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Bose–Einstein condensation in atomic gases was first observed in 1995. As we look back at the past 20 years of this thriving field, it's clear that there is much to celebrate.
Quantum technologies, including quantum sensors, quantum communication and quantum metrology, represent a growing industry. Out in space, such technologies can revolutionize the way we communicate and observe our planet.
On astronomical scales, gravity is the engine of the Universe. The launch of LISA Pathfinder this year to prepare the technology to detect gravitational waves will help us 'listen' to the whole Universe.
This year, NASA's Dawn and New Horizons rendezvoused with Ceres and Pluto, respectively. These worlds, despite their modest sizes, have much to teach us about the accretion of the Solar System and its dynamical evolution.
The history of the fierce opposition met by Einstein's theory of relativity in the 1920s teaches us that public controversies about science are not necessarily settled by sound scientific reasoning.
Coupling electromagnetic waves to mechanical waves has led to a remarkable miniaturization of wireless communication technologies. Now, spin waves could provide us with technologies that are small and reprogrammable.
Research in high-energy physics produces masses of data, demanding extensive computational resources. The scientists responsible for managing these resources are now turning to cloud and high-performance computing.
Writing efficient scientific software that makes best use of the increasing complexity of computer architectures requires bringing together modelling, applied mathematics and computer engineering. Physics may help unite these approaches.
Granting access to publications and data may be a step towards open science, but it's not enough to ensure reproducibility. Making computer code available is also necessary — but the emphasis must be on the quality of the programming.
Research in quantum optics has already led to commercial technologies, but the gap between the lab and market products is still large. Looking from the industrial side, one can see ways of bridging this gap.
New quantum algorithms promise an exponential speed-up for machine learning, clustering and finding patterns in big data. But to achieve a real speed-up, we need to delve into the details.
Magnetocaloric and electrocaloric effects are driven by doing work, but this work has barely been explored, even though these caloric effects are being exploited in a growing number of prototype cooling devices.
Our framework for understanding non-equilibrium behaviour is yet to match the simplicity and power of equilibrium statistical physics. But recent theoretical and experimental advances reveal key principles that unify seemingly unrelated topics.
