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Cosmic Heavyweights Collide — LIGO Detects Largest, Fastest-Spinning Black Holes Yet

In addition to their high masses, the black holes are also rapidly spinning.

“This is the most massive black hole binary we’ve observed through gravitational waves, and it presents a real challenge to our understanding of black hole formation,” says Mark Hannam of Cardiff University and a member of the LVK Collaboration. “Black holes this massive are forbidden through standard stellar evolution models. One possibility is that the two black holes in this binary formed through earlier mergers of smaller black holes.”

Breaking: Major Antimatter Discovery May Help Solve Mystery of Existence

We’re now a step closer to understanding how the Universe avoided an antimatter apocalypse. CERN scientists have discovered tantalizing clues of a fundamental difference in the way physics handles matter and antimatter.

Experiments at the Large Hadron Collider (LHC) have verified an asymmetry between matter and antimatter forms of a particle called a baryon.

Known as a charge-parity (CP) violation, the effect has only previously been detected in another class of particles, called mesons. But experimental evidence in baryons, which make up the bulk of the Universe’s matter, is something physicists have been long hunting for.

Google sues to disrupt BadBox 2.0 botnet infecting 10 million devices

Google has filed a lawsuit against the anonymous operators of the Android BadBox 2.0 malware botnet, accusing them of running a global ad fraud scheme against the company’s advertising platforms.

The BadBox 2.0 malware botnet is a cybercrime operation that utilizes infected Android Open Source Project (AOSP) devices, including smart TVs, streaming boxes, and other connected devices that lack security protections, such as Google Play Protect.

These devices become infected either by threat actors purchasing low-cost AOSP devices, modifying the operating system to include the BadBox 2 malware, and then reselling them online, or by tricking users into downloading and installing malicious apps on their devices that contain the malware.

Human-AI teamwork uncovers hidden magnetic states in quantum spin liquids

At the forefront of discovery, where cutting-edge scientific questions are tackled, we often don’t have much data. Conversely, successful machine learning (ML) tends to rely on large, high-quality data sets for training. So how can researchers harness AI effectively to support their investigations?

In Physical Review Research, scientists describe an approach for working with ML to tackle complex questions in condensed matter physics. Their method tackles hard problems which were previously unsolvable by physicist simulations or by ML algorithms alone.

The researchers were interested in frustrated magnets— in which competing interactions lead to exotic magnetic properties. Studying these materials has helped to advance our understanding of quantum computing and shed light on . However, frustrated magnets are very difficult to simulate, because of the constraints arising from the way magnetic ions interact.