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Physicists have measured ‘negative time’ in the lab

As Homer tells us, Odysseus made an epic journey, against the odds, from Troy to his home in Ithaca. He visited many lands, but mostly dwelt with the nymph Calypso on her island. We can imagine that his wife, Penelope, would have asked him about that particular time. Odysseus might have replied, “It was nothing. In fact, it was less than nothing. Negative five years I dwelt with Calypso. How else could I have arrived home after only ten years? If you don’t believe me, ask her.”

Quantum particles, it turns out, are just as wily as Odysseus, as we have shown in an experiment published in Physical Review Letters. Not only can their arrival time suggest that they dwelt with other particles for a negative amount of time, but if one asks those other particles, they will corroborate the story.

The way a cell fails to divide after copying its DNA can determine its fate

Cell division is one of the most fundamental and complex processes underpinning life. In human cells, thousands of molecules coordinate with one another in highly precise steps, all within a fraction of a second. But things don’t always go as planned.

Before a cell divides into two, it must first copy its DNA, so that each new cell receives a complete set. Occasionally, what can happen is, a cell successfully copies its DNA but then fails to split into two. When this happens, the cell is left with two copies of its DNA—a condition known as whole genome duplication (WGD).

One way to picture this is to imagine photocopying a document. Normally, you would make two copies and place one in each folder. In whole genome duplication, the copies are made but not separated, leaving one folder with both copies.

AI tackles one of math’s most brutal problems: Inverse PDEs

Penn Engineers have developed a new way to use AI to solve inverse partial differential equations (PDEs), a particularly challenging class of mathematical problems with broad implications for understanding the natural world.

The advance, which the researchers call “Mollifier Layers,” could benefit fields as varied as genetics and weather forecasting, because inverse PDEs help scientists work backward from observable patterns to infer the hidden dynamics that produced them.

“Solving an inverse problem is like looking at ripples in a pond and working backward to figure out where the pebble fell,” says Vivek Shenoy, Eduardo D. Glandt President’s Distinguished Professor in Materials Science and Engineering (MSE) and senior author of a study published in Transactions on Machine Learning Research (TMLR), which will be presented at the Conference on Neural Information Processing Systems (NeurIPS 2026). “You can see the effects clearly, but the real challenge is inferring the hidden cause.”

Slower access, faster chemistry: Nanoreactor design improves catalysis by balancing molecular flow

A new study by a team at Tohoku University, published in Chemical Engineering Journal, has shown that more isn’t always better when it comes to nanoscale chemical reactions. One might think that giving reactants completely unrestricted access to a speed-boosting catalyst would be the fastest way to drive a chemical reaction. Instead, it was shown that hollow nanoreactors can work more efficiently when transport into the reaction space is slightly restricted.

A nanoreactor is a porous shell that surrounds an inner space containing catalytically active nanoparticles. The inner space where reactions occur provides a special environment which opens the door for unique and highly useful chemical reactions. Finding ways to optimize reactions in these confined spaces could help to produce a myriad of everyday products more efficiently, and at a lower price.

While it might seem like flooding this inner space would get things done the fastest, researchers found that the key to optimization involved holding back a little.

A new type of optical chip cuts static power while enabling electrical reprogramming

As technology advances, and the demand for faster, higher-bandwidth, and more energy-efficient data processing continues to grow, scientists and engineers search for ways to improve electronic systems. One avenue they have been exploring is optoelectronics—the study and application of electronic devices that interface with light by detecting, emitting, or converting it into electrical signals.

Optoelectronics offers significant advantages over conventional electronics, including faster speed, higher bandwidth, lower power consumption, and improved reliability.

One particularly promising direction in optoelectronics has been the development of the photonic integrated circuit—an optical microchip that uses light (photons) instead of electricity (electrons) to sense, process, and transmit information. These optical chips are already being used in many advanced technologies today, such as high-speed fiber-optic communications, data center interconnects, sensors for autonomous vehicles, and hardware accelerators for machine learning and artificial intelligence.

Computer vision helps observers understand how iconic artworks were created

Paintings are often made up of thousands of tiny brushstrokes, each going in a certain direction, that are not easily observed by the viewer. A cross-disciplinary research team from the Penn State College of Information Sciences and Technology (IST) and Loughborough University in England has developed an image analysis method that helps to make the underlying brushstroke structure of paintings visible, giving new insight into how artists physically created their works.

This approach offers both experts and non-experts a fresh way to observe and interpret the making of artworks. The research was recently published in the journal Patterns.

The researchers bridged art and data science to show that painting style can be quantified and visualized as flow, turning elusive qualities like “gesture” into measurable, analyzable data. They used a computational technique to examine very small patches of Impressionist paintings, determining the direction of the brushstroke in each tiny spot and connect these different directions, as if drawing lines that follow the flow.

Proton beam timing tool could check radiotherapy energy before nearly every treatment

Proton beams are not only used in sophisticated nuclear physics experiments. Today, they are becoming increasingly popular in radiotherapy, where they are an irreplaceable tool for destroying cancer cells. Doctors and physicists can enhance their precision thanks to two solutions developed at the Cyclotron Center Bronowice of the Institute of Nuclear Physics, Polish Academy of Sciences.

In oncology, it is crucial to precisely eliminate cancer cells while causing as little damage as possible to healthy cells. For physicists, on the other hand, it is essential to have a precise understanding of the conditions under which they conduct their experiments. In the case of proton beams, used in radiotherapy and nuclear physics experiments, knowing the kinetic energy of the particles is key.

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