Alvaro Bermejillo

C12 quantum electronics
Title of Poster
High throughput characterization tools for carbon nanotube spin qubit integration
Abstract Regular

C12 quantum electronics is a deep tech start-up aiming at building a reliable and scalable quantum processor. The technology is based on manipulating the spin of an electron hosted in ultra-clean carbon nanotubes (CNTs), the closest realization of a single spin in vacuum- where we expect ultra-low decoherence rates. The information is processed by coupling the spin to superconducting microwave circuits. We aim to develop a scalable quantum platform with all-to-all connectivity thanks to the engineering of coherent coupling between the semiconducting qubits and the electromagnetic modes of a high quality resonator.

Our approach relies on massive feedback between the micro-chip properties, the carbon nanotubes properties, and the measured qubit performance. The unique technology relies on the quality of the material (the CNT) and the assembling technology not involving any chemical\physical treatment. Furthermore, a large number of high quality microchips is needed to get this fast-feedback and tune workflow to make high quality qubits. A fast selection process of the ‘ideal’ CNTs is critical. In this poster, I will present the characterization tools we are developing to assess the quality of the tubes before and after integration. The pre-selection of CNTs is relevant because the tubes are assembled on the last fabrication step on a fully processed silicon chip that we believe helps to preserve its pristine properties.  The carbon nanotubes are characterized and selected via optical spectroscopy (Raman and Rayleigh) and then undergo transport measurements. From the optical spectra, we can extract information about the material itself (quality and contaminations) and its environment (metal contact and adsorbates). Those parameters influence extremely the qubit performance. In addition, we are developing machine learning algorithms to analyze the large dataset that we will acquire and find correlations to define an optimum fabrication recipe.

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Poster Session