advantage could emerge as early as 2026. 𝗧𝗵𝗮𝘁’𝘀 𝗡𝗢𝗪. Many leaders think: “Quantum computing? I have more urgent problems.” And I get it. We are still: • Building resilient AI infrastructures • Securing data architectures • Debating AI sovereignty • Training organizations to use AI responsibly But here is the key question: 𝗛𝗼𝘄? Through 𝗛𝘆𝗯𝗿𝗶𝗱 𝗖𝗹𝗼𝘂𝗱 𝗯𝘆 𝗱𝗲𝘀𝗶𝗴𝗻 – giving leaders the flexibility to run AI anywhere (on-prem, cloud or edge). The infrastructure decisions made today are what make tomorrow’s quantum advantage possible. As technology becomes more powerful, governance becomes non-negotiable. & we are also witnessing a shift: From “AI that chats” to “Agentic AI that works”. From experimentation to trusted, agentic workflows embedded into real business processes. That future is not abstract anymore. It is a 2024–2025 business objective. And now Quantum too? 𝗬𝗲𝘀. Because in five years, you’ll be grateful you started today. Look closer and you’ll realize: 𝗤𝘂𝗮𝗻𝘁𝘂𝗺 𝗶𝘀 𝘀𝘆𝘀𝘁𝗲𝗺-𝗿𝗲𝗹𝗲𝘃𝗮𝗻𝘁. From the IBM study, three realities stand out: 𝗜. 𝗤𝘂𝗮𝗻𝘁𝘂𝗺 𝗶𝘀 𝗮𝗻 𝗲𝗰𝗼𝘀𝘆𝘀𝘁𝗲𝗺 𝗴𝗮𝗺𝗲 → Quantum-ready organizations are 𝟯𝘅 𝗺𝗼𝗿𝗲 𝗹𝗶𝗸𝗲𝗹𝘆 to belong to multiple ecosystems → 𝟳𝟵% say ecosystem partners accelerate adoption → 𝟳𝟳% say ecosystem data improves outcomes No company will win quantum alone. 𝗜𝗜. 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗱𝗲𝘁𝗲𝗿𝗺𝗶𝗻𝗲𝘀 𝗮𝗱𝘃𝗮𝗻𝘁𝗮𝗴𝗲 → 𝟳𝟱% see semiconductor dependence as a strategic risk → 𝟵𝟯% say technology sovereignty must be factored into 2026 strategy Quantum compute is even scarcer, more complex and geopolitically sensitive. Access = advantage. 𝗜𝗜𝗜. 𝗣𝗿𝗲𝗽𝗮𝗿𝗮𝘁𝗶𝗼𝗻 𝗶𝘀 𝗻𝗼𝘁 𝗼𝗽𝘁𝗶𝗼𝗻𝗮𝗹 Preparing does not mean building your own quantum computer tomorrow. It means: • Identifying high-impact use cases • Evaluating post-quantum cryptography • Building internal literacy • Securing the right partnerships — including a Hybrid Cloud architecture able to handle future data complexity • Experimenting before advantage becomes visible In this is why translation matters. And it is not only nice storytelling… It is 𝗦𝗧𝗥𝗔𝗧𝗘𝗚𝗜𝗖 𝗘𝗡𝗔𝗕𝗟𝗘𝗠𝗘𝗡𝗧. Grateful to collaborate with IBM to make quantum computing not only more powerful but actionable. Thank you Patrick Bauer!! 🤍🦾 𝗧𝗵𝗲 𝗳𝘂𝘁𝘂𝗿𝗲 𝗶𝘀 𝗻𝗼𝘁 𝗯𝘂𝗶𝗹𝘁 𝗯𝘆 𝘁𝗵𝗼𝘀𝗲 𝘄𝗵𝗼 𝗶𝗻𝘃𝗲𝗻𝘁 𝗲𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴. 𝗜𝘁’𝘀 𝗯𝘂𝗶𝗹𝘁 𝗯𝘆 𝘁𝗵𝗼𝘀𝗲 𝘄𝗵𝗼 𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱. Now to you: Is Quantum on your 2026 agenda? IBM Partner Plus

