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Airbus sets quantum computing challenge to explore solutions
for aircraft life cycle, and QC Ware will provide cloud-based software
support for this project
News/ > 2019/ > Airbus sets quantum computing challenge to explore solutions for aircraft life cycle.../
Airbus sets quantum computing challenge to explore solutions for aircraft life cycle, and QC Ware will provide cloud-based software support for this project
22 February 2019 Airbus has launched a global competition in quantum computing, inviting experts to propose and develop solutions, for complex optimisation and modelisation across the full aircraft life-cycle, using newly available computing capabilities.

The Airbus Quantum Computing Challenge (AQCC) aims to take science out of the lab and into industry, by applying newly-available computing capabilities to real-life industrial cases.

With traditional computers approaching their limits, the quantum computer promises to deliver a new level of computational power. As an active user of High Performance Computing (HPC), Airbus is already extending current capacity by integrating and leveraging quantum technologies in fields such as route optimisation and satellite imagery.

Flight physics, the broad denomination of all scientific and engineering aspects related to the flight of aircraft, is at the heart of Airbus’ business. The topic affects virtually all aspects of an aircraft’s life: from design to operation, from the quality of movement through the air to the revenue stream of airlines. The full lifetime cycle features many computationally difficult problems.

Quantum computing has the potential to yield a paradigm shift in flight physics, one that could forever alter how aircraft are built and flown. Airbus is fuelling this transformation by laying down five challenges faced in aircraft design and in-service optimisation for enthusiasts and experts to resolve using quantum computing and embark on this transformation journey collaboratively.

Solutions will enable Airbus to assess how this burgeoning computational technology could be included or even replace other high-performance computational tools that, today, form the cornerstone of aircraft design. >>>
>>> Problem statement 1: aircraft climb optimisation

Aircraft follow several flight phases during their «mission» from take-off to landing. Cruise is the longest segment and is considered most important from a fuel and time optimisation perspective. Yet for the ever-increasing volume of short-haul flights, climb and descent are more critical. Fuel optimisation during these segments is very valuable for airlines. This problem focuses on the climb and how quantum computing can be applied to arrive at a low-cost index (the relative cost of time and fuel), which is central to climb efficiency. In particular, a quantum computer must consider parameters such as weather and tailwind at every point during a flight to suggest the best course.

Problem statement 2: computational fluid dynamics

The efficiency of aircraft design relies heavily on the aircraft’s overall aerodynamic shape. This design is performed using Computational Fluid Dynamics (CFD), demonstrate airflow behaviour around the aircraft and reveal the aerodynamic forces acting on its surfaces. However, accurate CFD simulations are a resource- and time-consuming task. This challenge aims to show how established CFD simulations can be run using a quantum computing algorithm or in a hybrid quantum-traditional way for faster problem solving and how the algorithm can scale in line with the problem complexity including computational resources.

Problem statement 3: quantum neural networks for solving partial differential equations

Solving Partial Differential Equations (PDEs) is a major challenge when solving aerodynamic problems. Today, their resolution requires complex numerical schemes and high computational costs. Traditionally PDEs were solved in a deterministic manner using numerical methods. Recently, neural networks — deep-learning-based algorithms — have been developed to solve coupled PDEs. These networks compute the time and space derivatives of a PDE. The proposed challenge is to augment this new approach for aerodynamic problems with quantum capabilities. >>>
>>> Problem statement 4: wingbox design optimisation

Given the limitations of traditional computing, the aerospace industry faces a challenge in optimising multidisciplinary design. That’s when design configurations such as airframe loads, mass modelling and structural analysis must be simultaneously calculated. This can cause long design lead times, convoluted processes and conservative assessments. Quantum computing offers an alternative path to explore a wider design space by evaluating different parameters simultaneously, thus preserving structural integrity while optimising weight. This balance is particularly important in aircraft wingbox design, where weight optimisation is key to low operating costs and reduced environmental impact.

