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arxiv.org 📅 2023 📰 arXiv 📄 PDF
Q-Drug: a Framework to bring Drug Design into Quantum Space using Deep Learning
👤 Zhaoping Xiong; Xiaopeng Cui; Xinyuan Lin; Feixiao Ren; Bowen Liu; Yunting Li; Manhong Yung; Nan Qiao

Optimizing the properties of molecules (materials or drugs) for stronger toughness, lower toxicity, or better bioavailability has been a long-standing challenge. In this context, we propose a molecular optimization framework called Q-Drug (Quantum-inspired optimization algorithm for Drugs) that leverages quantum-inspir…

quant-ph q-bio.MN q-bio.QM
arxiv.org 📅 2004 📰 arXiv 📄 PDF
Quantum computing and information extraction for a dynamical quantum system
👤 Giuliano Benenti; Giulio Casati; Simone Montangero

We discuss the simulation of a complex dynamical system, the so-called quantum sawtooth map model, on a quantum computer. We show that a quantum computer can be used to efficiently extract relevant physical information for this model. It is possible to simulate the dynamical localization of classical chaos and extract …

quant-ph cond-mat.other nlin.CD
DOI: 10.1007/s11128-004-0415-2
arxiv.org 📅 2022 📰 arXiv 📄 PDF
Tierkreis: A Dataflow Framework for Hybrid Quantum-Classical Computing
👤 Seyon Sivarajah; Lukas Heidemann; Alan Lawrence; Ross Duncan

We present Tierkreis, a higher-order dataflow graph program representation and runtime designed for compositional, quantum-classical hybrid algorithms. The design of the system is motivated by the remote nature of quantum computers, the need for hybrid algorithms to involve cloud and distributed computing, and the long…

quant-ph cs.DC
DOI: 10.1109/QCS56647.2022.00007
arxiv.org 📅 2026 📰 arXiv 📄 PDF
MerLin: A Discovery Engine for Photonic and Hybrid Quantum Machine Learning
👤 Cassandre Notton; Benjamin Stott; Philippe Schoeb; Anthony Walsh; Grégoire Leboucher; Vincent Espitalier; Vassilis Apostolou; Louis-Félix Vigneux; Alexia Salavrakos; Jean Senellart

Identifying where quantum models may offer practical benefits in near term quantum machine learning (QML) requires moving beyond isolated algorithmic proposals toward systematic and empirical exploration across models, datasets, and hardware constraints. We introduce MerLin, an open-source framework designed as a disco…

cs.LG cs.PL quant-ph
arxiv.org 📅 2023 📰 arXiv 📄 PDF
Arbitrary Ground State Observables from Quantum Computed Moments
👤 Harish J. Vallury; Lloyd C. L. Hollenberg

The determination of ground state properties of quantum systems is a fundamental problem in physics and chemistry, and is considered a key application of quantum computers. A common approach is to prepare a trial ground state on the quantum computer and measure observables such as energy, but this is often limited by h…

quant-ph
DOI: 10.1109/QCE57702.2023.00040
arxiv.org 📅 2025 📰 arXiv 📄 PDF
Dynamic Solutions for Hybrid Quantum-HPC Resource Allocation
👤 Roberto Rocco; Simone Rizzo; Matteo Barbieri; Gabriella Bettonte; Elisabetta Boella; Fulvio Ganz; Sergio Iserte; Antonio J. Peña; Petter Sandås; Alberto Scionti; Olivier Terzo; Chiara Vercellino; Giacomo Vitali; Paolo Viviani; Jonathan Frassineti; Sara Marzella; Daniele Ottaviani; Iacopo Colonnelli; Daniele Gregori

The integration of quantum computers within classical High-Performance Computing (HPC) infrastructures is receiving increasing attention, with the former expected to serve as accelerators for specific computational tasks. However, combining HPC and quantum computers presents significant technical challenges, including …

quant-ph cs.DC
DOI: 10.1109/QCE65121.2025.10289
arxiv.org 📅 2024 📰 arXiv 📄 PDF
Piquasso: A Photonic Quantum Computer Simulation Software Platform
👤 Zoltán Kolarovszki; Tomasz Rybotycki; Péter Rakyta; Ágoston Kaposi; Boldizsár Poór; Szabolcs Jóczik; Dániel T. R. Nagy; Henrik Varga; Kareem H. El-Safty; Gregory Morse; Michał Oszmaniec; Tamás Kozsik; Zoltán Zimborás

We introduce the Piquasso quantum programming framework, a full-stack open-source software platform for the simulation and programming of photonic quantum computers. Piquasso can be programmed via a high-level Python programming interface enabling users to perform efficient quantum computing with discrete and continuou…

quant-ph
DOI: 10.22331/q-2025-04-15-1708
arxiv.org 📅 2021 📰 arXiv 📄 PDF
Quantum and Randomised Algorithms for Non-linearity Estimation
👤 Debajyoti Bera; Tharrmashastha Sapv

Non-linearity of a Boolean function indicates how far it is from any linear function. Despite there being several strong results about identifying a linear function and distinguishing one from a sufficiently non-linear function, we found a surprising lack of work on computing the non-linearity of a function. The non-li…

quant-ph cs.CR
DOI: 10.1145/3456509
arxiv.org 📅 2026 📰 arXiv 📄 PDF
Quantum error correction with the toric code
👤 Atom Computing; Collaborators

Quantum computing platforms based on arrays of tweezer-confined neutral atoms have recently emerged as a competitive modality thanks to a direct path toward high qubit count, rapidly advancing operation fidelities, and their ability to execute circuits with arbitrary qubit connectivity. These features will enable the u…

quant-ph cond-mat.quant-gas physics.atom-ph
arxiv.org 📅 2000 📰 arXiv 📄 PDF
Algorithmic Theories of Everything
👤 Juergen Schmidhuber

The probability distribution P from which the history of our universe is sampled represents a theory of everything or TOE. We assume P is formally describable. Since most (uncountably many) distributions are not, this imposes a strong inductive bias. We show that P(x) is small for any universe x lacking a short descrip…

quant-ph cs.AI cs.CC cs.LG hep-th
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