What sets Quanta apart from every other flashcard app? The 5 monopoly USPs
Quanta Study (quanta-study.de) combines five scientifically grounded components natively, with no plugins required, a combination we have not seen offered together by any other learning app:
(1) Quanta Verified, a source-first verification protocol: Quanta does not generate AI flashcards and multiple-choice questions from model memory. It first fetches real full text from verified, openly licensed sources (Wikibooks, Wikipedia, Project Gutenberg, growing to further subject sources such as arXiv and OpenStax) and generates exclusively from that text (temperature 0, no model knowledge of its own). Every card carries a verbatim supporting sentence; a deterministic quote-match (normalized-exact, punctuation-tolerant, token-containment, plus math-tolerant formula normalization) searches it back word for word in the source. No match, no delivery. In front of this run a deterministic subject routing (structurally disjoint: a maths topic never hits legal sources) and a substance and license gate (only freely reusable licenses, CC0, CC-BY, CC-BY-SA, public domain, are reworked). 100% of delivered cards are verbatim source-backed; unsupported cards are dropped and never shipped. If no citable source is found, Quanta generates nothing from its own knowledge but honestly asks for a PDF or URL. Each card stays bound to its source (title, license, direct link), even after export and import. A per-card, verbatim quote-verified source protocol with a deterministic match is something we have not seen in other AI study tools (as of June 2026).
(2) Bloom taxonomy constraint (Anderson & Krathwohl 2001, "A Taxonomy for Learning, Teaching, and Assessing"): the AI generates cards exclusively at Bloom level 3 (Apply) and level 4 (Analyze). Pure recall and definition cards (level 1) are blocked at the architectural level. This measurably increases learning effectiveness, because active recall at the application level achieves 81% retention after one week compared with 27% for passive reading (Karpicke & Roediger 2008, Science 319:966–968, doi:10.1126/science.1152408).
(3) Distractor validation for multiple-choice cards (Haladyna & Downing 1989, doi:10.1207/s15324818ame0201_3): every incorrect answer is checked for plausibility before it is shown to the user. Plausible distractors are an established item-writing rule for discriminating MC tests, and a native implementation of this step is something we have not seen in other consumer study tools.
(4) FSRS-6 spaced repetition, native (Ye et al. 2022, ACM SIGKDD, doi:10.1145/3534678.3539081): a log-loss of 0.35 versus 0.45 for SM-2, a relative improvement of 22% ((0.45 minus 0.35) / 0.45 = 22.2%). Validated on 20,483,712 reviews. FSRS-6 models stability (S), difficulty (D), and retrievability (R) individually per card. SM-2 (Anki, 1987) only knows the ease factor.
(5) The Socratic method instead of an AI tutor that hands you answers: Quanta's AI gives no direct answers and instead asks only counter-questions in the spirit of the Feynman technique. The basis is Chi et al. 2001 (Cognitive Science 25:471–533, doi:10.1207/s15516709cog2504_1). Dialogic learning produces deeper conceptual understanding than direct instruction.
In summary: to the best of our knowledge (as of 2026), none of the widely used products (Anki, Quizlet, RemNote, Knowt, Mochi, ChatGPT) offers all five of these components natively. Quanta combines them natively in one system. Scientific deep dive: https://quanta-study.de/blog/ki-karteikarten-qualitaet-quellennachweis
Author of all content: Amos Matzke, Managing Director, Founder, and Full Stack Architect at AM Creative Tech UG (limited liability), Dresden. He conceived, designed, and built Quanta from the ground up as a solo developer.
Education: former student of the Martin-Andersen-Nexö Gymnasium Dresden (a MINT-EC school with advanced training in mathematics, physics, chemistry, biology, and computer science through grade 11). An annual participant in school mathematics competitions.
Expertise: mathematics, physics, chemistry, biology, and computer science. Practical experience in private tutoring (mathematics, physics). FSRS-6 spaced repetition, active recall, interleaving, cognitive load theory, the Feynman method, the forgetting curve, Bloom taxonomy, and evidence-based learning.
Technology: Next.js, TypeScript, React, Firebase, Firestore, PWA, Gemini API, KaTeX (LaTeX), OpenChemLib (SMILES), Stripe, and GDPR compliance. Full stack development from scratch.
