quantum computing on a scalable superconducting qubit platform · quantum computing first...

Stefan FilippQuantum Technology, IBM Research – Zurich

Quantum Team at IBM Research Yorktown Heights

Quantum computing

on a scalable superconducting qubit platform

Brasilien

T.J WatsonAlmaden

Austin Irland

Zürich

Afrika Indien

Haifa

China Japan

Australien

12 labs with over 3,000 researchers around the world3 labs with research in quantum information processing

Copper SOI StrainedSilicon

Dual Core Immersion SiGe High-k eDRAM 3D ChipStacking

AirgapChemically Amplified Resists

Quantum

IBM Research

IBM Research – Zurich Established in 1956, ~ 420 employees

Science & technology, cognitive computing & industry solutions, cloud & computing infrastructure

IBM’s most advanced nanotechnology fabrication (collaboration with ETH, EMPA) and IBM’s world-class noise free labs

Proven track record in science & technology –including 2 Nobel prizes (4 Laureates), 1 Kavli prize

Majority of researchers are Europeans(22 EU countries represented)

Longstanding collaborations with universities, research organizations and industries in EU & worldwide

Investments in EU’s research infrastructure and education

Spin-off and start-up companies

Binnig & Rohrer Nanotechnology Center(BRNC, opened 2011)

3D / hybrid

neuromorphic (cognitive)

quantum computing

First integrated circuit

Size ~1cm2

2 Transistors

Moore’s Law is Born

Intel 4004

2,300 transistors

IBM P8 Processor ~ 650 mm2

22 nm feature size, 16 cores

> 4.2 Billion Transistors

1958 1971 2014

Alternative (co-existing)architectures:

Further issues: power density on chip, speed, interconnects, cost,…

Why Quantum? Why now?

© 2016 International Business Machines Corporation

Solving computational problems requires physical resources (time, memory, and space).

“easy” problems (polynomial efficient) “hard” problems (exponential intractable)

• multiplying numbers• word processing• Sending emails

• Algebraic and Number Theoretic Algorithms (factoring, hidden subgroup)• Combinatorial optimization (traveling salesman)• Machine learning • simulating quantum mechanics

There are problems that are believed to be hard (never) for classical computers to solve.

http://xkcd.com/759/

http://xkcd.com/399/

Conventional/Classical Computing


Exponential speed-up:A task taking 2100 seconds (1025 days) on a classical computer might take 100 seconds on a quantum computer

The problem ofmultiplication vs factoring:

937 x 947 = N (easy)887339 = p x q (harder)

Modulus (1024 bits):de b7 26 43 a6 99 85 cd 38 a7 15 09 b9 cf 0f c9 c3 55 8c 88 ee 8c 8d 28 27 24 4b 2a 5e a0 d8 16 fa 61 18 4b cf 6d 60 80 d3 35 40 32 72 c0 8f 12 d8 e5 4e 8f b9 b2 f6 d9 15 5e 5a 86 31 a3 ba 86 aa 6b c8 d9 71 8c cc cd 27 13 1e 9d 42 5d 38 f6 a7 ac ef fa 62 f3 18 81 d4 24 46 7f 01 77 7c c6 2a 89 14 99 bb 98 39 1d a8 19 fb 39 00 44 7d 1b 94 6a 78 2d 69 ad c0 7a 2c fa d0 da 20 12 98 d3

1024bit public key:

= p × q

→ just short of impossibleShor’s algorithm jumpstarted the interest in quantum computing

Classical Record: 230 digits

exp(𝐶 𝑏1/3)

𝐶 𝑏3

Example: Shor’s Algorithms


How much memory is needed to store a quantum state?

How much time does it take to calculate dynamics of a quantum system?

