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Thermodynamic Computing System for AI Applications
Recent breakthroughs in artificial intelligence (AI) algorithms have highlighted the need for novel computing hardware in order to truly unlock the potential for AI.
Resource frugal optimizer for quantum machine learning
In this work, we advocate for simultaneous random sampling over both the dataset as well as the measurement operators that define the loss function.
Inference-Based Quantum Sensing
We show that, for a general class of unitary families of encoding, $\mathcal{R}(\theta)$ can be fully characterized by only measuring the system response at $2n+1$ parameters.
Covariance matrix preparation for quantum principal component analysis
We also argue that PCA on quantum datasets is natural and meaningful, and we numerically implement our method for molecular ground-state datasets.
Simple Mitigation Strategy for a Systematic Gate Error in IBMQ
We report the observation and characterisation of a systematic error in the implementation of $U_3$ gates in the IBM quantum computers.
Quantum Physics 81P65 J.2
