NSA Building A $2 Billion Quantum Computer Spy Center?

The NSA is building a $2 billion spy center after reporting an enormous breakthrough in encryption cracking, which may be a massive Quantum computer center.

The National Security Center is building a highly fortified $2 Billion highly top secret complex simply named the “Utah Data Center.”

As wired reports (more below)

Flowing through its servers and routers and stored in near-bottomless databases will be all forms of communication, including the complete contents of private emails, cell phone calls, and Google searches, as well as all sorts of personal data trails—parking receipts, travel itineraries, bookstore purchases, and other digital “pocket litter.” It is, in some measure, the realization of the “total information awareness” program created during the first term of the Bush administration—an effort that was killed by Congress in 2003 after it caused an outcry over its potential for invading Americans’ privacy.

The news has conspiracy theorists, IT experts, and mathematicians abuzz with speculation that the NSA is building a quantum computer capable of cracking any type of encryption available today.

To be technically correct, there are known methods to break all of today’s known encryption methods.

Instead of creating unbreakable cryptograms, modern cryptologists rely on the proposition that today’s methods to break today’s most advanced encryption algorithms using any forecasted advancement in computer processing power way into the future would take more time than the life of the universe.

But Quantum computers, which were once only theoretical  scientists have in fact already been created.

Today’s quantum computers are however are rather limited in their current known implementations, which are claim the ability to crack at the most a 200 million combination Soduku puzzle.

Better quantum computers than those in existence today can crack any encryption that exists today an algorithm called  Shor’s algorithm.

Beyond just being able to crack cryptosystems, many in the scientific community speculation that quantum computing may be the bridge to obtain true artificial intelligence and when coupled with quantum memory create an a truly all-knowing omniscient AI network.

You’ll learn more about Quantum computers below, but first let’s review the work the NSA is doing followed by recent technology breakthroughs.

NSA Building A $2 Billion Quantum Computing Center?

Cryptogon reports :

Bamford Claims NSA Has Made “An Enormous Breakthrough” in Cryptanalysis

Well, it has been the $64,000 question for a couple of decades: Can NSA break something like PGP?

While there might be other black world technologies that could be up to the task (there’s no way to know), what we do know is that a practical quantum computing capability would be, for all intents and purposes, the master key.

I’m pretty confident that NSA has this capability and here’s why: IBM Breakthrough May Make Practical Quantum Computer 15 Years Away Instead of 50. There is no hard constant that one can point to when considering how much more advanced black world technologies are than what we think of as state of the art, but if IBM is 15 years away from building a useful quantum computer, it’s not a stretch to assume NSA has that capability already, or is close to having it.

Bamford lays out a narrative below about the “enormous breakthrough,” but, at the end of the day, it’s conventional computers. There’s no mention quantum computers, or even the far less “out there” photonic systems.

Is Bamford’s piece a limited hangout?

Maybe, but it makes for interesting reading in any event.

Note: For some reason, Bamford refers to Mark Klein as, “A whistle-blower,” without naming him. Because of Mark Klein, we know, for sure, that the mass intercepts are happening, how NSA is doing it, the equipment involved, etc. So, thanks, Mark Klein. Heroes have names on Cryptogon.

Source: Cryptogon

Cryptogon then goes on to quote wired.

The NSA Is Building the Country’s Biggest Spy Center (Watch What You Say)

Under construction by contractors with top-secret clearances, the blandly named Utah Data Center is being built for the National Security Agency. A project of immense secrecy, it is the final piece in a complex puzzle assembled over the past decade. Its purpose: to intercept, decipher, analyze, and store vast swaths of the world’s communications as they zap down from satellites and zip through the underground and undersea cables of international, foreign, and domestic networks. The heavily fortified $2 billion center should be up and running in September 2013. Flowing through its servers and routers and stored in near-bottomless databases will be all forms of communication, including the complete contents of private emails, cell phone calls, and Google searches, as well as all sorts of personal data trails—parking receipts, travel itineraries, bookstore purchases, and other digital “pocket litter.” It is, in some measure, the realization of the “total information awareness” program created during the first term of the Bush administration—an effort that was killed by Congress in 2003 after it caused an outcry over its potential for invading Americans’ privacy.

 

But “this is more than just a data center,” says one senior intelligence official who until recently was involved with the program. The mammoth Bluffdale center will have another important and far more secret role that until now has gone unrevealed. It is also critical, he says, for breaking codes. And code-breaking is crucial, because much of the data that the center will handle—financial information, stock transactions, business deals, foreign military and diplomatic secrets, legal documents, confidential personal communications—will be heavily encrypted. According to another top official also involved with the program, the NSA made an enormous breakthrough several years ago in its ability to cryptanalyze, or break, unfathomably complex encryption systems employed by not only governments around the world but also many average computer users in the US. The upshot, according to this official: “Everybody’s a target; everybody with communication is a target.”

