In recognition of Black History Month, we spoke with a few of our growing cohort of Black IBM Quantum team members working to build the future of quantum computing. The four featured here perform indispensable roles at each level of the quantum stack, from researching quantum algorithms and their potential applications to building a global quantum ecosystem. We hope you'll follow along and celebrate their accomplishments with us today and into the future.
In “Probing resonating valence bond states in artificial quantum magnets,” we show that quantum spin liquids can be built and probed with atomic precision.
The IBM-HBCU Quantum Center has announced a slate of new members for the Center, with 10 historically Black colleges and universities joining the Center’s 13 founding institutions.
We’ve made strides in delivering the next-gen AI computational systems with cutting-edge performance and unparalleled energy efficiency.
We have unveiled in the laboratory new details on how the famous Titan haze may have formed and what its chemical make-up looks like. Our findings in the latest issue of the Astrophysical Journal detail how we've resolved molecules of different sizes, giving snapshots of the different stages through which molecules grow to build up the haze.
PAGs play a vital role in the manufacturing of computer chips. They are also one of several classes of chemical compounds that have recently come under enhanced scrutiny from environmental regulators. Researchers have been racing to create more sustainable ones – but the traditional process of discovering new materials is too slow, too costly, and too risky. So IBM researchers have turned to AI for help – and created new PAGs much, much faster, paving the way to the era of Accelerated Discovery.
IBM Quantum systems can now measure and reset a qubit in the middle of a circuit execution.
At AAAI, our team presented two new multilingual research techniques that enable AI to understand different languages while only trained on one.
Our Zurich-based team of researchers has just managed to efficiently guide visible light through a silicon wire – an important milestone towards faster, more efficient integrated circuits. Our low-loss silicon waveguide could enable new photonic chip designs for applications that rely on visible light, and could lead to more efficient lasers and modulators used in telecoms.
Our team has developed an AI that verifies other AIs’ ‘fairness’ by generating a set of counterfactual text samples and testing machine learning systems without supervision.