Variational approach to quantum state tomography based on maximal entropy formalism

Rishabh Gupta, Manas Sajjan, Raphael D. Levine and Sabre Kais

Phys. Chem. Chem. Phys., 2022, 24, 28870
DOI: 10.1039/D2CP04493E

Universal neural network potentials as descriptors: towards scalable chemical property prediction using quantum and classical computers

Tomoya Shiota, Kenji Ishihara and Wataru Mizukami

Digital Discovery, 2024, 3, 1714
DOI: 10.1039/D4DD00098F

Enhancing chemistry-intuitive feature learning to improve prediction performance of optical properties

Ming Sun, Caixia Fu, Haoming Su, Ruyue Xiao, Chaojie Shi, Zhiyun Lu and Xuemei Pu

Chem. Sci., 2024, 15, 17533
DOI: 10.1039/D4SC02781G

Quantum machine learning of molecular energies with hybrid quantum-neural wavefunction

Weitang Li, Shi-Xin Zhang, Zirui Sheng, Cunxi Gong, Jianpeng Chen and Zhigang Shuai

Digital Discovery, 2025, 4, 2697
DOI: 10.1039/D5DD00222B

Applications of density functional theory and machine learning in nanomaterials: A review

Nangamso Nathaniel Nyangiwe

Next Materials, 2025, 8, 100683
DOI: 10.1016/j.nxmate.2025.100683

Quantum many-body simulations from a reinforcement-learned exponential Ansatz

Yuchen Wang and David A. Mazziotti

Phys. Rev. A, 2025, 112
DOI: 10.1103/hrgr-klw3

Maximum Entropy Methods for Quantum State Compatibility Problems

Shi‐Yao Hou, Zipeng Wu, Jinfeng Zeng, Ningping Cao, Chenfeng Cao, Youning Li and Bei Zeng

Adv Quantum Tech, 2024, 7
DOI: 10.1002/qute.202400172

Entanglement-enabled quantum kernels for enhanced feature mapping

Anand Babu, Saurabh G. Ghatnekar, Amit Saxena and Dipankar Mandal

APL Quantum, 2025, 2
DOI: 10.1063/5.0240894

FitQT: a fully integrated and trainable quantum transformer for scalable natural language processing

Phan Cong Lenh Pham and The Anh Le

Eng. Res. Express, 2026, 8, 075214
DOI: 10.1088/2631-8695/ae5507

Quantum machine learning: from physics to software engineering

Alexey Melnikov, Mohammad Kordzanganeh, Alexander Alodjants and Ray-Kuang Lee

Advances in Physics: X, 2023, 8
DOI: 10.1080/23746149.2023.2165452

A Machine Learning Approach for Modelling Cold-Rolling Curves for Various Stainless Steels

Julia Contreras-Fortes, M. Inmaculada Rodríguez-García, David L. Sales, Rocío Sánchez-Miranda, Juan F. Almagro and Ignacio Turias

Materials, 2023, 17, 147
DOI: 10.3390/ma17010147

Harvesting Chemical Understanding with Machine Learning and Quantum Computers

Shubin Liu

ACS Phys. Chem Au, 2024, 4, 135
DOI: 10.1021/acsphyschemau.3c00067

Mini Review: Synergizing Driven Quantum Dynamics, AI, and Quantum Computing for Next-Gen Materials Science

Opeyemi S. Akanbi, Jack P. Shannon, Jerome Delhommelle and Caroline Desgranges

J. Phys. Chem. Lett., 2025, 16, 11821
DOI: 10.1021/acs.jpclett.5c02390

Computational and Machine Learning Methods for CO2 Capture Using Metal–Organic Frameworks

Hossein Mashhadimoslem, Mohammad Ali Abdol, Peyman Karimi, Kourosh Zanganeh, Ahmed Shafeen, Ali Elkamel and Milad Kamkar

ACS Nano, 2024, 18, 23842
DOI: 10.1021/acsnano.3c13001

Simulation of Chemical Reactions on a Quantum Computer

Sumit Suresh Kale and Sabre Kais

J. Phys. Chem. Lett., 2024, 15, 5633
DOI: 10.1021/acs.jpclett.4c01100

Complexity of life sciences in quantum and AI era

Alexey Pyrkov, Alex Aliper, Dmitry Bezrukov, Dmitriy Podolskiy, Feng Ren and Alex Zhavoronkov

