10. Shor's algorithm II: From Factoring to Period-Finding, Writing the Quantum Program - Part 1
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- Опубликовано: 6 ноя 2024
- Lecturer: Abraham Asfaw
Lecture Notes and Labs: qiskit.org/lea...
#Qiskit
This course is an introduction to the world of quantum computing, with an exploration of some of the key quantum algorithms and their implementations using quantum circuits, as well as the quantum hardware that is designed to run these algorithms. The course was first offered during the Qiskit Global Summer School in July 2020 as a two-week intensive summer school.
thanks for the whole content, its amazing, so much brain excitation xD I love it, looking forward for the Summer School 2021 content
Hi, good content; congrats!! I’m looking for the qiskit code (general case) for the modular exponentiation subroutine. Do you know where to find it?
Check out this tutorial from the Community: github.com/qiskit-community/qiskit-community-tutorials/blob/master/algorithms/shor_algorithm.ipynb
Why is the screen blinking so much
At 34:46 in subtlely (1) you say "notice the 2 \pi i factor", but I do not see the factor in the outcome of the circuit. When you explained the relation between QPE and QFT you already explained that they where related (if QPE is thought as a function on the phase) by this factor, together with the power of 2 in the denominator (which is there in the output of the circuit). So I wonder why the factor 2 \pi i is not written in the output of the circuit. Is this a typo, or am I missing something significant?
One more comment: Around minute 14 there is formula for CROT_k for the case of two qbits, where the first qbit is set to 1, but I am not happy with this formula: it seems to me that the way it is written it introduces a phase into the "whole" second qbit x_j, but my understanding (coming from the unitary matrix describing it in the previous line) is that it should only affect the coefficient of 1 and not to the coefficient of 0 (the coefficients expressing x_j in the 0, 1 base). Thanks for the great lectures!
Thanks for the content
Well, I see now at minute 36 that it is QFT dagger (transpose conjugate) that you are applying here, not the inverse of QFT as in the previous lecture. Perhaps the two things are equivalent up to the 2 \pi i factor and if so this can be the answer to my previous question? . In any case, I have not seen in the previous lecture this dagger being used, perhaps it was explained in the labs and I have missed this. Problably it is just by some property (such as the fact that your matrices are unitary) that you simply can switch from "inverse" to "dagger" and that explains all.
For unitary operations, the transpose conjugate equals the inverse. (U-dagger = U-inverse) Abraham pointed that out in one of the previous lectures. My apologies that I don't have the timestamp for it. It was brought up at the same time that he said that for Hermetian operators, the transpose conjugate equals the original operator. (U-dagger = U)
How to construct a quantum circuit that performs addition modulo 2^n: |x⟩ ⊗ |y⟩ → |x + y mod 2^n⟩ ⊗ |y⟩.?
Can I still join the discord server, if yes, could someone please share me the link? Thank you
letters r very small, not seen clearly from the screen 😐