Quantum Computing in the Field of Earth Sciences

Rui A. P. Perdigão

Rui A. P. Perdigão

Muhammad Sahimi, Pejman Tahmasebi

Alessandro Sebastianelli, Francesco Mauro, Amer Delilbasic +7 more

Quantum machine learning (QML) is an emerging interdisciplinary field that employs quantum computing (QC) principles to address complex computational challenges. Traditional machine learning (ML) and deep learning (DL) models face major challenges in Earth observation (EO) due to the increasing volume and complexity of data. These challenges include computational intensity, energy consumption, and data management constraints. QML emerges as a promising paradigm for overcoming these barriers through quantum phenomena such as superposition, entanglement, and interference. This review aims at offering a detailed analysis of the state of the art and new trends in QML application to EO. This study methodically examines key advancements in QML for EO (QML4EO) through an exploration of the fundamental concepts of QML. The proposed review methodology involved systematic searches across prominent scientific databases, based on our extensive knowledge on the topic, using carefully formulated queries to ensure broad coverage and high relevance. In addition, this work addresses the changing institutional and geographic environment of QML4EO research, highlighting important centers of contribution and the important role of programs such as the IEEE Geoscience and Remote Sensing Society (GRSS) Quantum Earth Science and Technology (QUEST) Technical Committee. To transform QML from a specialized research area into a complementary and essential tool for advancing EO, this article critically analyzes current limitations and provides an outlook on future directions, highlighting the need for reliable hardware, improved algorithmic design, and standardized protocols.

Jevon J. Longdell

A great deal of theoretical activity has resulted from blending the fields of computer science and quantum mechanics. Out of this work has come the concept of a quantum computer, which promises to solve problems currently intractable for classical computers. This promise has, in turn, generated a large amount of effort directed toward investigating quantum computing experimentally. ¶ Quantum computing is difficult because fragile quantum superposition states of the computer’s register must be protected from the environment. This is made more difficult by the need to manipulate and measure these states. ¶ This thesis describes work that was carried out both to investigate and to demonstrate the utility of rare earth ion dopants for quantum computation. Dopants in solids are seen by many as a potential means of achieving scalable quantum computing. Rare earth ion dopants are an obvious choice for investigating such quantum computation. Long coherence times for both optical and nuclear spin transitions have been observed as well as optical manipulation of the spin states. The advantage that the scheme developed here has over nearly all of its competitors is that no complex nanofabrication is required. The advantages of avoiding nano-fabrication are two fold. Firstly, coherence times are likely to be adversely effected by the “damage” to the crystal structure that this manufacture represents. Secondly, the nano-fabrication presents a very serious difficulty in itself. ¶ ...

Milton Halem, Craig Pelissier, Michael M. Little +1 more