…

In the process—and for the first time since Watergate and the other scandals of the Nixon administration—the NSA has turned its surveillance apparatus on the US and its citizens. It has established listening posts throughout the nation to collect and sift through billions of email messages and phone calls, whether they originate within the country or overseas. It has created a supercomputer of almost unimaginable speed to look for patterns and unscramble codes. Finally, the agency has begun building a place to store all the trillions of words and thoughts and whispers captured in its electronic net. And, of course, it’s all being done in secret. To those on the inside, the old adage that NSA stands for Never Say Anything applies more than ever.

…

The data stored in Bluffdale will naturally go far beyond the world’s billions of public web pages. The NSA is more interested in the so-called invisible web, also known as the deep web or deepnet—data beyond the reach of the public. This includes password-protected data, US and foreign government communications, and noncommercial file-sharing between trusted peers. “The deep web contains government reports, databases, and other sources of information of high value to DOD and the intelligence community,” according to a 2010 Defense Science Board report. “Alternative tools are needed to find and index data in the deep web … Stealing the classified secrets of a potential adversary is where the [intelligence] community is most comfortable.” With its new Utah Data Center, the NSA will at last have the technical capability to store, and rummage through, all those stolen secrets. The question, of course, is how the agency defines who is, and who is not, “a potential adversary.”

…

According to Binney—who has maintained close contact with agency employees until a few years ago—the taps in the secret rooms dotting the country are actually powered by highly sophisticated software programs that conduct “deep packet inspection,” examining Internet traffic as it passes through the 10-gigabit-per-second cables at the speed of light.

The software, created by a company called Narus that’s now part of Boeing, is controlled remotely from NSA headquarters at Fort Meade in Maryland and searches US sources for target addresses, locations, countries, and phone numbers, as well as watch-listed names, keywords, and phrases in email. Any communication that arouses suspicion, especially those to or from the million or so people on agency watch lists, are automatically copied or recorded and then transmitted to the NSA.

The scope of surveillance expands from there, Binney says. Once a name is entered into the Narus database, all phone calls and other communications to and from that person are automatically routed to the NSA’s recorders. “Anybody you want, route to a recorder,” Binney says. “If your number’s in there? Routed and gets recorded.” He adds, “The Narus device allows you to take it all.” And when Bluffdale is completed, whatever is collected will be routed there for storage and analysis.

According to Binney, one of the deepest secrets of the Stellar Wind program—again, never confirmed until now—was that the NSA gained warrantless access to AT&T’s vast trove of domestic and international billing records, detailed information about who called whom in the US and around the world. As of 2007, AT&T had more than 2.8 trillion records housed in a database at its Florham Park, New Jersey, complex.

Verizon was also part of the program, Binney says, and that greatly expanded the volume of calls subject to the agency’s domestic eavesdropping. “That multiplies the call rate by at least a factor of five,” he says. “So you’re over a billion and a half calls a day.” (Spokespeople for Verizon and AT&T said their companies would not comment on matters of national security.)

After he left the NSA, Binney suggested a system for monitoring people’s communications according to how closely they are connected to an initial target. The further away from the target—say you’re just an acquaintance of a friend of the target—the less the surveillance. But the agency rejected the idea, and, given the massive new storage facility in Utah, Binney suspects that it now simply collects everything. “The whole idea was, how do you manage 20 terabytes of intercept a minute?” he says. “The way we proposed was to distinguish between things you want and things you don’t want.” Instead, he adds, “they’re storing everything they gather.” And the agency is gathering as much as it can.

Once the communications are intercepted and stored, the data-mining begins. “You can watch everybody all the time with data- mining,” Binney says. Everything a person does becomes charted on a graph, “financial transactions or travel or anything,” he says. Thus, as data like bookstore receipts, bank statements, and commuter toll records flow in, the NSA is able to paint a more and more detailed picture of someone’s life.

The NSA also has the ability to eavesdrop on phone calls directly and in real time. According to Adrienne J. Kinne, who worked both before and after 9/11 as a voice interceptor at the NSA facility in Georgia, in the wake of the World Trade Center attacks “basically all rules were thrown out the window, and they would use any excuse to justify a waiver to spy on Americans.” Even journalists calling home from overseas were included. “A lot of time you could tell they were calling their families,” she says, “incredibly intimate, personal conversations.” Kinne found the act of eavesdropping on innocent fellow citizens personally distressing. “It’s almost like going through and finding somebody’s diary,” she says.

…

Sitting in a restaurant not far from NSA headquarters, the place where he spent nearly 40 years of his life, Binney held his thumb and forefinger close together. “We are, like, that far from a turnkey totalitarian state,” he says.

…

Meanwhile, over in Building 5300, the NSA succeeded in building an even faster supercomputer. “They made a big breakthrough,” says another former senior intelligence official, who helped oversee the program. The NSA’s machine was likely similar to the unclassified Jaguar, but it was much faster out of the gate, modified specifically for cryptanalysis and targeted against one or more specific algorithms, like the AES. In other words, they were moving from the research and development phase to actually attacking extremely difficult encryption systems. The code-breaking effort was up and running.