WIREs Comput Mol Sci, 2024, 14
DOI: 10.1002/wcms.1701

Quasiparticle pairing encoding of atomic nuclei for quantum annealing

Emanuele Costa, Axel Pérez-Obiol, Javier Menéndez, Arnau Rios, Artur García-Sáez and Bruno Juliá-Díaz

Physics Letters B, 2026, 872, 140042
DOI: 10.1016/j.physletb.2025.140042

Explainable chemical artificial intelligence from accurate machine learning of real-space chemical descriptors

Miguel Gallegos, Valentin Vassilev-Galindo, Igor Poltavsky, Ángel Martín Pendás and Alexandre Tkatchenko

Nat Commun, 2024, 15
DOI: 10.1038/s41467-024-48567-9

Artificial intelligence in financial market prediction: advancements in machine learning for stock price forecasting

Arafat Rohan, Md. Deluar Hossen, Md. Nuruzzaman Pranto, Balayet Hossain, Areyfin Mohammed Yoshi and Rakibul Islam

Front. Artif. Intell., 2026, 8
DOI: 10.3389/frai.2025.1696423

Leveraging graph neural networks to predict Hammett’s constants for benzoic acid derivatives

Vaneet Saini and Ranjeet Kumar

Artificial Intelligence Chemistry, 2024, 2, 100079
DOI: 10.1016/j.aichem.2024.100079

Dimensionality Reduction for Data Analysis With Quantum Feature Learning

Shyam R. Sihare

WIREs Data Min & Knowl, 2025, 15
DOI: 10.1002/widm.1568

Imaginary components of out-of-time-order correlator and information scrambling for navigating the learning landscape of a quantum machine learning model

Manas Sajjan, Vinit Singh, Raja Selvarajan and Sabre Kais

Phys. Rev. Research, 2023, 5
DOI: 10.1103/PhysRevResearch.5.013146

Machine Learning of Two-Electron Reduced Density Matrices for Many-Body Problems

Luis H. Delgado-Granados, LeeAnn M. Sager-Smith, Kristina Trifonova and David A. Mazziotti

J. Phys. Chem. Lett., 2025, 16, 2231
DOI: 10.1021/acs.jpclett.4c03366

Paradigm shifts and application frontiers in analytical chemistry: advances in machine learning-enabled colorimetric sensing

Youqin Fang, Hui Gao and Guoqiang Wang

Microchemical Journal, 2025, 217, 115053
DOI: 10.1016/j.microc.2025.115053

Iterative method to improve the precision of the quantum-phase-estimation algorithm

Junxu Li

Phys. Rev. A, 2024, 109
DOI: 10.1103/PhysRevA.109.032606

Machine learning prediction of materials properties from chemical composition: Status and prospects

Mohammad Alghadeer, Nufida D. Aisyah, Mahmoud Hezam, Saad M. Alqahtani, Ahmer A. B. Baloch and Fahhad H. Alharbi

Chemical Physics Reviews, 2024, 5
DOI: 10.1063/5.0235541

Computational Performance Bounds Prediction in Quantum Computing With Unstable Noise

Jinyang Li, Samudra Dasgupta, Yuhong Song, Lei Yang, Travis Humble and Weiwen Jiang

IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst., 2026, 45, 969
DOI: 10.1109/TCAD.2025.3592605

MatGPT: A Vane of Materials Informatics from Past, Present, to Future

Zhilong Wang, An Chen, Kehao Tao, Yanqiang Han and Jinjin Li

Advanced Materials, 2024, 36
DOI: 10.1002/adma.202306733

Machine Learning Accelerates Precise Excited-State Potential Energy Surface Calculations on a Quantum Computer

Qianjun Yao, Qun Ji, Xiaopeng Li, Yehui Zhang, Xinyu Chen, Ming-Gang Ju, Jie Liu and Jinlan Wang

J. Phys. Chem. Lett., 2024, 15, 7061
DOI: 10.1021/acs.jpclett.4c01445

Quantum-to-Classical Neural Network Transfer Learning Applied to Drug Toxicity Prediction

