Quantum Computing

1. Quantum Computing Paul McGuirk 21 April 2005

2. Motivation: Factorization • An important problem in computing is finding the prime factorization of an integer. • Using classical algorithms, a number N of size n = log2(N) takes super-polynomial time. time is about the best we can get.

3. Motivation: Factorization • For example, on a particular personal computer, it may take four hours to factor a number with 78 digits (n = 256). • On the same computer, a 174 digit number (n = 576, which is the record) would take 43 days. • A 617 digit number (n = 2048, current size recommended for RSA encryption), would take 300,000 years.

4. Motivation: Factorization • Such superpolynomial growth is characteristic of many algorithms in classical computing. • However: Quantum Computing could provide a miraculous decrease in time. • A quantum algorithm reduces the integer factorization problem to polynomial time ( ). • Then, if n = 256 number takes four hours, n = 2048 will take 85 days.

5. Outline • Review of Classical Computing • Qubits and Quantum Operations • Quantum Algorithms • Physical Implementations • Future Developments

6. Outline • Review of Classical Computing • Data Representation • Operations • Qubits and Quantum Operations • Quantum Algorithms • Physical Implementations • Future Developments

7. Classical Data Representation • The basic unit in classical data is a binary digit, called a bit, that can take on the value 0 or 1. • In classical computing, we represent a datum by a string of bits. • The letter ‘A’ may be written 0100 0001 • The number 137 can be written 1000 1001

8. Classical Operations • All operations in classical computing are based on logic gates. • For example, the logical AND gate takes in two bits and returns 1 if and only if both inputs are 1.

9. Classical Algorithm • We define a Classical Algorithm to be any sequence of such classical operations (usually to do something useful). • A classical computer is any device that can implement a classical algorithm.

10. Classical Computing • Although modern classical computers depend on quantum mechanics, the algorithms that they implement do not. • We could, in principle, design a classical computer that does not depend on quantum mechanics.

11. Lego Computing • For example, one could build a computer out of Legos.

12. Outline • Review of Classical Computing • Qubits and Quantum Operations • Qubits as Two-State Systems • Quantum Gates • Quantum Registers • Entanglement • Quantum Algorithms • Physical Implementations • Future Developments

13. Qubits • A Quantum Bit (Qubit) is a two-level quantum system. • We can label the states |0> and |1>. • In principle, this could be any two-level system. |1> |0>

14. Qubits • Unlike a classical bit, which is definitely in either state, the state of a Qubit is in general a mix of |0> and |1>. • We assume a normalized state:

15. Qubits • For convenience, we will use the matrix representation

16. Quantum Gate • A Quantum Logic Gate is an operation that we perform on one or more Qubits that yields another set of Qubits. • We can represent them as linear operators in the Hilbert space of the system.

17. Quantum NOT Gate • As in classical computing, the NOT gate returns a 0 if the input is 1 and a 1 if the input is 0. • The matrix representation is

18. Other Quantum Gates • Other gates include the Hadamard-Walsh matrix: • And Phase Flip operation:

19. Multiple Qubits • Any useful classical computer has more than one bit. Likewise, a Quantum Computer will probably consist of multiple qubits. • A system of n Qubits is called a Quantum Register of length n. • To represent that Qubit 1 has value b1, Qubit 2 has value b2, etc., we will use the notation:

20. Multiple Qubits • For n Qubits, the vector representing the state is a 2n column vector. • The operations are then 2n x 2n matrices. • For n = 2, we use the representations

21. Quantum CNOT Gate • An important Quantum Gate for n = 2 is the conditional not gate. • The conditional not gate flips the second bit if and only if the first bit is on.

22. Reversibility and No-Cloning • In Quantum Computing, we use unitary operations (U*U = 1). • This ensures that all of the operations that we perform are reversible. • This fact is important, because there is no way to perfectly copy a state in Quantum Computing (No-Cloning Theorem).

23. No-Cloning Theorem • That is, the No-Cloning Theorem says that there is no linear operation that copy an arbitrary state to one of the basis states: • We can get around this if we are only interested in copying basis vectors, though.

24. Entanglement • In Quantum Mechanics, it sometimes occurs that a measurement of one particle will effect the state of another particle, even though classically there is no direct interaction. (This is a controversial interpretation). • When this happens, the state of the two particles is said to be entangled.

25. Entanglement: Formalism • More formally, a two-particle state is entangled if it cannot be written as a product of two one-particle states. • If a state is not entangled, it is decomposable.

26. Entanglement: Example • The state of two spinors is prepared such that the z-component of the spin is zero. • If we measure m = +1/2 for one particle, then the other particle must have m =-1/2. • The measurement performed on one particle resulted in the collapse of the wavefunction of the other particle.