Breaking Quantum News: Real algorithms, real data, real quantum machines HSBC, in partnership with IBM, has delivered the world’s first quantum-enabled algorithmic trading trial. Using live, production-scale data from the European corporate bond market, HSBC integrated IBM’s quantum processors with classical systems—achieving up to a 34% improvement in predicting the probability of winning trades compared with classical methods alone. Why it matters: - Bond trading is one of the most complex, data-heavy challenges in finance. - Classical models struggle to capture hidden pricing signals in noisy markets. - By augmenting workflows with IBM Quantum Heron, HSBC uncovered insights classical systems could not. As Philip Intallura Ph.D, HSBC’s Global Head of Quantum Technologies, put it: “This is a tangible example of how today’s quantum computers could solve a real-world business problem at scale and offer a competitive edge.” And as IBM’s Jay Gambetta emphasized: breakthroughs come from combining deep financial expertise with cutting-edge quantum algorithms—demonstrating what becomes possible as quantum advances. This is not hype. It’s not distant. Quantum is entering the market—today. #QuantumComputing #Finance #Innovation #PQC #QuantumReady

Everybody’s asking about the 𝗸𝗶𝗹𝗹𝗲𝗿 𝗮𝗽𝗽 𝗳𝗼𝗿 𝗾𝘂𝗮𝗻𝘁𝘂𝗺 𝗰𝗼𝗺𝗽𝘂𝘁𝗲𝗿𝘀. But when a team actually uses one to explore 𝗳𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹 𝗽𝗵𝘆𝘀𝗶𝗰𝘀 in a way we couldn't before, the 𝘀𝗶𝗹𝗲𝗻𝗰𝗲 from the broader community is deafening. Really? I’ve talked about using quantum computers for exploring physics before. I get it - 𝗶𝘁'𝘀 𝗻𝗼𝘁 𝘁𝗵𝗲 𝗶𝗺𝗺𝗲𝗱𝗶𝗮𝘁𝗲, 𝗱𝗶𝘀𝗿𝘂𝗽𝘁𝗶𝘃𝗲 𝗮𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝘁𝗵𝗮𝘁 𝗩𝗖𝘀 𝗮𝗻𝗱 𝗺𝗮𝗿𝗸𝗲𝘁 𝗮𝗻𝗮𝗹𝘆𝘀𝘁𝘀 𝘄𝗮𝗻𝘁 𝘁𝗼 𝗵𝗲𝗮𝗿 𝗮𝗯𝗼𝘂𝘁. 𝗕𝘂𝘁 𝗜 𝗳𝗶𝗻𝗱 𝗶𝘁 𝗮𝗯𝘀𝗼𝗹𝘂𝘁𝗲𝗹𝘆 𝗮𝗺𝗮𝘇𝗶𝗻𝗴 𝘁𝗵𝗮𝘁 𝘄𝗲'𝗿𝗲 𝗳𝗶𝗻𝗮𝗹𝗹𝘆 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝘁𝗼𝗼𝗹𝘀 𝘁𝗵𝗮𝘁 𝗮𝗹𝗹𝗼𝘄 𝘂𝘀 𝘁𝗼 𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱 𝗼𝘂𝗿 𝘄𝗼𝗿𝗹𝗱 𝗼𝗻𝗲 𝗹𝗮𝘆𝗲𝗿 𝗱𝗲𝗲𝗽𝗲𝗿. A new paper from Google 𝗤𝘂𝗮𝗻𝘁𝘂𝗺 𝗔𝗜 & 𝗰𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗼𝗿𝘀, is a perfect case in point. The team tackled a monster of a problem in condensed matter physics: 𝗵𝗼𝘄 𝘁𝗼 𝘀𝗶𝗺𝘂𝗹𝗮𝘁𝗲 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 𝘄𝗶𝘁𝗵 𝗱𝗶𝘀𝗼𝗿𝗱𝗲𝗿. Classically, this is a brute-force nightmare: You have to simulate thousands or even millions of different disorder configurations one by one, which can take an exponential amount of time. 