Papers
Live trends in quantum computing research, updated daily from arXiv.
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16,712 papers in 12 months (-57% vs prior quarter)
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Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
Relativistic Gravity-Induced Entanglement via Frame Dragging
Eyuri Wakakuwa, Luciano Petruzziello, Trinidad B. Lantaño +2 more·Jun 30, 2026
Gravity-induced entanglement has been proposed as a method for testing the non-classical nature of gravity via tabletop experiments. While most existing proposals are restricted to the Newtonian limit, the frame dragging effect offers access to genui...
Suppressing Parametric Instabilities in Driven Bosonic Lattices through Multi-tone Control
Robbie Cruickshank, Samuel Lellouch, Marin Bukov +3 more·Jun 30, 2026
Periodically driven quantum systems offer remarkable flexibility in tailoring effective Hamiltonians and synthetic band structures. However, such driving also induces heating and dynamical instabilities that limit the coherence and lifetime of many-b...
Nonequilibrium Casimir-Polder Force: Magnus-like Effect
Maria Vittoria Gurrieri, Kurt Busch, Francesco Intravaia·Jun 30, 2026
The motion of a particle in vacuum near macroscopic bodies gives rise to a Magnus-like contribution to the nonequilibrium Casimir-Polder force. This effect originates from the interplay between particle dynamics and material-modified electromagnetic ...
Memory-Scalable and Hardware-Adaptive Matrix-Free Quantum Simulation
Uriel Shafir, Ronnie Kosloff·Jun 30, 2026
The core step in quantum simulations is typically matrix vector multiplication $φ= \Hmat ψ$. Executing this step is limited by memory requirement to store the Hamiltonian. We present a memory-scalable, hardware-adaptive matrix-free framework for appl...
Power law scaling for classification accuracy in physical neural networks
Andrei V. Ermolaev, Mathilde Hary, Anas Skalli +7 more·Jun 30, 2026
Physical neural networks (PNNs) harness the intrinsic complexity of physical systems to perform neural computation, potentially at speeds and energy efficiencies inaccessible to conventional digital hardware. Yet, a principled framework for quantifyi...
Topological zero-reflection points in multi-terminal quantum wire junctions
Abhiram Soori, Udit Khanna, Diptiman Sen·Jun 30, 2026
We study scattering in noninteracting multi-terminal quantum wire junctions and show that junctions with dihedral symmetry can exhibit exact zero-reflection points for $N \ge 4$ terminals. By analyzing the scattering matrix, we identify these reflect...
A logarithmic phase singularity at the heart of Landau-Zener transitions
Eric P. Glasbrenner, David Fabian, Wolfgang P. Schleich·Jun 30, 2026
Three ingredients of the elementary Landau-Zener problem determine the familiar expression $a_{LZ}\equiv\exp\left[-π/(2ε)\right]$ for the asymptotic value of the probability amplitude for remaining in the initial level: (i) A wave whose phase is dete...
In-situ Indexing via Memristive Content-Addressable Memory
Bing Wu, Xueliang Wei, Shiyi Song +6 more·Jun 30, 2026
Processing-in-Memory (PIM) is a proven paradigm for overcoming the ``memory wall". However, while data indexing is severely bottlenecked by this same wall, it remains unclear how indexing can effectively benefit from PIM's unique capabilities. We pre...
Inverse-squeezing receivers for squeezed-state pulse-position modulation under ideal and phase-diffusion conditions
Enhao Bai, Fengkai Sun, Tianyi Wu +4 more·Jun 30, 2026
We introduce a squeezed-state pulse-position modulation (S-PPM) format, where the empty slots are squeezed vacuum states and the pulse slot is a displaced squeezed state. Based on this property, we propose an inverse-squeezing conditional pulse-nulli...
Beyond the Expressivity-Trainability Paradox: A Dynamical Lie Algebra Perspective on Navigating Barren Plateaus in Quantum Machine Learning
Kung-Ming Lan, Edward Huang·Jun 30, 2026
As Quantum Machine Learning (QML) transitions toward practical implementation, the field faces a critical architectural bottleneck that challenges the fundamental assumptions of classical statistical learning theory. In classical deep learning, incre...