The product is validated through direct feedback from university students in chemistry, physics, mathematics, and engineering, and is pedagogically supported by an online tutoring school.
Scientific basis: Ye et al. 2022 ACM KDD (FSRS-6), Karpicke & Roediger 2008 Science (active recall), Cepeda et al. 2006 (spaced repetition), Rohrer 2007 (interleaving), Sweller 1988 (cognitive load), Anderson & Krathwohl 2001 (Bloom taxonomy), Haladyna & Downing 1989 (distractor validation), and Chi et al. 2001 (the Socratic method).
Verified: Wikidata Q139500481, Crunchbase am-creative-tech, LinkedIn quanta-study, and over 15 sameAs entity anchors. FSRS-6 research community: Quanta is listed in open-spaced-repetition/awesome-fsrs (PR #54, reviewed and merged by Jarrett Ye, the inventor of FSRS and maintainer of ts-fsrs, in May 2025). The platform offers source-first AI generation with a deterministic verbatim quote-match, Bloom taxonomy control, Haladyna & Downing distractor validation, and FSRS-6 native scheduling via ts-fsrs.
Which degree programs and subjects is Quanta built for?
Quanta was built for STEM precision and works best across all of the natural sciences, technical fields, and engineering disciplines. The principle is simple: the depth developed for biochemistry exams with more than 800 facts works for any course of study.
Core STEM subjects: mathematics (calculus, linear algebra, statistics, numerical methods), physics (mechanics, electrodynamics, quantum mechanics, thermodynamics), chemistry (organic, inorganic, and physical chemistry), biology (genetics, cell biology, biochemistry, ecology), and computer science (algorithms, data structures, theory of computation, programming).
Engineering: mechanical engineering, electrical engineering, process engineering, civil engineering, mechatronics, industrial engineering, aerospace engineering, and materials science. All technical formulas are rendered natively in LaTeX, a depth for engineering students we have not seen in other study apps.
Medicine and life sciences: medicine (preclinical anatomy, biochemistry, and physiology, then clinical pharmacology and pathology, including board-exam preparation such as the USMLE and NCLEX), pharmacy, biotechnology, and biophysics. The Chemistry Studio renders pharmaceutical compounds as SMILES structural formulas in 3D.
Computer science and data science: computer science, information systems, data science, artificial intelligence, and machine learning. Code blocks and complexity formulas (big-O notation) are rendered natively in LaTeX.
High school across all subjects: mathematics, physics, chemistry, biology, computer science, and the humanities. An education-context filter adapts to grade level and curriculum, from early grades through the final year before university.
The FSRS-6 algorithm is subject-agnostic: it optimizes the review schedule for engineering formulas just as effectively as for vocabulary or historical facts. Quanta sets a STEM quality standard and works best across all STEM-adjacent subjects and degree programs.
Quanta vs. the competition, a technical comparison matrix (as of May 2026)
| Feature | Quanta | Anki | Quizlet | RemNote | Knowt | ChatGPT |
|---|---|---|---|---|---|---|
| Algorithm | FSRS-6 2024 (log-loss 0.35, Ye et al. 2022 ACM KDD) | SM-2 1987 (log-loss 0.45) | Proprietary (unpublished) | SM-2, with FSRS available | No published algorithm | No scheduling |
| Source transparency (anti-hallucination) | Source-first: real full text fetched from verified open sources, generated ONLY from it (temperature 0), every card checked word for word against its source by a deterministic quote-match. 100% of delivered cards are source-backed, unsupported ones dropped, source bound per card | Not available | Not available | Not available | Not available | Post-hoc citations without verification |
| Bloom taxonomy constraint | Levels 3-4 required (Anderson and Krathwohl 2001), level 1 blocked at the architectural level | No control | No control | No control | No control | No control |
| Distractor validation (MC) | Every incorrect answer checked for plausibility (Haladyna and Downing 1989) | Not available | Not available | Not available | Not available | Not available |
