1. Toward a Dependable Quantum Computing
Architecture
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2. Contents
• Introduction
• Technology
• System design
• Challenges
• Advantages and Disadvantages
• Applications
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3. INTRODUCTION
• Energy consumption
• Speed
• Data transportation
• Power of QC
• Qubit
• 0&1
• Superposition state
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4. How to encode quantum information ?
• Electrons are preferred (decoherence)
• Three ways
• Spin angle of photons & electrons
• Polarization of photons
• Reverse spin angle
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5. TECHNOLOGY
• QC & Qubits
• 0&1
• Superposition state
• Quantum dots
• a|0〉 + b|1〉
• |a|2 + |b|2 = 1
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6. • Parallelism
• Microscopic reversibility
• Vertical polarization _ or ↔
• Electron spin ↑ or ↓ ]
• Consider an operation g
• c0|g(00)〉 + c1|g(01)〉 + c2|g(10)〉 + c3|g(11)〉
• Qubit dots vs. parallelism
• quantum portioning
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7. • Quantum teleportation
• Process of sending quibts
• Using disintegration
• And reintegration(DISRE)
• qubits jbi and jci are distributed
• jai is combined with jbi
• produce two classical bits of information
• After transport, these bits are used to manipulate jci to regenerate state jai and
jbi at the destination. 7

8. SYSTEM DESIGN
• A N qubit =2^N superpostions
• Logical qubit
• Multitasking
• Parallelism
• Reversible
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9. CHALLENGES
• Decoherence: This property states that if a coherent state (state with
superposition) interacts with the environment, it will fall into a
classical physics state without superposition
• Zeno effect: States that an unstable particle, if constantly observed,
will never decay into a superpositioned state
• Entanglement: two or more particles can be linked, and if linked, you
can change properties of one particle changing the linked one.
• E.g.: polerization of single electrons can cause change in enture system
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10. ADVANTAGES AND DISADAVTAGES
• Advantages
• Faster computation
• Exponential Speed-up
• Used as classical computer
• Disadvantages
• Availability
• Zero interaction with environment is impossible
• Availability of advanced algorithms
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11. Applications
• Ultra-Precise Clocks
• Uncrackable Codes
• Improved Microscopes
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12. CONCLUSION
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13. REFERENCES
1. International Technology Roadmap for Semi-conductors, Semiconductor Industry Assoc., San Jose, Calif., 1999.
2. M.A. Nielsen and I.L. Chuang, Quantum Computation and Quantum Information, Cambridge Press, Cambridge, UK, 2000.
3. C.H. Bennett and D.P. DiVincenzo, “Quan-tum Information and Computation,” Nature, vol. 404, no. 6775, 2000, pp. 247-254.
4. N. Gershenfeld and I.L. Chuang, “Bulk Spin-Resonance Quantum Computing,” Science, vol. 275, 1997, pp. 350-356.
5. D.G. Cory, A.F. Fahmy, and T.F. Havel, “Nuclear Magnetic Resonance Spec-troscopy: An Experimentally Accessible Par-adigm for
Quantum Computing,” Proc. , vol. 94, Nat’l Academy of Sciences, Washington, D.C., 1997, pp. 1634-1639.
6. L.M.K. Vandersypen et al., “Experimental Realization of an Order-Finding Algorithm with an NMR Quantum Computer” Physical
Review Letters, vol. 85, no. 25, 2000, pp. 5452-5455.
7. P. Shor, “Algorithms for Quantum Compu-tation: Discrete Logarithms and Factoring,” Proc. 35th Ann. Symp. Foundations of Com-
puter Science, IEEE Computer Soc. Press, Los Alamitos, Calif., 1999, pp. 124-134.
8. A. Ekert and R. Jozsa, “Quantum Computa-tion and Shor’s Factoring Algorithm,” Reviews of Modern Physics, vol. 68, no. 3, 1996, pp.
733-753.
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14. THANK YOU
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