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20172026
most citedTapering off qubits to simulate fermionic Hamiltonians

192 citations · 225 across the 10 of their papers we have counts for

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quant-ph2026

Polynomial-time exact diagonalization via sparse guided eigenwalks

Zachary E. Chin, Mario Motta, Javier Robledo Moreno +3

Computing quantum ground states is generically difficult, but additional structure can sometimes allow diagonalization to be recast as a more feasible problem. For example, when th…

quant-ph2026

Molecular Quantum Computations on a Protein

Akhil Shajan, Danil Kaliakin, Fangchun Liang +7

This work presents the implementation of a fragment-based, quantum-centric supercomputing workflow for computing molecular electronic structure using quantum hardware. The workflow…

quant-ph2026

Shallow-circuit Supervised Learning on a Quantum Processor

Luca Candelori, Swarnadeep Majumder, Antonio Mezzacapo +6

Quantum computing has long promised transformative advances in data analysis, yet practical quantum machine learning has remained elusive due to fundamental obstacles such as a ste…

quant-ph2025

Adiabatic state preparation from general initial states

Bryce Fuller, Mario Motta, Stuart M. Harwood +4

A variety of quantum computing algorithms exist for the preparation of approximate Hamiltonian ground states. A natural and important question is how these ground-state approximati…

quant-ph2025

Closed-loop calculations of electronic structure on a quantum processor and a classical supercomputer at full scale

Tomonori Shirakawa, Javier Robledo-Moreno, Toshinari Itoko +18

Quantum computers must operate in concert with classical computers to deliver on the promise of quantum advantage for practical problems. To achieve that, it is important to unders…

quant-ph2025

Quantum chemistry with provable convergence via randomized sample-based Krylov quantum diagonalization

Samuele Piccinelli, Alberto Baiardi, Stefano Barison +12

Quantum algorithms based on classical processing of individual samples have recently emerged as the most effective and robust methods to approximate ground-state wave functions of…