SlideShare a Scribd company logo
1 of 27
Quantum Computers
Siva Desaraju
Bindu Katragadda
Manusri Edupuganti
presented by
Outline
Introduction
Quantum computation
Implementation
Quantum compiler
Error correction
Architecture
Classification
Fabrication
Challenges
Advantages over classical computers
Applications
Recent advances
Timeline
Conclusion
Introduction
Superposition
 Simultaneously possess two or more values
Entanglement
 Quantum states of two atoms correlated even though spatially
separated!!!
 Albert Einstein baffled “spooky action at a distance”
Quantum Mechanics
 Why? – Moore’s law
 Study of matter at atomic level (The power of atoms)
 Classical physics laws do not apply
[2]
Bits n Qubits
Classical computers 0 or 1 (bits)
 High/low voltage
Quantum computers 0 or 1 or 0 & 1 (Qubits)
 Nuclear spin up/down 0 or 1
 Isolated atom spin up & down 0 & 1
Represent more with less (n bits 2n states)
[2]
” To be or not to be. That is the question”
– William Shakespeare
The classic answers: ”to be” or ”not to be”
The quantum answers: ”to be” or ”not to be” or
a x (to be) + b x (not to be)
Quantum Computation
Prime factorization (Cryptography)
 Peter Shor’s algorithm
 Hard classical computation becomes easy quantum
computation
 Factor n bit integer in O(n3)
Search an unordered list
 Lov Grover’s algorithm
 Hard classical computation becomes less hard
quantum computation
 n elements in n1/2 queries
Implementation model
Quantum program
Quantum unitary
transforms (gates)
Quantum
measurements
Classical
computation
Classical control
flow decisions
Quantum compiler
Instruction
stream
Classical bit
instruction stream
Early quantum computation - Circuit model(ASIC)
Quantum Compiler
Static precompiler
 End-to-end error probability
Dynamic compiler
 Accepts the precompiled binary code &
produces an instruction stream
Error Correction
Localized errors on a few qubits can have global impact
Hamming code
Difficulty of error correcting quantum states
 Classical computers – bit flip
 Quantum computers – bit flip + phase flip
 Difficulty in measurement (collapses superposition)
Quantum error correction code
 [n,k] code uses n qubits to encode k qubits of data
 Extra bits (n-k) are called ancilla bits
 Ancilla bits are in initial state
Architecture
Aims of efficient architecture
 Minimize error correction overhead
 Support different algorithms & data sizes
 Reliable data paths & efficient quantum
memory
Major components
 Quantum ALU
 Quantum memory
 Dynamic scheduler
Architecture contd…
[1]
Quantum ALU
Sequence of transforms
 the Hadamard (a radix-2, 1-qubit Fourier
 transform)
 identity (I, a quantum NOP)
 bit flip (X, a quantum NOT)
 phase flip (Z, which changes the signs of amplitudes)
 bit and phase flip (Y)
 rotation by π/4 (S)
 rotation by π/8 (T)
 controlled NOT (CNOT)
Quantum Memory
Reliable memory
Refresh units
Multiple memory banks
Quantum wires
Teleportation
Quantum swap gates
Cat state
[1]
Dynamic Scheduler
Dynamic scheduler algorithm takes
 Input - logical quantum operations,
interleaved with classical control flow
constructs
 Output - physical individual qubit operations
Uses knowledge of data size & physical qubit
error rates
Classification
Quantum Computer
Liquid Quantum Computer Solid Quantum Computer
Si29 Doping Phosphorous Doping
Liquid Quantum Computers
NMR Technology
Disadvantages
 Massive redundancy
 Not scalable
Solid Quantum Computers
Why silicon
Chip design aims
 Capturing & manipulating individual sub
atomic particles
 Harnessing, controlling & coordinating millions
of particles at once
Si29 Doping
Need for Silicon 29 (Si29) doping
Fabrication
Advantages
Disadvantages
[9]
Phosphorous doping
[3]
Fabrication
STM technology to pluck individual atoms
from hydrogen
 PH3 used instead of P
Challenges
Decoherence
Chip fabrication
Error correction
Advantages over Classical
computers
Encode more information
Powerful
Massively parallel
Easily crack secret codes
Fast in searching databases
Hard computational problems become
tractable
Applications
Defense
Cryptography
Accurate weather forecasts
Efficient search
Teleportation
…
Unimaginable
Timeline
2003 - A research team in Japan demonstrated the first solid state
device needed to construct a viable quantum computer
2001 - First working 7-qubit NMR computer demonstrated at IBM’s
Almaden Research Center. First execution of Shor’s algorithm.
2000 - First working 5-qubit NMR computer demonstrated at IBM's
Almaden Research Center. First execution of order finding (part of
Shor's algorithm).
1999 - First working 3-qubit NMR computer demonstrated at IBM's
Almaden Research Center. First execution of Grover's algorithm.
1998 - First working 2-qubit NMR computer demonstrated at
University of California Berkeley.
1997 - MIT published the first papers on quantum computers based
on spin resonance & thermal ensembles.
1996 - Lov Grover at Bell Labs invented the quantum database
search algorithm
1995 - Shor proposed the first scheme for quantum error correction
Conclusion…will this be ever
true?
Millions into research
With a 100 qubit computer you can
represent all atoms in the universe.
If you succeed, the world will be at your
feet
[6]
References
[1] http://www.cs.washington.edu/homes/oskin/Oskin-A-Practical-
Architecture-for-Reliable-Quantum-Computers.pdf
[2] http://www.qubit.org
[3] http://www.nature.com
[4] http://www.wikipedia.com
[5] http://www.howstuffworks.com
[6] http://www.physicsweb.org/toc/world/11/3
[7] http://www.cs.ualberta.ca/~bulitko/qc/schedule/slides/QCSS-
2002-06-18.ppt
[8] http://physics.about.com/cs/quantumphysics/
[9] http://www.trnmag.com/Stories/2002/082102/Chip_
design_aims_for_quantum_leap_082102.html
Puzzled???
"I think I can safely say that nobody understands quantum
mechanics."
- Richard P. Feynman
“Anybody who thinks they understand quantum physics
is wrong."
- Niels Bohr

