Papers
Live trends in quantum computing research, updated daily from arXiv.
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Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
Comment on "Properties and dynamics of generalized squeezed states"
Rubén Gordillo-Hachuel, Ricardo Puebla·Jul 16, 2025
A recent article [S. Ashhab and M. Ayyash, New J. Phys. 27, 054104 (2025)] has reported unexpected oscillatory dynamics in generalized squeezed states of order higher than two as their squeezing parameter increases. This behaviour, observed through n...
Selective decoupling in multi-level quantum systems by the SU(2) sign anomaly
Giorgio Anfuso, Giulia Piccitto, Vittorio Romano +2 more·Jul 16, 2025
We investigate dynamical decoupling operated by $2π$-pulses in a two-level subspaces of a multilevel system showing that it may leads to selective decoupling. This provides a flexible strategy for decoupling transitions in a quantum network, when con...
Benchmarking fault-tolerant quantum computing hardware via QLOPS
Linghang Kong, Fang Zhang, Jianxin Chen·Jul 16, 2025
It is widely recognized that quantum computing has profound impacts on multiple fields, including but not limited to cryptography, machine learning, materials science, etc. To run quantum algorithms, it is essential to develop scalable quantum hardwa...
Unfolded distillation: very low-cost magic state preparation for biased-noise qubits
Diego Ruiz, Jérémie Guillaud, Christophe Vuillot +1 more·Jul 16, 2025
Magic state distillation enables universal fault-tolerant quantum computation by implementing non-Clifford gates via the preparation of high-fidelity magic states. However, it comes at the cost of substantial logical-level overhead in both space and ...
QAS-QTNs: Curriculum Reinforcement Learning-Driven Quantum Architecture Search for Quantum Tensor Networks
Siddhant Dutta, Nouhaila Innan, S. Yahia +1 more·Jul 16, 2025
Quantum Architecture Search (QAS) is an emerging field aimed at automating the design of quantum circuits for optimal performance. This paper introduces a novel QAS framework employing hybrid quantum reinforcement learning with quantum curriculum lea...
Efficient Preparation of Fermionic Superfluids in an Optical Dipole Trap through Reinforcement Learning
Yueyang Min, Ziliang Li, Yi Zhong +4 more·Jul 16, 2025
We demonstrate a reinforcement learning (RL)-based control framework for optimizing evaporative cooling in the preparation of strongly interacting degenerate Fermi gases of 6Li. Using a Soft Actor-Critic (SAC) algorithm, the system autonomously explo...
Heisenberg limited multiple eigenvalue estimation via off-the-grid compressed sensing
D. Castaldo, Stefano Corni·Jul 16, 2025
Quantum phase estimation is the flagship algorithm for quantum simulation on fault-tolerant quantum computers. We demonstrate that an \emph{off-grid} compressed sensing protocol, combined with a state-of-the-art signal classification method, enables ...
Surrogate Quantum Circuit Design for the Lattice Boltzmann Collision Operator
Monica Lacatus, Matthias Möller·Jul 16, 2025
This study introduces a framework for learning a low‐depth surrogate quantum circuit (SQC) that approximates the nonlinear, dissipative, and hence non‐unitary Bhatnagar–Gross–Krook (BGK) collision operator in the lattice Boltzmann method (LBM) for th...
Efficient Qudit Circuit for Quench Dynamics of $2+1$D Quantum Link Electrodynamics
Rohan Joshi, M. Meth, Jan C. Louw +4 more·Jul 16, 2025
A major challenge in the burgeoning field of quantum simulation for high-energy physics is the realization of scalable $2+1$D lattice gauge theories on state-of-the-art quantum hardware, which is an essential step towards the overarching goal of prob...
Material Loss Model Calibration for Tantalum Superconducting Resonators
G. Moshel, Sergei Masis, Moshe Schechter +1 more·Jul 16, 2025
Material research is a key frontier in advancing superconducting qubit and circuit performance. In this work, we develop a simple and broadly applicable framework for accurately characterizing two-level system (TLS) loss using internal quality factor...
