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Physics & Astronomy
Physics and astronomy have shared new results on arXiv for over thirty years. This page shows the newest papers ReadSearch has read there, from astrophysics and condensed matter to particle, quantum and applied physics, with papers OpenAlex files under the same subjects.
The newest 1,000 papers, from 29 October 2026 to 5 November 2026: 1,000 arXiv preprints.
Newest papers, page 35
An Observable-Algebra Approach to Quantum Coherence in Anyonic Systems
Physical restrictions on operations can make quantum coherence inaccessible.Quantum Lower Bounds for Collision Problems
We establish tight lower bounds on the adaptive and non-adaptive quantum query complexities of Promised $k$-to-one Finding on an exactly $k$-to-one input string $x\in\mathbb Z_q^n$, for every fixed…Detection Instead of Inversion: T1-T2 Microstructure Quantification With Detection Transformers
T1-T2 correlation MRI has strong potential to quantify microstructural compartments without imposing a biological model.Quantum Recovery from Black-Hole Radiation Beyond the Emission Yield
A proposed resolution of the black-hole information paradox must explain which information an outside observer can recover from escaping radiation\cite{Hawking,Page,Hayden,Almheiri}.Spin-induced lateral acoustic forces on chiral and achiral particles
Acoustic spin enables intriguing chiral sound-matter interactions, yet its mechanical consequences remain much less explored.Long-term yields of short-rate models as Feynman-Kac ground states: a variational quantum eigensolver with single-setting energy estimation on two NISQ platforms
We show that the long-term yield of a short-rate model is the ground-state energy of a Schrodinger operator obtained from the Feynman-Kac bond-pricing equation, so that it can be computed by a…Propagation invariant one-dimensional flat-top vector beam with conserved topology
We report the generation and control of a propagation invariant one-dimensional flat-top vector beam through the digitally controlled superposition of a first-order petal- and Gaussian- mode each…Prior-Guided Physics-Informed Deep Learning for Fast 4D MRI Reconstruction
Background and purpose: We propose PGPI4MR (prior-guided, physics-informed 4D MRI reconstruction), a deep learning method that leverages information from other respiratory phases or a setup scan…Tensor Contraction with ZX Calculus, a Graph-Theoretic Approach
Tensors are higher dimensional generalisations of vectors and matrices.Pore-scale mechanisms of capillary imbibition in cement-based materials revealed by direct numerical simulations in a realistic FIB-SEM microstructure
Moisture transport in cement-based materials involves transient multiphase flow through highly irregular pore networks, where evolving air--water interfaces strongly influence liquid invasion and…Experimental demonstration of phase-conjugated twin-wave coherent reception over 100 km with injection locking assisted phase stabilization
Recovering complex optical signals with high sensitivity is central to coherent communication and sensing.Quantum Path Finder: Navigating Constraint Space via Non-Abelian Gauge Dynamics
Quantum algorithms are commonly designed within the circuit paradigm or through adiabatic evolution.Seeing Why: Exact Evidence Maps for Quantum and Optical Image Classifiers
When an image classifier decides, we can usually only estimate why.Rule-based hardware-configurable static analysis for quantum programs
The rapid evolution of quantum hardware necessitates an adaptable static analysis framework for validating quantum programs.Controlling the Sign and Magnitude of the Thermoreflectance Coefficient of Gold-MoS$_2$ Metamaterials
Heating a material changes how much light it reflects.Beliefs in feedback: Factored representations of interacting agents in transformers
Complex systems, from ecosystems to brains, are usually modeled as modular components coupled through feedback rather than as indivisible wholes.Reinforcement Learning in High-Energy Physics: A Survey from Accelerator Control to Theory Exploration
Reinforcement learning (RL) is a machine learning paradigm in which an agent learns a decision-making policy by interacting with an environment, guided by a scalar reward rather than explicit…Classical and Quantum Logics with Multiple Non-Equivalent and Non-Isomorphic Models
Both quantum and classical logics have several mutually non-equivalent and non-isomorphic models as has repeatedly been proved in the literature.Black Hole Love Numbers with Physics-Informed Neural Networks
We develop and validate a physics-informed neural network (PINN) framework for computing the tidal Love numbers of black holes directly from their perturbation equations.Interaction order sets the onset cost of steady-state quantum magic
Maintaining quantum magic under continuous noise requires coherent control and a supply of purity.
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