activity
20082022
most citedQuantum Neuron: an elementary building block for machine learning on quantum computers

114 citations · 159 across the 6 of their papers we have counts for

collaborators

13 papers

quant-ph202213 cited

An LLVM-based C++ Compiler Toolchain for Variational Hybrid Quantum-Classical Algorithms and Quantum Accelerators

Pradnya Khalate, Xin-Chuan Wu, Shavindra Premaratne +6

Variational algorithms are a representative class of quantum computing workloads that combine quantum and classical computing. This paper presents an LLVM-based C++ compiler toolch…

quant-ph202117 cited

Solving Quadratic Unconstrained Binary Optimization with divide-and-conquer and quantum algorithms

Gian Giacomo Guerreschi

Quadratic Unconstrained Binary Optimization (QUBO) is a broad class of optimization problems with many practical applications. To solve its hard instances in an exact way, known cl…

quant-ph20202 cited

Realizing Quantum Algorithms on Real Quantum Computing Devices

Carmen G. Almudever, Lingling Lao, Robert Wille +1

Quantum computing is currently moving from an academic idea to a practical reality. Quantum computing in the cloud is already available and allows users from all over the world to…

quant-ph2020

On connectivity-dependent resource requirements for digital quantum simulation of -level particles

Nicolas P. D. Sawaya, Gian Giacomo Guerreschi, Adam Holmes

A primary objective of quantum computation is to efficiently simulate quantum physics. Scientifically and technologically important quantum Hamiltonians include those with spin-

quant-ph2020

Intel Quantum Simulator: A cloud-ready high-performance simulator of quantum circuits

Gian Giacomo Guerreschi, Justin Hogaboam, Fabio Baruffa +1

Classical simulation of quantum computers will continue to play an essential role in the progress of quantum information science, both for numerical studies of quantum algorithms a…

quant-ph201911 cited

Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design

Gian Giacomo Guerreschi

As quantum hardware increases in complexity, successful algorithmic execution relies more heavily on awareness of existing device constraints. In this work we focus on the problem…