Slashdot Mirror

They will not run Shor's algorithm and crack encryption but the class of problems they can tackle is still has very real world applications.

In fact, the factoring problem has a particularly nice algorithm in the adiabatic regime. It's just a multiplication circuit, where you clamp the outputs and "run it backwards" to deduce the inputs. It's not Shor's algorithm, but D-Wave is way ahead of the (gate-model quantum) competition in terms of factoring.

And the device has been shown to demonstrate some qualities in simulating quantum materials https://www.dwavesys.com/sites...

There are some solvers that make use of the D-Wave's limited connectivity (which will improve in the near future) like the HFS solver. These will become less effective as the connectivity improves

Overall, there may be a chance there isn't any single problem that a properly designe algorithm couldn't solve in an equivalent time with decently fast hardware.

And the device has been shown to demonstrate some qualities in simulating quantum materials https://www.dwavesys.com/sites...

There are some solvers that make use of the D-Wave's limited connectivity (which will improve in the near future) like the HFS solver. These will become less effective as the connectivity improves

Overall, there may be a chance there isn't any single problem that a properly designe algorithm couldn't solve in an equivalent time with decently fast hardware.

https://cloud.dwavesys.com/lea... - it's not BS, I've clicked through a lot of it. I can't say I understand it but it's given me an API token and I can run their "ping" command which apparently executes... something.

Wish I hadn't failed math!

Canadian-owned and operated D-Wave computer has way more that 50 Q-bits with a 1000Q model available and a 2K in the works.

My question is, if qubit gates have just been discovered, what the heck has D-Wave Systems been selling to Google and NASA in the past 2 years?

Non-silicon based systems.

and, significantly, did it in silicon

This is really the only new thing that has happened. Which is significant, but it seems a significant portion of ./ users don't remember the story from june when we have seen over 1000 qbits demonstrated

The folks at DWave would probably say no:

http://www.dwavesys.com/

They've been working on it for a while. :)

not sure how easily verified these would be, but this page gives a list of things they claim it's a better fit than conventional methods.

D-Wave's publication list is here.

Patents can be found just as easily.

After reviewing the documents please let me know what you feel is missing and should be disclosed.

How are they even programming this thing?

Simple, they use the Python library.

No joke, you use use statements like:

blackbox_answer = blackbox_solver.solve(obj, num_vars, cluster_num = 10, \
min_iter_inner = blackbox_parameter, max_iter_outer= blackbox_parameter, \
unchanged_threshold=blackbox_parameter, max_unchanged_objective_outer=blackbox_parameter, \
max_unchanged_objective_inner = blackbox_parameter, \
unchanged_best_threshold = blackbox_parameter, verbose=0)

As Megol said though it only works for certain problems. Their Python class is really called "BlackBoxSolver."

One of the earlier papers that supported their claim of actual quantum annealing is linked and discussed at this blog post.

D-Wave's publication list is too long at this point in order to give a synopsis here, but there are many blogs that follow this story, so it really isn't that hard to get a more up-to-date picture.

Maybe you should spend some more time on the D-Wave site and actually read it?

On the page you link to under the "What you will learn" section:

How to use the D-Wave OneTM System as a co-processor to a conventional computer in a scalable way.

The D-Wave chip is a special purpose solver, it relies on a classical processor for loading and pre-processing, that is where this python code gets executed.

Anyhow, if you want to learn what's on the chip check out this section.

Programming the D-Wave chip is nothing but initialising the spin states of the qubits, it has nothing to do with classical transistor logic. And no, it is not alien technology, although apparently pretty foreign to you.

Yet, you write like somebody who already made up his mind, and I doubt you're willing to learn anything that contradicts your preconceived notion.

Well then they duped them more than once and also duped Phys. Rev. A and B. Phys. Rev. Lett.

http://www.dwavesys.com/en/publications.html

Sorry pal, but you may as well subscribe to creationism. They have an adiabatic chip, the only open question is how good it is.

Indeed. The object you import is even called BlackBoxSolver.

Python.

http://www.dwavesys.com/en/dev-tutorial-getting-started.html

Ok, try programming anything that runs on binary, trinary, analog, quantum, and biological computers. It's virtually impossible.

D-Wave Systems

They are not strictly a quantum computer even though they market it as such, but they are one of a handful of companies in the world who seem to challenge this article's assertion that it won't be commercially viable.

Anyone know what Lockheed's plans are for this system? Complex fluid dynamics? Something else?

The press release only says ".. applied to some of Lockheed Martin's most challenging computation problems."

-molo

Or a few seconds if you believe D-Wave. (Don't believe D-wave, it's a well-funded scam.)

