Tag Archives: reality

Experiment confirms quantum theory weirdness

The bizarre nature of reality as laid out by quantum theory has survived another test, with scientists performing a famous experiment and proving that reality does not exist until it is measured.

Physicists at The Australian National University (ANU) have conducted John Wheeler’s delayed-choice thought experiment, which involves a moving object that is given the choice to act like a particle or a wave. Wheeler’s experiment then asks – at which point does the object decide?

Common sense says the object is either wave-like or particle-like, independent of how we measure it. But quantum physics predicts that whether you observe wave like behavior (interference) or particle behavior (no interference) depends only on how it is actually measured at the end of its journey. This is exactly what the ANU team found.

“It proves that measurement is everything. At the quantum level, reality does not exist if you are not looking at it,” said Associate Professor Andrew Truscott from the ANU Research School of Physics and Engineering.

Despite the apparent weirdness, the results confirm the validity of quantum theory, which governs the world of the very small, and has enabled the development of many technologies such as LEDs, lasers and computer chips.

The ANU team not only succeeded in building the experiment, which seemed nearly impossible when it was proposed in 1978, but reversed Wheeler’s original concept of light beams being bounced by mirrors, and instead used atoms scattered by laser light.

“Quantum physics’ predictions about interference seem odd enough when applied to light, which seems more like a wave, but to have done the experiment with atoms, which are complicated things that have mass and interact with electric fields and so on, adds to the weirdness,” said Roman Khakimov, PhD student at the Research School of Physics and Engineering.

Professor Truscott’s team first trapped a collection of helium atoms in a suspended state known as a Bose-Einstein condensate, and then ejected them until there was only a single atom left.

The single atom was then dropped through a pair of counter-propagating laser beams, which formed a grating pattern that acted as crossroads in the same way a solid grating would scatter light.

A second light grating to recombine the paths was randomly added, which led to constructive or destructive interference as if the atom had travelled both paths. When the second light grating was not added, no interference was observed as if the atom chose only one path.

However, the random number determining whether the grating was added was only generated after the atom had passed through the crossroads.

If one chooses to believe that the atom really did take a particular path or paths then one has to accept that a future measurement is affecting the atom’s past, said Truscott.

“The atoms did not travel from A to B. It was only when they were measured at the end of the journey that their wave-like or particle-like behavior was brought into existence,” he said.

The research is published in Nature Physics.

Source: ANU

Electrical and computer engineering Professor Barry Van Veen wears an electrode net used to monitor brain activity via EEG signals. His research could help untangle what happens in the brain during sleep and dreaming.

Photo Credit: Nick Berard/UW-Madison

Imagination, reality flow in opposite directions in the brain

By Scott Gordon


As real as that daydream may seem, its path through your brain runs opposite reality.

Aiming to discern discrete neural circuits, researchers at the University of Wisconsin–Madison have tracked electrical activity in the brains of people who alternately imagined scenes or watched videos.

“A really important problem in brain research is understanding how different parts of the brain are functionally connected. What areas are interacting? What is the direction of communication?” says Barry Van Veen, a UW-Madison professor of electrical and computer engineering. “We know that the brain does not function as a set of independent areas, but as a network of specialized areas that collaborate.”

Van Veen, along with Giulio Tononi, a UW-Madison psychiatry professor and neuroscientist, Daniela Dentico, a scientist at UW–Madison’s Waisman Center, and collaborators from the University of Liege in Belgium, published results recently in the journalNeuroImage. Their work could lead to the development of new tools to help Tononi untangle what happens in the brain during sleep and dreaming, while Van Veen hopes to apply the study’s new methods to understand how the brain uses networks to encode short-term memory.

During imagination, the researchers found an increase in the flow of information from the parietal lobe of the brain to the occipital lobe — from a higher-order region that combines inputs from several of the senses out to a lower-order region.

Electrical and computer engineering Professor Barry Van Veen wears an electrode net used to monitor brain activity via EEG signals. His research could help untangle what happens in the brain during sleep and dreaming. Photo Credit: Nick Berard/UW-Madison
Electrical and computer engineering Professor Barry Van Veen wears an electrode net used to monitor brain activity via EEG signals. His research could help untangle what happens in the brain during sleep and dreaming.
Photo Credit: Nick Berard/UW-Madison

In contrast, visual information taken in by the eyes tends to flow from the occipital lobe — which makes up much of the brain’s visual cortex — “up” to the parietal lobe.

“There seems to be a lot in our brains and animal brains that is directional, that neural signals move in a particular direction, then stop, and start somewhere else,” says. “I think this is really a new theme that had not been explored.”

The researchers approached the study as an opportunity to test the power of electroencephalography (EEG) — which uses sensors on the scalp to measure underlying electrical activity — to discriminate between different parts of the brain’s network.

Brains are rarely quiet, though, and EEG tends to record plenty of activity not necessarily related to a particular process researchers want to study.

To zero in on a set of target circuits, the researchers asked their subjects to watch short video clips before trying to replay the action from memory in their heads. Others were asked to imagine traveling on a magic bicycle — focusing on the details of shapes, colors and textures — before watching a short video of silent nature scenes.

Using an algorithm Van Veen developed to parse the detailed EEG data, the researchers were able to compile strong evidence of the directional flow of information.

“We were very interested in seeing if our signal-processing methods were sensitive enough to discriminate between these conditions,” says Van Veen, whose work is supported by the National Institute of Biomedical Imaging and Bioengineering. “These types of demonstrations are important for gaining confidence in new tools.”

