Colloquium : Machine learning in nuclear physics

Search for Majorana neutrinos exploiting millikelvin cryogenics with CUORE

(2022) et al.   NATURE

Constructing approximate shell-model wavefunctions by eigenvector continuation

(2022) Sota Yoshida et al.   Progress of Theoretical and Experimental Physics

Fabrication, characterization and analysis of a prototype high purity germanium detector for Ge-based neutrinoless double beta decay experiments

(2021) A. Jany et al.   EUROPEAN PHYSICAL JOURNAL C

Estimation of Thermodynamic Observables in Lattice Field Theories with Deep Generative Models

(2021) Kim A. Nicoli et al.   PHYSICAL REVIEW LETTERS

Multiobjective optimization of the dynamic aperture using surrogate models based on artificial neural networks

(2021) M. Kranjčević et al.   Physical Review Accelerators and Beams

Designing optimal experiments: an application to proton Compton scattering

(2021) J. A. Melendez et al.   EUROPEAN PHYSICAL JOURNAL A

Nuclear binding energy predictions using neural networks: Application of the multilayer perceptron

(2021) Esra Yüksel et al.   INTERNATIONAL JOURNAL OF MODERN PHYSICS E

Δ-machine learning for potential energy surfaces: A PIP approach to bring a DFT-based PES to CCSD(T) level of theory

(2021) Apurba Nandi et al.   JOURNAL OF CHEMICAL PHYSICS

Accelerating coupled cluster calculations with nonlinear dynamics and supervised machine learning

(2021) Valay Agarawal et al.   JOURNAL OF CHEMICAL PHYSICS

Identifying heavy-flavor jets using vectors of locally aggregated descriptors

(2021) J. Bielčíková et al.   Journal of Instrumentation

Combining Electromagnetic and Gravitational-Wave Constraints on Neutron-Star Masses and Radii

(2021) Mohammad Al-Mamun et al.   PHYSICAL REVIEW LETTERS

Direct measurements of neutrino mass

(2021) Joseph A. Formaggio et al.   PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS

Accurate and confident prediction of electron beam longitudinal properties using spectral virtual diagnostics

(2021) A. Hanuka et al.   Scientific Reports

Neural-network analysis of Parton Distribution Functions from Ioffe-time pseudodistributions

(2021) Luigi Del Debbio et al.   JOURNAL OF HIGH ENERGY PHYSICS

Bayesian inference on the isospin splitting of nucleon effective mass from giant resonances in Pb208

(2021) Z. Zhang et al.   Chinese Physics C

A.I. for nuclear physics

(2021) Paulo Bedaque et al.   EUROPEAN PHYSICAL JOURNAL A

The identification of -clustered doorway states in Ti using machine learning

(2021) Sam Bailey et al.   EUROPEAN PHYSICAL JOURNAL A

Development, characterisation, and deployment of the SNO+ liquid scintillator

(2021) M.R. Anderson et al.   Journal of Instrumentation

Extrapolating from neural network models: a cautionary tale

(2021) Alessandro Pastore et al.   JOURNAL OF PHYSICS G-NUCLEAR AND PARTICLE PHYSICS

Get on the BAND wagon: A Bayesian framework for quantifying model uncertainties in nuclear dynamics

(2021) Daniel R Phillips et al.   JOURNAL OF PHYSICS G-NUCLEAR AND PARTICLE PHYSICS

Modified empirical formulas and machine learning for α-decay systematics

(2021) G Saxena et al.   JOURNAL OF PHYSICS G-NUCLEAR AND PARTICLE PHYSICS

The description of giant dipole resonance key parameters with multitask neural networks

(2021) J.H. Bai et al.   PHYSICS LETTERS B

Deep learning jet modifications in heavy-ion collisions

(2021) Yi-Lun Du et al.   JOURNAL OF HIGH ENERGY PHYSICS

Extensive studies of the neutron star equation of state from the deep learning inference with the observational data augmentation

(2021) Yuki Fujimoto et al.   JOURNAL OF HIGH ENERGY PHYSICS

A comparison of Gaussian processes and neural networks for computer model emulation and calibration

(2021) Samuel Myren et al.   Statistical Analysis and Data Mining

A New Mass Model for Nuclear Astrophysics: Crossing 200 keV Accuracy

(2021) Matthew Shelley et al.   Universe

Bayesian Nonparametric Inference of the Neutron Star Equation of State via a Neural Network

