202 citations · 882 across the 12 of their papers we have counts for
12 papers
Efficient re-sampling in quasi-probability decompositions
Sara Santos, Stefan Woerner, Vincenzo Savona +1
Near-term quantum devices are limited by noise and hardware constraints, motivating algorithmic approaches that trade circuit complexity for increased sampling overhead. Quasi-prob…
Quantum computing with Qiskit
Ali Javadi-Abhari, Matthew Treinish, Kevin Krsulich +9
We describe Qiskit, a software development kit for quantum information science. We discuss the key design decisions that have shaped its development, and examine the software archi…
Scalable Quantum Algorithms for Noisy Quantum Computers
Julien Gacon
Quantum computing not only holds the potential to solve long-standing problems in quantum physics, but also to offer speed-ups across a broad spectrum of other fields. However, due…
Challenges and Opportunities in Quantum Optimization
Amira Abbas, Andris Ambainis, Brandon Augustino +43
Recent advances in quantum computers are demonstrating the ability to solve problems at a scale beyond brute force classical simulation. As such, a widespread interest in quantum a…
Stochastic Approximation of Variational Quantum Imaginary Time Evolution
Julien Gacon, Christa Zoufal, Giuseppe Carleo +1
The imaginary-time evolution of quantum states is integral to various fields, ranging from natural sciences to classical optimization or machine learning. Since simulating quantum…
Variational Quantum Time Evolution without the Quantum Geometric Tensor
Julien Gacon, Jannes Nys, Riccardo Rossi +2
The real- and imaginary-time evolution of quantum states are powerful tools in physics, chemistry, and beyond, to investigate quantum dynamics, prepare ground states or calculate t…
Variational quantum algorithm for unconstrained black box binary optimization: Application to feature selection
Christa Zoufal, Ryan V. Mishmash, Nitin Sharma +6
We introduce a variational quantum algorithm to solve unconstrained black box binary optimization problems, i.e., problems in which the objective function is given as black box. Th…
Scaling of the quantum approximate optimization algorithm on superconducting qubit based hardware
Johannes Weidenfeller, Lucia C. Valor, Julien Gacon +4
Quantum computers may provide good solutions to combinatorial optimization problems by leveraging the Quantum Approximate Optimization Algorithm (QAOA). The QAOA is often presented…
Simultaneous Perturbation Stochastic Approximation of the Quantum Fisher Information
Julien Gacon, Christa Zoufal, Giuseppe Carleo +1
The Quantum Fisher Information matrix (QFIM) is a central metric in promising algorithms, such as Quantum Natural Gradient Descent and Variational Quantum Imaginary Time Evolution.…
Efficient calculation of gradients in classical simulations of variational quantum algorithms
Tyson Jones, Julien Gacon
Calculating the energy gradient in parameter space has become an almost ubiquitous subroutine of variational near-term quantum algorithms. "Faithful" classical emulation of this su…
Quantum-Enhanced Simulation-Based Optimization
Julien Gacon, Christa Zoufal, Stefan Woerner
In this paper, we introduce a quantum-enhanced algorithm for simulation-based optimization. Simulation-based optimization seeks to optimize an objective function that is computatio…
Iterative Quantum Amplitude Estimation
Dmitry Grinko, Julien Gacon, Christa Zoufal +1
We introduce a new variant of Quantum Amplitude Estimation (QAE), called Iterative QAE (IQAE), which does not rely on Quantum Phase Estimation (QPE) but is only based on Grover's A…