# Qyber\black > Qyber\black is an open research network and GitLab-based platform for quantum control, geometry, magnetic resonance spectroscopy, cancer diagnosis, machine learning, and related open-source research outputs. Qyber\black provides project hosting, development infrastructure, project management, computing and communication resources for its members and collaborators. Most public outputs are research summaries, publications, code, data, results, and project wikis. Use this file as a curated entry point. For complete inline context, use https://qyber.black/llms-full.txt. ## Important Use and Licensing Notes - Qyber\black content includes wikis, publications, software, data, and results. Licences vary by resource; check the licence on each project, repository, data set, or publication before reuse. - Unless a resource states otherwise, Qyber\black wiki material is generally presented under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International. - Public software and data releases are intended to be open where possible, commonly under AGPL, GPL, Creative Commons, or project-specific licences. - When using Qyber\black content in AI systems, preserve attribution, respect each resource licence, and make derivative code, models, data, or other results available under a compatible licence where required. - Medical AI and cancer diagnosis material is research material, not clinical advice. Do not use it as a substitute for professional medical judgement or validated clinical systems. - Some project links, datasets, tools, repositories, or services may be internal, archived, mirrored, or unavailable without appropriate access. ## Core Overview - [Qyber\black main project](https://qyber.black/qyber/qyber): Overview of the Qyber research network, infrastructure, support contacts, licensing position, major research areas, members, and social links. - [Qyber\black help](https://qyber.black/help): Documentation entry point for GitLab, GitLab Pages, badges, diagrams, registry, object storage, communication, computing, and support services. - [Projects with Info topic](https://qyber.black/explore/projects/topics/Info): Curated project information pages summarising research outputs across major Qyber groups. - [Topics](https://qyber.black/explore/projects/topics): Topic index for machine learning, cancer, magnetic resonance imaging, magnetic resonance spectroscopy, quantum control, quantum spintronics, training, TeX, support, and education. - [GitHub mirror organisation](https://github.com/Qyber-black): Public mirror of released Qyber software repositories. ## Main Research Areas - [Cancer / Info - Cancer](https://qyber.black/ca/info-cancer): Multi-parametric MRI and spectroscopy for cancer diagnosis, with emphasis on early-stage cancers, robustness, lightweight machine learning, and explainable AI. - [Magnetic Resonance Spectroscopy / Info - MRS](https://qyber.black/mrs/info-mrs): Machine learning and quantum control approaches for MR spectra, metabolite quantification, and pulse-sequence development. - [SpinNet / Info - SpinNet](https://qyber.black/spinnet/info-spinnet): Robust quantum control of spin-1/2 networks, including gradient optimisation, reinforcement learning, energy landscape control, robustness analysis, and quantum process tomography. - [Quantum Spintronics / Info - Quantum Spintronics](https://qyber.black/quantum-spintronics/info-quantum-spintronics): Monte Carlo simulation and control of semiconductor spin transport, including Dresselhaus and Rashba effects in InGaAs MOSFET spintronic devices. ## Key Software and Results - [BCa - Brain Cancer Segmentation Python Package](https://qyber.black/ca/code-bca): Python package for brain cancer segmentation with machine learning; mirrored at https://github.com/qyber-black/Code-BCa. - [BCa Segmentation Results - LATUPNet](https://qyber.black/ca/results-bca-latup): Trained LATUPNet brain cancer segmentation models and results. - [PCaNet](https://qyber.black/ca/code-pcanet): Code for prostate cancer segmentation and classification with machine learning; mirrored at https://github.com/qyber-black/Code-PCaNet. - [PCaNet Models - Classification](https://qyber.black/ca/results-pcanet-models-classification): Trained prostate cancer classification models and results. - [QDicom Utilities](https://qyber.black/ca/code-qdicom-utilities): Utilities for DICOM files and data repositories. - [LWFIT](https://qyber.black/mrs/code-lwfit): MRS spectral analysis and quantification code; mirrored at https://github.com/qyber-black/Code-LWFIT. - [MRSNet](https://qyber.black/mrs/code-mrsnet): Deep learning framework for metabolite quantification in magnetic resonance spectroscopy; mirrored at https://github.com/qyber-black/Code-MRSNet. - [MRSNet models and data](https://qyber.black/mrs/info-mrs): Entry point for MRSNet trained models, model selection results, simulated spectra, basis spectra, and MEGAPRESS phantom spectra. - [AtomNet](https://qyber.black/spinnet/code-atomnet): Atom energy landscape optimisation and analysis code; mirrored at https://github.com/qyber-black/code-atomnet. - [Differential Sensitivity Bounds for Dynamic Quantum Control](https://qyber.black/spinnet/code-differential-sensitivity-bounds-for-dynamic-control): Code release for differential sensitivity bounds in dynamic quantum control. - [MatSpinNet](https://qyber.black/spinnet/code-matspinnet): MATLAB code for analysing quantum spin-1/2 networks; mirrored at https://github.com/qyber-black/Code-MatSpinNet. - [RobChar](https://github.com/qyber-black/Code-RobChar): Robust characterisation of quantum controls and quantum control algorithms. - [Energy Landscape Controllers for XX Spin Rings](https://qyber.black/spinnet/data-elc-xx-rings): Data for static bias and energy landscape controllers for XX spin rings and related robustness results. ## Selected Publications and Research Themes - [LATUP-Net brain tumour segmentation](https://arxiv.org/abs/2404.05911): Lightweight 3D attention U-Net with parallel convolutions for brain tumour segmentation. - [Texture feature analysis for early-stage prostate cancer](https://arxiv.org/abs/2406.15571): Prostate cancer classification in multi-parametric MRI. - [MRS quantification sim-to-real validation](https://arxiv.org/abs/2602.20289): Systematic deep learning validation for GABA quantification from magnetic resonance spectra. - [Robust quantum control in closed and open systems](https://arxiv.org/abs/2401.00294): Theory and practice of robust quantum control. - [Robustness of dynamic quantum control](https://arxiv.org/abs/2401.00301): Differential sensitivity bounds for dynamic quantum control. - [Sample-efficient model-based reinforcement learning for quantum control](https://arxiv.org/abs/2304.09718): Model-based RL for noisy quantum gate control. - [Monte Carlo simulations of spin transport in InGaAs FETs](https://doi.org/10.1063/1.4994148): Spin transport simulation in nanoscale InGaAs field-effect transistors. ## Optional - [Qymru archive](https://qymru.qyber.black): Archived Quantum Physics, Engineering and Technology in Wales site. - [Qyber YouTube](https://www.youtube.com/@qyber): Video abstracts, seminars, and presentations. - [Qyber Odysee](https://odysee.com/@qyber): Alternative video channel. - [Qyber LinkedIn](https://www.linkedin.com/company/qyber): Social profile. - [Qyber X/Twitter](https://x.com/qyber_black): Social profile.