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20152026
most citedManifold learning for parameter reduction

46 citations · 123 across the 20 of their papers we have counts for

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Showing 2025Show all

6 papers · 1 filter

quant-ph2025

Excising dead components in the surface code using minimally invasive alterations: A performance study

Ryan V. Mishmash, Vadym Kliuchnikov, Juan Bello-Rivas +7

The physical implementation of a large-scale error-corrected quantum processor will necessarily need to mitigate the presence of defective (thereby "dead") physical components in i…

quant-ph2025

A Topologically Fault-Tolerant Quantum Computer with Four Dimensional Geometric Codes

David Aasen, Matthew B. Hastings, Vadym Kliuchnikov +8

Topological quantum codes are intrinsically fault-tolerant to local noise, and underlie the theory of topological phases of matter. We explore geometry to enhance the performance o…

quant-ph2025

Repeated ancilla reuse for logical computation on a neutral atom quantum computer

J. A. Muniz, D. Crow, H. Kim +59

Quantum processors based on neutral atoms trapped in arrays of optical tweezers have appealing properties, including relatively easy qubit number scaling and the ability to enginee…

cs.LG2025

Towards Coordinate- and Dimension-Agnostic Machine Learning for Partial Differential Equations

Trung V. Phan, George A. Kevrekidis, Soledad Villar +2

The machine learning methods for data-driven identification of partial differential equations (PDEs) are typically defined for a given number of spatial dimensions and a choice of…

cs.LG2025

Generative Learning for Slow Manifolds and Bifurcation Diagrams

Ellis R. Crabtree, Dimitris G. Giovanis, Nikolaos Evangelou +2

In dynamical systems characterized by separation of time scales, the approximation of so called ``slow manifolds'', on which the long term dynamics lie, is a useful step for model…

quant-ph2025★ 5 cited

Roadmap to fault tolerant quantum computation using topological qubit arrays

David Aasen, Morteza Aghaee, Zulfi Alam +179

We describe a concrete device roadmap towards a fault-tolerant quantum computing architecture based on noise-resilient, topologically protected Majorana-based qubits. Our roadmap e…