Quantum computing
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Quantum computation its uses and the process and hinderences
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Quantum computing
- 1. Quantum Computing There's plenty of room at the bottom. Richard Feynman
- 2. Why Do We Need Quantum Computing ● Moore's Law. ● Calculations (Very Very …. Large ones) ● Security ● Optimizations ● Machine Learning ● Simulation
- 4. RSA-2048 (617 Digits) Prime Factorisation ● Using classical General Number Field Sieve ● Using Quantum Peter Shor's Factoring Alogorith ● t ~ 10seconds● T ~ 4 x 1017 seconds ~13 x 109 Years i.e Age of Universe Time to solve
- 5. Security
- 6. Optimization ● To find the best value to your capabilities,money,capital,etc ● Classical Light Switch Problem ● Water Network Optimization ● Radiotherapy Optimaztion ● Protein Folding
- 7. Machine Learning ● Artificial Intelligence ● Object Detection ● Labelling New Stories ● Video Compression
- 8. Harnessing Quantum Phenomenon for Computations ● Quantum Tunnelling ● Quantization of Energy ● Entanglement● Superposition Delhi Hyderabad
- 9. Bit vs Qubit ● 0 or 1 ● Freely readable ● Programming is done in 0's or 1's ● 0 or 1 or ● It is destroyed when reading Q-bit ● Programming is done in terms of energy to be given to a Q-bit ● Intrinsic Randomness ● Entanglement ● Uncertainty Principle
- 11. Classical Vs Quantum Register Quantum Classical If the n = 300, The Quantum Register could hold more numbers simultaneously than there are atoms in the 'Observable Universe'
- 12. How does it solve
- 13. Implementing ● Different Models:Different Models: Gate, One-way Topological, Adiabatic Annealing ● Different Basis:Different Basis: Superconducting metals, ion traps, photons, solid state SQuID Nuclear Spin Based Q-bit Trapped Ion QC
- 14. Decoherence ● Schrodinger's cat can be 'Dead' and 'Alive' only if its completely isolated from all kinds of interactions with the world. ● Likewise the Quantum computer should not be sneaked while computing. ● This is the major hinderance in Q-Computing
- 15. Till Now...
- 16. Till Now ● First execution of Shor's algorithm at IBM's Almaden Research Center and Stanford University. The number 15 was factored using 1018 identical molecules, each containing seven active nuclear spins ● Scientists transfer data by quantum teleportation over a distance of 10 feet with zero percent error rate, a vital step towards a quantum internet ● D-wave systems bult a 512 Q-bit Processor with NASA and Google's collaboration
- 17. Thank you
Editor's Notes
- "Moore's law" is the observation that, over the history of computing hardware, the number of transistors in a dense integrated circuit doubles approximately every two years. The observation is named after Gordon E. Moore, co-founder of the Intel Corporation, who first described the trend in a 1965 paper[1][2][2][3] and formulated its current statement in 1975. His prediction has proven to be accurate, in part because the law now is used in the semiconductor industry to guide long-term planning and to set targets for research and development.[4] The capabilities of many digital electronic devices are strongly linked to Moore's law: quality-adjusted microprocessor prices,[5] memory capacity, sensors and even the number and size of pixels in digital cameras.[6] All of these are improving at roughly exponential rates as well. This exponential improvement has dramatically enhanced the effect of digital electronics in nearly every segment of the world economy.[7] Moore's law describes a driving force of technological and social change, productivity, and economic growth in the late twentieth and early twenty-first centuries.[8][9][10][11] The period is often quoted as 18 months because of Intel executive David House, who predicted that chip performance would double every 18 months (being a combination of the effect of more transistors and their being faster).[12] Although this trend has continued for more than half a century, "Moore's law" should be considered an observation or conjecture and not a physical or natural law. Sources in 2005 expected it to continue until at least 2015 or 2020.[note 1][14] The 2010 update to the International Technology Roadmap for Semiconductors predicted that growth will slow at the end of 2013,[15] however, when transistor counts and densities are to double only every three years.