"First Electronic Quantum Processor Created".. Sorry to spoil the fun, but does anyone do facts checking with these articles before posting? Guess not, because these guys presented a 28 qbit prototype and working quantum processor back in 07.

I donate my idle processing power to the aqua@home project ( http://aqua.dwavesys.com/ ). They (d-wave) are building quantum computers and that's a field I'm more familiar with than medicine. Guess both are more sensible than looking for E.T. though. (Just my personal opinion.)

Since I was asked a couple times, here are my references.

Brown, Julian - "Minds, Machines, and the Multivers: The Quest for the Quantum Computer"

Williams, Colin P. and Clearwater Scott H. - "Explorations in Quantum Computing"

Simon Singh, - "The Code Book"

I also have a computational physics degree and would reference the text books if I currently had access to them (so yes, I'm also referencing my ass that sat through 4 years of physics classes).

There's also the obligatory wiki references.
Quantum Cryptography
Quantum Computer

Quantum cryptography does not use cubits. The photon used to exchange keys are specifically polarized. They are not in a superposition of polarizations. The "quantum" part comes in because, when a polarized photon hits a polarization screen that is at a 45 degree angle to the photon's polarization, there is exactly a 50% chance that the photon will go through due to quantum mechanics.

It is possible to use a photon as a qubit but it is very limiting. You have to have qubits that will interact with eachother. That is difficult with photons. You also have to have some way of storing them. A photon is very difficult to trap.

Some other methods of qubits are Heteropolymer (plastic), Ion Trap, Cavity QED and NMR.

Heteropolymer uses a laser pulse at specific energies to excite the outer electrons in plastic atoms to either an excited state or superposition of excited and ground states. We have these. The problem again is getting them to interact as needed.

Ion Traps use electromagnetic fields to trap a single ionized atom. The ions can in a grounded state or excited state. Ion trap qubits provide a method for interaction but they can only interact with their neighboring qubit. This method has been used to create an 8 qubit quantum computer.

Cavity QED (Quantum Electrodynamics) uses the polarization of photons for the qubits. We've got an XOR gate for this, but, as stated before, it's hard to store a photon.

NMR (Nuclear Magnetic Resonance) uses a sample of some liquid. Each atom in the liquid ends up being a qubit by using the spin of nucleus of one of the atoms in the molecules. It uses current technology (similar to MRI) and just about any liquid can be used. However, it's not an isolated system so it decoheres extremely fast (it naturally exits it's state of superposition).

According to D-wave systems (a company that sells quantum computers), superconductors can also be used for qubits. Using supercooled aluminum and niobium to cause the electrons to form Cooper pairs (bosons) which can be used as qubits. I don't know a lot about that method but you can read about it at D-wave QC hardware and Wiki: Superconducting QC

Heisenberg was driving down the road and got pulled over. The cop asks him, "Do you have any idea how fast you were going?" Heisenberg replies, "No, but I know exactly where I am!"

Since I was asked a couple times, here are my references.

Brown, Julian - "Minds, Machines, and the Multivers: The Quest for the Quantum Computer"

Williams, Colin P. and Clearwater Scott H. - "Explorations in Quantum Computing"

Simon Singh, - "The Code Book"

I also have a computational physics degree and would reference the text books if I currently had access to them (so yes, I'm also referencing my ass that sat through 4 years of physics classes).

There's also the obligatory wiki references.
Quantum Cryptography
Quantum Computer

Quantum cryptography does not use cubits. The photon used to exchange keys are specifically polarized. They are not in a superposition of polarizations. The "quantum" part comes in because, when a polarized photon hits a polarization screen that is at a 45 degree angle to the photon's polarization, there is exactly a 50% chance that the photon will go through due to quantum mechanics.

It is possible to use a photon as a qubit but it is very limiting. You have to have qubits that will interact with eachother. That is difficult with photons. You also have to have some way of storing them. A photon is very difficult to trap.

Some other methods of qubits are Heteropolymer (plastic), Ion Trap, Cavity QED and NMR.

Heteropolymer uses a laser pulse at specific energies to excite the outer electrons in plastic atoms to either an excited state or superposition of excited and ground states. We have these. The problem again is getting them to interact as needed.

Ion Traps use electromagnetic fields to trap a single ionized atom. The ions can in a grounded state or excited state. Ion trap qubits provide a method for interaction but they can only interact with their neighboring qubit. This method has been used to create an 8 qubit quantum computer.

Cavity QED (Quantum Electrodynamics) uses the polarization of photons for the qubits. We've got an XOR gate for this, but, as stated before, it's hard to store a photon.

