How Quantum Computers Work

A quantum computer is a computer design which uses the principles of quantum physics to increase the computational power beyond what is attainable by a traditional computer. Quantum computers have been built on a small scale and work continues to upgrade them to more practical models. How Computers Work Computers function by storing data in a binary number format, which result in a series of 1s 0s retained in electronic components such as transistors. Each component of computer memory is called a bit and can be manipulated through the steps of Boolean logic so that the bits change, based upon the algorithms applied by the computer program, between the 1 and 0 modes (sometimes referred to as on and off). How a Quantum Computer Would Work A quantum computer, on the other hand, would store information as either a 1, 0, or a quantum superposition of the two states. Such a quantum bit allows for far greater flexibility than the binary system. Specifically, a quantum computer would be able to perform calculations on a far greater order of magnitude than traditional computers ... a concept which has serious concerns and applications in the realm of cryptography encryption. Some fear that a successful practical quantum computer would devastate the worlds financial system by ripping through their computer security encryptions, which are based on factoring large numbers that literally cannot be cracked by traditional computers within the lifespan of the universe. A quantum computer, on the other hand, could factor the numbers in a reasonable period of time. To understand how this speeds things up, consider this example. If the qubit is in a superposition of the 1 state and the 0 state, and it performed a calculation with another qubit in the same superposition, then one calculation actually obtains 4 results: a 1/1 result, a 1/0 result, a 0/1 result, and a 0/0 result. This is a result of the mathematics applied to a quantum system when in a state of decoherence, which lasts while it is in a superposition of states until it collapses down into one state. The ability of a quantum computer to perform multiple computations simultaneously (or in parallel, in computer terms) is called quantum parallelism. The exact physical mechanism at work within the quantum computer is somewhat theoretically complex and intuitively disturbing. Generally, it is explained in terms of the multi-world interpretation of quantum physics, wherein the computer performs calculations not only in our universe but also in other universes simultaneously, while the various qubits are in a state of quantum decoherence. While this sounds far-fetched, the multi-world interpretation has been shown to make predictions which match experimental results. History of Quantum Computing Quantum computing tends to trace its roots back to a 1959 speech by Richard P. Feynman in which he spoke about the effects of miniaturization, including the idea of exploiting quantum effects to create more powerful computers. This speech is also generally considered the starting point of nanotechnology. Of course, before the quantum effects of computing could be realized, scientists and engineers had to more fully develop the technology of traditional computers. This is why, for many years, there was little direct progress, nor even interest, in the idea of making Feynmans suggestions into reality. In 1985, the idea of quantum logic gates was put forth by the University of Oxfords David Deutsch, as a means of harnessing the quantum realm inside a computer. In fact, Deutschs paper on the subject showed that any physical process could be modeled by a quantum computer. Nearly a decade later, in 1994, ATTs Peter Shor devised an algorithm that could use only 6 qubits to perform some basic factorizations ... more cubits the more complex the numbers requiring factorization became, of course. A handful of quantum computers has been built. The first, a 2-qubit quantum computer in 1998, could perform trivial calculations before losing decoherence after a few nanoseconds. In 2000, teams successfully built both a 4-qubit and a 7-qubit quantum computer. Research on the subject is still very active, although some physicists and engineers express concerns over the difficulties involved in upscaling these experiments to full-scale computing systems. Still, the success of these initial steps does show that the fundamental theory is sound. Difficulties With Quantum Computers The quantum computers main drawback is the same as its strength: quantum decoherence. The qubit calculations are performed while the quantum wave function is in a state of superposition between states, which is what allows it to perform the calculations using both 1 0 states simultaneously. However, when a measurement of any type is made to a quantum system, decoherence breaks down and the wave function collapses into a single state. Therefore, the computer has to somehow continue making these calculations without having any measurements made until the proper time, when it can then drop out of the quantum state, have a measurement taken to read its result, which then gets passed on to the rest of the system. The physical requirements of manipulating a system on this scale are considerable, touching on the realms of superconductors, nanotechnology, and quantum electronics, as well as others. Each of these is itself a sophisticated field which is still being fully developed, so trying to merge them all together into a functional quantum computer is a task which I dont particularly envy anyone ... except for the person who finally succeeds.

