Rensselaer Polytechnic Institute Plans to Deploy First IBM Quantum System One on a University Campus
Today, it was announced that Rensselaer Polytechnic Institute will become the first university in the world to house an IBM Quantum System One. The IBM quantum computer, intended to be operational by January of 2024, will serve as the foundation of a new IBM Quantum Computational Center in partnership with Rensselaer Polytechnic Institute (RPI). By partnering, RPI’s vision is to greatly enhance the educational experiences and research capabilities of students and researchers at RPI and other institutions, propel the Capital Region into a top location for talent, and accelerate New York's growth as a technology epicenter.
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Rensselaer Polytechnic Institute President Martin A. Schmidt ’81 presided over the 217th Commencement Ceremony, his first as president. During the ceremony, which was held at the East Campus Athletic Village, Rensselaer awarded a total of 1,988 degrees — 152 doctoral degrees, 390 master’s degrees, and 1,446 bachelor’s degrees — to 1,957 students, some of whom earned multiple degrees. Approximately 1,500 students attended the ceremony.
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Beginning at 9:30 a.m. on May 20, 2023, Rensselaer Polytechnic Institute will award a total of 1,988 degrees — 152 doctoral degrees, 390 master’s degrees, and 1,446 bachelor’s degrees — to 1,957 students, some of whom have earned multiple degrees. Approximately 1,500 students will attend the ceremony.
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With graduation season in full swing, Rensselaer Polytechnic Institute (RPI) is hosting the Lavender Graduation and Garnet D. Baltimore Students of Color Graduation ceremonies to celebrate the cultural diversity of the Class of 2023 graduates.
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A team of researchers led by Rensselaer Polytechnic Institute’s Trevor David Rhone, assistant professor in the Department of Physics, Applied Physics, and Astronomy, has identified novel van der Waals (vdW) magnets using cutting-edge tools in artificial intelligence (AI). In particular, the team identified transition metal halide vdW materials with large magnetic moments that are predicted to be chemically stable using semi-supervised learning. These two-dimensional (2D) vdW magnets have potential applications in data storage, spintronics, and even quantum computing.
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