Can a Qasm simulator generate a state vector?
If you’re using the QasmSimulator class from Aer it does not generate a state vector result. The statevector method you passed in as a backend option is the simulation method/technique that Aer will use for simulating the circuit, but it is still the QASM simulator which is expected to return measurement counts not a statevector.
What’s the difference between Qasm simulator and quantum?
The one thing that I noticed from the histograms is that the state with maximum probability for simulator was ‘11000’ and for quantum hardware, the state with maximum probability was ‘10000’. I think this difference is caused by the small shots number.
Where do I find the simulator in Qiskit?
The simulator we want is defined in the part of qiskit known as Aer. By giving the name of the simulator we want to the get_backend () method of Aer, we get the backend object we need. In this case, the name is ‘aer_simulator’.
Can a Qasm simulator be used as a backend option?
The statevector method you passed in as a backend option is the simulation method/technique that Aer will use for simulating the circuit, but it is still the QASM simulator which is expected to return measurement counts not a statevector. You can see a description of the different simulation methods in the QasmSimulator Docs.
How is qaoa used to solve combinatorial optimization problems?
QAOA takes the approach of classical approximate algorithms and looks for a quantum analogue that will likewise produce a classical bit string x ∗ that with high probability is expected to have a good approximation ratio α. Before discussing the details, let us first present the general idea of this approach.
How is qaoa different from Goemans-Williamson algorithm?
Unlike Goemans-Williamson algorithm, QAOA does not come with performance guarantees. QAOA takes the approach of classical approximate algorithms and looks for a quantum analogue that will likewise produce a classical bit string x ∗ that with high probability is expected to have a good approximation ratio α.
How to find the maximal string in qaoa?
We want to find the n-bit string x for which C(x) is the maximal. This cost function can be mapped to a Hamiltonian that is diagonal in the computational basis. Given the cost-function C this Hamiltonian is then written as where x ∈ {0, 1}n labels the computational basis states | x⟩ ∈ C2n.