{"schema_version":"onlylabs.public_signal.v1","title":"Google (DeepMind / Gemini) Repo: google-deepmind/qtqp","description":"Google (DeepMind / Gemini) repo signal with public source context, captured evidence pages, related signals, and data-business radar classification.","url":"https://onlylabs.fyi/signals/3c0e984d-be30-4a8d-9855-d9c0cfa3d060","json_url":"https://onlylabs.fyi/signals/3c0e984d-be30-4a8d-9855-d9c0cfa3d060/signal.json","generated_at":"2026-06-11T04:00:06.429898+00:00","org":{"slug":"google-deepmind","name":"Google (DeepMind / Gemini)","category":"frontier-lab","category_label":"Frontier lab","dossier_url":"https://onlylabs.fyi/labs/google-deepmind","dossier_json_url":"https://onlylabs.fyi/labs/google-deepmind/dossier.json"},"related_urls":{"signal":"https://onlylabs.fyi/signals/3c0e984d-be30-4a8d-9855-d9c0cfa3d060","signal_json":"https://onlylabs.fyi/signals/3c0e984d-be30-4a8d-9855-d9c0cfa3d060/signal.json","source":"https://github.com/google-deepmind/qtqp","lab_dossier":"https://onlylabs.fyi/labs/google-deepmind","lab_dossier_json":"https://onlylabs.fyi/labs/google-deepmind/dossier.json","analysis":"https://onlylabs.fyi/analysis/google-deepmind","analysis_json":"https://onlylabs.fyi/analysis/google-deepmind/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/google-deepmind/evidence.json","category":"https://onlylabs.fyi/frontier","category_json":"https://onlylabs.fyi/frontier.json","category_feed":"https://onlylabs.fyi/frontier/feed.xml","category_signals_json":"https://onlylabs.fyi/signals.json","topic":null,"topic_signals_json":null,"topic_feed":null,"data_business":null},"answer_pack":{"answer":"Google (DeepMind / Gemini) published google-deepmind/qtqp (Python). 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It solves the primal QP: ``` min. (1/2) x.T @ p @ x + c.T @ x s.t. a @ x + s = b s[:z] == 0 s[z:] >= 0 ``` With dual: ``` max. -(1/2) x.T @ p @ x - b.T @ y s.t. p @ x + a.T @ y = -c y[z:] >= 0 ``` with data `a, b, c, p, z` and variables `x, y, s`. It returns a primal-dual solution when one exists, or a certificate of primal or dual infeasibility otherwise. Installation QTQP is available via pip: ```bash python -m pip install qtqp ``` On supported platforms this also installs the recommended sparse CPU backend automatically: - Linux / Windows `x86_64`: `py-mkl-pardiso` - macOS `arm64`: `macldlt` To install from source, first clone the repository: ```bash git clone..."},"evidence_pages":[{"url":"https://github.com/google-deepmind/qtqp","final_url":"https://github.com/google-deepmind/qtqp","title":"google-deepmind/qtqp repository metadata","http_status":200,"content_type":"application/json","capture_method":"plain","fetched_at":"2026-06-11T04:00:06.429898+00:00","bytes":21890,"raw_path":"67f7602ef1c2189440a10857cee36113d12886f1d9fdb5901b3aab6cf9fca020.json","content_hash":"7f72de1e3255ba74a696b43ce570a0b796dfa54cbeb9f4aeeb9f470f0e4a812b","excerpt_chars":1200,"truncated":true,"excerpt":"google-deepmind/qtqp Language: Python License: Apache-2.0 Stars: 33 Forks: 4 Open issues: 2 Created: 2025-10-23T13:05:15Z Pushed: 2026-05-31T14:32:08Z Default branch: main Fork: no Archived: no README: QTQP [![Build Status](https://github.com/google-deepmind/qtqp/actions/workflows/ci.yml/badge.svg)](https://github.com/google-deepmind/qtqp/actions/workflows/ci.yml) The cutie QP solver is a primal-dual interior point method for solving convex quadratic programs (QPs), implemented in pure python. It solves the primal QP: ``` min. (1/2) x.T @ p @ x + c.T @ x s.t. a @ x + s = b s[:z] == 0 s[z:] >= 