Leave a CommentContext Aware Computing
Leave a Comment* [Presentation] Context-Awareness, Disappearing, and Distributed User Interfaces
http://www.vs.inf.ethz.ch/events/dag2001/slides/albrecht.pdf
* [Paper] A Survey of Context-Aware Mobile Computing Research
http://www.cs.dartmouth.edu/reports/TR2000-381.pdf
*[Paper] Towards a Better Understanding of Context and Context-Awareness
ftp://ftp.cc.gatech.edu/pub/gvu/tr/1999/99-22.pdf
* [Web Page] Context Awareness and Intelligent Environement (Smart Spaces) Survey Page
http://www.cs.cmu.edu/~jiangch/survey.html
* [Web Page] Intelligent Environments Resource Page
http://research.microsoft.com/ierp/
Leave a CommentHow Quantum Computers Work
How Quantum Computers Work
by Kevin Bonsor and Jonathan Strickland
Introduction to How Quantum Computers Will Work
The massive amount of processing power generated by computer manufacturers has not yet been able to quench our thirst for speed and computing capacity. In 1947, American computer engineer Howard Aiken said that just six electronic digital computers would satisfy the computing needs of the United States. Others have made similar errant predictions about the amount of computing power that would support our growing technological needs. Of course, Aiken didn’t count on the large amounts of data generated by scientific research, the proliferation of personal computers or the emergence of the Internet, which have only fueled our need for more, more and more computing power.
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.
You don’t have to go back too far to find the origins of quantum computing. While computers have been around for the majority of the 20th century, quantum computing was first theorized less than 30 years ago, by a physicist at the Argonne National Laboratory. Paul Benioff is credited with first applying quantum theory to computers in 1981. Benioff theorized about creating a quantum Turing machine. Most digital computers, like the one you are using to read this article, are based on the Turing Theory. Learn what this is in the next section.
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.
Image used under the GNU Free Documentation License 1.2
The Bloch sphere is a representation of a qubit, the fundamental building block of quantum computers.
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.
Next, we’ll look at some recent advancements in the field of quantum computing.
Qubit Control
Computer scientists control the microscopic particles that act as qubits in quantum computers by using control devices.
- Ion traps use optical or magnetic fields (or a combination of both) to trap ions.
- Optical traps use light waves to trap and control particles.
- Quantum dots are made of semiconductor material and are used to contain and manipulate electrons.
- Semiconductor impurities contain electrons by using “unwanted” atoms found in semiconductor material.
- Superconducting circuits allow electrons to flow with almost no resistance at very low temperatures.
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.
Photo courtesy © 2007
D-Wave Systems, Inc.
D-Wave’s 16-qubit
quantum computer
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.
But quantum computing is still in its early stages of development, and many computer scientists believe the technology needed to create a practical quantum computer is years away. Quantum computers must have at least several dozen qubits to be able to solve real-world problems, and thus serve as a viable computing method.
For more information on quantum computers and related topics, check out the links on the next page.
Lots More Information
Related HowStuffWorks Articles
- How PCs Work
- How Microprocessors Work
- How Computer Memory Works
- How Atoms Work
- How Electromagnets Work
- How Bits and Bytes Work
- How Radio Works
- How MRI Works
- How DNA Computers Will Work
- How Teleportation Will Work
- How do quantum computers work?
More Great Links
- Shtetl-Optimized
- The Hitchhiker’s Guide To Quantum Computing
- An Overview of Quantum Computers
- Centre for Quantum Computation
- D-Wave Computer Systems
Sources
- “12-qubits Reached In Quantum Information Quest.” Science Daily, May 2006.
http://www.sciencedaily.com/releases/2006/05/060508164700.htm - Aaronson, Scott. “Shtetl-Optimized.” April 10, 2007.
http://scottaaronson.com/blog - Bone, Simone and Matias Castro. “A Brief History of Quantum Computing.” Imperial College, London, Department of Computing. 1997.
http://www.doc.ic.ac.uk/~nd/surprise_97/journal/vol4/spb3/ - Boyle, Alan. “A quantum leap in computing.” MSNBC, May 18, 2000.
http://www.msnbc.msn.com/id/3077363 - “Center for Extreme Quantum Information Theory (xQIT), MIT.” TechNews, March 2007.