Anthony M. Smaldone and Victor S. Batista

J. Chem. Theory Comput., 2024, 20, 4901
DOI: 10.1021/acs.jctc.4c00432

Inter‐Hammett: Enhancing Interpretability in Hammett‘s Constant Prediction via Extracting Rules

Sadettin Y. Ugurlu

ChemistrySelect, 2025, 10
DOI: 10.1002/slct.202501778

Optimization Techniques for Asthma Exacerbation Prediction Models: A Systematic Literature Review

Dahiru Adamu Aliyu, Emelia Akashah Patah Akhir, Yahaya Saidu, Shamsuddeen Adamu, Kabir Ismail Umar, Abubakar Sadiq Bunu and Hussaini Mamman

IEEE Access, 2024, 12, 110862
DOI: 10.1109/ACCESS.2024.3440502

Random projection using random quantum circuits

Keerthi Kumaran, Manas Sajjan, Sangchul Oh and Sabre Kais

Phys. Rev. Research, 2024, 6
DOI: 10.1103/PhysRevResearch.6.013010

Analogy between Boltzmann Machines and Feynman Path Integrals

Srinivasan S. Iyengar and Sabre Kais

J. Chem. Theory Comput., 2023, 19, 2446
DOI: 10.1021/acs.jctc.3c00187

Quantum machine learning for multiclass classification beyond kernel methods

Chao Ding, Shi Wang, Yaonan Wang and Weibo Gao

Phys. Rev. A, 2025, 111
DOI: 10.1103/PhysRevA.111.062410

Quantum circuit for high order perturbation theory corrections

Junxu Li and Xingyu Gao

Sci Rep, 2024, 14
DOI: 10.1038/s41598-024-64854-3

Foray into the topology of poly‐bi‐[8]‐annulenylene

Varadharajan Muruganandam, Manas Sajjan and Sabre Kais

Natural Sciences, 2023, 3
DOI: 10.1002/ntls.20230015

Use of hybrid quantum-classical algorithms for enhancing biomarker classification

Aninda Astuti, Pin-Keng Shih, Shan-Chih Lee, Venugopala Reddy Mekala, Ezra B. Wijaya, Ka-Lok Ng and Richard Jiang

PLoS One, 2025, 20, e0327928
DOI: 10.1371/journal.pone.0327928

Enhancing variational quantum classifier performance with meta-heuristic feature selection for credit card fraud detection

Furkan Atban, Muhammed Yusuf Küçükkara and Cüneyt Bayılmış

Eur. Phys. J. Spec. Top., 2025, 234, 3705
DOI: 10.1140/epjs/s11734-025-01703-y

Quantum machine learning based wind turbine condition monitoring: State of the art and future prospects

Zhefeng Zhang, Yueqi Wu and Xiandong Ma

Energy Conversion and Management, 2025, 332, 119694
DOI: 10.1016/j.enconman.2025.119694

Mapping Molecular Hamiltonians into Hamiltonians of Modular cQED Processors

Ningyi Lyu, Alessandro Miano, Ioannis Tsioutsios, Rodrigo G. Cortiñas, Kenneth Jung, Yuchen Wang, Zixuan Hu, Eitan Geva, Sabre Kais and Victor S. Batista

J. Chem. Theory Comput., 2023, 19, 6564
DOI: 10.1021/acs.jctc.3c00620

Advancing oil-water separation: Design and efficiency of amphiphilic hyperbranched demulsifiers

Shu Yan, Pengfei Jiang, Xinghong Zhang, Yitong Dai, Bin Sun, Yongsheng Guo and Wenjun Fang

Journal of Colloid and Interface Science, 2025, 677, 583
DOI: 10.1016/j.jcis.2024.08.101

Pulse-Driven Spin Paradigm for Noise-Aware Quantum Classification

Carlos Riascos-Moreno, Andrés Marino Álvarez-Meza and German Castellanos-Dominguez

Computers, 2025, 14, 475
DOI: 10.3390/computers14110475

SERS Cheminformatics: Opportunities for Data-Driven Discovery and Applications

Emily Xi Tan, Lam Bang Thanh Nguyen, Yubin Jin, Yan Lv, In Yee Phang and Xing Yi Ling