Machine Learning based Optimization of CV-QKD Under Practical Constraints
Svitlana Matsenko, Amirhossein Ghazisaeidi, Marcin Jarzyna +4 more·Jun 30, 2026
Practical hardware limitations, including finite transmitter and receiver filter lengths as well as the finite resolution of digital-to-analog and analog-to-digital converters, lead to mode mismatch and degrade the performance of continuous-variable ...
Nonlinear Schrödinger equations: Symmetries, superposition, and classicality from a Bohmian perspective
Ángel S. Sanz·Jun 30, 2026
Interference is commonly regarded as the most direct manifestation of the superposition principle. This association is natural for the linear Schrödinger equation, where coherent alternatives combine at the level of probability amplitudes. However, t...
Resourcefulness without Resource: Geometric Origins and Robustness
Jingsong Ao, Aby Philip, Alexander Streltsov·Jun 30, 2026
A prevailing intuition holds that quantum protocols using only free states confer no operational advantage. This intuition is contradicted by free-state discrimination gaps in which restricted measurements fail to optimally distinguish even orthogona...
Temporal-Plane Carroll--Schrödinger Dynamics and Vortex Sectors in (2,2) Klein Space
José Rojas, Melvin Arias·Jun 30, 2026
Motivated by the temporal dynamics identified in the $(1+1)$ Carroll-Schrödinger theory, we derive a post-Carrollian Schrödinger dynamics in flat Klein space with signature $(2,2)$. Starting from the tachyonic Klein-Gordon equation in double-polar co...
Spectral Geometry and Bosonic-Bloch Probes: Explorations in Quantum Learning
Santanu Ganguly, Xing Liang, Dimitrios Makris·Jun 30, 2026
This paper studies how spectral geometry emerges in quantum learning models and how it can be diagnosed with physically grounded probes. In graph-regularized quantum networks, training reorganizes the output similarity graph, increases the effective ...
Spectral Multipartite Entanglement
Vahid Azimi-Mousolou·Jun 30, 2026
We introduce a unified, computable measure of multipartite entanglement based on the spectral properties of an entanglement graph and its associated entanglement matrix. This framework quantifies quantum correlations among arbitrary subsystems and pa...
Wave-particle duality as an uncertainty relation for the average confidence width
Shengjun Wu·Jun 30, 2026
We introduce the average confidence width $Δ_a x=\int_0^1 Δ_c x (θ_x) d θ_x$: the confidence width $Δ_c x(θ_x)$ -- the smallest position interval carrying a fraction $θ_x$ of the probability -- averaged over all levels. It is the first moment of the ...
The limits of erasure-based postselection for quantum error mitigation
Sam J. Griffiths, Jamie Friel, Brian Vlastakis·Jun 30, 2026
In both classical and quantum error correction, heralded erasures are known to be easier to tolerate than unheralded general stochastic errors. Whilst an established benefit of loss-dominant quantum architectures such as photonic qubits, this fact ha...
Programmable optical parametric amplifier synthesizer for cubic phase states and amplified Schrodinger cat states
Yusuf Turek, Ming-Yan Sun, Xiao-Xi Yao·Jun 30, 2026
We introduce a programmable optical parametric amplifier (OPA) synthesizer that, under a heralded photon-number-resolving framework, generates high-fidelity cubic phase states and amplifies Schrodinger cat states. By systematically exploring both the...
A Quantum-Classical Surrogate Model for the Collision Operator of the Lattice Boltzmann Method
Lukas C. Birk, David M. Wawrzyniak, Josef M. Winter +4 more·Jun 30, 2026
We introduce a hybrid approach utilising a quantum machine learning surrogate model to approximate the non-linear collision dynamics of the LBM. It effectively offloads the non-unitary operations that challenge pure quantum solvers. The expressivity ...