(2021) Ming-Zhe Han et al.   ASTROPHYSICAL JOURNAL

Classifying Near-Threshold Enhancement Using Deep Neural Network

(2021) Denny Lane B. Sombillo et al.   FEW-BODY SYSTEMS

Does Bayesian model averaging improve polynomial extrapolations? Two toy problems as tests

(2021) M A Connell et al.   JOURNAL OF PHYSICS G-NUCLEAR AND PARTICLE PHYSICS

Morphology of three-body quantum states from machine learning

(2021) David Huber et al.   NEW JOURNAL OF PHYSICS

Unsupervised learning for identifying events in active target experiments

(2021) R. Solli et al.   NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT

Vertex and energy reconstruction in JUNO with machine learning methods

(2021) Zhen Qian et al.   NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT

Variational Monte Carlo Calculations of A≤4 Nuclei with an Artificial Neural-Network Correlator Ansatz

(2021) Corey Adams et al.   PHYSICAL REVIEW LETTERS

Nuclear masses in extended kernel ridge regression with odd-even effects

(2021) X.H. Wu et al.   PHYSICS LETTERS B

Bayesian analysis of multimessenger M-R data with interpolated hybrid EoS

(2021) A. Ayriyan et al.   EUROPEAN PHYSICAL JOURNAL A

Nuclei with Up to $$\varvec{A=6}$$ Nucleons with Artificial Neural Network Wave Functions

(2021) Alex Gnech et al.   FEW-BODY SYSTEMS

Precision mass measurement of lightweight self-conjugate nucleus 80Zr

(2021) A. Hamaker et al.   Nature Physics

Classical and machine learning methods for event reconstruction in NeuLAND

(2021) Jan Mayer et al.   NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT

Reconstructing the kinematics of deep inelastic scattering with deep learning

(2021) Miguel Arratia et al.   NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT

Machine learning the nuclear mass

(2021) Ze-Peng Gao et al.   Nuclear Science and Techniques

Astrophysical Constraints on the Symmetry Energy and the Neutron Skin of Pb208 with Minimal Modeling Assumptions

(2021) Reed Essick et al.   PHYSICAL REVIEW LETTERS

Toward emulating nuclear reactions using eigenvector continuation

(2021) C. Drischler et al.   PHYSICS LETTERS B

Fast & accurate emulation of two-body scattering observables without wave functions

(2021) J.A. Melendez et al.   PHYSICS LETTERS B

Isotopic cross-sections in proton induced spallation reactions based on the Bayesian neural network method

(2020) Chun-Wang Ma et al.   Chinese Physics C

Extremum seeking for optimal control problems with unknown time‐varying systems and unknown objective functions

(2020) Alexander Scheinker et al.   INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING

A tagger for strange jets based on tracking information using long short-term memory

(2020) J. Erdmann   Journal of Instrumentation

Machine learning for imaging Cherenkov detectors

(2020) C. Fanelli   Journal of Instrumentation

$S$-factor and scattering-parameter extractions from $\het +\hef \rightarrow \bes + \gamma$

(2020) Xilin Zhang et al.   JOURNAL OF PHYSICS G-NUCLEAR AND PARTICLE PHYSICS

Cyclotron radiation emission spectroscopy signal classification with machine learning in project 8

(2020) A Ashtari Esfahani et al.   NEW JOURNAL OF PHYSICS

Analyzing the Nuclear Interaction: Challenges and New Ideas

(2020) Andreas Ekström   Frontiers in Physics

Theia: an advanced optical neutrino detector

(2020) M. Askins et al.   EUROPEAN PHYSICAL JOURNAL C

AI-optimized detector design for the future Electron-Ion Collider: the dual-radiator RICH case

(2020) E. Cisbani et al.   Journal of Instrumentation

Using machine learning to separate hadronic and electromagnetic interactions in the GlueX forward calorimeter

(2020) R. Barsotti et al.   Journal of Instrumentation

Calibration of energy density functionals with deformed nuclei

(2020) Nicolas Schunck et al.   JOURNAL OF PHYSICS G-NUCLEAR AND PARTICLE PHYSICS

Trees and Forests in Nuclear Physics

(2020) Marco Carnini et al.   JOURNAL OF PHYSICS G-NUCLEAR AND PARTICLE PHYSICS

Statistical aspects of nuclear mass models

(2020) Vojtech Kejzlar et al.   JOURNAL OF PHYSICS G-NUCLEAR AND PARTICLE PHYSICS

