Lifeboat Foundation

A new technique to measure vibrating atoms could improve the precision of atomic clocks and of quantum sensors for detecting dark matter or gravitational waves.

Gravitational waves are distortions or ripples in the fabric of space and time. They were first detected in 2015 by the Advanced LIGO detectors and are produced by catastrophic events such as colliding black holes, supernovae, or merging neutron stars.

A machine-learning algorithm that includes a quantum circuit generates realistic handwritten digits and performs better than its classical counterpart.

Machine learning allows computers to recognize complex patterns such as faces and also to create new and realistic-looking examples of such patterns. Working toward improving these techniques, researchers have now given the first clear demonstration of a quantum algorithm performing well when generating these realistic examples, in this case, creating authentic-looking handwritten digits [1]. The researchers see the result as an important step toward building quantum devices able to go beyond the capabilities of classical machine learning.

The most common use of neural networks is classification—recognizing handwritten letters, for example. But researchers increasingly aim to use algorithms on more creative tasks such as generating new and realistic artworks, pieces of music, or human faces. These so-called generative neural networks can also be used in automated editing of photos—to remove unwanted details, such as rain.

The quantum vibrations in atoms hold a miniature world of information. If scientists can accurately measure these atomic oscillations, and how they evolve over time, they can hone the precision of atomic clocks as well as quantum sensors, which are systems of atoms whose fluctuations can indicate the presence of dark matter, a passing gravitational wave, or even new, unexpected phenomena.

A major hurdle in the path toward better quantum measurements is noise from the classical world, which can easily overwhelm subtle atomic vibrations, making any changes to those vibrations devilishly hard to detect.

Now, MIT physicists have shown they can significantly amplify quantum changes in atomic vibrations, by putting the particles through two key processes: quantum entanglement and time reversal.

Before quantum computers and quantum networks can fulfil their huge potential, scientists have got several difficult problems to overcome – but a new study outlines a potential solution to one of these problems.

As we’ve seen in recent research, the silicon material that our existing classical computing components are made out of has shown potential for storing quantum bits, too.

These quantum bits – or qubits – are key to next-level quantum computing performance, and they come in a variety of types.

In this podcast we meet the CEO and co-founder of First Light Fusion.

Reimagining Nuclear Medicine — Dr. Stephen Moran, Ph.D., Global Program Head, Neuroendocrine Tumors & Other Radiosensitive Cancers, Advanced Accelerator Applications, Novartis

Dr. Stephen Moran, Ph.D., is Global Program Head, Neuroendocrine Tumors & Other Radiosensitive Cancers, for Advanced Accelerator Applications (AAA — https://www.adacap.com/), a Novartis company and also a member of the Oncology Development Unit Leadership Team at Novartis.

Continue reading “Dr. Stephen Moran, PhD — Reimagining Nuclear Medicine — Advanced Accelerator Applications, Novartis” »

Physicists cast doubt on the role of coherent superpositions in the brain.

Researchers at Simon Fraser University have made a crucial breakthrough in the development of quantum technology.

Their research, published in Nature today, describes their observations of more than 150,000 silicon “T center” photon-spin qubits, an important milestone that unlocks immediate opportunities to construct massively scalable quantum computers and the quantum internet that will connect them.

Quantum computing has enormous potential to provide computing power well beyond the capabilities of today’s supercomputers, which could enable advances in many other fields, including chemistry, materials science, medicine and cybersecurity.

Senior Analyst, AI & Quantum Computing, Paul Smith-Goodson, dives in as in today’s world, many critical business decisions and customer-facing services rely on accurate machine learning insights. Today, he discusses Google’s latest A.I. benchmarking test dethroning NVIDIA’s.