Google
 

 

 

 

Quantum Information Science & Technology

The Next Big Thing That Will Change Absolutely Everything

Francis Vale

Computers are killing the U.S. energy economy. Our silicon addiction is causing the national grid system to OD. At one point during the seemingly never ending California energy crisis, one of the national evening news programs contrasted the power requirements of a small one-story server farm with a 60-story office building. The diminutive server farm needed as much juice as the huge skyscraper.

The huge power supply drain at server farms is a natural consequence of the second law of thermodynamics, which in one form states that irreversible processes create entropy (which can be loosely stated as heat). AND gates, one of the most fundamental logic elements within a microprocessor, are presently designed to work in only one direction, and are thus irreversible in their operation. So whenever an AND gate clears (destroys) one bit of data, it also generates heat. The more AND gates, the more heat. Obviously, this is incredibly wasteful of energy resources. As Professor Tomasso Toffolli of M.I.T. put it, "How much free energy do you have to lose for a computation?"

Consequently, as you build ever faster and denser silicon-based processors that are irreversible in operation, heat dissipation, i.e., power consumption, eventually becomes an enormous obstacle. The short stack server farms discussed in that news story are thus consuming much more energy than gigantic office buildings because of their incredible wastefulness. The power crisis happened first in Silicon Valley because it is ground zero for probably the highest concentration of server farms and bit burning AND gates in the world. Entropy is killing them — and California’s lights. The rest of the global silicon economy is assuredly next.

Today (2001), the best commercial fabrication techniques produce devices with a line width of about 0.13 to 0.15 micron. But semiconductors will assuredly get faster and Internet server farms will get much more powerful and their demands for energy due to their extraordinary wastefulness will become increasingly insatiable, even if they were all to use low power versions of silicon. By about 2010, or just about the time it will take for building all those new generator plants and getting the half-baked Alaska oil flowing (if), the power requirements of Moore’s law-driven "classic" computing systems will have become truly enormous, making all these new power resources feebly redundant.

But quantum computers and communications don’t have an entropy problem, at least in the classic sense. First, quantum computations happen all at once — there is no sequential step by wasteful step process as in a classic semiconductor computer. But second, and much more critical, quantum computers by definition are inherently reversible because the laws of quantum mechanics are themselves reversible.

If a classic, i.e., non-quantum, computation could be reversed (unwound back to its original state), then no heat would be lost because the second law of thermodynamics would not be involved. The radical notion of reversible computer logic was discovered independently by Dr. Charles Bennett of IBM, and later by Dr. Edward Fredkin of M.I.T. Dr. Fredkin and Dr. Toffolli have since proved that a classic computer using reversible "Fredkin" logic could do anything that a conventional, irreversible system can. But just as it is cheaper to manufacture large displacement, fuel inefficient car engines than smaller ones with expensive turbochargers, so too, "It is cheaper to build systems that waste energy, as opposed to systems that conserve it" says Toffolli. The natural tendency for semiconductor companies, therefore, has been to design and build wasteful (i.e., irreversible) systems. On the other hand, sufficiently small systems, including quantum systems, are naturally reversible.

In nature, reversibility is a key factor in any type of truly successful, dynamic organism. As Henry Baker (of the former Thimble Systems in Encino, CA) stated it, "Biological computational processes, so unlike silicon ICs, rely on reversible chemical reactions, and are not so nearly wasteful of energy." Baker gives the example of DNA replication, which, he says, "if it wasted as much heat per bit as a modern CPU, would cause a developing chick to fry inside its own egg!" This is not to say that quantum computers don’t require energy just because they are reversible. They will need juice to run, but only as a means to a very minimal power requirement end.

Quantum computing and communications completely turn upside down our notions of time and space. What may be an impossible problem to solve on the world’s largest supercomputer could take an instant on a tiny quantum machine. For example, quantum-based, factorizing code breakers are often cited as a prime use of such machines. Today’s digital supercomputers would take billions of years to find the prime factors of a number that is a few hundred digits long, whereas large-scale quantum computers might perform that task in just seconds.