Problem statement 5: aircraft loading optimisation

Airlines try to make the best use of an aircraft’s payload capability to maximise revenue, optimise fuel burn and lower overall operating costs. Their scope for optimisation is limited by the aircraft’s operational envelope, which is determined by each mission’s maximum payload capacity, the aircraft’s centre of gravity and its fuselage shear limits. The objective of this challenge is to calculate the optimal aircraft configuration under coupled operational constraints, thus demonstrating how quantum computing can be used for practical problem solving and how it can scale towards more complex issues.

Quantum computing taking off in aerospace industry

Grazia Vittadini, Aibus chief technology officer, announced this competition at the Digital, Life, Design Conference in Munich on Jan. 20. The winner of the challenge is expected to be announced during the first quarter of 2020.

Airbus SE is expanding its yearslong quantum computing research effort by seeking help from outside experts on tough flight physics problems, said Ms. Vittadini. The initiative builds on about two years of research into applying quantum computing to complex tasks by Airbus’s in-house staff and external vendors.

The European aerospace giant joins several other firms in finance, biotech and the automotive sector that are experimenting with how quantum computers could take on complex calculations that are far too time-consuming for classical computers. >>>
>>> «We are convinced that quantum technologies and specifically quantum computing do represent a breakthrough for different industries, including our own,» Ms. Vittadini said in an interview, adding that it could take about 10 years to bring quantum computing to everyday applications.

Nobody has yet built a quantum computer that can be used for large-scale applications, but companies and governments around the world are investing heavily in developing the technology. Experts estimate quantum computers are still about five to 10 years away from achieving their full potential, and different approaches are being tested.

While traditional computers store information as either 0s and 1s, quantum computers use quantum bits, or qubits, which represent and store information as both 0s and 1s simultaneously. That means quantum computers have the potential to sort through a vast number of possible solutions in a fraction of a second. «We’d like this to be the first step for us to engage with experts and enthusiasts in the field…in what we believe will be a quantum era in aerospace,» Ms. Vittadini said.

The company also has formed partnerships with research institutions to use quantum mechanics to encrypt sensitive data being sent to and from drones. «This technology will become an essential building block for secure communication for any unmanned vehicle, including unmanned flying taxis,» Ms. Vittadini said. In 2016, the company invested an undisclosed amount in the seed-funding round of QC Ware Corp., which connects enterprises via the cloud with quantum computing hardware providers including D-Wave Systems Inc. and International Business Machines Corp.

Airbus sought QC Ware’s help in understanding how quantum computing could be applied to mathematical calculations in the design phase of aircraft systems and parts, Ms. Vittadini said. Redesigning parts can be a time-consuming process with classical computers, which can take days to perform calculations. The companies found that the time it takes to calculate the result was four times faster with a quantum computer, Ms. Vittadini said. >>>
>>> Introduction to QC Ware

QC Ware is a quantum computing software company based in Palo Alto, and it is now opening its European headquarters in Paris. The fast-growing firm has established itself as a leader in the nascent QC software space and is working with a number of Fortune 100 companies to develop prototype solutions and algorithms for some of their hard computing problems.

QC Ware has developed a hardware-agnostic software platform that serves as the «delivery vehicle» for those applications. The platform also provides a much-needed abstraction layer, which allows classically-trained data scientists to run problems on prevalent QC hardware stacks that are currently commercially exposed.

QC Ware’s mission

Matt Johnson, company’s founder and CEO, explained that QC Ware’s mission is to be a leading software solutions provider for enterprises, and that the company is playing the long game to achieve that goal. QC Ware has assembled one of the largest teams of quantum algorithms researchers in industry, and their sole focus is exploring methods to squeeze power out of the early-generation quantum processors that are being fielded by QC hardware developers such as IBM, Google, Rigetti and D-Wave Systems. The quantum computers that are being fielded today are referred to as having «noisy» processors, which means they are not fault-tolerant and hence calculations are subject to error.

