I am trying to learn more on quantum computing on my own...I was feeling hopeless as I was not able to understand...and use to feel stuck.... your explanation is really good, I am able to to keep up with it,thank you so much
It was a great lecture about QAQA Algorithms. How do the data scientists and engineers work on Classical Information and Quantum Information in practical? I watched a documentary about Quantum Information which was incredible and complicated. Thanks for nice lecture.
Thank you Olivia, very good video! Just a question, I'm not sure but at minute 12:00 you showed the cost function hamiltonian for the 6 edges (each having two Z operators), but what happened with the terms bi Zi of the Hamiltonian Hc showed al minute 10:00?
This is not a quantum Hamiltonian. It is the classical Ising model. I don’t understand why a quantum computer is needed for this. Could you please comment?
So essentially the quantum adiabatic theorem is the key ingredient. It allows us to solve (approximately) for the ground state of a classical Ising model. Is this correct?
I haven't watched it yet. But it sounds like you're referring to the output of the quantum computer, which isn't the point really. The power of the quantum computer comes from it's ability to represent 2^N positions per q-bit in quantum memory. Quantum and multiprocessing classical computers both essentially do the same thing. The tradeoff is in the power it takes to run the stacks to represent the positions in memory.
@@MatrixVectorPSISo even classically the state space is 2^N when you have N bits. Quantum offers a way to constructively or destructively superpose the state space to get a desired output. In this example, the QC is used to solve for the ground state of an Ising model. This in turn gives the solution to a combinatorial optimization problem. Where exactly the advantage of quantum lies here is an open question I believe.
Can anyone explain why the CHSH inequalities violation *2022 Nobel prize* claims a correlation of "Alice and Bob" at 2.8. I don't think that's possible as I believe it to be a purely mathematical correlation and a correlation above 2 can never be physically measured per instance.
Used rustworkx not retworkx, and corrected the graph code graph: rx.PyGraph to graph = rxPyGraph def build_max_cut_paulis(graph = rx.PyGraph) -> list[tuple[str, float]]: """Convert the graph to Pauli list. Giskit 1.3.1
This stuff is gold. I love Olivia work on all these tutorials.
I am trying to learn more on quantum computing on my own...I was feeling hopeless as I was not able to understand...and use to feel stuck.... your explanation is really good, I am able to to keep up with it,thank you so much
Greetings from Turkey. Awesome video, awesome explanation!
An excellent lecture and tutorial, can't wait for the next one. Thanks Olivia, thanks IBM Q.
Hello. Thank you Olivia 🌺. Take very good care of yourself 🎉
Very good Lecture, will there be one for the VQE?
One of the 2 or 3 people I can actually understand the explanations on here!
Thanks thats awesome to hear!
It was a great lecture about QAQA Algorithms.
How do the data scientists and engineers work on Classical Information and Quantum Information in practical?
I watched a documentary about Quantum Information which was incredible and complicated.
Thanks for nice lecture.
Thank you for this informative and clarity
Thank you Olivia, very good video! Just a question, I'm not sure but at minute 12:00 you showed the cost function hamiltonian for the 6 edges (each having two Z operators), but what happened with the terms bi Zi of the Hamiltonian Hc showed al minute 10:00?
Thank you, great video.
Olivia, Great video. (Suggestion: In Runtime, try using shots=100 first then increase shots ?)
Are you stuck in the queue?
i have done the math and yes she is very Symmetrical
Great tutorial! Thanks for making this!
This is not a quantum Hamiltonian. It is the classical Ising model. I don’t understand why a quantum computer is needed for this. Could you please comment?
So essentially the quantum adiabatic theorem is the key ingredient. It allows us to solve (approximately) for the ground state of a classical Ising model. Is this correct?
I haven't watched it yet. But it sounds like you're referring to the output of the quantum computer, which isn't the point really. The power of the quantum computer comes from it's ability to represent 2^N positions per q-bit in quantum memory. Quantum and multiprocessing classical computers both essentially do the same thing. The tradeoff is in the power it takes to run the stacks to represent the positions in memory.
@@MatrixVectorPSISo even classically the state space is 2^N when you have N bits. Quantum offers a way to constructively or destructively superpose the state space to get a desired output. In this example, the QC is used to solve for the ground state of an Ising model. This in turn gives the solution to a combinatorial optimization problem. Where exactly the advantage of quantum lies here is an open question I believe.
@@abhay_cs I'm sure QC has more advantages than a power tradeoff. Measurement based applications in QC are intriguing.
where is the .ipynb?
Can anyone explain why the CHSH inequalities violation *2022 Nobel prize* claims a correlation of "Alice and Bob" at 2.8. I don't think that's possible as I believe it to be a purely mathematical correlation and a correlation above 2 can never be physically measured per instance.
Used rustworkx not retworkx, and corrected the graph code graph: rx.PyGraph to graph = rxPyGraph
def build_max_cut_paulis(graph = rx.PyGraph) -> list[tuple[str, float]]:
"""Convert the graph to Pauli list.
Giskit 1.3.1
Kiernan Shipka is who you looks like ,