The breakthrough was enormous, says the former official, and soon afterward the agency pulled the shade down tight on the project, even within the intelligence community and Congress. “Only the chairman and vice chairman and the two staff directors of each intelligence committee were told about it,” he says. The reason? “They were thinking that this computing breakthrough was going to give them the ability to crack current public encryption.”

Source:Wired

 

Recent Quantum Science Breakthroughs

Science Daily reports the single atom transistor.

Single-Atom Transistor Is End of Moore’s Law; May Be Beginning of Quantum Computing

A controllable transistor engineered from a single phosphorus atom has been developed by researchers at the University of New South Wales, Purdue University and the University of Melbourne. The atom, shown here in the center of an image from a computer model, sits in a channel in a silicon crystal. The atomic-sized transistor and wires might allow researchers to control gated qubits of information in future quantum computers. (Credit: Purdue University image)

ScienceDaily (Feb. 19, 2012) — The smallest transistor ever built — in fact, the smallest transistor that can be built — has been created using a single phosphorus atom by an international team of researchers at the University of New South Wales, Purdue University and the University of Melbourne.

The single-atom device was described Sunday (Feb. 19) in a paper in the journal Nature Nanotechnology.

Michelle Simmons, group leader and director of the ARC Centre for Quantum Computation and Communication at the University of New South Wales, says the development is less about improving current technology than building future tech.

“This is a beautiful demonstration of controlling matter at the atomic scale to make a real device,” Simmons says. “Fifty years ago when the first transistor was developed, no one could have predicted the role that computers would play in our society today. As we transition to atomic-scale devices, we are now entering a new paradigm where quantum mechanics promises a similar technological disruption. It is the promise of this future technology that makes this present development so exciting.”

[...]

The single-atom transistor does have one serious limitation: It must be kept very cold, at least as cold as liquid nitrogen, or minus 391 degrees Fahrenheit (minus 196 Celsius).

“The atom sits in a well or channel, and for it to operate as a transistor the electrons must stay in that channel,” Klimeck says. “At higher temperatures, the electrons move more and go outside of the channel. For this atom to act like a metal you have to contain the electrons to the channel.

“If someone develops a technique to contain the electrons, this technique could be used to build a computer that would work at room temperature. But this is a fundamental question for this technology.”

[...]

Source: Science Daily

Science Daily reports the two atom radio.

World’s Smallest Radio Stations: Two Molecules Communicate Via Single Photons

Artist’s view of a single molecule sending a stream of single photons to a second molecule at a distance, in quantum analogy to the radio communication between two stations. (Credit: Robert Lettow)

ScienceDaily (Feb. 28, 2012) — We know since the dawn of modern physics that although events in our everyday life can be described by classical physics, the interaction of light and matter is down deep governed by the laws of quantum mechanics. Despite this century-old wisdom, accessing truly quantum mechanical situations remains nontrivial, fascinating and noteworthy even in the laboratory. Recently, interest in this area has been boosted beyond academic curiosity because of the potential for more efficient and novel forms of information processing.

n one of the most basic proposals, a single atom or molecule acts as a quantum bit that processes signals that have been delivered via single photons. In the past twenty years scientists have shown that single molecules can be detected and single photons can be generated. However, excitation of a molecule with a photon had remained elusive because the probability that a molecule sees and absorbs a photon is very small. As a result, billions of photons per second are usually impinged on a molecule to obtain a signal from it.

[...]

One common way to get around this difficulty in atomic physics has been to build a cavity around the atom so that a photon remains trapped for long enough times to yield a favorable interaction probability. Scientists at ETH Zurich and Max Planck Institute for the Science of Light in Erlangen have now shown that one can even interact a flying photon with a single molecule. Among many challenges in the way of performing such an experiment is the realization of a suitable source of single photons, which have the proper frequency and bandwidth. Although one can purchase lasers at different colors and specifications, sources of single photons are not available on the market.

So a team of scientists led by Professor Vahid Sandoghdar made its own. To do this, they took advantage of the fact that when an atom or molecule absorbs a photon it makes a transition to a so-called excited state. After a few nanoseconds (one thousand millionth of a second) this state decays to its initial ground state and emits exactly one photon. In their experiment, the group used two samples containing fluorescent molecules embedded in organic crystals and cooled them to about 1.5 K (-272 °C). Single molecules in each sample were detected by a combination of spectral and spatial selection.

[...]

Source: Science Daily

Quantum Computers And Quantum Algorithms

From How Stuff works, a layman’s explanation of Quantum computing, with another explanation and an overview of Shor’s algorithm followin:

How Quantum Computers Work

Will we ever have the amount of computing power we need or want? If, as Moore’s Law states, the number of transistors on a microprocessor continues to double every 18 months, the year 2020 or 2030 will find the circuits on a microprocessor measured on an atomic scale. And the logical next step will be to create quantum computers, which will harness the power of atoms and molecules to perform memory and processing tasks. Quantum computers have the potential to perform certain calculations significantly faster than any silicon-based computer.