ACS Cent. Sci., 2025, 11, 2034
DOI: 10.1021/acscentsci.5c00785

Unlocking the Potential of Quantum Machine Learning to Advance Drug Discovery

Maria Avramouli, Ilias K. Savvas, Anna Vasilaki and Georgia Garani

Electronics, 2023, 12, 2402
DOI: 10.3390/electronics12112402

Practical advantage of quantum machine learning in ghost imaging

Tailong Xiao, Xinliang Zhai, Xiaoyan Wu, Jianping Fan and Guihua Zeng

Commun Phys, 2023, 6
DOI: 10.1038/s42005-023-01290-1

Simulating Cavity-Modified Electron Transfer Dynamics on NISQ Computers

Ningyi Lyu, Pouya Khazaei, Eitan Geva and Victor S. Batista

J. Phys. Chem. Lett., 2024, 15, 9535
DOI: 10.1021/acs.jpclett.4c02220

Recent Advances in Quantum Computing for Drug Discovery and Development

Gautam Kumar, Sahil Yadav, Aniruddha Mukherjee, Vikas Hassija and Mohsen Guizani

IEEE Access, 2024, 12, 64491
DOI: 10.1109/ACCESS.2024.3376408

Physics-Inspired Quantum Simulation of Resonating Valence Bond States─A Prototypical Template for a Spin-Liquid Ground State

Manas Sajjan, Rishabh Gupta, Sumit Suresh Kale, Vinit Singh, Keerthi Kumaran and Sabre Kais

J. Phys. Chem. A, 2023, 127, 8751
DOI: 10.1021/acs.jpca.3c05172

Quantum extreme learning of molecular potential energy surfaces and force fields

Gabriele Lo Monaco, Marco Bertini, Salvatore Lorenzo and G Massimo Palma

Mach. Learn.: Sci. Technol., 2024, 5, 035014
DOI: 10.1088/2632-2153/ad6120

Survey on recent progress of AI for chemistry: methods, applications, and opportunities

Hu Ding, Pengxiang Hua and Zhen Huang

Front. Comput. Sci., 2026, 20
DOI: 10.1007/s11704-025-50127-3

Federated quanvolutional neural network: a new paradigm for collaborative quantum learning

Amandeep Singh Bhatia, Sabre Kais and Muhammad Ashraful Alam

Quantum Sci. Technol., 2023, 8, 045032
DOI: 10.1088/2058-9565/acfc61

Quantum Machine Learning in Drug Discovery: Applications in Academia and Pharmaceutical Industries

Anthony M. Smaldone, Yu Shee, Gregory W. Kyro, Chuzhi Xu, Nam P. Vu, Rishab Dutta, Marwa H. Farag, Alexey Galda, Sandeep Kumar, Elica Kyoseva and Victor S. Batista

Chem. Rev., 2025, 125, 5436
DOI: 10.1021/acs.chemrev.4c00678

Machine Learning Tackles the Challenge of Powder X-ray Diffraction Indexing for All Crystal Systems

Ke Shu, Dong-Yun Gui, Wei-Xin Yan and Chun-Hai Wang

J. Chem. Inf. Model., 2025, 65, 10025
DOI: 10.1021/acs.jcim.5c01506

Quantum Machine Learning Predicting ADME-Tox Properties in Drug Discovery

Amandeep Singh Bhatia, Mandeep Kaur Saggi and Sabre Kais

J. Chem. Inf. Model., 2023, 63, 6476
DOI: 10.1021/acs.jcim.3c01079

Chemical applications of variational quantum eigenvalue-based quantum algorithms: Perspective and survey

Dominic Alfonso, Yueh-Lin Lee, Hari P. Paudel and Yuhua Duan

Applied Physics Reviews, 2025, 12
DOI: 10.1063/5.0245874

Property-guided inverse design of metal-organic frameworks using quantum natural language processing

Shinyoung Kang and Jihan Kim

npj Comput Mater, 2025, 11
DOI: 10.1038/s41524-025-01806-z

Quantum computing and chemistry

Jared D. Weidman, Manas Sajjan, Camille Mikolas, Zachary J. Stewart, Johannes Pollanen, Sabre Kais and Angela K. Wilson

Cell Reports Physical Science, 2024, 5, 102105
DOI: 10.1016/j.xcrp.2024.102105

Variational Quantum Computing for Quantum Simulation: Principles, Implementations, and Challenges

