Papers
Live trends in quantum computing research, updated daily from arXiv.
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Hardware platform mentions in abstracts — Photonic leads
Choco-Q: Commute Hamiltonian-based QAOA for Constrained Binary Optimization
Debin Xiang, Qifan Jiang, Liqiang Lu +2 more·Mar 1, 2025
Constrained binary optimization aims to find an optimal assignment to minimize or maximize the objective meanwhile satisfying the constraints, which is a representative NP problem in various domains, including transportation, scheduling, and economy....
Collective neutrino oscillations in three flavors on qubit and qutrit processors
Luca Spagnoli, Noah Goss, A. Roggero +9 more·Mar 1, 2025
Collective neutrino flavor oscillations are of primary importance in understanding the dynamic evolution of core-collapse supernovae and subsequent terrestrial detection, but also among the most challenging aspects of numerical simulations. This situ...
iSWAP gate with polar molecules: Robustness criteria for entangling operations
Matteo Bergonzoni, Sven Jandura, G. Pupillo·Feb 28, 2025
Ultracold polar molecules in optical lattices or tweezer arrays offer a promising platform for quantum information processing and simulation, thanks to their rich internal structure and long-range dipolar interactions. Recent experimental advances no...
Imperfect preparation and Trojan attack on the phase modulator in the decoy-state BB84 protocol
Aleksei Reutov·Feb 28, 2025
Quantum key distribution (QKD) provides a theoretically secure method for cryptographic key exchange by leveraging quantum mechanics, but practical implementations face vulnerabilities such as Trojan horse attack on phase modulators. This work analyz...
Hybrid quantum neural networks with variational quantum regressor for enhancing QSPR modeling of CO2-capturing amine
Hyein Cho, Jeonghoon Kim, Kyoung Tai No +1 more·Feb 28, 2025
Accurate amine property prediction is essential for optimizing CO2 capture efficiency in post-combustion processes. Quantum machine learning (QML) can enhance predictive modeling by leveraging superposition, entanglement, and interference to capture ...
Digital-Controlled Method of Conveyor-Belt Spin Shuttling in Silicon for Large-Scale Quantum Computation
R. Nagai, Takashi Takemoto, Yusuke Wachi +1 more·Feb 28, 2025
We propose a digital-controlled conveyor-belt shuttling method for silicon-based quantum processors, addressing the scalability challenges of conventional analog sinusoidal implementations. By placing a switch matrix and low-pass filters in a cryogen...
Bogoliubov-Born-Green-Kirkwood-Yvon hierarchy for quantum error mitigation
Theo Saporiti, Oleg Kaikov, V. Sazonov +1 more·Feb 28, 2025
Mitigation of quantum errors is critical for current NISQ devices. In the present work, we address this task by treating the execution of quantum algorithms as the time evolution of an idealized physical system. We use knowledge of its physics to ass...
High-Fidelity Integrated Quantum Photonic Logic Via Robust Directional Couplers
Jonatan Piasetzky, Khen Cohen, Yehonatan Drori +4 more·Feb 27, 2025
Scalable quantum information processing with integrated photonics requires quantum logic operations with high fidelity and robustness. Directional couplers, the fundamental elements enabling quantum interference and logic operations, are inherently s...
Applications of the Quantum Phase Difference Estimation Algorithm to the Excitation Energies in Spin Systems on a NISQ Device
Boni Paul, S. B. Mandal, Kenji Sugisaki +1 more·Feb 27, 2025
The Quantum Phase Difference Estimation (QPDE) algorithm, as an extension of the Quantum Phase Estimation (QPE), is a quantum algorithm designed to compute the differences of two eigenvalues of a unitary operator by exploiting the quantum superpositi...
Advancements and Challenges in Quantum Machine Learning for Medical Image Classification: A Comprehensive Review
Md. Farhan Shahriyar, Gazi Tanbhir·Feb 27, 2025
Quantum technologies are rapidly advancing as image classification tasks grow more complex due to large image volumes and extensive parameter updates required by traditional machine learning models. Quantum Machine Learning (QML) offers a promising s...