On approximate quantum error correction for symmetric noise
Gereon Koßmann, Julius A. Zeiss, Omar Fawzi +1 more·Jul 16, 2025
We revisit the extendability-based semi-definite programming hierarchy introduced by Berta et al. [Mathematical Programming, 1 - 49 (2021)], which provides converging outer bounds on the optimal fidelity of approximate quantum error correction (AQEC)...
An Adversarial Quantum Key Distribution Project
Brian R. La Cour, Noah A. Davis·Jul 16, 2025
Quantum key distribution (QKD) is a popular introduction to quantum technologies used in education and public outreach, as very little background in quantum theory is needed and the practical applications are easily understood. There is considerably ...
Simultaneous High-Fidelity Single-Qubit Gates in a Spin Qubit Array
Yi-Hsien Wu, L. Camenzind, Patrick Butler +8 more·Jul 16, 2025
Silicon spin qubits are a promising platform for scalable quantum computing due to their compatibility with industrial semiconductor fabrication and the recent scaling to multi-qubit devices. Control fidelities above the 99% fault-tolerant threshold ...
Design Automation in Quantum Error Correction
Archisman Ghosh, Avimita Chatterjee, Swaroop Ghosh·Jul 16, 2025
Quantum error correction (QEC) underpins practical fault-tolerant quantum computing (FTQC) by addressing the fragility of quantum states and mitigating decoherence-induced errors. As quantum devices scale, integrating robust QEC protocols is imperati...
Jenga-Krotov algorithm: Efficient compilation of multiqubit gates for exchange-only qubits
Jiahao Wu, Guanjie He, Wenyuan Zhuo +2 more·Jul 16, 2025
Exchange-only (EO) qubits, implemented in triple-quantum-dot systems, offer a compelling platform for scalable semiconductor-based quantum computing by enabling universal control through purely exchange interactions. While high-fidelity single- and t...
BenchRL-QAS: Benchmarking reinforcement learning algorithms for quantum architecture search
Azhar Ikhtiarudin, Aditi Das, Param Thakkar +1 more·Jul 16, 2025
We present BenchRL-QAS, a unified benchmarking framework for reinforcement learning (RL) in quantum architecture search (QAS) across a spectrum of variational quantum algorithm tasks on 2- to 8-qubit systems. Our study systematically evaluates 9 diff...
Compensating connectivity restrictions in quantum annealers via splitting and linearization techniques
Marcel Seelbach Benkner, Zorah Lahner, Vladislav Golyanik +2 more·Jul 16, 2025
Current quantum annealing experiments often suffer from restrictions in connectivity in the sense that only certain qubits can be coupled to each other. The most common strategy to overcome connectivity restrictions so far is by combining multiple ph...
Qrisp Implementation and Resource Analysis of a T-Count-Optimised Non-Restoring Quantum Square-Root Circuit
Heorhi Kupryianau, Marcin Niemiec·Jul 16, 2025
Efficient quantum arithmetic operations are essential building blocks for complex quantum algorithms, yet few theoretical designs have been implemented in practical quantum programming frameworks. This paper presents the first complete implementation...
Beyond Ground States: Physics-Inspired Optimization of Excited States of Classical Hamiltonians
Erik Altelarrea-Ferr'e, J'ulia Barbera-Rodr'iguez, David Jansen +1 more·Jul 16, 2025
We introduce excited local quantum annealing (ExcLQA), a classical, physics-inspired algorithm that extends local quantum annealing (LQA) to identify excited states of classical Ising Hamiltonians. LQA simulates quantum annealing while constraining t...
Probing Hadron Scattering in Lattice Gauge Theories on Qudit Quantum Computers
Rohan Joshi, Jan C. Louw, M. Meth +5 more·Jul 16, 2025
An overarching goal in the flourishing field of quantum simulation for high-energy physics is the first-principles study of the microscopic dynamics of scattering processes on a quantum computer. Currently, this is hampered by small system sizes and ...