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A preview of Quantum Technology Challenge 2022

Quantum Technology
Emerging Technologies
RICO

A big thank you to all the teams and exhibitors involved in the successful conduct of Army’s Quantum Technology Challenge 2022 held in Adelaide earlier this month. Stand by for an in-depth announcement and review of the challenge on the Army Land Power forum soon.

This article provides a preview of the recent Quantum Technology Challenge (QTC) 22 Demonstration Day in Adelaide on 10 August 2022.

Background

The Army’s Quantum Technology Roadmap highlights quantum technology solutions and potential capabilities in the land domain. As part of this initiative, the QTC is an annual series of events that see teams of Australia’s world-leading quantum scientists and engineers competing to show how quantum technologies can solve important Army problems and deliver unprecedented capabilities. QTC 2022 is the second iteration of Quantum Technology Challenges (see the QTC21 problems and solutions, and the video of the QTC21 Demonstration Day).

In order to expand the opportunities for soldiers, officials and industrialists to gain tangible experience of quantum technologies and their uses, in 2022 Army extended invitations to a wider cross-section of Defence, government and industry groups.

Demonstration Day

The QTC22 Demonstration Day provided an opportunity for service members to become more aware of the potential applications of Quantum Technology in the land domain, as well to generate a better understanding of the technology and leverage of the ‘Quantum Advantage’.

The proceedings of the Day included:

  • a series of keynote presentations from distinguished guests, such as Australia’s Chief Scientist (Dr Cathy Foley) and the Branch Chief of Quantum Sciences at the United States Army Research Laboratory (Dr Fredrik Fatemi).
  • 11 teams exhibiting quantum technology demonstrations, including:
    • 6 teams participating in QTC22
    • the top-ranked team from Quantum Next Generation 2021 (QNG21)
    • the top-ranked team from Quantum Camouflage Challenge 2021 (QCamo21).
    • 3 teams undertaking Exploit Projects following QTC21 in subterranean imaging (QuantX Labs and QDM) and logistics optimisation (Q-CTRL) using quantum sensors and computers, respectively (see the QTC21 problems and solutions)
  •  Pitches from the 6 QTC22 teams and the QNG21 and QCamo21 teams.

A preview of the QTC22 Teams and their solutions

Eight months ago, QTC22 applicants participated in a selection process. Based on that process, six teams were awarded seed funding to prepare their solution for the Demonstration Day. The pitches and demonstrations they deliver on the day will be evaluated by an expert panel, drawn from across Defence and industry. The top-ranked teams will then be invited to submit proposals for the further development and evaluation of their solution over the next 1-2 years. 

The Challenge themes and teams that participated in QTC22 are: 

Theme 1 - Locating electromagnetic emitters in the battlespace: Can quantum sensors detect, locate and identify electromagnetic emitters with greater precision, range and bandwidth, whilst reducing (or at least not increasing) detector size, weight and power?

Q-CTRL

Q-CTRL is a global quantum technology startup headquartered in Sydney developing advanced quantum-powered technologies through a unique focus on quantum control. 

For QTC 2022, Q-CTRL will demonstrate the potential for quantum magnetometers to detect and localise an electromagnetic emitter in the battlespace. This proof-of-concept demonstration will utilise a 2x2 array of quantum magnetometers to detect and localise a small electromagnetic emitter within the VLF band. 

The Q-CTRL team, consisting of experts in quantum magnetometry, as well as electronics and systems engineers. Their complementary expertise is required to transform quantum magnetometers from historically lab-based devices to those compatible with field deployment.

A three dimensional CAD render of Q_CTRL’s 2x2 quantum magnetometer array locating a small electromagnetic emitter.
Figure 1: a three dimensional CAD render of Q_CTRL’s 2x2 quantum magnetometer array locating a small electromagnetic emitter

Monash Optical Magnetometry Team

Monash University’s School of Physics and Astronomy are developing high-bandwidth vector optical magnetometers using electron spins in diamond. The Monash team is focusing on developing compact and robust optical devices that don’t sacrifice magnetic sensitivity or bandwidth. 

The Monash team’s device is a vector magnetometer. This device can determine the magnitude and direction of electromagnetic waves from an electromagnetic source. They are developing a novel optical design and read-out methodology to make field deployable vector magnetometers that have the sensitivity to measure the magnetic component of high-frequency electromagnetic waves, i.e. a vector magnetic antenna. 

A laser passing through a diamond containing many of the defects that the Monash Optical Magnetometry Team use to perform quantum magnetometry. The defects absorb the green laser light and emit a red fluorescence.
Figure 2: A laser passing through a diamond containing many of the defects that the Monash Optical Magnetometry Team use to perform quantum magnetometry. The defects absorb the green laser light and emit a red fluorescence.

