Intel's Pat Gelsinger (NSDQ:INTC) sees a "clear way" to manufacturing chips under 10 nanometers and when the semiconductor industry transitions to 450mm silicon wafers around 2012, the number of companies that run their own fabs will drop into the single digits.
Intel debuted its 45nm process late last year and has been ramping its Penryn line of 45nm processors steadily throughout this year. The next die shrink milestone will be the 32nm process, set to kick off next year, followed by 14nm a few years after that and then sub-10nm, if all goes according to plan.
Gelsinger described the elemental hoops Intel has had to jump through to achieve each "tick" milestone in the chip maker's relentless pursuit of Moore's Law, noting that while each new process adds materials used in novel ways, modern processors are still built on a "silicon scaffolding."
"We are putting more and more of the periodic table onto that silicon scaffolding. Today we use about half of the elements on the periodic table. When [Intel co-founder Robert] Noyce and Moore started, they used six elements," Gelsinger said.
"We replaced the gate with high-K, we put metal on top of it, but it's still, quote, silicon. [The process of getting smaller] keeps moving forward. It may be carbon nanotubes next or it may be spintronics. But we'll keep moving forward."
ULTIMATE LIMITS
Previously Intel has forecast moore's law to continue to at least 2029.
This site has covered the future of lithography
There is going to be substantial re-architecting with more photonics and other changes like the Tensilica processors.
The GPGPU, FPGA, custom tensilica processors and cell type processors seem like the way forward. Plus the new universal memories.
New molecular computing architectures could have an impact or a niche.
A successful and inexpensive 3D architecture needs to be perfected. Ultimate limits will not be seen until we have 3D, 10 nanometer or less optical systems and are pushing the limits of cooling the heat generated and energy to power the devices. The technologies that could be involved are plasmonics, excitons, spintronics, metamaterials, room temperature superconductors and better cooling systems. There will be re-architecting with reversible computing architecture and more efficient parallel computing architectures.
So a 10 centimeter cube would have 10 million multi-nanometer layers. One layer of computing would be about 10 million times more powerful than what we currently have. so the small fist size cube would be100 trillion to 1000 trillion times more powerful for personal computing. This means 100,000 to 1 million zettaflops (10*23 to 10**24). Plus each person could have a few cubic meters of computronium. For
several more thousand times more compute power.
Heading to 1-2 nanometer feature and component sizes would probably also be possible for another 1000 times boost (The previous insane amount of compute power ought to help find a way to squeeze out another 1000-1 million improvement) (10**27 to 10**30)
For non-heroic cooling limits: 10**24 to 10**26 bits per cm**2 (but we added the third dimension for 10 million to 100 million fold gains)
There will also be comparable levels of scale and density for quantum computers (10**23 to 10**32 qubits)
All the individual compute power will be networked together across the solar system. The connection speeds will also be pushing whatever physical limits there are.
FURTHER READING
Intel is researching applications for this compute power
30 page transcript from the IDF (Intel Developers Forum) spring 2008 keynote address by Pat Gelsinger
July 02, 2008
Intel's Gelsinger sees clear path to 10 nanometer lithography
June 27, 2008
Advances toward quantum control: better trapped ion quantum gates, hybrid molecules in silicon, quantum coral
The new molecule is a hybrid, with the naturally occurring arsenic at one end in a normal spherical shape and a new, artificial atom at the other end in a flattened, 2-D shape. By controlling the voltage, the researchers found that they could make an electron go to either end of the molecule or exist in an intermediate, quantum, state.
Progress toward gate model Quantum Computer components with new molecule with more easily controlled quantum properties
"Our experiment made us realize that industrial electronic devices have now reached the level where we can study and manipulate the state of a single atom," Rogge says. "This is the ultimate limit, you can not get smaller than that."
Physicist Lloyd Hollenberg and colleagues at the University of Melbourne in Australia were able to construct a theoretical silicon-based quantum computer chip based on the concept of using an individual impurity.
"The team found that the measurements only made sense if the molecule was considered to be made of two parts," Hollenberg says. "One end comprised the arsenic atom embedded in the silicon, while the 'artificial' end of the molecule forms near the silicon surface of the transistor. A single electron was spread across both ends.
"What is strange about the 'surface' end of the molecule is that it occurs as an artifact when we apply electrical current across the transistor and hence can be considered 'manmade.' We have no equivalent form existing naturally in the world around us."
Klimeck, along with graduate student Rajib Rahman, developed an updated version of the nano-electronics modeling program NEMO 3-D to simulate the material at the size of 3 million atoms.
In a Nature Physics journal paper currently online, the researchers describe how they have created a new, hybrid molecule in which its quantum state can be intentionally manipulated - a required step in the building of quantum computers.
"Up to now large-scale quantum computing has been a dream," says Gerhard Klimeck, professor of electrical and computer engineering at Purdue University and associate director for technology for the national Network for Computational Nanotechnology.
"This development may not bring us a quantum computer 10 years faster, but our dreams about these machines are now more realistic."
