EXTINGUISHING THE BLACK HOLE FIREWALL PARADOX

In the quest for knowledge about how our universe works, physicists have been trying to understand black holes for decades. In 2014, Michigan State University professor Chris Adami published a paper that arguably solved the paradox of classical information and black holes.

He discovered that if you throw classical information at a black hole, the information is copied and contained in the stimulated emission of radiation, but not in the Hawking radiation, named after physicist Stephen Hawking. This means information is preserved and the laws of physics remain intact. Read the full press release.

Check out Chris's latest paper: Black holes as bosonic Gaussian channels

READ THE PAPER

Now out in Physical Review D, Chris Adami has a new in-depth investigation of the quantum capacity of black holes, using modern methods for the classification of so-called "One-Mode Gaussian" (OMG) channels. 

Chris in Huffington Post: Did Hawking Just Solve His Own Paradox - or Did Einstein?

It's been 40 years since Stephen Hawking shocked the physics world by claiming that the universe is inherently unpredictable. Now, at a conference in Stockholm where invited luminaries are discussing the impact of Hawking's discovery and possible ways to resolve the contradictions it has wrought, Hawking himself took the stage and announced that he had resolved all those contradictions.


Evolution RESEARCH

CHRIS FEATURED IN NATUREARTIFICIAL INTELLIGENCE: ROBOTS WITH INSTINCTS

Cully et al.1 have designed an algorithm that allows robots to develop strategies for overcoming the effects of damaged limbs. Two robots were used: a, a hexapod (width 50 centimeters); b, a robotic arm (length 62 cm). Antoine Cully/UPMC

Cully et al.1 have designed an algorithm that allows robots to develop strategies for overcoming the effects of damaged limbs. Two robots were used: a, a hexapod (width 50 centimeters); b, a robotic arm (length 62 cm). Antoine Cully/UPMC

An evolutionary algorithm has been developed that allows robots to adapt to unforeseen change. The robots learn behaviors quickly and instinctively by mining the memory of their past achievements.

Intelligence, by some accounts, is synonymous with the ability to predict the future. Because doing so quickly can often mean the difference between life and death, our brains have evolved to be able to search the vast number of potential futures easily. How is such a feat accomplished? Read more.


Chester  the Computational Cat helps illustrate the importance of trade-offs in evolution.

Chester  the Computational Cat helps illustrate the importance of trade-offs in evolution.

Evolutionary Compromises Drive Diversity

To paraphrase the Rolling Stones: we can’t always get everything we want in life, but we get what we need. My latest research has found this is a powerful principle in evolution as well. Trade-offs, which are evolutionary compromises, drive the diversity of life. Chester the Computational Cat helps illustrate these findings. Read the full press release.

This kind of knowledge will ultimately be important for preserving our current ecosystems.
— Chris Adami