Papers
Live trends in quantum computing research, updated daily from arXiv.
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Molecular electronic structure calculation via a quantum computer
H. Naeij, Erfan Mahmoudi, Hossein Davoodi Yeganeh +1 more·Mar 17, 2023
Quantum computers can be used to calculate the electronic structure and estimate the ground state energy of many-electron molecular systems. In the present study, we implement the Variational Quantum Eigensolver (VQE) algorithm, as a hybrid quantum-c...
Optimal parameter configurations for sequential optimization of the variational quantum eigensolver
Katsuhiro Endo, Yuki Sato, Rudy Raymond +3 more·Mar 13, 2023
Variational Quantum Eigensolver (VQE) is a hybrid algorithm for finding the minimum eigenvalue/vector of a given Hamiltonian by optimizing a parametrized quantum circuit (PQC) using a classical computer. Sequential optimization methods, which are oft...
Variational Quantum Neural Networks (VQNNS) in Image Classification
Meghashrita Das, T. Bolisetti·Mar 10, 2023
Quantum machine learning has established as an interdisciplinary field to overcome limitations of classical machine learning and neural networks. This is a field of research which can prove that quantum computers are able to solve problems with compl...
Efficient and Error-Resilient Data Access Protocols for a Limited-Sized Quantum Random Access Memory
Zhao-Yun Chen, Cheng Xue, Yun-Jie Wang +8 more·Mar 9, 2023
Quantum Random Access Memory (QRAM) is a critical component for loading classical data into quantum computers. While constructing a practical QRAM presents several challenges, including the impracticality of an infinitely large QRAM size and a fully ...
Design of an ultra-low mode volume piezo-optomechanical quantum transducer.
Piero Chiappina, J. Banker, S. Meesala +3 more·Mar 7, 2023
Coherent transduction of quantum states from the microwave to the optical domain can play a key role in quantum networking and distributed quantum computing. We present the design of a piezo-optomechanical device formed in a hybrid lithium niobate on...
Blueprint for quantum computing using electrons on helium
E. Kawakami, Jiabao Chen, M. Benito +1 more·Mar 7, 2023
We present a blueprint for building a fault-tolerant quantum computer using the spin states of electrons on the surface of liquid helium. We propose to use ferromagnetic micropillars to trap single electrons on top of them and to generate a local mag...
Quantum Circuit Completeness: Extensions and Simplifications
A. Cl'ement, Noé Delorme, S. Perdrix +1 more·Mar 6, 2023
Although quantum circuits have been ubiquitous for decades in quantum computing, the first complete equational theory for quantum circuits has only recently been introduced. Completeness guarantees that any true equation on quantum circuits can be de...
Feedback-based quantum algorithms for ground state preparation
James B. Larsen, Matthew D. Grace, A. Baczewski +1 more·Mar 6, 2023
The ground state properties of quantum many-body systems are a subject of interest across chemistry, materials science, and physics. Thus, algorithms for finding ground states can have broad impacts. Variational quantum algorithms are one class of gr...
QAOAwith $N\cdot p\geq 200$
Ruslan Shaydulin, Marco Pistoia·Mar 3, 2023
One of the central goals of the DARPA Optimization with Noisy Intermediate-Scale Quantum (ONISQ) program is to implement a hybrid quantum/classical optimization algorithm with high $N\cdot p$, where $N$ is the number of qubits and $p$ is the number o...
Determination of molecular energies via variational-based quantum imaginary time evolution in a superconducting qubit system
Z. Zong, Sai-nan Huai, T. Cai +10 more·Mar 2, 2023
As a valid tool for solving ground state problems, imaginary time evolution (ITE) is widely used in physical and chemical simulations. Different ITE-based algorithms in their quantum counterpart have recently been proposed and applied to some real sy...
Real-time hybrid quantum-classical computations for trapped ions with Python control-flow
Tobias Schmale, Bence Temesi, Niko Trittschanke +7 more·Mar 2, 2023
In recent years, the number of hybrid algorithms that combine quantum and classical computations has been continuously increasing. These two approaches to computing can mutually enhance each others’ performances thus bringing the promise of more adva...
MAQA: a quantum framework for supervised learning
A. Macaluso, M. Klusch, Stefano Lodi +1 more·Mar 1, 2023
Quantum machine learning has the potential to improve traditional machine learning methods and overcome some of the main limitations imposed by the classical computing paradigm. However, the practical advantages of using quantum resources to solve pa...
Quantum-Selected Configuration Interaction: classical diagonalization of Hamiltonians in subspaces selected by quantum computers
Keita Kanno, M. Kohda, R. Imai +4 more·Feb 22, 2023
We propose quantum-selected configuration interaction (QSCI), a class of hybrid quantum-classical algorithms for calculating the ground- and excited-state energies of many-electron Hamiltonians on noisy quantum devices. Suppose that an approximate gr...
A hybrid quantum-classical method for electron-phonon systems
M. Denner, Alexander Miessen, Haoran Yan +4 more·Feb 20, 2023
Quantum simulation of fermion-boson systems is significant in material applications, while limited by the unbounded boson states. By merging variational non-Gaussian transformations and variational quantum Eigensolvers, the authors design a hybrid qu...
Demonstration of a quantum-classical coprocessing protocol for simulating nuclear reactions
F. Turro, T. Chistolini, A. Hashim +9 more·Feb 13, 2023
Quantum computers hold great promise for arriving at exact simulations of nuclear dynamical processes (e.g., scattering and reactions) that are paramount to the study of nuclear matter at the limit of stability and to explaining the formation of chem...
An expressive ansatz for low-depth quantum approximate optimisation
V. Vijendran, Aritra Das, Dax Enshan Koh +2 more·Feb 9, 2023
The quantum approximate optimisation algorithm (QAOA) is a hybrid quantum–classical algorithm used to approximately solve combinatorial optimisation problems. It involves multiple iterations of a parameterised ansatz that consists of a problem and mi...
Formalising and Learning a Quantum Model of Concepts
S. Tull, R. A. Shaikh, Sara Sabrina Zemljič +1 more·Feb 7, 2023
In this report we present a new modelling framework for concepts based on quantum theory, and demonstrate how the conceptual representations can be learned automatically from data. A contribution of the work is a thorough category-theoretic formalisa...
High-Threshold Codes for Neutral-Atom Qubits with Biased Erasure Errors
K. Sahay, J. Jin, J. Claes +2 more·Feb 6, 2023
The requirements for fault-tolerant quantum error correction can be simplified by leveraging structure in the noise of the underlying hardware. In this work, we identify a new type of structured noise motivated by neutral atom qubits, biased erasure ...
A Quantum Neural Network Regression for Modeling Lithium-ion Battery Capacity Degradation
Anh Phuong Ngo, Nhat Le, Hieu Nguyen +2 more·Feb 6, 2023
Given their high power density, low discharge rate, and decreasing cost, rechargeable lithium-ion batteries (LiBs) have found a wide range of applications such as power grid-level storage systems, electric vehicles (EVs), and mobile devices. Developi...
Heterogeneous integration of superconducting thin films and epitaxial semiconductor heterostructures with lithium niobate
Michelle Lienhart, Michael Choquer, Emeline D. S. Nysten +5 more·Feb 6, 2023
We report on scalable heterointegration of superconducting electrodes and epitaxial semiconductor quantum dots (QDs) on strong piezoelectric and optically nonlinear lithium niobate. The implemented processes combine the sputter-deposited thin film su...