Scientists have already built basic quantum computers that can perform certain calculations; but a practical quantum computer is still years away. In this article, you’ll learn what a quantum computer is and just what it’ll be used for in the next era of computing.

The Bloch sphere is a representation of a qubit, the fundamental building block of quantum computers.

Defining the Quantum Computer

The Turing machine, developed by Alan Turing in the 1930s, is a theoretical device that consists of tape of unlimited length that is divided into little squares. Each square can either hold a symbol (1 or 0) or be left blank. A read-write device reads these symbols and blanks, which gives the machine its instructions to perform a certain program. Does this sound familiar? Well, in a quantum Turing machine, the difference is that the tape exists in a quantum state, as does the read-write head. This means that the symbols on the tape can be either 0 or 1 or a superposition of 0 and 1; in other words the symbols are both 0 and 1 (and all points in between) at the same time. While a normal Turing machine can only perform one calculation at a time, a quantum Turing machine can perform many calculations at once.

Today’s computers, like a Turing machine, work by manipulating bits that exist in one of two states: a 0 or a 1. Quantum computers aren’t limited to two states; they encode information as quantum bits, or qubits, which can exist in superposition. Qubits represent atoms, ions, photons or electrons and their respective control devices that are working together to act as computer memory and a processor. Because a quantum computer can contain these multiple states simultaneously, it has the potential to be millions of times more powerful than today’s most powerful supercomputers.

This superposition of qubits is what gives quantum computers their inherent parallelism. According to physicist David Deutsch, this parallelism allows a quantum computer to work on a million computations at once, while your desktop PC works on one. A 30-qubit quantum computer would equal the processing power of a conventional computer that could run at 10 teraflops (trillions of floating-point operations per second). Today’s typical desktop computers run at speeds measured in gigaflops (billions of floating-point operations per second).

Quantum computers also utilize another aspect of quantum mechanics known as entanglement. One problem with the idea of quantum computers is that if you try to look at the subatomic particles, you could bump them, and thereby change their value. If you look at a qubit in superposition to determine its value, the qubit will assume the value of either 0 or 1, but not both (effectively turning your spiffy quantum computer into a mundane digital computer). To make a practical quantum computer, scientists have to devise ways of making measurements indirectly to preserve the system’s integrity. Entanglement provides a potential answer. In quantum physics, if you apply an outside force to two atoms, it can cause them to become entangled, and the second atom can take on the properties of the first atom. So if left alone, an atom will spin in all directions. The instant it is disturbed it chooses one spin, or one value; and at the same time, the second entangled atom will choose an opposite spin, or value. This allows scientists to know the value of the qubits without actually looking at them.

[....]

Today’s Quantum Computers

Quantum computers could one day replace silicon chips, just like the transistor once replaced the vacuum tube. But for now, the technology required to develop such a quantum computer is beyond our reach. Most research in quantum computing is still very theoretical.

The most advanced quantum computers have not gone beyond manipulating more than 16 qubits, meaning that they are a far cry from practical application. However, the potential remains that quantum computers one day could perform, quickly and easily, calculations that are incredibly time-consuming on conventional computers. Several key advancements have been made in quantum computing in the last few years. Let’s look at a few of the quantum computers that have been developed.

1998

Los Alamos and MIT researchers managed to spread a single qubit across three nuclear spins in each molecule of a liquid solution of alanine (an amino acid used to analyze quantum state decay) or trichloroethylene (a chlorinated hydrocarbon used for quantum error correction) molecules. Spreading out the qubit made it harder to corrupt, allowing researchers to use entanglement to study interactions between states as an indirect method for analyzing the quantum information.

2000

In March, scientists at Los Alamos National Laboratory announced the development of a 7-qubit quantum computer within a single drop of liquid. The quantum computer uses nuclear magnetic resonance (NMR) to manipulate particles in the atomic nuclei of molecules of trans-crotonic acid, a simple fluid consisting of molecules made up of six hydrogen and four carbon atoms. The NMR is used to apply electromagnetic pulses, which force the particles to line up. These particles in positions parallel or counter to the magnetic field allow the quantum computer to mimic the information-encoding of bits in digital computers.

Researchers at IBM-Almaden Research Center developed what they claimed was the most advanced quantum computer to date in August. The 5-qubit quantum computer was designed to allow the nuclei of five fluorine atoms to interact with each other as qubits, be programmed by radio frequency pulses and be detected by NMR instruments similar to those used in hospitals (see How Magnetic Resonance Imaging Works for details). Led by Dr. Isaac Chuang, the IBM team was able to solve in one step a mathematical problem that would take conventional computers repeated cycles. The problem, called order-finding, involves finding the period of a particular function, a typical aspect of many mathematical problems involved in cryptography.

