When Twitter banned more than 70,000 traffickers of false information from its platform in the wake of the violence at the U.S. Capitol on Jan. 6, 2021, the impact went beyond the silencing of those users.

A study co-authored by UC Riverside public policy and political science scholars published in the journal Nature on June 5, found that the crackdown by Twitter (now called X after it was acquired by billionaire Elon Musk in late 2022) also significantly reduced the number of misinformation posts by users who stayed on the platform but had been following those who were kicked off.

Additionally, the study found that many of the misinformation traffickers, including those who posted Q-Anon conspiracy theories, left Twitter on their own accord after the massive de-platforming, which included the banning of then-President Donald Trump.

“There was a spillover effect,” said Kevin M. Esterling, a UCR professor of political science and public policy and a co-author of the study. “It wasn’t just a reduction from the de-platformed users themselves, but it reduced circulation on the platform as a whole.”

It was the first time such an effect had been shown, he said.

The researchers analyzed a panel of about 550,000 Twitter users in the United States who were active during the 2020 election cycle. This information was acquired by David Lazer, the corresponding author of the study, who is a professor of political science and computer and information science at Northeastern University in Boston.

A research team from Lazer’s laboratory collected Twitter posts through Twitter’s application programming interface, or API, which is a set of programmatic tools that allowed researchers to interact with Twitter’s platform and gather tweets and other information about users of the platform. The users in the panel were verified as real people by cross-referencing with voter registration data.

The analysis found that those who had followed one or more of the 70,000 who were de-platformed had been more frequent tweeters of URLs (Internet addresses) known to disseminate misinformation when compared with others in the panel of users.

The research also identified about 600 “super sharers” of misinformation in the panel who were in the top 0.1 percent of misinformation sharers in the months leading up to the Jan. 6 insurrection. The analysis found their ranks dropped by more than half after the de-platforming. Similarly, some 650 Q-Anon sharers in the panel dropped to about 200 two weeks after the de-platforming.

When monitoring their platforms, social media companies face a tradeoff between private economic interests and the public interest, said Diogo Ferrari, co-author of the paper and a UCR assistant professor of political science. Fake news posts increase engagement, which helps a platform’s bottom line. But curbing it “is good for democracy and democratic governance,” he said.

The study’s title is “Twitter’s post-January 6 de-platforming reduced the reach of misinformation.” In addition to Esterling, Ferrari, and Lazer, its co-authors are Jon Green of Duke University and Stefan McCabe of the Institute for Data, Democracy and Politics at the George Washington University.

A team of researchers led by Philip Walther at the University of Vienna carried out a pioneering experiment where they measured the effect of the rotation of Earth on quantum entangled photons. The work, published in Science Advances, represents a significant achievement that pushes the boundaries of rotation sensitivity in entanglement-based sensors, potentially setting the stage for further exploration at the intersection between quantum mechanics and general relativity.

Optical Sagnac interferometers are the most sensitive devices to rotations. They have been pivotal in our understanding of fundamental physics since the early years of the last century, contributing to establishing Einstein’s special theory of relativity. Today, their unparalleled precision makes them the ultimate tool for measuring rotational speeds, limited only by the boundaries of classical physics.

Interferometers employing quantum entanglement have the potential to break those bounds. If two or more particles are entangled, only the overall state is known, while the state of the individual particle remains undetermined until measurement. This can be used to obtain more information per measurement than would be possible without it. However, the promised quantum leap in sensitivity has been hindered by the extremely delicate nature of entanglement. Here is where the Vienna experiment made the difference.

The researchers built a giant optical fiber Sagnac interferometer and kept the noise low and stable for several hours. This enabled the detection of enough high-quality entangled photon pairs to outperform the rotation precision of previous quantum optical Sagnac interferometers by a thousand times.

In a Sagnac interferometer, two particles traveling in opposite directions of a rotating closed path reach the starting point at different times. With two entangled particles, it becomes spooky: they behave like a single particle testing both directions simultaneously while accumulating twice the time delay compared to the scenario where no entanglement is present.

This unique property is known as super-resolution. In the actual experiment, two entangled photons were propagating inside a 2-kilometer-long optical fiber wounded onto a huge coil, realizing an interferometer with an effective area of more than 700 square meters.

A significant hurdle the researchers faced was isolating and extracting Earth’s steady rotation signal. “The core of the matter lays in establishing a reference point for our measurement, where light remains unaffected by Earth’s rotational effect. Given our inability to halt Earth’s from spinning, we devised a workaround: splitting the optical fiber into two equal-length coils and connecting them via an optical switch,” explains lead author Raffaele Silvestri.

