Upload
others
View
4
Download
0
Embed Size (px)
Citation preview
Progress Towards Enabling
Quantum Engineering
Photonics for Quantum (PfQ) Workshop
RIT, Rochester, January 23-25, 2018
S. Olson, C. Hobbs, H. Chong, J. Nalaskowski, H. Stamper, J. Mucci, B. Martinick,
K. Beckmann, I. Wells, C. Johnson, V. Kaushik, T. Murray, S. Novak, S. Bennett, M. Rodgers,
C. Borst, M. Liehr and Satyavolu ‘Pops’ Papa Rao
Portions of this presentation are SUNY Polytechnic Institute Confidential as marked
Acknowledgements
2 SUNY Polytechnic Institute Confidential
• Thanks to our partners:
o University of Maryland/LPS (Kevin Osborn, Neda Forouzani, Steven Anlage)
o Syracuse University (Britton Plourde, Matt LaHaye)
o NIST Boulder (Jeff Shainline, Sonia Buckley, Richard Mirin, Sae Woo Nam)
o NIST Boulder (Dave Pappas)
o AFRL (Joe van Nostrand, Mike Fanto, Paul Alsing, Kathy-Anne Soderberg)
o Auburn University (Mike Hamilton, Mark Adams)
o Hypres (Oleg Mukhanov, Igor Vernik, Patrick Truitt)
o Yale (Rob Schoelkopf, Hong Tang, Fengnian Xia)
o Stony Brook University (Xu Du, Dmitri Averin)
o U. Rochester (Mishkat Bhattacharya)
o RIT (Stefan Preble)
o MIT (Dirk Englund)
o William & Mary (Seth Aubin)
o U. Maryland (Qudsia Quraishi)
From Devices To Complex Systems
3 SUNY Polytechnic Institute Confidential
• Order! Order!
semimd.com/chipworks) Intel finFET
https://en.wikipedia.org/wiki/Static_random-access_memory
http://www.computerhistory.org/ revolution/digital-logic/12/280
https://engineering.linkedin.com/blog/2016/11/linkedin_s-oregon-data-center-goes-live
https://commons.wikimedia.org/wiki/File:AMD_Bulldozer_block_diagram_(8_core_CPU).PNG
To Quantum Engineering
4 SUNY Polytechnic Institute Confidential
• Quantum Engineering adopt the ‘manufacturability mantra’
Gambetta et al, npj Quantum Information (2017) 3:2
From https://www.microsoft.com/en-us/quantum/development-kit
www.cqc2t.org (Centre for Quantum Computation & Communication Technology
https://www.dwavesys.com
https://newsroom.intel.com/news/intel-advances-quantum-neuromorphic-computing-research/
Efficient Technology Development
5 SUNY Polytechnic Institute Confidential
Photonic Quantum
Computing
Supercond. Quantum
Computing
Supercond. Opto-Elec.
