Expertini Research Research

Browse Research Papers

28,154+ open-access research outputs.

โœ• Clear
๐Ÿ” avoidance learning ๐Ÿ“‚ Physics
Showing 28154 results for "avoidance learning" in Physics
Physics Preprint PDF DOI

Calculating trace distances of bosonic states in Krylov subspace

Javier Martinez-Cifuentes, Nicolas Quesada ยท 2026

Continuous-variable quantum systems are central to quantum technologies, with Gaussian states playing a key role due to their broad applicability and simple description via first and second moments. Dโ€ฆ

Read Paper โ†’
Physics Preprint PDF DOI

Ansatz-Free Learning of Lindbladian Dynamics In Situ

Petr Ivashkov, Nikita Romanov, Weiyuan Gong, Andi Gu, Hong-Ye Hu, Susanne F. Yelin ยท 2026

Characterizing the dynamics of open quantum systems at the level of microscopic interactions and error mechanisms is essential for calibrating quantum hardware, designing robust simulation protocols, โ€ฆ

Read Paper โ†’
Physics Preprint PDF DOI

Local strategies are pretty good at computing Boolean properties of quantum sequences

Tathagata Gupta, Ankith Mohan, Shayeef Murshid, Vincent Russo, Jamie Sikora, Alice Zheng ยท 2026

Quantum memory is a scarce and costly resource, yet little is known about which learning tasks remain feasible under severe memory constraints. We study the problem of computing global properties of qโ€ฆ

Read Paper โ†’
Physics Preprint PDF DOI

Extreme Quantum Cognition Machines for Deliberative Decision Making

Francesco Romeo, Jacopo Settino ยท 2026

We introduce Extreme Quantum Cognition Machines, a class of quantum learning architectures for deliberative decision making that is tolerant to noisy and contradictory training data. Inspired by the qโ€ฆ

Read Paper โ†’
Physics Preprint PDF DOI

SpiderCat: Optimal Fault-Tolerant Cat State Preparation

Andrey Boris Khesin, Sarah Meng Li, Boldizsar Poor, Benjamin Rodatz, John van de Wetering, Richie Yeung ยท 2026

The ability to fault-tolerantly prepare CAT states, also known as multi-qubit GHZ states, is an important primitive for quantum error correction. It is required for Shor-style syndrome extraction, andโ€ฆ

Read Paper โ†’
Physics Preprint PDF DOI

Automated High-Throughput Screening of Polymers Using a Computational Workflow

Lois Smith, Samuel Ericson, Vittoria Fantauzzo, Chin Yong, Paola Carbone, Alessandro Troisi ยท 2026

High-throughput computational screening of polymers offers a powerful way to address the imbalance between the vast number of polymers synthesised for diverse applications and the relatively small subโ€ฆ

Read Paper โ†’
Physics Preprint PDF DOI

A Shift-Invariant Deep Learning Framework for Automated Analysis of XPS Spectra

Issa Saddiq, Yuxin Fan, Robert G. Palgrave, Mark A. Isaacs, David Morgan, Keith T. Butler ยท 2026

X-ray Photoelectron Spectroscopy (XPS) is a crucial technique for material surface analysis, yet interpreting its spectra is often challenging for both human analysts and automated methods due to the โ€ฆ

Read Paper โ†’
Physics Preprint PDF DOI

UK White Paper on Magnetohydrodynamic (MHD) seismology of solar and heliospheric plasmas

Valery M. Nakariakov, David B. Jess, Andrew N. Wright, Timothy K. Yeoman, Thomas Elsden, James A. McLaughlin, Dmitrii Y. Kolotkov, Viktor Fedun, Robertus Erdelyi ยท 2026

Magnetohydrodynamic (MHD) seismology uses naturally occurring MHD waves to infer plasma properties that are otherwise hard to measure, especially magnetic field strength and topology, electric currentโ€ฆ

Read Paper โ†’
Physics Preprint PDF DOI

EMU/GAMA: A statistical perspective on active galactic nuclei diagnostics

J. Prathap, A. M. Hopkins, R. Carvajal, M. Cowley, S. M. Croom, D. Farrah, I. Prandoni, S. S. Shabala, J. Th. van Loon, C. Pappalardo, K. A. Pimbblet, U. T. Ahmed, M. Bilicki, M. J. I. Brown, D. Leahy, A. Mailvaganam, J. R. Marvil, T. Mukherjee, S. F. Rahman, T. Vernstrom, J. Willingham, T. Zafar ยท 2026

While it is well known that galaxies are composites of many emission processes, quantifying the various contributions remains challenging. In this work, we use unsupervised machine learning based clusโ€ฆ

Read Paper โ†’
Physics Preprint PDF DOI

Multi-fidelity Machine Learning Interatomic Potentials for Charged Point Defects

Xinwei Wang, Irea Mosquera-Lois, Aron Walsh ยท 2026

Machine learning interatomic potentials (MLIPs) can now reproduce the energy, forces and stresses of bulk materials with high accuracy compared to first-principles calculations. The description of impโ€ฆ

