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Related papers: Dequantizability from inputs

200 papers

Many experiments in quantum information aim at creating multi-partite entangled states. Quantifying the amount of entanglement that was actually generated can, in principle, be accomplished using full-state tomography. This method requires…

Quantum Physics · Physics 2015-05-13 Harald Wunderlich , Martin B. Plenio

Quantum low-density parity-check codes are a promising candidate for fault-tolerant quantum computing with considerably reduced overhead compared to the surface code. However, the lack of a practical decoding algorithm remains a barrier to…

Any technology for quantum information processing (QIP) must embody within it quantum bits (qubits) and maintain control of their key quantum properties of superposition and entanglement. Typical QIP schemes envisage an array of physical…

Quantum Physics · Physics 2009-11-13 Joseph Fitzsimons , Li Xiao , Simon C. Benjamin , Jonathan A. Jones

The quest for successful variational quantum machine learning (QML) relies on the design of suitable parametrized quantum circuits (PQCs), as analogues to neural networks in classical machine learning. Successful QML models must fulfill the…

Quantum Physics · Physics 2025-07-09 Elies Gil-Fuster , Casper Gyurik , Adrián Pérez-Salinas , Vedran Dunjko

The distribution and processing of quantum entanglement form the basis of quantum communication and quantum computing. The realization of the two is difficult because quantum information inherently has a high susceptibility to decoherence,…

Quantum Physics · Physics 2012-08-30 Boris Hage , Aiko Samblowski , James DiGuglielmo , Jaromír Fiurášek , Roman Schnabel

Quantization-Aware Training from scratch has emerged as a promising approach for building efficient large language models (LLMs) with extremely low-bit weights (sub 2-bit), which can offer substantial advantages for edge deployment.…

Machine Learning · Computer Science 2026-02-27 Wenzheng Zhang , Bingzheng Liu , Yang Hu , Xiaoying Bai , Wentao Zhang , Bin Cui

Model quantization has emerged as an indispensable technique to accelerate deep learning inference. While researchers continue to push the frontier of quantization algorithms, existing quantization work is often unreproducible and…

Machine Learning · Computer Science 2022-01-26 Yuhang Li , Mingzhu Shen , Jian Ma , Yan Ren , Mingxin Zhao , Qi Zhang , Ruihao Gong , Fengwei Yu , Junjie Yan

We develop a framework for learning from noisy quantum experiments in which fault-tolerant devices access uncharacterized systems through noisy couplings. Introducing the complexity class $\textsf{NBQP}$ ("noisy BQP''), we model noisy…

Quantum Physics · Physics 2026-01-15 Jordan Cotler , Weiyuan Gong , Ishaan Kannan

In this paper we propose a new framework for distributed source coding of structured sources, such as sparse signals. Our framework capitalizes on recent advances in the theory of linear inverse problems and signal representations using…

Information Theory · Computer Science 2020-12-02 Maxim Goukhshtein , Petros T. Boufounos , Toshiaki Koike-Akino , Stark C. Draper

Dephasing is a ubiquitous phenomenon that leads to the loss of coherence in quantum systems and the corruption of quantum information. We present a universal dynamical control approach to combat dephasing during all stages of quantum…

Quantum Physics · Physics 2009-11-13 Goren Gordon , Gershon Kurizki

With the development of delegated quantum computation, clients will want to ensure confidentiality of their data and algorithms, and the integrity of their computations. While protocols for blind and verifiable quantum computation exist,…

Quantum Physics · Physics 2021-09-10 Dominik Leichtle , Luka Music , Elham Kashefi , Harold Ollivier

The Quantum Singular Value Transformation (QSVT) is a recent technique that gives a unified framework to describe most quantum algorithms discovered so far, and may lead to the development of novel quantum algorithms. In this paper we…

Quantum Physics · Physics 2024-01-05 Sevag Gharibian , François Le Gall

Model quantization is a promising approach to compress deep neural networks and accelerate inference, making it possible to be deployed on mobile and edge devices. To retain the high performance of full-precision models, most existing…

Computer Vision and Pattern Recognition · Computer Science 2021-03-31 Yuang Liu , Wei Zhang , Jun Wang

Sharing entanglement across quantum interconnects is fundamental for quantum information processing. We discuss a practical setting where this interconnect, modeled by a quantum channel, is used once with the aim of sharing high fidelity…

Quantum Physics · Physics 2023-10-09 Vikesh Siddhu , John Smolin

The data input model is a fundamental component of every quantum algorithm, as its efficiency is crucial for achieving potential speed-ups over classical methods. For quantum linear algebra tasks that utilize quantum eigenvalue or singular…

Quantum Physics · Physics 2025-09-03 Andreas Sturm , Niclas Schillo

The conventional paradigm of quantum computing is discrete: it utilizes discrete sets of gates to realize bitstring-to-bitstring mappings, some of them arguably intractable for classical computers. In parameterized quantum approaches, the…

Quantum Physics · Physics 2025-12-12 Adrián Pérez-Salinas , Mahtab Yaghubi Rad , Alice Barthe , Vedran Dunjko

We consider entanglement detection for quantum key distribution systems that use two signal states and continuous variable measurements. This problem can be formulated as a separability problem in a qubit-mode system. To verify…

Quantum Physics · Physics 2007-05-23 Johannes Rigas , Otfried Gühne , Norbert Lütkenhaus

Entanglement fidelity quantifies how well a quantum channel preserves the correlations between a transmitted system and an inaccessible reference system. We derive closed-form expressions for the entanglement fidelity associated with…

Quantum Physics · Physics 2026-03-10 Niccolò Zanieri , Marios Kountouris

This note is intended to foster a discussion about the extent to which typical problems arising in quantum information theory are algorithmically decidable (in principle rather than in practice). Various problems in the context of…

Quantum Physics · Physics 2011-11-24 Michael M. Wolf , Toby S. Cubitt , David Perez-Garcia

In this paper we develop two axiomatic tests for the controllability of subsystem codes embedded in decoherence-free subspaces of open quantum systems. The tests expand on existing control theory by considering quantum subsystems where a…

Quantum Physics · Physics 2025-03-10 Eric B. Kopp , Raymond Kwong