Theme 2 - Identifying threats and critical information in signals and images: Can quantum computers identify and classify features in signals and images more precisely and efficiently?

University of Melbourne Quantum Adversarial Learning for Threat Identification and Mitigation 

The University of Melbourne (UoM) team is developing a quantum solution to achieve computational efficiency and robustness in machine learning algorithms that underpin many autonomous military systems, including those deployed in cyber and electronic warfare.

UoM aims to answer the critical question of if - or when - quantum advantage can be achieved for machine learning tasks when compared to their classical counterparts. A key feature of UoM’s approach is quantitative benchmarking of transferability across quantum and classical machine learning implementations in the context of a range of adversarial attacks.

By undergoing adversarial training, the established quantum and hybrid quantum-classical machine learning frameworks will offer rapid identification of data manipulation attacks and their mitigation in realistic complex environments that are relevant to Defence applications.

A schematic representation of UoM team’s concept for the implementation of robust quantum adversarial machine learning against data manipulation attacks. An Attack Image fools a trained classical neural network to misclassify a STOP sign as a YIELD sign. However, the trained quantum network exhibits correct classification on both clean and attacked images. (Image credit: UoM Team)
Figure 3: A schematic representation of UoM team’s concept for the implementation of robust quantum adversarial machine learning against data manipulation attacks. An Attack Image fools a trained classical neural network to misclassify a STOP sign as a YIELD sign. However, the trained quantum network exhibits correct classification on both clean and attacked images. (Image credit: UoM Team)

Silicon Quantum Computing

Silicon Quantum Computing Pty Limited (SQC) is an Australian quantum computing company. With a full-stack team in-house (including fabrication facilities) SQC delivers customised, high-quality solutions to its clients. 

For the QTC 2022 challenge, SQC will determine where quantum computers may offer advantage over classical computing in the area of threat and critical information extraction in signals and images. To increase confidence in these estimates, the SQC team has deconstructed the problem into three components: data loading; feature identification and extraction; feature classification. 

SQC will also determine the resources required and timeframes to realise this quantum advantage. Given that SQC fabricates world-leading quantum hardware in-house, this resource estimation will also be considered based on SQC’s atomic qubits in silicon hardware. 

Figure 3: The silicon-based quantum computer being developed by Silicon Quantum Computing.
Figure 4: The silicon-based quantum computer being developed by Silicon Quantum Computing.

Theme 3- Securing our communications against quantum computers: Can post-quantum cryptography be practically employed to secure communications from the growing threat of quantum computers?

QuintessenceLabs

The QuintessenceLabs team will demonstrate communications over a secure link established using Quantum Resistant (QR) algorithms. The team will present the feasibility of migrating to QR algorithms, including impact on performance and computer resource needs.

The approach taken will centre on replacement of a standard secure communications software library with an alternative that uses NIST round 3 QR algorithms for key agreement and authentication. The library will be used to establish a secure communications channel that will demonstrate the carriage of secure data, including command, control, and video and audio feeds, between a simulated remote asset and a central control and monitoring facility. 

Figure 4 – Quintessence Lab’s concept of securing a communications channel using quantum resilient cryptography methods.
Figure 5: Quintessence Lab’s concept of securing a communications channel using quantum resilient cryptography methods.

Outlander Solutions Pty Ltd

Outlander Solutions Pty Ltd provides advanced communications and intelligence technology solutions and management consulting services to Defence and Government. Outlander Solutions is 100% Australian owned and operated. The QTC has supported Outlander Solutions to develop and demonstrate a 6th generation risk and assurance system to support advanced Cryptography and Tactical communications risk management tools that implement the latest National Institution Standards Technology (NIST) cryptographic competition winners into fieldable ADF capability.

C4NxusTM system uses propriety Lattice-AiTM hosting and compute technology to deliver modular and configurable communications, optimised edge-processing and scalable systems that include both Android and Linux operating systems. Lattice-AiTM technology enables C4NxusTM system to operate in secure environments through integration of command and control of cryptography, content encryption, TRANSEC and cross-domain capability.

To Learn More.  For more information, about QNG21 and QCamo21, go to the Land Power Forum post: Outcomes of Quantum Next Generation 2021 and Quantum Camouflage Challenge 2021 | Australian Army Research Centre (AARC). Further details about access to materials from the QTC Demonstration Day will be made available through the Land Power Forum, including videos of the pitches that will be released shortly after the event. 

The views expressed in this article and subsequent comments are those of the author(s) and do not necessarily reflect the official policy or position of the Australian Army, the Department of Defence or the Australian Government.

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