AMHERST, Mass. — Scientists in the Riccio College of Engineering at the University of Massachusetts Amherst and the University of California Santa Barbara have demonstrated key laser and ion trap components necessary to help drastically shrink the size of quantum computers, an achievement aligned with the shrinking of integrated microprocessors in the 1970s, 80s and 90s that allowed computers to move from room-sized behemoths to today’s ultrathin smartphones.

Grasping and transporting objects is one of the most critical tasks for robots in a variety of fields. This task requires accurate 3D measurement of the objects. However, transparent or specular objects make measurement challenging, reducing grasping success rate. To address this, researchers have developed HEAPGrasp, a new technique that performs 3D measurement of objects using only their silhouettes, thus avoiding dependence on their optical properties. This approach significantly improves grasping success rate of robots.

Nanoimprint lithography (NIL) is a highly promising large-area, high-throughput manufacturing technique that transfers nanoscale patterns through a mold replication-imprint-demolding process. Yet defects introduced during demolding are often unavoidable and can compromise device reliability. Now, teams from China and Singapore report a strategy in Science Bulletin that integrates NIL with topological protection to realize visible‑band nanolaser devices that remain stable even in the presence of defects or disorder.

Fujitsu Limited and the Center for Quantum Information and Quantum Biology at The University of Osaka today announced the development of a new technology designed to accelerate the industrial application of quantum computers in the era of early fault-tolerant quantum computing (early-FTQC). By combining ver. 3 of the STAR architecture, a unique highly efficient phase rotation gate quantum computing architecture, with a novel molecular model optimization technique, researchers have significantly reduced computational resource requirements. This breakthrough will enable the energy calculations for chemical material design such as catalyst molecules, within a realistic timeframe using early-FTQC quantum computers. These kinds of calculations are currently not possible using current computers, and would take millennia even using previous versions of the STAR architecture. The technologies are expected to contribute to solving various societal challenges, including accelerating drug discovery, improving the efficiency of ammonia synthesis processes, and advancing carbon recycling technologies.

The partnership between the BMW Group and ESMT Berlin enters its fifth year. In 2026, the BMW Group Change Maker Fellowship will once again support future leaders who want to actively shape digital transformation. The fellowships are available for ESMT’s Full-time MBA and MSc programs as well as the Global Online MBA.