Your research ideas to advance quantum information processing

Background and Motivation

The concept of employing quantum mechanical systems to perform computations or optimisations has developed over the past 40 years from an initial principle to an eagerly anticipated technology. Researchers hope that by leveraging the phenomena of superposition and entanglement, the complexity of solving common difficult problems may be reduced. Currently, there are two main approaches to using quantum systems to solve information processing problems. The first approach is to develop a quantum computer [1]. This is a device comprised of a number of logical qubits whose state can be prepared, manipulated, and read. Such a manipulation is called a gate and may address one or more qubits at once, interacting with different parts of the system. An algorithm in the form of a series of gates, called a circuit, may be run on the computer. A growing collection of algorithms have been found [2] that can run on the same, universal, quantum computer to tackle various problems. A notable example is Shor’s algorithm for factoring numbers, which outperforms the best classical methods with a superpolynomial speedup. The second approach is to develop a quantum annealer, or adiabatic quantum computer [3]. 

Quantum annealers show potential to solve difficult optimisations by using qubits with tunable mutual interactions to produce Hamiltonians that encode a problem. By slowly changing the Hamiltonian of the system, an initial ground state moves to the ground state of the target potential and a solution to the problem is found. Although these two approaches differ in objective, both need to overcome the obstacle of decoherence. All quantum information processing technologies require careful shielding of fragile quantum states whilst allowing for selective interaction between parts of the system, and eventually measurement. Overcoming decoherence represents an enormous engineering challenge, often incorporating low temperatures and precision fabrication. Beyond the technical feasibility of these technologies, conceptual issues remain to be solved. Quantum information processing is often touted to provide applications in many areas, from material science, drug research, and machine learning. However, these devices will not generically speed up all computation [4]. The algorithms discovered so far address a small class of problems, leaving many classically difficult problems still practically intractable. Substantial work is needed to identify precisely how future quantum technologies could be used to tackle these real-world tasks [5].   

Current Forefronts of Quantum Computing 

Today, various quantum computers with dozens of logical qubits and annealers with thousands of qubits are publicly available for use [6, 7]. However, despite many milestones having been reached recently [8], these devices have not seen wide-scale uptake outside of research environments, at least partially. Due to their limited number of qubits and low fidelity these devices are often described as Noisy Intermediate-Scale Quantum (NISQ) technologies. 

Within the foreseeable future, quantum computers will be limited in their scale and fidelity to the extent that their use will be restricted to performing part of a larger classical computation. As such, there has been great interest in using quantum devices to perform subroutines that are used in machine learning applications. Parallel to these efforts, researchers are working to find applications of quantum annealers. For example, they have been used to solve quadratic unconstrained binary optimisation problems, finding potential applications in areas such as air traffic management [9]. In addition, quantum computing has the potential to improve performance, decrease computational costs and solve previously intractable problems in Earth observation (EO). 

In particular, it could become a key capability for demanding EO applications and techniques such as data storage and retrieval, image processing, artificial intelligence and machine learning [10], and optimisation or simulation of complex systems. This Call for Ideas focuses on novel quantum information processing technologies or major advancements in currently proposed concepts that can be applied to ESA's activities. 

Research and Study Objectives 

The main aim of this call is to perform research on new and innovative scientific and technical concepts and techniques for quantum information processing. For the retained ideas, the first most important research step will be performed during the study. In principle, all scientific fields of potential relevance are encouraged to propose solutions.   

Main elements of ideas 

Ideas should contain: 

1. A description of the general idea
2. How the concept/idea can either substantially improve the state of the art or is substantially different to already described ones
3. The research step to be carried out that addresses and matures a key aspect of the concepts
4. Identification of possible demonstration opportunities for the proposed concepts. This may include the use of publicly available quantum computers highlighted above, for example IBM Quantum Experience (https://quantum-computing.ibm.com/) or D-Wave Leap (https://www.dwavesys.com/take-leap.

While completely novel ideas will be given preference, proposals which constitute a major improvement on an existing concept will also be considered. The proposed research scope needs to be feasible within the Ariadna study framework (www.esa.int/ariadna) or as a co-funded research activity (Discovery Ideas Channel) and constitute an important step towards implementing quantum information processing technology.  Proposers should underline their reasoning with references to published papers and research results and, where relevant, include an evaluation of the reference material attached to this call.   

