AWS Quantum Technologies Blog
Author: Mao Lin
Mao Lin is a Scientist at Amazon Braket. His past research focused on theoretical condensed matter physics, particularly topological phases of matter. He studied at University of Illinois where he received his PhD in Physics, and at National University of Singapore where he received his BS in Physics.
Thermodynamic sampling of disordered materials with an analog Hamiltonian Rydberg simulator
This post was contributed by Mao Lin, Bruno Camino, John Buckeridge and Scott M. Woodley Many advanced materials — from battery electrodes to semiconductor alloys — owe their useful properties to atomic-scale disorder. But predicting how atoms arrange themselves at a given temperature is hard: the number of possible configurations explodes combinatorially and sampling them […]
Reservoir computing on an analog Rydberg-atom quantum computer
This post shows how quantum reservoir computing (QRC) can tackle machine learning challenges using Rydberg-atom quantum computers. Readers will learn how QRC works, see its performance on image classification and time series prediction tasks, and understand when it outperforms classical methods—particularly for small datasets in pharmaceutical research. After decades of progress, machine learning (ML) has […]
Introducing Local Device Emulator for Verbatim Circuits on Amazon Braket
Today, we’re excited to announce the launch of local device emulator on Amazon Braket. This feature enables developers to emulate their verbatim circuits based on device calibration data. Local device emulation helps accelerate the development cycle by providing early feedback on circuit compatibility and expected behavior in the presence of noise. In this post, we […]
Analog Hamiltonian simulation with PennyLane
In this post, we’ll describe how the PennyLane-Braket SDK plugin to study the ground state of the anti-ferromagnetic Ising spin-chain on a 1D lattice on the Aquila quantum processor, a neutral-atom quantum computer available on-demand via the AWS Cloud.