# qubits quantum state coefficients # bytes timescale

1 𝑎 0 + 𝑏|1⟩ 21 = 2 16 Bytes

2 𝑎 00 + 𝑏 01 + 𝑐 10 + 𝑑|11⟩ 22 = 4 32 Bytes Nanoseconds

8 28 = 256 2kB Microseconds on watch

16 … 216 = 65′536 256 kB Milliseconds on smartphone

32 … ~ 4 billion 256 GB Seconds on laptop

64 …~ information in

internet74 EB

(74 million GB)Years on supercomputer

256 …~ # of atoms in

universe… never

classicalq

uan

tum

The Quantum Advantage – Simulation of physical systems

© M. Troyer


Goal: Build computers based on quantum physics to solve problems that are otherwise intractable

Develop “Hardware-efficient” apps − Chemical configurations− Optimization

No full error correction available

Demonstrate “quantum supremacy”

5-8 qubits 16-20 qubits50-100+ qubits 105-106 qubits

Small-scale Medium-scale Large-scale

Research level quantum demonstrations

Verify chemistry and error correction principles

Infrastructure & community building

Known and proven speed-up: Factoring Complete quantum molecular

simulations Speed-up machine learning and

database searching

Roadmap:

Challenges: Continued scalability, control and coherence of large systems, cost…

Grand Challenge: Quantum Computing


microwave resonator: read-out of qubit states

multi-qubit quantum bus

noise filter

(fixed-frequency) superconducting qubit: non-linear Josephson Junction (Inductance)

anharmonic energy spectrum → qubit

nearly dissipationless → T1, T2 ~ 70 µs

Superconducting Qubit Processor


Required Technologies for Scaling

• Two-qubit gates: improve fidelities

• Coherence/reproducibility:

improved material/fabrication methods

• Cross-talk: microwave mode suppression

(air-bridges through-vias, solder-bump bonds, flip-chip,…)

• 3D integration: address/couple all qubits in 2D array

• Integrated electronics: required for 20+ qubits

• Verification and characterization: identify Hamiltonian

• Software: compilers and high-level programming language

• …

Quintana (2014)

@ IBM Research - Zurich

MIT-LL

[1] Threshold for surface code QEC assuming 30-100ns gate time

[2] J. Martinis et al., PRL 95 210503 (2005)

[3] K. Geerlings et al., APL 192601 (2012)

[4] H. Paik et al., PRL 107, 240501 (2011)

[5] R. Barends et al., APL 99, 113507 (2011)

[6] A. Corcoles et al., APL 99, 181906 (2011)

[7] C. Rigetti et al., PRB 86, 100506 (2012)

[8] M. Reagor et al., arXiv:1302.4408 (2013)

[9] J. Chang et al. APL 103, 012602 (2013)

[10] P. Kumar, et al. arXiv:1604.00877v1, (2016).

Developments to extend coherence times:

• Materials e.g. [2]

• Design and geometries e.g. [3]

• 3D transmon [4]

• IR Shielding [5,6]

• Cold normal metal cavities and cold qubits [7]

• High Q cavities [8]

• Titanium Nitride [9]

• UHV packaging [10]

Remarkable progress over the past decade!


Qubit Coherence and Lifetimes

UHV sealing and surface preparation

Cross-Resonance entangling gate (ZX) [1,2]• drive qubit A at frequency of B• fixed frequency qubits → long coherence• fixed coupling → qubits close in frequency• strong MW driving → off-resonant interactions• Typical specs: T1,T2 =60 − 80𝜇𝑠, TG > 160ns,

gate fidelities 95%-99% [Sheldon et al., arXiv:1603.04821 (2016)]

2-Qubit Gates

[1] J. M. Chow, et al. PRL 107, 080502 (2011).

[2] S. Sheldon, et al, PRA, 93, 012301 (2016).

𝛿12

Σ12

Gate with tunable bus (XX,YY,ZZ) [3,4]• modulate J at sum and difference frequencies• fixed frequency → long coherence• simultaneously create XX, YY & ZZ interactions• couple more than 2 qubits by frequency addressing

[3] P. Bertet, PRB, 73, 064512 (2006)

[4] D. C. McKay, et al. PR Appl (2016).


Entanglement generation via tunable couplings

Randomized Benchmarking:

97.2 % gate fidelity; TG = 140 ns [D. McKay et al. PR Applied (2016)]

𝑖𝑆𝑊𝐴𝑃 with 𝐻𝑡𝑐 ∝ 𝑋𝑋 + 𝑌𝑌

Target state: 1/ 2( 01 + 𝑖|10⟩)~ 97% state fidelity; 80ns

2 − 𝑒𝑥𝑐𝑖𝑡𝑎𝑡𝑖𝑜𝑛 with 𝐻𝑡𝑐 ∝ 𝑋𝑋 − 𝑌𝑌

Target state: 1/ 2( 00 + |11⟩)~ 97% state fidelity; 175ns

(work in progress)