2001

Scientists from IBM and Stanford University successfully demonstrated Shor’s Algorithm on a quantum computer. Shor’s Algorithm is a method for finding the prime factors of numbers (which plays an intrinsic role in cryptography). They used a 7-qubit computer to find the factors of 15. The computer correctly deduced that the prime factors were 3 and 5.

2005

The Institute of Quantum Optics and Quantum Information at the University of Innsbruck announced that scientists had created the first qubyte, or series of 8 qubits, using ion traps.

2006

Scientists in Waterloo and Massachusetts devised methods for quantum control on a 12-qubit system. Quantum control becomes more complex as systems employ more qubits.

2007

Canadian startup company D-Wave demonstrated a 16-qubit quantum computer. The computer solved a sudoku puzzle and other pattern matching problems. The company claims it will produce practical systems by 2008. Skeptics believe practical quantum computers are still decades away, that the system D-Wave has created isn’t scaleable, and that many of the claims on D-Wave’s Web site are simply impossible (or at least impossible to know for certain given our understanding of quantum mechanics).

If functional quantum computers can be built, they will be valuable in factoring large numbers, and therefore extremely useful for decoding and encoding secret information. If one were to be built today, no information on the Internet would be safe. Our current methods of encryption are simple compared to the complicated methods possible in quantum computers. Quantum computers could also be used to search large databases in a fraction of the time that it would take a conventional computer. Other applications could include using quantum computers to study quantum mechanics, or even to design other quantum computers.

[...]

Source:How Stuff Works

More on Quantum computing, including the code cracking algorithm that threatens to decimate all of today’s encryption methods – Shor’s Algorithm:

A Brief History of Quantum Computing

By Simon Bone and Matias CastroStrange as it sounds, the computer of tomorrow could be built around a cup of coffee. The caffeine molecule is just one of the possible building blocks of a ‘quantum computer’, a new type of computer that promises to provide mind boggling performance that can break secret codes in a matter of seconds.

Table of contents

    1. Introduction
        1.1 Quantum computer basics
        1.2 The pitfall of quantum computing - decoherence
        1.3 Getting a result
    2. Theory of universal computation
        2.1 Heating up over lost information
        2.2 The universal quantum computer
        2.3 Artificial intelligence
    3. Building a quantum computer
        3.1 Quantum dots
        3.2 Computing liquids
    4. Applications of quantum computers
        4.1 Shor's algorithm
            - Shor's algorithm - An example
        4.2 Grover's algorithm
        4.3 Simulation of quantum mechanical systems
    5. Quantum communication
        5.1 How quantum communication works
        5.2 Quantum bit commitment
    6. Current progress & future prospects
    7. Conclusion
    8. Glossary of terms
    9. References
        9.1 Books
        9.1 People
        9.2 Magazine articles
        9.3 Web pages

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1. Introduction

Every so often a new technology surfaces that enables the bounds of computer performance to be pushed further forwards. From the introduction of valve technology through to the continuing development of VLSI designs, the pace of technological advancement has remained relentless. Lately, the key to improving computer performance has been the reduction of size in the transistors used in modern processors [18]. This continual reduction however, cannot continue for much longer. If the transistors become much smaller, the strange effects of quantum mechanics will begin to hinder their performance. It would therefore seem that these effects present a fundamental limit to our computer technology, or do they?

In 1982, the Nobel prize-winning physicist Richard Feynman thought up the idea of a ‘quantum computer’, a computer that uses the effects of quantum mechanics to its advantage [23]. For some time, the notion of a quantum computer was primarily of theoretical interest only, but recent developments have bought the idea to everybody’s attention. One such development was the invention of an algorithm to factor large numbers on a quantum computer, by Peter Shor (Bell Laboratories). By using this algorithm, a quantum computer would be able to crack codes much more quickly than any ordinary (or classical) computer could. In fact a quantum computer capable of performing Shor’s algorithm would be able to break current cryptography techniques in a matter of seconds. With the motivation provided by this algorithm, the topic of quantum computing has gathered momentum and researchers around the world are racing to be the first to create a practical quantum computer.

1.1 Quantum computer basics

In the classical model of a computer, the most fundamental building block, the bit, can only exist in one of two distinct states, a 0 or a 1. In a quantum computer the rules are changed [9],[10],[23]. Not only can a ‘quantum bit’, usually referred to as a ‘qubit’, exist in the classical 0 and 1 states, it can also be in a coherent superposition of both. When a qubit is in this state it can be thought of as existing in two universes, as a 0 in one universe and as a 1 in the other. An operation on such a qubit effectively acts on both values at the same time. The significant point being that by performing the single operation on the qubit, we have performed the operation on two different values. Likewise, a two-qubit system would perform the operation on 4 values, and a three-qubit system on eight. Increasing the number of qubits therefore exponentially increases the ‘quantum parallelism’ we can obtain with the system. With the correct type of algorithm it is possible to use this parallelism to solve certain problems in a fraction of the time taken by a classical computer.

