Adiabatic quantum computation (AQC) relies on the adiabatic theorem to do calculations[1] and is closely related to quantum annealing[2][3][4][5]. First, a complex Hamiltonian is found whose ground state describes the solution to the problem of interest. Next, a system with a simple Hamiltonian is prepared and initialized to the ground state. Finally, the simple Hamiltonian is adiabatically evolved to the complex Hamiltonian. By the adiabatic theorem, the system remains in the ground state, so at the end the state of the system describes the solution to the problem.
AQC is a possible method to get around the problem of energy relaxation. Since the quantum system is in the ground state, interference with the outside world cannot make it move to a lower state. If the energy of the outside world (that is, the "temperature of the bath") is kept lower than the energy gap between the ground state and the next higher energy state, the system has a proportionally lower probability of going to a higher energy state. Thus the system can stay in a single system eigenstate as long as needed.
Universality results in the adiabatic model are tied to quantum complexity and QMA-hard problems. The k-local Hamiltonian is QMA-complete for k ≥ 2.[6] QMA-hardness results are known for physically realistic lattice modelsofqubits such as [7]
In practice, there are problems during a computation. As the Hamiltonian is gradually changed, the interesting parts (quantum behaviour as opposed to classical) occur when multiple qubits are close to a tipping point. It is exactly at this point when the ground state (one set of qubit orientations) gets very close to a first energy state (a different arrangement of orientations). Adding a slight amount of energy (from the external bath, or as a result of slowly changing the Hamiltonian) could take the system out of the ground state, and ruin the calculation. Trying to perform the calculation more quickly increases the external energy; scaling the number of qubits makes the energy gap at the tipping points smaller.
For a theoretical study of the performance of an adiabatic optimization processor see [10].
The D-Wave One is an adiabatic quantum computer made by a Canadian company D-Wave Systems. In 2011, Lockheed-Martin purchased one for about US$10 million; in May 2013, Google purchased a D-Wave Two with 512 qubits.[11]
{{cite arXiv}}: Unknown parameter |accessdate= ignored (help); Unknown parameter |version= ignored (help)CS1 maint: multiple names: authors list (link)
{{cite journal}}: Check |arxiv= value (help).
{{cite arXiv}}: |class= ignored (help); Unknown parameter |coauthors= ignored (|author= suggested) (help); Unknown parameter |journal= ignored (help); Unknown parameter |number= ignored (help); Unknown parameter |volume= ignored (help)
{{cite journal}}: Unknown parameter |coauthors= ignored (|author= suggested) (help)
|
| |||||||||
|---|---|---|---|---|---|---|---|---|---|
| General |
| ||||||||
| Theorems |
| ||||||||
| Quantum communication |
| ||||||||
| Quantum algorithms |
| ||||||||
| Quantum complexity theory |
| ||||||||
| Quantum processor benchmarks |
| ||||||||
| Quantum computing models |
| ||||||||
| Quantum error correction |
| ||||||||
| Physical implementations |
| ||||||||
| Quantum programming |
| ||||||||
| |||||||||
