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From Demonstration of quantum volume 64 on a superconducting quantum computing system chapter IV on dynamical decoupling, we read: When quantum circuits are mapped to physical hardware, not all physical gates can be performed simultaneously. Gate execution-times can vary significantly, not only between single- and two-qubit gates, but also between ...


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Your code looks fine - I am afraid you just were out of luck - Bogota appears to have some problems today (24th Oct 2021 as of 11 PM EST). Try switching to a different backend, like ibmq-manila or ibmq-santiago. You can check a list of all backends available to you here. On a related note, I would sincerely recommend also playing with simpler circuits at ...


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IBM Quantum Systems are calibrated daily, and the system properties update once this calibration sequence is complete. It means that your noise model could change on a daily basis. More information in the documentation: https://quantum-computing.ibm.com/lab/docs/iql/manage/systems/properties https://quantum-computing.ibm.com/admin/docs/admin/calibration-jobs


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I expect you get the Noise Model from the calibrated data of the hardware, however I am not sure how often it is updated. I doubt that it is live or even daily. You can check the noise model by running noise_model._local_quantum_errors and noise_model._local_readout_errors For instance: device = provider.get_backend('ibmq_armonk') noise_model = NoiseModel....


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Based on the idea given by @Tristan Nemoz, you can do something like this in Qiskit code: from qiskit import QuantumRegister, ClassicalRegister, QuantumCircuit from numpy import pi qreg_q = QuantumRegister(1, 'q') creg_c = ClassicalRegister(1, 'c') circuit = QuantumCircuit(qreg_q, creg_c) circuit.h(qreg_q[0]) circuit.measure(qreg_q[0], creg_c[0]) circuit.h(...


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For surface codes, the syndrome measurements collapse the errors into either being $X$ or $Z$ errors. All Clifford gates have easy-to-compute commutation relations with $X$ and $Z$ gates. So the idea is not to actually correct the errors, since that would require more quantum operations which are difficult and error-prone, but to simply track the errors and ...


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As mentioned by @user47787 This is yet another case of floating-point representation error at the machine level. This behaviour is language agnostic and has nothing to do with Python or Numpy or Qiskit. Related Reads: A very old post on stackoverflow discussing this issue - Is Floating Point Math broken ? Python docs describing the same - Floating Point ...


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