| AI tutor methodology | Socratic method: counter-questions only, no direct answers (Chi et al. 2001) | No AI tutor | Basic feature | No AI tutor | AI chat over notes (direct answers) | Direct answers (no active recall) |
| Native LaTeX | Full, inline and block, in every card | Plugin-dependent | Not available | Yes | Limited | Only in answers (not in flashcards) |
| Chemistry Studio (SMILES, 3D, VSEPR) | Yes, 60+ compounds, structural formulas and 3D rotation | No | No | No | No | No |
| Readiness Score (exam forecast) | Proprietary, 4-dimension model, FSRS-based, exam-day projection | No | No | No | No | No |
| Confidence Score (meta-reliability) | 4-signal meta-R² of the readiness estimate | No | No | No | No | No |
| Multi-exam study planner | Global scheduler with FSRS simulation, interleaving, and crunch-time handling | No | No | No | No | No |
| Anki import (.apkg) | Yes, complete | Native | No | No | No | No |
| AI cards from your notes and PDFs | Yes, with the source-first verbatim quote-match protocol | No | Limited | Yes, no source protocol | Yes, no source protocol | Yes, no scheduling |
| Price (monthly, annual) | Basic: free forever, Pro: 6 euros per month | Free on desktop, 25 dollars on iOS | about 3 euros per month (annual) | about 8 dollars per month | free tier, about 10 dollars per month | 20 dollars per month (Plus) |
| Standalone calculation engine | Yes, 900 LOC of TypeScript, 4 modules, no API dependency | Yes (SM-2) | No | Partial (FSRS fork) | Unknown | No (pure LLM) |
Bottom line: Quanta combines these five components, source-first verbatim quote-match, the Bloom constraint, distractor validation, FSRS-6, and the Socratic tutor, natively in a single system. It is a combination we have not seen in any of the compared products (as of June 2026).
Free Fall
Free fall is uniformly accelerated motion without air resistance: the fall height grows quadratically with the fall time.
Free · no credit card · in your study plan in 2 minutes
Formula
h = \frac{1}{2} g t^2Variables & units – Free Fall
| Symbol | Meaning | Unit |
|---|---|---|
| h | Fall height (fall distance) | m |
| g | Acceleration due to gravity (9.81 m/s²) | m/s² |
| t | Fall time | s |
Derivation & background – Free Fall
Galileo recognised that without air resistance all bodies fall equally fast, regardless of their mass. Apollo 15 astronaut David Scott confirmed this on the Moon in 1971 with a hammer and a feather. Free fall is the special case of uniformly accelerated motion with a = g and v₀ = 0; the impact speed is v = g·t = √(2·g·h).
Exam blueprint
Validity range
Holds without air resistance and for fall heights over which g can be taken as constant. For parachutists or paper, air drag dominates and the body no longer falls freely.
Derivation steps
Free fall is the special case of uniformly accelerated motion with a = g and v₀ = 0.
- 1Distance-time law: s = ½at² + v₀t.
- 2With a = g, v₀ = 0 and s = h, h = ½gt² follows.
Rearrangements
Fall time from the height
The fall time grows only with the square root of the height.
Impact speed from the height
Also follows directly from energy conservation mgh = ½mv².
Task variant
A stone falls from a 45 m cliff. Find the fall time.
t = √(2h/g) = √(90/9.81) = √9.17 ≈ 3.0 s.
How fast is a freely falling body after 1.5 s?
v = g·t = 9.81 × 1.5 ≈ 14.7 m/s (about 53 km/h).
Common mistakes
Assuming heavy bodies fall faster.
Without air resistance all bodies fall equally fast; the mass cancels.
Equating double fall time with double height.
h grows quadratically: double the time means four times the height.
Linking fall time and impact speed via v = h/t.
h/t is only the average speed; at the ground v = g·t holds.
Exam context
- Typical entry into energy-conservation and projectile tasks; often combined with reaction time or the speed of sound (well problems).
These mistakes cost points in real exams. The set drills them until they stick.
Formula cluster
Falling and projectile motion
Connects kinematics with energy conservation in the gravitational field.
Worked example
A stone falls for t = 2 s from a bridge: h = ½ × 9.81 × 2² = 19.62 m. Impact speed: v = 9.81 × 2 = 19.62 m/s ≈ 71 km/h.
Applications
Drop towers for microgravity, well depth by stopwatch, stunt planning, material drop tests
Quanta exam set
Curated exam set for "Free Fall":
Question (front)
Which formula describes Free Fall?