1.2 The pitfall of quantum computing – decoherence

The very thing that makes quantum computing so powerful, its reliance on the bizarre subatomic goings-on governed by the rules of quantum mechanics, also makes it very fragile and difficult to control. For example, consider a qubit that is in the coherent state. As soon as it measurable interacts with the environment it will decohere and fall into one of the two classical states. This is the problem of decoherence and is a stumbling block for quantum computers as the potential power of quantum computers depends on the quantum parallelism brought about by the coherent state [14]. This problem is compounded by the fact that even looking at a qubit can cause it to decohere, making the process of obtaining a solution from a quantum computer just as difficult as performing the calculation itself.

1.3 Getting a result

Once a calculation that makes use of quantum parallelism has been performed, there will be any number of different results in different universes. The fact that the results are not in this universe means that we can only obtain a solution to a computation by looking at the interference of the various results. It is important to note that looking at the result (or any intermediate state) of a quantum computer prevents any further interference between the different versions from taking place, i.e. prevents any useful quantum computations from continuing. Such interference is best illustrated with a simple example; In Young’s two slit experiment, light is shone through two parallel slits onto a screen. The resulting pattern of light and dark fringes displayed on the screen is a result of constructive and destructive interference. In a similar way, the results from each universe’s calculation will constructively and destructively interfere to give a measurable result. This result has a different significance for different algorithms, and can be used to deduce the solution to the problem in hand (For an example see Shor’s algorithm – An example).

Figure 1 – Young’s two slit experiment demonstrates interference of photons. 

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2. Theory of universal computation

One thing that all computers have in common, from Charles Babbage’s analytical engine (1936) to Pentium(tm) based PC’s, is the theory of classical computation as described by the work of Alan Turing [3]. In essence, Turing’s work describes the idea of the universal turing machine, a very simple model of a computer that can be programmed to perform any operation that “would naturally be considered to be computable”. All computers are essentially implementations of a universal turing machine. They are all functionally equivalent and although some may be quicker, larger or more expensive than others, they can all perform the same set of computational tasks.

2.1 Heating up over lost information

A great deal of time has been spent on investigating whether quantum theory places any fundamental limits on computing machines. As a result, it is now believed that physics does not place any absolute limits on the speed, reliability or memory capacity of computing machines. One consideration that needs to be made however, concerns the information that may be ‘lost’ in a computation [23]. In order for a computer to run arbitrarily fast, its operation must be reversible (i.e. it’s inputs must be entirely deducible from its outputs). This is because irreversible computations involve a ‘loss’ of information which can be equated to a loss in heat, and thus the restricted ability of the system to dissipate heat will in turn limit the performance of the computer. An example of information being lost can be seen in an ordinary AND gate. An AND gate has two inputs and only one output, which means that in the process of moving from the input to the output of the gate, we loose one bit of information.

In 1976, Charles Bennett proved that it is possible to build a universal computer entirely from reversible gates, and that expressing a program in terms of primitive reversible operations does not significantly slow it down. A suitable universal and reversible gate with which we could build a computer is the Toffoli gate (see Figure x).

Figure 2 – The inputs of a Toffoli gate are entirely deducible from the outputs. 

2.2 The universal quantum computer

The Church-Turing principle – “There exists or can be built a universal computer that can be programmed to perform any computational task that can be performed by any physical object”.

A number of key advances have been made in the theory of quantum computation, the first being the discovery that a simple class of ‘universal simulator’ can mimic the behaviour of any finite physical object, by Richard Feynman in 1982. David Albert made the second discovery in 1984 when he described a ‘self measuring quantum automaton’ that could perform tasks that no classical computer can simulate. By instructing the automaton to measure itself, it can obtain ‘subjective’ information that is absolutely inaccessible by measurement from the outside. The final and perhaps most important discovery was made by David Deutsch in 1989, he proved that all the computational capabilities of any finite machine obeying the laws of quantum computation are contained in a single machine, a ‘universal quantum computer’. Such a computer could be built from the quantum equivalent of the Toffoli gate and by adding a few extra operations that can bring about linear superpositions of 0 and 1 states, the universal quantum computer is complete. This discovery requires a slight alteration to the Church-Turing principle – “There exists or can be built a universal quantum computer that can be programmed to perform any computational task that can be performed by any physical object”.

2.3 Artificial intelligence

The theories of quantum computation have some interesting implications in the world of artificial intelligence. The debate about whether a computer will ever be able to be truly artificially intelligent has been going on for years and has been largely based on philosophical arguments. Those against the notion suggest that the human mind does things that aren’t, even in principle, possible to perform on a Turing machine.

