⚛️ Category

quant-ph

9721 papers

Quantum physics explores the strange and often counterintuitive rules that govern the universe at its smallest scales. This field investigates how particles like electrons and photons behave in ways that defy our everyday intuition, forming the backbone of modern technologies from lasers to future quantum computers. While the mathematics can be daunting, the core ideas promise to revolutionize how we understand reality and process information.

At Gist.Science, we make these complex discoveries accessible to everyone. We systematically process every new preprint published in the Quant-Ph category on arXiv, transforming dense academic papers into clear, plain-language explanations alongside detailed technical summaries. Whether you are a seasoned researcher or a curious reader, our goal is to bridge the gap between cutting-edge theory and human understanding.

Below are the latest papers in quantum physics, distilled to help you grasp the newest breakthroughs without getting lost in the jargon.

⚛️ quantum physics

Cryptographic Conditions for Efficient Testing of Distributions and Quantum States

This paper introduces a cryptographic framework for distribution and quantum state testing that overcomes traditional sample complexity and independence limitations by proving that polynomially many samples suffice to verify efficiently samplable distributions even when samples are adversarially generated and correlated, utilizing novel Kolmogorov complexity techniques to achieve these results and enable applications like assumption-free certified randomness and quantum advantage benchmarking.

Bruno Cavalar, Eli Goldin, Matthew Gray, Taiga Hiroka, Min-Hsiu Hsieh, Tomoyuki Morimae2026-05-15
⚛️ quantum physics

DeepQuantum: A PyTorch-based Software Platform for Quantum Machine Learning and Photonic Quantum Computing

DeepQuantum is an open-source, PyTorch-based software platform that uniquely integrates quantum circuits, photonic quantum circuits, and measurement-based quantum computing to enable efficient hybrid quantum-classical modeling, large-scale tensor network simulations, and robust algorithm design for both photonic quantum computing and quantum machine learning.

Jun-Jie He, Ke-Ming Hu, Yu-Ze Zhu, Guan-Ju Yan, Shu-Yi Liang, Xiang Zhao, Ding Wang, Fei-Xiang Guo, Ze-Feng Lan, Xiao-We (…)2026-05-15
🔬 mesoscale physics

Coupled-wire construction of non-Abelian higher-order topological phases

This paper proposes a coupled-wire construction for non-Abelian higher-order topological phases, demonstrating a minimal model of a non-Abelian second-order topological insulator where hybridized corner states are protected by a unified topological vector combining non-Abelian quaternion charges and Abelian winding numbers, thereby bridging distinct topological classes and suggesting experimental realizations in synthetic quantum systems.

Jiaxin Pan, Longwen Zhou2026-05-15
⚛️ quantum physics

A Framework for Spatial Quantum Sensing

This paper introduces a framework for spatial quantum sensing that utilizes algebraic geometry to establish conditions for error-free field estimation via sensor placement, demonstrates that non-local entangled protocols achieve maximal precision under global resource constraints, and proposes error-free subspaces to reduce sensor requirements by leveraging prior knowledge of the field.

Luís Bugalho, Yasser Omar, Damian Markham2026-05-15
⚛️ quantum physics

A QPINN Framework with Quantum Trainable Embeddings for the Lid-Driven Cavity Problem

This paper proposes a Quantum Physics-Informed Neural Network (QPINN) framework utilizing quantum trainable embeddings to solve the lid-driven cavity problem, demonstrating that this approach achieves stable training and competitive accuracy with significantly fewer parameters than classical PINNs, thereby highlighting the potential of trainable quantum embeddings for parameter-efficient physics-informed learning.

Nahid Binandeh Dehaghani, Ban Q. Tran, Susan Mengel, Rafal Wisniewski, A. Pedro Aguiar2026-05-15
⚛️ quantum physics

Universal Spin Squeezing Dynamical Phase Transitions across Lattice Geometries, Dimensions, and Microscopic Couplings

This paper establishes the universality of a dynamical spin squeezing phase transition across diverse lattice geometries and interaction couplings, identifying a new non-equilibrium universality class with critical scaling that persists in both long-range and short-range regimes and offers a versatile route for controlling entanglement in quantum platforms.

Arman Duha, Thomas Bilitewski2026-05-15