1 / 45

Quantum Computing MAS 725

Quantum Computing MAS 725. Hartmut Klauck NTU 13.2.2012. Organization. Lectures: Mo. 10:00, TR+9 Lecturer: Hartmut Klauck Office: SPMS-MAS-05-44 Website: http://www.ntu.edu.sg/home/hklauck/QC12.html. Grading. Homework (biweekly): 40% Final exam: 60%

barto
Download Presentation

Quantum Computing MAS 725

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Quantum ComputingMAS 725 HartmutKlauckNTU 13.2.2012

  2. Organization • Lectures: Mo. 10:00, TR+9 • Lecturer: HartmutKlauck • Office: SPMS-MAS-05-44 • Website: http://www.ntu.edu.sg/home/hklauck/QC12.html

  3. Grading • Homework (biweekly): 40% • Final exam: 60% • Homework must be written individually! • And handed in on time

  4. Required Background • Linear algebra • Some basic probability theory • No background in physics required

  5. Textbook • Nielsen/Chuang: Quantum Computation and Quantum Information(Cambridge)

  6. Recommended Reading • http://homepages.cwi.nl/~rdewolf/qcnotes.pdf • http://www.cs.berkeley.edu/~vazirani/s09quantum.html • http://www.cs.uwaterloo.ca/~watrous/lecture-notes.html

  7. Quantum Mechanics • Quantum mechanics is one of the basic theories of physics • Quantum mechanics is concerned with states, and how they evolve/change • Includes many “strange” effects that are different from “classical”, Newtonian mechanics: • Superposition • Entanglement • Such effects usually appear in very small systems

  8. Quantum Mechanics and Computing • Moore’s Law: The number of transistors that can be placed on a chip doubles every two years • I.e., the computational power doubles • This trend has been approximately true for more than 50 years • Main way to achieve this is by making smaller transistors! • Even today quantum mechanical effects are important to chip design

  9. Quantum Mechanics and Computing • Another problem: heat generation in integrated circuits • This heat is the result of erasing information • Quantum computations are (for the most part) reversible • Reversible computations (ideally) do not generate (much)heat

  10. Quantum Mechanics and Computing • Chip designers nowadays mostly “combat” quantum effects • Is it possible to make good use of quantum effects?

  11. Quantum Computing • First suggested by Feynman and Benioff in the 1980’s • Feynman’s observation: • Simulating quantum systems on classical computers takes exponential time in the ‘size’ of the quantum system • Conclusion: build universal quantum systems • Quantum systems that can simulate all other quantum systems (up to a size) • I.e., quantum computers

  12. Quantum Computing • Hence reasons for investigating quantum computing are: • Making good use of quantum effects instead of trying to force microscopic system to adhere to classical physics • There are quantum algorithms and protocols that achieve things that seem to be impossible for classical algorithms/protocols • If the world is quantum mechanical, the ultimate limits of computation are determined by quantum physics

  13. Quantum Computing Examples • Some example of tasks that quantum computers can do: • Efficiently factor natural numbers • Break public key cryptosystems like RSA • Search an unordered database in sublinear time • Provide cryptographic protocols that are secure without placing assumptions on the computational power of an eavesdropper

  14. Quantum Computing Models • There are several models of quantum computing • E.g. Deutsch (1985) defined Quantum Turing Machines as a universal model of quantum computation • Another (easier to handle)model are quantum circuits • But first we need to understand some basics about quantum mechanics

  15. Quantum Mechanics • The double slit experiment for light

  16. Quantum Mechanics • Perform the “same” experiment with electrons • We observe the same outcome of the experiment • Even when single electrons are emitted • The wave-like behavior is not just statistical

  17. Quantum Mechanics • The name “Quantum Mechanics” (coined by Planck) derives from the fact that certain quantities can change only by a discrete amount • E.g. The smallest unit of electromagnetic radiation is a photon (a quantum of light) • It is possible to emit and detect single photons

  18. Quantum Mechanics

  19. Quantum Mechanics

  20. Some History • Development of quantum mechanics:Planck 1900, Schrödinger, Heisenberg, Bohr, Einstein..... • 1930’s: von Neumann’s formalism • 1935: Einstein, Podolsky, Rosen describe “entanglement” in an attempt to show that quantum mechanics is not a “complete” theory of reality (German “Verschränkung”) • Today quantum mechanics is the best established theory in physics

  21. (Quantum) Computer Science • 1936: Turing defines a “universal” machine (Church Turing Thesis) • 1948: Shannon’s Information Theory • 1965: Moore’s Law • 1982: Feynman proposes quantum computers (to simulate quantum systems) • 1982 Wiesner: first proposal of quantum cryptography published (after more than 10 years)

  22. (Quantum) Computer Science • 1985: Deutschfinds the first quantum algorithm • 1993: quantum teleportation • 1994: Shor finds a quantum algorithm for factorization • 1996: Grover’s algorithm finds a marked element in a database with n elements in time • Since then the field is steadily growing…

  23. Quantum States • Quantum mechanics is an abstract theory of states and transformations on states • Can be derived from certain axioms • Quantum states are vectors in a Hilbert space • Hilbert Space: • A real or complex vector space with an inner product that maps vectors to their length • Must be complete • We will only consider finite dimensional spaces • Usually either Rn or Cn

