Efficient Learning of Quantum States Prepared With Few Non-Clifford Gates

05/22/2023
∙
by   Sabee Grewal, et al.
∙
0
∙

We give an algorithm that efficiently learns a quantum state prepared by Clifford gates and O(log(n)) non-Clifford gates. Specifically, for an n-qubit state |ψ⟩ prepared with at most t non-Clifford gates, we show that 𝗉𝗈𝗅𝗒(n,2^t,1/ϵ) time and copies of |ψ⟩ suffice to learn |ψ⟩ to trace distance at most ϵ. This result follows as a special case of an algorithm for learning states with large stabilizer dimension, where a quantum state has stabilizer dimension k if it is stabilized by an abelian group of 2^k Pauli operators. We also develop an efficient property testing algorithm for stabilizer dimension, which may be of independent interest.

READ FULL TEXT

Please sign up or login with your details

Continue with:
Or login with email
Enter Password
Re-enter Password

Forgot password? Click here to reset
Success!
Error Icon An error occurred

Sign in with Google

×

Use your Google Account to sign in to DeepAI

×
Pro

Consider DeepAI Pro

Subscribe to DeepAI Pro
DeepAI Pro
Provides a limited generation allowance each month. When exceeded, you are charged overage rates available at deepai.org/pricing. Also includes an ad-free experience and API access. Renews automatically until canceled. Non-refundable.
Subtotal
Total due today

Payment

Add DeepAI credits
DeepAI credits
One-time purchase. Credits are added to your wallet after payment.
Subtotal
Total due today

Payment