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A team of researchers from the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory and Stony Brook University have devised a new quantum algorithm to compute the lowest energies of molecules at specific configurations during chemical reactions, including when their chemical bonds are broken. As described in Physical Review Research, compared to similar existing algorithms, including the team’s previous method, the new algorithm will significantly improve scientists’ ability to accurately and reliably calculate the potential energy surface in reacting molecules.

For this work, Deyu Lu, a Center for Functional Nanomaterials (CFN) physicist at Brookhaven Lab, worked with Tzu-Chieh Wei, an associate professor specializing in quantum information science at the C.N. Yang Institute for Theoretical Physics at Stony Brook University, Qin Wu, a theorist at CFN, and Hongye Yu, a Ph.D. student at Stony Brook.

“Understanding the quantum mechanics of a molecule, how it behaves at an atomic level, can provide key insight into its chemical properties, like its stability and reactivity,” said Lu.

In our common experience, you can’t get something for nothing. In the quantum realm, something really can emerge from nothing.

The activity of neurons has been measured in a slice of mouse tissue using a quantum diamond sensor – and it might one day enable a new type of non-invasive brain scanning.

Few things in the Universe keep the beat as reliably as an atom’s pulse.

Yet even the most advanced ‘atomic’ clocks based on variations of these quantum timekeepers lose count when pushed to their limits.

Physicists have known for some time that entangling atoms can help tie particles down enough to squeeze a little more tick from every tock, yet most experiments have only been able to demonstrate this on the smallest of scales.

Not everything needs to be seen to be believed; certain things are more readily heard, like a train approaching its station. In a recent paper, published in Physical Review Letters, researchers have put their ears to the rail, discovering a new property of scattering amplitudes based on their study of sound waves through solid matter.

Be it light or sound, physicists consider the likelihood of particle interactions (yes, sound can behave like a particle) in terms of probability curves or scattering amplitudes. It is common lore that when the momentum or energy of one of the scattered particles goes to zero, scattering amplitudes should always scale with integer powers of momentum (i.e., p¹, p², p³, etc.). What the research team found however, was that the amplitude can be proportional to a fractional power (i.e., p^1/2, p^1/3, p^1/4, etc.).

Why does this matter? While quantum field theories, such as the Standard Model, allow researchers to make predictions about particle interactions with extreme accuracy, it is still possible to improve upon current foundations of fundamental physics. When a new behavior is demonstrated—such as fractional-power scaling—scientists are given an opportunity to revisit or revise existing theories.

A new device has been fabricated that can demonstrate the quantum anomalous Hall effect, in which tiny, discrete voltage steps are generated by an external magnetic field. This work may enable extremely low-power electronics, as well as future quantum computers.

If you take an ordinary wire with electrical current running through it, you can create a new electrical voltage perpendicular to the flow of current by applying an external magnetic field. This so-called Hall effect has been used as part of a simple magnetic sensor, but the sensitivity can be low.

There is a corresponding quantum version, called the quantum anomalous Hall effect that comes in defined increments, or quanta. This has raised the possibility of using the quantum anomalous Hall effect for the purpose of constructing new highly conductive wires or even quantum computers. However, the physics that leads to this phenomenon is still not completely understood.

Collaboration will seek to advance the development of a quantum internet.

Quantum computing looks like a world of imagination where we’ll be processing data beyond our thoughts. Many Industries are working to make a powerful Quantum computer that will solve all the issues. But what IBM has done is really something exceptional. They have developed the world’s first Quantum computer that will change history.
In a classical computer, data is stored and processed in bits, represented by either a zero or a one. But in quantum computers, qubits can not only be in a zero or one state but a superposition of both simultaneously: the more qubits, the more computing power, and the more possibilities. IBM’s quantum computer journey started with a 5-qubit quantum computer on the cloud called the Quantum Experience and led to the Eagle chip that began in 2016. Since then, the company has released a succession of chips with increasing numbers of qubits, all named after birds, each with its own set of technological challenges.

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face_with_colon_three circa 2018.

Understanding the fundamental constituents of the universe is tough. Making sense of the brain is another challenge entirely. Each cubic millimetre of human brain contains around 4 km of neuronal “wires” carrying millivolt-level signals, connecting innumerable cells that define everything we are and do. The ancient Egyptians already knew that different parts of the brain govern different physical functions, and a couple of centuries have passed since physicians entertained crowds by passing currents through corpses to make them seem alive. But only in recent decades have neuroscientists been able to delve deep into the brain’s circuitry.

On 25 January, speaking to a packed audience in CERN’s Theory department, Vijay Balasubramanian of the University of Pennsylvania described a physicist’s approach to solving the brain. Balasubramanian did his PhD in theoretical particle physics at Princeton University and also worked on the UA1 experiment at CERN’s Super Proton Synchrotron in the 1980s. Today, his research ranges from string theory to theoretical biophysics, where he applies methodologies common in physics to model the neural topography of information processing in the brain.

Continue reading “Particle physics on the brain” »