Friday, 20 October 2017

U of A Lecture on Quantum Computing (D-Wave Systems)



U of A Lecture on Quantum Computing (D-Wave Systems)

The Speaker

We went to a lecture the other week (September 28, 2017) about developments in quantum computing, put on by the University of Alberta, for the Physics and Research Symposium and Public Outreach program.  The lecture was given by Dr. Emile Hoskinson, an experimental physicist at D-Wave Systems (located in Burnaby, British Columbia, near Vancouver), and thus focussed on that corporation’s “spin” (no quantum mechanics pun intended) on quantum computing.  Dr. Hoskinson did his undergrad at UBC, and his PhD at Berkeley. He went to high school just down way from the U of A, though, at Archbishop MacDonald High School, so he had a local connection.

He described his job as “to design, process, test, calibrate, and run experiments to evaluate performance of the D-Wave supercomputers”.  He also described his workplace as “one of the coolest places there is”, a riff on the fact that quantum computing is just plain cool, in the vernacular sense of the term, and that the process itself operates at near absolute zero, for reasons described below.

I should note that the talk was pitched at a general audience, so he intended it to be understandable, yet not dumbed down.  I think he succeeded in that objective, and I sensed that the audience would agree with that.  He also did a physics colloquium during his visit – presumably that was a more technical presentation.

I should also note that the public talk didn’t go into quantum theory in any depth – quantum tunnelling and superpositions were the main aspects of quantum theory that were touched upon.  So, it no doubt helped to have had some acquaintance with quantum theory, to get a better handle on the talk.  I have some background – basically lots of reading, and what mathematical/technical understanding that an undergrad in physics will confer.  But, obviously, to understand the technology at a deeper level would require a significant immersion in the subject.  The D-Wave site has plenty of description and documentation that the interested reader can peruse.

Quantum Computing Progress


There are several approaches to using quantum phenomena for computing, and D-Wave specializes in one particular approach, but more about that a bit further on.  It should be noted that the D-Wave approach has both academic and commercial aspects.  On the commercial side, buyers have included such outfits as NASA, Google and Lockheed Martin, and some 150 patents have been filed.  On the academic side, there have been some 90 peer reviewed papers written, relating to the technology. 

D-Wave One, their first commercial quantum computer was released in 2010; it had 128 Qbits of quantum processing capacity.  D-Wave 200Q is the most recent release, in 2017; it has 2000 Qbits of capacity.  The capacity of these computers has followed “Moore’s Law” like trajectory, with the number of Qbits increasing from 4 in 2004 (early research) to about 10,000 in 2018 (20,000 is possible in the next release).

Here’s my graph of that, from some things said during the talk (note that it is not official by any means, and I only have 4 data points).  I make the doubling time to be about 1.25 years.

I should note that a Qbit is something like a “bit” in regular computing.  However, where a regular bit can be in two states (and thus naturally leads to binary Boolean logic), a Qbit can exist in State 0 (off), State 1 (on) or a superposition of the two.  You can now meditate upon Schrodinger’s Cat, to consider the ramifications of such a device.  Plus, think a bit about quantum tunnelling.  As will be explained a bit later (to the extent it can be explained),  quantum tunnelling is probably the key phenomenon that D-Wave’s make use of.





The Quantum Computer

So, what is a quantum computer, as operationalized by D-Wave?  Visually, as he demonstrated in his presentation, it looks pretty much like a big black box. 

The Black Box


The black box has two main purposes:

  • It acts as a Faraday Cage, keeping stray electromagnetic signals away from the quantum chip, which does the quantum part of quantum computing.  Stray signals can interfere with the delicate process of maintaining quantum superpositions, which, of course, is the key to a quantum computer’s advantage over regular computing.

  • It contains the hardware necessary to produce the low temperatures at which the quantum chip operates.  Again, this has to do with maintaining a quantum superposition state for useful lengths of time – thermal agitation at the molecular level (i.e. heat) will also interfere with this.

  • The operating temperatures for the quantum chip are about 15 milli-Kelvins, or about 15 thousands of a Celsius degree above absolute zero.

  • The computer’s temperature is lowered via multiple stages, with each stage dropping the temperature more and more.   The final stage contains the quantum chip.