The theory of quantum computation allows us to look at the question of consciousness from a slightly different perspective. The first thing to note is that every physical object, from a rock to the universe as a whole, can be regarded as a quantum computer and that any detectable physical process can be considered a computation. Under these criteria, the brain can be regarded as a computer and consciousness as a computation. The next stage of the argument is based in the Church-Turing principle and states that since every computer is functionally equivalent and that any given computer can simulate any other, therefore, it must be possible to simulate conscious rational thought using a quantum computer.

Some believe that quantum computing could well be the key to cracking the problem of artificial intelligence but others disagree. Roger Penrose of Oxford University believes that consciousness may require an even more exotic (and as yet unknown) physics.

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3. Building a quantum computer

A quantum computer is nothing like a classical computer in design; you can’t for instance build one from transistors and diodes. In order to build one, a new type of technology is needed, a technology that enables ‘qubits’ to exist as coherent superpositions of 0 and 1 states. The best method of achieving this goal is still unknown, but many methods are being experimented with and are proving to have varying degrees of success.

3.1 Quantum dots

An example of an implementation of the qubit is the ‘quantum dot’ which is basically a single electron trapped inside a cage of atoms [7]. When the dot is exposed to a pulse of laser light of precisely the right wavelength and duration, the electron is raised to an excited state: a second burst of laser light causes the electron to fall back to its ground state. The ground and excited states of the electron can be thought of as the 0 and 1 states of the qubit and the application of the laser light can be regarded as a controlled NOT function as it knocks the qubit from 0 to 1 or from ‘ to 0.

If the pulse of laser light is only half the duration of that required for the NOT function, the electron is placed in a superposition of both ground and excited states simultaneously, this being the equivalent of the coherent state of the qubit. More complex logic functions can be modelled using quantum dots arranged in pairs. It would therefore seem that quantum dots are a suitable candidate for building a quantum computer. Unfortunately there are a number of practical problems that are preventing this from happening:

• The electron only remains in its excited state for about a microsecond before it falls to the ground state. Bearing in mind that the required duration of each laser pulse is around 1 nanosecond, there is a limit to the number of computational steps that can be made before information is lost.
• Constructing quantum dots is a very difficult process because they are so small. A typical quantum dot measures just 10 atoms (1 nanometer) across. The technology needed to build a computer from these dots doesn’t yet exist.
• To avoid cramming thousands of lasers into a tiny space, quantum dots could be manufactured so that they respond to different frequencies of light. A laser that could reliably retune itself would thus selectively target different groups of quantum dots with different frequencies of light. This again, is another technology that doesn’t yet exist.

3.2 Computing liquids

Quantum dots are not the only implementation of qubits that have been experimented with. Other techniques have attempted to use individual atoms or the polarisation of laser light as the information medium. The common problem with these techniques is decoherence. Attempts at shielding the experiments from their surroundings, by for instance cooling them to within a thousandth of a degree of absolute zero, have proven to have had limited success at reducing the effects of this problem.

The latest development in quantum computing takes a radical new approach [16]. It drops the assumption that the quantum medium has to be tiny and isolated from its surroundings and instead uses a sea of molecules to store the information. When held in a magnetic field, each nucleus within a molecule spins in a certain direction, which can be used to describe its state; spinning upwards can signify a 1 and spinning down, a 0. Nuclear Magnetic Resonance (NMR) techniques can be used to detect these spin states and bursts of specific radio waves can flip the nuclei from spinning up (1) to spinning down (0) and vice-versa.

The quantum computer in this technique is the molecule itself and its qubits are the nuclei within the molecule. This technique does not however use a single molecule to perform the computations; it instead uses a whole ‘mug’ of liquid molecules. The advantage of this is that even though the molecules of the liquid bump into one another, the spin states of the nuclei within each molecule remain unchanged. Decoherence is still a problem, but the time before the decoherence sets in is much longer than in any other technique so far. Researchers believe a few thousand primitive logic operations should be possible within time it takes the qubits to decohere.

Dr. Gershenfield from the Massachusetts Institute of Technology, is one of the pioneers of the computing liquid technique. His research team has already been able to add one and one together, a simple task which is way beyond any of the other techniques being investigated. The key to being able to perform more complex tasks is to have more qubits but this requires more complex molecules with a greater number of nuclei, the caffeine molecule being a possible candidate. Whatever the molecule, the advancement to 10 qubit systems is apparently straightforward. Such a system, Dr. Gershenfield hopes, will be possible by the end of this year, and should be capable of factoring the number 15.

Advancing beyond a 10-qubit system may prove to be more difficult. In a given sample of ‘computing liquid’ there will be a roughly even number of up and down spin states but a small excess of spin in one direction will exist. It is the signal from this small amount of extra spin, behaving as if it were a single molecule that can be detected and manipulated to perform calculations while the rest of the spins will effectively cancel each other out. This signal is extremely weak and grows weaker by a factor of roughly 2 for every qubit that is added. This imposes a limit on the number of qubits a system may have as the readable output will be harder to detect.

