Searcharxiv⌕ Search

arXiv subjects

Ethan G Arnault

Publications and source records attributed to Ethan G Arnault.

2 recordsLinked to original sources

Spatially Dense, Continuous-Variable Quantum Computing with Solid State Spin Nonlinearities

Nanomechanical structures have been investigated as a method of achieving long-lived quantum excitations at radio frequencies. Their high quality factors are especially intriguing as a medium for bosonic encoding of quantum information. However, to leading order, mechanical modes typically lack the nonlinearities necessary to achieve interaction between bosonic channels and thus are limited in their ability to scale to the many-qubit regime necessary for practical quantum computing. In this work, we propose and describe an approach for bosonic quantum information processing that uses strain-sensitive solid-state spins as nonlinear elements to produce the relevant nonclassical mechanical states. We outline the architecture required to achieve nearest-neighbor connectivity between mechanical cat-state qubits on-chip, as well as the control and readout architecture required for universal quantum computation. In addition, we show that this architecture can allow for a high spatial density of logical qubits by leveraging both the efficiency of bosonic error correction schemes and the small sizes of the constituent nanomechanical resonators and spin qubits. Finally, we identify the necessary performance metrics that will enable error-correction thresholds at high qubit densities, illuminating a path towards scalable quantum information processing.

quant-ph↗

Engineering Andreev Bound States for Thermal Sensing in Proximity Josephson Junctions

The thermal response of proximity Josephson junctions (JJs) is governed by the temperature ($T$)-dependent occupation of Andreev bound states (ABS), making them promising candidates for sensitive thermal detection. In this study, we systematically engineer ABS to enhance the thermal sensitivity of the critical current ($I_c$) of proximity JJs, quantified as $|\,dI_c/dT\,|$ for the threshold readout scheme and $|\,dI_c/dT \cdot I_c^{-1}\,|$ for the inductive readout scheme. Using a gate-tunable graphene-based JJ platform, we explore the impact of key parameters -- including channel length, transparency, carrier density, and superconducting material -- on the thermal response. Our results reveal that the proximity-induced superconducting gap plays a crucial role in optimizing thermal sensitivity. Notably, we see a maximum $|\,dI_c/dT \cdot I_c^{-1}\,|$ value of $0.6\,\mathrm{K}^{-1}$ at low temperatures with titanium-based graphene JJs. By demonstrating a systematic approach to engineering ABS in proximity JJs, this work establishes a versatile framework for optimizing thermal sensors and advancing the study of ABS-mediated transport.

cond-mat.supr-con↗