Quantum algorithm experts

And that is where QC Ware’s team of algorithm experts come into play. They work to express these problems in ways that make it possible to execute them on noisy quantum processors. Their goal is to construct so-called shallow-depth circuits on which the problems can be run. For the non-computer scientists in the room, that means they find mathematical shortcuts to minimize the number of steps (e.g., gate operations) required to solve the problem on a quantum processor. >>>
>>> Solutions for practical problems and applications

So what kinds of practical problems can these computers solve? Broadly speaking, quantum computers are able to solve problems in optimization, simulation, and machine learning. QC Ware is already running small-scale versions of such problems on quantum computers, but there are two things preventing QC systems from outperforming today’s «classical» computers. The first is the sheer size of today’s quantum processors. They lack enough physical qubits (think quantum transistors) and sufficiently high-quality qubits to produce any «wow» factor that an ROI-sensitive buyer or user cares about. In addition, the few useful quantum algorithms that have been invented to date (those that have a provable speedup over classical algorithms) need to be extended to handle the idiosyncrasies of practical computing problems. QC Ware is leaving the first problem in the hands of the QC hardware developers and is focusing exclusively on the algorithm/application development challenge.

QC Ware is employing this expertise with companies in various sectors including financial services, oil/gas, aerospace, and automotive. These companies all have computing bottlenecks, and they would have a competitive advantage if they were able to solve those problems faster.

Some of the problems Airbus wants to tackle include tasks that can be solved in minutes with a quantum computer, versus hours with a classical computer, said Mr. Johnson.

Enterprises across industries now realize that quantum computing isn’t just «vaporware» — an idea without a product to test, he said.

«Just about every company that has a long product life-cycle and some research and development component has this on their radar,» Mr. Johnson said. >>>
>>> Value to QC Ware customers

Yianni Gamvros, QC Ware’s head of business development, explained that the immediate benefit to getting involved in quantum computing today for enterprises is to start building the necessary skills to take advantage of quantum computing as soon as it is ready for production problems. Whoever starts investing now will be better prepared for the future when quantum computing will disrupt existing industries and create new ones in the same way machine learning and AI is doing today.

QC Ware’s objective while working with large companies is to build a software bridge between the API’s that the QC hardware vendors provide and the problems that the enterprise user has. QC Ware’s cloud platform provides users with a hosted jupyter notebook that has QC Ware’s python libraries pre-loaded and -configured. Users can also get an API key and use the python API from local installations. The company will also roll out APIs in other high-level languages such as Java and C++.

One unique attribute of the service is that it allows users to run problems on a variety of QC hardware platforms. QC Ware has managed to abstract away the programming complexity for each of the QC hardware platforms currently exposed so that users can easily run a particular job on any platform without having to re-formulate the problem or undertake any additional programming steps.

The company tested an alpha version of its service since last summer, and it will be launching an expanded beta version later this year. This version of the service will be made available to commercial enterprise users and government agencies–either as a stand-alone service or as part of a software development project. The cash generated from those services is plowed back into what QC Ware calls applied research. Its algorithm team spends its time figuring out how to map enterprise problems onto quantum algorithms, and to run those problems on QC hardware platforms. The work product of the research is function libraries and specialized algorithms that make their way into QC Ware’s cloud service. >>>
>>> Viewed from that angle, QC Ware’s business is on its way to becoming a force that is equal parts Oracle and Redhat. Oracle, in that it is making a hard-to-use resource accessible to the broad enterprise community. Remember that back in the 1970’s, relational databases were viewed as unbuildable curiosities and would be impossible to manipulate. Redhat, in that QC Ware’s software platform, sits on top of the basic API’s provided by QC hardware vendors. Their platform encapsulates an interface that allows classically-trained enterprise users (with no presumed QC knowledge) to interact with a stable, commercial-grade cloud service.

Both Matt and Yianni have a realistic view of the technical challenges that must be addressed to make QC a useful resource for enterprises. They are nonetheless moving out at a fast pace on software development because they are taking the view that the QC hardware vendors will solve those engineering and materials problems.

There is some risk attached to QC Ware’s thesis, but then again risk is not a foreign concept in QC Ware’s hometown of Palo Alto.

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