Inversely, secure quantum cryptographic signals are now routinely sent over fiber-optic cables and through the air for tens of miles. When secure quantum information is exchanged, cryptographic protocols use the laws of fundamental physics to ensure privacy. This is in marked contrast to current public-key crypto systems that decrypt a message requiring a time-consuming classic computation, such as prime factorization. Many, if not most, public key systems will likely become obsolete overnight when quantum computers become generally available.

Thus, for a very wide variety of reasons, quantum based systems are THE business technology story of the new millennium. Quantum computing and communications are a huge paradigm shift that is going to cause massive disruptions in numerous social, economic and industrial areas. They also usher in an era in which it is completely accepted that information processing and physics are fully interchangeable. IBM, the NSA, Siemens, DARPA NIST, the NSF, and other major commercial, governmental and academic organizations worldwide have now recognized and embraced the great commercial and technological significance of quantum information science. IBM’s quantum R&D effort is quite advanced. The following description of quantum computing from IBM is also among the best available. [Some further explanatory comments have also been added]:

"Quantum computers get their power by taking advantage of certain quantum physics properties of atoms or nuclei that allow them to work together as quantum bits, or "qubits," to be the computer's processor and memory. A quantum particle, such as an electron or atomic nucleus, can exist in two states at the same time -- say, with its spin simultaneously in the up and down states. This constitutes a qubit. When the spin is up, the atom can be read as a 1, and the spin down can be read as a 0. This corresponds with the digital 1s and 0s that make up the language of traditional computers. The spin of an atom up or down is the same as turning a transistor on and off, both represent data in terms of 1s and 0s. Qubits differ from traditional digital computer bits, however, because an atom or nucleus can be in a state of "superposition," representing simultaneously both 0 and 1 and everything in between."

"Moreover, without interference from the external environment, the spins can be "entangled" in such a way that effectively wires together a quantum computer's qubits. Two entangled atoms act in concert with each other -- when one is in the up position, the other is guaranteed to be in the down position. Entanglement makes possible highly orchestrated predictability and you can apply logical operations to entangled superpositions…." [Entanglement is a subtle quantum kind of correlation having no classical equivalent, and can be roughly described by saying that two systems are entangled when their joint state is more definite and less random than the state of either system by itself.]

"…The combination of superposition and entanglement permit a quantum computer to have enormous power, allowing it to perform calculations in a massively parallel, non-linear manner exponentially faster than a conventional computer. For certain types of calculations -- such as complex algorithms for cryptography or searching -- a quantum computer can perform billions of calculations in a single step. So, instead of solving the problem by adding all the numbers in order, a quantum computer would add all the numbers simultaneously."

 

Fig.1 When information is represented as a quantum state rather than in terms of classical bits, quantum information science is described as being generalizations or extensions of classical theory. The well-established theory of classical information and computation is thus a subset of a much larger topic, the emerging theory of quantum information and computation. (source, NSF)

At the angstrom scale of electron motion, as long as its motion is unobserved it is assumed to be "wavelike"; it can take all possible trajectories. But once observed, the wave collapses (called "decoherence") and becomes particle-like. Or stated more properly by David DiVincenzo of IBM’s T.J. Watson Research Center, "An unobserved attribute of a system can be in a superposition of different values, while an observed attribute assumes a definite value." In other words, as long as you don’t "look" at the quantum system, it’s continually calculating a huge probability of outcomes at the same time. In fact, a single qubit, because of the tremendous power of superposition, is in of itself a parallel computer. But when you interfere with it in any way, the system collapses ("decoheres") into a single state, destroying all other possibilities, and hence, stopping the computation process.

