rose.blog

I wonder if they have adiabatic versions?

I live near a community center in Vancouver where, early in the morning, a service is offered for free for homeless people-you can get a hot shower, free coffee, free breakfast.

So last Sunday I was out walking with my son around the community center and this guy who was coordinating the service comes up to me, real nice-like and tells me where the coffee is…he thought I was too embarrassed to ask where it was, assumed I was a homeless guy…

OK I can take a hint. I got a haircut the next day.

Anyway on that note here is some new and interesting hair science mulletpresentation3.pdf.

OK this is the only video I have ever seen that has Schrodinger’s equation featured… check it out, Al cold lamps with FLAVA on this track.

For those of you that don’t listen to The Beat 94.5 or equivalent the original was “Ridin Dirty” by Chamillionaire. The original song totally sucks, Chamillionaire is like the definition of a wac MC, which makes Al’s take even more funny.

Over the past few years we here at D-Wave have been busy turning blood, sweat, tears and cash into quantum computers. We tend to be tight-lipped about what we’re up to and rarely disclose anything directly related to what we’re building.

One strategy is to continue operating in this mode until we’ve built quantum computers that can solve problems obviously beyond the scope of any conventional computer, go on a road show and build a customer base. Now anyone who has been involved in technology commercialization should immediately realize that this approach has a basic flaw - we would be building the technology without having any input from end users. This is a very common and usually fatal mistake that a lot of techno-centered organizations make. There are several examples just from aborted attempts at commercializing superconducting gadgets. Products - yes, even quantum computers - are all about satisfying some customer need. Build in isolation from end users and usually you die.

Another strategy is to demonstrate versions of the machines we’ve built that are not yet competitive with conventional systems, but demonstrate all of the functionality of the larger scale machines we’re planning on building in the future.

This strategy has the advantage of announcing to potential users of the technology what the capability of the machines is expected to be, how to interact with them, how to program them, etc., with the objective of developing partnerships with eventual customers who will help guide the development of the hardware and applications that will run on it.

There is an unfortunate giant chasm between people who are potential users of this type of technology, and who would benefit alot from it, and the people who are building it (ie. us). This chasm needs to be bridged and I think the best way to do this is to announce what our machines do now.

Now we’ve been working on building real large-scale quantum computers for a long time, and have spend a lot of money. We’ve done things using “best practices”, using a full-time workforce made up of the best and brightest who share our common vision of building these things. We are considerably ahead of the “state of the art” as it’s known in the academic community that works in quantum computation.

Now let’s say we wanted to announce some capability in order to attract co-development partners that will help shape our products to be valuable for these partners. When we announce where we are, the reaction from the expert community is predictable: there will be a large amount of scepticism and disbelief.

“Where are the peer reviewed papers? Where is your proof of (fill in your favorite QC dogma requirement)?” Well heck if we told you everything about what we’re doing, that wouldn’t make much sense now, would it?

But on the other hand the scepticism is of course warranted. If I were working somewhere else on QC, I probably wouldn’t believe it either.

So what I’m going to do is release just enough technical information so that when we do begin to make our announcements, the experts among you should have enough to admit that, just possibly we may have done what we’ve claimed.

The first of these technical releases was the paper on one of the couplers we’ve built. This paper is here. We released this paper to demonstrate that we have the capability to produce world-best, quantum regime superconducting hardware.

The second of these papers, which I’m going to link to in this post in a bit (the first public release ever! Even prior to arxiv! See reading this blog does pay off!) describes the underlying model of quantum computation that our machines use.

See I really hate the gate model. For me, it’s personal, because we tried very hard to build a gate model QC. What I learned is that the gate model is very stupid from the practical standpoint, especially with superconducting systems. Not that I want to belabor the point, but you can actually demonstrate that the interaction of superconducting qubits with the intrinsic nuclear spins in any of the materials that superconducting electronics can actually be built out of (ie. niobium, possibly aluminum) creates errors above the amount required by the threshold theorem. It’s a simple calculation that completely rules out gate model quantum computers built using niobium or aluminum. Try it! Tell your friends!

