1. Quantum Computing
Hakem Alazmi Jhilakshi Sharma Linda Vu

2. Outline Fundamentals of Quantum Computing
Principles of Quantum Computing:
Qubits
Superposition
Entanglement
Classification
Classical vs. Quantum Computing
Types of Quantum Computing
Time Complexity
Advantages & Disadvantages
Present & Future Applications

3. Quantum Computing Timeline
1980’s Richard Feynman: “ We can leverage quantum properties for computation and solve problems unsolvable by classical computing”
1985 David Deutsch: called as “ Father” of quantum computing.
1994 Petre Shor’s algorithms for quantum code breaking.
2007 D wave, announced the first quantum computing chip.

4. Why Quantum Computing? Slowing down of Moore’s law.
Size of transistors.
Classical computers lag in solving many kinds of numerical problems. For example: Factorization.

5. What is Quantum Computing?
Fundamental Theories of Quantum Computing
Quantum computing is the intersection of math, physics, and computer science. Modern physics explains the behavior of matter and energy at an atomic and subatomic level.
Quantum bits
Superposition
Entanglement

6. Quantum Bit

7. Quantum Superposition
Possible states
Spin up and spin down
What happens when a qubit is observed or measured?
Depends on the probability
Benefits of quantum superposition
Calculations
Parallelism
What about multiple quantum bits?

8. Quantum Entanglement System of qubits
Quantum entanglement is a physical phenomenon that occurs when pairs or groups of qubits generated, interact, or share spatial proximity in ways such that the quantum state of each particle cannot be described independently of the state of the other(s).
System of qubits
System of qubits

9. Classical Computers vs Quantum Computers
Data storage: Based on voltage vs electron spin.
Speed: Measured in gigahertz vs. teraflops
Information Processing: Logic gates vs quantum logic gates
Circuit: Macroscopic technologies vs microscopic technologies.

10. Types of Quantum Computing
Quantum Annealers:
It performs specific functions.
Analogue Quantum:
It contains 50 to 100 qubits.
Universal Quantum:
It contains 100,000 qubits.

11. Quantum Computing Hardware Implementation Methods
Qubits
Most renowned way of building quantum computing is by Qubits.
Quantum dots:
It is also known as Ion Trap.
Nuclear Magnetic Resonance:
It uses the spin states of molecules as qubits.

12. Time Complexity
Time complexity of Quantum Computers is explained by the Quantum Complexity Theory
Computational complex theory in theoretical computer science
Quantum Query Complexity
Grover’s Algorithm
Has O√N complexity, that is, uses just O√N evaluations of the function, where N is the size of the domain
The quantum complexity classes BQP and QMA are the bounded-error quantum analogues of computational classes P and NP
BQP
Class of decision problems solvable by a quantum computer in polynomial time
QMA
The proofs have to be verifiable in polynomial time on a quantum computer

13. Advantages of Quantum Computers
Information Storage Pattern - Flexibility on storage
Speed - Perform multiple task simultaneously
Security - Provides unbreakable security features
Power Efficient - Quantum computers reduces power consumption by 100 up to 1000 times because of quantum tunneling
AI - Making exponentially fast connections for machine learning operations
Problem solving - Can solve unsolvable problems such as the traveling salesman problem and bounded-error quantum polynomial time (BQP) which are decision based problems

14. Disadvantages to Quantum Computing
Difficult to build - Quantum Computers need stability because of the atoms, any interference will cause the computer to be disrupted and cause the quantum particles to behave in a strange behavior
Temperature - Quantum Computers need to be in a cold environment (-460 degrees Fahrenheit)
Incompatibility - Quantum algorithms do not apply to most classical computing applications
Sensitivity - Quantum Computers are sensitive
Security - Quantum Computers will be able to decrypt and encrypt security that is much more difficult to break and/or encode.

15. Challenges in Implementation
Evaluating Time Complexity
Evaluating the complexity/power of various quantum models of computation, proof systems, games (sometimes suggested by theoretical physicists), reducing some of them to others
Information Processing
Quantum information processing with new particles and physical systems
New quantum models of computations and new types of quantum error-correction
Decoherence
Effective quantum control in reproducible quantum systems (including the control of quantum decoherence)
Quantum Error Correction
Consumer Friendly Implementation

16. Present and future applications
Present Applications:
Bristlecone, by Google
Boasts of 72 qubits
Q System, by IBM
Uses 49 qubits
D - Wave 2000Q, Goldman Sachs
a quantum annealing system with 2000 qubits and advanced feature controls
Hybrid Quantum/Classical Computing Applications
Future Applications:
Artificial Intelligence
Optimising search through gigantic datasets
Cybersecurity
Breaking Encryption
Quantum Enabled Discoveries

17. Recap

18. References
Project