Enhancing quantum computations with the synergy of auxiliary field quantum Monte Carlo and computational basis tomography
V. Khinevich, Wataru Mizukami·Feb 27, 2025
We introduce QC-CBT-AFQMC, a hybrid algorithm that incorporates computational basis tomography (CBT) into the quantum-classical auxiliary-field quantum Monte Carlo (QC-AFQMC) method proposed by Huggins et al. [Nature 603, 416-420 (2022)], replacing t...
AI-Powered Noisy Quantum Emulation: Generalized Gate-Based Protocols for Hardware-Agnostic Simulation
Matthew Ho, Jun Yong Khoo, A. Mak +1 more·Feb 27, 2025
Quantum computer emulators model the behavior and error rates of specific quantum processors. Without accurate noise models in these emulators, it is challenging for users to optimize and debug executable quantum programs prior to running them on the...
Experimental realization of a quantum heat engine based on dissipation-engineered superconducting circuits
Tuomas Uusnäkki, Timm Morstedt, Wallace S. Teixeira +2 more·Feb 27, 2025
Quantum heat engines (QHEs) have attracted long-standing scientific interest, especially inspired by considerations of the interplay between heat and work with the quantization of energy levels, quantum superposition, and entanglement. Operating QHEs...
Simulating non-Abelian statistics of parafermions with superconducting processor
Hongyu Wang, Xiong-jun Liu·Feb 27, 2025
Parafermions, which can be viewed as a fractionalized version of Majorana modes, exhibit profound non-Abelian statistics and emerge in topologically ordered systems, while their realization in experiment has been challenging. Here we propose a novel ...
Quantum low-density parity-check codes for erasure-biased atomic quantum processors
Laura Pecorari, G. Pupillo·Feb 27, 2025
Identifying the best families of quantum error correction (QEC) codes for near-term experiments is key to enabling fault-tolerant quantum computing. Ideally, such codes should have low overhead in qubit number, high physical error thresholds, and mod...
Linear optical quantum computing with a hybrid squeezed cat code
Shohei Kiryu, Kosuke Fukui, A. Okamoto +1 more·Feb 27, 2025
In recent years, squeezed cat codes with resilience to specific types of loss have been proposed as a step toward realizing fault-tolerant optical quantum computers. However, error correction for squeezed cat codes requires a strong nonlinearity, whi...
Quantum Natural Gradient optimizer on noisy platforms: QAOA as a case study
Federico Dell'Anna, Rafael Gomez-Lurbe, Armando Pérez +1 more·Feb 27, 2025
We investigate the performance of the Quantum Natural Gradient (QNG) optimizer in the presence of noise. Specifically, we evaluate the efficacy of QNG within the Quantum Approximate Optimization Algorithm (QAOA) for finding the ground state of the Tr...
Exploring experimental limit of deep quantum signal processing using a trapped-ion simulator
J. Bu, Lei Zhang, Zhan Yu +12 more·Feb 27, 2025
Quantum signal processing (QSP), which enables systematic polynomial transformations on quantum data through sequences of qubit rotations, has emerged as a fundamental building block for quantum algorithms and data re-uploading quantum neural network...
Digital-Analog quantum Rabi simulation in the Deep Strong Coupling Regime
Noureddine Rochdi, Rachid Ahl Laamara, Mohamed Bennai·Feb 26, 2025
We study the quantum Rabi model (QRM) in the deep strong coupling (DSC) regime. To capture the full dynamics of the QRM in the DSC regime, we implemented single-qubit rotations combined with integrated digital steps and qubit-bosonic blocks. This app...
Non-paraxial effects on laser-qubit operations
L. Gallagher, M. Mazzanti, Z. Ackerman +3 more·Feb 26, 2025
Tightly-focused laser beams, or optical tweezers, are essential for analogue and digital quantum simulation with neutral atoms and trapped ions. Despite this, most of the current intuition and theoretical treatment utilizes the paraxial approximation...