Canary Foundation at Stanford
D-Wave Systems
Murray Thom
February 27th, 2017
Introduction to Quantum Computing
Copyright © D-Wave Systems Inc. 3
Copyright © D-Wave Systems Inc. 4
Richard FeynmanRichard FeynmanRichard FeynmanRichard Feynman
1960 1970 1980 1990 2000 2010 2020
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Quantum Turing MachineQuantum Turing MachineQuantum Turing MachineQuantum Turing Machine
1950 1960 1970 1980 1990 2000 2010
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Quantum Annealing Outlined by Tokyo TechQuantum Annealing Outlined by Tokyo TechQuantum Annealing Outlined by Tokyo TechQuantum Annealing Outlined by Tokyo Tech
PHYSICAL REVIEW E VOLUME 58, NUMBER 5 NOVEMBER 1998
Quantum annealing in the transverse Ising model
Tadashi Kadowaki and Hidetoshi NishimoriDepartment of Physics, Tokyo Institute of Technology, Oh-okayama,
Meguro-ku, Tokyo 152-8551, Japan
(Received 30 April 1998)
We introduce quantum fluctuations into the simulated annealing process of
optimization problems, aiming at faster convergence to the optimal state. Quantum
fluctuations cause transitions between states and thus play the same role as thermal
fluctuations in the conventional approach. The idea is tested by the transverse Ising
model, in which the transverse field is a function of time similar to the temperature in
the conventional method. The goal is to find the ground state of the diagonal part of
the Hamiltonian with high accuracy as quickly as possible. We have solved the time-
dependent Schrödinger equation numerically for small size systems with various
exchange interactions. Comparison with the results of the corresponding classical
(thermal) method reveals that the quantum annealing leads to the ground state with
much larger probability in almost all cases if we use the same annealing schedule.
[S1063-651X~98!02910-9]
1960 1970 1980 1990 2000 2010 2020
https://upload.wikimedia.org/wikipedia/commons/thumb/1/12/Quant-annl.jpg/300px-Quant-annl.jpg
Copyright © D-Wave Systems Inc. 7
DDDD----Wave Announces 16 Qubit QCWave Announces 16 Qubit QCWave Announces 16 Qubit QCWave Announces 16 Qubit QC
1960 1970 1980 1990 2000 2010 2020
D-Wave Progression
• By 2004 it had become apparent that creating good ideas about quantum computing and looking externally for a research team to use this knowledge to build such a machine wouldn't work. So we decided to do it ourselves. We built our own fabrication facility - a superconducting electronics foundry - to produce the processors required to use quantum effects to compute. We assembled a team of scientists to design, fabricate, and test the processors in our own in-house labs.
• In 2010 we released our first commercial system, the D-Wave One™ quantum computer. We have doubled the number of qubits each 18 months, and in 2013 we shipped our 512-qubit D-Wave Two™ system. In 2015 we announced general availability of the 1000+ qubit D-Wave 2X™ system.
QC Models
Copyright © D-Wave Systems Inc. 9
Quantum Information ScienceQuantum Information ScienceQuantum Information ScienceQuantum Information Science
Quantum
Computing
Gate Model
Annealing
Topological
One-way/ cluster state
Quantum Cryptography
Quantum key distribution
Quantum Sensor
Quantum information processing
Quantum CommunicationEmerging
Emerging
Copyright © D-Wave Systems Inc. 10
What is a Quantum Computer? What is a Quantum Computer? What is a Quantum Computer? What is a Quantum Computer?