Read Paper โ†’
Physics Preprint PDF DOI

Machine Learning the Strong Disorder Renormalization Group Method for Disordered Quantum Spin Chains

A. Ustyuzhanin, J. Vahedi, S. Kettemann ยท 2026

We train machine learning algorithms to infer the entanglement structure of disordered long-range interacting quantum spin chains by learning from the strong disorder renormalisation group (SDRG) methโ€ฆ

Read Paper โ†’
Physics Preprint PDF DOI

Simultaneous Misalignment and Mode Mismatch Sensing in Optical Cavities Using Intensity-Only Measurements

Liu Tao, Eleonora Capocasa, Yuhang Zhao, Jacques Ding, Isander Ahrend, Matteo Barsuglia ยท 2026

Precise sensing and control of spatial mode content is essential for the performance of precision optical systems, particularly interferometric gravitational-wave detectors, where misalignment and modโ€ฆ

Read Paper โ†’
Physics Preprint PDF DOI

Bayesian Learning of (n,p) Reaction Cross Sections with Quantified Uncertainties

Arunabha Saha, Songshaptak De ยท 2026

Accurate modeling of neutron-induced (n,p) reaction cross sections is essential for diverse applications in nuclear physics, including reactor design, nuclear astrophysics, and radionuclide productionโ€ฆ

Read Paper โ†’
Physics Preprint PDF DOI

Predicting Atomistic Transitions with Transformers

Henry Tischler, Wenting Li, Qi Tang, Danny Perez, Thomas Vogel ยท 2026

Accurate knowledge of the atomistic transition pathways in materials and material surfaces is crucial for many material science problems. However, conventional simulation techniques used to find theseโ€ฆ

Read Paper โ†’
Physics Preprint PDF DOI

Revealing the Topology invariance of vectorial vortex beam in complex media

Shuailing Wang, Jingping Xu, Yaping Yang ยท 2026

Orbital angular momentum (OAM), a topological degree of freedom of light, is theoretically invariant under continuous deformations; yet, its physical observability degrades precipitously in complex meโ€ฆ

Read Paper โ†’
Physics Preprint PDF DOI

VarP-GP: cost-efficient Bayesian emulation of quark-gluon plasma modeling with variable statistical precision

R. Ehlers, Y. Ji, P. M. Jacobs, S. Mak ยท 2026

We present VarP-GP, a new cost-efficient Bayesian emulator for expensive computational models with variable statistical precision. We focus on the interpretation of measurements of the quark-gluon plaโ€ฆ

Read Paper โ†’
Physics Preprint PDF DOI

Unified Probe of Quantum Chaos and Ergodicity from Hamiltonian Learning

Nik O. Gjonbalaj, Christian Kokail, Susanne F. Yelin, Soonwon Choi ยท 2026

Developing measures of quantum ergodicity and chaos stands as a foundational task in the study of quantum many-body systems. In this work, we propose metrics for these effects based on Hamiltonian leaโ€ฆ

Read Paper โ†’
Physics Preprint PDF DOI

A Broker Integrated Algorithm for Gravitational Wave - Electromagnetic Counterpart Searches in O4a and O4b Runs

Hemanth Bommireddy, Francisco Forster, Isaac McMahon, Manuel Pavez Herrera, Regis Cartier, Felipe Olivares Estay, Lorena Hernandez Garcia, Mary Loli Martinez Aldama, Alejandra Munoz Arancibia ยท 2026

We present an automated framework to search for optical counterparts of LIGO-Virgo-KAGRA (LVK) gravitational wave (GW) superevents using public Zwicky Transient Facility (ZTF) alerts processed throughโ€ฆ

Read Paper โ†’
Physics Preprint PDF DOI

OptiQKD: A Machine Learning-Optimized Framework for Real-Time Parameter Tuning in Quantum Key Distribution

Noureldin Mohamed, Jawaher Kaldari, Saif Al-Kuwari ยท 2026

Despite the robust security guarantees of Quantum Key Distribution (QKD), its practical deployment is significantly challenged by the dynamic nature of quantum channels and the complexity of real-timeโ€ฆ

Read Paper โ†’
Physics Preprint PDF DOI

Achieving Optimal-Distance Atom-Loss Correction via Pauli Envelope

Pengyu Liu, Shi Jie Samuel Tan, Eric Huang, Umut A. Acar, Hengyun Zhou, Chen Zhao ยท 2026

Atom loss is a major error source in neutral-atom quantum computers, accounting for over 40% of the total physical errors in recent experiments. Its nonlinear and correlated nature poses significant cโ€ฆ

Read Paper โ†’
โ† Prev Page 42 of 1408 Next โ†’