Quantum Annealers: Quantum annealing is a specialized approach to quantum computing that focuses on solving optimization problems. Quantum annealers are quantum computing devices designed to implement this approach. They are typically based on qubits that can interact with each other and are programmed to find the lowest-energy state, or the optimal solution, of a given problem.
In terms of programming quantum annealers, you typically define an objective function that represents the optimization problem you want to solve. The objective function is formulated in a way that maps to the qubits and their interactions within the annealer. By setting up the problem and input parameters, you instruct the annealer to find the state with the lowest energy, which corresponds to the optimal solution.
Universal Quantum Computers: Universal quantum computers, unlike quantum annealers, are more versatile and can perform a wider range of quantum computations. They are designed to implement quantum gates, which are basic building blocks for manipulating qubits and performing complex quantum algorithms.
Programming universal quantum computers involves specifying quantum gates to perform operations on the qubits. Quantum algorithms are typically written in a programming language that supports quantum operations and quantum circuit representations. Some popular programming languages and frameworks for universal quantum computers include Qiskit, Cirq, and Forest (for Rigetti Quantum Computers).
In these programming languages, you can define and manipulate qubits, apply quantum gates to perform transformations, and perform measurements on the qubits to obtain results. Quantum algorithms, such as Shor's algorithm for factoring large numbers or Grover's algorithm for database search, are implemented by combining sequences of quantum gates and measurements in specific ways to achieve the desired computation.
It's worth noting that programming quantum computers, especially universal ones, is still an active area of research and development. The field is evolving, and new programming languages, frameworks, and methodologies are being developed to make quantum programming more accessible and efficient.