Scalable Pseudorandom Quantum States
April 04, 2020 Β· Declared Dead Β· π Annual International Cryptology Conference
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Zvika Brakerski, Omri Shmueli
arXiv ID
2004.01976
Category
quant-ph: Quantum Computing
Cross-listed
cs.CR
Citations
30
Venue
Annual International Cryptology Conference
Last Checked
3 months ago
Abstract
Efficiently sampling a quantum state that is hard to distinguish from a truly random quantum state is an elementary task in quantum information theory that has both computational and physical uses. This is often referred to as pseudorandom (quantum) state generator, or PRS generator for short. In existing constructions of PRS generators, security scales with the number of qubits in the states, i.e.\ the (statistical) security parameter for an $n$-qubit PRS is roughly $n$. Perhaps counter-intuitively, $n$-qubit PRS are not known to imply $k$-qubit PRS even for $k<n$. Therefore the question of \emph{scalability} for PRS was thus far open: is it possible to construct $n$-qubit PRS generators with security parameter $Ξ»$ for all $n, Ξ»$. Indeed, we believe that PRS with tiny (even constant) $n$ and large $Ξ»$ can be quite useful. We resolve the problem in this work, showing that any quantum-secure one-way function implies scalable PRS. We follow the paradigm of first showing a \emph{statistically} secure construction when given oracle access to a random function, and then replacing the random function with a quantum-secure (classical) pseudorandom function to achieve computational security. However, our methods deviate significantly from prior works since scalable pseudorandom states require randomizing the amplitudes of the quantum state, and not just the phase as in all prior works. We show how to achieve this using Gaussian sampling.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Quantum Computing
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
The power of quantum neural networks
R.I.P.
π»
Ghosted
Power of data in quantum machine learning
R.I.P.
π»
Ghosted
Quantum machine learning: a classical perspective
R.I.P.
π»
Ghosted
Noise-Adaptive Compiler Mappings for Noisy Intermediate-Scale Quantum Computers
R.I.P.
π»
Ghosted
ProjectQ: An Open Source Software Framework for Quantum Computing
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Language Models are Few-Shot Learners
R.I.P.
π»
Ghosted
PyTorch: An Imperative Style, High-Performance Deep Learning Library
R.I.P.
π»
Ghosted
XGBoost: A Scalable Tree Boosting System
R.I.P.
π»
Ghosted