  24. Bits • A bit is either the value 0 or the value 1, stored in a register • We will write the state of a bit as|0i, |1i • Examples: • A bit stored in the memory of a computer • The path that a ball took in a giant double slit experiment

  25. Bits and Qubits • We identify the states |0i, |1i with the basis vectors of a two dimensional space (say C2):(1,0) and (0,1) • The states of a quantum bit (qubit) are arbitrary unit vectors in C2 • Hence all the states of a qubit are:|0i + |1iwith ||2 +||2=1

  26. Qubits • |0i, |1i are two basis vectors in C2 • Qubits have states:  |0i+ |1iwith ||2 +||2=1 • ,are called amplitudes • Qubit states are unit vectors under the euclidean norm

  27. Comparison to Probability Theory • Suppose we have a random bit (say a coin flip) • Then we need to specify the probability of 1 and 0 (coin may not be fair) • For example0 has probability p, 1 has probability 1-p) probability distributions on bits are unit vectors under 1-Norm • Qubits: , are complex numbers,possibly negative! • The squares of the absolute values of the amplitudes form a probability distribution

  28. The Quantum Formalism • Quantum states are vectors in a Hilbert space • The Hilbert space corresponds to a register that can hold a quantum state • Hilbert space here: Ckwith the inner producth (vi) | (wi) i = i=1…k vi* wix*: complex conjugate

  29. Dirac Notation • h | “BRA” row vector • |  i “KET” column vector • h |  i inner product (product of a row and a column vector) • |ÁihÃ| outer (matrix valued) product

  30. Many Qubits • To hold k qubits we need a Hilbert space of dimension 2k • I.e. 2k basis vectors (corresponding to the 2k values of k bits) • First notation: |ii, i=1,...,2k. Unit vectors are of the formii |ii; i=1....2k with i |i |2 = 1 • Better notation: identify i=1...2k with x2{0,1}k • Basis states are |xi, x2 {0,1}k • Basis states correspond to classical values a register can hold • General quantum states are linear combinations of the 2k classical (basis) states • Also called “superpositions”

  31. Tensor Product • For Hilbert spacesH, K, with dimensions dHanddKtheir tensor product H­K is a Hilbert space of dimension dH¢dK • Tensor product of vectors: (a1,..., al) ­ (b1,...,br)= (a1b1,a1b2,...,a1br,a2 b1,......,albr) • Example: |0i = (10)T; |1i= (01)Tand |01i= |0i­|1i = (0100)T • A basis of H­K: all|xi­|yi=|xyiwhere |xi,|yi are basis vectors of H,K • Not all vectors in H­K are tensor products of vectors in H and K

  32. Example • Basis of C4: • |00i, |01i, |10i, |11i • Another basis: • (|00i + |11i)(|00i - |11i)(|01i + |10i)(|01i - |10i)(scaled by square root of 2) • None of these are tensor products of vectors in C2

  33. What can we do with one or more qubits? • Quantum systems evolve according to the Schrödinger equation • The result can be described as the application of a unitary transformation to the quantum state • Additionally quantum states can be measured • This leads to observable output • Need some background from linear algebra…

  34. Linear Algebra • Linear transformations: A(x+y)=Ax + Ay • x,y: vectors in Ck, A: k£k matrix (complex entries) • Over the reals a linear transformation O is orthogonal, ifOOT=I • Over the complex numbers a matrix U is unitary,ifUUy=IU*: take the complex conjugate of all entriesUy= (U*)T • Unitary transformation preserve the euclidean length of vectors • Transformations in QM: unitary(i.e., reversible and length preserving)

  35. Examples • On one qubit:classical transformations:identity, negation • Hadamard Transformation:

  36. Applying Hadamard

  37. Applying Hadamard

  38. Applying Hadamard

  39. Unitary Transformations • Define U |xifor allx2 {0,1}k) U is defined. The U|xi need to be unit vectors andU|xi?U|yi for all xy • Tensor product for matrices: • A ­ B=

  40. Unitary Transformations

  41. Hadamard Transformation • x,z2{0,1}n and x¢z=xizi • For any x we have H­n |xi=1/2n/2 (|0i +(-1)x(1) |1i)­­(|0i +(-1)x(n) |1i)

  42. Applying many unitary transformations • Later we will construct unitary transformations as the product of many “simple” unitary transformation • First applying a unitary U, and then a unitary V is the same as applying the product VU. • Note that the product of two unitary matrices is unitary • Careful: matrix multiplication is not commutative! • The exact sequence of multiplications matters

  43. Measurements • Quantum states (unit vectors in Ck) can be changes by applying a unitary transformation • Computations on quantum states consist of unitary transformations and measurements • Measurements allow us to access the result of a computation • What happens if we measure ii |ii ? • The result will be i with probability |i|2 • i |i2|=1 is very helpful now! • After measuring the value i the state “collapses” to |ii

  44. Example • Measuring the state • Will result in the outcome 0 or 1, each with probability ½ • If we measured 1, the resulting state after the measurement will be

  45. Overview • Quantum states: unit vectors in a Hilbert space, the log of the dimension corresponds to the number of qubits • States in a Hilbert space of dimension 2k correspond to superpositions of strings of length k and the space is a register of k qubits • Evolution: by applying unity transformations • Measurement: i |ii results in output iwith probability |i|2, the state collapses to |iiif i is the measurement result

More Related