Lucas Q. Galvão, Anna Beatriz M. de Souza, Marcelo A. Moret and Clebson Cruz

Braz J Phys, 2026, 56
DOI: 10.1007/s13538-025-01946-z

Knowledge distillation inspired variational quantum eigensolver with virtual annealing

Junxu Li

New J. Phys., 2026, 28, 024501
DOI: 10.1088/1367-2630/ae3b65

A dual-stage machine learning framework for comprehensive characterization of waste plastic pyrolysis oils

Xu Zhang, Shengji Wu, Ben Ge, Qing Zhou, Bin Yan and Zezhou Chen

Journal of Analytical and Applied Pyrolysis, 2025, 192, 107300
DOI: 10.1016/j.jaap.2025.107300

Quantum machine learning on near-term quantum devices: Current state of supervised and unsupervised techniques for real-world applications

Yaswitha Gujju, Atsushi Matsuo and Rudy Raymond

Phys. Rev. Applied, 2024, 21
DOI: 10.1103/PhysRevApplied.21.067001

Quantum‐Neural Network Model for Platform Independent Ddos Attack Classification in Cyber Security

Muhammed Yusuf Küçükkara, Furkan Atban and Cüneyt Bayılmış

Adv Quantum Tech, 2024, 7
DOI: 10.1002/qute.202400084

Hardware-efficient quantum arithmetic logic units for square lattice architectures

Junxu Li

Phys. Scr., 2026, 101, 105104
DOI: 10.1088/1402-4896/ae4b73

Permutation invariant encodings for quantum machine learning with point cloud data

Jamie Heredge, Charles Hill, Lloyd Hollenberg and Martin Sevior

Quantum Mach. Intell., 2024, 6
DOI: 10.1007/s42484-024-00156-1

The next revolution in computational simulations: Harnessing AI and quantum computing in molecular dynamics

Anna Lappala

Current Opinion in Structural Biology, 2024, 89, 102919
DOI: 10.1016/j.sbi.2024.102919

Anomaly detection speed-up by quantum restricted Boltzmann machines

Lorenzo Moro and Enrico Prati

Commun Phys, 2023, 6
DOI: 10.1038/s42005-023-01390-y

Differentiable architecture search for adversarially robust quantum computer vision

Mohamed Afane, Quanjiang Long, Haoting Shen, Ying Mao, Junaid Farooq, Ying Wang and Juntao Chen

Quantum Mach. Intell., 2026, 8
DOI: 10.1007/s42484-026-00353-0

Subsampling factorization machine annealing

Yusuke Hama and Tadashi Kadowaki

Phys. Rev. Research, 2026, 8
DOI: 10.1103/qgpq-6dmr

Construction of Chemistry-Inspired Dynamic Ansatz Utilizing Generative Machine Learning

Sonaldeep Halder, Kartikey Anand and Rahul Maitra

J. Phys. Chem. A, 2025, 129, 5889
DOI: 10.1021/acs.jpca.5c02346

Toward perturbation theory methods on a quantum computer

Junxu Li, Barbara A. Jones and Sabre Kais

Sci. Adv., 2023, 9
DOI: 10.1126/sciadv.adg4576

Accelerating Materials Discovery through Machine Learning: Predicting Crystallographic Symmetry Groups

Yousef A. Alghofaili, Mohammed Alghadeer, Abdulmohsen A. Alsaui, Saad M. Alqahtani and Fahhad H. Alharbi

J. Phys. Chem. C, 2023, 127, 16645
DOI: 10.1021/acs.jpcc.3c03274

Prepare Linear Distributions with Quantum Arithmetic Units

Junxu Li

Entropy, 2024, 26, 912
DOI: 10.3390/e26110912

A Survey on Quantum Machine Learning Applications in Medicine and Healthcare

Radosław Idzikowski, Mateusz A. Kucharski, Konrad Pempera and Michał Jaroszczuk

Applied Sciences, 2026, 16, 1630
DOI: 10.3390/app16031630

Hamiltonian Learning from Time Dynamics Using Variational Algorithms

Rishabh Gupta, Raja Selvarajan, Manas Sajjan, Raphael D. Levine and Sabre Kais

J. Phys. Chem. A, 2023, 127, 3246
DOI: 10.1021/acs.jpca.2c08993

Quantum Machine Learning for Drug Discovery: Taxonomy, Research Challenges, and the Road Ahead

