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Quantum computers have the potential to perform computational tasks beyond the reach of classical machines. A prominent example is Shor’s algorithm for integer factorization and discrete logarithms, which is of both fundamental importance and practical relevance to cryptography. However, due to the high overhead of quantum error correction, optimized resource estimates for cryptographically relevant instances of Shor’s algorithm require millions of physical qubits. Here, by leveraging advances in high-rate quantum error-correcting codes, efficient logical instruction sets, and circuit design, we show that Shor's algorithm can be executed at cryptographically relevant scales with as few as 10,000 reconfigurable atomic qubits. Increasing the number of physical qubits improves time efficiency by enabling greater parallelism; under plausible assumptions, the runtime for discrete logarithms on the P-256 elliptic curve could be just a few days for a system with 26,000 physical qubits, while the runtime for factoring RSA-2048 integers is one to two orders of magnitude longer. Recent neutral-atom experiments have demonstrated universal fault-tolerant operations below the error-correction threshold, computation on arrays of hundreds of qubits, and trapping arrays with more than 6,000 highly coherent qubits. Although substantial engineering challenges remain, our theoretical analysis indicates that an appropriately designed neutral-atom architecture could support quantum computation at cryptographically relevant scales. More broadly, these results highlight the capability of neutral atoms for fault-tolerant quantum computing with wide-ranging scientific and technological applications.
The goal of this meeting is to bring together researchers from many-body dynamics, quantum information, and quantum computation. It will showcase recent advances in experimental platforms for controlling many-body quantum dynamics, as well as progress in...
Arjun is a PhD student at the University of Washington. His current interests are Quantum Circuit Complexity and State Synthesis lower bounds
This workshop will be build on recent insights about two types of approximations for CSPs – quantitative approximation (Max-CSPs) and qualitative approximation (Promise CSPs). Talks will be dedicated to the underlying techniques, including analytical...
Nicholas Kocurek is currently a graduate student at the University of Washington studying quantum complexity theory, constraint satisfaction problems, and the mixing of Markov chains.
Zixia Wei is currently at Harvard University, and his reseach explores the microscopic nature of gravity through the holographic principle and its connections to statistical physics, condensed matter physics, information theory, and computational theory...
Margarita Davydova is a postdoctoral scholar at Caltech. Her research broadly centers on complex behavior in many-body physical systems and quantum dynamics. She is interested in finding new ways to bridge concepts in mathematics, computer science, quantum...
Thomas Schuster is a Sherman Fairchild Postdoctoral Scholar at the California Institute for Technology, and a Visiting Researcher at Google Quantum AI. His research lies at the interface of quantum information science and quantum many-body physics. He...
Shankar Balasubramanian is currently at Caltech and his interests are broadly in quantum computation and information and their connections to theoretical physics.
Adam is currently a PhD student at MIT interested in quantum error correction and fault-tolerance. He has worked on more theoretical elements on quantum coding theory, and is increasingly interested in more practical realisations of these ideas that could...