Papers
Live trends in quantum computing research, updated daily from arXiv.
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Hardware platform mentions in abstracts — Photonic leads
Quantum Machine Learning with SQUID
A. Roggero, Jakub Filipek, Shih-Chieh Hsu +1 more·Apr 30, 2021
In this work we present the Scaled QUantum IDentifier (SQUID), an open-source framework for exploring hybrid Quantum-Classical algorithms for classification problems. The classical infrastructure is based on PyTorch and we provide a standardized desi...
Calculating the Green’s function of two-site fermionic Hubbard model in a photonic system
Jie Zhu, Yuya O. Nakagawa, Yong-Sheng Zhang +2 more·Apr 26, 2021
The Green’s function has been an indispensable tool to study many-body systems that remain one of the biggest challenges in modern quantum physics for decades. The complicated calculation of the Green’s function impedes the research of many-body syst...
Tensor Network Quantum Virtual Machine for Simulating Quantum Circuits at Exascale
Thien Nguyen, Dmitry I. Lyakh, E. Dumitrescu +3 more·Apr 21, 2021
The numerical simulation of quantum circuits is an indispensable tool for development, verification, and validation of hybrid quantum-classical algorithms intended for near-term quantum co-processors. The emergence of exascale high-performance comput...
Calculation of generating function in many-body systems with quantum computers: technical challenges and use in hybrid quantum-classical methods
E. Guzman, D. Lacroix·Apr 16, 2021
The generating function of a Hamiltonian $H$ is defined as $F(t)=\langle e^{-itH}\rangle$, where $t$ is the time and where the expectation value is taken on a given initial quantum state. This function gives access to the different moments of the Ham...
Higgs analysis with quantum classifiers
Vasilis Belis, Samuel Gonz'alez-Castillo, C. Reissel +4 more·Apr 15, 2021
We have developed two quantum classifier models for the ttH classification problem, both of which fall into the category of hybrid quantumclassical algorithms for Noisy Intermediate Scale Quantum devices (NISQ). Our results, along with other studies,...
Permanent of random matrices from representation theory: moments, numerics, concentration, and comments on hardness of boson-sampling
Sepehr Nezami·Apr 13, 2021
Computing the distribution of permanents of random matrices has been an outstanding open problem for several decades. In quantum computing, “anti-concentration” of this distribution is an unproven input for the proof of hardness of the task of boson-...
Reduced density matrix sampling: Self-consistent embedding and multiscale electronic structure on current generation quantum computers
J. Tilly, P. V. Sriluckshmy, Akashkumar Patel +6 more·Apr 12, 2021
We investigate fully self-consistent multiscale quantum-classical algorithms on current generation superconducting quantum computers, in a unified approach to tackle the correlated electronic structure of large systems in both quantum chemistry and co...
Quantum-enhanced filter: QFilter
Parfait Atchade-Adelomou, Guillermo Alonso-Linaje·Apr 7, 2021
Convolutional neural networks (CNN) are used mainly to treat problems with many images characteristic of deep learning. In this work, we propose a hybrid image classification model to take advantage of quantum and classical computing. The method will...
A systematic variational approach to band theory in a quantum computer
Kyle Sherbert, F. Cerasoli, M. Buongiorno Nardelli·Apr 7, 2021
Quantum computers promise to revolutionize our ability to simulate molecules, and cloud-based hardware is becoming increasingly accessible to a wide body of researchers. Algorithms such as Quantum Phase Estimation and the Variational Quantum Eigensol...
Quantum Fourier analysis for multivariate functions and applications to a class of Schrödinger-type partial differential equations
Paula García-Molina, Javier Rodríguez-Mediavilla, J. García-Ripoll·Apr 6, 2021
In this work, we develop a highly efficient representation of functions and differential operators based on Fourier analysis. Using this representation, we create a variational hybrid quantum algorithm to solve static, Schrödinger-type, Hamiltonian p...
Fast-forwarding with NISQ processors without feedback loop
K. H. Lim, T. Haug, L. Kwek +1 more·Apr 5, 2021
Simulating quantum dynamics is expected to be performed more easily on a quantum computer than on a classical computer. However, the currently available quantum devices lack the capability to implement fault-tolerant quantum algorithms for quantum si...
Classically Optimal Variational Quantum Algorithms
J. Wurtz, P. Love·Mar 31, 2021
Hybrid quantum-classical algorithms, such as variational quantum algorithms (VQAs), are suitable for implementation on noisy intermediate-scale quantum computers. In this article, we expand an implicit step of VQAs: the classical precomputation subro...
Modelling Quantum Circuits with UML
Ricardo Pérez-Castillo, Luis Jiménez-Navajas, M. Piattini·Mar 30, 2021
None of the quantum computing applications imagined will ever become a reality without quantum software. Quantum programmes have, to date, been coded with ad hoc techniques. Researchers in the field of quantum software engineering are, therefore, now...
Hybrid light-matter networks of Majorana zero modes
L. Contamin, M. Delbecq, B. Douçot +2 more·Mar 30, 2021
Topological excitations, such as Majorana zero modes, are a promising route for encoding quantum information. Topologically protected gates of Majorana qubits, based on their braiding, will require some form of network. Here, we propose to build such...
Hidden qubit cluster states
Giacomo Pantaleoni, B. Baragiola, N. Menicucci·Mar 22, 2021
Continuous-variable cluster states (CVCSs) can be supplemented with Gottesman-Kitaev-Preskill (GKP) states to form a hybrid cluster state with the power to execute universal, fault-tolerant quantum computing in a measurement-based fashion. As the res...
QuClassi: A Hybrid Deep Neural Network Architecture based on Quantum State Fidelity
S. Stein, Y. Mao, Betis Baheri +5 more·Mar 21, 2021
In the past decade, remarkable progress has been achieved in deep learning related systems and applications. In the post Moore's Law era, however, the limit of semiconductor fabrication technology along with the increasing data size have slowed down ...
Quantum Machine Learning with HQC Architectures using non-Classically Simulable Feature Maps
Syed Farhan Ahmad, Raghav Rawat, Minal Moharir·Mar 17, 2021
Hybrid Quantum-Classical (HQC) Architectures are used in near-term NISQ Quantum Computers for solving Quantum Machine Learning problems. The quantum advantage comes into picture due to the exponential speedup offered over classical computing. One of ...
VQE method: a short survey and recent developments
D. Fedorov, Bo Peng, N. Govind +1 more·Mar 15, 2021
The variational quantum eigensolver (VQE) is a method that uses a hybrid quantum-classical computational approach to find eigenvalues of a Hamiltonian. VQE has been proposed as an alternative to fully quantum algorithms such as quantum phase estimati...
Diagrammatic Differentiation for Quantum Machine Learning
Alexis Toumi, Richie Yeung, G. Felice·Mar 14, 2021
We introduce diagrammatic differentiation for tensor calculus by generalising the dual number construction from rigs to monoidal categories. Applying this to ZX diagrams, we show how to calculate diagrammatically the gradient of a linear map with res...
Neural predictor based quantum architecture search
Shi-Xin Zhang, Chang-Yu Hsieh, Shengyu Zhang +1 more·Mar 11, 2021
Variational quantum algorithms (VQAs) are widely speculated to deliver quantum advantages for practical problems under the quantum–classical hybrid computational paradigm in the near term. Both theoretical and practical developments of VQAs share man...