Papers
Live trends in quantum computing research, updated daily from arXiv.
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Hybrid quantum-classical convolutional neural networks to improve molecular protein binding affinity predictions
L. Domingo, M. Djukic, C. Johnson +1 more·Jan 16, 2023
One of the main challenges in drug discovery is to find molecules that bind specifically and strongly to their target protein while having minimal binding to other proteins. By predicting binding affinity, it is possible to identify the most promisin...
Quantum simulations in effective model spaces: Hamiltonian-learning variational quantum eigensolver using digital quantum computers and application to the Lipkin-Meshkov-Glick model
C. Robin, M. Savage·Jan 14, 2023
The utility of effective model spaces in quantum simulations of non-relativistic quantum many-body systems is explored in the context of the Lipkin-Meshkov-Glick model of interacting fermions. We introduce an iterative hybrid-classical-quantum algori...
TeD-Q: a tensor network enhanced distributed hybrid quantum machine learning framework
Yaocheng Chen, C. Kuo, Yuxuan Du +2 more·Jan 13, 2023
TeD-Q is an open-source software framework for quantum machine learning, variational quantum algorithm (VQA), and simulation of quantum computing. It seamlessly integrates classical machine learning libraries with quantum simulators, giving users the...
SEQUENT: Towards Traceable Quantum Machine Learning using Sequential Quantum Enhanced Training
Philipp Altmann, Leo Sünkel, Jonas Stein +3 more·Jan 6, 2023
Applying new computing paradigms like quantum computing to the field of machine learning has recently gained attention. However, as high-dimensional real-world applications are not yet feasible to be solved using purely quantum hardware, hybrid metho...
Quantum Machine Learning Applied to the Classification of Diabetes
Juan Kenyhy Hancco-Quispe, Jordan Piero Borda-Colque, Fred Torres-Cruz·Dec 31, 2022
Quantum Machine Learning (QML) shows how it maintains certain significant advantages over machine learning methods. It now shows that hybrid quantum methods have great scope for deployment and optimisation, and hold promise for future industries. As ...
FIPS Compliant Quantum Secure Communication Using Quantum Permutation Pad
Alex He, Dafu Lou, Eric She +5 more·Dec 30, 2022
Quantum computing has entered a fast development track since Shor's algorithm was proposed in 1994. Multi-cloud services of quantum computing farms are currently available. One of which, IBM quantum computing, presented a road map showing their Kooka...
Reduced basis emulation of pairing in finite systems
V. Baran, D. Nichita·Dec 29, 2022
In recent years, reduced basis methods (RBMs) have been adapted to the many-body eigenvalue problem and they have been used, largely in nuclear physics, as fast emulators able to bypass expensive direct computations while still providing highly accur...
Hybrid quantum-gap-estimation algorithm using a filtered time series
Woojun Lee, Ryan Scott, V. Scarola·Dec 28, 2022
Quantum simulation advantage over classical memory limitations would allow compact quantum circuits to yield insight into intractable quantum many-body problems, but the interrelated obstacles of large circuit depth in quantum time evolution and nois...
Digitized Counterdiabatic Quantum Algorithm for Protein Folding
P. Chandarana, N. N. Hegade, I. Montalban +2 more·Dec 27, 2022
We propose a hybrid classical-quantum digitized-counterdiabatic algorithm to tackle the protein folding problem on a tetrahedral lattice. Digitized-counterdiabatic quantum computing is a paradigm developed to compress quantum algorithms via the digit...
An introduction to variational quantum algorithms for combinatorial optimization problems
Camille Grange, M. Poss, E. Bourreau·Dec 22, 2022
Noisy intermediate-scale quantum computers (NISQ computers) are now readily available, motivating many researchers to experiment with Variational Quantum Algorithms (VQAs). Among them, the Quantum Approximate Optimization Algorithm (QAOA) is one of t...
Recommending Solution Paths for Solving Optimization Problems with Quantum Computing
Benedikt Poggel, Nils Quetschlich, Lukas Burgholzer +2 more·Dec 21, 2022
Solving real-world optimization problems with quantum computing requires choosing between a large number of options concerning formulation, encoding, algorithm and hardware. Finding good solution paths is challenging for end users and researchers ali...
Matrix product channel: Variationally optimized quantum tensor network to mitigate noise and reduce errors for the variational quantum eigensolver
S. Filippov, Boris Sokolov, M. Rossi +5 more·Dec 20, 2022
Quantum processing units boost entanglement at the level of hardware and enable physical simulations of highly correlated electron states in molecules and intermolecular chemical bonds. The variational quantum eigensolver provides a hardware-efficien...
Robustness of quantum reinforcement learning under hardware errors
Andrea Skolik, Stefano Mangini, Thomas Bäck +2 more·Dec 19, 2022
Variational quantum machine learning algorithms have become the focus of recent research on how to utilize near-term quantum devices for machine learning tasks. They are considered suitable for this as the circuits that are run can be tailored to the...
Hybrid Quantum Singular Spectrum Decomposition for Time Series Analysis
Jasper Postema, P. Bonizzi, G. Koekoek +2 more·Dec 17, 2022
Classical data analysis requires computational efforts that become intractable in the age of Big Data. An essential task in time series analysis is the extraction of physically meaningful information from a noisy time series. One algorithm devised fo...
Hybrid Quantum Generative Adversarial Networks for Molecular Simulation and Drug Discovery
Prateek Jain, Param Pathak, Krishna Bhatia +2 more·Dec 15, 2022
In molecular research, the modelling and analysis of molecules through simulation is an important part that has a direct influence on medical development, material science and drug discovery. The processing power required to design protein chains wit...
Experimental quantum computational chemistry with optimized unitary coupled cluster ansatz
Shaojun Guo, Jinzhao Sun, H. Qian +35 more·Dec 15, 2022
Quantum computational chemistry has emerged as a potential application of quantum computing. Hybrid quantum-classical computing methods, such as variational quantum eigensolvers, have been designed as promising solutions to quantum chemistry problems...
Category Theory for Quantum Natural Language Processing
Alexis Toumi·Dec 13, 2022
This thesis introduces quantum natural language processing (QNLP) models based on a simple yet powerful analogy between computational linguistics and quantum mechanics: grammar as entanglement. The grammatical structure of text and sentences connects...
Quantum Clustering with k-Means: a Hybrid Approach
Alessandro Poggiali, Alessandro Berti, A. Bernasconi +2 more·Dec 13, 2022
Quantum computing is a promising paradigm based on quantum theory for performing fast computations. Quantum algorithms are expected to surpass their classical counterparts in terms of computational complexity for certain tasks, including machine lear...
Strong Photon‐Magnon Coupling Using a Lithographically Defined Organic Ferrimagnet
Qin Xu, H. Cheung, D. S. Cormode +7 more·Dec 8, 2022
A cavity‐magnonic system composed of a superconducting microwave resonator coupled to a magnon mode hosted by the organic‐based ferrimagnet vanadium tetracyanoethylene (V[TCNE]x) is demonstrated. This work is motivated by the challenge of scalably in...
Universal Kardar-Parisi-Zhang scaling in noisy hybrid quantum circuits
Shuo Liu, Ming-Rui Li, Shi-Xin Zhang +2 more·Dec 7, 2022
Measurement-induced phase transitions (MIPT) have attracted increasing attention due to the rich phenomenology of entanglement structures and their relation with quantum information processing. Since physical systems are unavoidably coupled to enviro...