NMR (Nuclear Magnetic Resonance) uses a sample of some liquid. Each atom in the liquid ends up being a qubit by using the spin of nucleus of one of the atoms in the molecules. It uses current technology (similar to MRI) and just about any liquid can be used. However, it's not an isolated system so it decoheres extremely fast (it naturally exits it's state of superposition).

According to D-wave systems (a company that sells quantum computers), superconductors can also be used for qubits. Using supercooled aluminum and niobium to cause the electrons to form Cooper pairs (bosons) which can be used as qubits. I don't know a lot about that method but you can read about it at D-wave QC hardware and Wiki: Superconducting QC

Heisenberg was driving down the road and got pulled over. The cop asks him, "Do you have any idea how fast you were going?" Heisenberg replies, "No, but I know exactly where I am!"

Quantum computers can be used to get approximate solutions to large NP-complete optimization problems much more quickly than the best known methods running on any supercomputer.

This dramatic advantage of quantum computers is currently known to exist for only those three problems: factoring, discrete logarithm, and quantum physics simulations. However, there is no proof that the advantage is real: an equally fast classical algorithm may still be discovered (though some consider this unlikely). There is one other problem where quantum computers have a smaller, though significant (quadratic) advantage. It is quantum database search, and can be solved by Grover's algorithm. In this case the advantage is provable. This establishes beyond doubt that (ideal) quantum computers are superior to classical computers.

BQP is suspected to be disjoint from NP-complete and a strict superset of P, but that is not known. Both integer factorization and discrete log are in BQP. Both of these problems are NP problems suspected to be outside BPP, and hence outside P. Both are suspected to not be NP-complete. There is a common misconception that quantum computers can solve NP-complete problems in polynomial time. That is not known to be true, and is generally suspected to be false.

I read the article, but it didn't make it very clear - what will be the advantages of paid use of their quantum computer? Unless it's going to be faster than other supercomputers, I can't see the point. Is there some other advantage I'm not aware of?

Yes, of course the goal is to be substantially faster than other supercomputers: for certain classes of problems. These are outlined on the company's website ( http://www.dwavesys.com/optimization.php ) and ( http://www.dwavesys.com/quantumcomputing.php ). But if you want a "Neutral Point of View" , I'll quote wikipedia:

It is widely believed that if large-scale quantum computers can be built, they will be able to solve certain problems faster than any classical computer...

Integer factorization is believed to be computationally infeasible with an ordinary computer for large numbers that are the product of two prime numbers of roughly equal size (e.g., products of two 300-digit primes). By comparison, a quantum computer could solve this problem relatively easily. If a number has n bits (is n digits long when written in the binary numeral system), then a quantum computer with just over 2n qubits can use Shor's algorithm to find its factors. It can also solve a related problem called the discrete logarithm problem. This ability would allow a quantum computer to "break" many of the cryptographic systems in use today, in the sense that there would be a relatively fast (polynomial time in n) algorithm for solving the problem....

This dramatic advantage of quantum computers is currently known to exist for only those three problems: factoring, discrete logarithm, and quantum physics simulations. However, there is no proof that the advantage is real: an equally fast classical algorithm may still be discovered (though some consider this unlikely). There is one other problem where quantum computers have a smaller, though significant (quadratic) advantage. It is quantum database search, and can be solved by Grover's algorithm. In this case the advantage is provable. This establishes beyond doubt that (ideal) quantum computers are superior to classical computers.

From D-Wave's website:

For several decades, computer scientists have been trying to classify all of the problems we know of. Whenever a new problem comes up, it is placed in one of the existing categories of problems. These categories describe how difficult the problems within it are, and why.

One of the most interesting categories contains problems that are called NP-complete. These all have the feature that in order to solve the problem all possible solutions must be tried, and the number of possible solutions grows exponentially with the problem size.

An example is the Travelling Salesman Problem, although there are literally thousands of them. This category is a particularly interesting target from a commercial perspective because most real-life business problems are in it.

...

Quantum computers can be used to get approximate solutions to large NP-complete optimization problems much more quickly than the best known methods running on any supercomputer.

I read the article, but it didn't make it very clear - what will be the advantages of paid use of their quantum computer? Unless it's going to be faster than other supercomputers, I can't see the point. Is there some other advantage I'm not aware of?

Yes, of course the goal is to be substantially faster than other supercomputers: for certain classes of problems. These are outlined on the company's website ( http://www.dwavesys.com/optimization.php ) and ( http://www.dwavesys.com/quantumcomputing.php ). But if you want a "Neutral Point of View" , I'll quote wikipedia:

It is widely believed that if large-scale quantum computers can be built, they will be able to solve certain problems faster than any classical computer...

