Demonstrates a task solvable with 12 qubits but requiring 62-382 classical bits of memory, yielding unconditional quantum information supremacy on a trapped-ion processor.
Title resolution pending
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
fields
quant-ph 4verdicts
UNVERDICTED 4representative citing papers
A dynamic-circuit framework for multi-step quantum Markov decision processes reduces physical qubit count from O(T) to O(1) while preserving trajectory fidelity and applying Grover amplification for high-return paths.
A two-step method minimizes entanglement entropy of target states before using matrix product state representations to achieve high-accuracy quantum state preparation on NISQ devices.
The paper claims a fully quantum MDP model for RL with quantum state transitions, return calculation, and trajectory search that achieves quantum enhancement.
citing papers explorer
-
Demonstrating an unconditional separation between quantum and classical information resources
Demonstrates a task solvable with 12 qubits but requiring 62-382 classical bits of memory, yielding unconditional quantum information supremacy on a trapped-ion processor.
-
Scalable Quantum Reinforcement Learning on NISQ Devices with Dynamic-Circuit Qubit Reuse and Grover Optimization
A dynamic-circuit framework for multi-step quantum Markov decision processes reduces physical qubit count from O(T) to O(1) while preserving trajectory fidelity and applying Grover amplification for high-return paths.
-
Minimizing entanglement entropy for enhanced quantum state preparation
A two-step method minimizes entanglement entropy of target states before using matrix product state representations to achieve high-accuracy quantum state preparation on NISQ devices.
-
Quantum framework for Reinforcement Learning: Integrating Markov decision process, quantum arithmetic, and trajectory search
The paper claims a fully quantum MDP model for RL with quantum state transitions, return calculation, and trajectory search that achieves quantum enhancement.