• Exploits quantum mechanical effects
• Built with “qubits” rather than “bits”
• Operates in an extreme environment
• Enables quantum algorithms to solve
very hard problems
Quantum Processor
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Gate Model Quantum ComputingGate Model Quantum ComputingGate Model Quantum ComputingGate Model Quantum Computing
http://www.nature.com/nature/journal/v414/n6866/images/414883a-f1.2.jpg
Copyright © D-Wave Systems Inc. 12
Quantum Annealing (T=0, N=0)Quantum Annealing (T=0, N=0)Quantum Annealing (T=0, N=0)Quantum Annealing (T=0, N=0)en
ergy
leve
ls
Sol
utio
n
Initi
al s
tate
10 s
HS(t) = (1−s)HI + sHP , s = t/tf
Copyright © D-Wave Systems Inc. 13
Quantum Annealing (+ Thermal Noise)Quantum Annealing (+ Thermal Noise)Quantum Annealing (+ Thermal Noise)Quantum Annealing (+ Thermal Noise)en
ergy
leve
ls
P0
kBT
System Bath Interaction
10
Dynamical freeze-out
s
SBBS HHtHtH ++= )()(
Copyright © D-Wave Systems Inc. 14
Topological Quantum ComputingTopological Quantum ComputingTopological Quantum ComputingTopological Quantum Computing
https://static1.squarespace.com/static/51ee6559e4b06fd80f3cb11e/t
/520540fce4b00fb5186e572f/1376076030364/SteveSimon_800_320.jpg
• Microsoft Research
• TU Delft
• And others
Anyons
Non-Abelian Anyons
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Photonic/OpticalPhotonic/OpticalPhotonic/OpticalPhotonic/Optical
• University of Bristol
• And others
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Trapped IonsTrapped IonsTrapped IonsTrapped Ions
• Oxford
• UofSussex
• UofMD
• Innsbruck
• And others
http://www.nature.com/nature/journal/v464/n7285/images/nature08812-f3.2.jpg
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SiliconSiliconSiliconSilicon----based devicesbased devicesbased devicesbased devices
• Intel
• University of New South Wales
• TU Delft
• And others
https://www.engineering.unsw.edu.au/news/quantum-computing-first-two-qubit-logic-gate-in-silicon
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Superconducting QubitsSuperconducting QubitsSuperconducting QubitsSuperconducting Qubits
• D-Wave Systems
• MIT-LL/IARPA
• IBM
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DDDD----Wave qubit count has grown exponentiallyWave qubit count has grown exponentiallyWave qubit count has grown exponentiallyWave qubit count has grown exponentially
Qubits(log scale)
‘04 ‘08 ‘12 ‘16
D-Wave One
128
D-Wave Two
512
28
16
4
D-Wave 2X
1000
1
10
100
1,000
10,000
D-Wave 2000Q
2000
‘18‘06 ‘10 ‘14
Next Gen
9
2
Gate
Model
Quantum Annealing
Copyright © D-Wave Systems Inc. 22
• Space of solutions defines an energy landscape & best solution is lowest valley
• Classical algorithms must walk over this landscape
• Quantum annealing uses quantum effects to go through the mountains
Energy LandscapeEnergy LandscapeEnergy LandscapeEnergy Landscape
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Quantum Effects on DQuantum Effects on DQuantum Effects on DQuantum Effects on D----Wave SystemsWave SystemsWave SystemsWave Systems
Superposition
Entanglement
Quantum Tunneling
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Quantum Turing MachineQuantum Turing MachineQuantum Turing MachineQuantum Turing Machine
1950 1960 1970 1980 1990 2000 2010
Copyright © D-Wave Systems Inc. 25
Quantum Annealing Outlined by Tokyo TechQuantum Annealing Outlined by Tokyo TechQuantum Annealing Outlined by Tokyo TechQuantum Annealing Outlined by Tokyo Tech
PHYSICAL REVIEW E VOLUME 58, NUMBER 5 NOVEMBER 1998
Quantum annealing in the transverse Ising model
Tadashi Kadowaki and Hidetoshi NishimoriDepartment of Physics, Tokyo Institute of Technology, Oh-okayama, Meguro-ku, Tokyo 152-
8551, Japan
(Received 30 April 1998)
We introduce quantum fluctuations into the simulated annealing process of optimization problems, aiming at
faster convergence to the optimal state. Quantum fluctuations cause transitions between states and thus play
the same role as thermal fluctuations in the conventional approach. The idea is tested by the transverse Ising
model, in which the transverse field is a function of time similar to the temperature in the conventional method.
