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Domenico Oricchio: "A new era in astronomy. I imagine dozens of observers to triangulate..." in LIGO to Make a...

Lorraine Ford: "Rob, you are not talking about REAL information, you are talking about..." in Measuring Consciousness...

Lorraine Ford: "That was me." in Measuring Consciousness...

Lorraine Ford: "Eckard, Re "I apologize for possibly hurting believers when I used the..." in How risky is too risky?...

Lorraine Ford: "I agree with Rob." in How risky is too risky?...

Zeeya Merali: "That's a good idea Steve. I've never thought about LinkedIn and FQXi, but..." in LIGO to Make a...

Nicholas I Hosein: "In the past couple months I've witnessed God a number of times. He is the..." in The Quantum Reality...

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The Quantum Reality Paradox
How the search for God’s limits led to the discovery of quantum contextuality—a weird phenomenon that could provide the 'magic' needed for super-fast computing.

Quantum Cybernetics
The quest for a meta-theory of quantum control that could one day explain physical systems, certain biological phenomena—and maybe even politics.

Video Article: Solar-System-Sized Experiment to Put Time to the Test
Is quantum theory or relativity right about the nature of time? Bouncing radar beams off the moons of Jupiter just might help sort things out.

Conjuring a Neutron Star from a Nanowire
Using tiny mechanical devices to create accelerations equivalent to 100 million times the Earth’s gravitational field—mimicking the arena of quantum gravity in the lab.

Inferring the Limits on Reality (that Even the Gods Must Obey)
The fuzziness of the quantum realm could arise from mathematical restrictions on what can ever be known.

February 12, 2016

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LIGO to Make a Gravitational Waves Announcement on Thursday 11 Feb 2016
By ZEEYA MERALI • Feb. 10, 2016 @ 16:18 GMT

Updated 4:15pm Feb 11: Congratulations to the LIGO collaboration for successfully detecting gravitational waves from the merger of two black holes. Follow @FQXi on Twitter for live updates.

I’m opening this thread as a place to watch and discuss Thursday’s big announcement from the LIGO collaboration about the hunt for gravitational waves from the merger of black holes. The press conference takes place at 3:30pm GMT, 4:30pm CET, 10:30am ET, 7:30am PT. You can watch the live stream here:

Sabine Hossenfelder has some nice background on gravitational waves over at Backreaction. At New Scientist, there’s a nice diagram using NASA’S WMAP image of the cosmic microwave background to attempt to located where a possible gravitational wave signal may have been found, accompanying an article by Joshua Sokol.

There are a host of other good articles out there—so feel free to link to any good ones that you find in the comments below.

See you tomorrow!

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RIP Edgar Mitchell
By WILLIAM OREM • Feb. 6, 2016 @ 21:28 GMT

Rest In Peace astronaut Edgar Mitchell, the sixth man to walk on the moon and the last member of the Apollo 14 mission. He was oddly credulous for a man of science, confusing the public with his proclamations that alien visitors interceded in the arms race, the Roswell incident was not a lot of tin foil and sticks but a downed saucer, and the like, on which I commented in a previous blog.

But we remember him this weekend for the uncommon bravery involved in his work as an aviator, test pilot, and NASA astronaut. Without sound data and dedicated skepticism (not cynicism), we are likely to believe any old thing. But without a passion for trying on new and even radical ideas, what we know will be surely chained by expectation.

Flaws notwithstanding, here was an explorer's mind.

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How risky is too risky? Evaluating the expected impact of high-risk/high-reward research
By ANTHONY AGUIRRE • Feb. 4, 2016 @ 17:51 GMT

Caltech, R. Hurt, IPAC
On Dec. 8, 2015, two different groups (sharing an author) posted papers to the arXiv announcing the possible detection of planet-sized objects in the far outer solar system (Vlemmings et al, arXiv:1512.02650v2 and Liseau et al, arXiv:1512.02652v2). There was a brief flutter on Twitter and in the media, which shortly died down. As far as I am aware, no large-scale effort has begun to confirm or refute these potential detections, and both papers have since been withdrawn, until further data is available.  

