Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Optimization of Quantum-dot Qubit Fabrication via Machine Learning   Precise nanofabrication represents a critical challenge to developing
semiconductor quantum-dot qubits for practical quantum computation. Here, we
design and train a convolutional neural network to interpret in-line scanning
electron micrographs and quantify qualitative features affecting device
functionality. The high-throughput strategy is exemplified by optimizing a
model lithographic process within a five-dimensional design space and by
demonstrating a new approach to address lithographic proximity effects. The
present results emphasize the benefits of machine learning for developing
robust processes, shortening development cycles, and enforcing quality control
during qubit fabrication.

10
The categories of this paper are: q-bio
15
The categories of this paper are: nucl-ex
25
The categories of this paper are: patt-sol
36
The categories of this paper are: cmp-lg
11
The categories of this paper are: hep-lat
3
The categories of this paper are: physics
30
The categories of this paper are: q-alg
5
The categories of this paper are: gr-qc
7
The categories of this paper are: hep-th
16
The categories of this paper are: stat
37
The categories of this paper are: supr-con
32
The categories of this paper are: atom-ph
22
The categories of this paper are: chao-dyn
19
The categories of this paper are: eess
26
The categories of this paper are: bayes-an
12
The categories of this paper are: nucl-th