Public Funding for Nanolayers Research Computing Ltd

Quantum computing promises tremendous advances in a number of applications, including finance, medicine, cryptography, and materials simulation. The fundamental computation element of a quantum computer is the quantum bit, or qubit, and to perform calculations that are truly transformative, huge numbers of qubits (potentially millions) are required. We propose to develop a process for fabricating many more qubits than have previously been made. Furthermore, we will do so using the material system silicon, which is directly compatible with the only ready-made industry currently available for largescale market production of a many qubit quantum computer. Our qubits will be made from impurity atoms in silicon, known as dopants. This is done using a scanning tunnelling microscope (STM), which "feels" the atoms on a surface with an extremely sharp probe tip, much like an audio record player feels the grooves of a vinyl record. Previously, only a pair of dopant qubits have been made, and with no route to scaling-up to a useful number. In order to move and see the millions of individual dopant atoms that will make up a quantum computer, we require advanced machine controls and data processing tools. Nanolayers Research Computing will use the proprietary machine learning software they have pioneered to train the STM to perform control and processing tasks on its own, without human user intervention. The use of this type of data processing, also known as artificial intelligence (AI), is particularly well-suited to image processing and pattern recognition, and can be used to find the proverbial "needle in a haystack". This is exactly what needs to be done when we use a scanning tunnelling microscope to move and then see a large collection of atoms in a silicon quantum computer component. In short, this project uses artificial intelligence to control an atomic resolution microscope and precisely position a large number of individual impurity atoms in silicon. This technology will enable the eventual fabrication of a silicon-based quantum computer.