jelena vuckovic - d113b16mcn34wy.cloudfront.net€¦ · 21/02/2018 · l. zhang et al, nano...

Jelena Vuckovic, StanfordStanford University

Optimized photonics:

from efficient computing to connecting

quantum processors

Samsung, San Jose, Feb. 21, 2018

Jelena Vuckovic

Jelena Vuckovic, Stanford

Photonics – emerging applications

Optical neural networkY. Shen et al, Nature Photonics 11, 441–

446 (2017)

On chip optical interconnects (C. Sun et al, Nature 528, 534–538 (2015)

2

But state of the art photonics is:

• Lossy: ~1pJ/bit (same as electronics)

• Bulky

• Very sensitive to fabrication and temperature errors => post tuning, heaters


Present photonics

3

• Optical components are currently designed by tuning a small

number of design parameters by optics experts

• They are large, inefficient, and very sensitive to environment

(temperature, fabrication imperfections…)

• Most of them are not optimal• Limited functionality

Lipson (Cornell/Columbia) Watts (MIT) JV (Stanford)

Jelena Vuckovic, Stanford 4

• Better device performance than what we know today

• Ultra-compact footprints

• Robust to fabrication errors, temperature variations

• Novel functionality

• No brute force design, manual parameter tuning

• Nanophotonic expertise not necessary in design process

Could we design and make better photonics?

J. Lu and J. Vuckovic, Optics Express Vol. 21, 11, pp. 13351-13367 (2013)

Developed a design method for any 3D linear nanophotonic

device: “objective first”, followed by adjoint optimization

1.3 m

1.5m

Fabricated device with superimposed E-fields

2.8 m

Other groups working on adjoint (gradient based) optimization in photonics:

S. Johnson (MIT), S. Fan (Stanford), Yablonovitch (UCB), Sigmund (DTU), Rodriguez

(Princeton),… Other approaches: Savona (EPFL), Lipson (Columbia), Lalanne (CNRS), Menon

(Utah)…


• Full parameter space is enormous => hand-tuning and brute

force search won’t work!

• Include/exclude per pixel gives us possibilities

237-digit number

784)28( 222

5

Broadband wavelength splitter design

2.8m

(100nm)2

pixel

• Full parameter space design must be design by specification!


Broadband wavelength splitter design

6

Nature Photonics 9, 374–377 (2015)

optimization techniques

applied to physics

(nanophotonic structures)


Broadband wavelength splitter

Robust, broadband, designed

for SOI

Nature Photonics 9, 374–377 (2015) 7


Fabrication – broadband wavelength splitter

8




Fabrication – broadband wavelength splitter


Experimental demonstration

Experiment

(3 devices

plotted

together)

Theory

10



Robust design

Optics Express Vol. 21, 11, pp. 13351-13367 (2013)

temperature robustness

fabrication imperfections

1.5 m

1.3m

11


Fabrication constraints?

12



Spatial mode splitter

• conversion efficiencies into the upper and

lower output arms: 88.7% and 77.4%

• rejection powers for the same modes: 0.27%

and 0.20%.

• Device footprint is 2.8×2.8 microns

Optics Express Vol. 21, 11, pp. 13351-13367 (2013)


Fabrication constrained design: mode splitter

• minimum radius of curvature of 40 nm

• minimum gap or bridge width of 90 nm

Scientific Reports, May 2017


3-way power splitter

Min. rad. of

curvature:

40nm

Min. gap /

bridge width:

90nm

15

simulationexperiment

Scientific Reports, May 2017


3-port wavelength demultiplexer

Su et al, ACS Photonics, ASAP (2017)


10-port wavelength demultiplexer - preliminary

4 x 12 microns

Min feature: 80 nm

N. Sapra, L. Su et al


Better grating couplers

19

0.18dB loss for fabricable structures!

