IQC

Cards (25)

  • Every Qubit is in superposition between 0 or 1
  • A variable x can be in superposition between all values
  • Any probalistic process can be written as nxn-matrix A Pr[output j | input i] = A_ji
  • Probabilistic -> Quantum :
    • distributions -> quantum state
    • probabilities -> amplitudes
    • deterministic possibilities -> classical possibilities/states
    • processes (stoch. matrices) -> unitary matrices
  • Probabilistically -> Quantumly
    distribution is a vector because it "mixes" deterministic possabilities ->
    quantum state is a vector because superposition "mixes" classical possabilities
  • Quantum systems are described by a list of n classical possibilities
  • A quantum state is a vector ψCn\psi \in \mathbb{C}^n with ψi2=\sum |\psi_i|^2 =1 1 or ψ=||\psi|| =1 1
  • Valid quantum processes are unitary matrices
  • A (square) matrix U is unitary if Uψ=||U_\psi||=1 1 whenψ=||\psi||=1 1
  • U is unitary if UtU=U^t U =I>(Ut=konjugiert+transponiert) I -> (U^t = konjugiert + transponiert)
  • Description of Systems
    • List of deterministic possibilities 1,...,N -> Probabilistic
    • List of classical possibilities 1,...,N -> Quantum
  • State of Systems
    • N-vector ψRn=\psi \in \mathbb{R}^n = probabilistic distribution ψi=\sum \psi_i =1,ψi>= 1, \psi_i >=0 0
    • N-vector ψCn=\psi \in \mathbb{C}^n =quantum state ψi2=\sum |\psi_i|^2 =1 1
  • Development of system
    Probabilistic:
    • Stochastic matrix RNxN\in R^{NxN}(Every column is probabilistic distribution)
    Quantum
    • Unitary matrix U UCNxNU\in \mathbb{C}^{NxN} maps quantum state to quantum state
    • UtU=U^t U =I I
  • Given distribution μ\mu, if we observe it , get outcome i with prob μi\mu_iand in that : new distribution is : eie_i:= (0,...,0,1,0,...0) at the i-th element
  • Measurments do change the system
  • Observation : Probabilitic -> Quantum
    Update of knowledge ->
    State becomes e_i -> physical effect -> no superposition -> no interference
  • ∣∣ϕ∣∣= sqrt(\sum|ϕi\phi_i|^2)
  • Hadamard H = 12\frac 1 {\sqrt2} (1111\begin{matrix} 1&1\\1&-1 \end{matrix})
  • You are given a n-dimensional probability distribution vector x.What is the average (a.k.a. mean value) of the entries x_i? :

    1/n
  • A quantum measurement changes the outcome probabilities of future observations.
  • Consider a vector x∈R^n and a vector y∈R^m. Then the tensor product x⊗y is in R^k.
    The value of k is n*m
  • |+> :=12\frac 1 {\sqrt2}|0> + 12\frac 1 {\sqrt2}|1> = H(|0>)
  • |-> := 12\frac 1 {\sqrt2}|0> - ​12\frac 1 {\sqrt2}|1> = H(|1>)
  • H(|+>) = H(120>\frac 1 {\sqrt2}|0>+ 121>\frac 1 {\sqrt2}|1>) = 1/2(|0> + |1>) + 1/2(|0> - |1>) = |0>
    • H(|->) = H(120>\frac 1 {\sqrt2}|0>-121>\frac 1 {\sqrt2}|1>) = 1/2(|0> + |1>) - 1/2(|0> - |1>) = |1>