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Quantum Computation

Query Complex

2019-09-05Original-language archivelegacy assets may be incomplete

Polynomial method

  • T-query algorithm: ψxt=UtOxUt1OxU2OxU1Oxψ=x,iαx,i(t)iψx,it|\psi_x^t\rangle=U_tO_xU_{t-1}O_x\cdots U_2O_xU_1O_x|\psi\rangle=\sum_{x,i}\alpha_{x,i}^{(t)}|i\rangle|\psi_{x,i}^t\rangle
    • αx,it\alpha_{x,i}^t is a deg tt polynomial
    • probability outputting f(x)f(x) is a degree 2t2t polynomial
  • Adversary method - polynomial method
    • negative adversary method
    • learning graph
  • degϵ(f)=min{d:f is a degree d polynomial and x{0,1}n,f(x)p(x)13}\text{deg}_\epsilon(f)=\min\{d:f \text{ is a degree }d\text{ polynomial and }\forall x\in\{0,1\}^n,|f(x)-p(x)|\leq\frac{1}{3}\}
  • Qϵ(f)=min{t:tQ_\epsilon(f)=\min\{t:\exists t-query algorithm that computes ff correctly with probabiliy at least 1ϵ}1-\epsilon\}
  • Theorem: Qϵ(f)12degϵ(f)Q_\epsilon(f)\geq\frac{1}{2}\text{deg}_\epsilon(f)
  • Parity function: f:{0,1}n{0,1},f(x)=[2ixi]f:\{0,1\}^n\rightarrow\{0,1\},f(x)=[2|\sum_i x_i]
    • degϵ(f)=Ω(n)\text{deg}_\epsilon(f)=\Omega(n)
  • Symmetriazation
    • Given any nn-variate multilinear polynomiial pp, P(k)=Ex=k[p(x)]P(k)=E_{|x|=k}[p(x)]. Then PP is a polynomial with degree deg(P)deg(P)\text{deg}(P)\leq\text{deg}(P)
    • Symmetrizing + Symmetrizing the approximating function
  • Unstructured search: deg(P)Ω(n)\text{deg}(P)\geq\Omega(n)
  • if the number of marked items is unknown, then there is no quantum speedup
  • Theorem(Paturi 92): degϵ(f)=Θ(n(nΓ(f)))\text{deg}_\epsilon(f)=\Theta(\sqrt{n(n-\Gamma(f))})
  • Theorem(Beals et.al. 95): for symmteric functions, Qϵ(f)=Θ(n(nΓ(f)))Q_\epsilon(f)=\Theta(\sqrt{n(n-\Gamma(f))})
  • Theorem: for any total booleam function ff, it holds that D(f)O(Qϵ(f)6)D(f)\leq O(Q_\epsilon(f)^6)
  • Theorem(2016): There exists a total Boolean functiion satisfying that Rϵ(f)Ω(Qϵ(f)2.5)R_\epsilon(f)\geq\Omega(Q_\epsilon(f)^{2.5})
    • Open Problam: gapp between Rϵ(f)R_\epsilon(f) and Qϵ(f)Q_\epsilon(f)
  • Collision Problem