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4. Applications of quantum computers

It is important to note that a quantum computer will not necessarily outperform a classical computer at all computational tasks. Multiplication for example, will not be performed any quicker on a quantum computer than it could be done on a similar classical computer. In order for a quantum computer to show its superiority it needs to use algorithms that exploit its power of quantum parallelism. Such algorithms are difficult to formulate, to date the most significant theorised being Shor’s algorithm and Grover’s algorithm. By using good these algorithms a quantum computer will be able to outperform classical computers by a significant margin. For example, Shor’s algorithm allows extremely quick factoring of large numbers, a classical computer can be estimated at taking 10 million billion billion years to factor a 1000 digit number, where as a quantum computer would take around 20 minutes.

4.1 Shor’s algorithm

This is an algorithm invented by Peter Shor in 1995 that can be used to quickly factorise large numbers. [7],[22]If it is ever implemented it will have a profound effect on cryptography, as it would compromise the security provided by public key encryption (such as RSA).

At Risk – Public Key Encryption This is currently the most commonly used method for sending encrypted data [3]. It works by using two keys, one public and one private. The public key is used to encrypt the data, while the private key is used to decrypt the data. The public key can be easily derived from the private key but not visa versa. However, an eavesdropper who has acquired your public key can in principle calculate your private key as they are mathematically related. In order to do so it is necessary to factorise the public key, a task that is considered to be intractable. For example, multiplying 1234 by 3433 is easy to work out, but calculating the factors of 4236322 is not so easy. The difficulty of factorising a number grows rapidly with additional digits. It took 8 months and 1600 Internet users to crack RSA 129 (a number with 129 digits). Cryptographers thought that more digits could be added to the key to combat increasing performance in computers (it would take longer than the age of the universe to calculate RSA 140). However, using a quantum computer, which is running Shor’s algorithm, the number of digits in the key has little effect on the difficulty of the problem. Cracking RSA 140 would take a matter of seconds.

Shor’s algorithm – An example

The purpose of this section is to illustrate the basic steps involved in Shor’s Algorithm. In order to keep the example relatively easy to follow we will consider the problem of finding the prime factors of the number 15. Since the Algorithm consists of three key steps, this explanation will be presented in 3 stages…

Stage 1

The first stage of the algorithm is to place a memory register into a coherent superposition of all its possible states. The letter ‘Q’ will be used denote a qubit that is in the coherent state.

Figure 3 – A three-qubit register can represent 8 classical states simultaneously.

When a qubit is in the coherent state, it can be thought of as existing in two different universes. In one universe it exists as a ’1′ and in the other it exists as a ’0′ (See Figure 1). Extending this idea to the 3 bit register we can imagine that the register exists in 8 different universes, one for each of the classical states it could represent (i.e. 000, 001, 010, 011, 100, 101, 110, 111). In order to hold the number 15, a four bit register is required (capable of representing the numbers 0 to 15 simultaneously in the coherent state).

A calculation performed on the register can be thought of as a whole group of calculations performed in parallel, one in each universe. In effect, a calculation performed on the register is a calculation performed on every possible value that register can represent.

Stage 2

The second stage of the algorithm performs a calculation using the register. The details of which are as follows:

• The number N is the number we wish to factorise, N = 15
• A random number X is chosen, where 1 X N-1
• X is raised to the power contained in the register (register A) and then divided by N
• The remainder from this operation is placed in a second 4 bit register (register B).

Figure 4 – Operation performed in stage 2.

After this operation has been performed, register B contains the superposition of each universes results. This is best illustrated with an example, if we choose X to be 2, then the contents of register B, for every possible value in register A are as follows.

 

Register A Register B 0 1 1 2 2 4 3 8 4 1 5 2 6 4 7 8 8 1 9 2 10 4 11 8 12 1 13 2 14 4 15 8 Table 1 – Contents of Register B, when N = 15 and X = 2.

Notice that the contents of register B follows a repeating sequence (1,2,4,8,1,2,4,8…), the frequency at which this repeats can be named f. In this case the repeating sequence (1, 2, 4, has four values so f = 4.

 

Stage 3

The final stage is perhaps the most difficult to follow. The frequency of repetition, f, can be found using a quantum computer. This is done by performing a complex operation on register B and then looking at its contents which causes the results from every universe to interfere with each other. The resulting value for f is then used in the following equation to calculate a (possible) factor.

Figure 5 – Equation used to calculate factor.

The resulting number cannot be guaranteed to be a prime factor, but there is a good chance that it is one. The interference that produces the value for f tends to favour the correct answer as incorrect answers cancel each other out.

In our example the value f = 4 does give a correct answer of 3.

The fact that the answer cannot be guaranteed to be correct is of little consequence as it can be easily checked with multiplication. If the answer is incorrect, there is a very strong chance that repeating the calculation a few times with different values of X will produce the right answer.

 

Source: NSA Building A $2 Billion Quantum Computer Spy Center? ©
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