Quantum Technology Challenge 2022 (QTC2022)

Quantum technologies exploit the fundamental laws of nature to reach the ultimate limits of sensing, imaging, communications and computing. They are diverse, complex, and generally early in technical readiness and demand new ways of thinking about the employment and exploitation of technology. Their true capabilities, limitations and most disruptive applications are still being discovered. This combination of disruptive potential, ambiguity and complexity presents both strategic risks and opportunities to land forces. As a result, the Australian Army finds itself in an accelerating global competition to understand, co-develop and exploit quantum technologies in land operations.

The emergence of quantum technology is part of a larger transformation of warfare, where geopolitics, demographics and technology are driving changes in the character of warfare at a rate faster than which many of Army’s processes, concepts, capabilities and structures are designed. Army has termed this change Accelerated Warfare and has mounted the strategic response: Army in Motion. Army has identified that the emergence of quantum technologies will impact two of the major technological drivers of Accelerated Warfare: robotics and autonomous systems, and cyber and information warfare.

In response, Army released the Army Quantum Technology Roadmap. The Roadmap articulates Army’s plan to leverage Australia’s national strategic strength in quantum technology research, its emerging quantum industry and cooperation with aligned nations, to gain and retain an early quantum advantage.

The Department of Defence via the Australian Army and the Land Capability Division (Defence) is seeking proposals that will demonstrate solutions to The Challenge (defined below) at the Quantum Technology Challenge 2022 (QTC2022), tentatively scheduled to be held on 11 August 2022 at the Adelaide Convention Centre. This date and location may change in response to COVID-19 travel restrictions and Defence suitability requirements.

The Challenge

In this Challenge, Defence wishes to test if:

• quantum sensors can detect, locate and identify electromagnetic emitters with greater precision, range and bandwidth, whilst reducing (or at least not increasing) detector size, weight and power
• quantum computers can identify and classify features in signals and images more precisely and efficiently
• post-quantum cryptography can be practically employed to secure communications from the threat of quantum computers.

The following three sub-themes define specific examples of the above in land operations. These examples have been chosen because they are both sufficiently specific and tangible for respondents to make appropriate assumptions and produce meaningful results, whilst also being generalisable to other situations and tasks in land operations.

Proposals must directly address one of the sub-themes.

Sub-theme 1: locating electromagnetic emitters in the battlespace

Context: Friendly and enemy forces use electromagnetic emissions for a variety purposes, including communications (i.e. radio), detection and targeting (i.e. radar) and control of robotic and autonomous systems (i.e. UXVs). Consequently, locating and identifying enemy electromagnetic emitters is a key resource for Army intelligence, surveillance, reconnaissance and targeting. But, this is becoming increasingly challenging for a variety of reasons, including the rapidly growing density and diversity of emitters in the battlespace, countermeasures to existing means of detection, and the increasing range of communications, weapons and targeting systems. Thus, Army is seeking technologies that can detect electromagnetic emitters with greater precision, range and bandwidth, whilst reducing (or at least not increasing) the burden of detection (e.g. detector size, weight, power, consumables and cost).

Current electromagnetic emitters typically emit radio- or micro- waves. The emissions are generally intermittent, vary in pulse length and may hop between frequency bands. Current locating methods generally employ a network of listening stations that contain collectors (i.e. antennas, amplifiers etc) and detectors. Measurements of the time of arrival and amplitude of an emission at each station can be used to estimate the location of its emitter. Measurements of other signal characteristics, such as frequency, pulse length and their variation, can be used to identify the emitter. Thus, the key metrics for detectors in the stations is their bandwidth and how precisely they can measure the time of arrival, amplitude, frequency and duration of signals.

Task: Your objective is to demonstrate a quantum sensor that has the potential to be employed as a detector for locating and identifying electromagnetic emitters in the battlespace. How precisely can your sensor detect the time of arrival, amplitude, frequency and duration of radio- and/ or micro-wave pulses? What is the bandwidth of your sensor? What advantages does it offer over existing technologies?

Sub-theme 2: identifying threats and critical information in signals and images

Context: The number, diversity and sophistication of sensing and imaging systems in land forces are growing dramatically. The efficient and precise identification and classification of features in the volumes of data they yield is critical to the greater employment of robotic and autonomous systems, improvement of intelligence, reconnaissance, surveillance and targeting, and acceleration of human and augmented decision making in Army. The problem is that the implementation of current signal/ image processing and machine learning methods demand significant classical computing resources. Thus, either limiting the accuracy and precision that can be obtained in a given task or how close the task can be performed to the sensor (i.e. at the network edge). The latter is important to enhancing the resiliency and performance of communication networks by minimising transmission of unfiltered data. The recent DST Group led Quantum Computing: in focus event highlighted significant opportunity in this area for Quantum Computing and Army wishes to explore its application.

Task: Your objective is to demonstrate how a quantum computer can more precisely identify and/ or classify features in signals and/ or images than a classical computer (of similar size, weight and power) in the same amount of computing time. Use simple examples to perform your demonstration and extrapolate to problem scales that are more relevant to Army’s uses. Make reasonable estimates of the size, weight, power and operation times of the classical and quantum computing hardware required to perform the computations at scale.

Sub-theme 3: securing our communications against quantum computers

Context: Via Shor’s algorithm, large-scale quantum computers will pose a threat to many widely used public key cryptosystems by providing an efficient means to factor semi-prime numbers. In the future, yet to be discovered quantum algorithms may also provide efficient means to attack other cryptosystems, including those employed by militaries. Given that there is significant uncertainty in the time until such large-scale quantum computers and new quantum algorithms are developed, it is critical for Army to begin to understand how to secure its communication systems against quantum computers. In particular, the key considerations, constraints and limitations of the new technologies required for this security.

Post-quantum cryptography methods are highly attractive because they employ classical communications hardware, and so are likely to be more practical, scalable and nearer-term than quantum communications technologies. Leading methods include the round 3 finalists of the NIST Post-Quantum Cryptography Standardisation process. However, post-quantum cryptography methods will likely require upgrades to the current classical communications infrastructure due to their expected reduction in software efficiency. It is currently not clear how substantial these upgrades will need to be, what new constraints and limitations they will introduce, and what degree of security against current and future threats they will provide.

Task: Your objective is to demonstrate the implementation of one or more of the round 3 finalists of the NIST standardisation process to secure a simple communications network. Use your demonstration to identify the key considerations, constraints and limitations of the methods and the requirements they place on the classical communications hardware.