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yes you are correct there is some missing information! This is known in the textbook and should be added in this PR. The reason is that the easiest way (I know of at least) to create a diffuser circuit is to actually create a circuit that inverts $|s\rangle$, instead of every state orthogonal to $|s\rangle$ as is required by the diffuser. I.e. we implement: $...


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(I'm unsure if you were asking for a derivation of the inner product, but hopefully this is insightful). Let's call the set of target states $T$. Recognize that, because $|\omega\rangle$ is the equal superposition of $ M$ states, each of the marked bitstrings will have a coefficient of $ \frac{1}{\sqrt{M}} $. For clarity, we can write: $$ | \omega \rangle = \...


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The circuit above is nothing but a bunch of matrix vector calculations of at most 32x32 elements. This is not hard for a classical computer to do. The quantum computer also has additional overhead, namely if your stuck in the queue, the circuit needs to be converted to waveforms, etc..


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While the URL of the API actually changed, it looks like all methods have remained the same. You can find a list of such methods in Practical Quantum Computing for Developers by Vladimir Silva, starting at page 101. Here are some examples of these methods: You have to log to your account: curl -d 'apiToken=API_TOKEN' 'https://api.quantum-computing.ibm.com/...


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You'e just experienced code transpilation. Transpilation is when source-to-source compilation takes place, as you have mentioned here. You can prevent the rearranging of the gates by using the "barriers", the Barrier operation is used to make your quantum program more efficient, the compiler will try to combine gates. The barrier is an instruction ...


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You might find some examples in this two-year-old question :) To the best of my knowledge, the most recent work that implements some code on IBMQ's quantum devices is about the repetition code (see the textbook or the paper). If you only want to do the simulation, there should be no problem to take a further step towards more advanced codes. But if you mean ...


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So any universal gate set can replicate any other, since both are universal, but different architectures generally have different physical gates. While Clifford+T is a universal gate set that is very nice to think about theoretically, it isn't generally close to the one used in the lab. In most experimental setups, the physical level universal gate set used ...


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The ibmq_qasm_simulator is a cloud-based simulator. You need to say from qiskit import IBMQ provider = IBMQ.load_account() sim = provider.backends.ibmq_qasm_simulator


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I'm not from IBM Q development team, but here is how I understand the problem: Qiskit's definition of $R_z$ gate coincides with the conventional definition used, for example, in M. Nielsen and I. Chuang's textbook (page 174): $$R_z(\theta) = \begin{pmatrix} e^{-i \theta/2} &0 \\ 0&e^{i \theta/2} \end{pmatrix}$$ The "problem" is not in the ...


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In the web based composer there is currently no way to adjust the optimization level. As a workaround, you can put a barrier before and after each gate. This will prevent them from being joined.


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When you transpile (either when calling execute or transpile), you should be able to set optimization_level=0 so the transpiler only maps the qubits to the backend. You can see an example here.


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I think its an error. If you want a poor temporary solution you can try to select the whole box starting at the big title Transpiled Circuit to the last code line. It will copy the line numbers together with the QASM code but I think it will be better than nothing.


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Optimization level 0 does not perform 1 qubit gate optimization and it will send 2 X gates (well 2 U3 gates after it unrolls to the basis set). You can see the passes optimization level 0 runs here: https://github.com/Qiskit/qiskit-terra/blob/master/qiskit/transpiler/preset_passmanagers/level0.py It will only map the circuit to the device and unroll the ...


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Could you point to the source? Your calculations seem correct, in Dirac notation: start with $|1\rangle \otimes |1\rangle$ apply H to each qubit: $|-\rangle \otimes |-\rangle = \frac12(|00\rangle - |01\rangle - |10\rangle + |11\rangle)$ Apply CZ: the sign of $|11\rangle$ changes, for the final result $\frac12(|00\rangle - |01\rangle - |10\rangle - |11\...


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Quantum machine learning can help you to enhance classical machine learning algorithms by outsourcing difficult calculations to a quantum computer. You can also optimise quantum algorithms using classical machine learning architectures. IBM researchers have developed a series of quantum algorithms that show how entanglement can improve AI classification ...


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For you first question, I do not think you can get the time_taken for each individual circuit that were sent bundled into one job. I believe, like you saw in your example, it will only show the time_taken to complete the entire job. For your second question, it is possible to queue multiple jobs without waiting for one of them to finish. The only blocker ...


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The documentation states that "All quantum systems are given a city name, e.g., ibmq_johannesburg. This name does not indicate where the actual quantum system is hosted." https://quantum-computing.ibm.com/docs/cloud/backends/configuration Some cities (e.g., Yorktown) host IBM Research centers.


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