More Related Content

Similar to Quantum Computers.ppt

What is Quantum Computing and Why it is Important
What is Quantum Computing and Why it is ImportantWhat is Quantum Computing and Why it is Important
What is Quantum Computing and Why it is ImportantSasha Lazarevic
 
DEF CON 23 - Phillip Aumasson - quantum computers vs computers security
DEF CON 23 - Phillip Aumasson - quantum computers vs computers securityDEF CON 23 - Phillip Aumasson - quantum computers vs computers security
DEF CON 23 - Phillip Aumasson - quantum computers vs computers securityFelipe Prado
 
Quantum Computing and its security implications
Quantum Computing and its security implicationsQuantum Computing and its security implications
Quantum Computing and its security implicationsInnoTech
 
Quantum computation: past-now-future - 2021-06-19
Quantum computation: past-now-future - 2021-06-19Quantum computation: past-now-future - 2021-06-19
Quantum computation: past-now-future - 2021-06-19Aritra Sarkar
 
Fundamentals of Quantum Computing
Fundamentals of Quantum ComputingFundamentals of Quantum Computing
Fundamentals of Quantum Computingachakracu
 
Quantum Computers
Quantum ComputersQuantum Computers
Quantum Computerskathan
 
Let's build a quantum computer!
Let's build a quantum computer!Let's build a quantum computer!
Let's build a quantum computer!Andreas Dewes
 
Seminar on quatum
Seminar on quatumSeminar on quatum
Seminar on quatumaprameyabr1
 
An Introduction to Quantum computing
An Introduction to Quantum computingAn Introduction to Quantum computing
An Introduction to Quantum computingJai Sipani
 

Similar to Quantum Computers.ppt (20)

What is Quantum Computing and Why it is Important
What is Quantum Computing and Why it is ImportantWhat is Quantum Computing and Why it is Important
What is Quantum Computing and Why it is Important
 
DEF CON 23 - Phillip Aumasson - quantum computers vs computers security
DEF CON 23 - Phillip Aumasson - quantum computers vs computers securityDEF CON 23 - Phillip Aumasson - quantum computers vs computers security
DEF CON 23 - Phillip Aumasson - quantum computers vs computers security
 
Documents
Documents Documents
Documents
 
Quantum computing
Quantum computingQuantum computing
Quantum computing
 
Ibm quantum computing
Ibm quantum computingIbm quantum computing
Ibm quantum computing
 
Quantum Computing and its security implications
Quantum Computing and its security implicationsQuantum Computing and its security implications
Quantum Computing and its security implications
 
