English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

Tensor networks have been successfully applied in simulation of quantumphysical systems for decades. Recently, they have also been employed inclassical simulation of quantum computing, in particular, random quantumcircuits. This paper proposes a decision diagram style data structure, calledTDD (Tensor Decision Diagram), for more principled and convenient applicationsof tensor networks. This new data structure provides a compact and canonicalrepresentation for quantum circuits. By exploiting circuit partition, the TDDof a quantum circuit can be computed efficiently. Furthermore, we show that theoperations of tensor networks essential in their applications (e.g., additionand contraction), can also be implemented efficiently in TDDs. Aproof-of-concept implementation of TDDs is presented and its efficiency isevaluated on a set of benchmark quantum circuits. It is expected that TDDs willplay an important role in various design automation tasks related to quantumcircuits, including but not limited to equivalence checking, error detection,synthesis, simulation, and verification.

A Tensor Network based Decision Diagram for Representation of Quantum Circuits