Integer factorization is believed to be computationally infeasible with an ordinary computer for large numbers that are the product of two prime numbers of roughly equal size (e.g., products of two 300-digit primes). By comparison, a quantum computer could solve this problem relatively easily. If a number has n bits (is n digits long when written in the binary numeral system), then a quantum computer with just over 2n qubits can use Shor's algorithm to find its factors. It can also solve a related problem called the discrete logarithm problem. This ability would allow a quantum computer to "break" many of the cryptographic systems in use today, in the sense that there would be a relatively fast (polynomial time in n) algorithm for solving the problem....

This dramatic advantage of quantum computers is currently known to exist for only those three problems: factoring, discrete logarithm, and quantum physics simulations. However, there is no proof that the advantage is real: an equally fast classical algorithm may still be discovered (though some consider this unlikely). There is one other problem where quantum computers have a smaller, though significant (quadratic) advantage. It is quantum database search, and can be solved by Grover's algorithm. In this case the advantage is provable. This establishes beyond doubt that (ideal) quantum computers are superior to classical computers.

From D-Wave's website:

For several decades, computer scientists have been trying to classify all of the problems we know of. Whenever a new problem comes up, it is placed in one of the existing categories of problems. These categories describe how difficult the problems within it are, and why.

One of the most interesting categories contains problems that are called NP-complete. These all have the feature that in order to solve the problem all possible solutions must be tried, and the number of possible solutions grows exponentially with the problem size.

An example is the Travelling Salesman Problem, although there are literally thousands of them. This category is a particularly interesting target from a commercial perspective because most real-life business problems are in it.

...

Quantum computers can be used to get approximate solutions to large NP-complete optimization problems much more quickly than the best known methods running on any supercomputer.

... What have I missed here?

For starters; a link to the company's website instead of somebody's "See Spot run" blog post:

http://www.dwavesys.com/quantumcomputing.php

KFG

A quick search on Google would suggests that there is increasing interest in this field. How aboutIBM , as well as a start up company called D-Wave Systems located in Vancouver, for a start.

As for my two cents, don't bet on an up-and-comer quantum-computer-making-business "knock them [the processor giants] them of their perch". The article (in addition to previous stories) doesn't predict a quantum computer that you'll be able to buy off the shelf and use on your desktop. Perhaps a look at the current prospects for implementations of quantum computers, and a miniscule amount of common sense would convince you of this unliklihood.

Application 1: Optimization

http://www.dwavesys.com/optimization.php

Quantum computers can be used to get approximate solutions to large NP-complete optimization problems much more quickly than the best known methods running on any supercomputer.

Application 2: Quantum Simulation

http://www.dwavesys.com/quantumsimulation.php

Simulation has always been an important part of what conventional computers do. For engineers and scientists, simulation is about asking "what if?" questions without having to actually do it. Today's engineering marvels would not be possible were it not for computer modeling. Everything from the car you drive, to the plane you last flew in, to the building in which you sit, to the computer chip in your PC, are made possible by simulation.

There is an implicit assumption that the tactics used in engineering today will apply to engineering at the nanoscale. The promise of nanotechnology is based on the premise that since everything is built of atoms, if we can manipulate matter on the level of atoms, we can build anything that is physically possible.

Building, however, is only a part of engineering. Just being able to build any given assembly of atoms does not mean that we can predict how it behaves before we build it.

Unfortunately, conventional (non-quantum) computers, no matter how powerful, are very bad at predicting the behaviour of nature at the nanoscale. The quantum properties of matter and energy that make nanotechnology so interesting wreak havok with conventional simulation methods.

Quantum computers are the only known solution to this problem. They are able to directly solve the fundamental equations of quantum mechanics for any physical system. Sufficiently robust quantum computers will be able to create the ultimate virtual reality environment, where products and processes at the level of atoms and molecules can be exactly and effortlessly probed.

Application 1: Optimization

http://www.dwavesys.com/optimization.php

Quantum computers can be used to get approximate solutions to large NP-complete optimization problems much more quickly than the best known methods running on any supercomputer.

Application 2: Quantum Simulation

http://www.dwavesys.com/quantumsimulation.php

Simulation has always been an important part of what conventional computers do. For engineers and scientists, simulation is about asking "what if?" questions without having to actually do it. Today's engineering marvels would not be possible were it not for computer modeling. Everything from the car you drive, to the plane you last flew in, to the building in which you sit, to the computer chip in your PC, are made possible by simulation.

There is an implicit assumption that the tactics used in engineering today will apply to engineering at the nanoscale. The promise of nanotechnology is based on the premise that since everything is built of atoms, if we can manipulate matter on the level of atoms, we can build anything that is physically possible.