Implementation Paths 

Retained ideas will be implemented in one of the following ways 

• An Ariadna study with ESA's Advanced Concepts Team (ACT): Activities under this heading typically last four months and are funded with 30 k€. Ariadna is mechanism for collaborative joint research projects between ESA's internal research think tank, the Advanced Concepts Team and academia.
• A Co-funded research activities: Activities under this heading last between six months and three years, with ESA co-funding typically of 20–90 k€. Co-funded research activities include the co-funding of PhDs and post-docs, as described for Discovery Preparation studies in the discovery ideas channel. Research activities related to quantum information processing and Earth Observation will be conducted together with ESA's Φ-lab. All other retained quantum information processing research activities could be included in a general co-funded research activities frame.

In all cases please clearly formulate a short and poignant research question, and describe the differences between your ideas and the latest published research in this field Authors are invited to state their intended implementation path when submitting the idea.   

Process 

The first step is to propose an idea through this channel. This is in the form of a short description of the idea, including an indication for which of the aforementioned implementation paths it is intended (or both). All ideas will then be reviewed by our evaluation board based on the evaluation criteria given below. In a second step, the authors of selected ideas will then be invited to submit a research proposal via a template according to the implementation paths. A proposal review will select the ideas to be implemented dependent on the nature of the proposed study.   

References 

Banner Photo Credit: IBM Research Michael 

1. A. Nielsen and Isaac L. Chuang. Quantum Computation and Quantum Information: 10th Anniversary Edition. Cambridge University Press, 2010.
2. Quantum Algorithm Zoo.
3. Tameem Albash and Daniel A. Lidar. Adiabatic quantum computation. Rev. Mod. Phys., 90:015002, Jan 2018.
4. Scott Aaronson. Read the fine print. Nature Physics, 11(4):291–293, Apr 2015.
5. Ashley Montanaro. Quantum algorithms: An overview, 2016. npj Quantum Inf 2, 15023 (2016).
6. IBM Q Experience.
7. D-Wave Leap.
8. Quantum supremacy using a programmable superconducting processor. Nature, 574(7779):505–510, 2019.
9. T. Stollenwerk, B. O’Gorman, D. Venturelli, S. Mandra, O. Rodionova, H. Ng, B. Sridhar, E. G. Rieffel, and R. Biswas. Quantum annealing applied to de-conflicting optimal trajectories for air traffic management. IEEE Transactions on Intelligent Transportation Systems, 21(1):285–297, 2020.
10. Biamonte, J., Wittek, P., Pancotti, N., Rebentrost, P., Wiebe, N. & Lloyd, S. Quantum machine learning. Nature 549, 195–202 (2017).

Special Conditions

The Campaign/Channel is open for submissions for participants registered in one of ESA Member States, Associate Member States or Cooperating States. 

For general conditions of participation to this campaign, please refer to the above document.
Please note, that restrictions exist for certain implementation paths, e.g. ESA procurement actions are restricted to entities eligible for doing business with ESA (see also here).
In addition to the provisions in the General Conditions of Use of the Open Space Innovation Platform (OSIP) (e.g. article VI) and the General Conditions of Participation to Campaigns and Channels organised by ESA in OSIP (e.g. article 4.3) idea will be excluded, which:

• do not clearly describe an activity to be pursued by ESA
• do not show a minimum quality in the submission which includes, for example, scientifically proper citing, clear stating of objectives
• have no clear space application
• violate fundamental laws of physics
• cannot be implemented via one of the proposed implementation schemes; research co-sponsorship, study or early technology development (however the option of being redirected to another scheme remains potentially open)
• have already been submitted to ESA, including via other OSIP Channels or Campaignsare submitted by a participants not registered in one of ESA's Member States, Associate Member States or Cooperating States.

Evaluation Criteria

Ideas submitted through this channel will be evaluated based on: Novelty of the proposed ideaClarity of the short description of the ideaApplicability to space and ESA's activities