Papers
Live trends in quantum computing research, updated daily from arXiv.
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Hardware platform mentions in abstracts — Photonic leads
A Study on Optimization Techniques for Variational Quantum Circuits in Reinforcement Learning
Michael Kölle, Timo Witter, Tobias Rohe +3 more·May 20, 2024
Quantum Computing aims to streamline machine learning, making it more effective with fewer trainable parameters. This reduction of parameters can speed up the learning process and reduce the use of computational resources. However, in the current pha...
Resource-Efficient Hybrid Quantum-Classical Simulation Algorithm
Chong Hian Chee, Daniel Leykam, A. Mak +2 more·May 17, 2024
Digital quantum computers promise exponential speedups in performing quantum time-evolution, providing an opportunity to simulate quantum dynamics of complex systems in physics and chemistry. However, the task of extracting desired quantum properties...
Silicon nitride integrated photonics from visible to mid-infrared spectra
K. Buzaverov, A. Baburin, Evgeny V. Sergeev +15 more·May 16, 2024
Recently, silicon nitride (Si3N4) photonic integrated circuits (PICs) are of a great interest due to their extremely low waveguides losses. The number of Si3N4 integrated photonics platform applications is constantly growing including the Internet of...
Noise-resilient and resource-efficient hybrid algorithm for robust quantum gap estimation
Woo-Ram Lee, Nathan M. Myers, V. Scarola·May 16, 2024
We present a hybrid quantum algorithm for estimating gaps in many-body energy spectra, supported by an analytic proof of its inherent resilience to state preparation and measurement errors, as well as mid-circuit multi-qubit depolarizing noise. Our a...
Boosting End-to-End Entanglement Fidelity in Quantum Repeater Networks via Hybridized Strategies
Poramet Pathumsoot, Theerapat Tansuwannont, Naphan Benchasattabuse +5 more·May 16, 2024
Quantum networks are expected to enhance distributed quantum computing and quantum communication over long distances while providing security dependent upon physical effects rather than mathematical assumptions. Through simulation, we show that a qua...
Compact quantum algorithms for time-dependent differential equations
Sachin S. Bharadwaj, K. Sreenivasan·May 16, 2024
Many claims of computational advantages have been made for quantum computing over classical but they have not been demonstrated for practical problems. Here, we present algorithms for solving time-dependent PDEs, with particular reference to fluid eq...
Hybrid Meta-Solving for Practical Quantum Computing
Domenik Eichhorn, Maximilian Schweikart, Nick Poser +3 more·May 15, 2024
The advent of quantum algorithms has initiated a discourse on the potential for quantum speedups for optimization problems. However, several factors still hinder a practical realization of the potential benefits. These include the lack of advanced, e...
Unveiling quantum phase transitions from traps in variational quantum algorithms
C. Cao, F. M. Gambetta, Ashley Montanaro +1 more·May 14, 2024
Understanding quantum phase transitions in physical systems is fundamental to characterize their behavior at low temperatures. Achieving this requires both accessing good approximations to the ground state and identifying order parameters to distingu...
Hype or Heuristic? Quantum Reinforcement Learning for Join Order Optimisation
Maja Franz, Tobias Winker, S. Groppe +1 more·May 13, 2024
Identifying optimal join orders (JOs) stands out as a key challenge in database research and engineering. Owing to the large search space, established classical methods rely on approximations and heuristics. Recent efforts have successfully explored ...
Quantum Krylov-Subspace Method Based Linear Solver
Ruibin Xu, Zhu-Jun Zheng, Zheng Zheng·May 10, 2024
Despite the successful enhancement to the Harrow-Hassidim-Lloyd algorithm by Childs et al., who introduced the Fourier approach leveraging linear combinations of unitary operators, our research has identified non-trivial redundancies within this meth...
Hybrid Quantum Graph Neural Network for Molecular Property Prediction
Michael Vitz, Hamed Mohammadbagherpoor, S. Sandeep +3 more·May 8, 2024
To accelerate the process of materials design, materials science has increasingly used data driven techniques to extract information from collected data. Specially, machine learning (ML) algorithms, which span the ML discipline, have demonstrated abi...
Resource-Efficient and Self-Adaptive Quantum Search in a Quantum-Classical Hybrid System
Zihao Jiang, Zefan Du, Shaolun Ruan +5 more·May 7, 2024
Over the past decade, the rapid advancement of deep learning and big data applications has been driven by vast datasets and high-performance computing systems. However, as we approach the physical limits of semiconductor fabrication in the post-Moore...
A Greedy Quantum Route-Generation Algorithm
Jordan Makansi, David E. Bernal Neira·May 5, 2024
Routing and scheduling problems with time windows have long been important optimization problems for logistics and planning. Many classical heuristics and exact methods exist for such problems. However, there are no satisfactory methods for generatin...
Characterizing randomness in parameterized quantum circuits through expressibility and average entanglement
Guilherme Ilário Correr, Ivan Medina, P. C. Azado +2 more·May 3, 2024
While scalable error correction schemes and fault tolerant quantum computing seem not to be universally accessible in the near sight, the efforts of many researchers have been directed to the exploration of the contemporary available quantum hardware...
Multiple quantum exceptional, diabolical, and hybrid points in multimode bosonic systems: II. Nonconventional PT-symmetric dynamics and unidirectional coupling
Jan Peřina, Kishore Thapliyal, Grzegorz Chimczak +2 more·May 2, 2024
We analyze the existence and degeneracies of quantum exceptional, diabolical, and hybrid points in simple bosonic systems - comprising up to six modes with damping and/or amplification - under two complementary scenarios to those described in Quantum...
Multiple quantum exceptional, diabolical, and hybrid points in multimode bosonic systems: I. Inherited and genuine singularities
Kishore Thapliyal, Jan Peřina, Grzegorz Chimczak +2 more·May 2, 2024
The existence and degeneracies of quantum exceptional, diabolical, and hybrid (i.e., diabolically degenerated exceptional) singularities of simple bosonic systems composed of up to five modes with damping and/or amplification are analyzed. Their dyna...
Digital-analog counterdiabatic quantum optimization with trapped ions
Shubham Kumar, N. N. Hegade, Alejandro Gomez-Cadavid +3 more·May 2, 2024
We introduce a hardware-specific, problem-dependent digital-analog quantum algorithm of a counterdiabatic quantum dynamics tailored for optimization problems. Specifically, we focus on trapped-ion architectures, taking advantage from global Mølmer–Sø...
Barren plateaus in variational quantum computing
Martín Larocca, Supanut Thanasilp, Samson Wang +7 more·May 1, 2024
Variational quantum computing offers a flexible computational approach with a broad range of applications. However, a key obstacle to realizing their potential is the barren plateau (BP) phenomenon. When a model exhibits a BP, its parameter optimizat...
Light cone cancellation for variational quantum eigensolver in solving noisy Max-Cut
Xinwei Lee, Xinjian Yan, Ningyi Xie +5 more·Apr 30, 2024
Variational Quantum Eigensolver (VQE) is a quantum-classical hybrid algorithm used to estimate the ground energy of a given Hamiltonian. It consists of a parameterized quantum circuit, which the parameters are optimized using a classical optimizer. W...
Expanding the Horizon: Enabling Hybrid Quantum Transfer Learning for Long-Tailed Chest X-Ray Classification
Sk Chan, Pranav Kulkarni, P. Yi +1 more·Apr 30, 2024
Quantum machine learning (QML) has the potential for improving the multi-label classification of rare, albeit critical, diseases in large-scale chest x-ray (CXR) datasets due to theoretical quantum advantages over classical machine learning (CML) in ...