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When you think of empty space, you almost certainly imagine a vacuum in which nothing interesting can ever happen. However, if we zoom in to tiny length scales where quantum effects start to become important, it turns out that what you thought was empty is actually filled at all times with a seething mass of electromagnetic activity, as virtual photons flicker in and out of existence. This unexpected phenomenon is known as the vacuum fluctuation field. However, because these fluctuations of light energy are so small and fleeting in time, it is difficult to find ways for matter to interact with them, especially within a single, integrated device.

In a study published this month in Nano Letters (“Electrical Detection of Ultrastrong Coherent Interaction between Terahertz Fields and Electrons Using Quantum Point Contacts”), researchers from the Institute of Industrial Science, The University of Tokyo succeeded in fabricating a single nanoscale hybrid system for doing exactly this. In their design, a quantum point contact connects a single on-chip split-ring resonator with a two-dimensional electron system.

Quantum Hall edge channels at the quantum point contact. (Image: University of Tokyo)

A method developed at the University of Duisburg-Essen makes it possible to read data from noisy signals. Theoretical physicists and their experimental colleagues have published their findings in the current issue of Physical Review Research. The method they describe could also be significant for quantum computers.

You know it from the car radio: The weaker the signal, the more disturbing the . This is even more true for laboratory measurements. Researchers from the Collaborative Research Center 1,242 and the Center for Nanointegration (CENIDE) at the University of Duisburg-Essen (UDE) have now described a method for extracting data from noise.

What is a bit in a conventional computer, i.e., state 1 (current on) or state 0 (current off), is taken over in the quantum computer by the quantum bits, or qubits for short. To do this, they need defined and distinguishable states, but they can overlap at the same time and therefore enable many times the computing power of a current computer. This means they could also be used where today’s supercomputers are overtaxed, for example in searching extremely large databases.

Summary: New study on mice decision-making reveals that choice is not a singular moment but a reflection of the brain’s preexisting state.

The research, using Buridan’s Assay, suggests that the mice’s brain constantly broadcasts its goal, even before options are available, with patterns of neuron activity predicting choice.

Hunger and thirst don’t directly drive behavior; instead, they modulate the brain’s goal-setting, with an element of randomness causing switches between needs, ensuring both are met over time.

The aviation industry could be on the cusp of a revolution, following recent tests of a new purely electric jet engine that packs the same punch as its traditional fossil fuel-burning cousins.

Canadian-based company Duxion Motors recently celebrated a significant milestone with the successful ground test of its eJet Motor – the world’s first rim-driven jet propulsion motor.

The eJet motor, an electric jet engine, represents a significant leap in electric aviation, utilizing permanent magnet technology to deliver unprecedented power-to-weight ratios within a compact design. Duxion’s approach could revolutionize the industry, offering scalable efficiency suited to larger aircraft, hybrid cooling for enhanced power density and reliability, and a flexible design that can be tailored to various airframes.

Not a perfect presentation but a quantum Internet will be nice. The question is, how will bad actors/Black Hat hackers adapt?


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Another good use for AI. Fighting disinformation.


About 60% of adults in the US who get their news through social media have, largely unknowingly, shared false information, according to a poll by the Pew Research Center. The ease at which disinformation is spread and the severity of consequences it brings — from election hacking to character assassination — make it an issue of grave concern for us all.

One of the best ways to combat the spread of fake news on the internet is to understand where the false information was started and how it was disseminated. And that’s exactly what Camille Francois, the chief innovation officer at Graphika, is doing. She’s dedicated to bringing to light disinformation campaigns before they take hold.

Francois and her team are employing machine learning to map out online communities and better understand how information flows through networks. It’s a bold and necessary crusade as troll farms, deep fakes, and false information bombard the typical internet user every single day.

Francois says, this work is two parts technology, one part sociology. The techniques are always evolving, and we have to stay one step ahead.” We sit down with Francois for an in-depth discussion on how the tech works and what it means for the dissemination of information across the internet.