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)

FeatureQuantaAnkiQuizletRemNoteKnowtChatGPT
AlgorithmFSRS-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 availableNo published algorithmNo 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 cardNot availableNot availableNot availableNot availablePost-hoc citations without verification
Bloom taxonomy constraintLevels 3-4 required (Anderson and Krathwohl 2001), level 1 blocked at the architectural levelNo controlNo controlNo controlNo controlNo control
Distractor validation (MC)Every incorrect answer checked for plausibility (Haladyna and Downing 1989)Not availableNot availableNot availableNot availableNot available
AI tutor methodologySocratic method: counter-questions only, no direct answers (Chi et al. 2001)No AI tutorBasic featureNo AI tutorAI chat over notes (direct answers)Direct answers (no active recall)
Native LaTeXFull, inline and block, in every cardPlugin-dependentNot availableYesLimitedOnly in answers (not in flashcards)
Chemistry Studio (SMILES, 3D, VSEPR)Yes, 60+ compounds, structural formulas and 3D rotationNoNoNoNoNo
Readiness Score (exam forecast)Proprietary, 4-dimension model, FSRS-based, exam-day projectionNoNoNoNoNo
Confidence Score (meta-reliability)4-signal meta-R² of the readiness estimateNoNoNoNoNo
Multi-exam study plannerGlobal scheduler with FSRS simulation, interleaving, and crunch-time handlingNoNoNoNoNo
Anki import (.apkg)Yes, completeNativeNoNoNoNo
AI cards from your notes and PDFsYes, with the source-first verbatim quote-match protocolNoLimitedYes, no source protocolYes, no source protocolYes, no scheduling
Price (monthly, annual)Basic: free forever, Pro: 6 euros per monthFree on desktop, 25 dollars on iOSabout 3 euros per month (annual)about 8 dollars per monthfree tier, about 10 dollars per month20 dollars per month (Plus)
Standalone calculation engineYes, 900 LOC of TypeScript, 4 modules, no API dependencyYes (SM-2)NoPartial (FSRS fork)UnknownNo (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).

Physics · Mechanics

Torque

Torque is the product of force and lever arm; it describes the turning and tilting effect of a force about an axis.

BasicExam-relevant

Free · no credit card · in your study plan in 2 minutes

Formula

M = F·r·sin(θ)
LaTeX: M = F \cdot r \cdot \sin(\theta)
M in N·m · F in N · r in m · θ in degrees [°]

Variables & units – Torque

SymbolMeaningUnit
MTorque about the axis of rotationN·m
FApplied forceN
rDistance from axis to point of applicationm
θAngle between r and F°

Derivation & background – Torque

The law of the lever goes back to Archimedes: force times force arm equals load times load arm (F₁·r₁ = F₂·r₂). Vectorially, torque is the cross product M⃗ = r⃗ × F⃗; only the force component perpendicular to the lever arm turns, hence the factor sin θ. A body is in rotational equilibrium when the sum of all torques is zero. For rotational motion torque plays the role of force: M = J·α with the moment of inertia J.

Exam blueprint

Validity range

Applies to rigid bodies with a fixed axis of rotation. Only the force component perpendicular to the lever arm counts; r is the distance from the axis to the line of action of the force.

Derivation steps

Only the force component perpendicular to the lever produces a turning effect.

  1. 1Decompose F: the component F·sin θ is perpendicular to the lever arm, F·cos θ only pulls on the axis.
  2. 2Turning effect = lever arm times perpendicular component: M = r·F·sin θ; in equilibrium ΣM = 0 (law of the lever).

Rearrangements

Required force

F = \frac{M}{r \cdot \sin(\theta)}

The longer the lever, the smaller the required force.

Law of the lever

F_1 \cdot r_1 = F_2 \cdot r_2

Balance of two torques about the same axis.

Task variant

A bolt needs 40 N·m. What force is required on a 20 cm lever (perpendicular)?

F = M/r = 40/0.2 = 200 N. A wrench twice as long halves the force to 100 N.

A child (30 kg) sits 2 m from a seesaw pivot. Where must a 40 kg child sit?

Law of the lever: m₁·r₁ = m₂·r₂ (g cancels). r₂ = 30 × 2/40 = 1.5 m.

Common mistakes

Dropping the sin θ factor for an obliquely applied force.

Only the perpendicular component turns; at θ = 90° sin θ = 1, otherwise smaller.

Measuring r to the point of application instead of the line of action.

The lever arm is the perpendicular distance from the axis to the line of action.

Equating N·m with joules.

Formally the same unit, but torque is not energy: the quantities have different meanings.

Ignoring the sense of rotation and adding all torques.