Ph.D. Defense
Ph.D. DefensePh.D. Defense
Ph.D. Defense
 
preskill.pptx
preskill.pptxpreskill.pptx
preskill.pptx
 
Quantum computation: past-now-future - 2021-06-19
Quantum computation: past-now-future - 2021-06-19Quantum computation: past-now-future - 2021-06-19
Quantum computation: past-now-future - 2021-06-19
 
Fundamentals of Quantum Computing
Fundamentals of Quantum ComputingFundamentals of Quantum Computing
Fundamentals of Quantum Computing
 
Quantum Computers
Quantum ComputersQuantum Computers
Quantum Computers
 
Let's build a quantum computer!
Let's build a quantum computer!Let's build a quantum computer!
Let's build a quantum computer!
 
Introduction to Quantum Computing
Introduction to Quantum ComputingIntroduction to Quantum Computing
Introduction to Quantum Computing
 
Quantum programming
Quantum programmingQuantum programming
Quantum programming
 
Des2017 quantum computing_final
Des2017 quantum computing_finalDes2017 quantum computing_final
Des2017 quantum computing_final
 
Quantum computing
Quantum computingQuantum computing
Quantum computing
 
Quantum Information
Quantum InformationQuantum Information
Quantum Information
 
Quantum computing
Quantum computingQuantum computing
Quantum computing
 
Seminar on quatum
Seminar on quatumSeminar on quatum
Seminar on quatum
 
An Introduction to Quantum computing
An Introduction to Quantum computingAn Introduction to Quantum computing
An Introduction to Quantum computing
 

Recently uploaded

Building a General PDE Solving Framework with Symbolic-Numeric Scientific Mac...
Building a General PDE Solving Framework with Symbolic-Numeric Scientific Mac...Building a General PDE Solving Framework with Symbolic-Numeric Scientific Mac...
Building a General PDE Solving Framework with Symbolic-Numeric Scientific Mac...stazi3110
 
What is Fashion PLM and Why Do You Need It
What is Fashion PLM and Why Do You Need ItWhat is Fashion PLM and Why Do You Need It
What is Fashion PLM and Why Do You Need ItWave PLM
 
Cloud Data Center Network Construction - IEEE
Cloud Data Center Network Construction - IEEECloud Data Center Network Construction - IEEE
Cloud Data Center Network Construction - IEEEVICTOR MAESTRE RAMIREZ
 
MYjobs Presentation Django-based project
MYjobs Presentation Django-based projectMYjobs Presentation Django-based project
MYjobs Presentation Django-based projectAnoyGreter
 
software engineering Chapter 5 System modeling.pptx
software engineering Chapter 5 System modeling.pptxsoftware engineering Chapter 5 System modeling.pptx
software engineering Chapter 5 System modeling.pptxnada99848
 
Salesforce Certified Field Service Consultant
Salesforce Certified Field Service ConsultantSalesforce Certified Field Service Consultant
Salesforce Certified Field Service ConsultantAxelRicardoTrocheRiq
 
Folding Cheat Sheet #4 - fourth in a series
Folding Cheat Sheet #4 - fourth in a seriesFolding Cheat Sheet #4 - fourth in a series
Folding Cheat Sheet #4 - fourth in a seriesPhilip Schwarz
 
Adobe Marketo Engage Deep Dives: Using Webhooks to Transfer Data
Adobe Marketo Engage Deep Dives: Using Webhooks to Transfer DataAdobe Marketo Engage Deep Dives: Using Webhooks to Transfer Data
Adobe Marketo Engage Deep Dives: Using Webhooks to Transfer DataBradBedford3
 
Unveiling Design Patterns: A Visual Guide with UML Diagrams
Unveiling Design Patterns: A Visual Guide with UML DiagramsUnveiling Design Patterns: A Visual Guide with UML Diagrams
Unveiling Design Patterns: A Visual Guide with UML DiagramsAhmed Mohamed
 
Building Real-Time Data Pipelines: Stream & Batch Processing workshop Slide
Building Real-Time Data Pipelines: Stream & Batch Processing workshop SlideBuilding Real-Time Data Pipelines: Stream & Batch Processing workshop Slide
Building Real-Time Data Pipelines: Stream & Batch Processing workshop SlideChristina Lin
 