Capital Punishment Of The Criminal Justice System

In the United States, capital punishment has always been the spotlight of many debates concerning the consequences of severe crimes. Although capital punishment is deemed to be acceptable for violent crimes such as murder, there are numerous individuals who oppose the usage of capital punishment against violent offenders. Both proponents and opponents have given countless opinions concerning the deterrence effect of capital punishment. Research studies have also added fuel to the debate in regards to the effectiveness of capital punishment in the criminal justice system. With the differences in between the pros and cons of capital punishment, it is hard to come to a concrete conclusion on whether or not if this element serves its purpose in the penal system. This paper will further discuss if capital punishment is effective in deterring violent crimes as well its implications for the future. As common knowledge, the word â€Å"punishment† is usually used to describe something that is a painful consequence or outcome based on one’s actions and/or poor decision-making. In the criminal justice system, â€Å"punishment’ is a sanction that is opposed on offenders for committing a criminal offense (Banks, 2013). Thus, the utilization of capital punishment is not new when it comes to the element of punishment. Capital punishment can be traced all the way back to ancient Greece. For example, Socrates was tried and executed for corrupting the minds of Athenian youth (Ristroph, 2009,Show MoreRelatedThe United States Incarceration System1710 Words   |  7 PagesThe United States incarceration system is a structural foundation of punishment in which is formed by robust authoritarian power. 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In the U.S, Capital Punishment has been legalized in 32 states since 1996. Capital Punishment is not as inhumane as it sounds; it is limited under the 8th amendment in the U.S . Contrary to most beliefs, Capital Punishment is not used on every case of rapistsRead MoreThe Canadian Justice System And Capital Punishment1713 Words   |  7 Pagesthe Canadian justice system in its views on capital punishment. Two men, Arthur Lucas, and Ronald Turpin was to be executed in Canada for committing crimes. Both had been accused of committing murder, Lucas for killing an officer while fleeing a robbery and Turpin for murdering an undercover narcotics officer. Both were hanged back to back at midnight and buried side by side with no marking on their graves. 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In other, the advantages of capital punishment outweigh its disadvantages. Introduction Capital punishment is also known as death penalty and it has been in existence since time immemorial. Throughout history, the death penalty has been used to punish a number of crimes that include murder

Compute Unified Device Design (CUDA)

