Applications of Quantum Simulation in Physics Research

Today in Science Magazine, work from our IBM team, in collaboration with The University of Manchester, University of Oxford, ETH Zürich, EPFL and the University of Regensburg, shows the creation and simulation of a new molecule with an electronic structure that has never existed before — a half‑Möbius topology: https://lnkd.in/eFU5s9qR. The molecule was assembled using scanning probe microscopy at temperatures just above absolute zero — building it one atom at a time using STM, atom manipulation, and AFM. The electronic orbitals of this half‑Möbius molecule twist by 90 degrees with every loop around the ring, completing a full turn only after four revolutions. Why is this also important for quantum computing? This work demonstrates, for the first time, that quantum computing calculations can provide decisive scientific guidance and powerful characterization capabilities to support the discovery of new complex chemical molecules. In close collaboration with leading experimental laboratories, quantum simulations can now contribute directly to interpreting experimental observations and to guiding the design and understanding of novel molecular systems. The calculations performed in this project go well beyond the regime accessible to brute-force classical simulations, although we do not exclude the possibility that approximate classical methods could also provide valuable insights. Nevertheless, the discovery process itself benefited from quantum simulation, and we chose to employ quantum computing because it offers a natural and scalable framework for tackling problems of this kind. In particular, by comparing Dyson orbitals measured with scanning tunneling microscopy (STM) with images reconstructed from electronic structure calculations performed on a quantum computer using the SqDRIFT algorithm, we were able, for the first time, to contribute directly to the discovery and characterization of a new molecule exhibiting entirely novel electronic structure properties. paper: https://lnkd.in/esg9sHqV

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

The Schrödinger Equation Gets Practical: Quantum Algorithm Speeds Up Real-World Simulations Quantum computing has taken a major leap forward with a new algorithm designed to simulate coupled harmonic oscillators, systems that model everything from molecular vibrations to bridges and neural networks. By reformulating the dynamics of these oscillators into the Schrödinger equation and applying Hamiltonian simulation methods, researchers have shown that complex physical systems can be simulated exponentially faster on a quantum computer than with traditional algorithms. This breakthrough demonstrates not only a practical use of the Schrödinger equation but also the deep connection between quantum dynamics and classical mechanics. The study introduces two powerful quantum algorithms that reduce the required resources to only about log(N) qubits for N oscillators, compared to the massive computational demands of classical methods. This exponential speedup could transform fields such as engineering, chemistry, neuroscience, and material science, where coupled oscillators serve as the backbone of real-world modeling. By bridging theory and application, this research underscores how quantum computing is redefining problem-solving in physics and beyond. With proven exponential advantages and the ability to simulate systems once thought computationally impossible, this quantum algorithm marks a milestone in quantum simulation, Hamiltonian dynamics, and real-world physics applications. The findings point toward a future where quantum computers can accelerate scientific discovery, optimize engineering designs, and even open new frontiers in AI and computational neuroscience. #QuantumComputing #SchrodingerEquation #HamiltonianSimulation #QuantumAlgorithm #CoupledOscillators #QuantumPhysics #ComputationalScience #Neuroscience #Chemistry #Engineering

Quantum Computers Simulate Particle Creation in an Expanding Universe A new study published in Scientific Reports has successfully simulated particle creation in an expanding universe using IBM quantum computers, marking a significant step in digital quantum simulations of quantum field theory in curved spacetime (QFTCS). This research provides a new approach to studying quantum effects in curved spacetime without requiring a full quantum theory of gravity. Key Breakthroughs • Quantum Field Theory in Curved Spacetime (QFTCS): • This framework treats spacetime as a classical background while describing matter and force fields quantum mechanically. • It has predicted Hawking radiation from black holes and particle creation in expanding universes, but experimental verification has remained difficult. • First Digital Quantum Simulation of Expanding Spacetime: • While analog quantum simulations (e.g., Bose-Einstein condensates) have explored these phenomena, digital quantum computers had not been used until now. • IBM’s quantum computers successfully simulated particle creation, providing new computational methods for exploring cosmology. Why This Matters • A New Path for Quantum Gravity Research: Although a complete quantum theory of gravity is still elusive, this approach allows scientists to study quantum effects in general relativity-based spacetime models. • Advancing Quantum Computing in Physics: The research demonstrates how quantum computers can be used to explore fundamental questions about the universe, bridging the gap between cosmology and quantum mechanics. • Verifying Theoretical Predictions: Quantum simulations could help confirm or refine theories about the early universe, black holes, and quantum fluctuations. What’s Next? • Scaling Up Quantum Simulations: Future studies will aim to increase computational complexity and simulate more realistic spacetime conditions. • Exploring Black Hole Evaporation: Scientists may use quantum computers to model Hawking radiation more precisely, deepening our understanding of black hole thermodynamics. • Bridging the Gap Between Theory and Experiment: These digital simulations could provide new ways to test and refine cosmological theories, offering insights into early-universe physics and quantum gravitational effects. This study demonstrates the power of quantum computing in simulating cosmological phenomena, paving the way for new discoveries at the intersection of quantum mechanics and general relativity.