Fault tolerant Trapped ion quantum gate
Towards fault-tolerant quantum computing with trapped ions
Ion traps are among the most promising physical systems for constructing a quantum device harnessing the computing power inherent in the laws of quantum physics. For the implementation of arbitrary operations, a quantum computer requires a universal set of quantum logic gates. As in classical models of computation, quantum error correction techniques enable rectification of small imperfections in gate operations, thus enabling perfect computation in the presence of noise. For fault-tolerant computation, it is believed that error thresholds ranging between 10**-4 and 10**-2 will be required—depending on the noise model and the computational overhead for realizing the quantum gates—but so far all experimental implementations have fallen short of these requirements. Here, we report on a Mølmer–Sørensen-type gate operation entangling ions with a fidelity of 99.3(1)%. The gate is carried out on a pair of qubits encoded in two trapped calcium ions using an amplitude-modulated laser beam interacting with both ions at the same time. A robust gate operation, mapping separable states onto maximally entangled states is achieved by adiabatically switching the laser–ion coupling on and off. We analyse the performance of a single gate and concatenations of up to 21 gate operations.
Changing the properties of a Quantum Corral by changing one atom
Single-atom gating of quantum-state superpositions
Unprecedented control over the superposition of electronic states of a 'quantum corral', by changing the position of a single atom within it, provides a powerful tool for studying the quantum behaviour of matter. Quantum corral are discussed in creating quantum mirages
Work by Chris Moon and others at Stanford working in the Manipulating the Atom group
The ultimate miniaturization of electronic devices will probably require local and coherent control of single electronic wavefunctions. Wavefunctions exist within both physical real space and an abstract state space with a simple geometric interpretation: this state space—or Hilbert space—is spanned by mutually orthogonal state vectors corresponding to the quantized degrees of freedom of the real-space system. Measurement of superpositions is akin to accessing the direction of a vector in Hilbert space, determining an angle of rotation equivalent to quantum phase. Here, we show that an individual atom inside a designed quantum corral1 can control this angle, producing arbitrary coherent superpositions of spatial quantum states. Using scanning tunnelling microscopy and nanostructures assembled atom-by-atom2, we demonstrate how single spins and quantum mirages3 can be harnessed to image the superposition of two electronic states. We also present a straightforward method to determine the atom path enacting phase rotations between any desired state vectors. A single atom thus becomes a real-space handle for an abstract Hilbert space, providing a simple technique for coherent quantum-state manipulation at the spatial limit of condensed matter.
FURTHER READING
Publications of Jan Benhelm
May 09, 2008
Quantum dot based quantum logic gate proven possible
engineers and physicists from Stanford and the University of California at Santa Barbara demonstrate a potential progenitor of an essential component of quantum computers, "a logic gate" that enables interaction between just two particles of light.
"We have demonstrated a system composed of a single quantum dot in a cavity that can be used to realize such a gate, and we demonstrated that two photons can be made to interact with each other via this system," says Stanford applied physics doctoral student Ilya Fushman, a lead author on the paper along with two other doctoral students from the Vuckovic group, Dirk Englund and Andrei Faraon. "So we showed that such a gate is possible and demonstrated the first necessary steps in that direction."
The team has demonstrated that when the two photons are identical, a phase shift of 12.6 degrees is achieved. This is only a fraction of the 180-degree rotation required to make a full logic gate, Vuckovic says, but by combining several of the devices in a row, her team expects to attain the needed effect. Also, when the signal and control photons are allowed to differ, the phase shifts can be up to 45 degrees.
Other challenges include eliminating manufacturing imperfections and reliably placing the quantum dots right where they need to be within the crystals, but the team is optimistic.
"We are hopeful that these engineering challenges can be overcome to open the path to chip-based high-fidelity quantum logic with photons," Vuckovic says
April 22, 2008
Seth Lloyd of MIT on Dwave Systems Adiabatic quantum computer
Seth Lloyd discusses adiabatic quantum computers in MIT technology review. Seth Lloyd and Kaminsky created the theoretical design of a superconducting adiabatic quantum computer on which the Dwave System is based.
Seth has suggested experiments that Dwave can perform to prove if their system is achieving a quantum state.
The pioneers of superconducting quantum computation had been able to demonstrate the quantum nature of their devices by zapping them with fast microwave pulses and looking at their responses. But those devices weren't adiabatic; they operated at speeds comparable to those of a conventional computer. The D-Wave device, by contrast, is purposefully slow: therefore, no zapping is possible. As a result, there are a limited number of experiments that can indicate whether the device is really doing quantum computation. One, however, is to vary the slowness with which the device oozes from its initial state to its final state. Halfway through the oozing process, the computer arrives at a point where it must start making the hard choices that lead to the problem's solution. Here the computer is in a weird quantum state, in which every bit registers 0 and 1 at the same time. I urged the D-Wave researchers to explore this critical point and search for the telltale signs.
More recently, I [Seth Lloyd] spoke with Herb Martin, the CEO of D-Wave, and Geordie Rose, the company's chief technology officer and cofounder, and emphasized the need for them to pursue these experiments if they are truly interested in explaining how their devices work. One experiment that I [Seth Lloyd] recommended to Rose is a specific protocol for creating and verifying the presence of a so-called Schrödinger's-cat state, a specific instance of the state in which all the qubits register both 0 and 1 simultaneously
Scott Aaronson also has a short article with his views.
April 17, 2008
Graphene nanoelectronics
The Journal Science has a paper "Chaotic Dirac Billiard in Graphene Quantum Dots" which describes the smallest transistor ever made was created using graphene.
