7 papers
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…
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,…
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…
Investigating Different Barren Plateaus Mitigation Strategies in Variational Quantum Eigensolver
Mostafa Atallah, Nouhaila Innan, Muhammad Kashif +1
Variational Quantum Eigensolver (VQE) algorithms suffer from barren plateaus, where gradients vanish with system size and circuit depth. Although many mitigation strategies exist,…
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-…
An Exclusive-Sum-of-Products Pipeline for QAOA
Matthew Brunet, Shilpi Shah, Mostafa Atallah +2
The quantum approximate optimization algorithm is commonly used to solve combinatorial optimization problems. While unconstrained problems map naturally into the algorithm, incorpo…