Bayesian Optimization of a Free-Electron Laser

(2020) J. Duris et al.   PHYSICAL REVIEW LETTERS

Taming Nuclear Complexity with a Committee of Multilayer Neural Networks

(2020) Raphaël-David Lasseri et al.   PHYSICAL REVIEW LETTERS

Online multi-objective particle accelerator optimization of the AWAKE electron beam line for simultaneous emittance and orbit control

(2020) Alexander Scheinker et al.   AIP Advances

Neural Canonical Transformation with Symplectic Flows

(2020) Shuo-Hui Li et al.   Physical Review X

Machine learning for orders of magnitude speedup in multiobjective optimization of particle accelerator systems

(2020) Auralee Edelen et al.   Physical Review Accelerators and Beams

Completing density functional theory by machine learning hidden messages from molecules

(2020) Ryo Nagai et al.   npj Computational Materials

Basic Reinforcement Learning Techniques to Control the Intensity of a Seeded Free-Electron Laser

(2020) Niky Bruchon et al.   Electronics

Stringent constraints on neutron-star radii from multimessenger observations and nuclear theory

(2020) Collin D. Capano et al.   Nature Astronomy

Covariant Density Functional Theory in Nuclear Physics and Astrophysics

(2020) Junjie Yang et al.   Annual Review of Nuclear and Particle Science

Identifying the nature of the QCD transition in relativistic collision of heavy nuclei with deep learning

(2020) Yi-Lun Du et al.   EUROPEAN PHYSICAL JOURNAL C

A Bayesian Analysis of Nuclear Deformation Properties with Skyrme Energy Functionals

(2020) Nicolas Schunck et al.   JOURNAL OF PHYSICS G-NUCLEAR AND PARTICLE PHYSICS

Quantifying uncertainties on fission fragment mass yields with mixture density networks

(2020) Amy Lovell et al.   JOURNAL OF PHYSICS G-NUCLEAR AND PARTICLE PHYSICS

Adaptive model tuning studies for non-invasive diagnostics and feedback control of plasma wakefield acceleration at FACET-II

(2020) Alexander Scheinker et al.   NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT

Efficient machine learning approach for optimizing the timing resolution of a high purity germanium detector

(2020) R.W. Gladen et al.   NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT

Reconstruction of D0 meson in d+Au collisions at $\sqrts}_{{NN$ = 200 GeV by the STAR experiment

(2020) Lukáš Kramárik for the STAR collabor   PHYSICA SCRIPTA

Deep Learning the Hohenberg-Kohn Maps of Density Functional Theory

(2020) Javier Robledo Moreno et al.   PHYSICAL REVIEW LETTERS

Bayesian analysis on interactions of exotic nuclear systems

(2020) L. Yang et al.   PHYSICS LETTERS B

ML-assisted versatile approach to Calorimeter R&D

(2020) A. Boldyrev et al.   Journal of Instrumentation

Recent advances in the quantification of uncertainties in reaction theory

(2020) Amy Lovell et al.   JOURNAL OF PHYSICS G-NUCLEAR AND PARTICLE PHYSICS

Application of artificial intelligence in the determination of impact parameter in heavy-ion collisions at intermediate energies

(2020) Fupeng Li et al.   JOURNAL OF PHYSICS G-NUCLEAR AND PARTICLE PHYSICS

Enhancing nuclear data validation analysis by using machine learning

(2020) D. Neudecker et al.   NUCLEAR DATA SHEETS

Evaluating 239Pu(n,f) cross sections via machine learning using experimental data, covariances, and measurement features

(2020) B. Whewell et al.   NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT

Equivariant Flow-Based Sampling for Lattice Gauge Theory

(2020) Gurtej Kanwar et al.   PHYSICAL REVIEW LETTERS

Efficient emulators for scattering using eigenvector continuation

(2020) R.J. Furnstahl et al.   PHYSICS LETTERS B

Machine learning the deuteron

(2020) J.W.T. Keeble et al.   PHYSICS LETTERS B

Complex-valued neural networks for machine learning on non-stationary physical data

(2020) Jesper Sören Dramsch et al.   COMPUTERS & GEOSCIENCES

Jet flavour classification using DeepJet

(2020) E. Bols et al.   Journal of Instrumentation

Bayesian inference of the incompressibility, skewness and kurtosis of nuclear matter from empirical pressures in relativistic heavy-ion collisions

