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Quantum Computing Meets Finance

Eric Ghysels made a name for himself in financial econometrics and time-series analysis. Now he translates financial models into quantum algorithms.

Economist Eric Ghysels has spent most of his career fascinated by a fundamental problem in the financial industry: figuring out how to put a price on any financial asset whose future value depends on market conditions. Ghysels, a professor at the University of North Carolina at Chapel Hill, has now set himself a new problem: studying the impact that quantum computing could have on solving asset pricing, portfolio optimization, and other computationally intensive financial problems.

He admits that nobody knows when quantum computers will have commercially viable applications, but, he says, it’s important to invest now. Physics Magazine spoke with Ghysels to learn why.

Physicists demonstrate controlled expansion of quantum wavepacket in a levitated nanoparticle

Quantum mechanics theory predicts that, in addition to exhibiting particle-like behavior, particles of all sizes can also have wave-like properties. These properties can be represented using the wave function, a mathematical description of quantum systems that delineates a particle’s movements and the probability that it is in a specific position.

Newly discovered cell machinery breaks down protein aggregates into smaller pieces before ‘taking it to the trash’

A new study from Aarhus University shows that our cells’ ability to clean out old protein clumps, known as aggregates, also includes a—up till now unknown—partnership with an engine that breaks down bigger pieces into smaller before “taking it to the trash.” An important find for future treatments of diseases like Alzheimer’s, Parkinson’s, ALS and Huntington’s, which are all characterized by the accumulation of protein in the brain.

Imagine you’re about to eat a big pizza. In order to not choke on it, you cut it up into slices and eat it bite by bite. And while you’re chomping down on your slices, cells inside your body are busy slicing the built-up protein clumps into pieces that are more manageable for the body’s trash system—otherwise it would clog up and malfunction.

Researchers from the department of Biomedicine at Aarhus University have just released a new study, which for the first time documents exactly how those clumps of unwanted protein get reduced to smaller pieces before being disposed of by the cells’ garbage disposal system—called autophagy. The work is published in the journal Nature Cell Biology.

Scientist returns to microbial roots and discovers potential quantum computing advancement

During his Ph.D. at UMass, Nikhil Malvankar was laser-focused on quantum mechanics and the movement of electrons in superconductors. Now a professor at Yale, the native of Mumbai, India, has pivoted toward biology to explain how bacteria breathe deep underground without the aid of oxygen.

Sustainable AI: Physical neural networks exploit light to train more efficiently

Artificial intelligence is now part of our daily lives, with the subsequent pressing need for larger, more complex models. However, the demand for ever-increasing power and computing capacity is rising faster than the performance traditional computers can provide.

To overcome these limitations, research is moving towards innovative technologies such as physical neural networks, analog circuits that directly exploit the laws of physics (properties of light beams, quantum phenomena) to process information. Their potential is at the heart of the study published in the journal Nature. It is the outcome of collaboration between several international institutes, including the Politecnico di Milano, the École Polytechnique Fédérale in Lausanne, Stanford University, the University of Cambridge, and the Max Planck Institute.

The article entitled “Training of Physical Neural Networks” discusses the steps of research on training physical neural networks, carried out with the collaboration of Francesco Morichetti, professor at DEIB—Department of Electronics, Information and Bioengineering, and head of the university’s Photonic Devices Lab.

Cracks in flexible electronics run deeper than expected: Study points to potential fix

From health monitors and smartwatches to foldable phones and portable solar panels, demand for flexible electronics is growing rapidly. But the durability of those devices—their ability to stand up to thousands of folds, flexes and rolls—is a significant concern.

New research by engineers from Brown University has revealed surprising details about how cracks form in multilayer flexible electronic devices. The team shows that small cracks in a device’s fragile electrode layer can drive deeper, more destructive cracks into the tougher polymer substrate layer on which the electrodes sit. The work overturns a long-held assumption that polymer substrates usually resist cracking.

“The substrate in is a bit like the foundation in your house,” said Nitin Padture, a professor of engineering at Brown and corresponding author of the study published in npj Flexible Electronics. “If it’s cracked, it compromises the mechanical integrity of the entire device. This is the first clear evidence of cracking in a device substrate caused by a brittle film on top of it.”

High-entropy alloys: How chaos takes over in layered carbides as metal diversity increases

In the tug-of-war between order and chaos within multielemental carbides, entropy eventually claims victory over enthalpy by pushing the system toward complete disorder as the diversity of elements in the material increases, as revealed in a study published in Science.

Researchers synthesized 40 layered carbide phases with composition MAlX materials (M is a transition metal, Al is for aluminum, and X is either C or N), where the number of M was between 2 and 9.

Their goal was to uncover the trends in short-range ordering and compositional disorder in so-called high– systems. They found that in carbides with fewer constituent elements, short-range order driven by enthalpy dominated. However, as the number of elements increased, entropy took control, randomizing the metal configurations.

Rolling soft electronics yields 3D brain probes for precise neuron mapping

To shed new light on the contribution of different brain regions and neural circuits to specific mental functions, neuroscientists and medical researchers rely on advanced imaging techniques and neural probes. These are electronic devices embedding electrodes, components that can measure the electrical impulses produced by neurons, which are known as spikes.

While existing probes have helped to map various networks of neurons and understand their functions, most of them have two-dimensional (2D) layouts. This is because they are made employing conventional semiconductor-based devices and fabrication strategies.

Researchers at Dartmouth College, University of Pittsburgh, Oklahoma State University and other institutes have developed a new approach that could enable the fabrication of soft three-dimensional (3D) neural probes on a large scale. Their proposed method, outlined in a paper published in Nature Electronics, entails the rolling of flat into cylindrical 3D structures.

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