Anyway once we realized that the gate model was out, we had to either (A) give up and get real jobs or (B) find a different model of computation. So we looked around and found this cool thing called adiabatic quantum computing, which seemed to have an intrinsic resistance to the types of noise found in real niobium electronics.

So we started building components and AQC circuits and fell in love with the model. We started building more and more advanced stuff and found out a huge amount of fascinating things that would make your head fall off if we disclosed it all.

One of the coolest things we found out is that noise actually helps AQC. Yes, you read that right. AQCs can be run in the presence of noise, without quantum error correction, and still provide optimal scaling.

This appears to fly in the face of conventional QC dogma re. decoherence times, threshold theorems etc. but actually it doesn’t. It is entirely consistent with all of the rest of the QC literature, although the details of why this is true are highly non-trivial.

The key finding that we’re disclosing now is that quantum error correction (and fault tolerance) can be achieved PASSIVELY instead of actively, which in practice is the difference between large scale quantum computers today and in 20+ years (or whatever your favorite misty future date is).

Anyway with that as a brief intro, I am pleased and honored to release, for the very first time, an introduction to the model of quantum computation underlying our processors. We’ve disclosed an analysis of the model as applied to the adiabatic Grover search problem, which is of course sort of artificial, but demonstrates the basic principle.

Here it is! Enjoy!

I’m a big college football fan, both US and Canadian versions. Of course I am a big fan of McMaster, my alma mater, which has been so close so many times but hasn’t won a national championship for several eons (OK guys you’re going to win it all this year, right?). In fact the last time Mac won a national championship in anything (note: baseball and tennis don’t count as they are not real sports) was when we won the wrestling title in 1994.

Anyway the Ohio State Buckeyes are currently ranked #1 in the US. My Interesting Fact is that Ohio State linebacker James Laurinaitis is the son of Legion of Doom/Road Warriors member Animal.

“Don’t even mention the gate model, or there’s gonna be a vintage Road Warrior beat down fool!!!!!”

A recent poll of more than 700 IEEE Fellows provides this amusing little nugget:

Seventy-eight percent of respondents doubt that a commercial quantum computer will reach the market in the next 50 years.

Unfortunately for these hallowed Fellows, commercial quantum computers already exist; you can buy a liquid state NMR machine from Bruker for about $1m a pop. A case of mass extralusionary intelligence?

In the vein of otherwise competent experts making stupid statements, let’s stroll down memory lane. It’s more fun if you say these out loud. With gravitas. Also some pompous posturing doesn’t hurt, and experimenting with accents is also fun.

“This ‘telephone’ has too many shortcomings to be seriously considered as a means of communication.” — Western Union internal memo, 1876.

This one I particularly like:

“Heavier-than-air flying machines are impossible.” — Lord Kelvin, president, Royal Society, 1895.

Uhhh…birds? Did they have those in 1895?

“Everything that can be invented has been invented.” — Charles H. Duell, Commissioner, U.S. Office of Patents, 1899

Note: Apparently this one isn’t real, at least according to Kevin Maney. (thanks to Tim for the link).

“I see no progress in this industry. These clocks are no faster than the ones they made a hundred years ago.” — Henry Ford, while visiting a museum.

Note: This one looks suspect also.

“I think there is a world market for maybe five computers.” — Thomas Watson, chairman of IBM, 1943.

“Where a calculator on the ENIAC is equipped with 18 000 vacuum tubes and weighs 30 tons, computers of the future may have only 1 000 vacuum tubes and perhaps weigh 1½ tons.” — Popular Mechanics, March 1949.

“I have traveled the length and breadth of this country and talked with the best people, and I can assure you that data processing is a fad that won’t last out the year.” — The editor in charge of business books for Prentice Hall, 1957.

“But what… is it good for ?” — An engineer at the Advanced Computing Systems Division of IBM, commenting on the microchip in 1968.