Researchers have carved graphene to create the world's smallest transistor, one atom thick and ten atoms wide.
the New Scientist magazine also has coverage
Applying a magnetic field to the smallest dots lets current flow again, making a switchable transistor. The smallest dots that worked as transistors contained as few as five carbon rings – around 10 atoms or 1nm wide.
There are other kinds of prototype transistors in this size range. But they usually need supercooling using liquid gas, says Novoselov. The new graphene devices work at room temperature.
Such prototypes are typically made by building one atom at a time, or wiring up individual molecules. Those approaches are complex and impractical, Novoselov says.
By contrast, the graphene transistors were made in the same way that silicon devices are, by etching them out of larger pieces of material. "That's their big advantage," he says.
The most amazing result for me is that they were able to obtain quantum dots as small as 1 nm," says Antonio Castro Neto of Boston University, US. "This is shocking." "If you try to reduce the dimensions of any other structure, the structure would disintegrate before you reach these dimensions," Neto adds.
"There is no doubt in my mind that these structures can be used for technological applications," he says. "The electronic flexibility and structural stability, fundamental for modern device development, are unmatched in any other material on Earth." But working out how to manufacture graphene devices on a practical scale remains a challenge, he concludes
Graphene quantum dots offer a new approach to quantum nanoelectronics. (article by R. M. Westervelt of Harvard University)
FURTHER READING
Other publications from Westervelt research group at Harvard
Graphene quantum dots may help solve quantum computing problems.
Ensslin, along with fellows at the Solid State Physics Laboratory, Stampfer, Güttinger, Molitor, Graf and Ihn, believe that they can use electron spins from a tunable graphene quantum dot to create qubits, the building blocks of a quantum computer. These graphene-based qubit could rectify some of the problems found with gallium arsenide. As a first step they present a graphene single electron transistor in Applied Physics Letters: “Tunable Coulomb blockade in nanostructured graphene.”
One of the main problems with spin-based quantum computers, Ensslin explains, is that spins won’t keep their direction indefinitely.
“Graphene turns out to be a material which is expected to overcome this,” Ensslin says. He is careful to explain that even though he and his peers have created a graphene quantum dot, extrapolations of how it would work in a quantum computer are still at the theory stage. “When you look at this theoretically, you find that 98 percent of carbon has no nuclear spin. This means that the coupling between nuclear spins and electron spins would be strongly reduced.”
However, March 2008 researchers found that spin and orbital motion of electrons in carbon nanotubes is coupled The findings have important implications for spin-based applications in carbon-based systems, entailing new design principles for the realization of quantum bits (qubits) in nanotubes and providing a mechanism for all-electrical control of spins in nanotubes.
March 14, 2008
Artificial Intelligence ? You're soaking in it.
This phrase was popularized by a television commercial campaign for Palmolive dish washing detergent. Madge, a manicurist, would comment on the dry, rough appearance of her client's skin as she worked on one hand while the other soaked in a bowl of light green liquid. The client would ask her advice; Madge would recommend Palmolive; the client would act surprised (after all, how could a dish washing detergent affect one's skin? Preposterous.). Then Madge would inform the client about the liquid in the bowl: "You're soaking in it," she'd say, in a very matter-of-fact tone. The shocked client would immediately remove her hand from the bowl, and Madge would guide it back down, assuring her that everything was fine: "Palmolive softens hands as you do dishes."
Program trading (using classic artificial intelligence techniques) is closing in on controlling half of all financial transactions in the world and 80% in the USA.
A third of all EU and US stock trades in 2006 were driven by automatic programs, or algorithms, according to Boston-based consulting firm Aite Group LLC. By 2010, that figure will reach 50 percent, according to Aite.
In 2006 at the London Stock Exchange, over 40% of all orders were entered by algo traders, with 60% predicted for 2007. American markets and equity markets generally have a higher proportion of algo trades than other markets, and estimates for 2008 range as high as an 80% proportion in some markets.
University endowments and corporate pension funds are distributed into Hedge Funds (20%) and stock, bond and commodity funds which are mostly algorithmically controlled. Particularly US markets with 80% program trading.
University endowment investments are described in this pdf
Some people like to mock the idea of Artificial Intelligence and Artificial General intelligence as "robot gods". The generally superior than human generated returns from program trading are helping to provide money for paycheck, pension and department budgets of those who mock AI and mock the idea that better AI is coming or that AI will have more and more influence on society.
Reality and facts would just get in the way of Dale's worldview.
Ray Kurzweil is on the vanguard of using even more advanced AI to run his own hedge fund. Part of $30 billion/year invested in hardware and software for financial trading and spending on improving the power and capabilities of those AI systems. As if better AI won't be adopted in this financial intelligence arms race.
A breakthrough that could happen this year [October, 2008] is a supercomputer able to model what people believe could pass a form of the Turing test.
Google is using artificial intelligence techniques to provide better searches and to provide better matching of advertising with search results.
It's pretty clear from what [Google co-founders] Larry Page and Sergey Brin have said in interviews that
Google sees search as essentially a basic form of artificial intelligence. A year ago, Google executives said the company had achieved just 5% of its complete vision of search. That means, in order to provide the best possible results, Google's search engine will eventually have to know what people are thinking, how to interpret language, even the way users' brains operate.
