23 citations · 30 across the 12 of their papers we have counts for
12 papers
Absorbing Many-Body Correlations into Core-Optimized Orbitals
Hao Zhang, Matthew Otten
The cost of simulating quantum many-body systems - on classical or quantum hardware - scales with the number of variational parameters, so progress at fixed computational budget hi…
CANOE: Classically Assisted Non-Orthogonal Eigensolver
Jihyeon Park, Collin C. D. Frink, Matthew Otten
In the early fault-tolerant regime, where quantum resources remain limited, hybrid quantum-classical strategies offer one possible route toward quantum advantage. We introduce CANO…
Energy-Scaled Zero-Noise Extrapolation for Gottesman-Kitaev-Preskill Code
Gui-Zhong Luo, Matthew Otten
The performance of Gottesman-Kitaev-Preskill (GKP) codes, an approach to hardware-efficient quantum error correction, is limited by the finite squeezing capabilities of current exp…
First ionization potentials of Cr, Mo, and W calculated with SHCI
Zachary T. Jerzyk, David R. Smith, Matthew Otten
The design and performance of future fusion power plants will depend on accurate atomic data for plasma-facing material and plasma impurity species. A leading candidate for the pla…
Achieving Utility-Scale Applications through Full Stack Co-Design of Fault Tolerant Quantum Computers
Katerina Gratsea, Matthew Otten
Quantum computing promises revolutionary advances in modeling materials and molecules. However, the up-to-date runtime estimates for utility-scale applications on certain quantum h…
From Random Determinants to the Ground State
Hao Zhang, Matthew Otten
Accurate quantum many-body calculations often depend on reliable reference states or good human-designed ansätze, yet these sources of knowledge can become unreliable in hard probl…
Physics-Informed Neural Networks for Gate Design using Quantum Optimal Control
Sofiia Lauten, Matthew Otten
Implementing quantum gates on quantum computers can require the application of carefully shaped pulses for high-fidelity operations. We explore the use of physics-informed neural n…
A Versatile Variational Quantum Kernel Framework for Non-Trivial Classification
Jiang Yuhan, Matthew Otten
Quantum kernel methods are a promising branch of quantum machine learning, but their per- formance across data types and encoding choices remains incompletely understood. To addres…
Efficient algorithms for quantum chemistry on modular quantum processors
Tian Xue, Jacob P. Covey, Matthew Otten
Quantum chemistry is a promising application of future quantum computers, but the requirements on qubit count and other resources suggest that modular computing architectures will…
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…
Architecture for fast implementation of qLDPC codes with optimized Rydberg gates
C. Poole, T. M. Graham, M. A. Perlin +2
We propose an implementation of bivariate bicycle codes (Nature {\bf 627}, 778 (2024)) based on long-range Rydberg gates between stationary neutral atom qubits. An optimized layout…
Simulating Neutral Atom Quantum Systems with Tensor Network States
James Allen, Matthew Otten, Stephen Gray +1
In this paper, we describe a tensor network simulation of a neutral atom quantum system under the presence of noise, while introducing a new purity-preserving truncation technique…