By toggling the switch on and off, the researchers could effectively cancel the rotation signal at will, which also allowed them to extend the stability of their large apparatus. “We have basically tricked the light into thinking it’s in a non-rotating universe,” says Silvestri.

The experiment, which was conducted as part of the research network TURIS hosted by the University of Vienna and the Austrian Academy of Sciences, has successfully observed the effect of the rotation of Earth on a maximally entangled two-photon state. This confirms the interaction between rotating reference systems and quantum entanglement, as described in Einstein’s special theory of relativity and quantum mechanics, with a thousand-fold precision improvement compared to previous experiments.

“That represents a significant milestone since, a century after the first observation of Earth’s rotation with light, the entanglement of individual quanta of light has finally entered the same sensitivity regimes,” says Haocun Yu, who worked on this experiment as a Marie-Curie Postdoctoral Fellow.

“I believe our result and methodology will set the ground to further improvements in the rotation sensitivity of entanglement-based sensors. This could open the way for future experiments testing the behavior of quantum entanglement through the curves of spacetime,” adds Philip Walther.

in the Planetary Science Journal, the research by Brown scholars Benjamin Boatwright and James Head describes enhancements to a mapping technique called shape-from-shading. The technique is used to create detailed models of lunar terrain, outlining craters, ridges, slopes and other surface hazards. By analyzing the way light hits different surfaces of the moon, it allows researchers to estimate the three-dimensional shape of an object or surface from composites of two-dimensional images.

Accurate maps can help lunar mission planners to identify safe landing spots and areas of scientific interest, making mission operations smoother and more successful.

“It helps us piece together a better idea of what is actually there,” said Boatwright, a postdoctoral researcher in Brown’s Department of Earth, Environmental and Planetary Sciences and lead author of the new paper. “We need to understand the surface topography of the moon where there isn’t as much light, like the shadowed areas of the lunar south pole where NASA’s Artemis missions are targeting.

“That will allow autonomous landing software to navigate and avoid hazards, like large rocks and boulders, that could endanger a mission. For that reason, you need models that map the topography of the surface at as high a resolution as possible because the more detail you have, the better.”

The process to develop precision maps, however, is labor intensive and has limitations when it comes to complex lighting conditions, inaccurate shadow interpretation and handling terrain variability. The Brown researchers’ improvements to the shape-from-shading technique focus on addressing these issues.

The scholars outline in the study how advanced computer algorithms can be used to automate much of the process and significantly heighten the resolution of the models. The new software gives lunar scientists the tools to create larger maps of the moon’s surface that contain finer details at a much faster pace, the researchers say.

“Shape-from-shading requires that the images that you’re using be perfectly aligned with one another so that a feature in one image is in the exact same place in another image to build up those layers of information, but current tools are not quite in a place where you can just give it bunches of images and it’ll spit out a perfect product,” Boatwright said.

“We implemented an image alignment algorithm where it picks out features in one image and tries to find those same features in the other and then line them up, so that you’re not having to sit there manually tracing interest points across multiple images, which takes a lot a of hours and brain power.”

The researchers also implemented quality control algorithms and additional filters to reduce outliers from the alignment process—tools to ensure the aligned images actually match and remove images that don’t align as well. By only selecting images that end up being usable, this improves quality and takes precision down to submeter resolutions. The speed also allows for larger surface areas to be examined, increasing the production of these maps.

The researchers evaluated the accuracy of their maps by comparing them with other existing topographic models, looking for discrepancies or errors in lunar surface features. They found the maps generated using their refined shape-from-shading method were more precise compared to those derived from traditional techniques, showing more subtle features and variations of lunar surface terrain.

For the study, the researchers primarily used data from Lunar Orbiter Laser Altimeter and Lunar Reconnaissance Orbiter Camera, instruments onboard NASA’s Lunar Reconnaissance Orbiter, which has been orbiting the moon since 2009.

The scientists plan to use their refined shape-from-shading software to produce lunar maps, and they hope others will use it in their modeling efforts, as well. It’s why they used open-source algorithms to produce the tool.

“These new map products are significantly better than what we had in exploration planning during the Apollo missions, and they will very much improve the mission planning and scientific return for Artemis and robotic missions,” said Head, a professor of geological sciences at Brown who worked in the Apollo program.

The researchers hope the new tool will add to the current interest in the science and exploration of the moon happening at NASA and in space agencies around the world.

“There’s a wealth of information to be gained from making these types of tools accessible to all,” Boatwright said. “It’s an egalitarian way of doing science.”