Google has lots of experts in artificial intelligence working on these problems, largely from an academic perspective. But from a business perspective, artificial intelligence's effects on search results or advertising would mean huge amounts of money.
Some of the most powerful AI will be trying to achieve the goal of anticipating what you want to buy when you want to buy it.
FURTHER READING: Many competing options to make computers millions of times more powerful than today.
Proper framing of the transhumanist debate
Promising new approach to molecular computing.
Brain simulation progress.
Tensilica configurable processors could make affordable petaflop and exaflop computers
New nanoscale metamaterial architecture for enabling an all optical computer.
More autonomous robots using better 3D freeze frame visual systems with LIDAR
The struggle over high risk high payoff research.
Quantum annealing can be millions of times faster than classical computers.
Predictions on artificial general intelligence.
Hardware for artificial intelligence.
Cognitive enhancement methods
March 07, 2008
Proper framing of the transhumanist debate
Michael Anissimov has another article related to the defence of transhumanism from misguided attacks.
Transhumanism (sometimes symbolized by >H or H+), a term often used as a synonym for "human enhancement", is an international intellectual and cultural movement supporting the use of new sciences and technologies to enhance human mental and physical abilities and aptitudes, and ameliorate what it regards as undesirable and unnecessary aspects of the human condition, such as stupidity, suffering, disease, aging and involuntary death.
I think the discussions around Transhumanism get bogged down because the discussions too often skip over the history and trends around the use of technology to enhance human mental and physical abilities. They also add in a bunch of convoluted and unnecessary intellectual baggage. Enhancement has been going on since someone picked up a rock or stick to fight an animal or prepare one for food or clothing. Improved enhancement since someone sharpened the stick or the rock or tied the sharpened rock to the stick. Riding a horse to enhance mobility. Writing and paper to enhance communication and memory. Steam engines for enhanced mechanical/physical productivity.
Does every attempt at improvement succeed ? No, but since individuals switch to what is better for them then there is a strong general trend toward improvement.
Wired has an interesting little article which I would categorize as transhumanist lite. Compares hypothetical augmentation drug with coffee.
I would like to see some kind of definitions around “end of history”.
History is the continuous, systematic narrative and the research of events in the past of importance to the human race, including the study of events over time and their relation to humanity.
So there is the history before homo-sapiens. There would still be history even if homo-sapiens are modified.
In regards to augmentation with technology and biological and non-biological. Currently many people have smart phones that they carry around all the time, some have cochlear implants, pace makers etc… They also have lasik eye surgery, millions take steroids, millions take test score enhancing drugs, cosmetics, cosmetic surgery, take vitamins etc… People drive cars, forklifts, and ride Segways. Sometimes we integrate with technology like with prosthesis or surgery and sometimes we don't. However, voluntary modification of all types is common place.
The smart cellphones can provide access to the internet, google, wikipedia etc.. to augment the ability of someone to access facts, other resources etc… They can also access systems for enhancing the ability to perform math (calculators).
So technology has caused and is causing enhancement and modification.
So the only things at issue are how much more and how will this change in the future.
Will the bandwidth speed to my smartphone increase ? Will its processing power improve ? Will the interface get better (true some companies could backslide on this but people would then choose not to buy their phones) ?
Certain features trends seem certain. Some of the products can be bought now and some seem likely to be more available and cheaper in the future.
Recently there is lab work for human power generated from regenerative braking from walking. Generates 5 watts while someone is walking A square meter of flexible solar cells could generate 19-56 watts depending upon location and sunlight conditions. US army has solar tent material for generating up to 1000 watts.
There is plenty of other energy that could be captured to power devices.Broken into usable terms, waiting to be harvested are 81 watts from a sleeping person, 128 from a soldier standing at ease, 163 from a walking person, 407 from a briskly walking person, 1,048 from a long-distance runner, and 1,630 from a sprinter, according to the center. But of course there’s not 100% capture. Body heat, for example, can only be converted with 3% efficiency with current thermoelectric materials.
Computing at about 19.4 gigaflops per watt for best new chips. This is a continually improving metric (just like flops per $ they go along with Moore's law).
Exaflop processing with configurable semi-custom processors is achievable by 2015. Other kinds of computers could achieve success and provide different kinds of computational advantages. quantum computers, optical computers, artificial intelligence and neural simulators.
Lightweight batteries and ultracapacitors. 100-300 watt-hours/kg.
So within say 10 years, carrying around teraflop+ class smartphones that are constantly charged with gigabit+ connections seems likely. One would also be able to network to quantum computers and supercomputers of all types for remote processing. Plus other components and gear could be carried and powered. 36V power tools (not used constantly unless you had access to a solar tent or we were capturing a lot more of the ambient power) or human body powered tasers, vision enhancement gear etc… Also, not including all the gear you might have in the future car or around your home. Also, you could have availed yourself of immune system enhancement, myostatin inhibitors etc…
Would individuals choose a better-faster phone ? Those who argue against enhancement are saying no, at some point all people will not choose better products.
Comments on the class arguements of rich versus poor
Would the businessperson or someone with more money have a better phone ? Maybe. Students with not much income can still own iPhones. How about medical procedures ? Who is paying $500-1000 for lasik now ? Is it only the wealthy ?