Six weeks later on January 20, a paper appeared in The Astronomical Journal adducing strong circumstantial evidence, based on solar system object orbits, for a large 9th planet in the outer solar system (K. Batygin and M. E. Brown, The Astronomical Journal Volume 151, Number 2). The media attention was staggering, and the paper downloaded 243,547 times of this writing. There are almost certainly numerous intense efforts underway to try to detect the object.

While it may be surprising to see much more attention (and resources) directed toward circumstantial evidence for a 9th planet than to direct potential observation of one, this is the sort of decision with which researchers — and research funders, and journalists — are confronted all the time.  

These decisions are, in essence, predictions about how things are going to unfold; this has gotten me interested in how to better solicit and aggregate expert predictions in science and technology, and helped motivate a new project I and several other physicists have been developing, called Metaculus.

To be more specific, there is an important class of decisions that can be posed in the form of "what is the expected return on my investment of time/effort/attention/funding in X?" For some science-based examples:

— "What is my expected return in using my time on telescope X to search for the planet suggested by this data?" Here the potential "return" is fame and satisfaction at discovering a planet.

— "What is my expected return in skimming/reading/studying this new paper?" Here the return might be insight gained, entry into a promising new research direction, etc. 

— "What is the expected return in funding this research grant?" Here, the return could be papers published, talks given, meetings run, or more abstractly intellectual impact on a field or set of questions.

— "What is the expected return on building this instrument?" The impact here would be scientific discovery, possibly measured by papers, citations, etc.

A central idea in these questions is that of expected return. Most simply, this could be the likelihood of success times the return if successful. Or, if there are multiple possible outcomes, it could be the sum/integral of the probability of each outcome times that outcome's impact. 

The idea of high expected return (per dollar) is part of FQXi's core philosophy (and grantmaking criteria). To make a financial analogy, government funding agencies tend to purchase the equivalent of a diverse-but-safe portfolio of bonds and index funds: decent returns, fairly safe. These agencies tend not to fund the science equivalents of startup companies — projects where the chance of major success is fairly low, but the impact if successful is very high. We believe that in the science, as in the corporate, world, both types of investment are very important, and one role of FQXi is trying to fill in this end of the research funding portfolio.  

Evaluating the "probability of success" is, though, rather difficult. It's  often not hard to assess which of two projects is more likely to be successful. For example, I would say the Wendelstein 7-X fusion experiment and subsequent efforts are more likely to lead to useful energy generation than Brillouin Energy's LENR experiments. But how much more likely? Ten times? A thousand? A million? The 7-X’s funding is probably about 1000 times higher, so which experiment has the higher per-dollar expected return on investment depends on this likelihood ratio! Or what about tabletop quantum gravity experiments versus a bigger version of the "holometer"? 

The idea of Metaculus is to generate quantitative and well-calibrated predictions of success probabilities, by soliciting and aggregating expert opinion, and by (in the process) helping people improve their skills at quantifying and predicting impact. Metaculus poses a series of questions, for example "Has a new boson been discovered at the LHC?", with relatively precise criteria for resolving the question after a specific time. Users are invited to predict likelihoods (1-99%) for these questions, and later awarded points for accuracy in their predictions. Studies show that by carefully combining the predictions of many users, better precision and calibration can be achieved.

My experience so far suggests to me that there are several ways a prediction platform like this, when applied to scientific research, can be complementary to traditional peer-review. The effort of creating precise criteria for 'success', and in trying to assign numbers to success likelihood, has a quite different feel than just reading to understand whether a paper/proposal is intellectually sound or correct. It also makes me realize that in all of the peer review and assessment that I have done, I've never been asked (or asked someone) to supply a number like "what is the probability that X will be the result of funding/publishing Y?"  Since that's a significant part of what peer review is, isn't that a bit odd?

Perhaps there is an opportunity for real improvement here. A recent study made the case that prediction 'markets' are quite effective — and more effective than surveys even of experts — in forecasting whether given research (in this case in psychology) would be successfully reproduced (PNAS, Vol 112, no. 50).

