Los Alamos National Laboratory recently published a Quantum Computer programming guide in ACM Transactions on Quantum Computing. For would-be quantum programmers scratching their heads over how to jump into the game as quantum computers proliferate and become publicly accessible, a new beginner’s guide provides a thorough introduction to quantum algorithms and their implementation on existing hardware. Deep-diving guide […]
A team of researchers including Google Quantum AI has developed a theory suggesting that quantum computers should be exponentially faster on some learning tasks than classical machines. The scientists tested their work on Google’s Sycamore quantum computer. To find out if the idea might be possible, and more importantly, if the results would be better […]
To overcome the limitations of current quantum computers, researchers at Pacific Northwest National Laboratory (PNNL) are developing simulations that provide a glimpse into how quantum computers work. In collaboration with Oak Ridge National Laboratory and Microsoft, the team uses high performance computing to develop simulators that mimic real quantum devices for executing complex quantum circuits. […]
A team of researchers have presented the Scaled QUantum IDentifier (SQUID), an open-source framework for exploring hybrid Quantum-Classical algorithms for classification problems. The classical infrastructure is based on PyTorch and they provide a standardized design to implement a variety of quantum models with the capability of back-propagation for efficient training. Quantum Machine Learning (QML) is […]
Research in Quantum Machine Learning (QML) has focused primarily on variational quantum algorithms (VQAs), and several proposals to enhance supervised, unsupervised and reinforcement learning (RL) algorithms with VQAs have been put forward. Out of the three, RL is the least studied and it is still an open question whether VQAs can be competitive with state-of-the-art […]
Variational Quantum Algorithms (VQAs) are expected to be a path to quantum advantages on noisy intermediate-scale quantum devices. However, both empirical and theoretical results exhibit that the deployed ansatz heavily affects the performance of VQAs such that an ansatz with a larger number of quantum gates enables a stronger expressivity, while the accumulated noise may […]
Researchers have proposed a quantum implementation of the Stochastic Series Expansion (SSE) Monte Carlo method and shown it offers significant advantages over classical implementations of SSE. In particular, for problems where classical SSE encounters the sign problem, the cost of implementing a Monte Carlo iteration scales only linearly with system size in quantum SSE, while […]
Lawrence Berkeley National Laboratory physicists have leveraged an IBM Q quantum computer through the Oak Ridge Leadership Computing Facility to capture part of a calculation of two protons colliding. The calculation can show the probability that an outgoing particle will emit additional particles. The researchers used a method called effective field theory to break down their full […]
NVIDIA cuQuantum debuts with an expanding ecosystem and a collaboration building the programming model for tomorrow’s most powerful systems. As quantum computers improve, researchers share a vision of a hybrid computing model where quantum and classical computers work together, each addressing the challenges they’re best suited to. To be broadly useful, these systems will need […]
Researchers at MIT are working to mitigate the noise problem in quantum computing by developing a technique that makes the quantum circuit itself resilient to noise. (Specifically, these are “parameterized” quantum circuits that contain adjustable quantum gates.) The team created a framework that can identify the most robust quantum circuit for a particular computing task […]
