17 citations · 32 across the 11 of their papers we have counts for
10 papers · 1 filter
Temporal information processing on a 4,500-qubit quantum annealer
Antonio Sannia, Roberto Menta, Pratik Sathe +7
Quantum machine learning could uncover statistical structure beyond the reach of classical models, but this requires quantum models large and expressive enough to be useful and che…
Quantum Approximate Optimization via Noise-Directed Adaptive Warm-Starting
Filip B. Maciejewski, Stuart Hadfield, Oscar Wallis +5
Progress towards a quantum advantage using known heuristic methods for combinatorial optimization is impeded by hardware noise and limited qubit count. Here, we propose a noise-awa…
Noise-Directed Adaptive Remapping for Integer Optimization: from qubits to (encoded) qudits
Stuart Hadfield, Filip B. Maciejewski, Davide Venturelli
We extend Noise-Directed Adaptive Remapping (NDAR), a recently proposed heuristic meta-algorithm that leverages device noise as a computational resource, to optimization problems o…
Quantum Sensing using Geometrical Phase in Qubit-Oscillator Systems
Nishchay Suri, Zhihui Wang, Tanay Roy +2
We present a quantum sensing protocol for coupled qubit-oscillator systems that surpasses the standard quantum limit (SQL) by exploiting a geometrical phase. The signal is encoded…
From quantum feature maps to quantum reservoir computing: perspectives and applications
Casper Gyurik, Filip Wudarski, Evan Philip +5
We explore the interplay between two emerging paradigms: reservoir computing and quantum computing. We observe how quantum systems featuring beyond-classical correlations and vast…
How to Build a Quantum Supercomputer: Scaling from Hundreds to Millions of Qubits
Masoud Mohseni, Artur Scherer, K. Grace Johnson +48
In the span of four decades, quantum computation has evolved from an intellectual curiosity to a potentially realizable technology. Today, small-scale demonstrations have become po…
A Multilevel Approach For Solving Large-Scale QUBO Problems With Noisy Hybrid Quantum Approximate Optimization
Filip B. Maciejewski, Bao Gia Bach, Maxime Dupont +5
Quantum approximate optimization is one of the promising candidates for useful quantum computation, particularly in the context of finding approximate solutions to Quadratic Uncons…
Assessing and Advancing the Potential of Quantum Computing: A NASA Case Study
Eleanor G. Rieffel, Ata Akbari Asanjan, M. Sohaib Alam +20
Quantum computing is one of the most enticing computational paradigms with the potential to revolutionize diverse areas of future-generation computational systems. While quantum co…
Improving Quantum Approximate Optimization by Noise-Directed Adaptive Remapping
Filip B. Maciejewski, Jacob Biamonte, Stuart Hadfield +1
We present Noise-Directed Adaptive Remapping (NDAR), a heuristic algorithm for approximately solving binary optimization problems by leveraging certain types of noise. We consider…
Uniformly Decaying Subspaces for Error Mitigated Quantum Computation
Nishchay Suri, Jason Saied, Davide Venturelli
We present a general condition to obtain subspaces that decay uniformly in a system governed by the Lindblad master equation and use them to perform error mitigated quantum computa…