 

Fig. 2. The quantum-classical boundary. A classical computer can efficiently simulate a system that behaves classically, but not one that behaves "quantumly." Hence it is possible to identify a sharp transition between the quantum and classical phases of some physical systems. For the first time, the physical form of information has a qualitative rather than merely a quantitative bearing on how efficiently the information can be processed, and the things that can be done with it. (source, NSF)

As for communications, quantum effects are similarly powerful and bizarre. There is quantum teleportation (yep, it’s been proven to exist) which offers a convenient and safe way to pass quantum information from one part of a quantum computer to another, and even between quantum computers. A quantum computer can also be instantly knowledgeable of another’s state (i.e., entangled), no matter how distant. The usual laws of space and time seemingly do not apply in the quantum world. The upshot is that if quantum information rather than classical information is exchanged between systems, then the amount of communication required to perform certain distributed tasks can be drastically reduced. All of these unique aspects have obvious and major implications for the folks in the communications infrastructure business.

The radical notion of quantum computation has been around for some time. This wild idea first began making the rounds in the 1970’s and 1980’s, promulgated by people of the likes of Richard Feynman, Paul Benioff, David Deutsch, Charles Bennett, and some other visionaries. But until the early 1990’s it was mostly dismissed as just another esoteric exercise for the theoretical physicists. However, the role of quantum effects in silicon systems was well known and understood. Present-day electronic devices rely on quantum mechanics. It is the wave nature of the electron travelling through the periodic potential of the crystal that provides the starting point for everything done in silicon systems (it produces the 1.1 eV stop band). It wasn't until it was shown that quantum devices could do astonishing feats with cryptographic algorithms that the finally field took off.

Peter Shor of AT&T’s Bell Labs published a paper in 1994 that finally got people’s quantum attention. His paper, "Algorithms for quantum computation: discrete logarithms and factoring", gave the NSA and many commercial folks (banks, etc.) who rely on ultrasecure crypto codes a very rude wake up call. Shor showed in his paper how quantum computers could rapidly calculate the factors of very large numbers. Such large numbers are at the core of modern cyrpto codes. Factoring (calculating the divisors) of a 512-bit number, which is about 155 decimal digits, and even that of much bigger numbers might turn out to be child’s play for a quantum computer.

Until Shor’s paper arrived on the startled security scene, it had been safely assumed that factoring extremely large primes, even on the biggest supercomputers, would take billions of years. Some problems are tractable and others are intractable. The latter become exponentially harder; i.e., they don’t scale. A problem of size N is said to be tractable if its solution takes a length of time that depends on a polynomial function of N —- that is, an algebraic power of N such as N squared, N cubed, and so on. The computational resources required for a tractable problem generally scale with the numbers in a moderate way. If, on the other hand, the time taken to solve a problem blows up exponentially with the size of the input — for example, on the order 2N or greater -- the problem is deemed to be intractable. It just won’t scale. Factoring extremely large primes, e.g., code breaking, had been assumed to be such an intractable problem.

But Shor shook the safe house. He showed, to the shock of many, that by using quantum rules there was a polynomial-time algorithm for factoring. Suddenly, the security of nations and the global banking system was seen to possibly be at grave risk. It’s therefore no wonder that quantum information science was suddenly catapulted from its lofty intellectual aerie down to brass tacks urgency. Since Shor’s seminal 1994 paper, the field now known as quantum information science has slowly but inexorably been making its way into a large number of back room and not so back room projects in a wide variety of commercial, governmental, and university settings.

For quantum computing to succeed commercially and on a large scale, at least the following technology areas will have to have been successfully tackled:

  • Error-correcting systems for quantum computers and communications.
  • Techniques for creating highly reliable quantum devices.
  • New classes of quantum algorithms that significantly broaden the utility of these remarkable devices.
  • New manufacturing know how and materials technologies for building highly scalable, small sized, and inexpensive quantum devices.

So how do you maintain a coherent quantum computer system (all the atoms or particles are in the same quantum state regardless of whether the state is a superposition) and its crucial entanglement? You can’t go anywhere near it or observe it; in fact, a stray photon or a colliding atom will ruin the computation completely or cause huge errors. And how do you "read out" a definitive quantum answer without destructively interfering with the very computation you went to such pains to set up? (Even spookier, it has been experimentally shown that what you simply intend to measure is enough to determine the quantum outcome! The quantum world is like a huge psychic massage parlor; you think it and it will unkink it.)