(97% coupling efficiency)

Su et al, Optics Express 26, 4023-4034 (2018)


Inverse design of better cavities

𝑄~80,000

𝑉~0.12 𝜆 𝑛 3

Lu, Boyd, and

Vuckovic, Optics Express, 19,

pp. 10563-10570 (2011).


Photonics can be robust and insensitive to errors

A. Piggot

et al,

Nature

Photonics

(2015)

L. Su et al,

ACS

Photonics

(2017)


• Full parameter space adjoint (gradient descent) optimization in 3D (not fixed

geometry optimization)

• Use of 3D FDFD (homemade) on GPUs to dramatically speed up optimization

• Objective first approach (initial condition)

• Design of robust structures (temperature, fabrication errors)

• Lu &Vuckovic, Optics Express 21, pp. 13351-13367 (2013);

Optics Express 20, pp. 7221-7236 (2012)

• Lu, Boyd, & Vuckovic, Optics Express, 19, pp. 10563-10570 (2011)

• First experimental demonstrations of such structures

• Piggott, Lu, Babinec, Lagoudakis, Petykiewicz, Vuckovic,

Scientific Reports 4, 7210, (2014);


• Fabrication constrained inverse design

• Variety of optimization algorithms (higher order gradient

descent, biasing, etc)

• Piggott, Petykiewicz, Su & Vučković. Scientific Reports 7, 1786 (2017)

• Su, Piggott, Sapra, Petykiewicz, Vuckovic (2017) (arXiv:1709.08809)

Our inverse design approach

22

https://arxiv.org/abs/1709.08809


SiC

5 um

Ge

Present nanophotonics

1m

~200 nmDiamond

GaPGaP

23

GaAs

GaAsdiamond


24

3 way power splitterWavelength demultiplexers

Broadband grating coupler

1.3 m

1.5m

Fabricated device with superimposed E-fields

2.8 m


Quantum processors

IBM, Google – 50 qubits

Harvard-MIT, 51-atom quantum simulator

• Scaling is hard

• Bulky, fragile systems; operation at mK temperature

• Noisy intermediate scale quantum technology (NISQ) [J. Preskill, arXiv:1801.00862]

Lucas and Steane groups


Multi-core quantum processors?

26

C. Monroe, J. Kim, Science 339, 1164 (2013)

Quantum optical

connections needed!


Quantum processors in friendlier environments?

27

@ SciFoo 2017


Circuit

QED

Gate-

defined QDs

Trapped

ions

Self-

assembled

QDs

SiV in

diamond

VSi in silicon

carbide

Coherence time

(T2)

50 µs 30 ms 50 s 2 µs 1 ms 75 ms

Single qubit gate

time

10 ns 40 ns 1 µs 10 ps 1 ns 50 ns

2 (identical)

qubits gate time

50 ns 10 µs 50 µs 300 ps *1 ns *8 ns

1-qubit fidelity 99.92% 99.95% 99.9999% 98% 95% -

2-qubit fidelity 99.4% 90% 99.9% 80% - -

# of 2-qubit

operations

1,000 3,000 1,000,000 10,000 *1,000,000 *9,000,000

Scalable? YES YES MAYBE MAYBE YES YES

Optical

interface?

MAYBE MAYBE YES YES YES YES

[Martinis/Google][Monroe/ JQI] [Vuckovic/ Stanford][Marcus/NBI,

Petta/Princeton]

[Vuckovic/Stanford,

Loncar/Harvard]

500 nm

[Vuckovic/Stanford,

Wrachtrup/Stuttgart]

Qubits &

properties


Quantum dots in optical cavities

LIGHT: Optical cavity MATTER: quantum dot

GaAs

InAs5nm

250nm

AFM

TEM (Finley, TUM)

Experiment:

Q=25300,

V~0.7(/n)3

Resonator

spectrum

wavelength [nm]

2

~5 m

910 914 9180

200

400

600

800

Inte

nsity (

arb

. u

nits)

Wavelength (nm)

~2

QD

spectrum

29


Quantum dots in optical cavities

30

Strong coupling

• g exceeds loss rates (/2, /2)