0 ``` With dual: ``` max. -(1/2) x.T @ p @ x - b.T @ y s.t. p @ x + a.T @ y = -c y[z:] >= 0 ``` with data `a, b, c, p, z` and variables `x, y, s`. It returns a primal-dual solution when one exists, or a certificate of primal or dual infeasibility otherwise. Installation QTQP is available via pip: ```bash python -m pip install qtqp ``` On supported platforms this also installs the recommended sparse CPU backend automatically: - Linux / Windows `x86_64`: `py-mkl-pardiso` - macOS `arm64`: `macldlt` To install from source, first clone the repository: ```bash git clone..."}],"related_signals":[{"id":"02f8701d-7bfd-41b5-aabe-1ad72a880dfb","url":"https://onlylabs.fyi/signals/02f8701d-7bfd-41b5-aabe-1ad72a880dfb","source_url":"https://github.com/google-deepmind/unpic","title":"google-deepmind/unpic","context":"Python","kind":{"key":"repo_new","label":"Repo"},"org":{"slug":"google-deepmind","name":"Google (DeepMind / Gemini)","category":"frontier-lab"},"occurred_at":"2026-06-04T14:37:24+00:00","first_seen_at":"2026-06-05T05:42:58.453363+00:00","date_source":"source"},{"id":"35320cac-ddbe-4f25-a3b5-384a0ca0030b","url":"https://onlylabs.fyi/signals/35320cac-ddbe-4f25-a3b5-384a0ca0030b","source_url":"https://github.com/google-deepmind/seeing_without_pixels","title":"google-deepmind/seeing_without_pixels","context":"Python","kind":{"key":"repo_new","label":"Repo"},"org":{"slug":"google-deepmind","name":"Google (DeepMind / Gemini)","category":"frontier-lab"},"occurred_at":"2026-06-03T04:04:52+00:00","first_seen_at":"2026-06-05T05:42:58.453363+00:00","date_source":"source"},{"id":"62f799ef-bf1d-4aee-9f87-fa0de8bb5e81","url":"https://onlylabs.fyi/signals/62f799ef-bf1d-4aee-9f87-fa0de8bb5e81","source_url":"https://github.com/google-deepmind/nested","title":"google-deepmind/nested","context":"Python","kind":{"key":"repo_new","label":"Repo"},"org":{"slug":"google-deepmind","name":"Google (DeepMind / Gemini)","category":"frontier-lab"},"occurred_at":"2026-05-18T16:16:42+00:00","first_seen_at":"2026-06-05T05:42:58.453363+00:00","date_source":"source"},{"id":"e67b1d5f-ef62-4574-80df-a72a4bded705","url":"https://onlylabs.fyi/signals/e67b1d5f-ef62-4574-80df-a72a4bded705","source_url":"https://github.com/google-deepmind/science-skills","title":"google-deepmind/science-skills","context":"Python","kind":{"key":"repo_new","label":"Repo"},"org":{"slug":"google-deepmind","name":"Google (DeepMind / Gemini)","category":"frontier-lab"},"occurred_at":"2026-05-13T16:17:41+00:00","first_seen_at":"2026-06-05T05:42:58.453363+00:00","date_source":"source"},{"id":"7b714793-a56e-495b-8d57-85fd2850555a","url":"https://onlylabs.fyi/signals/7b714793-a56e-495b-8d57-85fd2850555a","source_url":"https://github.com/google-deepmind/alphaproof-nexus-results","title":"google-deepmind/alphaproof-nexus-results","context":"Lean","kind":{"key":"repo_new","label":"Repo"},"org":{"slug":"google-deepmind","name":"Google (DeepMind / Gemini)","category":"frontier-lab"},"occurred_at":"2026-05-13T09:59:21+00:00","first_seen_at":"2026-06-05T05:42:58.453363+00:00","date_source":"source"},{"id":"dab748d2-53d6-4972-a594-eb6bfbf727ea","url":"https://onlylabs.fyi/signals/dab748d2-53d6-4972-a594-eb6bfbf727ea","source_url":"https://github.com/google-deepmind/tecci","title":"google-deepmind/tecci","context":"JavaScript","kind":{"key":"repo_new","label":"Repo"},"org":{"slug":"google-deepmind","name":"Google (DeepMind / Gemini)","category":"frontier-lab"},"occurred_at":"2026-05-05T12:22:40+00:00","first_seen_at":"2026-06-05T05:42:58.453363+00:00","date_source":"source"}]}