Amazon Braket is a fully managed service that helps you get started with quantum computing by providing a development environment to explore and design quantum algorithms, test them on simulated quantum computers, and run them on your choice of different quantum hardware technologies.
Quantum computing has the potential to solve computational problems that are beyond the reach of classical computers by harnessing the laws of quantum mechanics to build more powerful tools for processing information. This approach to computing has the ability to transform areas such as energy storage, chemical engineering, material science, drug discovery, optimization, and machine learning. But defining those problems and programming quantum computers to solve them requires a new set of skills. At the same time, gaining access to quantum computing hardware to run your algorithms and optimize your designs can be expensive and inconvenient. This has made it difficult to evaluate the current state of the technology and plan for when to invest your resources to maximize its potential.
Amazon Braket helps overcome these challenges by providing a service that lets developers, researchers, and scientists explore, evaluate, and experiment with quantum computing. Amazon Braket lets you design your own quantum algorithms from scratch or choose from a set of pre-built algorithms. Once you define your algorithm, Amazon Braket provides a fully managed simulation service to help troubleshoot and verify your implementation. When you are ready, you can run your algorithm on your choice of different quantum computers, including gate based superconductor computers from Rigetti, quantum annealing superconductor computers from D-Wave, and ion trap computers from IonQ. To make it easier to develop hybrid algorithms that combine classical and quantum tasks, Amazon Braket helps manage classical compute resources and establish low-latency connections to the quantum hardware. With Amazon Braket you can explore quantum computing, evaluate its potential, and build expertise for the future.
Get started quickly
Amazon Braket provides a single environment to design, test, and run quantum algorithms without having to setup and manage infrastructure, negotiate access with multiple vendors, and write code to integrate different environments. Amazon Braket provides fully-managed Jupyter notebooks that you can use to explore possible applications, visualize your results, and optimize quantum algorithms. You can choose from notebooks with pre-installed developer tools, sample algorithms, and tutorials that make it easy to get started quickly.
Experiment with multiple technologies
Amazon Braket gives you access to a variety of different types of quantum computers, including gate based and quantum annealing superconductors, and ion trap hardware. Amazon Braket’s cross-platform developer tools provide a consistent experience so you don’t need to learn multiple development environments and makes it easy to work with different quantum hardware technologies to understand which physical implementation will best fit your applications.
Run hybrid quantum and classical algorithms
Amazon Braket makes it easy to run hybrid quantum algorithms that combine quantum operations with optimization and other processes running on classical compute instances. This allows you to create iterative systems that help mitigate the effect of errors inherent in todays’ quantum computing systems. Amazon Braket supports the execution of hybrid algorithms as fully managed jobs, orchestrating the necessary resources to maximize efficiency and reduce cost.
Get expert help
The Amazon Quantum Solutions Lab is a collaborative research program to help you accelerate the development of new quantum applications. The Quantum Solutions Lab connects you with quantum computing experts from Amazon and its technology and consulting partners to help you identify potential uses of quantum computing, build internal expertise, and collaborate on programs to design and test quantum algorithms.
How it works
Amazon Braket provides step-by-step guides, tutorials, and a resource library to help you get started quickly with quantum computing.
To design quantum algorithms, you can use fully managed Jupyter notebooks directly from the Amazon Braket console. Sample notebooks give you access to pre-installed developer tools, example algorithms, and documentation that makes it easy to get started.
Simulators running on classical hardware can be used to accelerate algorithm development by making it easy to troubleshoot code and optimize designs. Amazon Braket runs simulations as a fully managed service, automatically setting up the required compute instances, running the simulation, publishing results to Amazon S3, and turning off resources when complete.
You can execute your quantum algorithm on your choice of quantum hardware, paying only for the time that you use. If you chose to run hybrid quantum algorithms, Amazon Braket can automatically set up the required classical compute resources and manage the workflow between classical and quantum tasks.
After completion, you will be automatically notified and your results will be stored in Amazon S3. Amazon Braket publishes event logs and performance metrics such as completion status and execution time to Amazon CloudWatch.
Designing useful quantum applications requires new skills and potentially radically different approaches to problem solving. Building this expertise will take time and requires access to quantum technologies and programming tools. Amazon Braket help organizations begin exploring the potential of quantum computers today, and prepare for the future.
Simulation of quantum systems
Although many approximation methods have been introduced, simulating quantum systems in physics and chemistry still represents a significant challenge for classical computers. However, the unique features of quantum computers and the ability to natively manipulate quantum mechanical states creates the potential to efficiently solve important problems such as describing the electronic structure of molecules. Simulation of quantum systems will have broad applications including the design of new materials and catalysts, drug discovery, and the exploration of high-temperature superconductors.
Optimization problems are ubiquitous across many industries including telecommunications, supply chain logistics, and financial services. Finding the optimal approach from a set of alternatives can overwhelm classical systems as the number of possible combinations drives up complexity. Quantum computing can be used to address a wide range of these problems, for instance in the field of combinatorial optimization by accelerating linear programming algorithms and Monte Carlo methods. While future error-corrected quantum computers have provable speed-ups, near-term devices can be used to run heuristic algorithms which might already give an advantage.
Machine learning provides methods for systems to learn from data, identify patterns, and make decisions in an autonomous way. Scalable error-corrected quantum computers can improve many widely-used tools in machine learning including recommendation systems and support-vector machines for classification. Quantum computing also has the potential of offering a richer class of learning models. As data sets are typically very large, quantum machine learning will have limited impact in the near term. However early explorations might give useful insights about using future quantum hardware more effectively for machine learning.
Quantum Hardware Technologies
Gate-based, superconducting qubits
Superconducting qubits are built with superconducting electric circuits that operate at cryogenic temperature. Amazon Braket provides access to quantum hardware based on superconducting qubits from Rigetti.
Gate-based, ion traps
Trapped ion quantum computers implement qubits using electronic states of charged atoms called Ions. The Ions are confined and suspended in free space using electromagnetic fields. Amazon Braket provides access to ion trap quantum computers from IonQ.
Quantum annealing, superconducting qubits
Quantum annealing uses a physical process to find a low energy configuration that encodes the solution of an optimization problem. Amazon Braket provides access to quantum computers that use quantum annealing technology based on superconducting qubits from D-Wave.
Learn more about Amazon Braket
Instantly get access to the AWS Free Tier.
Sign up for the preview to get started