Efficiently Embedding QUBO Problems on Adiabatic Quantum … · 2018. 10. 11. · Efficiently Embedding QUBO Problems on Adiabatic Quantum Computers Prasanna Date PhD Candidate Department

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Efficiently Embedding QUBO Problems on Adiabatic Quantum Computers

Prasanna Datehttps://prasannadate.github.io

PhD CandidateDepartment of Computer Science

Rensselaer Polytechnic Institute (RPI)Advisor: Prof. Chris Carothers

datep@rpi.edu

ASTRO Intern (Jan-Aug, 2018)Computational Data Analytics (CDA) Group

Oak Ridge National Laboratory (ORNL)Mentor: Dr. Robert Patton

datep@ornl.gov

Quantum Computing with D-Wave

Prasanna Date | datep@rpi.edu | prasannadate.github.io 2

End of Moore’s Law

Rise of Machine Learning and Deep Learning

Neuromorphic Computing

Quantum Computing

Universal Quantum

Computing

Adiabatic Quantum

Computing

Quantum Computing with D-Wave

Prasanna Date | datep@rpi.edu | prasannadate.github.io 3

End of Moore’s Law

Rise of Machine Learning and Deep Learning

Neuromorphic Computing

Quantum Computing

Universal Quantum

Computing

Adiabatic Quantum

Computing

Can quantum computers be used for machine learning?

Quantum Computing with D-Wave

Prasanna Date | datep@rpi.edu | prasannadate.github.io 4

End of Moore’s Law

Rise of Machine Learning and Deep Learning

Neuromorphic Computing

Quantum Computing

Universal Quantum

Computing

Adiabatic Quantum

Computing

Can quantum computers be used for machine learning?

What can the D-Wave do?

The QUBO Problem

Prasanna Date | datep@rpi.edu | prasannadate.github.io 5

min$ ∈ {'(,*(},

-./- + -.1 + 2

QUBO = Quadratic Unconstrained Binary Optimization

The QUBO Problem

Prasanna Date | datep@rpi.edu | prasannadate.github.io 6

min$ ∈ {'(,*(},

-./- + -.1 + 2

QUBO = Quadratic Unconstrained Binary Optimization

NP Hard !!!

Embedding

Prasanna Date | datep@rpi.edu | prasannadate.github.io 7

What is Embedding?

Prasanna Date | datep@rpi.edu | prasannadate.github.io 8

Traveling Salesman Problem (TSP)

Airline Scheduling Problem

Protein Folding Problem

Node Packing Problem

Any NP Hard Problem

QUBO Problem D-Wave Hardware

min% ∈ {(),+)}-

./0. + ./2 + 3

EMBEDDING

What is Embedding?

Prasanna Date | datep@rpi.edu | prasannadate.github.io 9

QUBO Problem D-Wave Hardware

min$ ∈ {'(,*(},

-./- + -.1 + 2

EMBEDDING

NP Hard Problem

REDUCTION

Why is Embedding hard?

Prasanna Date | datep@rpi.edu | prasannadate.github.io 10

0 120 0

Why is Embedding hard?

Prasanna Date | datep@rpi.edu | prasannadate.github.io 11

0 120 0

Why is Embedding hard?

Prasanna Date | datep@rpi.edu | prasannadate.github.io 12

0 120 0

0 120 0

1321

0 0 0

Why is Embedding hard?

Prasanna Date | datep@rpi.edu | prasannadate.github.io 13

0 120 0

0 120 0

1321

0 0 0

Why is Embedding hard?

Prasanna Date | datep@rpi.edu | prasannadate.github.io 14

0 120 0

0 120 0

1321

0 0 0

0 120 0

13 1423 24

0 00 0

0 340 0

Why is Embedding hard?

Prasanna Date | datep@rpi.edu | prasannadate.github.io 15

0 120 0

0 120 0

1321

0 0 0

0 120 0

13 1423 24

0 00 0

0 340 0

Why is Embedding hard?

Prasanna Date | datep@rpi.edu | prasannadate.github.io 16

0 120 0

0 120 0

1321

0 0 0

0 120 0

13 1423 24

0 00 0

0 340 0

0 12 130 0 230 0 0

14 1524 2534 35

0 0 00 0 0

0 450 0

Why is Embedding hard?

Prasanna Date | datep@rpi.edu | prasannadate.github.io 17

0 120 0

0 120 0

1321

0 0 0

0 120 0

13 1423 24

0 00 0

0 340 0

0 12 130 0 230 0 0

14 1524 2534 35

0 0 00 0 0

0 450 0

Why is Embedding hard?

Prasanna Date | datep@rpi.edu | prasannadate.github.io 18

!" !# !$ !% !& !'

( =

0 12 130 0 230 0 0

14 15 1624 25 2634 35 36

0 0 00 0 00 0 0

0 45 460 0 560 0 0

!"!#!$!%!&!'

Why is Embedding hard?

Prasanna Date | datep@rpi.edu | prasannadate.github.io 19

!" !# !$ !% !& !'

( =

0 12 130 0 230 0 0

14 15 1624 25 2634 35 36

0 0 00 0 00 0 0

0 45 460 0 560 0 0

!"!#!$!%!&!'

What makes a GOOD Embedding Algorithm?

• Time: Should run as fast as possible• Qubit Footprint: Should as few qubits as possible• Accuracy: Should get the objective function value as close to the

global minima as possible

Prasanna Date | datep@rpi.edu | prasannadate.github.io 20

Embedding Algorithm Comparison

• Compared my algorithm to D-Wave’s algorithm• Criteria for comparison:• Embedding Time• Qubit Footprint• Accuracy

• Generated problems synthetically, while ensuring at least one global minima

Prasanna Date | datep@rpi.edu | prasannadate.github.io 21

Embedding Algorithm Comparison: Time

Prasanna Date | datep@rpi.edu | prasannadate.github.io 22

QUBO Problem:

min$ ∈ {'(,*(},

-./- + -.1 + 2

Embedding Algorithm Comparison: Qubit Footprint

Prasanna Date | datep@rpi.edu | prasannadate.github.io 23

QUBO Problem:

min$ ∈ {'(,*(},

-./- + -.1 + 2

30% Less Qubits!!!

Embedding Algorithm Comparison: Accuracy

Prasanna Date | datep@rpi.edu | prasannadate.github.io 24

QUBO Problem:

min$ ∈ {'(,*(},

-./- + -.1 + 2

Other Metrics

• Longest qubit chain length• Number of bit flips from

globally optimal solution

Prasanna Date | datep@rpi.edu | prasannadate.github.io 25

Conclusion

• Quantum Computing with D-Wave• Efficient Embedding Algorithm for D-Wave• Other Work: Quantum Machine Learning

Prasanna Date | datep@rpi.edu | prasannadate.github.io 26

Thank You!Prasanna Date

https://prasannadate.github.io

PhD CandidateDepartment of Computer Science

Rensselaer Polytechnic Institute (RPI)datep@rpi.edu

ASTRO Intern (Jan-Aug, 2018)Computational Data Analytics (CDA) Group

Oak Ridge National Laboratory (ORNL)datep@ornl.gov

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