181 citations · 281 across the 11 of their papers we have counts for
11 papers
Qiskit Machine Learning: an open-source library for quantum machine learning tasks at scale on quantum hardware and classical simulators
M. Emre Sahin, Edoardo Altamura, Oscar Wallis +6
We present Qiskit Machine Learning (ML), a high-level Python library that combines elements of quantum computing with traditional machine learning. The API abstracts Qiskit's primi…
Variational preparation of normal matrix product states on quantum computers
Ben Jaderberg, George Pennington, Kate V. Marshall +6
Preparing matrix product states (MPSs) on quantum computers is an essential routine in the simulation of many-body physics. However, widely-used schemes based on staircase circuits…
Evolving a multi-population evolutionary-QAOA on distributed QPUs
Francesca Schiavello, Edoardo Altamura, Ivano Tavernelli +2
Our work integrates an Evolutionary Algorithm (EA) with the Quantum Approximate Optimization Algorithm (QAOA) to optimize ansatz parameters in place of traditional gradient-based m…
Boosted Imaginary Time Evolution of Matrix Product States
Benjamin C. B. Symons, Dilhan Manawadu, David Galvin +1
In this work, we consider the imaginary time evolution of matrix product states. We present a novel quantum-inspired classical method that, when combined with time evolving block d…
Efficient Parameter Optimisation for Quantum Kernel Alignment: A Sub-sampling Approach in Variational Training
M. Emre Sahin, Benjamin C. B. Symons, Pushpak Pati +5
Quantum machine learning with quantum kernels for classification problems is a growing area of research. Recently, quantum kernel alignment techniques that parameterise the kernel…
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…
Toward Accurate Post-Born-Oppenheimer Molecular Simulations on Quantum Computers: An Adaptive Variational Eigensolver with Nuclear-Electronic Frozen Natural Orbitals
Anton Nykänen, Aaron Miller, Walter Talarico +11
Nuclear quantum effects such as zero-point energy and hydrogen tunnelling play a central role in many biological and chemical processes. The nuclear-electronic orbital (NEO) approa…
Nonadiabatic nuclear-electron dynamics: a quantum computing approach
Arseny Kovyrshin, Mårten Skogh, Lars Tornberg +6
The combined quantum electron-nuclear dynamics is often associated with the Born-Huang expansion of the molecular wave function and the appearance of nonadiabatic effects as a pert…
A Practitioner's Guide to Quantum Algorithms for Optimisation Problems
Benjamin C. B. Symons, David Galvin, Emre Sahin +2
Quantum computing is gaining popularity across a wide range of scientific disciplines due to its potential to solve long-standing computational problems that are considered intract…
A Quantum Computing Implementation of Nuclear-Electronic Orbital (NEO) Theory: Towards an Exact pre-Born-Oppenheimer Formulation of Molecular Quantum Systems
Arseny Kovyrshin, Mårten Skogh, Anders Broo +4
Nuclear quantum phenomena beyond the Born-Oppenheimer approximation are known to play an important role in a growing number of chemical and biological processes. While there exists…
Quantum Machine Learning Framework for Virtual Screening in Drug Discovery: a Prospective Quantum Advantage
Stefano Mensa, Emre Sahin, Francesco Tacchino +2
Machine Learning (ML) for Ligand Based Virtual Screening (LB-VS) is an important in-silico tool for discovering new drugs in a faster and cost-effective manner, especially for emer…