The architecture of an atom

Linipun Phuttitarn, B. M. Becker, Ravikumar Chinnarasu +2 more

We demonstrate qubit-state measurements assisted by a supervised convolutional neural network (CNN) in a neutral-atom quantum processor. We present two CNN architectures for analyzing neutral-atom qubit readout data: a compact five-layer single-qubit CNN architecture and a six-layer multiqubit CNN architecture. We benchmark both architectures against a conventional Gaussian-threshold analysis method. In a sparse array (9-$\text{\ensuremath{\mu}}\mathrm{m}$ atom separation) which experiences negligible crosstalk, we have observed up to 32% and 56% error reduction for the multiqubit and single-qubit architectures, respectively, as compared to the benchmark. In a tightly spaced array (5-$\text{\ensuremath{\mu}}\mathrm{m}$ atom separation), which suffers from readout crosstalk, we have observed up to 43% and 32% error reduction in the multiqubit and single-qubit CNN architectures, respectively, as compared to the benchmark. By examining the correlation between the predicted states of neighboring qubits, we have found that the multiqubit CNN architecture reduces the crosstalk correlation by up to 78.5%. This work demonstrates a proof of concept for a CNN network to be implemented as a real-time readout-processing method on a neutral-atom quantum computer, enabling faster readout time and improved fidelity.

Lyguat Lee, Xin Xie, Geng-Sheng Kuo

Nanotechnology uses the smallest unit of matter to engineering new materials and devices atom by atom, aiming at achieving superior properties and performance through atomic scale architecture. In general, the nanoscale structures, devices, and systems cannot be studied using conventional concepts. In other words, we have to study novel phenomena in nanosystems using quantum and optimization theories. In this paper, we study a novel architecture of our proposed quantum-based nanosensor node for future wireless sensor networks. In addition, we conduct a mathematical analysis on one of the modules in our designed architecture-classical to quantum (C/Q) converter.

Andrew Litteken, Jonathan M. Baker, Frederic T. Chong

Neutral atoms are a promising choice for scalable quantum computing architectures. Features such as long distance interactions and native multiqubit gates offer reductions in communication costs and operation count. However, the trapped atoms used as qubits can be lost over the course of computation and due to adverse environmental factors. The value of a lost computation qubit cannot be recovered and requires the reloading of the array and rerunning of the computation, greatly increasing the number of runs of a circuit. Software mitigation strategies exist [1] but exhaust the original mapped locations of the circuit slowly and create more spread out clusters of qubits across the architecture decreasing the probability of success. We increase flexibility by developing strategies that find all reachable qubits, rather only adjacent hardware qubits. Second, we divide the architecture into separate sections, and run the circuit in each section, free of lost atoms. Provided the architecture is large enough, this resets the circuit without having to reload the entire architecture. This increases the number of effective shots before reloading by a factor of two for a circuit that utilizes 30% of the architecture. We also explore using these sections to parallelize execution of circuits, reducing the overall runtime by a total 50% for 30 qubit circuit. These techniques contribute to a dynamic new set of strategies to combat the detrimental effects of lost computational space.