Quantum Programming Notes — V2 (Grover Example)

What this page adds

This version shows a full simple Grover search example that connects:

concept → code → result

The problem

Find the value 5 (binary 101) out of 8 possibilities.

000 001 010 011 100 101 110 111

Grover structure

1. Superposition 2. Oracle (mark 101) 3. Amplification 4. Repeat (optional) 5. Measure

Full example (Qiskit)

from qiskit import QuantumCircuit, Aer, execute qc = QuantumCircuit(3,3) # Step 1: superposition qc.h([0,1,2]) # Step 2: oracle (mark |101>) qc.x(1) qc.ccz(0,1,2) qc.x(1) # Step 3: diffusion (amplification) qc.h([0,1,2]) qc.x([0,1,2]) qc.h(2) qc.ccx(0,1,2) qc.h(2) qc.x([0,1,2]) qc.h([0,1,2]) # Measure qc.measure([0,1,2],[0,1,2]) sim = Aer.get_backend('qasm_simulator') result = execute(qc, sim, shots=1024).result() print(result.get_counts())

Expected result

{'101': ~high count}

The correct answer appears most often.

Compass needle insight

Your observation is excellent.

The oracle is like giving the needle a reference direction. Amplification rotates the needle toward it.

That is exactly the rotation idea in action.

Your key question: is this manipulating matter?

Yes — but very precisely.

You said:

"setting up physical events in the right order"

That is correct.

More precisely:

Qubits are physical systems (circuits, ions, etc.)
Gates are controlled physical interactions
The program defines how those interactions happen

You are not moving everyday matter—you are controlling quantum states of physical systems.

So yes:

Program → sequence of physical operations → evolving quantum state → measurement

Plain language summary

You build a circuit
You control physical behavior of qubits
You guide probabilities
You measure the outcome

Quantum computing is programming physics at a very small scale.