𝗜𝗻𝘀𝘁𝗲𝗮𝗱 𝗼𝗳 𝘀𝗶𝗺𝘂𝗹𝗮𝘁𝗶𝗻𝗴 𝗼𝗻𝗲 𝗰𝗼𝗻𝗳𝗶𝗴𝘂𝗿𝗮𝘁𝗶𝗼𝗻 𝗮𝘁 𝗮 𝘁𝗶𝗺𝗲, 𝗚𝗼𝗼𝗴𝗹𝗲 𝘂𝘀𝗲𝗱 𝘁𝗵𝗲𝗶𝗿 𝟴𝟭-𝗾𝘂𝗯𝗶𝘁 𝗾𝘂𝗮𝗻𝘁𝘂𝗺 𝗽𝗿𝗼𝗰𝗲𝘀𝘀𝗼𝗿 𝘁𝗼 𝗽𝗿𝗲𝗽𝗮𝗿𝗲 𝗮 𝘀𝘁𝗮𝘁𝗲 𝘁𝗵𝗮𝘁 𝗶𝘀 𝗮 𝘀𝘂𝗽𝗲𝗿𝗽𝗼𝘀𝗶𝘁𝗶𝗼𝗻 𝗼𝗳 𝗮𝗹𝗹 𝗽𝗼𝘀𝘀𝗶𝗯𝗹𝗲 𝗱𝗶𝘀𝗼𝗿𝗱𝗲𝗿 𝗰𝗼𝗻𝗳𝗶𝗴𝘂𝗿𝗮𝘁𝗶𝗼𝗻𝘀. Then they gave it a tiny kick of energy in one spot, and watched what happened. The result? The energy stayed put. It refused to spread. This is a phenomenon called 𝗗𝗶𝘀𝗼𝗿𝗱𝗲𝗿-𝗙𝗿𝗲𝗲 𝗟𝗼𝗰𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻 (𝗗𝗙𝗟). Even though the system's evolution and the initial state were perfectly uniform and disorder-free, the underlying superposition over different "backgrounds" caused the system to localize. 𝗜𝘁’𝘀 𝗮 𝘀𝘁𝘂𝗻𝗻𝗶𝗻𝗴 𝗱𝗲𝗺𝗼𝗻𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻 𝗼𝗳 𝗾𝘂𝗮𝗻𝘁𝘂𝗺 𝗺𝗲𝗰𝗵𝗮𝗻𝗶𝗰𝘀 𝗮𝘁 𝘄𝗼𝗿𝗸 𝗼𝗻 𝗮 𝘀𝗰𝗮𝗹𝗲 𝘁𝗵𝗮𝘁’𝘀 𝗶𝗻𝗰𝗿𝗲𝗱𝗶𝗯𝗹𝘆 𝗱𝗶𝗳𝗳𝗶𝗰𝘂𝗹𝘁 𝗳𝗼𝗿 𝗰𝗹𝗮𝘀𝘀𝗶𝗰𝗮𝗹 𝗰𝗼𝗺𝗽𝘂𝘁𝗲𝗿𝘀 𝘁𝗼 𝗵𝗮𝗻𝗱𝗹𝗲, 𝗲𝘀𝗽𝗲𝗰𝗶𝗮𝗹𝗹𝘆 𝗶𝗻 𝟮𝗗. But this isn't just a cool physics experiment. This work carves out a concrete path to quantum advantage. The team proposed an 𝗮𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺 based on this technique that offers a 𝗽𝗼𝗹𝘆𝗻𝗼𝗺𝗶𝗮𝗹 𝘀𝗽𝗲𝗲𝗱𝘂𝗽 𝗳𝗼𝗿 𝘀𝗮𝗺𝗽𝗹𝗶𝗻𝗴 𝗱𝗶𝘀𝗼𝗿𝗱𝗲𝗿𝗲𝗱 𝘀𝘆𝘀𝘁𝗲𝗺𝘀. So yes, let's keep working toward fault-tolerant machines that can break RSA and optimize your portfolio. But let's not ignore the incredible science happening right now. 📸 Credits: Google 𝗤𝘂𝗮𝗻𝘁𝘂𝗺 𝗔𝗜 & 𝗖𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗼𝗿𝘀 (arXiv:2410.06557) Pedram Roushan

Many of you will have seen the news about HSBC’s world-first application of quantum computing in algorithmic bond trading. Today, I’d like to highlight the technical paper that explains the research behind this milestone. In collaboration with IBM, our teams investigated how quantum feature maps can enhance statistical learning methods for predicting the likelihood that a trade is filled at a quoted price in the European corporate bond market. Using production-scale, real trading data, we ran quantum circuits on IBM quantum computers to generate transformed data representations. These were then used as inputs to established models including logistic regression, gradient boosting, random forest, and neural networks. The results: • Up to 34% improvement in predictive performance over classical baselines. • Demonstrated on real, production-scale trading data, not synthetic datasets. • Evidence that quantum-enhanced feature representations can capture complex market patterns beyond those typically learned by classical-only methods. This marks the first known application of quantum-enhanced statistical learning in algorithmic trading. For full technical details please see our published paper: 📄 Technical paper: https://lnkd.in/eKBqs3Y7 📰 Press release: https://lnkd.in/euMRbbJG Congratulations to Philip Intallura Ph.D , Joshua Freeland Freeland and all HSBC colleagues involved — and huge thanks to IBM for their partnership.

