Large-Scale Quantum System Experiments with Many Atoms

Today at #THINK26, researchers from Cleveland Clinic, RIKEN, and IBM showed the largest known quantum computing-powered simulation of two proteins, T4-Lysozyme and Trypsin, reaching a scale of 12,635 atoms through a new algorithm and quantum‑centric supercomputing workflow: https://lnkd.in/eQHsUDxv The results not only demonstrate a ~40-fold increase in system size compared to work from just six months earlier, but also a 210-fold improvement in accuracy during a key step of the workflow. To reach these new levels of scale and accuracy, the researchers orchestrated the Fugaku (RIKEN) and Miyabi-G (The University of Tokyo and University of Tsukuba) supercomputers alongside two 156-qubit IBM Quantum Heron r2 processors, using up to 94 qubits to run 9,200 circuits over more than 100 hours and collect 1.3 billion measurement outcomes, making this work the largest quantum‑centric supercomputing execution for quantum chemistry to date. But advanced hardware is only part of the story. A new method, EWF‑TrimSQD, improves how large molecules can be fragmented into smaller, tractable clusters that quantum and classical systems solve together, depending on complexity. Our latest blog linked above shares more details on how the team crossed the barrier for how quantum computers can be used to model proteins with more than 12,000 atoms and what this milestone means for the future of quantum chemistry. Paper here: https://lnkd.in/eFXfhpKi

Scientists just trapped 78,400 atoms using a single flat surface thinner than a human hair, a breakthrough that could unlock the next era of quantum computing. By holding thousands of atoms in precise positions, researchers can create highly controlled quantum systems, a critical step toward building scalable, reliable quantum devices. This flat surface acts as a stable platform where quantum states can be maintained, minimizing interference and decoherence, which are major challenges in quantum technology. The experiment could accelerate the development of advanced quantum computers capable of solving problems far beyond the reach of classical machines, from drug discovery to material design. Trapping atoms at this scale demonstrates how quantum physics can be harnessed with extreme precision, revealing the potential to control matter at the smallest levels and reshape the future of computing. Thank YOU — Quantum Cookie In March 2026, physicists at Tsinghua University in China (led by researchers including Tao Zhang) demonstrated an optical metasurface — a single flat silicon nitride chip, patterned with nanoscale pillars and thinner than a human hair—that can generate a 280 × 280 array of 78,400 individual optical tweezers from one input laser beam. These tweezers are focused laser spots that trap and hold individual neutral atoms (likely rubidium or similar) in precise positions with high uniformity (>96% intensity consistency across the array). The metasurface replaces bulky, complex traditional optics like spatial light modulators (SLMs) and acousto-optic deflectors (AODs), making the setup far more compact, stable, scalable, and CMOS-compatible for manufacturing. Why this matters for quantum computing Neutral-atom platforms are promising for quantum computers because atoms are identical, can have long coherence times, and support two-qubit gates via Rydberg interactions. Scaling them up has been limited by the difficulty of creating and controlling huge numbers of stable traps without massive, expensive optical systems. This work shows a path to tens of thousands (or more) of trapped atoms on a simpler platform, addressing a key bottleneck. The team is already working on a larger ~19.5 mm metasurface aimed at >10,000 atoms in a more practical external configuration. Similar metasurface approaches have been explored by groups at Columbia University and others, but this hits a notable record for a single flat device generating that many traps.

Exciting quantum computing progress from #ColumbiaUniversity’s Quantum Initiative! Professors Sebastian Will (Physics) and Nanfang Yu (Applied Physics & Applied Mathematics) are pioneering a powerful approach to large-scale quantum systems using neutral-atom arrays. In their latest work, the team combined optical tweezers with engineered metasurfaces to trap over 1,000 strontium atoms, and they see a clear path toward 100,000+ qubits—a scale that could dramatically advance quantum computing performance. Unlike many other qubit platforms, neutral atoms are identical by nature, simplifying control and scaling. Key innovations: • Novel metasurface-based optical tweezers for massively scalable atom arrays • Successfully trapping and controlling more than 1,000 atoms • A scalable foundation for high-qubit quantum computing platforms Congratulations to Prof. Will, Prof. Yu, and their teams for this impactful step toward truly large-scale quantum hardware! Their work not only pushes fundamental science but also brings us closer to quantum systems capable of solving complex simulations and optimization challenges that classical computers cannot. https://lnkd.in/eVSV8GbN #QuantumComputing #NeutralAtoms #Metasurfaces #Qubits #ColumbiaResearch #OpticalTweezers #Innovation #TechLeadership #ColumbiaEngineering