ODSC - Batch to Stream workshop - integration of Apache Spark, Cassandra, Pos...
ODSC - Batch to Stream workshop - integration of Apache Spark, Cassandra, Pos...ODSC - Batch to Stream workshop - integration of Apache Spark, Cassandra, Pos...
ODSC - Batch to Stream workshop - integration of Apache Spark, Cassandra, Pos...Christina Lin
 
Advancing Engineering with AI through the Next Generation of Strategic Projec...
Advancing Engineering with AI through the Next Generation of Strategic Projec...Advancing Engineering with AI through the Next Generation of Strategic Projec...
Advancing Engineering with AI through the Next Generation of Strategic Projec...OnePlan Solutions
 
KnowAPIs-UnknownPerf-jaxMainz-2024 (1).pptx
KnowAPIs-UnknownPerf-jaxMainz-2024 (1).pptxKnowAPIs-UnknownPerf-jaxMainz-2024 (1).pptx
KnowAPIs-UnknownPerf-jaxMainz-2024 (1).pptxTier1 app
 
Asset Management Software - Infographic
Asset Management Software - InfographicAsset Management Software - Infographic
Asset Management Software - InfographicHr365.us smith
 
Automate your Kamailio Test Calls - Kamailio World 2024
Automate your Kamailio Test Calls - Kamailio World 2024Automate your Kamailio Test Calls - Kamailio World 2024
Automate your Kamailio Test Calls - Kamailio World 2024Andreas Granig
 
Der Spagat zwischen BIAS und FAIRNESS (2024)
Der Spagat zwischen BIAS und FAIRNESS (2024)Der Spagat zwischen BIAS und FAIRNESS (2024)
Der Spagat zwischen BIAS und FAIRNESS (2024)OPEN KNOWLEDGE GmbH
 
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...MyIntelliSource, Inc.
 
Cloud Management Software Platforms: OpenStack
Cloud Management Software Platforms: OpenStackCloud Management Software Platforms: OpenStack
Cloud Management Software Platforms: OpenStackVICTOR MAESTRE RAMIREZ
 
Alluxio Monthly Webinar | Cloud-Native Model Training on Distributed Data
Alluxio Monthly Webinar | Cloud-Native Model Training on Distributed DataAlluxio Monthly Webinar | Cloud-Native Model Training on Distributed Data
Alluxio Monthly Webinar | Cloud-Native Model Training on Distributed DataAlluxio, Inc.
 

Recently uploaded (20)

Building a General PDE Solving Framework with Symbolic-Numeric Scientific Mac...
Building a General PDE Solving Framework with Symbolic-Numeric Scientific Mac...Building a General PDE Solving Framework with Symbolic-Numeric Scientific Mac...
Building a General PDE Solving Framework with Symbolic-Numeric Scientific Mac...
 
What is Fashion PLM and Why Do You Need It
What is Fashion PLM and Why Do You Need ItWhat is Fashion PLM and Why Do You Need It
What is Fashion PLM and Why Do You Need It
 
Cloud Data Center Network Construction - IEEE
Cloud Data Center Network Construction - IEEECloud Data Center Network Construction - IEEE
Cloud Data Center Network Construction - IEEE
 
MYjobs Presentation Django-based project
MYjobs Presentation Django-based projectMYjobs Presentation Django-based project
MYjobs Presentation Django-based project
 
software engineering Chapter 5 System modeling.pptx
software engineering Chapter 5 System modeling.pptxsoftware engineering Chapter 5 System modeling.pptx
software engineering Chapter 5 System modeling.pptx
 
Salesforce Certified Field Service Consultant
Salesforce Certified Field Service ConsultantSalesforce Certified Field Service Consultant
Salesforce Certified Field Service Consultant
 
Folding Cheat Sheet #4 - fourth in a series
Folding Cheat Sheet #4 - fourth in a seriesFolding Cheat Sheet #4 - fourth in a series
Folding Cheat Sheet #4 - fourth in a series
 
Adobe Marketo Engage Deep Dives: Using Webhooks to Transfer Data
Adobe Marketo Engage Deep Dives: Using Webhooks to Transfer DataAdobe Marketo Engage Deep Dives: Using Webhooks to Transfer Data
Adobe Marketo Engage Deep Dives: Using Webhooks to Transfer Data
 
Unveiling Design Patterns: A Visual Guide with UML Diagrams
Unveiling Design Patterns: A Visual Guide with UML DiagramsUnveiling Design Patterns: A Visual Guide with UML Diagrams
Unveiling Design Patterns: A Visual Guide with UML Diagrams
 