http://www.technologynewsdaily.com/node/6280 - Centre for Quantum Computer Technology
http://www.qcaustralia.org/ - Cory, D.G., et al. “Experimental Quantum Error Correction.” Amerian Physical Society, Physical Review Online Archive, September 1998.
http://prola.aps.org/abstract/PRL/v81/i10/p2152_1 - Grover, Lov K. “Quantum Computing.” The Sciences, July/August 1999.
http://cryptome.org/qc-grover.htm - Hogg, Tad. “An Overview of Quantum Computing.” Quantum Computing and Phase Transitions in Combinatorial Search. Journal of Artificial Intelligence Research, 4, 91-128 (1996).
http://www.cs.cmu.edu/afs/cs/project/jair/pub/volume4/ hogg96a-html/node6.html - “IBM’s Test-Tube Quantum Computer Makes History.” IBM Research, December 19, 2001.
http://domino.watson.ibm.com/comm/pr.nsf/pages/ news.20011219_quantum.html - Institute for Quantum Computing.
http://www.iqc.ca - Jonietz, Erika. “Quantum Calculation.” Technology Review, July 2005.
http://www.technologyreview.com/Infotech/14591 - Maney, Kevin. “Beyond the PC: Atomic QC.” USA Today.
http://www.amd1.com/quantum_computers.html - “Quantum Computing.” Stanford Encyclopedia of Philosophy, February 26, 2007.
http://plato.stanford.edu/entries/qt-quantcomp - Qubit.org
http://www.qubit.org - Simonite, Tom. “Flat ‘ion trap’ holds quantum computing promise.” NewScientistTech, July 2006.
http://www.newscientisttech.com/article/ dn9502-flat-ion-trap-holds-quantum-computing-promise.html - Vance, Ashlee. “D-Wave qubits in the era of Quantum Computing.” The Register, February 13, 2007.
http://www.theregister.co.uk/2007/02/13/dwave_quantum - West, Jacob. “The Quantum Computer.” Computer Science at CalTech, April 28, 2000.
http://www.cs.caltech.edu/~westside/quantum-intro.html
How DNA Computers Will Work?
Browse the article How DNA Computers Will Work?
How DNA Computers Will Work?
by Kevin Bonsor
Introduction to How DNA Computers Will Work
Even as you read this article, computer chip manufacturers are furiously racing to make the next microprocessor that will topple speed records. Sooner or later, though, this competition is bound to hit a wall. Microprocessors made of silicon will eventually reach their limits of speed and miniaturization. Chip makers need a new material to produce faster computing speeds.
You won’t believe where scientists have found the new material they need to build the next generation of microprocessors. Millions of natural supercomputers exist inside living organisms, including your body. DNA (deoxyribonucleic acid) molecules, the material our genes are made of, have the potential to perform calculations many times faster than the world’s most powerful human-built computers. DNA might one day be integrated into a computer chip to create a so-called biochip that will push computers even faster. DNA molecules have already been harnessed to perform complex mathematical problems.
While still in their infancy, DNA computers will be capable of storing billions of times more data than your personal computer. In this article, you’ll learn how scientists are using genetic material to create nano-computers that might take the place of silicon-based computers in the next decade.
A Fledgling Technology
DNA computers can’t be found at your local electronics store yet. The technology is still in development, and didn’t even exist as a concept a decade ago. In 1994, Leonard Adleman introduced the idea of using DNA to solve complex mathematical problems. Adleman, a computer scientist at the University of Southern California, came to the conclusion that DNA had computational potential after reading the book “Molecular Biology of the Gene,” written by James Watson, who co-discovered the structure of DNA in 1953. In fact, DNA is very similar to a computer hard drive in how it stores permanent information about your genes.
Adleman is often called the inventor of DNA computers. His article in a 1994 issue of the journal Science outlined how to use DNA to solve a well-known mathematical problem, called the directed Hamilton Path problem, also known as the “traveling salesman” problem. The goal of the problem is to find the shortest route between a number of cities, going through each city only once. As you add more cities to the problem, the problem becomes more difficult. Adleman chose to find the shortest route between seven cities.
