activity
20212025
most citedEarly Fault-Tolerant Quantum Computing

99 citations · 104 across the 5 of their papers we have counts for

collaborators

6 papers

quant-ph2025

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…

quant-ph2024★ 1 cited

OnionVQE Optimization Strategy for Ground State Preparation on NISQ Devices

Katerina Gratsea, Johannes Selisko, Maximilian Amsler +3

The Variational Quantum Eigensolver (VQE) is one of the most promising and widely used algorithms for exploiting the capabilities of current Noisy Intermediate-Scale Quantum (NISQ)…

quant-ph2024★ 2 cited

Comparing Classical and Quantum Ground State Preparation Heuristics

Katerina Gratsea, Jakob S. Kottmann, Peter D. Johnson +1

One promising field of quantum computation is the simulation of quantum systems, and specifically, the task of ground state energy estimation (GSEE). Ground state preparation (GSP)…

quant-ph2023★ 99 cited

Early Fault-Tolerant Quantum Computing

Amara Katabarwa, Katerina Gratsea, Athena Caesura +1

Over the past decade, research in quantum computing has tended to fall into one of two camps: near-term intermediate scale quantum (NISQ) and fault-tolerant quantum computing (FTQC…

quant-ph2022★ 2 cited

When to Reject a Ground State Preparation Algorithm

Katerina Gratsea, Chong Sun, Peter D. Johnson

In recent years substantial research effort has been devoted to quantum algorithms for ground state energy estimation (GSEE) in chemistry and materials. Given the many heuristic an…

cond-mat.dis-nn2021

Storage properties of a quantum perceptron

Aikaterini, Gratsea, Valentin Kasper +1

Driven by growing computational power and algorithmic developments, machine learning methods have become valuable tools for analyzing vast amounts of data. Simultaneously, the fast…