At first, the rules of classic Boolean logic don’t seem to apply to quantum information science. However, as noted, quantum computers are intrinsically reversible, so you can take the AND of two bits and place them into a third in an unobserved fashion. Moreover, so long as these bits are unobserved (not interfered with), the bits can be in superposition of different values, as indeed can the state of a whole register. This is a nonsense notion so long as you think in terms of a macroscopic, i.e., classical computing, means of controlling the register, like via a gate voltage. But once you dispense with such macroscopic notions and do all the control at the atomic or microscopic level, reliable quantum systems with programmable logic become a reality.

Some of the first functioning quantum systems therefore rely on working completely at the atomic level. One quantum computer contender is ion trap technology. Trap approaches vary, but fundamentally the idea is to convince some ionized atoms or other charged particles to get into an evacuated chamber, and then hold them there using magnetic, static electric and/or radio frequency fields. Ions are just atoms that have lost or gained one or more electrons, thus acquiring an electrical charge. But even so trapped, the struggling atoms put up a thermal ruckus that interferes in creating a coherent state useful for quantum computation. To overcome the thermal fuss, special supercooling techniques using lasers have been developed.

In 1994 (clearly, a seminal year in quantum computing science) two very clever theoretical physicists, Ignazio Cirac and Peter Zeller at the University of Innsbruck Austria, had the notion that the minimized vibrations of cooled, trapped particles could be used to create a quantum computer. They subsequently showed that with three precisely timed laser pulses the interacting vibrations between qubits produced a controlled-NOT operation, which is also called an exclusive-OR logic gate. (The state of one input controls whether the signal presented at the other input is inverted at the output.) Moreover, as the effects rippled right down the whole qubit chain, the qubits did not have to be adjacent to each other to create this operation. They also showed that it was possible to create three-bit gates or higher by directing additional laser pulses aimed at other ions in this trapped string of atomic pearls. The coherence times lasted about a thousandth of second. And so in 1995, one year after Cirac and Zeller’s pivotal insight, the first-ever quantum logic gate arrived on the scene. Programmable systems at the atomic level were now a reality.

 

Fig. 3. Andrew Steane and Derek Stacey of Oxford University have also developed a quantum ion trap system. This is a picture of their ion trap electrode structure. The trapping electrodes are the central ones, and are approximately 1 mm in diameter. There are four long thin electrodes about 3 cm in length that provide horizontal confinement, and two short pin-like electrodes at each end that provide confinement along the axis. The rest of the structure consists of auxiliary electrodes and steel rods to support everything. (source, Oxford University)

 

Fig. 4. Ions in Oxford: six calcium ions glowing in the center of their trap

 

But like all quantum devices, ion trap-based systems have their drawbacks. The coherence times need to be much improved (although Circa and Zeller have recently said they can now achieve coherence times of about ten minutes). However, even these two very ardent fans of ion trap systems admit that ion traps will probably run out of scalability steam at about 2,000 qubits, if that number is truly achievable at all.

Another type of quantum computing system relies on Nuclear Magnetic Resonance (NMR), which is more or less the same as Magnetic Resonance Imaging (MRI). The only real distinction between MRI and NMR is the nomenclature (Don’t want to scare off those poor patients with the word "Nuclear", do we doctor?). Hence, MRI is used on humans and NMR is used in chemistry and spectroscopy. This exotic-sounding technique detects magnetic properties of nuclear spins in both chemical and biological materials. For example, the single proton nucleus of each hydrogen atom has a particular spin e.g. "up" or "down" (or a quantum superposition of both up and down). When a material is immersed in a strong static magnetic field and then exposed to a second dynamic field and/or electromagnetic (e.g. RF) radiation, some proton spins are altered and eventually relax to their original orientation (imagine a spinning top canting over from the vertical). This precession of the nuclei about a magnetic field produces a very weak, but highly characteristic, measurable signal. The medium and other conditions in which the protons find themselves determine their response. If you are doing a MRI, these atomic-level signals will produce a computer-enhanced image to diagnose for injury or disease.