There are 3 billion people with some kind of cellphone now. It seems penetration of some technology is reaching even the poorest people in the world.
There are choices and priorities now and there will be options, choices and priorities in the future.
Those who ridicule the idea that technology can make us even richer are wrong
People who take advantage of opportunity - technological or otherwise - are and have become richer. Ray Kurzweil, Bill Joy are both what I consider rich. I do not know what the quantity is of “beyond dreams of avarice”. It appears to be a useless subjective phrase with an anti-wealth bias most frequently used by Berkeley communists.
One could look at the economic history of the world. List of regions by past GDP on a PPP basis and divide by populations to get per capita levels of wealth. It seems pretty plain that in the thought experiment of asking someone from one of those past times to compare their economic lot versus someone at a place and time with more tech that the place with more tech is richer with a larger fraction of people who would classified as rich. There seems to be no reason to believe that this trend to wealth enabled by better technology and economy will end. Those who argue about resource limits are ignoring vastly improved nuclear fission, successful development of nuclear fusion, development of economical space travel and techonlogy for tapping the resources of the solar system which I discuss throughout my thousands of articles.
FURTHER READING
Nick Bostrom discusses the impact of a 1% general and safe treatment for general cognitive improvement.
UPDATE:
One person who posted anonymously on the Chronicle of Higher Education Web site said that a daily regimen of three 20-milligram doses of Adderall transformed his career: “I’m not talking about being able to work longer hours without sleep (although that helps),” the posting said. “I’m talking about being able to take on twice the responsibility, work twice as fast, write more effectively, manage better, be more attentive, devise better and more creative strategies.”Surveys of college students have found that from 4 percent to 16 percent say they have used stimulants or other prescription drugs to improve their academic performance — usually getting the pills from other students.
In a recent commentary in the journal Nature, two Cambridge University researchers reported that about a dozen of their colleagues had admitted to regular use of prescription drugs like Adderall, a stimulant, and Provigil, which promotes wakefulness, to improve their academic performance.
March 05, 2008
Nanomagnets with controlled Quantum tunneling could create powerful quantum computers
There is the possibility that single molecular nanomagnets or nanoparticle nanomagnets could be used to create powerful quantum computers. If quantum tunneling could be controlled in nanomagnets then they could create quantum computer gates or devices. The current work identifies that quantum tunneling can be turned on and off in nanomagnets.
According to quantum mechanics, small magnetic objects called nanomagnets can exist in two distinct states (i.e. north pole up and north pole down). They can switch their state through a phenomenon called quantum tunneling.
When the nanomagnet switches its poles, the abrupt change in its magnetization can be observed with low-temperature magnetometry techniques used in del Barco’s lab. The switch is called quantum tunneling because it looks like a funnel cloud tunneling from one pole to another.
Del Barco published paper shows that two almost independent halves of a new magnetic molecule can tunnel, or switch poles, at once under certain conditions. In the process, they appear to cancel out quantum tunneling.
“It’s similar to what can be observed when two rays of light run into interference,” del Barco said. “Once they run into the interference you can expect darkness.”
Controlling quantum tunneling shifts could help create the quantum logic gates necessary to create quantum computers. It is believed that among the different existing proposals to obtain a practical quantum computer, the spin (magnetic moment) of solid-state devices is the most promising one.
Here is a paper on their previous work to make single electron transistors to study single molecule nanomagnets
Quantum computers could make very powerful pattern recognizers
Here is a research paper that discusses using adiabatic quantum computation using liquid state nuclear magnetic resonance quantum computers for pattern recognition.
UPDATE:
Pattern recognition is a critical aspect of artificial intelligence. I have a new article "Artificial Intelligence: You are soaking in it", which discusses mostly ignored penetration of artificial intellience and its future with a lot of links to my articles on near terms pathways to computers millions of times more powerful than todays.
Via Ars technica
Dwave systems has used their quantum computer for image matching.
A novel quantum pattern recognition scheme is presented, which combines the idea of aclassic Hopfield neural network [shown to the left] with quantum adiabatic computation. Both the input and the memorized patterns are represented by means of the problem Hamiltonian. In contrast to classic neural networks, the algorithm can simultaneously return multiple recognized patterns. The approach also promises extension of classic memory capacity. A proof of principle for the algorithm for two qubits is provided using a liquid state NMR quantum computer.
In contrast to classic neural networks, a quantum neural register can represent a superposition of recognized patterns. Quantum superposition allows each of these patterns to be identified which is not the case for linearly combined mixture states in classic neural networks.
February 17, 2008
Quantum effects for better computer memory, clocks and microscopes
Over the last decade, Seth Lloyd and his colleagues and postdocs at MIT have been looking at how quantum mechanics can make things better. What Lloyd refers to as the “funky effects” of quantum theory, such as squeezing and entanglement, could ultimately be harnessed to make measurements of time and distance more precise and computers more efficient.
Among the ways that these quantum effects are beginning to be harnessed in the lab, he said, is in prototypes of new imaging systems that can precisely track the time of arrival of individual photons, the basic particles of light. “There’s significantly greater accuracy in the time-of-arrival measurement than what one would expect,” he said. And this could ultimately lead to systems that can detect finer detail, for example in a microscope’s view of a minuscule object, than what were thought to be the ultimate physical limitations of optical systems set by the dimensions of wavelengths of light.