Fridge Wiring



The quantum chip looks pretty normal, somewhat like a GPU processer used in graphics applications.  It actually is based on small, but still macroscopic devices which create superconducting current loops.  Thus, the need for near absolute zero temperatures.  The current can flow in either of the two directions around the loop, creating a digital one or zero.  But it can also quantum tunnel between these states, which is the key to quantum computing, of course.  The direction and amplitude of the current in these loops is altered by applying a magnetic bias to the loop.  In this respect it sounded to me somewhat like “core” memory in the old mainframes of the past era, but with a superconducting quantum twist to it.

Quantum Chip



Note that the computer also has a conventional front end, as well as the quantum chip back end.  The quantum computer, as realized with this technology is only productive for certain types of problems, that it is optimized for.  These tend to be algorithms that don’t scale up to huge sizes well.

 

Quantum Computer Applications


An example given was essentially as sort of permutation problem, which has a huge search space as it is scaled up.  Finding the most efficient solution to a logistical problem or a consumer preference optimization might come to mind – problems in finding correlations in genetics were another example mentioned.

Suppose one was searching for an optimal solution to such a permutation problem.  Normally, finding the global minimum in such a search space would soon get out of hand, as the problem would grow exponentially as it is scaled up.

But, with clever design of the quantum chip, the chip can be made in such a way that it mimics the physical or conceptual problem.   The chip can then quantum tunnel to get out of a local minimum, which can be a huge problem in conventional computing, requiring computing time and resources that are not practical (it sounds like a gradient descent problem, a key aspect of many AI algorithms).  However, the quantum chip will evolve to a ground state solution, via quantum mechanics.  If the chip has been designed to mimic the physical problem, this can give the solution to the problem.



Note that this can involve a lot of custom design of the chip, to fit the specified problem.  Obviously, not all interesting and useful problems in computing can be solved via this technology.  More general purpose quantum computers are being explored, though they are still in the early stages.

In some ways, the D-Wave quantum computer reminded me of analogue computers, in the sense that the hardware is built to mimic a physical problem of interest.  In the past, if I recall correctly, this was a method for solving differential equations.  Basically, one designed a circuit that corresponded to a particular differential equation, and solved the equation via analysis of the corresponding circuit’s behaviour.

 

Richard Feynman on Quantum Computing


Dr. Hoskinson noted that Richard Feynman once said about the possibilities of quantum computing: 
And I'm not happy with all the analyses that go with just the classical theory, because nature isn't classical, dammit, and if you want to make a simulation of nature, you'd better make it quantum mechanical, and by golly it's a wonderful problem, because it doesn't look so easy.
International Journal of Theoretical Physics, VoL 21, Nos. 6/7, 1982 Simulating Physics with Computers Richard P. Feynman

This is pretty mind bending stuff, so I would also add that he once quoted as saying: 
 "If you think you understand quantum mechanics, you don't understand quantum mechanics."

I think many of us can agree with him on that point, and that goes double for understanding quantum computers.  Nonetheless, the lecture was very informative, entertaining and engaging.

Sources:



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Now that you have read of some cutting edge science, you should consider reading some Science Fiction.  How about a short story, set in the Arctic, with some alien and/or paranormal aspects.  Only 99 cents on Amazon.

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“A geophysical crew went into the Canadian north. There were some regrettable accidents among a few ex-military who had become geophysical contractors after their service in the forces. A young man and young woman went temporarily mad from the stress of seeing that. They imagined things, terrible things. But both are known to have vivid imaginations; we have childhood records to verify that. It was all very sad. That’s the official story.”



Tuesday, 10 October 2017

Cassiopeia Photographed with an iPhone 7 – October 2017



Cassiopeia with iPhone 7 – October 2017


I took a few photos of the main asterism in the constellation Cassiopeia, on a recent very clear October morning, with my iPhone 7 camera.  The early fall can be a great time for very clear skies around my area, even in a fairly large light polluted city.

Here’s the result, with a little labelling and photo enhancement in GIMP.

2017 iPhone 7 photo. 



The upper photo has had the brightness and contrast pushed in GIMP.  That gives the sky a somewhat mottled appearance.  The thing on the left of the picture is a tree.  The lower picture uses the GIMP brightness threshold filter, to only show pixels above of a certain brightness level.  This effectively isolates the main stars of the “W”.

Here’s an inverted picture of the second image.