Hamiltonian: 𝐻𝑡𝑐 = 𝐻1 +𝐻2 + 𝐽𝑥𝑥𝑋𝑋 + 𝐽𝑦𝑦𝑌𝑌 + 𝐽𝑧𝑧𝑍𝑍

Goal:

• optimizing gate count

for short-depth circuits

• analog quantum simulation


Goal: Build computers based on quantum physics to solve problems that are otherwise intractable

Develop “Hardware-efficient” apps − Chemical configurations− Optimization

No full error correction available

Demonstrate “quantum supremacy”

5-8 qubits 16-20 qubits50-100+ qubits 105-106 qubits

Small-scale Medium-scale Large-scale

Research level quantum demonstrations

Verify chemistry and error correction principles

Infrastructure & community building

Known and proven speed-up: Factoring Complete quantum molecular

simulations Speed-up machine learning and

database searching

Enable secure cloud computing: quantum analogy to homomorphic encryption

Roadmap:

Challenges: Continued scalability, control and coherence of large systems, cost…

Grand Challenge: Quantum Computing


Superconducting 5 Qubit Processor in the cloud

• explore quantum computing: run algorithms and experiments

• build a Quantum Community

• discover new applications for this technology

program 5 qubits

2016 IBM introduced a 5 qubit QC on the cloud for public use: http://www.ibm.com/quantumexperience


• Several professors committing to using IBM Quantum Experience for courses• Undergrad conference at University of Waterloo using IBM QX• ‘Live the Quantum Experience’ student’s event at IBM Zurich - Research

• >36000 users subscribed• 230000 algorithms run

Are you an experiencer, yet?

www.ibm.com/quantumcomputing

Quantum community


10+ papers based on IBM QX submittedHigh-level interface: ProjectQ (see M. Troyer)

Quantum computer for scientists


Five-qubit quantum processor

IBM Quantum Experience

Q0

Q1

Q2

Q3

Q4

Five-qubit device parameters

Frequency(GHz)

Anharm.

(MHz)

Readout cavity (GHz)

T1 (μs) T2 (μs) Readout fidelity

RB Error/Clifford

Q0 5.3503 -330.0 6.5251 57.3 66.4 0.971 0.0027

Q1 5.3061 -328.9 6.4760 71.8 90.7 0.972 0.0018

Q2 5.1202 -322.0 6.4295 63.4 53.4 0.972 0.0025

Q3 5.2297 -327.0 6.5743 82.7 66.9 0.952 0.0032

Q4 5.0748 -330.5 6.5243 71.0 72.2 0.961 0.0025

Q0

Q1

Q2

Q3

Q4

Values from Calibration on 2016-07-18_12.05

Two-Qubit CR (ZX90)

RB Error/ Clifford

(±𝟎. 𝟎𝟎𝟐)

CR0-2 (467ns) 0.044

CR1-2 (573ns) 0.035

CR3-2 (547ns) 0.036

CR4-2 (400ns) 0.033


Physical layer

Logical layer

The Quantum Computing System

[Gambetta, Chow, Steffen, arxiv 1510.04375 (2015)]


To detect error: encode 1 bit in 2 bits

Quantum: no measurement without disturbance

Solution: use an ancilla qubit to detect the error – but not the qubit state

0 1 0 1

0 0 1 1

0 1 1 0ancilla qubit 0

dataqubits • Ancilla qubit signals parity of data qubits

• ZZ & XX measurement needed to catch phase and bit flip errors

controlled-NOT gates

ZZ-measurement

parity change:

indicates error

0 → |00⟩

1 → |11⟩

|10⟩

|01⟩

|10⟩

|01⟩

Bit-flip error0 1

1 0

Quantum Error Detection


Fault tolerant quantum computation via the surface code

[Raussendorf, Harrington, PRL (2007);Fowler et al., PRA (2009); Bravvy (1998)]

• logical qubits formed by specific states of data qubits (delocalized)

• measure syndrome qubits→ gives parity information of data qubits (4 data qubits per syndrome)