In addition, quantum effects could be used to make much-more-efficient memory chips for computers, by drastically reducing the number of transistors that need to be used each time data is stored or retrieved in a random-access memory location. Lloyd and his collaborators devised an entirely new way of addressing memory locations, using quantum principles, which they call a “bucket brigade” system. A similar, enhanced scheme could also be used in future quantum computers, which are expected to be feasible at some point and could be especially adept at complex operations such as pattern recognition.
Another example of the potential power of quantum effects is in making more accurate clocks, using the property of entanglement, in which two separate particles can instantaneously affect each other’s characteristics.
While some of these potential applications have been theorized for many years, Lloyd said, experiments are “slowly catching up” to the theory. “We can do a lot already,” he said, “and we’re hoping to demonstrate a lot more” in coming years.
V Giovannetti and L Maccone wrote the main papers on using quantum entanglement to reach a quantum speed limit. The quantum speed limit is the Margolus-Levitin speed limit.
Quantum enhanced measurements that gets beyond some classical limits and closer to ultimate limits
FURTHER READING
Fundamental limits to sensing and control Seth Lloyd from 2006.
A presentation on the quantum speed limit
The latest thinking on optical quantum computing Previous optical quantum computing schemes had too much overhead, and new approaches are simplified. Key challenges will be the realization of high-efficiency sources of indistinguishable single photons, low-loss, scalable optical circuits, high-efficiency single-photon detectors, and low-loss interfacing of these components.
A presentation on quantum optics and other quantum effect applications
Quantum optics is a field of research in physics, dealing with the application of quantum mechanics to phenomena involving light and its interactions with matter.
February 15, 2008
Quantum annealing can be millions of times faster than Classical computing
Picture is the 16 qubit prototype. There was a 28 qubit prototype as well. A new announcement seems to imply 2000-4000 qubits by the end of 2008. "low thousands of qubits by the end of the year [2008]". The die has room for a million qubits.
A research paper has results that compare the time for a quantum annealer to achieve the same levels of accuracy. They obtain times of 10 milliseconds for the quantum annealer for 10 hours of simulated annealing time–a speed-up of more than six orders of magnitude. The speed improvement in the analyzed case was 3,600,000 times.
Dwave Systems has an analog quantum computer, which should have a 2000-4000 qubit version by the end of 2008. It appears likely that they will be able to solve certain classes of optimization problems significantly faster than current methods. Optimization problems are important for businesses like Airlines and delivery companies like Fedex. If they make money solving those problems then they will have more money to research and development better versions (cleaner qubits that stay coherent longer) of their system that could solve a wider range of problems.
It is important to note that for any given problem, heuristics superior to simulated annealing almost always exist. Therefore comparing the performance benefits of quantum vs. classical annealing does not fully answer the question of what the expected speed-up of quantum annealing over the best known classical approaches is. In order to perform this analysis, more specificity with the instance class involved and the specific heuristic being used to solve the problem are required.
D-Wave processors are designed to harness a fundamental principle of nature that operates in both quantum that operates in both quantum and classical regimes - the propensity for all physical systems to minimize their free energy.
Free energy minimization in a classical system is often referred to as annealing. For example, in metallurgy, annealing a metal involves heating it and then cooling
it. This type of thermal annealing allows a metal that is originally filled with defects (a metastable ‘high energy’ state) to become crystalline and defect-free (the minimum free energy state).
The simulation of this type of thermal annealing using classical computers is known as simulated annealing, which is a commonly used heuristic approach to solving
certain classes of hard optimization problems.
Quantum annealing slide
Another research paper from Dwave: Quantum annealing may provide good solutions [a good approximate answer] in a short time, although finding the global minimum [perfect answer] via AQC can take an extremely long time. The energy gaps
considered here are only the avoided crossing type, which correspond to first-order quantum phase transitions. This means that only certain classes of quantum computer algorithms would work at this time.
Problems that have exponentially large number of local minima close to the global minimum, the gap becomes exponentially small making the computation time exponentially long. The quantum advantage of adiabatic quantum computation may then be accessed only via the local adiabatic evolution, which requires phase coherence throughout the evolution and knowledge of the spectrum. Such problems, therefore, are not suitable for adiabatic quantum computation.So optimization problems are ones where AQC could provide a speedup over current systems and a better useful answer.
One type of problems for which quantum mechanics may provide an advantage over classical computation is optimization. In optimization problems, one is interested in finding solutions that optimize some function subject to some constraints. Usually, not only the best solution, but also solutions close to it are of interest.
The global scheme of adiabatic quantum computation maintains its performance even for strong decoherence. The more efficient local adiabatic computation, however, does not improve scaling of the computation time with the number of qubits n as in the decoherence-free case, although it does provide some “prefactor” improvement. The scaling improvement requires phase coherence throughout the computation, limiting the computation time and the problem size n. This means that some algorithms like the Adiabatic Grover search (faster database search) would not be sped up unless the quality of the qubits is improved beyond the level that Dwave Systems will initially be starting at.