27. Outline • Review of Classical Computing • Qubits and Quantum Operations • Quantum Algorithms • Definitions • Universal Gate Sets • Example: Quantum Teleportation • Physical Implementations • Future Developments

28. Definitions • A Quantum Algorithm is any algorithm that requires Quantum Mechanics to implement. • A Quantum Computer is any device that can implement a Quantum Algorithm.

29. Universal Gate Sets • It would be convenient if there was a small set of operations from which all other operations could be produced. • That is, a set of operators {U1,…,Un} such that any other operator W could be written W = UiUj…Uk. • Such a set of operators in the context of computation is called a universal gate set.

30. Classical NAND Gate • One universal set for Classical Computation consists of only the NAND gate which returns 0 only if the two inputs are 1.

31. Quantum Universal Gate Set • There are a few universal sets in Quantum Computing. • Two convenient sets: • CNOT and single Qubit Gates • CNOT, Hadamard-Walsh, and Phase Flips • Having such a set could greatly simplify implementation and design of Quantum Algorithms.

32. Quantum Teleportation • Suppose two parties, Alice and Bob. • Alice is in possession of a state, but does not know anything about it. • Alice desires to send this state to Bob, but cannot do so directly (no Quantum Channel). They can exchange classical data (there is a Classical Channel).

33. Quantum Teleportation • Alice cannot observe this state to give the information about it to Bob, since observing it destroys the state. • Nor could she, even if given an infinite number of states, reconstruct the state from probability measurements since phase information is lost.

34. Quantum Teleportation • Alice cannot give the state to Bob by classical means. • She can, however, communicate the state if Alice and Bob share a register of length 2 that is prepared in an entangled state. Alice and Bob each have access to one Qubit.

35. Quantum Teleportation • The full-state then is the product of Alice’s Qubit and the shared register: • The notation is such that the left-most Qubit is Alice’s mystery Qubit, the middle one is Alice’s half of register, and the rightmost is Bob’s half of the register.

36. Quantum Teleportation Classical Channel Alice Bob Copied State Initial State Entangled Source

37. Quantum Teleportation • Alice then performs a CNOT operation on her half of the register, using her mystery bit as the control.

38. Quantum Teleportation • She then applies the Hadamard-Walsh matrix to the state. The result can be written where the lone Qubit is Bob’s half of the register.

39. Quantum Teleportation • Alice then observes her two Qubits. Note that this destroys her original state. • The outcome of this observation is totally unpredictable. • After observing her bits, Bob knows what his bit must be, because of the entanglement of the states.

40. Quantum Teleportation • If Alice Observes 00, then Bob has the original state. Otherwise, Bob has some other linear combination of Qubits. • The linear combination is known, so Bob can perform a specific operation to retrieve the original state.

41. Quantum Teleportation • This procedure was fundamentally quantum mechanical. It relied on superposition and, especially, entanglement of states. • It was necessary to account for the probabilistic nature of Quantum Mechanics by giving Alice and Bob particular actions to take, depending on the (unpredictable) outcome of the observation.

42. Quantum Teleportation • This experiment has been performed. • Bouwmeester, et al. in 1997. • Boschi, et al. in 1998. • Both experiments involved the transportation of a state of polarization.

43. Outline • Review of Classical Computing • Qubits and Quantum Operations • Quantum Algorithms • Physical Implementations • Requirements • NMR Implementation • Future Developments

44. Physical Implementation • Any physical implementation of a quantum computer must have the following properties to be practical(DiVincenzo) • The number of Qubits can be increased • Qubits can be arbitrarily initialized • A Universal Gate Set must exist • Qubits can be easily read • Decoherence time is relatively small

45. Decoherence • As the number of Qubits increases, the influence of external environment perturbs the system. • This causes the states in the computer to change in a way that is completely unintended and is unpredictable, rendering the computer useless. • This is called decoherence.

46. Shor’s Algorithm • A Quantum Algorithm, due to P. W. Shor (1994) allows for very fast factoring of numbers. • The algorithm uses other algorithms: the Quantum Fourier Transform, and Euclid’s Algorithm. • It also relies on elements of group theory.

47. Shor’s Algorithm • Because of the unpredictability of Quantum Mechanics, it only gives the correct answer to within a certain probability. • Multiple runs can be performed to increase the probability that the answer is correct. This increases the complexity to • A Quantum Computer with 7 Qubits was developed in 2001 to implement Shor’s algorithm to factor 15.

48. NMR Implementation • Vandersypen, et al. used an NMR computer to implement Shor’s algorithm. • We can consider two different Qubits as two different nuclei in the magnetic field, oriented in slightly different directions, so that the energy splitting isdifferent between them. |1>2 |1>1 |0>1 |0>2

49. NMR Implementation • Since the energy splittings are different, we can control each Qubit independently by using different frequencies of radiation. • The two Qubits will also interact slightly due to their spins. This allows for the implementation of a CNOT gate.

50. Other Implementations • There are other possible ways to produce quantum computers: • Quantum dots • Superconductors • Lasers acting on ion traps • Molecular magnetic computers