Quantum Computing gate matricies

In summary, the conversation discusses the process of calculating a matrix for consecutive quantum gates, specifically when a CNOT gate is added after a hadamard gate. The expert advises to use matrix multiplication instead of addition and explains that the input state is multiplied by the hadamard and identity matrices before being input into the CNOT gate. This results in the final output state being equivalent to the matrix multiplication of the CNOT gate and the hadamard and identity matrices with the input state.
  • #1
Fixxxer125
41
0
Hi there
I am working through a quantum gate section of my course and I am a bit puzzled on how to calculate a matrix for consecutive quantum gates. I understand how to generate a matrix for

|q0⟩--------[H]-------
|q1⟩------------------
Which is simply the tensor product of the hadamard and identity matrix. However I am unsure what to do if the circuit is modified to be have a CNOT gate after the hadamard gate with the top qubit as the control and the bottom as a target. i have tried adding the matricies but this doesn't seem to work. Thanks for your time
 
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  • #2
You should do matrix multiplication(keeping in mind the order) not addition.

The matrices represent operations (hence operators) done on the state. So if we take the input state as |in>, have state after the above circuit is (H x I)|in>, which is then the input to CNOT gate. So finally you get |out>=CNOT((H x I)|in>) which is equivalent to matrix multiplication of CNOT with H x I and |in>
 
  • #3
Thanks for your help!
 

1. What is a quantum computing gate matrix?

A quantum computing gate matrix is a mathematical representation of the operations performed by quantum gates on qubits. It shows how the input qubits are transformed into output qubits through the application of specific quantum gates.

2. How are quantum computing gate matrices different from classical computing gate matrices?

Quantum computing gate matrices operate on qubits, which can exist in multiple states at once, while classical computing gate matrices operate on bits, which can only exist in one of two states (0 or 1) at a time. This allows quantum gate matrices to represent and manipulate a much larger range of information and perform more complex operations.

3. What are some commonly used quantum computing gate matrices?

Some commonly used quantum gate matrices include the Pauli gates (X, Y, Z), Hadamard gate, CNOT gate, and Toffoli gate. These gates are frequently used in quantum algorithms to perform operations such as flipping qubit states, creating superposition, and entangling qubits.

4. How are quantum computing gate matrices used in quantum algorithms?

Quantum gate matrices are used in quantum algorithms to perform operations on qubits and manipulate their states. They can also be combined to create larger circuits that perform more complex tasks, such as searching a database or factoring large numbers.

5. What challenges are associated with working with quantum computing gate matrices?

One of the main challenges with quantum gate matrices is maintaining the delicate state of qubits. Any external interference or errors in the gate operations can cause the qubits to lose their quantum properties, known as decoherence. This makes it difficult to build and maintain reliable quantum systems and perform accurate computations.

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