Quantum Circuit on networkx as a graph model

We usually design a quantum circuit on quantum computer. Basically the interface consists of the initial state of qubits as |0> and do quantum operation with quantum gate. And then finally we have measurement to finish the circuit.

Basically we have number of qubits to initialize, and then have a timeline as horizontal line.

The circuit is designed for the universal model of quantum computer to have a universal calculation.

Recently the quantum computer come to realize and sometimes new circuit implementation. For example google cirq has NISQ circuit for simulating hybrid algorithm.

And xanadu for photonics circuit. It has different type of circuit and gate set called continuous valuable.

Recently number of applications and algorithms are proposed to achieve much more better solutions comparing to the classical computer. Especially quantum chemistry and quantum physics is an advanced field of quantum computing applications.

And also the machine learning is coming to be a big topic in the field of the quantum computation these 2–3years.

How to design the quantum circuit and how to get better quantum state optimized are very important topic even for NISQ-era.

We usually working on quantum-classical hybrid system to get the quantum circuit shorter and get more efficient way to update parameters, especially angle parameter on variational method.

To get much better quantum circuit we have to learn linear algebra and quantum physics for many technique for solutions.

If we can have the quantum circuit as a graph model we an optimize the circuit itself using several algorithms.

We have,

Now we have graph model of quantum circuit. It is little bit messy and we can fix the position of initial quantum qubits position and the last measurement gate position.

With the graphical model we can develop a lot of applications suitable for the structure of the problem both on backend-side and application side.

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