most citedQuantum Computing and Visualization Research Challenges and Opportunities

1 citations · 1 across the 5 of their papers we have counts for

collaborators

9 papers

quant-ph2026

Practical block encodings of matrix polynomials that can also be trivially controlled

Martina Nibbi, Filippo Della Chiara, Yizhi Shen +2

Quantum circuits naturally implement unitary operations on input quantum states. However, non-unitary operations can also be implemented through block encodings, where additional a…

quant-ph20261 cited

Quantum Computing and Visualization Research Challenges and Opportunities

E. Wes Bethel, Roel Van Beeumen, Talita Perciano

Quantum computing (QC) has experienced rapid growth in recent years with the advent of robust programming environments, readily accessible software simulators and cloud-based QC ha…

math.NA2025

Computing excited states with isometric tensor networks in two-dimensions

Alec Dektor, Runze Chi, Roel Van Beeumen +1

We present a new subspace iteration method for computing low-lying eigenpairs (excited states) of high-dimensional quantum many-body Hamiltonians with nearest neighbor interactions…

quant-ph2025

Quantum Krylov Algorithm for Szegö Quadrature

William Kirby, Yizhi Shen, Daan Camps +3

We present a quantum algorithm to evaluate matrix elements of functions of unitary operators. The method is based on calculating quadrature nodes and weights using data collected f…

quant-ph2025

Efficient LCU block encodings through Dicke states preparation

Filippo Della Chiara, Martina Nibbi, Yizhi Shen +1

With the Quantum Singular Value Transformation (QSVT) emerging as a unifying framework for diverse quantum speedups, the efficient construction of block encodings -- their fundamen…

quant-ph2025

From noisy observables to accurate ground state energies: a quantum classical signal subspace approach with denoising

Hardeep Bassi, Yizhi Shen, Harish S. Bhat +1

We propose a hybrid quantum-classical algorithm for ground state energy (GSE) estimation that remains robust to highly noisy data and exhibits low sensitivity to hyperparameter tun…