But if you are doing NMR for quantum computing, you can achieve something else entirely. By filling a test tube with a liquid comprised of appropriate molecules (coffee does very nicely!) you can "program" the NMR system. Creating logic gates is possible by using the interacting spins of two nuclei. By then using precise radio frequency pulses as "software" you can alter the interacting atomic spins in a highly particular way, e.g., your code-breaking/factoring algorithm, so the nuclei will perform a useful calculation. Using NMR also elegantly addresses the problem of decoherence -- The interfering phenomenon that destroys the utility of a quantum system. Nuclear spins in a NMR quantum computer can have long coherence times, lasting from many seconds to minutes in liquids. And in gases, the times can last hours. Finally, you need to read out the answer — the very weak but measurable signal produced by the precession of the nuclei in the NMR’s magnetic field.

But you can’t measure the signal directly because that will interfere with the incredibly delicate coherent state of the system and contaminate the answer with errors. By using a huge number of individual quantum computers instead of just one representing each qubit (the fundamental building block of a quantum computer) you can afford to let your measurements interact with a few of them and still get a reliable answer. This type of multi-qubit system is known as an ensemble quantum computer (EQC) and its result measurement as ensemble averaging. IBM, The Institute of Theoretical Physics at Santa Barbara, Harvard Medical School, the MIT Media Lab, and Oxford University, to name just some, have all built functioning quantum computers based on NMR technology. There is also a formal quantum NMR quantum collaboration project between researchers at Stanford University, U.C. Berkeley, MIT, and IBM (see squint.stanford.edu).

 

Fig. 5 IBM physicists Isaac Chuang and Costantino Yannoni performing a NMR quantum-computing experiment (the NMR device is the big cylinder in the background) at IBM’s Almaden research facilities. They announced their quantum computing success at the 2000 Hot Chips conference. [IBM-Almaden photo]

One catch (and there are others) to the NMR approach is that your average cup of Starbucks has more than a hundred billion trillion molecules all charging off into different caffeine crazed directions. If the quantum-computing goal is to start off with a coherent system that you can reliably and consistently set up and use, this is not good. You could possibly isolate and trap some of these bouncing molecules and get them into a coherent state by using something called an atomic force microscope (AFM) and set them up the way you want. Unlike traditional microscopes, scanned-probe AFM systems do not use lenses, so the size of the probe rather than diffraction effects generally limit their resolution. AFMs can achieve a resolution of 10 pm, and also unlike electron microscopes, can work on samples in air and under liquids, like that coffee-filled quantum system. But using AFMs in quantum systems is still an ongoing area of exploration. As an alternative to using an AFM, you could rely on the fact that most of the NMR signals average out to zero. You could then scheme up ways to get just a few desired molecules to stand out from the silent crowd and use these highly vocal lads as your qubits. Several techniques have been shown to be effective in orchestrating such a quantum computing chorus call.

Fig. 6. A "desktop quantum computer." This machine consists of two magnets with a space between them for the tube with a liquid (coffee works quite nicely) made up of appropriate molecules. Inexpensive table-top devices now under development, like the one sketched here, will be able to outperform the costly commercial NMR spectrometers that are used in current studies of room temperature ensemble quantum computation. (source, NSF)

Neil Gershenfeld of MIT’s Media Lab has said that ‘Round about fifty qubits is when you begin to beat classical computers." But easily achieving that fifty+ qubit number in a NMR system appears to be remote and there is currently a hot debate about whether NMR-based quantum systems will ever be more than first step technical curiosities, despite their early promise.

Another approach to constructing quantum devices builds on the 1960’s discovery of molecular beam epitaxy (MBE) at Bell Labs. In MBE, the constituent elements of a semiconductor in the form of ‘molecular beams’ are deposited onto a heated crystalline substrate to form thin epitaxial layers. Basically, MBE is used to vaporize materials like aluminum and gallium arsenide in separate chambers. These vaporized materials are then joined together layer by atomic layer in another chamber by carefully spraying them on a wafer’s surface. Growth rates are typically on the order of a few Å/s and the beams can be shuttered in a fraction of a second, allowing for nearly atomically abrupt transitions from one material to another. The technique is so precise that these different layers form a single crystal with their respective lattices precisely lining up top to bottom. It is the resulting precise atomic structure lattice that holds the quantum-computing key. If the electrons don’t scatter as they move through the layers, as they do in conventional semiconductors, they can achieve coherence, the essential ingredient for a quantum computing system.

