activity
20242026
collaborators

18 papers

quant-ph2026

Observation of Improved Accuracy over Classical Sparse Ground-State Solvers using a Quantum Computer

William Kirby, Bibek Pokharel, Javier Robledo Moreno +25

Demonstrating quantum advantage over classical algorithms for ground state energy problems is an outstanding open problem in quantum computation. We experimentally demonstrate that…

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

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…

cs.ET2026

Scaling Sample-Based Quantum Diagonalization on GPU-Accelerated Systems using OpenMP Offload

Robert Walkup, Juha Jäykkä, Igor Pasichnyk +14

Hybrid quantum-HPC algorithms advance research by delegating complex tasks to quantum processors and using HPC systems to orchestrate workflows and complementary computations. Samp…

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…