Tight Bounds on the Spooky Pebble Game: Recycling Qubits with Measurements

Fuente: arXiv
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Main Authors: Kornerup, Niels, Sadun, Jonathan, Soloveichik, David
Format: Preprint
Published: 2021
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_version_ 1866929719135436800
author Kornerup, Niels
Sadun, Jonathan
Soloveichik, David
author_facet Kornerup, Niels
Sadun, Jonathan
Soloveichik, David
contents Pebble games are popular models for analyzing time-space trade-offs. In particular, the reversible pebble game is often applied in quantum algorithms like Grover's search to efficiently simulate classical computation on inputs in superposition. However, the reversible pebble game cannot harness the additional computational power granted by irreversible intermediate measurements. The spooky pebble game, which models interleaved measurements and adaptive phase corrections, reduces the number of qubits beyond what reversible approaches can achieve. While the spooky pebble game does not reduce the total space (bits plus qubits) complexity of the simulation, it reduces the amount of space that must be stored in qubits. We prove asymptotically tight trade-offs for the spooky pebble game on a line with any pebble bound, giving a tight time-qubit tradeoff for simulating arbitrary classical sequential computation with the spooky pebble game. For example, for all $ε\in (0,1]$, any classical computation requiring time $T$ and space $S$ can be implemented on a quantum computer using only $O(T/ ε)$ gates and $O(T^εS^{1-ε})$ qubits. This improves on the best known bound for the reversible pebble game with that number of qubits, which uses $O(2^{1/ε} T)$ gates. We also consider the spooky pebble game on more general directed acyclic graphs (DAGs), capturing fine-grained data dependency in computation. We show that for an arbitrary DAG even approximating the number of required pebbles in the spooky pebble game is PSPACE-hard. Despite this, we are able to construct a time-efficient strategy for pebbling binary trees that uses the minimum number of pebbles.
format Preprint
id arxiv_https___arxiv_org_abs_2110_08973
institution arXiv
publishDate 2021
record_format arxiv
spellingShingle Tight Bounds on the Spooky Pebble Game: Recycling Qubits with Measurements
Kornerup, Niels
Sadun, Jonathan
Soloveichik, David
Quantum Physics
Computational Complexity
68Q12
F.2.3
Pebble games are popular models for analyzing time-space trade-offs. In particular, the reversible pebble game is often applied in quantum algorithms like Grover's search to efficiently simulate classical computation on inputs in superposition. However, the reversible pebble game cannot harness the additional computational power granted by irreversible intermediate measurements. The spooky pebble game, which models interleaved measurements and adaptive phase corrections, reduces the number of qubits beyond what reversible approaches can achieve. While the spooky pebble game does not reduce the total space (bits plus qubits) complexity of the simulation, it reduces the amount of space that must be stored in qubits. We prove asymptotically tight trade-offs for the spooky pebble game on a line with any pebble bound, giving a tight time-qubit tradeoff for simulating arbitrary classical sequential computation with the spooky pebble game. For example, for all $ε\in (0,1]$, any classical computation requiring time $T$ and space $S$ can be implemented on a quantum computer using only $O(T/ ε)$ gates and $O(T^εS^{1-ε})$ qubits. This improves on the best known bound for the reversible pebble game with that number of qubits, which uses $O(2^{1/ε} T)$ gates. We also consider the spooky pebble game on more general directed acyclic graphs (DAGs), capturing fine-grained data dependency in computation. We show that for an arbitrary DAG even approximating the number of required pebbles in the spooky pebble game is PSPACE-hard. Despite this, we are able to construct a time-efficient strategy for pebbling binary trees that uses the minimum number of pebbles.
title Tight Bounds on the Spooky Pebble Game: Recycling Qubits with Measurements
topic Quantum Physics
Computational Complexity
68Q12
F.2.3
url https://arxiv.org/abs/2110.08973