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I'm currently reading the paper Classification with Quantum Neural Networks on Near Term Processors

It shows a method to determine the following quantity:

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Where U is a unitary operator acting on $|z,1\rangle$. The paper states the following: enter image description here enter image description here

I am wondering if there is a way to calculate any general inner product like $\langle z_2, 1|U|z, 1\rangle$ or just $\langle a | b \rangle $ in general? How could I modify the circuit to do so? (or is there a different methodology to calculate the inner product with different vectors?)

Martin Vesely
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Rehaan Ahmad
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1 Answers1

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We can use the SWAP test to determine the inner product of 2 states $|\phi\rangle$ and $|\psi\rangle$. The circuit is shown below SWAP Test Circuit

The state of the system at the beginning of the protocol is $|0\rangle \otimes |\phi \rangle \otimes |\psi \rangle$. After the Hadamard gate, the state of the system is $|+\rangle \otimes |\phi \rangle \otimes |\psi \rangle$.

The controlled SWAP gate transforms the state into $\frac{1}{\sqrt {2}}|0\rangle \otimes |\phi \rangle \otimes |\psi \rangle + |1\rangle \otimes |\psi \rangle \otimes |\phi \rangle$.

The second Hadamard gate results in $$\frac {1}{2}(|0\rangle|\phi\rangle|\psi\rangle +|1\rangle|\phi\rangle|\psi\rangle +|0\rangle|\psi\rangle|\phi\rangle -|1\rangle|\psi\rangle|\phi\rangle ) \\ =\frac {1}{2}|0\rangle (|\phi\rangle|\psi\rangle +|\psi\rangle|\phi\rangle)+ \frac{1}{2}|1\rangle(|\phi\rangle|\psi\rangle -|\psi\rangle|\phi \rangle)$$

The Measurement gate on the first qubit ensures that it's 0 with a probability of $P(\text{First qubit}=0)=\frac {1}{2}\Big(\langle\phi|\langle\psi| + \langle\psi|\langle\phi|\Big ) \frac {1}{2}\Big (|\phi\rangle|\psi\rangle + |\psi\rangle |\phi\rangle \Big )=\frac {1}{2}+\frac {1}{2}|\langle\psi|\phi\rangle|^{2}$ when measured.

The downside of this test is that the qubits cannot be recovered to the same state as before. Hence $|\psi\rangle,|\phi\rangle|$ must be prepared multiple times independently in order to get a good probability estimate and hence the value of inner product.

vasjain
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