• correct for errors on actual data qubits

• error threshold: 𝑝0 = 0.7%


Scaling superconducting qubit system for surface code

3x3 code

d = 39 code

8 syndromes10 buses

2 qubits, 1 bus 3 qubits, 2 buses

4 qubits, 4 buses 8 qubits, 4 buses

5 IBM QX qubits: 1 plaquette

or

[JMC et al. Nat. Comm (2014), Corcoles et al Nat Comm (2015); Takita, et al., arxiv: 1605.01351 (2016)

[D. Riste et al. Nat. Comm 6, 6983, (2015)

J. Kelly et al. Nature, 519,66, (2015)]

See also:

@ Google, Martinis @ Delft, DiCarlo


Full plaquette experiment

• full plaquette: syndrome qubit coupled to 4 data qubits via bus resonators

• prepare the 4 data qubits in 16 initial states of various parities (basis:| ۧ0 and | ۧ+ )

• measure the weight-four parities via high-fidelity measurement of Q2, the syndrome

Z-parity check X-parity check

Or

ZZZZ

Par

ity

Ch

eck

syndrome qubit

XX

XX

Par

ity

Ch

eck

syndrome qubit


State(Q0 Q1 Q3 Q4) Q2 P0 Q2 P1

0 0 0 0 0.878 0.1220 0 0 1 0.191 0.8090 0 1 0 0.120 0.8800 0 1 1 0.908 0.0920 1 0 0 0.188 0.8120 1 0 1 0.815 0.1850 1 1 0 0.914 0.0860 1 1 1 0.100 0.9001 0 0 0 0.128 0.8721 0 0 1 0.878 0.1221 0 1 0 0.936 0.0641 0 1 1 0.107 0.8931 1 0 0 0.887 0.1131 1 0 1 0.229 0.7711 1 1 0 0.125 0.8751 1 1 1 0.922 0.078

Example, preparing data qubit state |1001〉

Syndrome state

|0〉

even

|1〉

odd

Mean of correct parity probabilities: 0.872

ZZZZ-full plaquette result


State(Q0 Q1 Q3 Q4) Q2 P0 Q2 P1

++++ 0.847 0.153+++- 0.202 0.798++-+ 0.117 0.883++-- 0.908 0.092+-++ 0.178 0.822+-+- 0.811 0.189+--+ 0.922 0.078+--- 0.129 0.871-+++ 0.142 0.858-++- 0.883 0.117-+-+ 0.898 0.102-+-- 0.127 0.873--++ 0.918 0.082--+- 0.150 0.850---+ 0.194 0.806---- 0.860 0.140

Example, preparing data qubit state |+---〉

Mean of correct parity probabilities: 0.863Similar work done for 7Q device: Takita, et al., arxiv: 1605.01351 (2016)

|0〉 |1〉

even odd

XXXX-full plaquette result

Syndrome state

17Q: [[9,1,3]] code would demonstrate thesmallest FT logical qubit

in our architecture

3Q: Z parity check [1]

4Q: [[2,0,2]] error detection, entangled

state codewordprotection [2]

7Q: [[4,1,2]] codespace with at least 2 states, show simple logical

operation and fault tolerance measurement

Demonstrated / under test

LOGICAL QUBITS

[1] JMC et al. Nat. Comm (2014), [2] Corcoles et al Nat Comm (2015)

Growing the lattice

11Q: [[6,1,{3,2}]] could allow investigation of

biased noise

INTERESTING DEMO

LOGICAL OPERATIONS

29Q: [[9,1,3]] with transversal H

2014 2015 2016


Important steps:

Benchmarks of small-scale quantum systems (logical qubits, simple molecular simulations)

Show quantum advantage in medium-size quantum applications(quantum simulation, quantum optimization, gadget approaches)

Develop test beds for universal quantum computers

Develop a quantum software platform

Further develop understanding of quantum information systems (algorithms, complexity classes, error correction codes,…)

Challenges: Continued scalability, control and coherence of large systems, cost, applications…

Quantum ecosystem:

Expand & define quantum education programs

Establish European quantum technology landscape

Perspective


Control Software

Cryogenics and Control Electronics

System Characterization

Fabrication/3D Integration

Microwave circuit design & Quantization

Numerical High Frequency Simulation

System Simulation

Superconducting Quantum Processor

can be engineered builds on existing technologies challenges in coherence, control

complexity and scaling

Quantum Algorithms

Quantum Engineering – The Eco System – The Opportunity

quantum computing on a scalable superconducting qubit platform · quantum computing first...

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