Papers
Live trends in quantum computing research, updated daily from arXiv.
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Hardware platform mentions in abstracts — Photonic leads
Non-Variational Quantum Combinatorial Optimisation
Tavis Bennett, L. Noakes, Jingbo Wang·Apr 4, 2024
This paper introduces a non-variational quantum algorithm designed to solve a wide range of combinatorial optimisation problems, including constrained and non-binary problems. The algorithm leverages an engineered interference process achieved throug...
Molecular Ground State Simulation by Subspace Restriction and Hund's Rule
Leo H. Chiang, Ching-Jui Lai·Apr 4, 2024
Molecular ground state simulation is a promising application of quantum computing. Nevertheless, this question has been shown as a QMA-complete problem, indicating that its complexity increases with the size of the molecule. To address this challenge...
Hamiltonian Simulation in the Interaction Picture Using the Magnus Expansion
Kunal Sharma, M. Tran·Apr 3, 2024
We propose an algorithm for simulating the dynamics of a geometrically local Hamiltonian $A$ under a small geometrically local perturbation $\alpha B$. In certain regimes, the algorithm achieves the optimal scaling and outperforms the state-of-the-ar...
Surrogate optimization of variational quantum circuits
Erik J Gustafson, Juha Tiihonen, Diana Chamaki +8 more·Apr 3, 2024
Significance Optimization on quantum hardware is required in many applications, including Hamiltonian simulation to quantum machine learning; this entails interesting problems that must be addressed both for noisy near-term and fault-tolerant hardwar...
Efficient Quantum Circuits for Non-Unitary and Unitary Diagonal Operators with Space-Time-Accuracy Trade-Offs
Julien Zylberman, Ugo Nzongani, Andrea Simonetto +1 more·Apr 3, 2024
Unitary and non-unitary diagonal operators are fundamental building blocks in quantum algorithms with applications in the resolution of partial differential equations, Hamiltonian simulations, the loading of classical data on quantum computers (quant...
QUSL: Quantum unsupervised image similarity learning with enhanced performance
Lianhui Yu, Xiao-yu Li, Geng Chen +3 more·Apr 2, 2024
Leveraging quantum properties to enhance complex learning tasks has been proven feasible, with excellent recent achievements in the field of unsupervised learning. However, current quantum schemes neglect adaptive adjustments for unsupervised task sc...
Ab initio extended Hubbard model of short polyenes for efficient quantum computing.
Yuichiro Yoshida, Nayuta Takemori, Wataru Mizukami·Apr 2, 2024
We propose introducing an extended Hubbard Hamiltonian derived via the ab initio downfolding method, which was originally formulated for periodic materials, toward efficient quantum computing of molecular electronic structure calculations. By utilizi...
Photonic quantum walk with ultrafast time-bin encoding
Kate L. Fenwick, Frédéric Bouchard, Duncan England +3 more·Apr 2, 2024
The quantum walk (QW) has proven to be a valuable testbed for fundamental inquiries in quantum technology applications such as quantum simulation and quantum search algorithms. Many benefits have been found by exploring implementations of QWs in vari...
A case study against QSVT: assessment of quantum phase estimation improved by signal processing techniques
S. Greenaway, W. Pol, Sukin Sim·Apr 1, 2024
In recent years, quantum algorithms have been proposed which use quantum phase estimation (QPE) coherently as a subroutine without measurement. In order to do this effectively, the routine must be able to distinguish eigenstates with success probabil...
Classical modelling of a lossy Gaussian bosonic sampler
M. V. Umanskii, A. N. Rubtsov·Apr 1, 2024
Gaussian boson sampling (GBS) is considered a candidate problem for demonstrating quantum advantage. We propose an algorithm for approximate classical simulation of a lossy GBS instance. The algorithm relies on the Taylor series expansion, and increa...
Feasibility of first principles molecular dynamics in fault-tolerant quantum computer by quantum phase estimation
I. Kikuchi, Akihito Kikuchi·Mar 31, 2024
This article shows a proof of concept regarding the feasibility of ab initio molecular simulation, wherein the wavefunctions and the positions of nuclei are simultaneously determined by the quantum algorithm, as is realized by the so-called Car-Parri...
Efficient and precise quantum simulation of ultrarelativistic quark-nucleus scattering
Sihao Wu, W. Du, Xingbo Zhao +1 more·Mar 31, 2024
We present an efficient and precise framework to quantum simulate the dynamics of the ultra-relativistic quark-nucleus scattering. This framework employs the eigenbasis of the asymptotic scattering system and implements a compact scheme for encoding ...
Solving reaction dynamics with quantum computing algorithms
Ronen Weiss, Alessandro Baroni, Joseph Carlson +1 more·Mar 30, 2024
The description of quantum many-body dynamics is extremely challenging on classical computers, as it can involve many degrees of freedom. On the other hand, the time evolution of quantum states is a natural application for quantum computers that are ...
Quantum real-time evolution of entanglement and hadronization in jet production: Lessons from the massive Schwinger model
A. Florio, D. Frenklakh, Kazuki Ikeda +4 more·Mar 29, 2024
The possible link between entanglement and thermalization, and the dynamics of hadronization are addressed by studying the real-time response of the massive Schwinger model coupled to external sources. This setup mimics the production and fragmentati...
On the feasibility of quantum teleportation protocols implemented with silicon devices.
Junghee Ryu, Hoon Ryu·Mar 28, 2024
With recent experimental advancements demonstrating high-fidelity universal logic gates and basic programmability, silicon-based spin quantum bits (qubits) have emerged as promising candidates for scalable quantum computing. However, implementation o...
Optimizing Quantum Convolutional Neural Network Architectures for Arbitrary Data Dimension
Changwon Lee, Israel F. Araujo, Dongha Kim +4 more·Mar 28, 2024
Quantum convolutional neural networks (QCNNs) represent a promising approach in quantum machine learning, paving new directions for both quantum and classical data analysis. This approach is particularly attractive due to the absence of the barren pl...
Schrödingerisation based computationally stable algorithms for ill-posed problems in partial differential equations
Shi Jin, Nana Liu, Chuwen Ma·Mar 28, 2024
We introduce a simple and stable computational method for ill-posed partial differential equation (PDE) problems. The method is based on Schr\"odingerization, introduced in [S. Jin, N. Liu and Y. Yu, arXiv:2212.13969][S. Jin, N. Liu and Y. Yu, Phys. ...
Fermihedral: On the Optimal Compilation for Fermion-to-Qubit Encoding
Yuhao Liu, Shize Che, Junyu Zhou +2 more·Mar 26, 2024
This paper introduces Fermihedral, a compiler framework focusing on discovering the optimal Fermion-to-qubit encoding for targeted Fermionic Hamiltonians. Fermion-to-qubit encoding is a crucial step in harnessing quantum computing for efficient simul...
Using Quantum Computers In Control: Interval Matrix Properties
Jan Schneider-Barnes, Julian Berberich·Mar 26, 2024
Quantum computing provides a powerful frame-work for tackling computational problems that are classically intractable. The goal of this paper is to explore the use of quantum computers for solving relevant problems in systems and control theory. In t...
Quadratic Speed‐ups in Quantum Kernelized Binary Classification
Jungyun Lee, Daniel K. Park·Mar 26, 2024
Classification is at the core of data‐driven prediction and decision‐making, representing a fundamental task in supervised machine learning. Recently, several quantum machine learning algorithms that use quantum kernels as a measure of similarities b...