Neuromorph. Computing
Single Flux Quantum
Logic
UV PIC + μ-wave
wave guides
3DI
Qubits Using 193 nm Lithography
6 SUNY Polytechnic Institute Confidential
Josephson Junction Arrays
48 junctions measured for each datum (JJ’s distributed over 25 mm x 16 mm area)
Foroozani et al, manuscript submitted (2018)
Qubit measurements at ~10 mK (LPS) 𝜔𝑞
2𝜋= 𝟒. 𝟕𝟔𝟔𝟏𝟐 GHz & 𝟒. 𝟕𝟎𝟐𝟔𝟕 GHz
T1 = 𝟐𝟔. 𝟕𝟗 μs & 𝟐𝟓. 93 μs
Why Advanced Fabrication (II)
7 SUNY Polytechnic Institute Confidential
• New processes New device architectures
• New devices Better systems larger horizons for imagination
As deposited
Post CMP
Al
Si
ECS Transactions 85(6) 151 (2018)
1 nm
Across-Wafer Uniformity & Targeting
8 SUNY Polytechnic Institute Confidential
Metal film CMP: Automated adjustment of zone pressures for thickness uniformity
Reactive Ion Etch: Optical endpointing frequently harnessed to improve processes New 300mm tools have chucks with multi-zone temperature controls
Optical emission trace shows SiCN layer uncovered
Al
SiOx
Aluminum Nitride at 300mm scale
9 SUNY Polytechnic Institute Confidential
• UV-PICs with Si/SiO2/poly AlN at 300mm scale
• In partnership with RIT (Stefan Preble), AFRL (Mike Fanto) and MIT (Dirk Englund)
Ion λ (nm)
199 Hg+ 282
171 Yb+ 369.5
88 Sr+ 422
138 Ba+ 650
Crystalline AlN on Sapphire Lu et al, Optics Express 26 (9) 11147 (2018)
AlN on sapphire
Poly AlN on Si/SiO2
Xiong et al, New J Phys 14, 095014 (2012)
Electro-optic modulation with AlN Low loss waveguides, grating couplers … for UV
AlN Deposition & Characterization
10 SUNY Polytechnic Institute Confidential
• AlN film characterization on 300 mm Si wafers
SIMS analysis to quantify contaminants
XRD spectrum from 20nm PVD-AlN film
Glancing Incidence XRD from ALD AlN variants
~20nm PVD AlN
~90nm ALD AlN
Thick oxide
Chemical Mechanical Planarization
of AlN films
11 SUNY Polytechnic Institute Confidential
Pre CMP: 1.7 nm
AlN roughness (XRR fit)
Inte
nsi
ty (
cps)
Angle (seconds)
Post CMP: 0.6 nm
AlN roughness (XRR fit)
Pre CMP: 1.6nm Rq
Post CMP: 0.5nm Rq
<100 defects post CMP
(at ~0.12 um sensitivity)
• Next: 193nm litho & RIE + Cu for RF
In partnership with NIST Boulder (Shainline, Buckley, Mirin, Nam) and using AFRL-funded maskset
Josephson junctions 30,000x faster than brain (fast, sub-aJ pulses!) spikes/s/W ~ human brain Cryo-photonics + SNSPDs 1:1000 neuron connections 1 cm2die: 8k neurons + 330k synapses … and further scalable
Photonics and Quantum
12 SUNY Polytechnic Institute Confidential
Superconductors in our pockets
13 SUNY Polytechnic Institute Confidential
• CMOS-compatible Josephson junctions with α-Tantalum & ALD-TaN
• PVD TaN-based SNSPDs
PVD TaN/~80nm Ta
ALD TaN/~80nm Ta
Measurements by Mike Hamilton group (Auburn University) not yet published α Ta
α Ta
ALD TaN
Al for e-test
Ta/TaN/Ta
Light Emission by Si Defects at 4 K
14 SUNY Polytechnic Institute Confidential
• Si-defect based IR emission into SOI waveguides
implant energy splits
Measurements at NIST Boulder (Buckley, Shainline, et al)
Unpublished
Wavelength (nm)
Co
un
t ra
te
Cryogenic Si defect light emission (Si on 300 nm BOX for faster testing)
Accelerating Functional Integration
15 SUNY Polytechnic Institute Confidential
• One Fab to Make Them All… And With Light Bind Them!
MTJs for cryogenic memory
Integrated Photonics
UV-PIC with AlN
SiC: Er quantum emitters
Adv. CMOS: spin qubit compatible
[1]
[6]
[4]
[3]
Superconducting Quantum Computing
Superconducting Digital electronics
[5] alpha-Ta superconducting line [6] Transmon qubit using 193nm lithography [7] fab-friendly UV-VIS waveguide material [8] Supercond Optoelectronic Neuromorphic computing elements
[5]
[7]
[8]
[2]
SCOE-NM
[1] Atabaki et al, Nature 556 (2018) 349 [2] SiC:Er research by S. Galis group [3] 7nm CMOS test chip fab’ed at SUNY Poly [4] MTJ fabricated at SUNY Poly, 2015