The goal is to find the ground state of the diagonal part of the Hamiltonian with high accuracy as quickly as
possible. We have solved the time-dependent Schrödinger equation numerically for small size systems with
various exchange interactions. Comparison with the results of the corresponding classical (thermal) method
reveals that the quantum annealing leads to the ground state with much larger probability in almost all cases if
we use the same annealing schedule.
[S1063-651X~98!02910-9]
1960 1970 1980 1990 2000 2010 2020
Copyright © D-Wave Systems Inc. 26
Making Use of Quantum StatesMaking Use of Quantum StatesMaking Use of Quantum StatesMaking Use of Quantum States
By Peppergrower - Own work, CC BY-SA 3.0,
https://commons.wikimedia.org/w/index.php?curid=6007495
1
0
Gate
Model
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Making Use of Quantum StatesMaking Use of Quantum StatesMaking Use of Quantum StatesMaking Use of Quantum States
1
0
Quantum
Annealing
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Quantum Enhanced OptimizationQuantum Enhanced OptimizationQuantum Enhanced OptimizationQuantum Enhanced Optimization
Quantum Hamiltonian is an operator on Hilbert space:
ℋ � = ℰ � ����
�� +���
�
�� � + Δ � ���
�
�
Corresponding classical optimization problem:
Obj(��, �� ; ��) =������
�+��� ���
�
��
Copyright © D-Wave Systems Inc. 29
DDDD----Wave 2X Quantum ProcessorWave 2X Quantum ProcessorWave 2X Quantum ProcessorWave 2X Quantum Processor
Qubits within red boxes
Overview of D-Wave
Copyright © D-Wave Systems Inc. 31
First and only commercial quantum computerFirst and only commercial quantum computerFirst and only commercial quantum computerFirst and only commercial quantum computer
• Customers include Google, NASA, Lockheed, University of
Southern California, Los Alamos National Laboratory, Temporal
Defense Systems
• 150 U.S. patents
• 160 employees, 45 with Ph.D.
• HQ in Vancouver, B.C.
• Founded in 1999
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MissionMissionMissionMission
To help solve the most challenging problems in the multiverse:
• Optimization
• Machine Learning
• Monte Carlo/Sampling
Copyright © D-Wave Systems Inc. 33
Better Answers for Hard ProblemsBetter Answers for Hard ProblemsBetter Answers for Hard ProblemsBetter Answers for Hard Problems
Graph
Coloring
Factoring
V&V
Constraint Satisfaction
Monte
Carlo
Financial
Modeling
Filtering
Sampling
Scaling Error
Treatment
Topology
Quantum Research
Optimization/Decision Support
Scheduling Logistics
Planning
Deep Learning
Structured
Prediction
Boltzmann
Machines
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Google Optimization BenchmarksGoogle Optimization BenchmarksGoogle Optimization BenchmarksGoogle Optimization Benchmarks (2013)(2013)(2013)(2013)
0.001
0.01
0.1
1
10
100
1000
10000
0 100 200 300 400 500
Me
dia
n t
ime
to
be
st s
olu
tio
n (
s)
Problem size (number of qubits)
Series1
Series2
Series3
Series4
11000 x
Timing Benchmark – Smaller is Better
11,000xD-WAVE II
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Machine Learning: Binary ClassificationMachine Learning: Binary ClassificationMachine Learning: Binary ClassificationMachine Learning: Binary Classification
• Traditional algorithm recognized car about 84% of the time
• Google/D-Wave Qboostalgorithm implemented to recognize a car (cars have big shadows!)
• “Quantum Classifier” was more accurate (94%) and more efficient
• Ported quantum classifier back to traditional computer, more accurate and fewer CPU cycles (less power)!
