ORGANIZED BY
JUNE 20TH
2019
French industrial quantum use cases
Henri CALANDRAExpert in Numerical algorithms and High Performance Computing for Geosciences at Total E&P
Scientific Advisor for Total Corporate Research, France
Quantum Computing @ TOTALHenri Calandra, TOTAL E&P
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Why explore Quantum computing technology?EXPLORE QUANTUM COMPUTING TECHNOLOGY
WHAT HAVE WE DONE SO FAR…
CONCLUSION
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Why explore Quantum computing technology?
Toward more and more complex classical HPC systems
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✓ Classical computers have fundamental limits:
▪ Transistor scaling
▪ Energy consumption
✓ HPC systems are likely to become much more heterogeneous and
massively-parallel systems
▪ Parallelism limitations: Adhams’law
✓ End of Moore’s law is expected by around 2025 !!
Compute requirements continue to grow
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✓ Seismic depth imaging:
✓ compute better, faster
✓ More physics
✓ More data integration
✓ Uncertainty quantification
✓ Reservoir simulation:
✓ Compute faster
✓ Better predictability
✓ Multi real time simulations✓ Inversion of subsurface models
✓ operations optimization, ✓ cost and risk reduction
✓ More complex targets:✓ strong geological heterogeneity – several reservoirs
✓ Massive simulations:✓ history matches; uncertainty Mgt on huge models
✓ New physics for EOR & integration of different processes incl. geomechanics
An there’s more we want to do
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Machine learning, HPDA
✓ Development of new training set
and algorithms
✓ Classification and sampling of large
dataset
✓ Physics-constrained neural nets…
A
B
Liquid
Vapor
Combinatorial optimization
✓ MINLP (Mixed Integer Non Linear
programming) problems in general
including:
✓ Refinery blending,
✓ Scheduling, production, shipping.
✓ Oil field/reservoir optimization
✓ ….
Computational material science
✓ The ability to accurately model
ground states of fermionic systems
would have significant implications
for many areas of chemistry and
materials science:✓ Catalysis, Solvents, Lubricants,
batteries…
An there’s more we want to do
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Machine learning, HPDA
✓ Development of new training set
and algorithms
✓ Classification and sampling of large
dataset
✓ Physics-constrained neural nets…
A
B
Liquid
Vapor
Combinatorial optimization
✓ MNILP problems in general including:
✓ Refinery blending,
✓ Scheduling, production, shipping.
✓ Oil field/reservoir optimization
✓ ….
Computational material science
✓ The ability to accurately model
ground states of fermionic systems
would have significant implications
for many areas of chemistry and
materials science:✓ Catalysis, Solvents, Lubricants,
batteries…
✓ Compute better, compute faster
✓ Solve intractable problems on classical High Performance Computing
Explore Quantum computing as a disruptive technology ?
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explore Quantum computing technology
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0
QUANTUM HARDWARE DEVELOPMENT IS ACCELERATING
✓ A groundbreaking new approach to pave the way for the future of scientific computing
beyond exascale ?
A very challenging technology
✓Quantum Hardware comes in many forms (supra-conductors, ion trap, photonics…)
✓ Still limited to few ten’s of qubits NISQ (Noisy Intermediate scale Quantum device)
From Denis Vion, CEA, 41th Orap Forum
IBM
Rigetti
IONQ
XANADU
OBJECTIVEs
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✓ Understand Quantum Computers technology evolution
D’WAVE computerIBM Q
Google: bristlecone Rigetti : 16Q Aspen
✓ Accelerate and build in-house competencies skill set with research
partners and hardware providers ecosystem to develop algorithms for
Total business use cases
✓ Be ready when industrial quantum computers become available and quantum supremacy is
demonstrated.
✓ Quantum computing is a huge paradigm shift and Quantum algorithmics is a brand new science
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Anticipated Impact ( what we expect)
✓ Compute better, compute faster
✓Open new frontiers in R&D for Chemistry, material science, optimization, machine learning,….
Quantum linear algebra
(qublas), solving ODEs. PDEs,
inverse problems…Quantum
combinatorial
optimization
Quantum machine
learningQuantum Chemistry
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What have we done so Far…
Define an appropriate R&D roadmap and potential Use CASES
Quantum combinatorial
optimization
Quantum machine learningQuantum Chemistry
NISQ device ~ (102 qubits) 3-5 years (pre)-QEC device ~ (103(-6) qubits) 5+ (++?) years
Quantum linear algebra (qublas), solving ODEs. PDEs,
inverse problems…
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Quantum Computing at Total
Q Hardware Q Software Applications
Math librariesATOS QLM - emulator
Verification: simulation, benchmarking, testing
Chemistry, Material Science
Optimization, Machine Learning
Hybrid (QC-HPC)
Gate-based (IBM, Rigetti, google…)
Annealer ( D-Wave,….)
Programming models
Hybrid computing ODEs, PDEs, linear algebra, inverse problem…
Quantum computing global program overview
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academic and industrial collaborations network
Collaboration agreement, purchase of a 30 and 35 qubits QLM
ATOS QLM-30 system, installed September 2018, ATOS QLM 35 Qubits system upgrade in progress
Quantum Machine learning
for industrial applications.
Ph.D. 07/01/2019-
06/30/2024
Quantum Derivative free
gradient optimization for
inverse problems
Ph.D. 10/01/2019-09/30/2024
Jülich Unified Infrastructure for Quantum computing (JUNIQ)
2 months internship on quantum micro benchmark
Quantum Gibbs sampling on
NISQ devices. 2 years PostDoc,
09/01/2019-08/31/2021
EU-Project (FETFLAG-QUANTUM): PasQuans
Quantum Seismic Imaging, 2 years postdoc,
07/01/2019-06/30/2021
Qualitative Computing for Quantum Computing,
2 years postdoc, 07/01/2019-06/30/2019
Construction of a QBLAS library, Ph.D. 10/01/2019-09/30/2022
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Get one’s hands dirty in Programming models and algorithm design✓ Examples of on going dev:
✓ NISQ oriented applications development on ATOS QLM : VQE and QAOA
VQE QAOA
✓ Understand existing implementations: QISKIT (IBM), Pyquil (Rigetti)….
✓ Understand actual limitations (HW and algorithm) and possible test cases.✓ « hybrid » programming , mixing quantum speedup procedures and classical ones
conclusion✓ Quantum computing is a huge paradigm shift and Quantum
algorithmics is a brand new science
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GROVER ALGORITHM
✓ Quantum computing can provide new opportunities,
opening new frontiers in R&D in many fields of application.
✓ Set up a good academic, partners and industrial network
based on an appropriate research program
✓ Build internal skills to develop algorithms for Total business use case
✓ Quantum Computing for Industrial Applications Project:✓ 2018: project design, collaboration setup , purchase of a QLM30 qubits
✓ 2019: ✓ 2(3) Total researchers,✓ 3 Postdocs and 3 PhDs,✓ Upgrade to a QLM 35 qubits✓ Develop internal skills on NISQ devices