(2020) Wen-Jie Xie et al.   JOURNAL OF PHYSICS G-NUCLEAR AND PARTICLE PHYSICS

Optimization and supervised machine learning methods for fitting numerical physics models without derivatives

(2020) Raghu Bollapragada et al.   JOURNAL OF PHYSICS G-NUCLEAR AND PARTICLE PHYSICS

Revisiting Bayesian constraints on the transport coefficients of QCD

(2020) Jean-François Paquet   NUCLEAR PHYSICS A

Final Results of GERDA on the Search for Neutrinoless Double- β Decay

(2020) M. Agostini et al.   PHYSICAL REVIEW LETTERS

A fast centrality-meter for heavy-ion collisions at the CBM experiment

(2020) Manjunath Omana Kuttan et al.   PHYSICS LETTERS B

Automation and control of laser wakefield accelerators using Bayesian optimization

(2020) R. J. Shalloo et al.   Nature Communications

Policy gradient methods for free-electron laser and terahertz source optimization and stabilization at the FERMI free-electron laser at Elettra

(2020) F. H. O’Shea et al.   Physical Review Accelerators and Beams

Superconducting radio-frequency cavity fault classification using machine learning at Jefferson Laboratory

(2020) Chris Tennant et al.   Physical Review Accelerators and Beams

Sample-efficient reinforcement learning for CERN accelerator control

(2020) Verena Kain et al.   Physical Review Accelerators and Beams

Cherenkov detectors fast simulation using neural networks

(2019) Denis Derkach et al.   NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT

Reinforcement learning based schemes to manage client activities in large distributed control systems

(2019) Y. Gao et al.   Physical Review Accelerators and Beams

Bayesian approach for linear optics correction

(2019) Yongjun Li et al.   Physical Review Accelerators and Beams

Accurate molecular polarizabilities with coupled cluster theory and machine learning

(2019) David M. Wilkins et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

A high-bias, low-variance introduction to Machine Learning for physicists

(2019) Pankaj Mehta et al.   PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS

Neutron Drip Line in the Ca Region from Bayesian Model Averaging

(2019) Léo Neufcourt et al.   PHYSICAL REVIEW LETTERS

Probing heavy ion collisions using quark and gluon jet substructure with machine learning

(2019) Yang-Ting Chien   NUCLEAR PHYSICS A

Convolutional neural network-based method for real-time orientation indexing of measured electron backscatter diffraction patterns

(2019) Yu-Feng Shen et al.   ACTA MATERIALIA

Deep learning based pulse shape discrimination for germanium detectors

(2019) P. Holl et al.   EUROPEAN PHYSICAL JOURNAL C

Parallel general purpose multiobjective optimization framework with application to electron beam dynamics

(2019) N. Neveu et al.   Physical Review Accelerators and Beams

Alpha half-lives calculation of superheavy nuclei with Qα-values predictions based on Bayesian neural network approach

(2019) Ubaldo Baños Rodríguez et al.   JOURNAL OF PHYSICS G-NUCLEAR AND PARTICLE PHYSICS

Bayesian optimization in ab initio nuclear physics

(2019) A Ekström et al.   JOURNAL OF PHYSICS G-NUCLEAR AND PARTICLE PHYSICS

Unsupervised word embeddings capture latent knowledge from materials science literature

(2019) Vahe Tshitoyan et al.   NATURE

Analyzing nuclear reactor simulation data and uncertainty with the Group Method of Data Handling

(2019) Majdi I. Radaideh et al.   Nuclear Engineering and Technology

Bayesian Extraction of Jet Energy Loss Distributions in Heavy-Ion Collisions

(2019) Yayun He et al.   PHYSICAL REVIEW LETTERS

Direct Comparison between Bayesian and Frequentist Uncertainty Quantification for Nuclear Reactions

(2019) G. B. King et al.   PHYSICAL REVIEW LETTERS

Reconstructing parton distribution functions from Ioffe time data: from Bayesian methods to neural networks

(2019) Joseph Karpie et al.   JOURNAL OF HIGH ENERGY PHYSICS

Neutrinoless Double-Beta Decay: Status and Prospects

(2019) Michelle J. Dolinski et al.   Annual Review of Nuclear and Particle Science

Bayesian estimation of the specific shear and bulk viscosity of quark–gluon plasma

