Quantum Machine Learning

[This review is intended solely for my personal learning] Paper Info arXiv: 2210.00864v1 Title: quEEGNet: Quantum AI for Biosignal Processing Authors: Toshiaki Koike-Akino, Ye Wang Prior Knowledge Biosignal Processing in Human-Machine Interfaces (HMI) Biosignals such as EEG (electroencephalogram), EMG (electromyogram), and ECoG (electrocorticogram) are fundamental to developing brain-computer interfaces (BCI) and HMIs. However, biosignals are subject to high variability and noise, requiring robust machine-learning models for feature extraction and classification. ...

[This review is intended solely for my personal learning] [Qiix at Qiskit Hackathon Taiwan 2024 was inspired by this paper] Paper Info arXiv: 2406.04305 Title: Quixer: A Quantum Transformer Model Authors: Nikhil Khatri, Gabriel Matos, Luuk Coopmans, Stephen Clark (Quantinuum) Prior Knowledge Linear Combination of Unitaries (LCU) The LCU technique allows the combination of multiple unitary operators into one overall operator using additional control qubits and postselection. Given unitaries $U_0, U_1, \dots, U_{n-1}$ with complex coefficients $b_0, b_1, \dots, b_{n-1}$, one can effectively prepare a block-encoded operator $$ M = \sum_{j=0}^{n-1} b_j U_j. $$ ...