I had taken the highlights of a Dwave presentation from Nov 2007 on how their quantum computer works
FURTHER READING
More quantum computer research papers
February 04, 2008
Dwave Systems has $17 million in added funding to make a quantum computer with thousands of qubits by the end of 2008
Dwave Systems closed a $17M financing round as of the end of January 2008. These funds will be used primarily to push the level of integration of our chips into the low thousands of qubits by the end of the year. In parallel with this central effort we will be working on running experiments on smaller systems to map out features of these systems important to their operation as quantum computers.
On November 2007, the last iteration of D-Wave’s chip was 28 qubits (quantum bits). The CTO Geordie rose said they were on track to show a 512 qubit machine in 2008 and 1024 the year after that (by the end of 2008. The die has room for a million qubits. This new announcement seems to imply 2000-4000 qubits by the end of 2008. "low thousands of qubits by the end of the year [2008]".
The latest financing round was fully subscribed by existing investors Draper Fisher Jurvetson (DFJ), GrowthWorks Capital Ltd, BDC Venture Capital, Harris & Harris, bcIMC and Pender Fund.
This was the number 1 item on my list of technologies to watch in 2008 It is ahead of the Bussard fusion because the Bussard fusion prototype could answer a lot of the questions about the potential of that potentially bigger technology but not all of the issues will be answered until the commercial fusion system is funded, built and operating. By the end of 2008, the Dwave quantum computer should be operating (or not) at a commercial level. Thousands of qubits will have applications where it should be clearly superior to any conventional computer system.
2-5 months until the Q2, 2008, 512 qubit machine.
9-11 months until a Q4, 2008, 2000-4000 qubit machine.
That will be great to see.
Hopefully by 2009-2010 we can fill out that die and get up to 1 million qubits and start transforming business and science.
UPDATE: Is it Quantum computing ?
Scott Aaronson, Dwave critic, has finally met Geordie Rose, CTO of Dwave They met at MIT when Geordie presented four hard problems to get MIT help in solving.These problems were as follows:
1. Find a practical adiabatic factoring algorithm. Because of the equivalence of adiabatic and standard quantum computing, we know that such an algorithm exists, but the running time you get from applying the reduction is something like O(n11). Geordie asks for an O(n3) factoring algorithm in the adiabatic model. It was generally agreed (with one dissent, from Geordie) that reducing factoring to a 3SAT instance, and then throwing a generic adiabatic optimization algorithm at the result, would be a really, really bad approach to this problem.
2. Find a fault-tolerance threshold for adiabatic quantum computing, similar to the known threshold in the circuit model. Geordie asserted that such a threshold has to exist, because of the equivalence of adiabatic and standard quantum computing. However, others immediately pointed out that this is not so: the equivalence theorem is not known to be “fault-tolerance-preserving.” This is a major open problem that many people have worked on without success.
3. Prove upper and lower bounds on the adiabatic algorithm’s performance in finding exact solutions to hard optimization problems.
4. Prove upper and lower bounds on its performance in finding approximate solutions to such problems. (Ed Farhi described 3 and 4 as “so much harder than anything else we’ve failed to solve.”)
Scott is leaving himself an out in case Dwave's system works in 2008: Scott says: Even if D-Wave managed to build (say) a coherent 1,024-qubit machine satisfying all of its design specs, it’s not obvious it would outperform a classical computer on any problem of practical interest. This is true both because of the inherent limitations of the adiabatic algorithm, and because of specific concerns about the Ising spin graph problem. On the other hand, it’s also not obvious that such a machine wouldn’t outperform a classical computer on some practical problems. The experiment would be an interesting one! Of course, this uncertainty — combined with the more immediate uncertainties about whether D-Wave can build such a machine at all, and indeed, about whether they can even produce two-qubit entanglement.
Scott also shows that he still does not understand business:also means that any talk of “lining up customers” is comically premature
Geordie responded:The first is that there are already buyers and sellers of quantum computers for research (Bruker NMR machines) and our systems are already much more useful and interesting than these.
The second is that we expect that even for fairly small systems (~1,000 qubits, which we plan to do this year) this type of special purpose hardware can beat the best known classical approaches for instance classes where the class embed directly onto the hardware graph even if the “spins” are treated entirely classically, which we assume is a worst-case bound. Often forgotten in this type of conversation is the fact that there is a long history of simple special purpose analog hardware outperforming general purpose machines. If you want an example, look at Condon and Ogielski’s 1985 Rev Mod Sci article–their Ising model simulator beat the fastest Cray of the time in Monte Carlo steps/second. You can’t draw conclusions about the general utility of this type of approach without looking at details.
I would note that it is standard business practice to pre-sell tickets to things that are not complete and may or may not work.
Examples: Aptera electric car, Tesla electric car, Toyota Prius sign up lists, music concerts, Microsoft sells software subscriptions with the understanding that their should be major software upgrades (yet Vista and other major upgrades were delayed for years), Virgin Galactic has presold hundreds of tickets for its yet to be completed sub-orbital rocket.
November 26, 2007
Dwave's Quantum computer Presentation from SC07
Dwave systems CTO Geordie Rose has published his slides from the SC07 conference, where he demonstrated there latest 28 qubit system.