(2019) Jonah E. Bernhard et al.   Nature Physics

Bayesian Evaluation of Incomplete Fission Yields

(2019) Zi-Ao Wang et al.   PHYSICAL REVIEW LETTERS

Probing Majorana neutrinos with double-β decay

(2019) M. Agostini et al.   SCIENCE

Model-independent tuning for maximizing free electron laser pulse energy

(2019) Alexander Scheinker et al.   Physical Review Accelerators and Beams

Bayesian modeling of the nuclear equation of state for neutron star tidal deformabilities and GW170817

(2019) Y. Lim et al.   EUROPEAN PHYSICAL JOURNAL A

Machine learning methods for track classification in the AT-TPC

(2019) M.P. Kuchera et al.   NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT

Search for Neutrinoless Double- β Decay with the Complete EXO-200 Dataset

(2019) G. Anton et al.   PHYSICAL REVIEW LETTERS

Suppression of cosmic muon spallation backgrounds in liquid scintillator detectors using convolutional neural networks

(2019) A. Li et al.   NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT

Electromagnetic showers beyond shower shapes

(2019) Luke de Oliveira et al.   NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT

Predicting particle accelerator failures using binary classifiers

(2019) Miha Rescic et al.   NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT

Estimation of fusion reaction cross-sections by artificial neural networks

(2019) Serkan Akkoyun   NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION B-BEAM INTERACTIONS WITH MATERIALS AND ATOMS

Global Sensitivity Analysis of Bulk Properties of an Atomic Nucleus

(2019) Andreas Ekström et al.   PHYSICAL REVIEW LETTERS

Constraining the symmetry energy with heavy-ion collisions and Bayesian analyses

(2019) P. Morfouace et al.   PHYSICS LETTERS B

Machine learning and the physical sciences

(2019) Giuseppe Carleo et al.   REVIEWS OF MODERN PHYSICS

A machine learning study to identify spinodal clumping in high energy nuclear collisions

(2019) Jan Steinheimer et al.   JOURNAL OF HIGH ENERGY PHYSICS

NLO PDFs from the ABMP16 fit

(2018) S. Alekhin et al.   EUROPEAN PHYSICAL JOURNAL C

Neutrinoless double beta decay with 82SeF6 and direct ion imaging

(2018) D.R. Nygren et al.   Journal of Instrumentation

Making the Coupled Cluster Correlation Energy Machine-Learnable

(2018) Johannes T Margraf et al.   JOURNAL OF PHYSICAL CHEMISTRY A

Method to Solve Quantum Few-Body Problems with Artificial Neural Networks

(2018) Hiroki Saito   JOURNAL OF THE PHYSICAL SOCIETY OF JAPAN

ENDF/B-VIII.0: The 8 th Major Release of the Nuclear Reaction Data Library with CIELO-project Cross Sections, New Standards and Thermal Scattering Data

(2018) D.A. Brown et al.   NUCLEAR DATA SHEETS

Experimental test of an online ion-optics optimizer

(2018) A.M. Amthor et al.   NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT

Novel particle tracking algorithm based on the Random Sample Consensus Model for the Active Target Time Projection Chamber (AT-TPC)

(2018) Yassid Ayyad et al.   NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT

First Monte Carlo Global Analysis of Nucleon Transversity with Lattice QCD Constraints

(2018) H.-W. Lin et al.   PHYSICAL REVIEW LETTERS

Eigenvector Continuation with Subspace Learning

(2018) Dillon Frame et al.   PHYSICAL REVIEW LETTERS

Nuclear mass predictions based on Bayesian neural network approach with pairing and shell effects

(2018) Z.M. Niu et al.   PHYSICS LETTERS B

An automated isotope identification and quantification algorithm for isotope mixtures in low-resolution gamma-ray spectra

(2018) Mark Kamuda et al.   RADIATION PHYSICS AND CHEMISTRY

An equation-of-state-meter of quantum chromodynamics transition from deep learning

(2018) Long-Gang Pang et al.   Nature Communications

Genetic algorithm enhanced by machine learning in dynamic aperture optimization

(2018) Yongjun Li et al.   Physical Review Accelerators and Beams

Automatic trajectory recognition in Active Target Time Projection Chambers data by means of hierarchical clustering

(2018) Christoph Dalitz et al.   COMPUTER PHYSICS COMMUNICATIONS

Machine learning n/γ discrimination in CLYC scintillators

(2018) E. Doucet et al.   NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT

