Primitives | Coding with Qiskit 1.x | Programming on Quantum Computers

Join us in Episode 4 of "Coding with Qiskit 1.x" as Derek Wang dives deeper into Qiskit Primitives. The Estimator and Sampler primitives, for computing expectation values and sampling of quantum states, simplify interactions with quantum hardware. We'll use practical examples inspired by a pioneering IBM Quantum study featured in Nature.

Whether you're a quantum novice or enthusiast, this tutorial is for you. Like, subscribe, and tune in to expand your quantum programming toolkit!

Qiskit Resources:

#ibmquantum #learnquantum #qiskit

[jackburgess]

I ran into an error at 29:58 with the backend argument in Sampler. A fix for this is to write sampler = Sampler(backend) instead of sampler = Sampler(backend=backend)

[enriquantum]

Congratulations Derek for this excelent explanation! Regards from Argentina

[JHful]

Great video. Thanks. (Explanations and clarity are brilliant)

[andrewcursons]

My graph is a straight line on the 0 axis. Seems likely that the suvival_probability_list generation took the else clause on the try for all iterations!

[chisomodaka]

Hi Derek, this is amazing!!! I have one issue that I may need to get your insight into. At the moment I am trying to simulate strongly correlated (you may say maximally entangled) "physics" using the Sachdev-Ye-Kitaev (SYK) model on IBM QP. However, I noticed that in your Ising Model, the Hamiltonian was simulated sequentially (i.e. using trotter steps). In this case, I can not adopt a similar "sequential" approach for the SYK model - since I need to simulate the dynamical evolution of the Hamiltonian. So my question is... is there any way to simulate a dynamically evolving Hamiltonian on IBM QP? Or could there be an approach to mimic maximally entangled systems? Your feedback will be greatly appreciated

[dipanjanbera]

Hello sir in the last estimation technique, in post processing and plotting I got a value error of “x and y must have same first dimension, but you have shapes (1, ) and (9, )”
And I have another question that - any job id can I use which is already completed in ibm platform in post processing technique ?

[Destabilizator]

Instead of manually inverting the circuit, why cannot we simply do
qc_inversed = qc.inverse() # Invert the circuit
qc.compose(qc_inversed, inplace=True) # Connect original and inversed, qc will be modified
qc.draw(output='mpl', fold=-1)

(now this results in a bit of mess in the barriers, but that's still easier to solve than inversing all the functions)
Is it because it doesn't really know how to invert our custom gates?