Hoang Phi Yen Duong, Syed Muhammad Abuzar Rizvi, Brad McNiven, Thanh Tuan Nguyen, Hyundong Shin, Octavia Dobre and Trung Q. Duong

ACM Comput. Surv., 2026, 58, 1
DOI: 10.1145/3785660

Time Resolved Quantum Tomography in Molecular Spectroscopy by the Maximal Entropy Approach

Varun Makhija, Rishabh Gupta, Simon Neville, Michael Schuurman, Joseph Francisco and Sabre Kais

J. Phys. Chem. Lett., 2024, 15, 9525
DOI: 10.1021/acs.jpclett.4c02368

The Role of Quantum Computing in Advancing Scientific High-Performance Computing: A perspective from the ADAC Institute

Gilles Buchs, Thomas Beck, Ryan Bennink, Daniel Claudino, Andrea Delgado, Nur Aiman Fadel, Peter Groszkowski, Kathleen Hamilton, Travis Humble, Neeraj Kumar, Ang Li, Phillip Lotshaw, Olli Mukkula, Ryousei Takano, Amit Saxena, In-Saeng Suh, Miwako Tsuji, Roel Van Beeumen, Ugo Varetto, Yan Wang, Kazuya Yamazaki and Mikael P. Johansson

Future Generation Computer Systems, 2026, 108487
DOI: 10.1016/j.future.2026.108487

Machine learning for gas–solid interaction materials and devices

Peiyuan Liu, Xiaoyang Zhu, Xu Ran, Hengchang Bi, Xiao Huang and Ning Gu

Coordination Chemistry Reviews, 2025, 524, 216329
DOI: 10.1016/j.ccr.2024.216329

Predicting the ET(30) parameter of organic solvents via machine learning

Vaneet Saini and Harsh Singh

Chemical Physics Letters, 2023, 826, 140672
DOI: 10.1016/j.cplett.2023.140672

A quantum information processing machine for computing by observables

F. Remacle and R. D. Levine

Proc. Natl. Acad. Sci. U.S.A., 2023, 120
DOI: 10.1073/pnas.2220069120

Mixtures Recomposition by Neural Nets: A Multidisciplinary Overview

Andre Nicolle, Sili Deng, Matthias Ihme, Nursulu Kuzhagaliyeva, Emad Al Ibrahim and Aamir Farooq

J. Chem. Inf. Model., 2024, 64, 597
DOI: 10.1021/acs.jcim.3c01633

Deep learning molecular dynamics for large-scale insights into yttrium's structural, thermal and diffusion properties

Li Ma, Haowen Wang, Yongzhi Wu, Keyuan Chen, Haoxiang Zhang, Xingkao Zhang, Ju Rong, Yudong Sui, Xiaohua Yu and Jing Feng

Appl. Phys. A, 2025, 131
DOI: 10.1007/s00339-025-08560-5

Comprehensive Drug-Likeness Prediction Using a Pretrained Transformer Model and Multitask Learning

Yi Cai, Qian Zhang, Wenchong Tan, Jing Li, Dong Chen, Xiaoyun Lu and Hongli Du

J. Chem. Inf. Model., 2025, 65, 5370
DOI: 10.1021/acs.jcim.5c00455

Hybrid quantum-classical unsupervised data clustering based on the self-organizing feature map

I. D. Lazarev, Marek Narozniak, Tim Byrnes and A. N. Pyrkov

Phys. Rev. A, 2025, 111
DOI: 10.1103/PhysRevA.111.012416

Entanglement detection with quantum support vector machine (QSVM) on near-term quantum devices

Mahmoud Mahdian and Zahra Mousavi

Sci Rep, 2025, 15
DOI: 10.1038/s41598-025-95897-9

Properties of fermionic systems with the path-integral ground state method

Sebastian Ujevic, Vinicius Zampronio, Bruno R. de Abreu and Silvio A. Vitiello

SciPost Phys. Core, 2023, 6
DOI: 10.21468/SciPostPhysCore.6.2.031

A Hybrid Quantum-Classical Algorithm for Underwater Target Classification

Furong Wang, Fan Yang, Yixing Li, Gang Fan, Long He, Yang Liu, Yu Bai, Ya Zhang and Guo-Xing Miao