Building Real-Time Data Pipelines: Stream & Batch Processing workshop Slide
Building Real-Time Data Pipelines: Stream & Batch Processing workshop SlideBuilding Real-Time Data Pipelines: Stream & Batch Processing workshop Slide
Building Real-Time Data Pipelines: Stream & Batch Processing workshop Slide
 
ODSC - Batch to Stream workshop - integration of Apache Spark, Cassandra, Pos...
ODSC - Batch to Stream workshop - integration of Apache Spark, Cassandra, Pos...ODSC - Batch to Stream workshop - integration of Apache Spark, Cassandra, Pos...
ODSC - Batch to Stream workshop - integration of Apache Spark, Cassandra, Pos...
 
Hot Sexy call girls in Patel Nagar🔝 9953056974 🔝 escort Service
Hot Sexy call girls in Patel Nagar🔝 9953056974 🔝 escort ServiceHot Sexy call girls in Patel Nagar🔝 9953056974 🔝 escort Service
Hot Sexy call girls in Patel Nagar🔝 9953056974 🔝 escort Service
 
Advancing Engineering with AI through the Next Generation of Strategic Projec...
Advancing Engineering with AI through the Next Generation of Strategic Projec...Advancing Engineering with AI through the Next Generation of Strategic Projec...
Advancing Engineering with AI through the Next Generation of Strategic Projec...
 
KnowAPIs-UnknownPerf-jaxMainz-2024 (1).pptx
KnowAPIs-UnknownPerf-jaxMainz-2024 (1).pptxKnowAPIs-UnknownPerf-jaxMainz-2024 (1).pptx
KnowAPIs-UnknownPerf-jaxMainz-2024 (1).pptx
 
Asset Management Software - Infographic
Asset Management Software - InfographicAsset Management Software - Infographic
Asset Management Software - Infographic
 
Automate your Kamailio Test Calls - Kamailio World 2024
Automate your Kamailio Test Calls - Kamailio World 2024Automate your Kamailio Test Calls - Kamailio World 2024
Automate your Kamailio Test Calls - Kamailio World 2024
 
Der Spagat zwischen BIAS und FAIRNESS (2024)
Der Spagat zwischen BIAS und FAIRNESS (2024)Der Spagat zwischen BIAS und FAIRNESS (2024)
Der Spagat zwischen BIAS und FAIRNESS (2024)
 
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
 
Cloud Management Software Platforms: OpenStack
Cloud Management Software Platforms: OpenStackCloud Management Software Platforms: OpenStack
Cloud Management Software Platforms: OpenStack
 
Alluxio Monthly Webinar | Cloud-Native Model Training on Distributed Data
Alluxio Monthly Webinar | Cloud-Native Model Training on Distributed DataAlluxio Monthly Webinar | Cloud-Native Model Training on Distributed Data
Alluxio Monthly Webinar | Cloud-Native Model Training on Distributed Data
 

