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Quantum impurity solvers have a broad range of applications in theoretical studies of strongly correlated electron systems. Especially, they play a key role in dynamical mean-field theory calculations of correlated lattice models and…

Strongly Correlated Electrons · Physics 2015-06-23 Li Huang , Yilin Wang , Zi Yang Meng , Liang Du , Philipp Werner , Xi Dai

We have developed a software library that simulates noisy quantum logic circuits. We represent quantum states by their density matrices in the Pauli basis, and incorporate possible errors in initialisation, logic gates, memory and…

Quantum computing's transition from theory to reality has spurred the need for novel software tools to manage the increasing complexity, sophistication, toil, and fallibility of quantum algorithm development. We present Qualtran, an…

We introduce ProjectQ, an open source software effort for quantum computing. The first release features a compiler framework capable of targeting various types of hardware, a high-performance simulator with emulation capabilities, and…

Quantum Physics · Physics 2018-02-01 Damian S. Steiger , Thomas Häner , Matthias Troyer

Quantum algorithms, represented as quantum circuits, can be used as benchmarks for assessing the performance of quantum systems. Existing datasets, widely utilized in the field, suffer from limitations in size and versatility, leading…

Quantum Physics · Physics 2024-02-26 Boran Apak , Medina Bandic , Aritra Sarkar , Sebastian Feld

Currently, quantum hardware is restrained by noises and qubit numbers. Thus, a quantum virtual machine that simulates operations of a quantum computer on classical computers is a vital tool for developing and testing quantum algorithms…

Quantum Physics · Physics 2022-06-10 Chuong Nguyen Quoc , Le Bin Ho , Lan Nguyen Tran , Hung Q. Nguyen

Characterizing quantum systems through experimental data is critical to applications as diverse as metrology and quantum computing. Analyzing this experimental data in a robust and reproducible manner is made challenging, however, by the…

Quantum Machine Learning is a new computational tool that combines the quantum properties from quantum computing with the pattern recognition from machine learning. In this paper, we apply the Variational Quantum Classifier algorithm to the…

Quantum Physics · Physics 2025-05-22 Anna B. M. Souza , Clebson Cruz , Marcelo A. Moret

We present a novel one-way quantum key distribution protocol based on 3-dimensional quantum state, a qutrit, that encodes two qubits in its 2-dimensional subspaces. The qubits hold the classical bit information that has to be shared between…

Quantum Physics · Physics 2012-02-03 R. Kumar , R. Demkowicz-Dobrzanski , K. Banaszek

Quantum programs are typically developed using quantum Software Development Kits (SDKs). The rapid advancement of quantum computing necessitates new tools to streamline this development process, and one such tool could be Generative…

Quantum computing has become an active research field in recent years, as its applications in fields such as cryptography, optimization, and materials science are promising. Along with these developments, challenges and opportunities exist…

Software Engineering · Computer Science 2026-01-13 Neilson Carlos Leite Ramalho , Erico A. da Silva , Higor Amario de Souza , Marcos Lordello Chaim

Exploiting the properties of quantum information to the benefit of machine learning models is perhaps the most active field of research in quantum computation. This interest has supported the development of a multitude of software…

Quantum Physics · Physics 2023-10-24 Francesco Di Marcantonio , Massimiliano Incudini , Davide Tezza , Michele Grossi

We propose the QHyper library, which is aimed at researchers working on computational experiments with a variety of quantum combinatorial optimization solvers. The library offers a simple and extensible interface for formulating…

Mathematical Software · Computer Science 2024-09-25 Tomasz Lamża , Justyna Zawalska , Kacper Jurek , Mariusz Sterzel , Katarzyna Rycerz

The availability of large-scale datasets on which to train, benchmark and test algorithms has been central to the rapid development of machine learning as a discipline and its maturity as a research discipline. Despite considerable…

Quantum Physics · Physics 2021-08-17 Elija Perrier , Akram Youssry , Chris Ferrie

We propose a realistic hybrid classical-quantum linear solver to solve systems of linear equations of a specific type, and demonstrate its feasibility using Qiskit on IBM Q systems. This algorithm makes use of quantum random walk that runs…

Quantum Physics · Physics 2019-11-12 Chih-Chieh Chen , Shiue-Yuan Shiau , Ming-Feng Wu , Yuh-Renn Wu

Quantum Key Distribution (QKD) enables two parties to securely share encryption keys by leveraging the principles of quantum mechanics, offering protection against eavesdropping. In practical implementations, QKD systems often rely on a…

The field of quantum algorithms is vibrant. Still, there is currently a lack of programming languages for describing quantum computation on a practical scale, i.e., not just at the level of toy problems. We address this issue by introducing…

Programming Languages · Computer Science 2013-07-08 Alexander S. Green , Peter LeFanu Lumsdaine , Neil J. Ross , Peter Selinger , Benoît Valiron

Quantum computers are available to use over the cloud, but the recent explosion of quantum software platforms can be overwhelming for those deciding on which to use. In this paper, we provide a current picture of the rapidly evolving…

Quantum Physics · Physics 2019-03-26 Ryan LaRose

We describe Superstaq, a quantum software platform that optimizes the execution of quantum programs by tailoring to underlying hardware primitives. For benchmarks such as the Bernstein-Vazirani algorithm and the Qubit Coupled Cluster…

Quantum computer simulation software is an integral tool for the research efforts in the quantum computing community. An important aspect is the efficiency of respective frameworks, especially for training variational quantum algorithms.…