In order to characterize and benchmark computational hardware, software, and algorithms, it
is essential to have many problem instances on-hand. This is no less true for quantum …

Quantum computing has shown promise in solving complex problems by leveraging the
principles of superposition and entanglement. Variational quantum algorithms (VQA) are a …

The Pauli-based Circuit Optimization, Analysis and Synthesis Toolchain (PCOAST) was
recently introduced as a framework for optimizing quantum circuits. It converts a quantum …

Processing quantum information poses novel challenges regarding the debugging of faulty
quantum programs. Notably, the lack of accessible information on intermediate states during …

Quantum computing carries significant potential for addressing practical problems. However,
currently available quantum devices suffer from noisy quantum gates, which degrade the …

Hamiltonian simulation represents an important module in a large class of quantum
algorithms and simulations such as quantum machine learning, quantum linear algebra …

This paper introduces a novel abstraction for programming quantum operations, specifically
projective Cliffords, as functions over the qudit Pauli group. We define a categorical …

Fault-tolerant quantum computing (FTQC) is essential for executing reliable quantum
computations of meaningful scale. Widely adopted QEC codes for FTQC, such as the …

Quantum computing is getting increasing interest from both academia and industry, and the
quantum software landscape has been growing rapidly. The quantum software stack …

Optimizing quantum circuits is critical: the number of quantum operations needs to be
minimized for a successful evaluation of a circuit on a quantum processor. In this paper we …