All rates in GHz regime => GHz speed

(dipole decay)

=/2Q (cavity decay rate)

g~1/V0.5 (QD-cavity coupling strength)


Laser – classical (Poissonian) light source

31

• Number of photons per pulse not fixed

• Emitted photons obey Poisson statistics

Laser

13 ns

3 ps

Time (t)

Photon

number

N(t)

13 ns

HBT setup• Coincident clicks of

2 detectors

• 2nd order auto-

correlation function

g (2) (0)=1

1

!N

neNP

Nn


1

Single photon source (non-classical)

32

• Number of photons per pulse = 1

Single photon source

13 ns

HBT setup • g(2)(0)= 0 (ideal)

(probability of detecting 2

photons at the same

time)

Time (t)

Photon

number

N(t)

13 ns

1

• Non-ideal (sub-Poissonian):

0<g(2)(0)<1


Bosonic interference

Nature, vol. 419, pp. 594-597, 2002

Used to measure photon

indistinguishabulity and build

large entangled states


Multi-photon probability =0?

34arXiv:1801.01672

Collaboration with TU Munich, Mueller & Finley groups


Why are quantum dots hard to scale?

Site and size control –

key to scalability

250nm

• Random positions

• Random sizes and shapes =>

inhomogeneous broadening

35

910 914 9180

200

400

600

800

In

ten

sity (

arb

. u

nits)

Wavelength (nm)

~2

Single QD

spectrum

904 906 908 910 912 914 9160

10

20

30

Wavelength (nm)

PL I

nte

nsity (

kcps)

Ensemble of QDs

Jelena Vuckovic, StanfordNano Letters 16 (1), pp. 212-217 (2016)

SiV in

Optica 4 (11), 1317-1321 (2017)

Coherent

control of a

single SiV

With ZX Shen, N.Melosh, S.Chu (Stanford)

Vsi in 4H SiC

36

4H-SiC

With Wrachtrup (Stuttgart), Janzen,

Son (Linkoping), Ohshima (Japan)

Nano Letters 17 (3) , pp 1782–1786 (2017)

• Vsi spin control at room T

• Optical interface


Cavity QED with SiV in diamond

37

Collaboration with Marko Loncar, Harvard

L. Zhang et al, Nano Letters, ASAP (2018)


Cavity QED with SiV in diamond

0 1.84

194 8on ps

ns 42.4x

increase

in PL

Cooperativity C=1.4

g/2= 5 GHz, /2=25GHz, /2 ~1GHz

Reduce V by 1.5x, increase Q by 2x to make g> /2

L. Zhang et al, Nano Letters, ASAP (2018)


Scalable photonics with single color centers in SiC

500 nm

10 µm

39

Collaboration with Wrachtrup, Jenzen, Oshima groups

Nano Letters 17 (3) , pp 1782–1786 (2017)


Single photon emission from

VSi- in nanopillar

Optically detected magnetic resonance

from VSi- in nanopillar

Scalable photonics with single color centers in SiC

Nano Letters 17 (3) , pp 1782–1786 (2017)


• We’ve made remarkable progress, but quantum hardware

still has to be improved

• Like classical photonics, we perform intuition driven design,

use standard components from microwave and optical

engineering

• Can we use AI

techniques to build better

quantum hardware?

[Martinis/Google][Monroe/ JQI] [Vuckovic/ Stanford][Marcus/NBI,

Petta/Princeton]

[Vuckovic/Stanford,

Loncar/Harvard]

500 nm

[Vuckovic/Stanford,

Wrachtrup/Stuttgart]

Jelena Vuckovic, Stanford http://nqp.stanford.edu

+ recent alumni: Jesse Lu (Google),

Jan Petykiewicz (Global Foundries),

Kai Mueller (TUM)

jelena vuckovic - d113b16mcn34wy.cloudfront.net€¦ · 21/02/2018 · l. zhang et al, nano...

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