21 citations · 23 across the 16 of their papers we have counts for
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Predicting Resource Efficient Hamiltonian Decomposition for Continuous-Time Quantum Walk Simulations
Mostafa Atallah, Rebekah Herrman, Zain H. Saleem
Simulating a continuous-time quantum walk (CTQW) on a graph in the circuit model of quantum computing requires decomposing its Hamiltonian into terms that can be Trotterized into h…
Moment-Structured Block Encodings of Periodic Finite-Difference Operators
Jishnu Mahmud, Rebekah Herrman
Block encoding is the standard technique for accessing matrix data in quantum linear-algebra algorithms. Its implementation directly affects its subnormalization, which in turn con…
Explicit Block Encoding of Difference-of-Gaussian Operators on a Periodic Grid
Jishnu Mahmud, John Winship, Tom Lash +2
The Difference-of-Gaussian (DoG) is a widely used operator across applications, including image processing (feature and edge detection), quantum machine learning, and finite-differ…
Layer-wise QUBO-Based Training of CNN Classifiers for Quantum Annealing
Mostafa Atallah, Rebekah Herrman
Variational quantum circuits for image classification suffer from barren plateaus, while quantum kernel methods scale quadratically with dataset size. We propose an iterative frame…
A matching decomposition algorithm for simulating quantum walk Hamiltonians
Mostafa Atallah, Alvin Gonzales, Daniel Dilley +3
In this work, we present a new algorithm for generating quantum circuits that efficiently implement continuous time quantum walks on arbitrary simple sparse graphs. The algorithm,…
Efficient circuits for leaf-separable state preparation
Sunil Vittal, Anthony Wilkie, Nika Rastegari +2
Efficient state preparation is a challenging and important problem in quantum computing. In this work, we present a recursive state preparation algorithm that combines logarithmic-…