AWS Quantum Technologies Blog
Author: Tim Chen
Yi-Ting (Tim) Chen is a scientist at Amazon Braket. He works on quantum verification, programming experience, and compilers. His past research focused on applying atom manipulation to study atomic physics and condensed matter physics, and on simulating quantum systems. He studied at Stanford University where he received his PhD in Applied Physics, and at National Taiwan University where he received his BS in Physics.
Experiment with dynamic circuits on IQM Garnet with Amazon Braket
Customers use Amazon Braket to design and run quantum algorithms to explore applications of quantum computing. As the complexity of research workloads matures, it is important to have access to innovative capabilities. In this blog post, we announce an expansion of Amazon Braket’s experimental capabilities by adding support for dynamic circuits on the IQM Garnet […]
Speeding up hybrid quantum algorithms with parametric circuits on Amazon Braket
Today, we’re announcing improvements to the task-processing speed and our support for parametric compilation on QPUs from Rigetti Computing in Amazon Braket. This enables up to 10x faster runtime performance for algorithms that use Amazon Braket Hybrid Jobs.
Amazon Braket now supports verbatim compilation and native gates with IonQ
As of 05/17/2023, the ARN of the IonQ Harmony device changed to arn:aws:braket:us-east-1::device/qpu/ionq/Harmony. Therefore, information on this page may be outdated. Learn more. Previously, when customers submitted a circuit to the IonQ device on Amazon Braket, the circuit was automatically compiled to native instructions. Today, we are extending the verbatim compilation feature to IonQ’s 11-qubit […]
Using embedded simulators in Amazon Braket Hybrid Jobs
Today, we launched a new feature in Amazon Braket Hybrid Jobs, which allows you to run hybrid workloads with simulators that are embedded with your algorithm code. For instance, one of the simulators available in this new feature is the PennyLane Lightning GPU simulator, accelerated by NVIDIA’s cuQuantum library. In this blog post, we show […]