Source: UW-Madison News

Projecting a robot’s intentions

A new spin on virtual reality helps engineers read robots’ minds.  

By Jennifer Chu


Video/release: http://newsoffice.mit.edu/2014/system-shows-robot-intentions-1029

MIT Video release for the news

[MIT researchers explain their new visualization system that can project a robot's "thoughts." Video: Melanie Gonick/MIT]

CAMBRIDGE, Mass. – In a darkened, hangar-like space inside MIT’s Building 41, a small, Roomba-like robot is trying to make up its mind.

Standing in its path is an obstacle — a human pedestrian who’s pacing back and forth. To get to the other side of the room, the robot has to first determine where the pedestrian is, then choose the optimal route to avoid a close encounter.

As the robot considers its options, its “thoughts” are projected on the ground: A large pink dot appears to follow the pedestrian — a symbol of the robot’s perception of the pedestrian’s position in space. Lines, each representing a possible route for the robot to take, radiate across the room in meandering patterns and colors, with a green line signifying the optimal route. The lines and dots shift and adjust as the pedestrian and the robot move.

This new visualization system combines ceiling-mounted projectors with motion-capture technology and animation software to project a robot’s intentions in real time. The researchers have dubbed the system “measurable virtual reality (MVR) — a spin on conventional virtual reality that’s designed to visualize a robot’s “perceptions and understanding of the world,” says Ali-akbar Agha-mohammadi, a postdoc in MIT’s Aerospace Controls Lab..

“Normally, a robot may make some decision, but you can’t quite tell what’s going on in its mind — why it’s choosing a particular path,” Agha-mohammadi says. “But if you can see the robot’s plan projected on the ground, you can connect what it perceives with what it does to make sense of its actions.”

Agha-mohammadi says the system may help speed up the development of self-driving cars, package-delivering drones, and other autonomous, route-planning vehicles.

“As designers, when we can compare the robot’s perceptions with how it acts, we can find bugs in our code much faster,” Agha-mohammadi says. “For example, if we fly a quadrotor, and see something go wrong in its mind, we can terminate the code before it hits the wall, or breaks.”

The system was developed by Shayegan Omidshafiei, a graduate student, and Agha-mohammadi. They and their colleagues, including Jonathan How, a professor of aeronautics and astronautics, will present details of the visualization system at the American Institute of Aeronautics and Astronautics’ SciTech conference in January.

Seeing into the mind of a robot

The researchers initially conceived of the visualization system in response to feedback from visitors to their lab. During demonstrations of robotic missions, it was often difficult for people to understand why robots chose certain actions.

“Some of the decisions almost seemed random,” Omidshafiei recalls.

The team developed the system as a way to visually represent the robots’ decision-making process. The engineers mounted 18 motion-capture cameras on the ceiling to track multiple robotic vehicles simultaneously. They then developed computer software that visually renders “hidden” information, such as a robot’s possible routes, and its perception of an obstacle’s position. They projected this information on the ground in real time, as physical robots operated.

The researchers soon found that by projecting the robots’ intentions, they were able to spot problems in the underlying algorithms, and make improvements much faster than before.

“There are a lot of problems that pop up because of uncertainty in the real world, or hardware issues, and that’s where our system can significantly reduce the amount of effort spent by researchers to pinpoint the causes,” Omidshafiei says. “Traditionally, physical and simulation systems were disjointed. You would have to go to the lowest level of your code, break it down, and try to figure out where the issues were coming from. Now we have the capability to show low-level information in a physical manner, so you don’t have to go deep into your code, or restructure your vision of how your algorithm works. You could see applications where you might cut down a whole month of work into a few days.”

Bringing the outdoors in

The group has explored a few such applications using the visualization system. In one scenario, the team is looking into the role of drones in fighting forest fires. Such drones may one day be used both to survey and to squelch fires — first observing a fire’s effect on various types of vegetation, then identifying and putting out those fires that are most likely to spread.

To make fire-fighting drones a reality, the team is first testing the possibility virtually. In addition to projecting a drone’s intentions, the researchers can also project landscapes to simulate an outdoor environment. In test scenarios, the group has flown physical quadrotors over projections of forests, shown from an aerial perspective to simulate a drone’s view, as if it were flying over treetops. The researchers projected fire on various parts of the landscape, and directed quadrotors to take images of the terrain — images that could eventually be used to “teach” the robots to recognize signs of a particularly dangerous fire.

Going forward, Agha-mohammadi says, the team plans to use the system to test drone performance in package-delivery scenarios. Toward this end, the researchers will simulate urban environments by creating street-view projections of cities, similar to zoomed-in perspectives on Google Maps.

“Imagine we can project a bunch of apartments in Cambridge,” Agha-mohammadi says. “Depending on where the vehicle is, you can look at the environment from different angles, and what it sees will be quite similar to what it would see if it were flying in reality.”

Because the Federal Aviation Administration has placed restrictions on outdoor testing of quadrotors and other autonomous flying vehicles, Omidshafiei points out that testing such robots in a virtual environment may be the next best thing. In fact, the sky’s the limit as far as the types of virtual environments that the new system may project.

“With this system, you can design any environment you want, and can test and prototype your vehicles as if they’re fully outdoors, before you deploy them in the real world,” Omidshafiei says.

This work was supported by Boeing.

Source: MIT News