Quantum Engineering, 2023, 2023, 1
DOI: 10.1155/2023/6766820

Quantum Biosensors on Chip: A Review from Electronic and Photonic Integrated Circuits to Future Integrated Quantum Photonic Circuits

Yasaman Torabi, Shahram Shirani and James P. Reilly

Microelectronics, 2025, 1, 5
DOI: 10.3390/microelectronics1020005

Transitioning From Federated Learning to Quantum Federated Learning in Internet of Things: A Comprehensive Survey

Cheng Qiao, Mianjie Li, Yuan Liu and Zhihong Tian

IEEE Commun. Surv. Tutorials, 2025, 27, 509
DOI: 10.1109/COMST.2024.3399612

From Synthesis Conditions to UiO-66 Properties: Machine Learning Approach

Kirill P. Larionov and Vasilii Yu. Evtushok

Chem. Mater., 2024, 36, 4291
DOI: 10.1021/acs.chemmater.3c03180

Topology Meets Reactivity: Rationalizing Electron Rearrangements in Cycloadditions Through Thom’s Polynomials and Bonding Evolution Theory

Leandro Ayarde-Henríquez, Cristian J. Guerra, Hans Lenes, Elizabeth Rincón and Eduardo Chamorro

Reactions, 2026, 7, 1
DOI: 10.3390/reactions7010001

ChiGNN: Interpretable Algorithm Framework of Molecular Chiral Knowledge-Embedding and Stereosensitive Property Prediction

Jiaxin Yan, Haiyuan Wang, Wensheng Yang, Xiaonan Ma, Yajing Sun and Wenping Hu

J. Chem. Inf. Model., 2025, 65, 3239
DOI: 10.1021/acs.jcim.4c02259

Magnetic phases of spatially modulated spin-1 chains in Rydberg excitons: Classical and quantum simulations

Manas Sajjan, Hadiseh Alaeian and Sabre Kais

The Journal of Chemical Physics, 2022, 157
DOI: 10.1063/5.0128283

Quantum computing for near-term applications in generative chemistry and drug discovery

Alexey Pyrkov, Alex Aliper, Dmitry Bezrukov, Yen-Chu Lin, Daniil Polykovskiy, Petrina Kamya, Feng Ren and Alex Zhavoronkov

Drug Discovery Today, 2023, 28, 103675
DOI: 10.1016/j.drudis.2023.103675

Rotationally Invariant Crystallographic Representation for Enhancing the Inverse Design of Materials

Yuan Xing, Shiru Shen, Liangfeng Xu, Huaijuan Zang, Yongsheng Ren and Shu Zhan

Cryst. Res. Technol., 2025, 60
DOI: 10.1002/crat.70043

A General Approach to Dropout in Quantum Neural Networks

Francesco Scala, Andrea Ceschini, Massimo Panella and Dario Gerace

Adv Quantum Tech, 2025, 8
DOI: 10.1002/qute.202300220

QGAN-based data augmentation for hybrid quantum–classical neural networks

Run-Ze He, Jun-Jian Su, Su-Juan Qin, Zheng-Ping Jin and Fei Gao

Chinese Journal of Physics, 2025, 97, 1453
DOI: 10.1016/j.cjph.2025.07.017

Designing Variational Ansatz for Quantum‐Enabled Simulation of Non‐Unitary Dynamical Evolution ‐ An Excursion into Dicke Supperradiance

Saurabh Shivpuje, Manas Sajjan, Yuchen Wang, Zixuan Hu and Sabre Kais

Adv Quantum Tech, 2025, 8
DOI: 10.1002/qute.202400088

Dequantizing quantum machine learning models using tensor networks

Seongwook Shin, Yong Siah Teo and Hyunseok Jeong

Phys. Rev. Research, 2024, 6
DOI: 10.1103/PhysRevResearch.6.023218

Hyperparameter importance and optimization of quantum neural networks across small datasets