You can see how the iPhone picked up pretty well all of the stars of the “W” of Cassiopeia.

Note that the stars are somewhat blurred, though not by very much.  Since the iPhone 7 was hand-held, there was naturally some blurring.

Below is a photo that was “pushed” even further in GIMP.  This has picked up some of the less prominent stars in the constellation.   I have labelled those stars in yellow and have given their magnitudes (lower magnitudes are brighter).  I also included a map of Cassiopeia (from Wiki, but originally from Sky and Telescope) and oriented the photo to be similar to the map, so that the two can be more easily compared.

As you can see, the iPhone photograph captured a number of the “non-W” stars in Cassiopeia, which are labelled in yellow.  Interestingly, it seems to have picked up the fact that Sigma Cass is an optical double, even though one of the companions is actually rather dim, listed at 7th magnitude.  Of course, there is some scope for mis-identification.



When you take a photograph of the sky with the iPhone, your first reaction will probably be that there isn’t much there.  It helps to take the picture when the seeing is exceptionally good, if course. As noted earlier, the autumn months are often the best time of year for this, as the atmosphere is relatively dry and clear (vegetation is not very biologically active, so the air is dry).
After taking the picture, you have to push the image in an imaging processing program, like GIMP or even the iPhone’s own photo editing app.  Turn the brightness way up, the raise the contrast slowly as well.  The stars will come out, like magic, though you will want to experiment with settings, to get the best effect.  Some of the other features of GIMP (like the threshold filter, or the sparkle filter) can also help bring things out, or eliminate background clutter.
I will use Wiki’s article, to give a brief overview of Cassiopeia:

  • The most recognizable part of it is the W asterism.
  • Since it is a circumpolar constellation (always above the horizon in northern regions), and not far from Polaris (the north star), it actually rotates around the north star, so sometimes the W is upside down.
  • It is easy to find, as long as you can find the Big Dipper.  Just look along a line from the dipper pointer stars to Polaris, then about the same distance across the sky, until you see the W shape of Cassiopeia.
  • The five stars in the W are all bright, and three of them are variable (their brightness changes over time):
  • o   Alpha Cass is magnitude 2.2, and about 230 light years (l.y.) from Earth.
  • o   Beta Cass is magnitude 2.3 and about 55 l.y. from Earth.
  • o   Gamma Cass is magnitude 3.1 to 1.6, as it is a highly variable star.  It’s about 550 l.y. from Earth.
  • o   Delta Cass is magnitude 2.7 and about 99 l.y. from Earth.
  • o   Epsilon Cass is magnitude 3.3 and about 410 l.y. from Earth.
  • As for the dimmer stars that the iPhone captured:
  • o   Kappa Cass is magnitude 4.2 and about 4000 l.y. from Earth.  As you might imagine, being visible from that distance, it is huge and extremely bright.
  • o   Eta Cass is about magnitude 3.5 and about 20 l.y. from Earth.  It is very similar to the sun.  In fact, if you could see the sun from Eta Cass, it would look like Eta Cass looks like from Earth.
  • o   Theta Cass is about magnitude 4.3 and some 135 l.y. from Earth.
  • o   Zeta Cass is about magnitude 3.7 and 590 l.y. from Earth.
  • o   Sigma Cass is a binary, 5000 l.y. from Earth and magnitude 4.9.
 
  • Cassiopeia has a number of deep sky objects, nebulae, open clusters and galaxies.  A favorite is NGC457, the E.T. cluster, which does look rather like a friendly alien beckoning to one, from across the cosmos.
  • Cassiopeia is useful for locating the Andromeda galaxy, via a line drawn from Alpha Cass, in a direction moving away from Beta and Gamma.

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Now that you have read some real science (astronomy and astrophysics), you should read some science fiction.

Kati of Terra

How about trying Kati of Terra, the 3-novel story of a feisty young Earth woman, escaping from criminal aliens, and bringing them to justice, with the help of an alien police agent and a curmudgeonly, somewhat criminally inclined but brilliant brain implant.




The Witches’ Stones

Or, you might prefer, the trilogy of the Witches’ Stones, which follows the cold war intrigue and adventure of a future democratic Earth confederation, an opposing dictatorial galactic power, and the Witches of Kordea, a third power which doesn't trust either side (they’re psychic aliens, not actual witches).