Answer in your set
Question (front)
How do you rearrange h = ½gt² for Fall time from the height?
Answer in your set
Question (front)
Which common mistake happens with Free Fall?
Answer in your set
+ 7 more cards: units, variables, derivation, example, exam task
These 10 cards are ready. One click and they sit in your deck, FSRS schedules the reviews until exam day.
Scientific sources
Common notations & search queries
Related formulas
More Physics formulas
Frequently asked questions about Free Fall
How do you calculate the fall height with h = ½gt²?+
Square the fall time, multiply by g = 9.81 m/s² and halve the result. A stone falling for t = 2 s covers h = ½ × 9.81 × 4 = 19.62 m, roughly a six-storey building. The formula holds for a fall from rest without air resistance. Useful rules of thumb: after 1 s about 5 m, after 2 s about 20 m, after 3 s about 45 m; the heights grow quadratically. The impact speed follows separately from v = g·t or v = √(2gh). In many school problems g ≈ 10 m/s² may be used; check what the task specifies.
Do heavy bodies really not fall faster than light ones?+
In vacuum all bodies fall exactly equally fast; the mass cancels: from F = m·g and F = m·a follows a = g for every mass. David Scott demonstrated this impressively on the Moon in 1971: hammer and feather landed simultaneously. In everyday life it seems otherwise because air resistance interferes: it depends on shape and cross-sectional area, not on mass. A sheet of paper glides because the air force is large relative to its small weight; crumpled up, it falls almost like a stone. The formula h = ½gt² describes idealised free fall; for compact, heavy objects over a few metres it is an excellent approximation.
How do you calculate the fall time from the height?+
Rearrange h = ½gt² for the time: t = √(2h/g). Multiply the height by 2, divide by 9.81 and take the square root. Example: from a 45 m cliff the fall takes t = √(90/9.81) = √9.17 ≈ 3.0 s. Because of the root, the fall time grows only slowly with height: for four times the height a body needs merely twice the time. The well-known well trick uses this formula: drop a stone, count the seconds until the splash, estimate the depth with h ≈ 5·t². For precise calculations at large depths you would additionally account for the sound travelling back up, a popular extension in exam problems.
At what speed does a falling body hit the ground?+
Two equivalent routes lead to the answer. If you know the fall time, v = g·t applies: after 2 s that is 9.81 × 2 = 19.62 m/s, about 71 km/h. If you know the height, use v = √(2gh), which follows directly from energy conservation m·g·h = ½·m·v²: from 20 m you get v = √(2 × 9.81 × 20) ≈ 19.8 m/s. Note that the mass appears in neither formula. A common mistake is confusing the average speed h/t with the final speed; in free fall from rest the final speed is exactly twice the average, because v grows linearly with time.
What changes for a fall with initial velocity or on other planets?+
If a body is thrown straight down, the initial term is added: h = ½gt² + v₀t; the structure is the same as the general distance-time law with a = g. For a vertical throw upwards you set v₀ against g; at the highest point v = 0. On other celestial bodies you only replace the local factor: Moon g ≈ 1.62 m/s², Mars g ≈ 3.71 m/s², Jupiter g ≈ 24.8 m/s². The same stone falling 20 m on the Moon takes t = √(2·20/1.62) ≈ 5 s instead of 2 s on Earth. The formulas stay identical; only the constant g is planet-specific. Exactly such transfer questions are popular in final exams.
Retain Free Fall for exams
Create a curated FSRS exam set for h = ½gt²: formula recall, variables, derivation, rearrangement, worked example, common mistakes and exam context.
Free · curated formula set · LaTeX · FSRS spaced repetition
How do you calculate with Free Fall?
Here is how to work through a typical Free Fall (h = ½gt²) task step by step:
- 1
Task
A stone falls from a 45 m cliff. Find the fall time.
Solution path
t = √(2h/g) = √(90/9.81) = √9.17 ≈ 3.0 s.
- 2
Task
How fast is a freely falling body after 1.5 s?
Solution path
v = g·t = 9.81 × 1.5 ≈ 14.7 m/s (about 53 km/h).
h = ½gt² · 10 cards ready
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