Copyright © D-Wave Systems Inc. 36
Google Blog December 8, 2015Google Blog December 8, 2015Google Blog December 8, 2015Google Blog December 8, 2015http://googleresearch.blogspot.ca/2015/12/when-can-quantum-annealing-win.htmlWhen can Quantum Annealing win?
Tuesday, December 08, 2015Posted by Hartmut Neven, Director of Engineering-
During the last two years, the Google Quantum AI team has made progress in understanding the physics governing quantum annealers. We recently applied these new insights to construct proof-of-principle optimization problems and programmed these into the D-Wave 2X quantum annealer that Google operates jointly with NASA. The problems were designed to demonstrate that quantum annealing can offer runtime advantages for hard optimization problems characterized by rugged energy landscapesWe found that for problem instances involving nearly 1000 binary variables, quantum annealing significantly outperforms its classical counterpart, simulated annealing. It is more than 108 times faster than simulated annealing running on a single core.
100,000,000x
Quantum Computing System
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DDDD----Wave Container Wave Container Wave Container Wave Container ----““““SCIFSCIFSCIFSCIF----like” like” like” like” ---- No No No No RFRFRFRF InterferenceInterferenceInterferenceInterference
Copyright © D-Wave Systems Inc. 43
System ShieldingSystem ShieldingSystem ShieldingSystem Shielding
• 16 Layers between the quantum chip
and the outside world
• Shielding preserves the quantum
calculation
Copyright © D-Wave Systems Inc. 44
Processor EnvironmentProcessor EnvironmentProcessor EnvironmentProcessor Environment
• Cooled to 0.015 Kelvin, 175x colder
than interstellar space
• Shielded to 50,000× less than Earth’s
magnetic field
• In a high vacuum: pressure is 10 billion
times lower than atmospheric pressure
• On low vibration floor
• <25 kW total power consumption – for
the next few generations
15mK
Copyright © D-Wave Systems Inc. 45
DDDD----Wave Wave Wave Wave 2000Q 2000Q 2000Q 2000Q Quantum ProcessorQuantum ProcessorQuantum ProcessorQuantum Processor
Copyright © D-Wave Systems Inc. 46
Processing Using DProcessing Using DProcessing Using DProcessing Using D----Wave Wave Wave Wave
• A lattice of superconducting loops (qubits)
• Chilled near absolute zero to quiet noise
• User maps a problem into search for “lowest point in a vast landscape” which corresponds to the best possible outcome
• Processor considers all possibilities simultaneously to satisfy the network of relationships with the lowest energy
• The final state of the qubits yields the answer
Copyright © D-Wave Systems Inc. 47
�
��
��
Qubit assuperconducting loop
The EnergyPotential
The QubitThe QubitThe QubitThe Qubit
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The The The The CouplingCouplingCouplingCoupling
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QubistQubistQubistQubist
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Colors encoded in unit cellsColors encoded in unit cellsColors encoded in unit cellsColors encoded in unit cells
Copyright © D-Wave Systems Inc. 52
“Virtual” QUBO
qbsolv
DDDD----Wave Software EnvironmentWave Software EnvironmentWave Software EnvironmentWave Software Environment
LANL Assembler
Environment/
Libraries
1Qbit SDK
JADE/QuellE…
QUBOINTERMEDIATE
REPRESENTATION
TARGET SYSTEM
HOST LIBRARY AND COMMAND
LINE INTERFACE
C, C++, MATLAB Python
DW
SAPI SYSTEM INTERFACE AND
CONTROL
TRANSLATORSQSAGE
OptimizationConstraint
Satisfaction
ToQ
SamplingSAT, ML
?� � �
QUANTUM MACHINE INSTRUCTIONQMI
APPLICATIONS
“QUORTRAN” COMPILERS“Q++”
PRODUCT PROTOTYPE CONCEPT
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