Exciting yet under-the-radar paper (arXiv:2506.10191) from Google Quantum AI on higher-order OTOCs (out-of-time-order correlators) -- a big leap toward practical (scientific) quantum advantage! 🚀 Using their Willow chip with ~100 qubits, they’ve shown remarkable result, yet it’s surprising this hasn’t sparked more buzz -- perhaps because OTOCs are tricky to explain to a wider audience. 🤔   Key Takeaways: 🕒 Quantum Speed: Willow chip solves quantum Hamiltonian properties in ~2.1 hours, using ~40 kWh of energy. 💻 Classical Lag: Best classical method (tensor networks) on Frontier supercomputer estimated to take 3.2 years, 550GWh energy—practically infeasible! 🧪 Real-World Impact: Enables learning properties of quantum materials, with applications in chemistry and quantum control. 10,000x reduction in needed energy for simulation.   This showcases power of NISQ-era quantum devices for quantum simulation. Shall we call it scientific quantum advantage? 📢 #QuantumComputing #QuantumAdvantage #GoogleQuantumAI

Physical Review X publication on realization of quantum spin liquids in Rydberg “quantum simulators” https://lnkd.in/e2qhT2WG There are many different spin liquids which are possible in principle, and roughly these are states where quantum fluctuations are so strong that they quantum-melt the ordered states (somewhat like thermal fluctuations melt crystals into classical liquids). Among the quantum spin liquid states, there are two distinct kinds: 1. rigid (“gapped”) states where it takes a finite energy to excite the system and 2. Truly liquid (“gapless”) phases which are a little bit like emergent electromagnetism where synthetic photons can freely fly around. An example of the former is Kitaev’s toric code, which also is the basis of many error correcting schemes. There have been no realizations of the latter (and Polyakov had shown long time ago that such states are only possible in 3 dimensions and higher). The present paper demonstrates that modern day quantum simulators, such as by Quera for example, can actually realize these quantum liquid states on 3D Rydberg graphs for the first time.

𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗺𝗲𝗻𝘁𝘀 𝗶𝗻 𝗾𝘂𝗮𝗻𝘁𝘂𝗺 𝘀𝗶𝗺𝘂𝗹𝗮𝘁𝗶𝗼𝗻𝘀 𝗮𝗿𝗲 𝗵𝗲𝗿𝗲! While many quantum hardware platforms aren't yet fully fault-tolerant, they can still function as analogue quantum simulators to address complex many-body problems. This paper explores this potential. 🚀🔬 🔍 𝗞𝗲𝘆 𝗛𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝘀: 𝗘𝗿𝗿𝗼𝗿 𝗦𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆: The paper introduces a novel, system-size independent notion of stability against extensive errors. This has been proven for Gaussian fermion models and a specific class of spin systems, indicating these models remain stable even with errors. 📊🛡️ 𝗖𝗿𝗶𝘁𝗶𝗰𝗮𝗹 𝗠𝗼𝗱𝗲𝗹 𝗦𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆: Remarkably, the analysis shows that critical models with long-range correlations also exhibit stability, suggesting robustness in systems with extensive interactions. 🌐💡 𝗤𝘂𝗮𝗻𝘁𝘂𝗺 𝗔𝗱𝘃𝗮𝗻𝘁𝗮𝗴𝗲 𝗣𝗼𝘁𝗲𝗻𝘁𝗶𝗮𝗹: The authors examine how this stability might lead to a quantum advantage for computing the thermodynamic limit of many-body models, even with a constant error rate and without explicit error correction. This could enable practical applications of quantum simulators in solving complex physical problems. 🧩🔗 Explore the details of this transformative research and its potential to shape the future of quantum simulations. 🌐✨ #QuantumComputing #QuantumSimulators #ManyBodyProblems #ResearchInnovation #QuantumAdvantage

A milestone in quantum physics — rooted in a student project What began as a student's undergraduate thesis at Caltech — later continued as a graduate student at MIT — has grown into a collaborative experiment between researchers from MIT, Caltech, Harvard, Fermilab, and Google Quantum AI. Using Google’s Sycamore quantum processor, the team simulated traversable wormhole dynamics — a quantum system that behaves analogously to how certain wormholes are predicted to work in theoretical physics. Here’s what they did: Implemented two coupled SYK-like quantum systems on the processor that represent black holes in a holographic model. Sent a quantum state into one system. Applied an effective “negative energy” pulse to make the simulated wormhole traversable. Observed the state emerge on the other side — consistent with quantum teleportation. This wasn’t just classical computer modeling — it ran on real qubits, using 164 two-qubit quantum gates across nine qubits. Why it matters: The results are consistent with the ER=EPR conjecture, which suggests a deep link between quantum entanglement and spacetime geometry. In the holographic picture, patterns of entanglement can be interpreted as wormhole-like “bridges.” This experiment shows how quantum processors can begin to probe aspects of quantum gravity in a laboratory setting, complementing astrophysical observations and theoretical work. While no physical wormhole was created, this is a step toward using quantum computers to explore some of the most fundamental questions in physics. What breakthrough in science excites you most? Share your thoughts below — and let’s discuss how quantum computing is reshaping our understanding of reality. ♻️ Repost to help people in your network. And follow me for more posts like this. CC: thebrighterside