Parameterized circuit instantiation is a common technique encountered in the generation of
circuits for a large class of hybrid quantum-classical algorithms. Despite being supported by …

In this paper, we introduce a tensor network (TN) scheme into the entanglement
augmentation process of the synergistic optimization framework by Rudolph et al.[arXiv …

This paper presents the Pauli-based Circuit Optimization, Analysis, and Synthesis Toolchain
(PCOAST), a framework for quantum circuit optimizations based on the commutative …

Quantum random access memory (QRAM) is an essential ingredient for many quantum
algorithms, such as quantum machine learning models. The quantum resources (qubit …

We introduce a domain-specific algorithm for numerical optimization operations used by
quantum circuit instantiation, synthesis, and compilation methods. QFactor uses a tensor …

We demonstrate the implementation of a novel machine learning framework for probability
density estimation and classification using quantum circuits. The framework maps a training …

Building efficient large-scale quantum computers is a significant challenge due to limited
qubit connectivities and noisy hardware operations. Transpilation is critical to ensure that …

We consider the problem of the variational quantum circuit synthesis into a gate set
consisting of the CNOT gate and arbitrary single-qubit (1q) gates with the primary target …

Near-term quantum computers have significant error rates and short coherence times, so
compilation of circuits to be as short as possible is essential. Two types of compilation …

In this article, we generalize the approximate quantum compiling algorithm into a new
method for cnot-depth reduction, which is apt to process wide target quantum circuits …