Machine Learning Meets Quantum Computation
Min-Hsiu Hsieh (謝明修)
University of Technology Sydney
f:X→Y
f: X\to Y
Unknown Function
{(xi,yi)}i=1N
\{(x_i,y_i)\}_{i=1}^N
Training Data
H
\mathcal{H}
Hypothesis Set
Learning
Algorithm
f^
\hat{f}
Comp. Complexity
Sample Complexity
Quantum Challenge #1
Noncommutative: AB=BA
Moment Generating Function: Eeθ(A+B)=EeθAeθB
ba↦AB−1?
\frac{a}{b} \mapsto A B^{-1}?
ea+b↦eAeB?
e^{a+b} \mapsto e^A e^B?
Quantum Challenge #2
Entanglement: ρAB=ρA⊗ρB
Problem Setup
={±1}
=\{\pm 1\}
={±1}
=\{\pm 1\}
={±1}
=\{\pm 1\}
={±1}
=\{\pm 1\}
Alice
Bob
Compute (QS+RS+RT−QT)




Q
Q
R
R
S
S
T
T
Classical Mechanics
θ=(Q+R)S+(R−Q)T≤2
Let p(qrst):=Pr{Q=q,R=r,S=s,T=t}.
E[θ]=∑qrstp(qrst)(qs+rs+rt−qt)
\mathbb{E}[\theta]= \sum_{qrst}\text{p} (qrst)(qs+rs+rt-qt)
≤2
\leq 2
Probabilistically,
Quantum Mechanics
∣ΨAB⟩=21(∣0⟩A∣1⟩B−∣1⟩A∣0⟩B)
|\Psi_{AB}\rangle = \frac{1}{\sqrt{2}}\left(|0\rangle_A|1\rangle_B -|1\rangle_A |0\rangle_B\right)
={±1}
=\{\pm 1\}
={±1}
=\{\pm 1\}
={±1}
=\{\pm 1\}
={±1}
=\{\pm 1\}




Q
Q
R
R
S
S
T
T
Q=Z
Q=Z
R=X
R=X
S=2−Z−X
S=\frac{-Z-X}{\sqrt{2}}
T=2Z−X
T=\frac{Z-X}{\sqrt{2}}
Quantum Mechanics
E[θ]=⟨QS⟩+⟨RS⟩+⟨RT⟩−⟨QT⟩=22
\mathbb{E}[\theta] = \langle QS\rangle + \langle RS\rangle + \langle RT\rangle - \langle QT\rangle= 2\sqrt{2}


Why Quantum Computation Matters?
Type of Input
Type of Algorithms
CQ
CC
QC
QQ
CQ
QQ
QC
-
Linear Equation Solvers
-
Peceptron
-
Recommendation Systems
-
Semidefinite Programming
-
Many Others (such as non-Convex Optimization)
-
State Tomography
-
Entanglement Structure
-
Quantum Control
CC
-
Linear Equation Solvers
-
Recommendation Systems
-
Semidefinite Programming
-
Minimum Conical Hull
CQ
QQ




CC

Sample Complexity for Learning Quantum Objects
Q. State
Measurement
Learning States
Learning Measurements
fatD(H)(ϵ,E(H))=O(logd/ϵ2)
fatE(H)(ϵ,D(H))=O(d/ϵ2)
Hao-Chung Cheng, MH, Ping-Cheng Yeh. The learnability of unknown quantum measurements. QIC 16(7&8):615–656 (2016).
Thank you for your attention!
Machine Learning Meets Quantum Computation Min-Hsiu Hsieh (謝明修) University of Technology Sydney
Machine Learning Meets Quantum Computation
By Lawrence Min-Hsiu Hsieh
Machine Learning Meets Quantum Computation
01 Aug 2019
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