Three weeks ago, our Devsinc security architect, walked into my office with a chilling demonstration. Using quantum simulation software, she showed how RSA-2048 encryption – the same standard protecting billions of transactions daily – could theoretically be cracked in just 24 hours by a sufficiently powerful quantum computer. What took her classical computer billions of years to attempt, quantum algorithms could solve before tomorrow's sunrise. That moment crystallized a truth I've been grappling with: we're not just approaching a technological evolution; we're racing toward a cryptographic apocalypse. The quantum computing market tells a story of inevitable disruption, surging from $1.44 billion in 2025 to an expected $16.22 billion by 2034 – a staggering 30.88% CAGR that signals more than market enthusiasm. Research shows a 17-34% probability that cryptographically relevant quantum computers will exist by 2034, climbing to 79% by 2044. But here's what keeps me awake at night: adversaries are already employing "harvest now, decrypt later" strategies, collecting our encrypted data today to unlock tomorrow. For my fellow CTOs and CIOs: the U.S. National Security Memorandum 10 mandates full migration to post-quantum cryptography by 2035, with some agencies required to transition by 2030. This isn't optional. Ninety-five percent of cybersecurity experts rate quantum's threat to current systems as "very high," yet only 25% of organizations are actively addressing this in their risk management strategies. To the brilliant minds entering our industry: this represents the greatest cybersecurity challenge and opportunity of our generation. While quantum computing promises revolutionary advances in drug discovery, optimization, and AI, it simultaneously threatens the cryptographic foundation of our digital world. The demand for quantum-safe solutions will create entirely new career paths and industries. What moves me most is the democratizing potential of this challenge. Whether you're building solutions in Silicon Valley or Lahore, the quantum threat affects us all equally – and so does the opportunity to solve it. Post-quantum cryptography isn't just about surviving disruption; it's about architecting the secure digital infrastructure that will power humanity's next chapter. The countdown has begun. The question isn't whether quantum will break our current security – it's whether we'll be ready when it does.

History was made this week in financial markets. HSBC, Europe’s largest bank, has proven that quantum isn’t just theory...it’s a powerful competitive advantage. In partnership with IBM, HSBC’s quantum pilot delivered a 34% improvement in predicting bond trade fill rates at quoted prices. In markets where milliseconds move billions, that edge is transformative. By combining quantum and classical computing, HSBC tackled complex pricing algorithms that factor in real-time market conditions and risks. Philip Intallura, HSBC’s Group Head of Quantum Technologies, explained: “It means we now have a tangible example of how today’s quantum computers could solve a real-world business problem at scale.” Why it matters: • Quantum computing is projected to become a $100B market within a decade (McKinsey). • Finance is the proving ground where nanoseconds and probabilities drive outcomes. • HSBC just demonstrated how quantum can deliver measurable results today. Quantum is still in its early stages, but breakthroughs like this set the benchmarks for what comes next. Which industry do you think will unlock the first trillion-dollar quantum advantage? #QuantumComputing #FinancialMarkets #BondTrading #FinTech #InnovationLeadership #HSBC #IBM

Quantum Finance: A Leap into the Future Quantum finance field explores how the principles of quantum mechanics can revolutionize the financial world. One exciting area within this field is quantum option pricing: utilizing the power of quantum computers to estimate the theoretical value of options with greater accuracy and efficiency than classical methods. The research paper "Option Pricing using Quantum Computers", presented below, explores precisely this. It details a methodology for pricing various types of options (including vanilla, multi-asset, and even path-dependent options) on a quantum computer using the amplitude estimation algorithm. This algorithm provides a quadratic speedup compared to traditional Monte Carlo simulations, potentially leading to significantly faster and more precise option valuations. The implications for quantum finance are profound. Faster and more accurate option pricing allows for: 1. Dynamic portfolio optimization: Real-time adjustments based on market fluctuations through efficient risk-reward assessment. 2. Enhanced derivatives pricing: Valuing complex financial instruments that are currently computationally prohibitive. 3. Discovering hidden correlations: Unearthing subtle market relationships that elude classical analysis, leading to better-informed investment decisions. However, the future of quantum finance remains a horizon to be crossed. Current challenges include hardware limitations (noisy qubits) and the need for further algorithm development. Nonetheless, the immense potential of quantum computing in finance is undeniable. Quantum finance holds the promise of transforming the financial landscape. With breakthroughs in hardware and algorithms, this field could redefine financial modelling, risk management, and ultimately, the way we make investment decisions. The research on quantum option pricing, as seen in the presented paper, is a crucial step towards this future, laying the groundwork for a new era of financial possibilities. Do give this paper a read! It can give insights into the novel quantum circuits and architecture which can be used to price options. Follow Quant Insider for quant finance related insights and research articles.