What’s especially appealing about MBE is that it can be used to create large numbers of self-assembling quantum dots -- miniscule semiconductors on a chip surrounded by an insulator such as aluminum gallium arsenide.

Fig. 7. Schematic of a quantum dot (Source, MITRE)

Single electrons are readily observable in a quantum dot, via a voltage jump, as they move in and out of these islands that are just a few hundred atoms across. Obviously, if quantum dot technology is commercially perfected (the major semi-memory makers in Japan take quantum dot technology very seriously), memory capacity of these microdevices will be extraordinary.

However, as far back 1994, researchers and theoreticians such as Adriano Barenco, David Deutsch and Artur Ekert postulated that quantum dots could also be used to implement conditional quantum logic. Barenco, who is at Oxford University in the UK, showed that the state of one quantum dot could be used to alter the behavior of another, leading to the possibility of creating programmable logic gates and low cost, easy to make quantum computers. (Oxford is the site of some of the most important and exciting research in the quantum field.) Sandia National Labs has also recently uncovered a repulsion effect between quantum dots, and this effect may completely govern the way they organize themselves.

But quantum dots have their own problems when it comes to quantum computation. Unlike NMR-based systems whose nuclear spins for a quantum computation have very long coherence times ranging from seconds to hours, quantum dots are notoriously reluctant to maintain appreciable coherence. Typically, coherence lasts about a billionth of a second. The primary culprits are thermal vibration and material impurities. The quantum house of computational cards collapses in a nanosecond.

But interestingly, Josephson junctions, the great superconducting hope for building wicked fast, but very low energy supercomputers that first surfaced in the 1970’s and which then just as quickly faded from view, seem to be on the comeback trail. A Josephson junction is a weak link between two superconducting films separated by a thin oxide layer enabling the tunneling of Cooper pairs of electrons. Josephson junctions may solve the coherence stability dilemma that to date has plagued quantum dot systems designers. There have been some recent quantum success stories using these superconducting devices. For example Nakamura, Pashkin and Tsai of NEC Fundamental Research Laboratories in Tsukuba, Japan demonstrated a Josephson junction quantum computer in April 1999. Although the NEC researchers did not perform any quantum calculations with their achievement, it was a notable breakthrough and there are growing indications that Josephson junctions might play a major role in building quantum computers. For example, D.V. Averin (Department of Physics and Astronomy, SUNY at Stony Brook) will be giving a paper in March 2001 at an American Physical Society meeting that discusses a recent experimental demonstration of a single qubit operation using a superconducting Josephson junction.

Scalability, error correcting, and coherence are the trinity that makes up the Holy Grail of the quantum quest. Quantum dots probably hold the greatest promise of becoming the most scalable of all current quantum design ideas. Numbers in excess of 1,000+ qubits are being thrown about for fully realized quantum dot systems, and much greater qubit densities will likely be possible as manufacturing techniques gain in sophistication. This is way ahead of NMR systems, which seem to be struggling with achieving qubit numbers of even fifty or so. Meanwhile, it seems that Ion traps may top out at about 2,000 qubits, and even that sounds quite optimistic.

Apparently, driving this scalability mania (and also a good deal of the field’s funding) are the good people at the NSA and other deep spook agencies around the world. The factorization-cyrpto breakers seem to want to have at least a few thousand qubits to do meaningful work. To put that numerical goal in perspective, bear in mind that a quantum computer’s power increases exponentially. In general, L qubits can store 2L numbers at once. Thus, three qubits can store 8 different numbers at once, four qubits can store 16 numbers at once, and on up it goes. Now imagine the computing power in a system having several thousand qubits!