Demonstration of Model-Independent Control of the Longitudinal Phase Space of Electron Beams in the Linac-Coherent Light Source with Femtosecond Resolution

(2018) Alexander Scheinker et al.   PHYSICAL REVIEW LETTERS

Deep Learning and Its Application to LHC Physics

(2018) Dan Guest et al.   Annual Review of Nuclear and Particle Science

Exploring Bayesian parameter estimation for chiral effective field theory using nucleon-nucleon phase shifts

(2018) Sarah Wesolowski et al.   JOURNAL OF PHYSICS G-NUCLEAR AND PARTICLE PHYSICS

A comparison of machine learning methods for automated gamma-ray spectroscopy

(2018) Mark Kamuda et al.   NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT

A neural network approach for identification of gamma-ray spectrum obtained from silicon photomultipliers

(2018) Seungho Jhung et al.   NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT

Fermions at Finite Density in 2+1 Dimensions with Sign-Optimized Manifolds

(2018) Andrei Alexandru et al.   PHYSICAL REVIEW LETTERS

A simple approach towards the sign problem using path optimisation

(2018) Francis Bursa et al.   JOURNAL OF HIGH ENERGY PHYSICS

Machine learning-based longitudinal phase space prediction of particle accelerators

(2018) C. Emma et al.   Physical Review Accelerators and Beams

Automated Isotope Identification Algorithm Using Artificial Neural Networks

(2017) M. Kamuda et al.   IEEE TRANSACTIONS ON NUCLEAR SCIENCE

Background rejection in NEXT using deep neural networks

(2017) J. Renner et al.   Journal of Instrumentation

First Simultaneous Extraction of Spin-Dependent Parton Distributions and Fragmentation Functions from a Global QCD Analysis

(2017) J. J. Ethier et al.   PHYSICAL REVIEW LETTERS

Deep learning in color: towards automated quark/gluon jet discrimination

(2017) Patrick T. Komiske et al.   JOURNAL OF HIGH ENERGY PHYSICS

Pileup Mitigation with Machine Learning (PUMML)

(2017) Patrick T. Komiske et al.   JOURNAL OF HIGH ENERGY PHYSICS

Neutron star mass and radius measurements from atmospheric model fits to X-ray burst cooling tail spectra

(2017) J. Nättilä et al.   ASTRONOMY & ASTROPHYSICS

FastDIRC: a fast Monte Carlo and reconstruction algorithm for DIRC detectors

(2016) J. Hardin et al.   Journal of Instrumentation

Nuclear charge radii: density functional theory meets Bayesian neural networks

(2016) R Utama et al.   JOURNAL OF PHYSICS G-NUCLEAR AND PARTICLE PHYSICS

First Measurement of Electron Neutrino Appearance in NOvA

(2016) P. Adamson et al.   PHYSICAL REVIEW LETTERS

Search for Majorana Neutrinos Near the Inverted Mass Hierarchy Region with KamLAND-Zen

(2016) A. Gando et al.   PHYSICAL REVIEW LETTERS

Erratum to: Monte Carlo study of Lefschetz thimble structure in one-dimensional Thirring model at finite density

(2016) Hirotsugu Fujii et al.   JOURNAL OF HIGH ENERGY PHYSICS

Signal recognition efficiencies of artificial neural-network pulse-shape discrimination in HPGe $$\varvec{0\nu \beta \beta }$$ 0 ν β β -decay searches

(2015) A. Caldwell et al.   EUROPEAN PHYSICAL JOURNAL C

Parton distributions in the LHC era: MMHT 2014 PDFs

(2015) L. A. Harland-Lang et al.   EUROPEAN PHYSICAL JOURNAL C

A Bayesian approach for parameter estimation and prediction using a computationally intensive model

(2015) Dave Higdon et al.   JOURNAL OF PHYSICS G-NUCLEAR AND PARTICLE PHYSICS

Statistical error propagation inab initiono-core full configuration calculations of light nuclei

(2015) R. Navarro Pérez et al.   PHYSICAL REVIEW C

Thimble regularization at work: From toy models to chiral random matrix theories

(2015) F. Di Renzo et al.   PHYSICAL REVIEW D

Covariant approximation averaging

(2015) Eigo Shintani et al.   PHYSICAL REVIEW D

Uncertainty Quantification for Nuclear Density Functional Theory and Information Content of New Measurements