Quantum Teleportation Achieved Over 79 km of Standard Internet Fiber Introduction Quantum teleportation has moved from isolated laboratory experiments into real-world infrastructure. German physicists have successfully teleported quantum information over 79 kilometers of standard fiber-optic cables, demonstrating that quantum communication can coexist with everyday internet traffic and bringing the concept of a practical quantum internet significantly closer. The Breakthrough Researchers at the Ferdinand-Braun-Institut achieved quantum teleportation using existing telecom infrastructure. • Quantum states were teleported over 79 km of conventional fiber-optic cable • Transmission occurred at standard telecom wavelengths around 1550 nanometers • Quantum signals coexisted with classical internet data without interference • The work was conducted under the EU Quantum Flagship program How It Works The experiment relied on established quantum principles implemented in a novel way. • Entangled photons were generated using indium gallium arsenide quantum dots • Quantum entanglement allowed the state of one particle to be transferred to another at a distance • Operating at telecom wavelengths minimized signal loss and noise • Careful stabilization preserved fragile quantum states across long distances Why This Is Different Previous teleportation experiments required specialized or dedicated infrastructure. • No custom fiber lines were needed • No disruption to normal data traffic occurred • The approach dramatically reduces cost and complexity • It demonstrates realistic scalability beyond the lab Implications for Security and Networks The findings have immediate relevance for secure communications. • Enables quantum key distribution resistant to future quantum attacks • Supports hybrid networks carrying classical and quantum data side by side • Advances the feasibility of quantum repeaters for global-scale networks • Strengthens applications in finance, defense, and critical infrastructure Why It Matters This achievement marks a turning point for quantum communications. By proving that quantum teleportation works over standard internet fiber, researchers have lowered one of the biggest barriers to deployment. Instead of rebuilding global networks from scratch, quantum security and computation can be layered onto existing infrastructure, accelerating timelines toward a secure, quantum-enabled internet and redefining how information may be protected in the decades ahead. I share daily insights with 35,000+ followers across defense, tech, and policy. If this topic resonates, I invite you to connect and continue the conversation. Keith King https://lnkd.in/gHPvUttw

Interesting research in Quantum Machine Learning addresses key challenges in scalability and data encoding. The GitHub repository is included for further reference. A recent study titled "An Efficient Quantum Classifier Based on Hamiltonian Representations" (Tiblias et al.) proposes a novel approach to quantum classification. The study tackles the limitations of current QML methods that often rely on toy datasets or significant feature reduction due to hardware constraints and the high costs of encoding dense vector representations on quantum devices. The researchers introduce an efficient approach called the Hamiltonian classifier, which circumvents the costs of data encoding by mapping inputs to a finite set of Pauli strings and making predictions based on their expectation values. They also present two classifier variants, PEFF and SIM, with different trade-offs in terms of parameters and sample complexity. Key outcomes of this work include: * A new encoding scheme achieving logarithmic complexity in both qubits and quantum gates relative to the input dimensionality. * The development of classifier variants (PEFF and SIM) offers different performance-cost trade-offs. PEFF reduces model size, while SIM boasts better sample complexity. * The Simplified Hamiltonian (SIM) variant achieves logarithmic scaling in qubit and gate complexity along with a constant sample complexity, making it a strong candidate for practical implementation on Noisy Intermediate-Scale Quantum (NISQ) devices. * Experiments showed that increasing the number of Pauli strings in the SIM model leads to better performance and more stable training dynamics, with models using 500 to 1000 Pauli strings often matching the performance of classical baselines. You can find the GitHub repo here: https://lnkd.in/dN38CFPv. The article here: https://lnkd.in/dG4agXap #quantumcomputing #machinelearning #quantummachinelearning #artificialintelligence #research #nlp #imageclassification #datascience