AWS Quantum Technologies Blog

Martin Schuetz

Author: Martin Schuetz

Martin Schuetz is a Principal Research Scientist at the Amazon Quantum Solutions Lab. Martin has worked several years as an academic researcher with a focus on quantum simulation and computing, at ETH Zurich, the Max-Planck-Institute for Quantum Optics and Harvard University. Today Martin is working with customers to help solve some of their hardest problems, designing and building quantum computing, machine learning and optimization solutions on AWS.

JPMorgan Chase and AWS study the prospects for quantum speedups with near-term Rydberg atom arrays

JPMorgan Chase and AWS study the prospects for quantum speedups with near-term Rydberg atom arrays

Want the details on using quantum optimization for finance? New research from Amazon QSL and JPMorgan Chase maps out pathways to quantum advantage. Their post analyzes problem classes inspired by real-world use cases, setting the stage for impactful future experiments.

Combinatorial Optimization with Physics-Inspired Graph Neural Networks

Combinatorial optimization problems, such as the traveling salesman problem where we are looking for an optimal path with a discrete number of variables, are pervasive across science and industry. Practical (and yet notoriously challenging) applications can be found in virtually every industry, such as transportation and logistics, telecommunications, and finance. For example, optimization algorithms help […]

BMW robotic assembly line

Exploring industrial use cases in the BMW Group Quantum Computing Challenge

Today, the BMW Group launched a global open innovation challenge focused on discovering potential quantum computing solutions for real-world use cases: The BMW Group Quantum Computing Challenge. We are delighted to collaborate with BMW on this challenge, and to invite the quantum community explore new approaches to industrial applications. It’s still early days in quantum […]