Quantum noise is the key challenge in Noisy Intermediate-Scale Quantum (NISQ)
computers. Previous work for mitigating noise has primarily focused on gate-level or pulse …

In the effort to develop useful quantum computers simulating quantum machines with
conventional computing resources is a key capability. Such simulations will always face …

Abstract Machine learning (ML) techniques have become pervasive across a range of
different applications, and are now widely used in areas as disparate as recidivism …

Quantum programs are written in high-level languages, whereas quantum hardware can
only execute low-level native gates. To run programs on quantum systems, each high-level …

Noise detrimentally affects quantum computations so that they not only become less
accurate but also easier to simulate classically as systems scale up. We construct a classical …

We define QSE, a symbolic execution framework for quantum programs by integrating
symbolic variables into quantum states and the outcomes of quantum measurements. The …

This article presents a new compressed representation of Boolean functions, called
CFLOBDDs (for Context-Free-Language Ordered Binary Decision Diagrams). They are …

Variational quantum algorithms (VQAs) provide a promising approach to achieve quantum
advantage in the noisy intermediate-scale quantum era. In this era, quantum computers …

Quantum computing is a rapidly evolving computational means that offers significant
speedups for a variety of scientific applications, including machine learning, unsorted …

In this paper, we introduce VeriQBench--an open source benchmark for quantum circuits. It
offers high-level quantum circuit abstractions of various circuit types, including 1) …