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, we used the Recursive Quantum Approximate Optimization Algorithm (R-QAOA) to tackle number partitioning, a classic combinatorial problem that is an entry point to numerous logistics and supply chain problems of industrial interest.

The x-axis variable is the problem size in the figure below, while the y-axis variable measures the performance…

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 statistical learning techniques.

Ref. Polyadic Quantum Classifier — arXiv:2007.14044

Today, we release our code to contribute to the collective quest towards QML, encouraging teams around the world to try their own datasets, improve the existing algorithms and come up with new ones.

How it works —in 15 minutes

How does this result stand in the current QML landscape ?

I am…

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 best to foster a scientific research environment that allows a wide range of quantum computing problems to be explored and developed. Through our collaborative research approach, we thrive to do the most with quantum computing, today.

This week we asked our tech interns a few questions to shed light on…

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 medium post features our three business development interns and their pathways towards interning at Entropica Labs. We hope that this article will be a helpful resource for students who are keen to learn more about career opportunities in quantum computing!

The dream BD team!

Olivia, Computer Science @Stanford’24

My path started while I was…

“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 VC Elev8. We are humbled to be supported by an incredible group of investors, including SGInnovate, early-stage enterprise and deep tech VC Wavemaker Partners, the Lim Teck Lee Group, Japanese software enterprise TIS Inc, V1 Capital (the seed investment office of Vy Capital) and talent investor Entrepreneur First. …

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. The EntropicaQAOA package integrates fully with our partner Rigetti’s Quantum Cloud Services™ (QCS).

Quantum computing in the near-term

Quantum processors are steadily becoming more powerful, and applications to both scientific research and real-world enterprise problems are now being actively pursued.

Three weeks ago, a post on NASA’s website — which was quickly removed — reported that Google has achieved “quantum supremacy”

Entropica Labs

Doing the most with quantum computers, today.

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