IBM and RIKEN just hit a massive milestone. They simulated a protein with 12,635 atoms. To put that in perspective? It is a 40x increase in size in just six months. And the accuracy improved by over 200x. 🚀 Here is why this theoretical and hardware leap changes everything. 1. The Hardware Tag-Team 🤝 They didn't do this with quantum alone. They used a powerful hybrid approach. Supercomputers broke the protein into computable fragments. Then, the IBM Heron quantum processor stepped in. It pushed its limits, utilizing 94 of its 156 superconducting qubits. It calculated the complex quantum mechanics of those specific fragments. Finally, the classical systems stitched the full molecular representation back together. It is the perfect marriage of classical scale and quantum precision. 2. The Algorithmic Breakthrough 🧠 Hardware is nothing without the right math. The real hero here is a novel hybrid algorithm. It is called EWF-TrimSQD. Traditional methods like VQE hit a wall when scaling past a handful of atoms. This new subspace quantum diagonalization approach bypassed that bottleneck entirely. It dramatically reduced the computational overhead. It allowed researchers to map complex chemistry directly onto quantum hardware without breaking the system. 3. Scaling the Physics 🧬 They proved the theory by steadily scaling the complexity. They started simple with a 10-atom molecule. Then they moved to a 303-atom protein. Now, they have successfully calculated the total energy of an enzyme with nearly 13,000 atoms. Modeling the quantum-mechanical behavior of a system this massive was previously unheard of. We are finally moving past the era of toy models. We are witnessing hardware and algorithms maturing hand in hand. The era of utility is officially here. ⚛️

IBM just hit a milestone that pulls quantum computing closer to real-world impact. Working with Cleveland Clinic and RIKEN, the company simulated a 12,635-atom protein, the largest biologically meaningful molecule ever modeled with quantum hardware. The advance comes from pairing quantum systems with classical supercomputers, boosting accuracy by up to 210x in key steps and pushing into problems that matter for drug discovery. For years, quantum progress was tracked in qubits and error rates. Now it is being judged by whether it can solve real scientific problems. This is an early but clear shift toward practical use.

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

Each dot in that circle is a single trapped cesium atom — a neutral-atom qubit held in place by an optical tweezer (a tightly focused laser beam). Caltech has now set a record: 6,100 qubits in one tweezer array (loaded into ~12,000 trap sites) — and the impressive part is they scaled without sacrificing quality. What stood out to me: • Coherence: ~13 seconds (reported as T₂ = 12.6(1) s). • Control: 99.98% individual-qubit manipulation accuracy (per Caltech’s release). • Reconfigurability: they can move atoms hundreds of micrometers while maintaining superposition — a key ingredient for scalable architectures and error correction. Big picture: this is a massive, highly coherent qubit register with coherence-preserving transport — one of the clearest “quantity + quality” steps toward large-scale quantum error correction. The next frontier is wiring up large-scale entanglement and turning this into a full algorithmic machine. Paper (arXiv): https://lnkd.in/dDAKCtCd Caltech news release: https://lnkd.in/dRVDPF_d #QuantumComputing #QuantumPhysics #NeutralAtoms #OpticalTweezers #Qubits #QuantumErrorCorrection #AtomicPhysics #Caltech

Each dot in this image is a working quantum bit. Physicists at Caltech have just unveiled the world’s largest working array of quantum bits (qubits)—an astonishing grid of 6,100 individual cesium atoms, each precisely trapped using beams of laser light. These atoms, suspended in a vacuum by “optical tweezers,” serve as qubits, the basic building blocks of quantum computers. Unlike classical bits that are either 0 or 1, qubits can exist in both states at once, thanks to a property called superposition. This quantum weirdness gives such machines immense power—but also makes them delicate and error-prone. Caltech’s breakthrough pushes the boundaries by maintaining coherence for up to 13 seconds—ten times longer than previous systems—and achieving control accuracy above 99.98%. What sets this system apart isn't just its size, but its flexibility and stability at scale. The researchers showed that they could move atoms across the grid while preserving their quantum state, a major step toward creating fault-tolerant quantum computers. With previous atom-based arrays only holding hundreds of qubits, this leap to thousands—without losing quality—marks a critical milestone. The next phase is to entangle these qubits so they act in concert, enabling powerful quantum calculations. From simulating exotic materials to probing the nature of space-time, this platform could lay the foundation for the next era of computing. Source: Caltech. (2025). Caltech Team Sets Record with 6,100-Qubit Array. #leadership #skills #innovation