Getting clear on what is meant by annealing!!
From the Merriam-Webster Dictionary:
From Wikipedia:
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As explained by Copilot:
qiskit; what is quantum annealing?
Quantum annealing is a quantum computing technique used to solve optimization problems by finding the global minimum of a given objective function. It leverages quantum fluctuations to explore the solution space more efficiently than classical methods.
Key Concepts
Quantum Fluctuations: Quantum annealing uses quantum fluctuations to escape local minima and find the global minimum of an objective function.
Objective Function: The function that needs to be minimized or maximized. In optimization problems, this function represents the cost or energy of a particular solution.
Hamiltonian: In quantum annealing, the problem is encoded into a Hamiltonian, which describes the energy landscape of the system.
Process
Initialization: The system starts in a superposition of all possible states.
Evolution: The system evolves according to the time-dependent Schrödinger equation, with the transverse field causing quantum tunneling between states.
Annealing: The transverse field is gradually reduced, allowing the system to settle into the ground state of the problem Hamiltonian, which corresponds to the optimal solution.
Applications
Quantum annealing is particularly useful for solving combinatorial optimization problems, such as the traveling salesman problem, scheduling, and finding the ground state of spin glasses.
D-Wave Annealing:
What is a D-Wave quantum computer?
A D-Wave quantum computer is a type of quantum computing system developed by D-Wave Systems, a company known for pioneering quantum annealing technology. Unlike traditional quantum computers that use gate-based models, D-Wave's quantum computers are designed specifically for solving optimization problems through quantum annealing.
Key Features of D-Wave Quantum Computers
Quantum Annealing: This is the primary method used by D-Wave quantum computers to find low-energy solutions to optimization problems. Quantum annealing leverages quantum fluctuations to explore the solution space and find the global minimum of an objective function.
Qubits: D-Wave's quantum processors use qubits, which are the quantum analogs of classical bits. These qubits can exist in a superposition of states, allowing the quantum computer to process a vast number of possibilities simultaneously.
Couplers and Biases: Qubits in a D-Wave system are connected by couplers, which allow them to influence each other. The couplers and qubit biases define the energy landscape of the problem being solved.
Applications: D-Wave quantum computers are particularly well-suited for solving combinatorial optimization problems, such as scheduling, logistics, portfolio optimization, and machine learning tasks.
How It Works
Initialization: The system starts with qubits in a superposition of all possible states.
Annealing Process: The system evolves according to the time-dependent Schrödinger equation, with the transverse field causing quantum tunneling between states.
Final State: At the end of the annealing process, the qubits collapse into classical states that represent the solution to the optimization problem.
Real-World Applications
D-Wave quantum computers have been used in various fields, including:
Logistics: Optimizing routes and schedules for transportation and delivery.
Drug Discovery: Accelerating the identification of potential drug candidates.
Machine Learning: Enhancing probabilistic models and improving training processes.
You can find more detailed information on the D-Wave Systems website.
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D-Wave is not IBM's approach, but this explanation is nonetheless very interesting:
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