Innovation

Microsoft’s Majorana 1 reignited the buzz about our quantum future. Here’s why Quantum is an important step forward for the world: Traditional computers struggle with solving some problems that quantum computing can easily tackle. When it comes to drug discovery, for example, traditional computers must approximate solutions for molecular behavior, often at the expense of time and precision. Quantum computing, leveraging the unique properties of quantum mechanics, promises to simulate these interactions with far greater accuracy and efficiency. This means accelerating the discovery of new drugs and potentially revolutionizing healthcare. Just as AI has sped up our ability to innovate, pairing it with quantum computing could supercharge that acceleration. Unlike AI, Quantum won’t be something that hits consumers with a “Chat GPT moment” right now. The impact of quantum breakthroughs will be felt in improved healthcare, better materials, and smarter technologies that enhance our daily lives in the background. It’s also important to note: Majorana 1 and other breakthroughs are a massive step forward in building a quantum-world, but history reminds us that transformative change is often a journey. Even the loudest proponents agree—real, tangible benefits won't happen instantly. Yet, as with every pioneering technology, the potential is immense, and the iterative process of innovation will get us there.

EeroQ researchers published new findings in Physical Review X about controlling individual electrons at temperatures above 1 Kelvin. Here's what they accomplished: Current quantum computers operate near 10 millikelvin. EeroQ demonstrated electron control at temperatures 100 times higher. Their approach uses electrons floating on superfluid helium, integrated with standard superconducting circuits. Why this matters for quantum computing: → Reduces extreme cooling requirements   → Uses existing quantum hardware infrastructure   → Creates a cleaner environment for qubit operations   → May help with scaling challenges Johannes Pollanen, EeroQ's cofounder, noted this "reduces a key barrier to scalable quantum computing." The company has been developing this electron-on-helium technology since 2017. The work validates theoretical predictions about using helium as a platform for quantum operations. The research addresses a practical problem: current quantum systems require expensive, complex cooling to near absolute zero temperatures. For those working in quantum computing: What cooling challenges do you face in your systems? ♻️ Repost to help people in your network. And follow me for more posts like this.

Thought you knew which #quantumcomputers were best for #quantum optimization? The latest results from Q-CTRL have reset expectations for what is possible on today's gate-model machines. Q-CTRL today announced newly published results that demonstrate a boost of more than 4X in the size of an optimization problem that can be accurately solved, and show for the first time that a utility-scale IBM quantum computer can outperform competitive annealer and trapped ion technologies. Full, correct solutions at 120+ qubit scale for classically nontrivial optimizations! Quantum optimization is one of the most promising quantum computing applications with the potential to deliver major enhancements to critical problems in transport, logistics, machine learning, and financial fraud detection. McKinsey suggests that quantum applications in logistics alone are worth over $200-500B/y by 2035 – if the quantum sector can successfully solve them. Previous third-party benchmark quantum optimization experiments have indicated that, despite their promise, gate-based quantum computers have struggled to live up to their potential because of hardware errors. In previous tests of optimization algorithms, the outputs of the gate-based quantum computers were little different than random outputs or provided modest benefits under limited circumstances. As a result, an alternative architecture known as a quantum annealer was believed – and shown in experiments – to be the preferred choice for exploring industrially relevant optimization problems. Today’s quantum computers were thought to be far away from being able to solve quantum optimization problems that matter to industry. Q-CTRL’s recent results upend this broadly accepted industry narrative by addressing the error challenge. Our methods combine innovations in the problem’s hardware execution with the company’s performance-management infrastructure software run on IBM’s utility-scale quantum computers. This combination delivered improved performance previously limited by errors with no changes to the hardware. Direct tests showed that using Q-CTRL’s novel technology, a quantum optimization problem run on a 127-qubit IBM quantum computer was up to 1,500 times more likely than an annealer to return the correct result, and over 9 times more likely to achieve the correct result than previously published work using trapped ions These results enable quantum optimization algorithms to more consistently find the correct solution to a range of challenging optimization problems at larger scales than ever before. Check out the technical manuscript! https://lnkd.in/gRYAFsRt

For those tracking progress in Quantum… As my colleague Hartmut Neven has predicted, real-world applications possible only on quantum computers are much closer than people think – as near as five years, even though fully error corrected quantum computers may be further away.  Recently, my colleagues on our Quantum AI team at Google Research took another important step on that path with a new set of results we published last week in Nature that share a promising new approach to applications on today’s quantum computers. Our analog-digital quantum simulator using super-conducting qubits shows performance beyond the reach of classical simulations in cross-entropy benchmarking experiments. Simulations with the level of experimental fidelity in this simulator would require more than a million years on a Frontier supercomputer. The simulator brings together digital’s flexibility and control with the analog’s speed – and provides a path towards applications that cannot be accomplished on a classical computer. Along the way, my colleagues also made a scientific discovery – they observed the breakdown of a well-known prediction in non-equilibrium physics, the Kibble-Zurek mechanism - an important result in our understanding of magnetism, and also useful in various kinds of quantum simulations. Congratulations to Trond Andersen, Nikita Astrakhantsev, and the rest of the team on this exciting step – much more to come! You can read the Nature paper here: https://lnkd.in/gg2En5qe 

