Canary Foundation at Stanford. D-Wave Systems Murray Thom February 27 th, 2017

Transcription

1 Canary Foundation at Stanford D-Wave Systems Murray Thom February 27 th, 2017

2 Introduction to Quantum Computing

3 Copyright D-Wave Systems Inc. 3

4 Richard Feynman Copyright D-Wave Systems Inc. 4

5 Quantum Turing Machine Copyright D-Wave Systems Inc. 5

6 Quantum Annealing Outlined by Tokyo Tech PHYSICAL REVIEW E VOLUME 58, NUMBER 5 NOVEMBER 1998 Quantum annealing in the transverse Isingmodel Tadashi Kadowaki and Hidetoshi Nishimori Department of Physics, Tokyo Institute of Technology, Oh-okayama, Meguro-ku, Tokyo , 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 timedependent 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. [S X~98! ] Copyright D-Wave Systems Inc. 6

7 D-Wave Announces 16 Qubit QC 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 qubit D-Wave 2X system Copyright D-Wave Systems Inc. 7

8 QC Models

9 Quantum Information Science Quantum key distribution Quantum information processing One-way/ cluster state Topological Quantum Sensor Emerging Quantum Cryptography Quantum Communication Quantum Computing Annealing Gate Model Emerging Copyright D-Wave Systems Inc. 9

10 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 Copyright D-Wave Systems Inc. 10

11 Gate Model Quantum Computing Copyright D-Wave Systems Inc. 11

12 Quantum Annealing (T=0, N=0) H S (t) = (1 s)h I + sh P, s = t/t f Initial state energy levels 0 s 1 Solution Copyright D-Wave Systems Inc. 12

13 Quantum Annealing (+ Thermal Noise) H ( t) = H ( t) + H + S B H SB System Bath Interaction k B T energy levels 0 s 1 Dynamical freeze-out Copyright D-Wave Systems Inc. 13 P 0

14 Topological Quantum Computing Microsoft Research TU Delft And others Anyons Non-Abelian Anyons /520540fce4b00fb5186e572f/ /SteveSimon_800_320.jpg Copyright D-Wave Systems Inc. 14

15 Photonic/Optical University of Bristol And others Copyright D-Wave Systems Inc. 15

16 Trapped Ions Oxford UofSussex UofMD Innsbruck And others Copyright D-Wave Systems Inc. 16

17 Silicon-based devices Intel University of New South Wales TU Delft And others Copyright D-Wave Systems Inc. 17

18 Superconducting Qubits D-Wave Systems Google MIT-LL/IARPA IBM Copyright D-Wave Systems Inc. 18

19 D-Wave qubit count has grown exponentially 10,000 1,000 D-Wave Two 512 D-Wave 2000Q 2000 Next Gen D-Wave 2X 1000 Qubits (log scale) 100 D-Wave One Gate Model Copyright D-Wave Systems Inc. 19

20 Quantum Annealing

21 Energy Landscape Space of solutions defines an energy landscape & best solution is lowest valley Classical algorithms must walk overthis landscape Quantum annealing uses quantum effects to go through the mountains Copyright D-Wave Systems Inc. 22

22 Quantum Effects on D-Wave Systems Superposition Entanglement QuantumTunneling Copyright D-Wave Systems Inc. 23

23 Quantum Turing Machine Copyright D-Wave Systems Inc. 24

24 Quantum Annealing Outlined by Tokyo Tech PHYSICAL REVIEW E VOLUME 58, NUMBER 5 NOVEMBER 1998 Quantum annealing in the transverse Isingmodel Tadashi Kadowaki and Hidetoshi Nishimori Department of Physics, Tokyo Institute of Technology, Oh-okayama, Meguro-ku, Tokyo , 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. [S X~98! ] Copyright D-Wave Systems Inc. 25

25 Making Use of Quantum States Gate Model 1 0 By Peppergrower-Own work, CC BY-SA 3.0, Copyright D-Wave Systems Inc. 26

26 Making Use of Quantum States Quantum Annealing 1 0 Copyright D-Wave Systems Inc. 27

27 Quantum Enhanced Optimization Quantum Hamiltonian is an operator on Hilbert space: H =E + +Δ Corresponding classical optimization problem: Obj(, ; )= + Copyright D-Wave Systems Inc. 28

28 D-Wave 2X Quantum Processor Qubits within red boxes Copyright D-Wave Systems Inc. 29

29 Overview of D-Wave

30 First 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 Copyright D-Wave Systems Inc. 31

31 Mission To help solve the most challenging problems in the multiverse: Optimization Machine Learning Monte Carlo/Sampling Copyright D-Wave Systems Inc. 32

32 Better Answers for Hard Problems Optimization/ Decision Support Constraint Satisfaction Sampling Deep Learning Quantum Research Scheduling Logistics Graph Coloring Factoring Monte Carlo Financial Modeling Structured Prediction Boltzmann Machines Scaling Error Treatment Planning V&V Filtering Topology Copyright D-Wave Systems Inc. 33

33 (2013) Google Optimization Benchmarks(2013) Timing Benchmark Smaller is Better Median time to best solution (s) Series1 Series2 Series3 D-WAVE Series4 II 11,000x x Problem size (number of qubits) Copyright D-Wave Systems Inc. 34

34 Machine Learning: Binary Classification Traditional algorithm recognized car about 84% of the time Google/D-Wave Qboost algorithm 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. 35

35 Google Blog December 8, 2015 When can Quantum Annealing win? Tuesday, December 08, 2015 Posted 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 landscapes We found that for problem instances involving nearly 1000 binary variables, quantum annealing significantly outperforms its classical counterpart, simulated annealing. It is more than 10 8 times faster than simulated annealing running on a single core ,000,000x Copyright D-Wave Systems Inc. 36

36 Quantum Computing System

37 D-Wave Container - SCIF SCIF-like - No RF Interference Copyright D-Wave Systems Inc. 42

38 System Shielding 16 Layers between the quantum chip and the outside world Shielding preserves the quantum calculation Copyright D-Wave Systems Inc. 43

39 Processor Environment Cooled to 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. 44

40 D-Wave 2000Q Quantum Processor Copyright D-Wave Systems Inc. 45

41 Processing Using D-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 qubitsyields the answer Copyright D-Wave Systems Inc. 46

42 The Qubit Qubit as superconducting loop The Energy Potential Copyright D-Wave Systems Inc. 47

43 The Coupling Copyright D-Wave Systems Inc. 48

44 Qubist Copyright D-Wave Systems Inc. 50

45 Colors encoded in unit cells Copyright D-Wave Systems Inc. 51

46 D-Wave Software Environment APPLICATIONS Environment/ Libraries QUORTRAN Q++ COMPILERS 1Qbit SDK Optimization Constraint Satisfaction Sampling SAT, ML JADE/QuellE QSAGE ToQ? TRANSLATORS Virtual QUBO LANL Assembler QUBO qbsolv INTERMEDIATE REPRESENTATION C, C++, MATLAB Python DW HOST LIBRARY AND COMMAND LINE INTERFACE SAPI SYSTEM INTERFACE AND CONTROL QMI QUANTUM MACHINE INSTRUCTION TARGET SYSTEM PRODUCT PROTOTYPE CONCEPT Copyright D-Wave Systems Inc. 52