You could probably draw this problem out on paper and come to a solution faster than Adleman did using his DNA test-tube computer. Here are the steps taken in the Adleman DNA computer experiment:
- Strands of DNA represent the seven cities. In genes, genetic coding is represented by the letters A, T, C and G. Some sequence of these four letters represented each city and possible flight path.
- These molecules are then mixed in a test tube, with some of these DNA strands sticking together. A chain of these strands represents a possible answer.
- Within a few seconds, all of the possible combinations of DNA strands, which represent answers, are created in the test tube.
- Adleman eliminates the wrong molecules through chemical reactions, which leaves behind only the flight paths that connect all seven cities.
The success of the Adleman DNA computer proves that DNA can be used to calculate complex mathematical problems. However, this early DNA computer is far from challenging silicon-based computers in terms of speed. The Adleman DNA computer created a group of possible answers very quickly, but it took days for Adleman to narrow down the possibilities. Another drawback of his DNA computer is that it requires human assistance. The goal of the DNA computing field is to create a device that can work independent of human involvement.
Three years after Adleman’s experiment, researchers at the University of Rochester developed logic gates made of DNA. Logic gates are a vital part of how your computer carries out functions that you command it to do. These gates convert binary code moving through the computer into a series of signals that the computer uses to perform operations. Currently, logic gates interpret input signals from silicon transistors, and convert those signals into an output signal that allows the computer to perform complex functions.
The Rochester team’s DNA logic gates are the first step toward creating a computer that has a structure similar to that of an electronic PC. Instead of using electrical signals to perform logical operations, these DNA logic gates rely on DNA code. They detect fragments of genetic material as input, splice together these fragments and form a single output. For instance, a genetic gate called the “And gate” links two DNA inputs by chemically binding them so they’re locked in an end-to-end structure, similar to the way two Legos might be fastened by a third Lego between them. The researchers believe that these logic gates might be combined with DNA microchips to create a breakthrough in DNA computing.
DNA computer components — logic gates and biochips — will take years to develop into a practical, workable DNA computer. If such a computer is ever built, scientists say that it will be more compact, accurate and efficient than conventional computers. In the next section, we’ll look at how DNA computers could surpass their silicon-based predecessors, and what tasks these computers would perform.
A Successor to Silicon
Silicon microprocessors have been the heart of the computing world for more than 40 years. In that time, manufacturers have crammed more and more electronic devices onto their microprocessors. In accordance with Moore’s Law, the number of electronic devices put on a microprocessor has doubled every 18 months. Moore’s Law is named after Intel founder Gordon Moore, who predicted in 1965 that microprocessors would double in complexity every two years. Many have predicted that Moore’s Law will soon reach its end, because of the physical speed and miniaturization limitations of silicon microprocessors.
DNA computers have the potential to take computing to new levels, picking up where Moore’s Law leaves off. There are several advantages to using DNA instead of silicon:
- As long as there are cellular organisms, there will always be a supply of DNA.
- The large supply of DNA makes it a cheap resource.
- Unlike the toxic materials used to make traditional microprocessors, DNA biochips can be made cleanly.
- DNA computers are many times smaller than today’s computers.
DNA’s key advantage is that it will make computers smaller than any computer that has come before them, while at the same time holding more data. One pound of DNA has the capacity to store more information than all the electronic computers ever built; and the computing power of a teardrop-sized DNA computer, using the DNA logic gates, will be more powerful than the world’s most powerful supercomputer. More than 10 trillion DNA molecules can fit into an area no larger than 1 cubic centimeter (0.06 cubic inches). With this small amount of DNA, a computer would be able to hold 10 terabytes of data, and perform 10 trillion calculations at a time. By adding more DNA, more calculations could be performed.
Unlike conventional computers, DNA computers perform calculations parallel to other calculations. Conventional computers operate linearly, taking on tasks one at a time. It is parallel computing that allows DNA to solve complex mathematical problems in hours, whereas it might take electrical computers hundreds of years to complete them.
The first DNA computers are unlikely to feature word processing, e-mailing and solitaire programs. Instead, their powerful computing power will be used by national governments for cracking secret codes, or by airlines wanting to map more efficient routes. Studying DNA computers may also lead us to a better understanding of a more complex computer — the human brain.
Touch Screen Bars
iBar
interactive multitouch cocktail bar