The last two days have seen two extremely interesting breakthroughs announced in quantum computing. There is a long path ahead, but these both point to the potential for dramatically upscaling ambitions for what's possible in relatively short timeframes. The most prominent advance was Microsoft's announcement of Majorana 1, a chip powered by "topological qubits" using a new material. This enables hardware-protected qubits that are more stable and fault-tolerant. The chip currently contains 8 topologic qubits, but it is designed to house one million. This is many orders of dimension larger than current systems. DARPA has selected the system for its utility-scale quantum computing program. Microsoft believes they can create a fault-tolerant quantum computer prototype in years. The other breakthrough is extraordinary: quantum gate teleportation, linking two quantum processes using quantum teleportation. Instead of packing millions of qubits into a single machine—which is exceptionally challenging—this approach allows smaller quantum devices to be connected via optical fibers, working together as one system. Oxford University researchers proved that distributed quantum computing can perform powerful calculations more efficiently than classical systems. This could not only create a pathway to workable quantum computers, but also a quantum internet, enabling ultra-secure communication and advanced computational capabilities. It certainly seems that the pace of scientific progress is increasing. Some of the applications - such as in quantum computing - could have massive implications, including in turn accelerating science across domains.

Google Unveils Willow: A Leap Forward in Quantum Computing Google Quantum AI has introduced Willow, a cutting-edge quantum chip designed to address two of the field’s most significant challenges: error correction and computational scalability. Willow, fabricated in Google’s Santa Barbara facility, achieves state-of-the-art performance, marking a pivotal step toward realizing a large-scale, commercially viable quantum computer. It gets way geekier from here – but if you’re with me so far… Exponential Error Reduction Julian Kelly, Director of Quantum Hardware at Google, emphasized Willow’s ability to exponentially reduce errors as the system scales. Utilizing a grid of superconducting qubits, Willow demonstrated a historic breakthrough in quantum error correction. By expanding arrays from 3×3 to 5×5 and then 7×7 qubits, researchers cut error rates in half with each iteration. This achievement, referred to as being “below threshold,” signifies that larger quantum systems can now exhibit fewer errors, a challenge pursued since Peter Shor introduced quantum error correction in 1995. The chip also achieved “beyond breakeven” performance, where arrays of qubits outperformed the lifetimes of individual qubits, which is key to ensuring the feasibility of practical quantum computations. Ten Septillion Years in Five Minutes Willow’s computational capabilities were validated using the Random Circuit Sampling (RCS) benchmark, a rigorous test of quantum supremacy. According to Google’s estimates, Willow completed a task in under five minutes that would take a modern supercomputer ten septillion years—a timescale exceeding the age of the universe. This achievement underscores the rapid, double-exponential performance improvements of quantum systems over classical alternatives. While the RCS benchmark lacks direct commercial applications, it remains a critical indicator of quantum computational power. Kelly noted that surpassing classical systems on this benchmark solidifies confidence in the broader potential of quantum technology. Building Toward Practical Applications Google’s roadmap aims to bridge the gap between theoretical quantum advantage and real-world utility. The team is now focused on achieving “useful, beyond-classical” computations that solve practical problems. Applications in drug discovery, battery design, and AI optimization are among the potential breakthroughs quantum computing could unlock. Willow’s advancements in quantum error correction and computational scalability highlight its transformative potential. As Kelly explained, “Quantum algorithms have fundamental scaling laws on their side,” making quantum computing indispensable for tasks beyond the reach of classical systems. Quantum computing is still years away, but this is an exciting milestone. Considering the remarkable rate of technological improvement we’re experiencing right now, practical quantum computing (and quantum AI) may be closer than we think. -s