Question: Discuss about compute unified device design (CUDA)? Answer: Introduction Main confront in image process is to realize high preciseness and high performance that is troublesome to attain even with high speed central processing unit. CUDA has get rid of the blockage of high execution time by parallel execution of image instead of consecutive execution. Compute Unified Device design (CUDA) could be a innovative hardware and computer code design produced by NVIDIA for planning and coping with GPUs parallel computations. The early CUDA SDK was opened for public on fifteen February 2007, for maintenance was later supplemental in CUDA 2.0 compatible with every NVIDIA GPUs, in addition to Quadro, Tesla line and Deforces. The platform for GPU programming released on CUDA presents extremely parallel computation and versatile platform with programmable nature. CUDA API allows computer code developers to admittance the GPU and additionally authorize researcher to style programs for each central processing unit and GPU, while not basic information on tricks. . The platform of CUDA is reachable to computer code developers in the course of compiler directives like OpenACC, accelerated libraries and conservatory to standards of industry. CUDA give right of entry to developers to aboard memory, parallel process components and virtual instruction set of GPU. CUDA give large process power to programming persons as CUDA is universal and intended to supply parallel computations to GPUs. CUDA hold up parallelism of type fine grained (account look upon lesser elements of that the larger are collected) enough for making use of extremely multithreaded GPUs CUDA Design The CUDA design GPUs will be utilized for common reason (that not solely parallel) by application of CUDA. By means of CUDA GPUs shows parallel output design that highlights on simultaneous threads execution gradually, instead of single thread execution rapidly just in case of central processing unit .The universal CUDA design consists of many elements like 1. Cypher engines Parallel within each NVIDIA GPUs.2. Support level at OS kernel or hardware formatting, design, etc.3. Driver of User-mode, which offers an interface AP or application programming interface at device-level for developers.4. Instruction set design (ISA) of PTX (Parallel Thread Execution) for calculations of functions and kernels in parallel fashion. Fig. Elements of CUDA design CUDA Computer CODE Development The CUDA computer code Development kit offers instances, Documentation and all available tools that helps in applications development which are: 1. Libraries: - CUDA design includes advanced libraries like FFT, BLAS.2. C Runtime: - It hold up normal C functions execution on the top of GPU and permits function of native bindings for alternative languages such as Java, FORTRAN, which are high-level language and peripheral interface such as DX Compute, OpenCL.3. Tools: - CUDA give tools like, CUDA computer programme (cudagdb), NVIDIA compiler (nvcc ), CUDA Visual Profiler (cudaprof), and alternative useful tools.4. Documentation:- comprises the Programming Guide for CUDA, specifications of CUDA API, and alternative useful documentation. Functioning of CUDA Model CUDA is at level of C standards which satisfy industry with lowest extensions and computer user should write down a program for single thread. CUDA forms a type of scalable programming with inherent parallel model which means program executes on many processors while not recompiling. CUDA Memories CUDA comprises of essentially 5 kinds of recollections these global, shared, constant, texture and local memory. Shared and global recollections are brought in CUDA, these 2 are most vital and unremarkably in use. Alternative 3 are utilized to get better performance. CUDA Advantages 1. Intended to last non graphic functions.2. Its computer code development kit comprises varied debugging, libraries, identification and tools for compilation.3. Task for programming is straightforward and simple as C-like language is used to write kernel calls.4. It give quicker readbacks and downloads to and as of the GPU.5. CUDA depiction a region of quick shared memory region speed of 48KB per Processor. CUDA Limitations 1. CUDA is limited to NVIDIA GPUs solely. 2. CUDA executes its cod of host in the course of a C++ compiler therefore it doesnt hold up the total standard of C. 3. Texture representation isn't maintained in CUDA. CUDA Applications 1. Mainly CUDA is intended for technical functions. 2. it's additionally employed in cryptography, medical imaging to execute algorithms of image process, neural networks, quick video transcoding etc. Conclusion After contrast of CUDA with alternative techniques of parallel computing. it's obvious that CUDA is far quick. Therefore there's a good scope of NVIDIAs CUDA design. CUDA is extremely economical and may solve any advanced drawback in milliseconds. CUDA act as a tool of parallel computing on a GPU and make use of the entire cores and additionally free the central processing unit clock cycles for alternative imperative works. CUDA design combines each central processing unit and GPUs to perform sequent task by central processing unit and parallel task by GPUs. during this approach CUDA decreases the time of execution to good extend. References 1. Nickolls "Scalable Parallel Programming with CUDA", ACM Queue, vol. 6, no. 2, pp.40 -53 2008 2. Lindholm "NVIDIA Tesla: A Unified Graphics and Computing Architecture", IEEE Micro, vol. 28, no. 2, pp.39 -55 2008 3. Catanzaro , N. Sundaram and K. Keutzer "Fast Support Vector Machine Training and Classification on Graphics Processors", Proc. 25th Ann. Int'l Conf. Machine Learning, pp.104 -111 2008 4. He "Relational Joins on Graphics Processors", Proc. ACM SIGMOD 2008, 2008 [online] Available:5. Schatz "High-Throughput Sequence Alignment Using Graphics Processing Units", BMC Bioinformatics, vol. 8, no. 1, pp.474 2007 [online] Available:6. Manavski and G. Valle "CUDA Compatible GPU Cards as Efficient Hardware Accelerators for Smith-Waterman Sequence Alignment", BMC Bioinformatics, vol. 9, pp.S10 2008 [online] Available:7. S. Stone "How GPUs Can Improve the Quality of Magnetic Resonance Imaging", Proc. 1st Workshop General Purpose Processing on Graphics Processing Units, 2007 8. Frenkel and B. Smit Understanding Molecular Simulations, 2002 :Academic Press 9. A. Anderson , C. D. Lorenz and A. Travesset "Micellar Crystals in Solution from Molecular Dynamics Simulations", J. Chemical Physics, vol. 128, pp.184906 -184916 2008 10. A. Anderson , C. D. Lorenz and A. Travesset "General Purpose Molecular Dynamics Simulations Fully Implemented on Graphics Processing Units", J. Computational Physics, vol. 227, no. 10, pp.5342 -5359 2008