245 citations · 783 across the 82 of their papers we have counts for
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Inverse Design of Quantum Control Sequences with Fourier Neural Operators
Anastasia Pipi, Valentin Duruisseaux, Emily Been +4
Quantum optimal control is a key tool for steering quantum dynamics, but its computational cost grows rapidly with the Hilbert space dimension. Here, we introduce a Fourier Neural…
Extending Quantum Perceptrons: Rydberg Devices, Multi-Class Classification, and Error Tolerance
Ishita Agarwal, Taylor L. Patti, Rodrigo Araiza Bravo +2
Quantum Neuromorphic Computing (QNC) merges quantum computation with neural computation to create scalable, noise-resilient algorithms for quantum machine learning (QML). At the co…
GPU-accelerated Effective Hamiltonian Calculator
Abhishek Chakraborty, Taylor L. Patti, Brucek Khailany +2
Effective Hamiltonian calculations for large quantum systems can be both analytically intractable and numerically expensive using standard techniques. In this manuscript, we presen…
Fourier Neural Operators for Learning Dynamics in Quantum Spin Systems
Freya Shah, Taylor L. Patti, Julius Berner +3
Fourier Neural Operators (FNOs) excel on tasks using functional data, such as those originating from partial differential equations. Such characteristics render them an effective a…
Elevating Variational Quantum Semidefinite Programs for Polynomial Objectives
Iria W. Wang, Robin Brown, Taylor L. Patti +3
Many practically important NP-hard optimization problems are inherently higher-order polynomial optimizations, which are typically addressed using approximation algorithms. Classic…
Towards large-scale quantum optimization solvers with few qubits
Marco Sciorilli, Lucas Borges, Taylor L. Patti +4
We introduce a variational quantum solver for combinatorial optimizations over binary variables using only qubits, with tunable . The number of parame…