“There is no reason anyone would want a computer in their home.” — Ken Olson, president/founder of Digital Equipment Corp., 1977.

These seems to be a lot of confusion about how to make two superconducting qubits talk to each other, so I’m going to explain how one of the couplers we’ve developed works.

First a word about the qubits. This coupler is designed for flux qubits. Flux qubits are loops of metal, interrupted by one or more weak links (called Josephson junctions). The qubits are operated so that the bit state zero (0) corresponds to current circulating clockwise around the loop, and bit state one (1) corresponds to current circulating in the counterclockwise direction. The magnitude of these currents is about one microamp, and they are persistent currents - no dissipation.

The bit states (circulating currents) generate magnetic fields. Another way of thinking about the information that the qubits store is to think bit state zero = magnetic field pointing down through the loop, bit state one = magnetic field pointing up through the loop.

These magnetic fields are very useful “handles” we can use to interact with the qubits.

Here’s how the coupler works: Put two of these qubits down somewhere on the chip. Inductively couple both of these qubits to a third loop of metal (the coupler).

If the coupler has a Josephson junction (a weak link) in its loop, the effect it has on the induced coupling between the two qubits can be tuned from anti-ferromagnetic (qubits prefer to be aligned oppositely) through zero (no coupling) to ferromagnetic (qubits prefer to align in the same bit state).

Here is a schematic of two qubits plus a coupler:

For the experts: This system has the effective Hamiltonian

where we can slowly change the terms (on scales of microseconds) with a high degree of precision on the final target values.

The coupler allows us to tune the J term over some range [-J_max^0..0..+J_max^1].

So how is it able to do this? For a full description you can read this. The short version is that the magnetic susceptibility of the coupler loop as a function of magnetic flux applied through the loop changes sign, and the induced coupling between the qubits is proportional to the magnetic susceptibility of the coupler. Nice.

I’ve had a lot of interest from people wanting to learn more about D-Wave. Satisfy those informational urges! Join the company! Visit the widget bar!

Damn I love Slayer. I celebrated the International Day of Slayer. I saw them live 4 times in 2005. I have probably listened to Hallowed Point a million times.

Some people wonder why I like Slayer so much. Then I got to wondering the same thing myself, and while wondering this I started thinking about William Gibson’s microsofts (again).

Here is my theory: Slayer’s music acts just like a microsoft. It plugs directly into the part of your brain that takes over when you’re running from a sabertoothed tiger. It makes the hairs on the back of your neck stand up and your heart race. Three hundred thousand years of evolution peeled back by the Slayer microsoft.

This is why I think Slayer is so revered by so many. They have figured something out that no other musical act has - how to plug directly into the lizard brain.

Anyway they have a new CD out. I have only listened to it a few times but if you’re a Slayer fan you should definitely pick it up. A buddy of mine said it sounded like a Kerry King solo album, and it is a little more heavy on the lead guitar line than usual, but I still think it rocks. It is amazing that they can keep putting out quality material with their kind of aggression. Usually acts mellow with age but these guys are still killing it like they did 20 years ago.

The other day I was discussing the concept of downloading brains into silicon with Steve Jurvetson. (I’ve been thinking alot about this recently, which I blame in part on William Gibson).

Part of what got me thinking about this is that I get to spend a considerable amount of time hanging out with biotechnology & pharmaceutical researchers.

The paradigm for health research is to try to use science and technology to fix our bodies when something goes wrong. Here are some interesting facts:

1. The pharmaceutical industry spends a lot of money on what they call research (note that not everybody would agree with calling everything they spend this money on research but let’s ignore that). In 2005, the total spent on research was about $40 billion dollars (see page 15 here). Including the biotech industry ups this number to about $50 billion.

2. Projecting forward twenty years with no growth in spending (which is a very conservative assumption), gives roughly $1 trillion dollars of spending to 2026. I will be 54 in 2026. My eldest son will be 22.