Dwave system is a web services QUBO solver
Dwave to a computer scientist. QUBO is NP-hard. the decision version is NP complete
Real physical systems
dwave device schematic: nobium cjj rs-squid flux qubit
Dwave approach to AQC
dwave superconducting chip: bipolar couplers
dwave potential energy of Adiabatic quantum computer can be programmed by user
Device physics : the hamiltonian
Qubit manipulation: modulate the barrier height
Qubit manipulation: tilt the double well
Readout bias: direction of the current
Dwave picture of the chip: readout section
dwave device schematic: symmetric bipolar coupler
The Dwave AQC implements both the AQC model and the quantum annealing model.
adiabatic quantum computation model
Quantum annealing model
Dwave implementing part of the image matching as AQC, part is a regular computer program.
The steps to run an adiabatic quantum computer
November 23, 2007
More technical details on Dwave System's Quantum Computing
D-Wave Senior Scientist and condensed matter physicist Mohammad Amin gave a highly technical presentation at MIT. (54 slides in this power point presentation) Dwave recently demonstrated a 28 qubit computer. They are predicting that they will have 512 qubit and 1024 qubit quantum computer systems in 2008. If Dwave is successful then in 2009 it will begin to greatly accelerate the development of molecular nanotechnology which needs better molecular modeling.
Adiabatic quantum computer (AQC) required conditions
AQC Theory from 2001 requires an energy gap
AQC Theory predicts energy levels
Experimental measurements show energy levels consistent with quantum noise
Experimental measurements fit the theory
What the difference regions of quantum effects, mixed effects and classical effects would be
Interpreting several Measurements 
The experimental results are indicating that Dwave is looking at quantum results
FURTHER READING
The point of view of Dwave skeptic Scott Aaronson
Amin and Berkley maintained that their 16-qubit device was indeed a quantum computer and their evidence was that simulations of its behavior that took quantum mechanics into account gave, they said, a better fit to the data than simulations that didn’t. On the other hand, they said they were not able to test directly for the presence of any quantum effect such as entanglement. (They agreed that entanglement was a non-negotiable requirement for quantum computing.)
Dwave CTO Geordie Rose replies in the comments
Finally, the variety of demos we’ve run (including sudoku, image matching, etc.) are not “crap”. They use a novel hybrid approach to integrating QCs into classical solvers. In hindsight it is pretty obvious that to make any QC useful it needs to be integrated with the best known classical techniques regardless of what quantum algorithm it’s embodying. And while I’ve said this 10^87 times I’ll say it again: what we’re doing is explicitly heuristic and has no global optimality guarantees. While you can use the system we’re building on decision problems it is natively an optimization solver for quadratic unconstrained binary optimization problems
From another commenter:
How then does Dwave “solve” the image feature matching problem using just 28 bits, for images that are large and have many features (such as those that Dwave used in their SC demo)? Apparently they “cheat” and break the overall problem into many small maximum common subgraph problems (of a size that can be encoded in 28 bits). Each small MCS problem is “solved” on the QC, and then the solutions are somehow combined classically.
Like the soduku, solve the 3X3 squares iteravely then combine to a 9X9 solution.
It is not a cheat in that they are using the quantum system to its best ability by combining with our current best methods. To only solve problems with quantum systems is like having only allowing pencil and paper on tests when the real world has regular computers, wikipedia and Google.
November 15, 2007
Reports of Dwave's latest quantum computer demo
Zdnet blogs on the latest quantum computer demo by Dwave Systems
The latest iteration of D-Wave’s chip has 28 qubits (quantum bits), according to Rose. He said they were on track to show a 512 qubit machine next year, and 1024 the year after that. The die has room for a million qubits. But first things first, says Rose. “If we can’t get to 512 qubits by the end of next year, we’re in trouble,” he admitted.
Dwave's press release on the demo and future plans is more optimistic.
Our product roadmap takes us to 512 qubits in the second quarter of 2008 and 1024 qubits by the end of 2008.
At the future of things, Rose takes a tougher stance.
Rose has responded to the criticism saying that major developments have been made in quantum computing systems in the past years. He said that the 28-qubit computer, which will be demonstrated at SC07, will be able to use Dr. Neven's image recognition algorithm to analyze a 300-image database, grouping the objects according to detected similarities. "Our image-matching demonstration, the core of which is too difficult for traditional computers, can automatically extract information from photos-recognizing whether photos contain people, places or things, and then categorize them by visual similarity" – he said.
The actual machine is a bit unweildy at the moment. In fact, it’s about as large as D-Wave’s entire booth, so demos were run remotely via a web service back to the lab. “We’re going to work on making the refrigerator a bit smaller and self-contained,” said Rose, thinking ahead to commercial deployments.
In the picture above you can see a magnified view of the individual qubits on the chip. Each qubit is connected to three of its neighbors. Rose was asked why people were so skeptical of his work. It all comes down to the traditional way of relating discoveries through peer reviewed journals, he explained... He promised. “We’re going to go out to some of the hotbeds of skepticism” in the coming year, he said, with the goal of silencing the nay-sayers. They might even file a paper or two, but it didn’t seem to be a priority.
Apparently the US Patent and Trademark office is convinced, having granted the company dozens of patents on the technology. Dozens more are pending. “We have more [quantum computing] patents than any other company in the world,” said Rose.
November 13, 2007
Other progress in quantum computing
Other Quantum computer progress discussed at SC07
The quest to build fully functioning quantum hardwa