Current quantum computer technology is still too noisy and imperfect to construct a universal digital quantum computer with quantum error correction. Inspired by the evolution of classical computation, an alternative paradigm merging the flexibility of […]
Quantum Machines (QM), an Israeli startup, funded with $5.5 million by Battery Ventures and TLV Partners, has just revealed the Quantum Orchestration Platform (QOP), a full hardware and software solution, which is claimed as the […]
Researchers at the Department of Energy’s Oak Ridge National Laboratory have developed a quantum chemistry simulation benchmark to evaluate the performance of quantum devices and guide the development of applications for future quantum computers. The […]
Atos announces that it is continuing to enrich its quantum development ecosystem, through the creation of a global User Group of the Atos Quantum Learning Machine (QLM), which will be chaired by Henri Calandra, a representative from French […]
Google has used its Sycamore record-breaking quantum computer to achieve the biggest quantum chemistry simulation ever. The team modeled the behavior of a long chain of hydrogen atoms. The simulation of large molecules is one of the […]
Interesting article from Tennin Yan, QunaSys CEO & Co-founder. The startup is developing quantum computer algorithms and applications. As he states, a quantum computer simulator is an essential tool for quantum algorithm research. Most researchers […]
Researchers at Freie Universität Berlin and Rice University, Texas, reviewed recent ML (Machine Learning) methods for molecular simulation, with particular focus on (deep) neural networks for the prediction of quantum-mechanical energies and forces, coarse-grained molecular […]
Scientists at Singapore University of Technology and Design and others researchers in China propose a hybrid quantum-classical convolutional neural network (QCCNN), inspired by convolutional neural networks (CNNs) but adapted to quantum computing to enhance the […]
Researchers at International Institute of Information Technology Bhubaneswar, India and Shanghai University have used the techniques of deep learning and supervised learning in the quantum framework, to propose a quantum neural network and showcase its […]
This is a proof of concept by IBM that hints at how quantum computing could generate Minecraft-like scenes, levels or even complete video games that are better than the ones we have today. For example, […]
Researchers at the California Institute of Technology (Caltech) have recently published the development of three new algorithms that could help to overcome the limitations of existing phase estimation and variational methods techniques for computing Hamiltonian eigenstates on […]
Amazon AWS announces new Quantum Computing Service (Amazon Braket) along with AWS Center for Quantum Computing and AWS Quantum Solutions Lab. It had been hardly a secret for weeks but now it’s disclosable. At Swiss […]
Toronto-based quantum computing startup Xanadu announced today that it has secured a grant from the Defense Advanced Research Projects Agency (DARPA). The startup, which provides both hardware and software-based solutions, says the grant will be used to […]
Researchers from Rigetti Computing and the Commonwealth Bank of Australia (CBA) announce they have taken an important step towards the use of quantum computing in the financial services sector. This week, they published details of […]
Researchers at CNRS, IRIF and Université Paris Diderot have described the first CNN implementation on quantum processors, with an advantage that could allow for bigger and faster CNN, thus many more applications.
IBM recently added support in Qiskit for trapped ion-based quantum computing devices.
Microsoft Quantum is driving innovation in quantum computing with Azure Quantum to address complex global challenges through a scalable quantum system.
Researchers at Google Research and X, The Moonshot Factory have proposed modifications to the Quantum Approximate Optimization Algorithm (QAOA).
PennyLane, Xanadu’s software for quantum machine learning & optimization of hybrid quantum-classical computations, now has support for Google AI Cirq via the new PennyLane-Cirq plugin!
Researchers at University of Trento, Italy, propose a hybrid quantum-classical algorithm to solve optimization problems with an adiabatic machine assuming restrictions on the class of available problem Hamiltonians.
A team at Argonne National Laboratory and Clemson University in USA has performed a large-scale numerical study of the approximation ratios attainable by QAOA.
Solving linear systems of equations is an essential component in science and technology, including in many machine learning algorithms. Existing quantum algorithms have demonstrated large speedups in solving linear systems, but the required quantum resources are not available on near- term quantum devices.
The Green’s function plays a crucial role to study the nature of quantum many-body systems, especially strongly-correlated systems. Although the development of quantum computers in near term is expected to enable us to compute energy […]
Boltzmann machines are the basis of several deep learning methods that have been successfully applied to both supervised and unsupervised machine learning tasks. These models assume that a dataset is generated according to a Boltzmann distribution, and the goal of the training procedure is to learn the set of parameters that most closely match the input data distribution.
The researchers at Lawrence Berkeley National Laboratory show that even without achieving full fault-tolerance, quantum error detection is already useful on the current generation of quantum hardware.