(2015) J. D. McDonnell et al.   PHYSICAL REVIEW LETTERS

Constraining the Equation of State of Superhadronic Matter from Heavy-Ion Collisions

(2015) Scott Pratt et al.   PHYSICAL REVIEW LETTERS

Adaptive method for electron bunch profile prediction

(2015) Alexander Scheinker et al.   PHYSICAL REVIEW SPECIAL TOPICS-ACCELERATORS AND BEAMS

Halo effective field theory constrains the solar 7 Be + p → 8 B + γ rate

(2015) Xilin Zhang et al.   PHYSICS LETTERS B

Searching for Neutrinoless Double-Beta Decay of130Te with CUORE

(2015) D. R. Artusa et al.   Advances in High Energy Physics

Instantaneous stochastic perturbation theory

(2015) Martin Lüscher   JOURNAL OF HIGH ENERGY PHYSICS

Monte Carlo study of Lefschetz thimble structure in one-dimensional Thirring model at finite density

(2015) Hirotsugu Fujii et al.   JOURNAL OF HIGH ENERGY PHYSICS

Hamilton dynamics for Lefschetz-thimble integration akin to the complex Langevin method

(2015) K. Fukushima et al.   Progress of Theoretical and Experimental Physics

Uncertainties of mass extrapolations in Hartree-Fock-Bogoliubov mass models

(2014) S. Goriely et al.   PHYSICAL REVIEW C

An efficient method to compute the residual phase on a Lefschetz thimble

(2014) M. Cristoforetti et al.   PHYSICAL REVIEW D

Simultaneous optimization of the cavity heat load and trip rates in linacs using a genetic algorithm

(2014) Balša Terzić et al.   PHYSICAL REVIEW SPECIAL TOPICS-ACCELERATORS AND BEAMS

Galaxy Formation: Bayesian History Matching for the Observable Universe

(2014) Ian Vernon et al.   STATISTICAL SCIENCE

Present Status and Future Perspectives of the NEXT Experiment

(2014) J. J. Gómez Cadenas et al.   Advances in High Energy Physics

Pulse shape discrimination for Gerda Phase I data

(2013) M. Agostini et al.   EUROPEAN PHYSICAL JOURNAL C

Efficient, reliable and fast high-level triggering using a bonsai boosted decision tree

(2013) V V Gligorov et al.   Journal of Instrumentation

Maximizing the Information Content of Experiments in Systems Biology

(2013) Juliane Liepe et al.   PLoS Computational Biology

Artificial intelligence methods applied for quantitative analysis of natural radioactive sources

(2012) M.E. Medhat   ANNALS OF NUCLEAR ENERGY

New approach to the sign problem in quantum field theories: High density QCD on a Lefschetz thimble

(2012) Marco Cristoforetti et al.   PHYSICAL REVIEW D

Testing trivializing maps in the Hybrid Monte Carlo algorithm

(2011) Georg P. Engel et al.   COMPUTER PHYSICS COMMUNICATIONS

The Nuclear Science References (NSR) database and Web Retrieval System

(2011) B. Pritychenko et al.   NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT

Finding Nature’s Missing Ternary Oxide Compounds Using Machine Learning and Density Functional Theory

(2010) Geoffroy Hautier et al.   CHEMISTRY OF MATERIALS

Applying Bayesian neural networks to identify pion, kaon and proton in BESII

(2010) Xu Ye et al.   Chinese Physics C

A first unbiased global NLO determination of parton distributions and their uncertainties

(2010) Richard D. Ball et al.   NUCLEAR PHYSICS B

Critical slowing down and error analysis in lattice QCD simulations

(2010) Stefan Schaefer et al.   NUCLEAR PHYSICS B

Trivializing Maps, the Wilson Flow and the HMC Algorithm

(2009) Martin Lüscher   COMMUNICATIONS IN MATHEMATICAL PHYSICS

Decodingβ-decay systematics: A global statistical model forβ−half-lives

(2009) N. J. Costiris et al.   PHYSICAL REVIEW C

Relativistic cyclotron radiation detection of tritium decay electrons as a new technique for measuring the neutrino mass

(2009) Benjamin Monreal et al.   PHYSICAL REVIEW D

Classification of the impact parameter in nucleus–nucleus collisions by a support vector machine method

(2008) J De Sanctis et al.   JOURNAL OF PHYSICS G-NUCLEAR AND PARTICLE PHYSICS