Optimized Distribution of Entanglement Graph States in Quantum Networks

Building large-scale quantum computers, essential to demonstrating quantum advantage, is a key challenge. Quantum networks can help address this challenge by enabling the construction of large, robust, and more capable quantum computing platforms by connecting smaller quantum computers. Moreover, unlike classical systems, quantum networks can enable fully secured long-distance communication. Thus, quantum networks lie at […]

Observing the Poisson Distribution of a Coherent Microwave Field With a Parametric Photon Detector

Abstract: Single-photon detectors are essential for implementing optical quantum technologies, such as quantum key distribution, and for enhancing optical imaging systems such as lidar, while also playing a crucial role in studying the statistical properties of light. In this work, we show how the underlying photon statistics can be revealed by using a threshold detector, […]

Utilizing Quantum Annealing in Computed Tomography Image Reconstruction

Abstract: One of the primary difficulties in computed tomography (CT) is reconstructing cross-sectional images from measured projections of a physical object. There exist several classical methods for this task of generating a digital representation of the object, including filtered backprojection or simultaneous algebraic reconstruction technique. Our research aims to explore the potential of quantum computing […]

Observing the Poisson Distribution of a Coherent Microwave Field With a Parametric Photon Detector

Single-photon detectors are essential for implementing optical quantum technologies, such as quantum key distribution, and for enhancing optical imaging systems such as lidar, while also playing a crucial role in studying the statistical properties of light. In this work, we show how the underlying photon statistics can be revealed by using a threshold detector, implemented […]

Quantum Circuit Compilation for Trapped-Ion Processors With the Drive-Through Architecture

Abstract: Trapped-ion technologies stand out as leading contenders in the pursuit of quantum computing, due to their capacity for highly entangled qubits. Among many proposed trapped-ion architectures, the “drive-through” architecture has drawn increasing attention, notably for its remarkable ability to minimize heat generation, which is crucial for low-temperature operation and thermal noise reduction, thus reliable […]

Two-Step Quantum Search Algorithm for Solving Traveling Salesman Problems

Quantum search algorithms, such as Grover’s algorithm, are anticipated to efficiently solve constrained combinatorial optimization problems. However, applying these algorithms to the traveling salesman problem (TSP) on a quantum circuit presents a significant challenge. Existing quantum search algorithms for the TSP typically assume that an initial state—an equal superposition of all feasible solutions satisfying the […]

Explicit Quantum Circuit for Simulating the Advection–Diffusion–Reaction Dynamics

We assess the convergence of the Carleman linearization of advection–diffusion–reaction (ADR) equations with a logistic nonlinearity. It is shown that five Carleman iterates provide a satisfactory approximation of the original ADR across a broad range of parameters and strength of nonlinearity. To assess the feasibility of a quantum algorithm based on this linearization, we analyze […]

Qubit Rate Modulation-Based Time Synchronization Mechanism for Multinode Quantum Networks

The combination of quantum and telecommunication networks enables to revolutionize the way information is used, offering unparalleled capabilities and making it an ideal choice for many critical applications. In this sense, quantum protocols generally have a unique requirement to have strict time synchronization in order to operate, which generally consume quantum resources of part of […]

Generating Shuttling Procedures for Constrained Silicon Quantum Dot Array

In silicon quantum computers, a single electron is trapped in a microstructure called a quantum dot, and its spin is used as a qubit. For large-scale integration of qubits, we previously proposed an approach of sharing a control gate in the row or column of a 2-D quantum dot array. In our array, the shuttling […]

Benchmarking Quantum Machine Learning Kernel Training for Classification Tasks

Quantum-enhanced machine learning is a rapidly evolving field that aims to leverage the unique properties of quantum mechanics to enhance classical machine learning. However, the practical applicability of these methods remains an open question, particularly beyond the context of specifically crafted toy problems, and given the current limitations of quantum hardware. For more about this […]