by the Entropica Labs Team. To tackle how to trust the results of calculations performed on unreliable or error-prone quantum processors, a research team involving academic groups and several quantum startups comes up with a new cross-check procedure. It allows the results of a calculation performed on one device to…

by the Entropica Labs Team Today we are very pleased to announce the results of a collaboration between Honeywell, the BMW Group’s IT Tech office in Singapore, and Entropica Labs. We developed and ran a benchmark for near-term quantum optimisation on Honeywell’s H1 hardware, a 10-qubit trapped-ion quantum computer. Specifically…

Some weeks ago, we successfully trained a quantum machine learning model on IBM quantum computers. Our QML algorithm reached the accuracy level of classical ML in solving a simple problem, the ternary classification of the Iris flower dataset. This well known dataset is typically used as a test case for…

Meet Entropica Labs’ Tech Interns! This week, we are proud to turn the spotlight onto our tech interns at Entropica Labs. As a quantum computing startup, we enjoy the unique balance of exploring pure science, while probing real-world quantum solutions. In the growing field of quantum computing, we do our…

Featuring Entropica Labs’ Business Development Interns! The ongoing Covid-19 crisis has disrupted many studies and internship plans. At Entropica Labs, we are lucky to be in a position to support local students by offering them technical and non-technical summer internship opportunities in the exciting, emerging field of Quantum Computing! This…

“No sensible decision can be made any longer without taking into account not only the world as it is, but the world as it will be.” — Isaac Asimov Singapore, May 11th, 2020 We are excited to announce the close of a S$2.6m seed investment round led by deep tech…

Optimising with near-term quantum computers — Today we are pleased to announce the public release of EntropicaQAOA, a free and open source software package implementing the quantum approximate optimisation algorithm (QAOA). QAOA is an algorithm designed for near-term quantum computers, and has applications to both machine learning and discrete optimisation. …