Among different quantum algorithms, PQC for QML show promises on near-term devices. To
facilitate the QML and PQC research, a recent python library called TorchQuantum has been …

Entropy measures quantify the amount of information and correlation present in a quantum
system. In practice, when the quantum state is unknown and only copies thereof are …

There is a folkloric belief that a depth-$\Theta (m) $ quantum circuit is needed to estimate the
trace of the product of $ m $ density matrices (ie, a multivariate trace), a subroutine crucial to …

Fidelity is a fundamental measure for the closeness of two quantum states, which is
important both from a theoretical and a practical point of view. Yet, in general, it is difficult to …

We propose a series of quantum algorithms for computing a wide range of quantum
entropies and distances, including the von Neumann entropy, quantum Rényi entropy, trace …

Learning tasks play an increasingly prominent role in quantum information and computation.
They range from fundamental problems such as state discrimination and metrology over the …

The performance of a quantum information processing protocol is ultimately judged by
distinguishability measures that quantify how distinguishable the actual result of the protocol …

Measuring the distinguishability between quantum states is a basic problem in quantum
information theory. In this paper, we develop optimal quantum algorithms that estimate both …

In quantum information, trace distance is a basic metric of distinguishability between
quantum states. However, there is no known efficient approach to estimate the value of trace …

Quantum Computing has attracted much research attention because of its potential to
achieve fundamental speed and efficiency improvements in various domains. Among …