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The Feynman path integral is defined over the space $\mathbb{R}^T$ of all possible paths; it has been a powerful tool to develop Quantum Mechanics. The absolute value of Feynman's integrand is not integrable, then Lebesgue integration…

Mathematical Physics · Physics 2020-03-02 Ricardo Gaitan , M. Guadalupe Morales

Quantum annealing algorithms belong to the class of meta-heuristic tools, applicable for solving binary optimization problems. Hardware implementations of quantum annealing, such as the quantum processing units (QPUs) produced by D-Wave…

The absent-minded driver's problem illustrates that probabilistic strategies can give higher pay-offs than deterministic ones. We show that there are strategies using quantum entangled states that give even higher pay-offs, both for the…

Quantum Physics · Physics 2009-07-28 Adan Cabello , John Calsamiglia

We address the question of how many maximally entangled photon pairs are needed in order to build up cluster states for quantum computing using the toolbox of linear optics. As the needed gates in dual-rail encoding are necessarily…

Quantum Physics · Physics 2015-06-26 K. Kieling , D. Gross , J. Eisert

We examine a fundamental problem in quantum optics: What is the optimal pulse form to drive a two-photon-transition? We show that entangled photons in general do so more efficiently than optimal classical pulses, and provide the first…

Quantum Physics · Physics 2015-10-23 Frank Schlawin , Andreas Buchleitner

In this PhD thesis, several aspects regarding maximal entanglement are analyzed. In the first chapter, Bell Inequalities are analyzed from an operational perspective as well as novel Bell inequalities are obtained together with their…

Quantum Physics · Physics 2019-07-01 Alba Cervera-Lierta

We optimize a quantum walk of multiple fermions following a quench in a spin chain to generate near ideal resources for quantum networking. We first prove an useful theorem mapping the correlations evolved from specific quenches to the…

Quantum Physics · Physics 2014-10-08 Bedoor Alkurtass , Leonardo Banchi , Sougato Bose

Building large-scale quantum computers, essential to demonstrating quantum advantage, is a key challenge. Quantum Networks (QNs) can help address this challenge by enabling the construction of large, robust, and more capable quantum…

Quantum Physics · Physics 2025-03-20 Xiaojie Fan , Caitao Zhan , Himanshu Gupta , C. R. Ramakrishnan

We show that recent experiments in hybrid qubit-oscillator devices that measure the phase-space characteristic function of the oscillator via the qubit can be seen through the lens of functional calculus and path integrals, drawing a clear…

Quantum Physics · Physics 2024-11-11 S. Varona , S. Saner , O. Băzăvan , G. Araneda , G. Aarts , A. Bermudez

Reliable preparation of entanglement between distant systems is an outstanding problem in quantum information science and quantum communication. In practice, this has to be accomplished via noisy channels (such as optical fibers) that…

Quantum Physics · Physics 2007-11-01 Liang Jiang , Jacob M. Taylor , Navin Khaneja , Mikhail D. Lukin

We provide a new paradigm for quantum simulation that is based on path integration that allows quantum speedups to be observed for problems that are more naturally expressed using the path integral formalism rather than the conventional…

Quantum Physics · Physics 2024-10-15 Serene Shum , Nathan Wiebe

We consider a suboptimal solution path algorithm for the Support Vector Machine. The solution path algorithm is an effective tool for solving a sequence of a parametrized optimization problems in machine learning. The path of the solutions…

Machine Learning · Computer Science 2011-05-04 Masayuki Karasuyama , Ichiro Takeuchi

Entangled photons are widely used in quantum technologies. Many photonic experiments generate them with probabilistic photon-pair sources that can be modeled as squeeze operators. In practice, these sources are usually treated in the…

Quantum Physics · Physics 2026-05-05 Carlos Ruiz-Gonzalez , Mario Krenn , Xuemei Gu

Gate-based universal quantum computation is formulated in terms of two types of operations: local single-qubit gates, which are typically easily implementable, and two-qubit entangling gates, whose faithful implementation remains one of the…

Quantum Physics · Physics 2023-10-18 Xiaoqin Gao , Paul Appel , Nicolai Friis , Martin Ringbauer , Marcus Huber

Quantum computers are different from binary digital electronic computers based on transistors. Common digital computing encodes the data into binary digits (bits), each of which is always in one of two definite states (0 or 1), quantum…

Emerging Technologies · Computer Science 2018-08-28 Carla Silva , Inês Dutra , Marcus S. Dahlem

Quantum entanglement is a key resource for quantum technologies, including emerging ground-to-satellite quantum communication. In such a scenario, an important challenge to be overcome is to consider entanglement between two or more quantum…

Quantum Physics · Physics 2024-10-10 Yannick Noel Freitag , Julien Pinske , Jan Sperling

We develop a strong and computationally simple entanglement criterion. The criterion is based on an elementary positive map Phi which operates on state spaces with even dimension N >= 4. It is shown that Phi detects many entangled states…

Quantum Physics · Physics 2007-05-23 Heinz-Peter Breuer

Identifying and extracting the past information relevant to the future behaviour of stochastic processes is a central task in the quantitative sciences. Quantum models offer a promising approach to this, allowing for accurate simulation of…

Quantum Physics · Physics 2019-06-26 Qing Liu , Thomas. J. Elliott , Felix. C. Binder , Carlo Di Franco , Mile Gu

We study in detail the algebraic structures underlying quantum circuits generated by CNOT gates. Our results allow us to propose polynomial-time heuristics to reduce the number of gates used in a given CNOT circuit and we also give…

Quantum Physics · Physics 2020-12-18 Marc Bataille

Many computational problems are unchanged under some symmetry operation. In classical machine learning, this can be reflected with the layer structure of the neural network. In quantum machine learning, the ansatz can be tuned to correspond…