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Will Silicon Save Quantum Computing?

Silicon has become a leading contender in the hunt for a practical, scalable quantum bit

19 min read
Will Silicon Save Quantum Computing?
Illustration: Bryan Christie Design

Grand engineering challenges often require an epic level of patience. That’s certainly true for quantum computing. For a good 20 years now, we’ve known that quantum computers could, in principle, be staggeringly powerful, taking just a few minutes to work out problems that would take an ordinary computer longer than the age of the universe to solve. But the effort to build such machines has barely crossed the starting line. In fact, we’re still trying to identify the best materials for the job.

Today, the leading contenders are all quite exotic: There are superconducting circuits printed from materials such as aluminum and cooled to one-hundredth of a degree above absolute zero, floating ions that are made to hover above chips and are interrogated with lasers, and atoms such as nitrogen trapped in diamond matrices.

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The World’s Largest Camera Is Nearly Complete

The future heart of the Vera C. Rubin Observatory will soon make its way to Chile

3 min read
A large black cylinder with a glass lens in front rests on a sturdy white structure in a bright room.

The LSST camera, eventually bound for the Vera C. Rubin Observatory in Chile, sits on its stand in a Bay Area clean room.

Jacqueline Ramseyer Orrell/SLAC National Accelerator Laboratory

The world’s largest camera sits within a nondescript industrial building in the hills above San Francisco Bay.

If all goes well, this camera will one day fit into the heart of the future Vera C. Rubin Observatory in Chile. For the last seven years, engineers have been crafting the camera in a clean room at the SLAC National Accelerator Laboratory in Menlo Park, Calif. In May 2023, if all goes according to plan, the camera will finally fly to its destination, itself currently under construction in the desert highlands of northern Chile.

Building a camera as complex as this requires a good deal of patience, testing, and careful engineering. The road to that flight has been long, and there’s still some way to go before the end is in sight.

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Lab Revisits the Task of Putting Common Sense in AI

New nonprofit Basis hopes to model human reasoning to inform science and public policy

5 min read
ai hand and human hand touching pointer fingers
iStock

The field of artificial intelligence has embraced deep learning—in which algorithms find patterns in big data sets—after moving on from earlier systems that more explicitly modeled human reasoning. But deep learning has its flaws: AI models often show a lack of common sense, for example. A new nonprofit, Basis, hopes to build software tools that advance the earlier method of modeling human reasoning, and then apply that method toward pressing problems in scientific discovery and public policy.

To date, Basis has received a government grant and a donation of a few million dollars. Advisors include Rui Costa, a neuroscientist who heads the Allen Institute in Seattle, and Anthony Philippakis, the chief data officer of the Broad Institute in Cambridge, Mass. In July, over tacos at the International Conference on Machine Intelligence, I spoke with Zenna Tavares, a Basis cofounder, and Sam Witty, a Basis research scientist, about human intelligence, problems with academia, and trash collection. The following transcript has been edited for brevity and clarity.

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Modeling Thermal Management Systems for Electronics

Learn how to model conjugate heat transfer in electronic devices with COMSOL Multiphysics

1 min read
Comsol

The ability to dissipate heat is one of the most important features of modern electronic devices and is usually a limiting factor in the miniaturization of these devices.

COMSOL Multiphysics includes functionality for heat transfer through conduction, convection, and radiation. Its ability to treat conjugate heat transfer, including laminar and turbulent flow as well as surface-to-surface radiation, has proven to be of great importance for the design and optimization of thermal management systems in electronics. Its multiphysics modeling capabilities also enable the study of thermoelectric effects as well as thermal–structural effects, such as thermal expansion.

In this webinar, we will demonstrate how to create models and apps for conjugate heat transfer in electronic devices. We will also give a general overview of the software’s capabilities for multiphysics modeling, including heat transfer as one of the modeled phenomena.

Register now for this free webinar!

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