3. The end result of this spending are mostly small molecule drugs, which we can ingest in pill form, that have some kind of effect on our health. There are also a small number of vaccines and medical devices that will also produced.

4. All of these products have as their intended objective one or both of: (1) alleviating symptoms of uncomfortable conditions (allergies, colds, flus, erectile dysfunctions, etc…) (2) curing specific disease conditions (cancers, viral diseases, AIDS, etc…).

OK so does anyone else see the basic fundamental flaw here… let’s say we manage to cure 50% of all of the life threatening ailments we have names for in the 20 years to 2026. That’s pretty good, but unfortunately one of the other 50% are still gonna getcha.

I think the whole idea of trying to extend life by fixing the things that go wrong with our bodies is totally quixotic. Let’s say I get skin cancer in 2026. By then there’s a marvelous cure, so it goes away, but eventually something is going to go wrong that we don’t have a cure for, and then it’s worm food time.

I guess I see the current approach to health kind of like tring to build a car that can drive to the moon. We keep building faster and faster cars and we call it progress, but it’s not really progress because the whole idea is doomed to failure from the outset.

OK so are there any other alternative ways we could go about the whole life extension / health business?

One way to try is to develop methods for “copying” all of the circuitry we use to interact with the world around us into a more robust substrate. Even though our brains & bodies are amazing marvels they have some obvious flaws (they have 100% failure if you wait long enough). If we could figure out how to copy all of these marvels into something that is equivalent in its information storage and processing capacity but didn’t have that annoying property of certain death, lots of people would want access to the process.

I think it’s naive to assume that we can’t figure out a way to do this eventually, which brings me around to the point of this post. So let’s say we do get there at some point. How do we get from there to here?

Obvious Fact #2 (see previous posts for #1): Doing research on “downloading” biological brains into other substrates (silicon probably, maybe with a bit of niobium ) won’t be begun by using human subjects. When this future technology is under development, it’s absolutely clear that the first “test subjects” will be things like nematodes: really simple nervous systems where we can look very carefully at everything that’s going on in the “transferrence”.

Now here’s the thing: Silicon computing machines have MUCH faster operating time scales than biological computing machines. Like a factor of a million or so. So every second to a bio brain is like (all other things being equal) a million seconds to a silico-brain. A million seconds is about 12 days. So every second that passes for the bio-brain is like 12 days for the silico-brain. A month for the bio-brain is like 83 millenia for the silico-brain!

Not only does the time scale change, but the silico-brain can be connected to other systems that can do stuff to it in ways that probably can’t be done to the bio-brain (think Gibson’s microsofts… learn Spanish by plugging it into a socket in your brain).

Back to the nematode: so you download the nematode’s brain into silicon. Can you teach it Spanish? Probably not, because it likely doesn’t have the necessary hardware to store and process information of the quantity and type required. So the “hardware” has some limit - at some point, we can make it do whatever it can do, but this might not be all that interesting.

After the nematode we could try some other downloads. At some point in this evolution we get to an experimental subject whose nervous system is close to ours, say a rat. Rats are used in early stage drug testing because they’re ugly and pharma people think of them as mini-humans (obscure reference warning: Dreams in the Witch-House).

So we download a rat’s brain. Now this brain might have the capacity to design a slightly better version of itself, given enough time. If it can, then that slightly improved version might be able to make at even better version, and so on, etc… this feedback loop could create an “entity” with a silico-brain whose powers of comprehension dwarf the original brain, and of course dwarf human bio-brains.

If this were to occur, then we would have (maybe inadvertently) created a new type of being, evolved from a mammalian brain at an enormously accelerated rate (being in silicon and all), that is not at all human, with massive thinking power, which would eventually find its way into cyberspace. A year after being downloaded is like a million years to the silico-rat; that’s a long time to evolve into something else.

Not sure exactly what this would mean, but we might start seeing What would the cosmically intelligent post-singularity rat god do? bumper stickers.