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In continuous-variable quantum computation, identifying key elements that enable a quantum computational advantage is a long-standing issue. Starting from the standard results on the necessity of Wigner negativity, we develop a…

Quantum Physics · Physics 2025-03-12 Massimo Frigerio , Antoine Debray , Nicolas Treps , Mattia Walschaers

For many practical applications of quantum computing, the most costly steps involve coherently accessing classical data. We help address this challenge by applying mass production techniques, which can reduce the cost of applying an…

Quantum Physics · Physics 2025-06-03 William J. Huggins , Tanuj Khattar , Nathan Wiebe

Quantum computers hold the promise to solve certain computational task much more efficiently than classical computers. We review the recent experimental advancements towards a quantum computer with trapped ions. In particular, various…

Quantum Physics · Physics 2008-11-20 H. Haeffner , C. F. Roos , R. Blatt

Density-functional theory (DFT) has revolutionized computer simulations in chemistry and material science. A faithful implementation of the theory requires self-consistent calculations. However, this effort involves repeatedly diagonalizing…

Quantum Physics · Physics 2023-07-17 Taehee Ko , Xiantao Li , Chunhao Wang

Quantum algorithms for scientific computing require modules implementing fundamental functions, such as the square root, the logarithm, and others. We require algorithms that have a well-controlled numerical error, that are uniformly…

Quantum Physics · Physics 2016-02-02 Mihir K. Bhaskar , Stuart Hadfield , Anargyros Papageorgiou , Iasonas Petras

Gate-based quantum computations represent an essential to realize near-term quantum computer architectures. A gate-model quantum neural network (QNN) is a QNN implemented on a gate-model quantum computer, realized via a set of unitaries…

Quantum Physics · Physics 2019-09-04 Laszlo Gyongyosi , Sandor Imre

Classical matching theory can be defined in terms of matrices with nonnegative entries. The notion of Positive operator, central in Quantum Theory, is a natural generalization of matrices with nonnegative entries. Based on this point of…

Quantum Physics · Physics 2007-05-23 Leonid Gurvits

Quantum embedding is a fundamental prerequisite for applying quantum machine learning techniques to classical data, and has substantial impacts on performance outcomes. In this study, we present Neural Quantum Embedding (NQE), a method that…

Quantum Physics · Physics 2024-08-12 Tak Hur , Israel F. Araujo , Daniel K. Park

We investigate the amount of noise required to turn a universal quantum gate set into one that can be efficiently modelled classically. This question is useful for providing upper bounds on fault tolerant thresholds, and for understanding…

Quantum Physics · Physics 2007-05-23 S. Virmani , Susana F. Huelga , Martin B. Plenio

Quantum computing has made remarkable strides in recent years, as demonstrated by quantum supremacy experiments and the realization of high-fidelity, fault-tolerant gates. However, a major obstacle persists: practical real-world…

The model of open quantum systems is adopted to describe the non-local dynamical behaviour of qubits processed by entangling gates. The analysis gets to the conclusion that a distinction between evaluation steps and task-oriented computing…

Quantum Physics · Physics 2015-12-24 Stefano Bonzio , Paola Verrucchi

Quantum computing promises to solve problems beyond the reach of classical computers, but today's quantum hardware is error-prone and much slower than classical hardware. Every quantum operation is costly, making it crucial to minimize…

Quantum Physics · Physics 2026-05-25 Lian Remme , Alexander Weinert , Andre Waschk , Lukas Burgholzer , Robert Wille

The sum gate is the canonical two-mode gate for universal quantum computation based on continuous quantum variables. It represents the natural analogue to a qubit C-NOT gate. In addition, the continuous-variable gate describes a quantum…

With the advent of exascale computing, effective load balancing in massively parallel software applications is critically important for leveraging the full potential of high performance computing systems. Load balancing is the distribution…

Quantum Physics · Physics 2025-01-30 Omer Rathore , Alastair Basden , Nicholas Chancellor , Halim Kusumaatmaja

A classical decision tree is completely based on splitting measures, which utilize the occurrence of random events in correspondence to its class labels in order to optimally segregate datasets. However, the splitting measures are based on…

Quantum Physics · Physics 2024-12-10 Diksha Sharma , Parvinder Singh , Atul Kumar

Hybrid quantum-classical machine learning offers a path to leverage noisy intermediate-scale quantum (NISQ) devices for drug discovery, but optimal model architectures remain unclear. We systematically optimize the quantum-classical bridge…

Machine Learning · Computer Science 2025-07-28 Andrew Smith , Erhan Guven

Gate-model quantum computers provide an experimentally implementable architecture for near term quantum computations. To design a reduced quantum circuit that can simulate a high complexity reference quantum circuit, an optimization should…

Quantum Physics · Physics 2019-09-04 Laszlo Gyongyosi , Sandor Imre

Quantum key distribution (QKD) allows for secure communications safe against attacks by quantum computers. QKD protocols are performed by sending a sizeable, but finite, number of quantum signals between the distant parties involved. Many…

Quantum Physics · Physics 2021-01-05 Darius Bunandar , Luke C. G. Govia , Hari Krovi , Dirk R. Englund

We propose a scalable scheme for optical quantum computing using measurement-induced continuous-variable quantum gates in a loop-based architecture. Here, time-bin-encoded quantum information in a single spatial mode is deterministically…

Quantum Physics · Physics 2017-09-27 Shuntaro Takeda , Akira Furusawa

We consider the scattering matrix approach to quantum electron transport in meso- and nano-conductors. This approach is an alternative to the more conventional kinetic equation and Green's function approaches, and often is more efficient…

Mesoscale and Nanoscale Physics · Physics 2015-04-09 G. B. Lesovik , I. A. Sadovskyy