Every simulation now opens on its own dedicated route.
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Hardware-constrained learning for quantum computing and artificial intelligence
Simulation program
The simulation layer now behaves like a real library instead of a single long document. The original sixteen course labs remain grouped by the original six-module studio core, and eighteen new academy-style labs now live in their own subject tracks and dedicated studio routes while the broader public curriculum continues to expand.
This page now includes browser-playable educational prototypes for all sixteen verified simulation concepts. They run live in the browser today, while session persistence, analytics, and lesson-embedded progression remain the next implementation layer.
Every simulation now opens on its own dedicated route.
The original curriculum-aligned sixteen-lab track remains intact.
Reference-inspired subjects now add topic-specific simulation tracks.
Five subject families complement the original simulation-track modules.
The simulation catalog still stays grouped by the six-module studio core.
Separated catalog
This browser keeps the module grouping visible while letting each lab stand on its own page, closer to a real simulation library than a single scroll-heavy gallery.
Module 1
Module 1 simulations make the NISQ-era constraints visible and clarify where the quantum subroutine actually sits inside a hybrid workflow.
Dedicated labs separated into individual routes.
Suggested starting point for this module.
Each lab opens as its own simulation studio page.
Controls include circuit depth, epsilon, qubit count, and backend options for IBM Heron, IonQ Forte, and a simulated ideal baseline.
Learners adjust circuit depth, gate error rate, qubit count, and backend assumptions while a live fidelity curve collapses from 1.0 toward 0.0.
F(G, epsilon) = (1 - epsilon)^G
Drag each abstract into the correct bucket, then inspect why the classification is right or wrong after every move.
Ten real abstracts from the 2025 and 2026 proceedings are sorted into QAI or AI4QC with immediate reasoning feedback.
Task cards such as normalization, gate compilation, parameter optimization, measurement averaging, and output decoding are dragged into the most plausible stage, then scored against cost and orchestration tradeoffs.
A hybrid pipeline is split into classical preprocessing, quantum subroutine, and classical post-processing zones.
Additional subject tracks
These new tracks follow the reference browsing pattern more closely: topic-based groupings, distinct accent systems, and launch cards that open one simulation studio at a time.
Math subjects
Explore state geometry, superposition, interference, tunneling, entanglement, and measurement collapse through visual-first interactive labs.
Algorithm subjects
Step through core algorithmic ideas such as teleportation, Deutsch-Jozsa, the QFT, Shor-style period finding, and Grover amplification.
Programming subjects
Practice gate sequencing, small-circuit construction, Qiskit-style code generation, and statevector reasoning in a browser-first environment.
Software subjects
Explore error-correction logic, syndrome decoding, and hybrid quantum-classical learning loops through compact engineering-focused prototypes.
Finance subjects
Connect quantum-inspired optimization and Monte Carlo ideas to concrete finance-style decisions around allocation, pricing, and risk.
Design rules
Roadmap snapshot
3 corrected curriculum labs remain labeled explicitly, while the new academy tracks provide a broader public-facing simulation surface.