Adversary method for a pair of inputs

  • Adversary matrix Γ\Gamma
    • Γxy=Γyx0\Gamma_{xy}=\Gamma_{yx}\geq0
    • if f(x)=f(y)f(x)=f(y) then Γxy=0\Gamma_{xy}=0
  • Wj=xyΓxyaxayψxtψytW^j=\sum_{xy}\Gamma_{xy}a_x^**a_y\langle\psi_x^t|\psi_y^t\rangle
    • W0=Γ|W^0|=\|\Gamma\|
      • Γ\|\Gamma\| is the largest eigenvalue in absolute value
      • (ax)(a_x) is the priciple eigenvector of TT
      • (Γi)xy=Γxy(\Gamma_i)_{xy}=\Gamma_{xy} if xiyix_i\neq y_i
    • WT2ϵ(1ϵ)Γ|W^T|\leq2\sqrt{\epsilon(1-\epsilon)}\|\Gamma\|
    • Wj+1Wj2max1inΓi|W^{j+1}-W^j|\leq2\max_{1\leq i\leq n}\|\Gamma_i\|
  • Theorem: Qϵ(f)Adv(f)=maxΓΓmaxiΓiQ_\epsilon(f)\geq\text{Adv}(f)=\max_{\Gamma}\frac{\|\Gamma\|}{\max_i\|\Gamma_i\|}
  • Other adversary methods
    • Weighted adversary method [Ambainis 03]
    • Strong weighted adversary method
    • Kolmogorov complexity
    • Minimax method
    • Theorem: All adversary methods are equivalent[SS'04]
  • Limitation of adversary method
    • certificate complexity
      • 11-certificate: C1(f)C_1(f)
      • 00-certificate: C0(f)C_0(f)
    • Adv(f)O(C0(f)C1(f))\text{Adv}(f)\leq O(\sqrt{C_0(f)C_1(f)})
    • Element-Distinctness
    • 与 Polynomial method 不可比较
  • General adversary matrix Γ\Gamma
    • Γxy=ΓyxR\Gamma_{xy}=\Gamma_{yx}\in\mathbb{R}
    • if f(x)=f(y)f(x)=f(y) then Γxy=0\Gamma_{xy}=0
    • Qϵ(f)=Θ(Adv±(f))Q_\epsilon(f)=\Theta(\text{Adv}^{\pm}(f)) [Reichardt 09,11]
    • Learning graph [Belios]

Quantum Operations and Quantum Noise

  • Classical noise

[q0q1]=[1ppp1p][p0p1]\begin{bmatrix}q_0\newline q_1\end{bmatrix}=\begin{bmatrix}1-p & p'\newline p& 1-p'\end{bmatrix}\begin{bmatrix}p_0\newline p_1\end{bmatrix}

  • Quantum operations: ρE(ρ)\rho\rightarrow\mathcal{E}(\rho)
    • Unitary: ρUρU\rho\rightarrow U\rho U^\dagger
    • Partial trace: ρABρA\rho_{AB}\rightarrow \rho_A
    • Attachment: ρρσ0\rho\rightarrow\rho\otimes\sigma_0
  • E:M2nM2m\mathcal{E}:M_{2^n}\rightarrow M_{2^m}
    • Linearity
    • Trace-preserving
    • Positivity
    • Complete Positivity E(ρ)Ik\mathcal{E}(\rho)\otimes I_k positive for any integer k>0k>0
  • System coupled to environment
    • E(X)=TrBU(ρ00B)U\mathcal{E}(X)=Tr_B U(\rho\otimes|0\rangle\langle 0|_B)U^\dagger
    • E(ρ)=kEkρEk\mathcal{E}(\rho)=\sum_kE_k\rho E_k^\dagger, kEkEk=I\sum_kE_k^\dagger E_k=I
  • Theorem: Three conditions equivalent (合法量子操作)
  • Quantum Noise
    • Bit flip channel
    • Phase flip channel
    • Bit-phase flip channel
    • Depolarizing channel: E(ρ)=pI2+(1p)ρ=(1p)ρ+p3(XρX+YρY+ZρZ)\mathcal{E}(\rho)=p\cdot\frac{I}{2}+(1-p)\rho=(1-p)\rho+\frac{p}{3}(X\rho X+Y\rho Y+Z\rho Z)
      • XMX+YMY+ZMZ+M=2TrMIXMX+YMY+ZMZ+M=2TrM\cdot I
    • Amplitude damping channel
  • Theorem: Let E:M2M2\mathcal{E}:M_2\rightarrow M_2 be a one-qubit quantum operation, then there exist real numbers a,b,c,da,b,c,d such that E(ρ)=aρ+bXρX+cYρY+dZρZ,a2+b2+c2+d2=1\mathcal{E}(\rho)=a\rho+bX\rho X+cY\rho Y+dZ\rho Z,a^2+b^2+c^2+d^2=1