Charles Moussa, Yash J. Patel, Vedran Dunjko, Thomas Bäck and Jan N. van Rijn

Mach Learn, 2024, 113, 1941
DOI: 10.1007/s10994-023-06389-8

Quantum entanglement, quantum teleportation, multilinear polynomials and geometry

Juan M. Romero, Emiliano Montoya-González and Oscar Velazquez-Alvarado

Int. J. Geom. Methods Mod. Phys., 2026, 23
DOI: 10.1142/S0219887825502081

A machine learning approach for predicting the reactivity power of hypervalent iodine compounds

Vaneet Saini, Ramesh Kataria and Shruti Rajput

Artificial Intelligence Chemistry, 2024, 2, 100032
DOI: 10.1016/j.aichem.2023.100032

Quantum informative analysis for weather of San Francisco

Yasser Kotb, Amr A. Youssef, Dieaa I. Nassr and Hatem M. Bahig

Sci Rep, 2026, 16
DOI: 10.1038/s41598-025-33459-9

A Quantum Framework for Protein Binding‐Site Structure Prediction on Utility‐Level Quantum Processors

Yuqi Zhang, Yuxin Yang, William Martin, Kingsten Lin, Zixu Wang, Cheng‐Chang Lu, Weiwen Jiang, Ruth Nussinov, Joseph Loscalzo, Qiang Guan and Feixiong Cheng

Advanced Science, 2026, 13
DOI: 10.1002/advs.202513641

Machine learning and artificial intelligence in perovskite quantum dot electroanalysis: From data-driven synthesis to intelligent sensing interfaces

Mohamed Abu Shuheil, Ahmed Aldulaimi, Rekha M M, Subhashree Ray, Omayma salim waleed, CP. Surya, Renu Sharma, Vatsal Jain, Hadi Noorizadeh and Mosstafa Kazemi

Talanta Open, 2026, 13, 100623
DOI: 10.1016/j.talo.2026.100623

Many-body eigenstates from quantum manifold optimization

Scott E. Smart and Prineha Narang

Phys. Rev. A, 2024, 110
DOI: 10.1103/PhysRevA.110.052430

Dimensionality Reduction with Variational Encoders Based on Subsystem Purification

Raja Selvarajan, Manas Sajjan, Travis S. Humble and Sabre Kais

Mathematics, 2023, 11, 4678
DOI: 10.3390/math11224678

Toward Efficient and Accurate Prediction of Phonon‐Limited Carrier Mobility by First Principles

Yingqi Wang and Zhirong Liu

Adv Funct Materials, 2026, 36
DOI: 10.1002/adfm.202423252

Multi-omic and quantum machine learning integration for lung subtypes classification

Mandeep Kaur Saggi, Amandeep Singh Bhatia, Isaiah K. Mensah, Humaira Gowher and Sabre Kais

Future Generation Computer Systems, 2026, 174, 107905
DOI: 10.1016/j.future.2025.107905

Research on Quantum Circuit Learning Models for Molecular Dynamics Simulation

Y. Nishida

J. Phys. Chem. A, 2025, 129, 9434
DOI: 10.1021/acs.jpca.5c03624

Quantum computing for solid mechanics and structural engineering – A demonstration with Variational Quantum Eigensolver

Yunya Liu, Jiakun Liu, Jordan R. Raney and Pai Wang

Extreme Mechanics Letters, 2024, 67, 102117
DOI: 10.1016/j.eml.2023.102117

Reducing the Quantum Many-Electron Problem to Two Electrons with Machine Learning

LeeAnn M. Sager-Smith and David A. Mazziotti

J. Am. Chem. Soc., 2022, 144, 18959
DOI: 10.1021/jacs.2c07112

Integrating quantum computing resources into scientific HPC ecosystems

Thomas Beck, Alessandro Baroni, Ryan Bennink, Gilles Buchs, Eduardo Antonio Coello Pérez, Markus Eisenbach, Rafael Ferreira da Silva, Muralikrishnan Gopalakrishnan Meena, Kalyan Gottiparthi, Peter Groszkowski, Travis S. Humble, Ryan Landfield, Ketan Maheshwari, Sarp Oral, Michael A. Sandoval, Amir Shehata, In-Saeng Suh and Christopher Zimmer

Future Generation Computer Systems, 2024, 161, 11
DOI: 10.1016/j.future.2024.06.058