Warmstarting Techniques Enhance Efficiency, Reduce Wait Times in Quantum Computing

Warmstarting is a technique used in quantum computing to address the limitations of Noisy Intermediate-Scale Quantum (NISQ) computers, which are characterized by low numbers of qubits and high error-proneness. The technique reduces quantum resource consumption by using known or inexpensively generated approximations, solutions, or models as a starting point, rather than starting from scratch. This approach increases the efficiency of quantum applications and reduces waiting times, particularly important as quantum computation on NISQ devices is currently possible only via limited cloud services. The future of warmstarting techniques lies in developing a systematic overview of existing techniques through a systematic mapping study.

What is Warmstarting in Quantum Computing?

Warmstarting is a technique used in quantum computing to address the limitations of Noisy Intermediate-Scale Quantum (NISQ) computers. These computers are characterized by low numbers of qubits and a high error-proneness, which limits the size of quantum algorithms they can successfully execute. Warmstarting techniques aim to reduce quantum resource consumption by utilizing known or inexpensively generated approximations, solutions, or models as a starting point to approach a task, instead of starting from scratch. This facilitates the design of algorithms that suit the capabilities of NISQ computers.

The term “warmstarting” is widely used in classical computation, such as machine learning and optimization, to describe techniques that reduce the usage of resources. The idea is to use known or inexpensively generated approximations, solutions, or models as a starting point to improve upon, instead of starting from scratch. Another category of warmstarting techniques in classical computation focuses on preparing an execution environment, such as reusing a running container in Function-as-a-Service offerings, as opposed to cold-starting a new container.

How is Warmstarting Applied in Quantum Computing?

In the domain of quantum computing, warmstarting techniques differ significantly from each other in various properties. For example, they target a quantum algorithm in different ways, such as biasing the initial quantum state as opposed to selecting advantageous initial circuit parameters in Variational Quantum Algorithms (VQAs). Furthermore, different warmstarting techniques may be applicable in conjunction with each other. However, approaches on how to categorize them and check their compatibility with each other are currently missing.

The application of warmstarting techniques in quantum computing is aimed at increasing the efficiency of quantum applications and reducing waiting times. This is particularly important as quantum computation on NISQ devices is currently possible only via cloud services from a limited number of vendors. Computational tasks on NISQ devices can be either scheduled via reserved time slots or queued for execution on the respective cloud offering. In both cases, quantum devices may not be available as needed or only after an undesirable significant waiting time.

What is the Current State of Research on Warmstarting Techniques?

While a number of publications focus on the topic of warmstarting quantum algorithms, there are no comprehensive secondary studies aiming to categorize such approaches. Many of these warmstarting techniques in the quantum computing domain differ significantly from each other in various properties. Therefore, a categorization of warmstarting techniques and an overview of their properties would be beneficial to researchers and quantum software engineers to understand which techniques or combinations thereof suit their quantum applications.

The current state of research introduces various techniques addressing the limitations of NISQ computers by utilizing known or inexpensively generated approximations, solutions, or models as a starting point to approach a task, instead of starting from scratch. These so-called warmstarting techniques aim to reduce quantum resource consumption, thus facilitating the design of algorithms suiting the capabilities of NISQ computers.

What is the Future of Warmstarting Techniques in Quantum Computing?

The future of warmstarting techniques in quantum computing lies in the development of a systematic overview of existing state-of-the-art warmstarting techniques employed in the domain of quantum computing. This can be achieved by means of a systematic mapping study (SMS). The study relies on established guidelines for SMSs. The multiphase literature search and selection process comprises database searches, snowballing, and precise selection criteria to identify relevant research.

The results of such a study would provide insights into the research field and help quantum software engineers to categorize warmstarting techniques and apply them in practice. Moreover, the contributions may serve as a starting point for further research on the warmstarting topics since they provide an overview of existing work and facilitate the identification of research gaps.