Noisy intermediate-scale quantum algorithms
A universal fault-tolerant quantum computer that can efficiently solve problems such as
integer factorization and unstructured database search requires millions of qubits with low …
integer factorization and unstructured database search requires millions of qubits with low …
NISQ computing: where are we and where do we go?
In this short review article, we aim to provide physicists not working within the quantum
computing community a hopefully easy-to-read introduction to the state of the art in the field …
computing community a hopefully easy-to-read introduction to the state of the art in the field …
Absence of barren plateaus in quantum convolutional neural networks
Quantum neural networks (QNNs) have generated excitement around the possibility of
efficiently analyzing quantum data. But this excitement has been tempered by the existence …
efficiently analyzing quantum data. But this excitement has been tempered by the existence …
Avoiding barren plateaus via transferability of smooth solutions in a Hamiltonian variational ansatz
A large ongoing research effort focuses on variational quantum algorithms (VQAs),
representing leading candidates to achieve computational speed-ups on current quantum …
representing leading candidates to achieve computational speed-ups on current quantum …
Tequila: A platform for rapid development of quantum algorithms
JS Kottmann, S Alperin-Lea… - Quantum Science …, 2021 - iopscience.iop.org
Variational quantum algorithms are currently the most promising class of algorithms for
deployment on near-term quantum computers. In contrast to classical algorithms, there are …
deployment on near-term quantum computers. In contrast to classical algorithms, there are …
Quantum machine learning on near-term quantum devices: Current state of supervised and unsupervised techniques for real-world applications
The past decade has witnessed significant advancements in quantum hardware,
encompassing improvements in speed, qubit quantity, and quantum volume—a metric …
encompassing improvements in speed, qubit quantity, and quantum volume—a metric …
Graph neural network initialisation of quantum approximate optimisation
Approximate combinatorial optimisation has emerged as one of the most promising
application areas for quantum computers, particularly those in the near term. In this work, we …
application areas for quantum computers, particularly those in the near term. In this work, we …
A semi-agnostic ansatz with variable structure for quantum machine learning
Quantum machine learning (QML) offers a powerful, flexible paradigm for programming near-
term quantum computers, with applications in chemistry, metrology, materials science, data …
term quantum computers, with applications in chemistry, metrology, materials science, data …
Optimized low-depth quantum circuits for molecular electronic structure using a separable-pair approximation
We present a classically tractable model that leads to optimized low-depth quantum circuits
leveraging separable-pair approximations. The obtained circuits are well suited as a …
leveraging separable-pair approximations. The obtained circuits are well suited as a …
Quantum nuclear dynamics on a distributed set of ion-trap quantum computing systems
Quantum nuclear dynamics with wavepacket time evolution is classically intractable and
viewed as a promising avenue for quantum information processing. Here, we use IonQ …
viewed as a promising avenue for quantum information processing. Here, we use IonQ …