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Quantum Circuit Design Gate Engineering Quantum Machine Learning Quantum Simulation

TorchQuantumDistributed

arXiv

Authors: Oliver Knitter, Jonathan Mei, Masako Yamada, Martin Roetteler

Year

2025

Paper ID

16727

Status

Preprint

Abstract Read

~2 min

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Abstract

TorchQuantumDistributed (tqd) is a PyTorch-based [Paszke et al., 2019] library for accelerator-agnostic differentiable quantum state vector simulation at scale. This enables studying the behavior of learnable parameterized near-term and fault- tolerant quantum circuits with high qubit counts.

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This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
It adds a 2025 reference point for readers tracking recent quantum research.
TorchQuantumDistributed (tqd) is a PyTorch-based [Paszke et al., 2019] library for accelerator-agnostic differentiable quantum state vector simulation at scale.

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References & Citation Signals

[1] DOI https://doi.org/arXiv:2511.19291 [2] arXiv https://arxiv.org/abs/2511.19291 [3] Publisher https://arxiv.org/abs/2511.19291

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