🚨 Quantum Computing Breakthrough in Finance 🚨 HSBC just announced a world-first. By using IBM’s Heron quantum processor, the bank achieved a 34% improvement in predicting bond trading probabilities. This marks the first time a bank has applied quantum computing to real financial trading data at scale, moving beyond theory and into production-level application. Some are calling this a “Sputnik moment” for quantum. That is not a perfect analogy, given the geopolitical nature of Sputnik and the corporate implications of HSBC's use of quantum computing. But I am not surprised to see a big leap forward for quantum in the world of finance. In fact, when I wrote Quantum: Computing Nouveau back in 2018, I predicted this exact trajectory: that quantum would move from academic labs to financial markets and other industries where optimization, forecasting, and massive data challenges are prevalent. In my 2018 book, I outlined - Why finance would be among the earliest adopters of quantum, thanks to its reliance on complex risk management, forecasting, and trading models. - How quantum computing could deliver step-change improvements in processing power, solving problems classical computing struggles and corporate NP problems. In computer science, NP (nondeterministic polynomial-time) problems are problems where it’s easy to verify a solution once you have it, but extremely hard to calculate the solution in the first place. - The looming arms race for quantum advantage, not only among tech companies, but also in financial services, energy, logistics, and governments. HSBC’s milestone confirms that we’re crossing the threshold from theory to practice. Quantum computing isn’t just “new math”—it’s new computing, with profound implications for markets, cybersecurity, and global competition. 🔮 Back in 2018, I wrote that quantum computing is not just optional. It is a conditio sine qua non for the future of finance and data-driven industries. Today, we’re watching that future unfold. #Quantum #QuantumComputing #Future #Finance https://lnkd.in/gMNc2M9b

Chinese scientists build largest array of atoms for quantum computing in the world - SCMP Peer reviewers hail breakthrough as ‘significant’ advance in the development of atom-related quantum physics A team led by renowned Chinese physicist Pan Jianwei has built a key component for a quantum computer — an atom-arranging setup capable of creating arrays 10 times larger than previous systems — that raised hopes it could one day be scaled to tens of thousands of these tiny building blocks. The approach taken by Pan and his team from the University of Science and Technology of China overcomes a major hurdle to atom-based quantum computing, according to a paper published last week in the peer-reviewed Physical Review Letters. The researchers designed an artificial intelligence system capable of arranging more than 2,000 rubidium atoms – each serving as a qubit, the two-state basic unit of quantum computing – into perfect patterns in a mere 60,000th of a second, it said. The milestone array was hailed by the paper’s reviewers as “a significant leap forward in computational efficiency and experimental feasibility within atom-related quantum physics”, according to a press release on the university’s website. Three main ways to build a quantum computer have emerged since the concept was first envisioned in the 1980s, with the atom-based approach considered especially promising. Unlike the alternatives, which use superconducting circuits or trapped ions as qubits, neutral atoms are more stable and easier to control in large numbers. However, atom-based systems have so far been limited to arrays of just a few hundred. In an atom-based quantum computer, the atoms are held in place by focused laser beams called optical tweezers, which manipulate their energy levels and link them to perform calculations. #QuantumComputing #China #AtomBasedQuantumComputing #technology #physics #laser

MIT Sets Quantum Computing Record with 99.998% Fidelity Researchers at MIT have achieved a world-record single-qubit fidelity of 99.998% using a superconducting qubit known as fluxonium. This breakthrough represents a significant step toward practical quantum computing by addressing one of the field’s greatest challenges: mitigating noise and control imperfections that lead to operational errors. Key Highlights: 1. The Problem: Noise and Errors • Qubits, the building blocks of quantum computers, are highly sensitive to noise and imperfections in control mechanisms. • Such disturbances introduce errors that limit the complexity and duration of quantum algorithms. “These errors ultimately cap the performance of quantum systems,” the researchers noted. 2. The Solution: Two New Techniques To overcome these challenges, the MIT team developed two innovative techniques: • Commensurate Pulses: This method involves timing quantum pulses precisely to make counter-rotating errors uniform and correctable. • Circularly Polarized Microwaves: By creating a synthetic version of circularly polarized light, the team improved the control of the qubit’s state, further enhancing fidelity. “Getting rid of these errors was a fun challenge for us,” said David Rower, PhD ’24, one of the study’s lead researchers. 3. Fluxonium Qubits and Their Potential • Fluxonium qubits are superconducting circuits with unique properties that make them more resistant to environmental noise compared to traditional qubits. • By applying the new error-mitigation techniques, the team unlocked the potential of fluxonium to operate at near-perfect fidelity. 4. Implications for Quantum Computing • Achieving 99.998% fidelity significantly reduces errors in quantum operations, paving the way for more complex and reliable quantum algorithms. • This milestone represents a major step toward scalable quantum computing systems capable of solving real-world problems. What’s Next? The team plans to expand its work by exploring multi-qubit systems and integrating the error-mitigation techniques into larger quantum architectures. Such advancements could accelerate progress toward error-corrected, fault-tolerant quantum computers. Conclusion: A Leap Toward Practical Quantum Systems MIT’s achievement underscores the importance of innovation in error correction and control to overcome the fundamental challenges of quantum computing. This breakthrough brings us closer to the realization of large-scale quantum systems that could transform fields such as cryptography, materials science, and complex optimization problems.