I'm very interested in everyone's ideas for how something like Metaculus could be used in trying to make the biggest impact we can out of the limited resource society throws in the direction of us scientists — please comment!
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Measuring Consciousness in the Lab
By MAX TEGMARK • Jan. 14, 2016 @ 15:47 GMT

If you're driving, you're having a subjective experience of colors, sounds and vibrations. But does a self-driving car have a subjective experience? Does it feel like anything at all to be a self-driving car, or is it a zombie in the sense of having behaviour without experience? This question of why and when matter is conscious is the essence of what philosopher David Chalmers has coined "the hard problem" of consciousness, and it's important not only in philosophy. For example, if you're an emergency room doctor, how can you determine whether an unresponsive patient is conscious or not in the sense of having a subjective experience? Patients with locked-in syndrome have functioning minds without being able to move or communicate. And what about a future robot intelligent enough to converse like a human? 

A traditional answer to this problem is dualism — that living entities differ from inanimate ones because they contain some non-physical element such as an "anima" or "soul". Support for dualism among scientists has gradually dwindled. To understand why, consider that your body is made of about 10^29 quarks and electrons, which as far as we can tell move according to simple physical laws. Imagine a future technology able to track all your particles: if they were found to obey the laws of physics exactly, then your purported soul is having no effect on your particles, so your conscious mind and its ability to control your movements would have nothing to do with a soul. If your particles were instead found not to obey the known laws of physics because they were being pushed around by your soul, then we could treat the soul as just another physical entity able to exert forces on particles, and study what physical laws it obeys.

Let us therefore explore the other option, known as physicalism: that consciousness is a process that can occur in certain physical systems. Instead of starting with the hard problem, we can then start with the hard fact that some quark blobs are conscious and others aren't, which leads to the fascinating question of what makes the difference. I've long contended that consciousness is the way information feels when being processed in certain complex ways, but what types of information processing quality? Specifically, what mathematical equation must an information processing system satisfy to be conscious? Answering this question might allow future ER-physicians to have a consciousness detector, and would let future programmers control whether they built consciousness into their artificial intelligence systems. 

Neuroscientist Giulio Tononi has proposed just such an equation, which forms the core of his Integrated Information Theory of consciousness (IIT). It says that information being processed is conscious if a mathematical quantity called "Phi". Phi quantifies integration,  the extent to which information is interconnected into a unified whole rather than split into disconnected parts. The theory has generated interest from the neuroscience community, but also controversy, including recent critique from FQXi member Scott Aaronson.

I want to see the question of whether IIT is correct or not resolved by experimental tests. Unfortunately, Tononi’s proposed measure of integration is too slow to compute in practice from state-of-the-art patient data, requiring longer than the age of our universe, let alone the lifetime of the patient. I’ve therefore worked hard over the last year in search of a faster way to compute integration, and I’m happy report that I’ve found one--in fact, several. In a paper I just posted, I explored and classify existing and novel integration measures by various desirable properties, and found that although there at first seem to be a few hundred options, there are in fact only a handful of attractive ones (arXiv:1601.02626). I was happy to discover that there's an approximation based on graph theory that lets you dramatically speed up the exact formulas, so that they can be applied to real-world data from laboratory experiments without posing unreasonable computational demands. This improves the prospects of making fascinating questions and theories about consciousness experimentally testable.
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2015 in Review: New Podcast on Planets, Particles and Perceptions of Reality
By ZEEYA MERALI • Dec. 28, 2015 @ 15:14 GMT

We’re taking our annual look back at the physics highlights of the past 12 months — as chosen by FQXi member Ian Durham, a quantum physicist at Saint Anselm College in New Hampshire. Ian will be counting down his top 5 picks in a special podcast series.

Free Podcast

Our review of the year in physics, with quantum physicist Ian Durham, begins.


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Here’s part 1, in which Ian talks about what didn’t quite make his list this year (and why), and reveals the physics breakthrough takes the 5th spot in his countdown.

The rest of Ian’s list will follow over the next few days. But how would you rank this year’s physics achievements? What makes the top of your list?

And, of course, from all of us at FQXi: Best wishes for the coming New Year!

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Our countdown of the biggest physics breakthroughs of 2015 continues, with Ian Durham.


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Updated on 29 December 2015 to say: Part 2 has now been added, revealing pick 4 and 3.

Updated on 30 December 2015 to say that I've tweaked the second podcast since first posting it yesterday. We had a slight mistake in the first version. I'll avoid telling you what it was because if I do, it will spoil you on what's on the list. Corrected now though.

Updated on 31 December 2015 to say that the third and final part of Ian's list is now up.
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