But quantum computer acting on even just hundreds of qubits is capable in principle of performing tasks that could never be performed by conventional digital computers. For example, a classical computer requires a time proportional to N to search for a particular item in a list of N items, whereas a quantum computer can perform the search in a time proportional to the square root of N.

Even with several K qubits pumping exponentially away in a system that stays coherent for hours on end, you still have the problem of error correction. A quantum computer is the quintessential black go-boom box. Any type of disturbing, i.e., interfering behavior, will cause the incredibly fragile contraption to stop working in a snit of decoherent quantum mechanics pique. So how do you know or ensure that the qubit results you have been able to ever so slyly pull out are correct? Once again, it was left to Peter Shor of ATT Bell labs to set the quantum world on its ear. In 1995 he announced his discovery of an algorithm that achieved reliable quantum error correcting.

Fundamentally, Shor’s new algorithm took advantage of the fact that it only dealt with the "noise" inherent in the quantum system and completely disregarded the signal, or information. By subtracting out the noise, you are left with a reliable result. His algorithm proved that it was possible to restore the quantum state to its original form without any contaminating errors creeping in. Moreover, to almost everyone’s surprise and research delight, he showed that you could pull off this rabbit in a quantum hat trick by correcting individual qubits. Up until Shor showed otherwise, it had been assumed that measuring such individual qubit operations would contaminate and crash the entire system.

Almost immediately after Shor’s breakthrough was announced, it was found that Andrew Steane of Oxford had independently discovered another error correction scheme. Since 1995, a slew of ever-refined quantum error correcting methodologies has been discovered, most of which build on Shor and Steane’s original insights.

Fig. 8. The secret of quantum error correction is to encode a quantum state in a cleverly selected subspace of a larger vector space. Errors that move the vector in a direction perpendicular to the code subspace can easily be detected and reversed, while errors parallel to the code subspace cause trouble. But if the code subspace is carefully chosen, typical errors will have only a very small component along the code subspace, and encoded information will be well protected. Entanglement is an essential feature of quantum error-correcting codes. (source, NSF)

It is now 2001, and we have more than six years experience in designing, building and operating quantum computers, of many different stripes. And almost certainly, better materials and technologies than NMR, quantum dots, and ion traps will soon be appearing, for such is the nature of scientific discovery these days. So what will you do when this wonderfully weird thing finally lands in your palm? Cracking crypto codes may be a good time for some, but that’s still a pretty limited (if potentially immensely rewarding) field of activity. Current wisdom has it that algorithms that work in an iterative fashion with many intermediary steps, for example weather forecasting, will not be the province of quantum computers and we will still need conventional, "classic" systems to do that kind of algorithmic work.

But maybe not, as apparently human beings routinely use quantum computing to perform the widest imaginable variety of tasks. It seems your brain is also a quantum computer! For example, a new method for doing a MRI of the brain is based on the detection of quantum coherence. The new MRI technique was recently developed at Princeton University, University of Pennsylvania, and the University of Minnesota. The methods, intermolecular multiple quantum coherence "IMQC" and intermolecular zero quantum coherence "IZQC", were created to enhance the contrast of a conventional MRI and offer much greater resolution. The MRI magnet and excitation techniques externally induce quantum coherence in the brain. Quantum dipole couplings of proton spins in two molecules (e.g. water, protein) separated by distances ranging from 10 microns to one millimeter yield detectable MRI signals under certain conditions. While it is true this coherence is an artifact produced from outside the brain by the MRI system, that your wet and noisy brain can support detectable quantum coherence of any kind comes as a shock to most people, including many well-established researchers. It also supports the growing idea that our brain may be quite capable of naturally producing quantum coherence.

This scientific evidence could indicate that coherent quantum processing is naturally occurring all the time in the brain. And so, incredibly, the key to unlocking the secrets of reliable quantum computing -- and keeping the lights on -- may have been not under, but on top of our noses all along.

Copyright 2001, All Rights Reserve

21st, The VXM Network, http://www.vxm.com

s