Building, however, is only a part of engineering. Just being able to build any given assembly of atoms does not mean that we can predict how it behaves before we build it.

Unfortunately, conventional (non-quantum) computers, no matter how powerful, are very bad at predicting the behaviour of nature at the nanoscale. The quantum properties of matter and energy that make nanotechnology so interesting wreak havok with conventional simulation methods.

Quantum computers are the only known solution to this problem. They are able to directly solve the fundamental equations of quantum mechanics for any physical system. Sufficiently robust quantum computers will be able to create the ultimate virtual reality environment, where products and processes at the level of atoms and molecules can be exactly and effortlessly probed.

Application 1: Optimization

http://www.dwavesys.com/optimization.php

Quantum computers can be used to get approximate solutions to large NP-complete optimization problems much more quickly than the best known methods running on any supercomputer.

Application 2: Quantum Simulation

http://www.dwavesys.com/quantumsimulation.php

Simulation has always been an important part of what conventional computers do. For engineers and scientists, simulation is about asking "what if?" questions without having to actually do it. Today's engineering marvels would not be possible were it not for computer modeling. Everything from the car you drive, to the plane you last flew in, to the building in which you sit, to the computer chip in your PC, are made possible by simulation.

There is an implicit assumption that the tactics used in engineering today will apply to engineering at the nanoscale. The promise of nanotechnology is based on the premise that since everything is built of atoms, if we can manipulate matter on the level of atoms, we can build anything that is physically possible.

Building, however, is only a part of engineering. Just being able to build any given assembly of atoms does not mean that we can predict how it behaves before we build it.

Unfortunately, conventional (non-quantum) computers, no matter how powerful, are very bad at predicting the behaviour of nature at the nanoscale. The quantum properties of matter and energy that make nanotechnology so interesting wreak havok with conventional simulation methods.

Quantum computers are the only known solution to this problem. They are able to directly solve the fundamental equations of quantum mechanics for any physical system. Sufficiently robust quantum computers will be able to create the ultimate virtual reality environment, where products and processes at the level of atoms and molecules can be exactly and effortlessly probed.

Application 1: Optimization

http://www.dwavesys.com/optimization.php

Quantum computers can be used to get approximate solutions to large NP-complete optimization problems much more quickly than the best known methods running on any supercomputer.

Application 2: Quantum Simulation

http://www.dwavesys.com/quantumsimulation.php

Simulation has always been an important part of what conventional computers do. For engineers and scientists, simulation is about asking "what if?" questions without having to actually do it. Today's engineering marvels would not be possible were it not for computer modeling. Everything from the car you drive, to the plane you last flew in, to the building in which you sit, to the computer chip in your PC, are made possible by simulation.

There is an implicit assumption that the tactics used in engineering today will apply to engineering at the nanoscale. The promise of nanotechnology is based on the premise that since everything is built of atoms, if we can manipulate matter on the level of atoms, we can build anything that is physically possible.

Building, however, is only a part of engineering. Just being able to build any given assembly of atoms does not mean that we can predict how it behaves before we build it.

Unfortunately, conventional (non-quantum) computers, no matter how powerful, are very bad at predicting the behaviour of nature at the nanoscale. The quantum properties of matter and energy that make nanotechnology so interesting wreak havok with conventional simulation methods.

Quantum computers are the only known solution to this problem. They are able to directly solve the fundamental equations of quantum mechanics for any physical system. Sufficiently robust quantum computers will be able to create the ultimate virtual reality environment, where products and processes at the level of atoms and molecules can be exactly and effortlessly probed.

Shor's factoring algorithm has two registers, which are pretty much seperate parts of the algorithm. One register you hit with a hadamard to put n bits in a superposition of all possible states, and the other is what you run through an algoritm to do all the exponents and mods etc, then you do the quantum FFT at the end and get the period.

Also I think DWave has been doing doing this thing with superconductors for quite a while now. NMR quantum computers have never really been proposed as practical implimentations, its just really cheap to build smaller ones.

I'm not saying this isn't dificult - but the former is more of a manufacturing challenge where you make incremental improvements to relatively well known structures. Optimizing the efficiency of manufacturing plants and logistics operations of Wal*Mart is also an *EXTREMELY* difficult problems, and yes, I'm sure to some degree Wal*Mart's optimization of these processes could be considered innovative R&D work. But I (or, I think Dell, in the context of this thread) would call this an Engineering Led business.

But mostly I meant the stuff Dell and HP does - find a cheap contract manufacturer, find a cheap chipset, see if Intel or AMD are the better deal of the day, and put them all in a box with a pretty package.