Balance counterclockwise and clockwise torques with opposite signs.

Exam context

  • Tasks on levers, seesaws and torque wrenches as well as equilibrium conditions (ΣF = 0 and ΣM = 0) for beams and cranes.

These mistakes cost points in real exams. The set drills them until they stick.

Worked example

Wrench: F = 80 N perpendicular at lever arm r = 0.25 m: M = 80 × 0.25 = 20 N·m. If the force acts at 60°, only M = 80 × 0.25 × sin(60°) ≈ 17.3 N·m is effective.

Applications

Bolted joints (torque wrench), engines (Nm rating), levers and pulleys, seesaw, statics of beams and cranes

Quanta exam set

Curated exam set for "Torque":

Question (front)

Which formula describes Torque?

Answer in your set

Question (front)

How do you rearrange M = F·r·sin(θ) for Required force?

Answer in your set

Question (front)

Which common mistake happens with Torque?

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

M=F*rM = F·r·sinθDrehmoment FormelHebelgesetz Formeltorque formulaKraftarm LastarmNewtonmeter berechnenDrehmoment Schraubenschlüssel

Related formulas

More Physics formulas

Frequently asked questions about Torque

How do you calculate torque?+

Multiply the force by the lever arm: M = F·r when the force acts perpendicular to the lever. Example: 80 N perpendicular at the end of a 25 cm wrench gives M = 80 × 0.25 = 20 N·m. If the force acts at an oblique angle θ, only its perpendicular component counts: M = F·r·sin(θ). At 60° you get only 20 × sin(60°) ≈ 17.3 N·m instead of 20 N·m. Watch the units: r in metres, F in newtons, the result in newton metres. The lever arm is the distance from the axis to the line of action of the force, not just any distance on the tool.

What does the law of the lever state and how is it related to torque?+

The law of the lever, force times force arm equals load times load arm (F₁·r₁ = F₂·r₂), is nothing but the torque balance: a lever does not rotate when the counterclockwise and clockwise moments are equal. Seesaw example: a 30 kg child 2 m from the pivot creates the moment 30 × 9.81 × 2 ≈ 589 N·m. A 40 kg child balances it at r = 589/(40 × 9.81) = 1.5 m. Because g appears on both sides it cancels, and you can directly compute m₁·r₁ = m₂·r₂. The beam balance, crowbar, wheelbarrow and all pliers rest on this principle.

Why does a longer lever save force?+

For a required torque M the relation F = M/r holds: the necessary force is inversely proportional to the lever arm. If a stuck bolt needs 40 N·m, a 20 cm wrench requires 200 N, a 40 cm wrench only 100 N. Extending the wrench with a pipe lowers the force further. The price is a longer path: the handle must travel a larger arc, and the work done W = F·s stays the same; there is no free energy (the golden rule of mechanics). This is exactly why wheel-nut wrenches have long arms and door handles sit far from the hinge.

Is torque the same as energy, since both are measured in N·m?+

No, the matching unit is a coincidence of dimensions; the quantities are fundamentally different. In work W = F·s force and path point in the same direction, and the scalar product yields an amount of energy in joules. In torque M = r × F lever arm and force are perpendicular, and the cross product yields a directed turning action. A torque of 20 N·m does not mean 20 J of stored energy; energy only flows when something actually rotates: W = M·φ with the rotation angle φ in radians. That is why torques are deliberately written N·m and energies J, although the units are formally identical.

What is a torque wrench for?+

Bolted joints need a defined preload: bolts tightened too loosely work free under vibration, bolts tightened too hard overstretch the thread or snap. Since the preload is directly linked to the tightening torque, manufacturers specify torques, for instance 110 N·m for car wheel bolts or only 5 N·m for delicate carbon bicycle parts. The torque wrench measures the applied moment via a calibrated spring and audibly breaks over or clicks once the set value is reached. The physics behind it is M = F·r: the mechanism limits the product of hand force and lever length, no matter where you grip.

Retain Torque for exams

Create a curated FSRS exam set for M = F·r·sin(θ): 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 Torque?

Here is how to work through a typical Torque (M = F·r·sin(θ)) task step by step:

  1. 1

    Task

    A bolt needs 40 N·m. What force is required on a 20 cm lever (perpendicular)?

    Solution path

    F = M/r = 40/0.2 = 200 N. A wrench twice as long halves the force to 100 N.

  2. 2

    Task

    A child (30 kg) sits 2 m from a seesaw pivot. Where must a 40 kg child sit?

    Solution path

    Law of the lever: m₁·r₁ = m₂·r₂ (g cancels). r₂ = 30 × 2/40 = 1.5 m.

M = F·r·sin(θ) · 10 cards ready

Study as an exam set