Quantum Computers.ppt

  • 1. Quantum Computers Siva Desaraju Bindu Katragadda Manusri Edupuganti presented by
  • 2. Outline Introduction Quantum computation Implementation Quantum compiler Error correction Architecture Classification Fabrication Challenges Advantages over classical computers Applications Recent advances Timeline Conclusion
  • 3. Introduction Superposition  Simultaneously possess two or more values Entanglement  Quantum states of two atoms correlated even though spatially separated!!!  Albert Einstein baffled “spooky action at a distance” Quantum Mechanics  Why? – Moore’s law  Study of matter at atomic level (The power of atoms)  Classical physics laws do not apply [2]
  • 4. Bits n Qubits Classical computers 0 or 1 (bits)  High/low voltage Quantum computers 0 or 1 or 0 & 1 (Qubits)  Nuclear spin up/down 0 or 1  Isolated atom spin up & down 0 & 1 Represent more with less (n bits 2n states) [2] ” To be or not to be. That is the question” – William Shakespeare The classic answers: ”to be” or ”not to be” The quantum answers: ”to be” or ”not to be” or a x (to be) + b x (not to be)
  • 5. Quantum Computation Prime factorization (Cryptography)  Peter Shor’s algorithm  Hard classical computation becomes easy quantum computation  Factor n bit integer in O(n3) Search an unordered list  Lov Grover’s algorithm  Hard classical computation becomes less hard quantum computation  n elements in n1/2 queries
  • 6. Implementation model Quantum program Quantum unitary transforms (gates) Quantum measurements Classical computation Classical control flow decisions Quantum compiler Instruction stream Classical bit instruction stream Early quantum computation - Circuit model(ASIC)
  • 7. Quantum Compiler Static precompiler  End-to-end error probability Dynamic compiler  Accepts the precompiled binary code & produces an instruction stream
  • 8. Error Correction Localized errors on a few qubits can have global impact Hamming code Difficulty of error correcting quantum states  Classical computers – bit flip  Quantum computers – bit flip + phase flip  Difficulty in measurement (collapses superposition) Quantum error correction code  [n,k] code uses n qubits to encode k qubits of data  Extra bits (n-k) are called ancilla bits  Ancilla bits are in initial state
  • 9. Architecture Aims of efficient architecture  Minimize error correction overhead  Support different algorithms & data sizes  Reliable data paths & efficient quantum memory Major components  Quantum ALU  Quantum memory  Dynamic scheduler
  • 11. Quantum ALU Sequence of transforms  the Hadamard (a radix-2, 1-qubit Fourier  transform)  identity (I, a quantum NOP)  bit flip (X, a quantum NOT)  phase flip (Z, which changes the signs of amplitudes)  bit and phase flip (Y)  rotation by π/4 (S)  rotation by π/8 (T)  controlled NOT (CNOT)
  • 12. Quantum Memory Reliable memory Refresh units Multiple memory banks
  • 14. Dynamic Scheduler Dynamic scheduler algorithm takes  Input - logical quantum operations, interleaved with classical control flow constructs  Output - physical individual qubit operations Uses knowledge of data size & physical qubit error rates
  • 15. Classification Quantum Computer Liquid Quantum Computer Solid Quantum Computer Si29 Doping Phosphorous Doping
  • 16. Liquid Quantum Computers NMR Technology Disadvantages  Massive redundancy  Not scalable
  • 17. Solid Quantum Computers Why silicon Chip design aims  Capturing & manipulating individual sub atomic particles  Harnessing, controlling & coordinating millions of particles at once
  • 18. Si29 Doping Need for Silicon 29 (Si29) doping Fabrication Advantages Disadvantages [9]
  • 20. Fabrication STM technology to pluck individual atoms from hydrogen  PH3 used instead of P
  • 22. Advantages over Classical computers Encode more information Powerful Massively parallel Easily crack secret codes Fast in searching databases Hard computational problems become tractable
  • 24. Timeline 2003 - A research team in Japan demonstrated the first solid state device needed to construct a viable quantum computer 2001 - First working 7-qubit NMR computer demonstrated at IBM’s Almaden Research Center. First execution of Shor’s algorithm. 2000 - First working 5-qubit NMR computer demonstrated at IBM's Almaden Research Center. First execution of order finding (part of Shor's algorithm). 1999 - First working 3-qubit NMR computer demonstrated at IBM's Almaden Research Center. First execution of Grover's algorithm. 1998 - First working 2-qubit NMR computer demonstrated at University of California Berkeley. 1997 - MIT published the first papers on quantum computers based on spin resonance & thermal ensembles. 1996 - Lov Grover at Bell Labs invented the quantum database search algorithm 1995 - Shor proposed the first scheme for quantum error correction
  • 25. Conclusion…will this be ever true? Millions into research With a 100 qubit computer you can represent all atoms in the universe. If you succeed, the world will be at your feet [6]
  • 26. References [1] http://www.cs.washington.edu/homes/oskin/Oskin-A-Practical- Architecture-for-Reliable-Quantum-Computers.pdf [2] http://www.qubit.org [3] http://www.nature.com [4] http://www.wikipedia.com [5] http://www.howstuffworks.com [6] http://www.physicsweb.org/toc/world/11/3 [7] http://www.cs.ualberta.ca/~bulitko/qc/schedule/slides/QCSS- 2002-06-18.ppt [8] http://physics.about.com/cs/quantumphysics/ [9] http://www.trnmag.com/Stories/2002/082102/Chip_ design_aims_for_quantum_leap_082102.html
  • 27. Puzzled??? "I think I can safely say that nobody understands quantum mechanics." - Richard P. Feynman “Anybody who thinks they understand quantum physics is wrong." - Niels Bohr