Removing complexity layers from the universe's creation

Complicated statistical behaviour observed in complex systems such as early universe can often be understood if it is broken down into simpler ones. Two physicists, Petr Jizba (currently affiliated with the Czech Technical ...

Ultrafast technique unlocks design principles of quantum biology

University of Chicago researchers have created a synthetic compound that mimics the complex quantum dynamics observed in photosynthesis and may enable fundamentally new routes to creating solar-energy technologies. Engineering ...

Unlocking nature's quantum engineering for efficient solar energy

(Phys.org)—Quantum scale photosynthesis in biological systems which inhabit extreme environments could hold key to new designs for solar energy and nanoscale devices. Certain biological systems living in low light environments ...

Can fluid dynamics offer insights into quantum mechanics?

In the first decades of the 20th century, physicists hotly debated how to make sense of the strange phenomena of quantum mechanics, such as the tendency of subatomic particles to behave like both particles and waves. One ...

Combating disruptive 'noise' in quantum communication

In a significant milestone for quantum communication technology, an experiment has demonstrated how networks can be leveraged to combat disruptive 'noise' in quantum communications.

Simulations reveal the atomic-scale story of qubits

Researchers led by Giulia Galli at University of Chicago's Pritzker School of Molecular Engineering report a computational study that predicts the conditions to create specific spin defects in silicon carbide. Their findings, ...

Capturing the evolution of complex quantum systems

Through a new survey, researchers show how mathematical representations named 'tensor trains' can help to capture and simulate the dynamics of evolving quantum systems across a range of different scenarios.

Machine learning enhances X-ray imaging of nanotextures

Using a combination of high-powered X-rays, phase-retrieval algorithms and machine learning, Cornell researchers revealed the intricate nanotextures in thin-film materials, offering scientists a new, streamlined approach ...

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