For more information, see Q program implementation. For example, if running the program on the full-state simulator , the simulator performs the corresponding mathematical operations to the simulated quantum system. But looking toward the future, when the target machine is a real quantum computer, calling such operations in Q will direct the quantum computer to perform the corresponding real operations on the real quantum hardware.
For example, in a trapped-ion quantum computer the quantum operations are realised by precisely timed laser pulses. A Q program recombines these operations as defined by a target machine to create new, higher-level operations to express quantum computation. In this way, Q makes it easy to express the logic underlying quantum and hybrid quantum—classical algorithms, while also being general with respect to the structure of a target machine or simulator. If you want to learn more, the Quantum Katas provide a good introduction to quantum computing concepts such as common quantum operations and how to manipulate qubits.
For more information, see the Q user guide. The Quantum Development Kit is a full-featured development kit for Q that you can use with common tools and languages to develop quantum applications that you can run in various environments. A Q program can compile into a standalone application, through Jupyter Notebooks, or be called by a host program that is written either in Python or a.
NET language. When you compile and run the program, it creates an instance of the quantum simulator and passes the Q code to it. The simulator uses the Q code to create qubits simulations of quantum particles and apply transformations to modify their state. The results of the quantum operations in the simulator are then returned to the program. Isolating the Q code in the simulator ensures that the algorithms follow the laws of quantum physics and can run correctly on quantum computers.
You use the same Q code for all steps of the workflow. In the short term you might have to tweak some portions of the code to account for the current hardware limitations. You can follow the Q tutorials and start writing quantum programs to explore superposition , entanglement , Grover's quantum algorithm , and other quantum phenomena.
The Q libraries will help you keep your code high-level, enabling you to run complex quantum operations without having to design low-level operation sequences. The Microsoft. Sdk NuGet package automatically includes the Q standard library , which provides a set of essential and very useful functions and operations that can be used when writing quantum programs in Q.
NET languages. You can also formulate optimization solutions with the Azure Quantum optimization Python package. As an additional feature, the QDK supports integration with Qiskit and Cirq , so quantum developers that are already working in other development languages, can also run their programs on Azure Quantum.
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There is no notion of a quantum state or a circuit; instead, Q implements programs in terms of statements and expressions, much like classical programming languages. The Q language guide provides a full specification and documentation of the Q quantum programming language. Quantum simulators documentation : Quantum simulators are software programs that run on classical computers and act as the target machine for a Q program, making it possible to run and test quantum programs on classical computers.
The Q library documentation : The Quantum Development Kit provides additional domain-specific functionality through NuGet packages that can be added to your Q projects. The documentation includes operations, functions, user-defined types, examples, and concepts that make up the standard Q library, as well as the quantum chemistry, quantum machine learning, and quantum numerics libraries.
Q is a stand-alone language offering a high level of abstraction. Distinct quantum capabilities such as support for functors and control-flow constructs facilitate expressing, for example, phase estimation and quantum chemistry algorithms. Q is hardware agnostic, meaning that the Q language provides the means to express and leverage powerful quantum computing concepts independent on how hardware evolves in the future.
To be useable across a wide range of applications, Q allows to build reusable components and layers of abstractions. To achieve performance with growing quantum hardware size, the Q quantum programming language ensures the scalability of both applications and development effort.
Even though the full complexity of such computations requires further hardware development, Q programs can be targeted to run on various quantum hardware backends in Azure Quantum.
The Q language is focused on expressing information to optimize execution. The goal is to ensure an efficient execution of quantum components, independent of the context within which they are invoked. Q allows the developer to communicate their knowledge about a computation so that the compiler can make an informed decision regarding how to translate it into instructions, leveraging information about the end-to-end application that is not available to the developer.
The type system permits Q programs to safely interleave and naturally represent the composition of classical and quantum computations. A Q program may express arbitrary classical computations based on quantum measurements that execute while qubits remain live, meaning they are not released and maintain their state.
Let's explore the general pieces that fit within a Q program. Consider the following Q program:. EntryPoint tells the Q compiler where to begin executing the program. The program prints this message:. Namespaces help you organize related functionality.
Their use becomes important when you use Q libraries in your programs and when you write your own libraries. Q makes extensive use of libraries. A library is a package that contains functions and operations that you can use in quantum programs.
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