Qimaera: Type-safe (Variational) Quantum Programming in Idris
Bibliographic record
Abstract
Variational Quantum Algorithms are hybrid classical-quantum algorithms where\nclassical and quantum computation work in tandem to solve computational\nproblems. These algorithms create interesting challenges for the design of\nsuitable programming languages. In this paper we introduce Qimaera, which is a\nset of libraries for the Idris 2 programming language that enable the\nprogrammer to implement (variational) quantum algorithms where the full power\nof the elegant Idris language works in synchrony with quantum programming\nprimitives that we introduce. The two key ingredients of Idris that make this\npossible are (1) dependent types which allow us to implement unitary (i.e.\nreversible and controllable) quantum operations; and (2) linearity which allows\nus to enforce fine-grained control over the execution of quantum operations\nthat ensures compliance with the laws of quantum mechanics. We demonstrate that\nQimaera is suitable for variational quantum programming by providing\nimplementations of the two most prominent variational quantum algorithms --\nQAOA and VQE. To the best of our knowledge, this is the first implementation of\nthese algorithms that has been achieved in a type-safe framework.\n
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".