Elements of Quantum Annealing (1)

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January 22, 2019

Elements of Quantum Annealing (1)

This slide is to learn English and presentation for me.
So, It might have some mistakes.
Contents:
1.1 Social background
1.2 Whai is Quantum Annealing ?
1.3 Purpose of Quantum Annealing
1.4 How to solve the optimization problem

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January 22, 2019
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  1. Elements of Quantum Annealing (1) Chapter 1 What is Quantum

    Annealing ? B3 English Seminar 2019/1/22 Nagaoka University of Technology Atom Yoshizawa
  2. References Hidetoshi Nishimori , Masayuki Ohzeki “Elements of Quantum Annealing”

    , Kyouritu Publishing Ltd. (2018) 2
  3. Contents 1.1 Social background 1.2 What is Quantum Annealing ?

    1.3 Purpose of Quantum Annealing 1.4 How to solve the optimization problem 3
  4. 1.1 Social background ◦ Problem 1 : The limits of

    transistor’s scale Moore's law : The number of transistors doubles every two years. However, It is becoming difficult to make the transistor small. ◦ Problem 2 : The increase in power consumption IT consumes 10% of the total electricity generation in the world. Especially the server uses huge amount of power. 4
  5. 1.1 Social background Qbit using superconductors use little power except

    small chips. Supercomputer K (京) 's power consumption is about 12 MW. On the other hand, the power consumption of the D-wave quantum annealing machine is about 20 kW. 5 Quantum annealing is an ecological computer.
  6. Two types of systems ◦ Quantum Gates Target issue :

    Generic quantum computation ◦ Quantum Annealing Target issue : Combinatorial optimization problems 6 1.2 What is Quantum Annealing Both systems use Qbit.
  7. Quantum Annealing is different from Quantum Gates in that quantum

    bits are always coupled to each other. Because noise acts on the entire system, it is smaller than it works individually. 7 1.2 What is Quantum Annealing Quantum Annealing is easy to operate stably. http://obeidlab.blogspot.com/2011/06/ising-model-quantum-mechanics-and-very.html
  8. Trends are beginning to use quantum annealing beyond combinatorial optimization

    problems. 8 1.3 Purpose of Quantum Annealing If Quantum Annealing is expanded, in principle it can be the same as the Quantum Gates and greatly speed up certain problems.
  9. The combination optimization problem is, a problem of minimizing or

    maximizing their single-valued cost function when there are many variables taking discrete values. Example : Ising model = − � < 𝑖𝑖 − � =1 ℎ = 1 , 2 , ⋯ , 9 1.4 How to solve the optimization problem
  10. The problem of finding the ground state of the Ising

    model belongs to the combinatorial optimization problem. Each Ising spin takes two values of ± 1. So, the total number of combinations is 2. 10 1.4 How to solve the optimization problem https://www.zaikei.co.jp/photo/237081.html
  11. How to solve the optimization problem. 1. Make the state

    of each spin quantum mechanically uncertain. Initial setting to take two states at the same time in the sense of quantum mechanics. 11 1.4 How to solve the optimization problem
  12. 2. Reduce quantum fluctuation and strengthen exchange interaction between spins

    𝑖𝑖 and the local magnetic field ℎ . Each Ising spin selects autonomously confirmed state. 3. Block quantum fluctuation. The ground state of Hamiltonian is chosen. 12 1.4 How to solve the optimization problem