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 · Kinematics

Velocity-Time Law

The velocity-time law describes how the velocity grows linearly with time under constant acceleration.

BasicExam-relevant

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

Formula

v = a·t + v₀
LaTeX: v = a \cdot t + v_0
v in m/s · a in m/s² · t in seconds [s] · v₀ in m/s
Diagram: a v-t line meets the axis at v₀; a slope triangle shows Δv over Δt as the acceleration a.tvv₀ΔtΔva = Δv/Δt
The velocity grows linearly with time; the slope of the line is the acceleration a, the intercept is v₀.

Variables & units – Velocity-Time Law

SymbolMeaningUnit
vVelocity at time tm/s
aConstant accelerationm/s²
tTimes
v₀Initial velocitym/s

Derivation & background – Velocity-Time Law

Acceleration is defined as the change of velocity per time: a = Δv/Δt. If a is constant, v grows linearly, a straight line with slope a in the v-t diagram. The area under the line is the distance travelled, which is how the v-t law and the distance-time law are connected. Braking is the case a < 0.

Exam blueprint

Validity range

Holds for constant acceleration along a straight line. Braking is described with negative a. For varying a the relation only holds differentially: a = dv/dt.

Derivation steps

Constant acceleration means the velocity changes by the same amount every second.

  1. 1Definition: a = Δv/Δt = (v − v₀)/t.
  2. 2Solve for v: v = a·t + v₀.

Rearrangements

Time to reach a target speed

t = \frac{v - v_0}{a}

The numerator is the change in speed, not the final speed.

Acceleration from two speeds

a = \frac{v - v_0}{t}

A negative value means braking (deceleration).

Task variant

A car accelerates at a = 2.5 m/s² from 0 to 100 km/h. How long does it take?

100 km/h = 27.8 m/s. t = (27.8 − 0)/2.5 ≈ 11.1 s.

A cyclist speeds up from 20 m/s to 26 m/s in 3 s. Find a.

a = (26 − 20)/3 = 2 m/s².

Common mistakes

Substituting km/h directly.

Always convert to m/s by dividing by 3.6 first.

Dropping v₀ and writing v = a·t although the body is already moving.

v = a·t only holds for a start from rest.

Ignoring the sign of a when braking.

Insert deceleration as a < 0, otherwise the body speeds up in the calculation.

Exam context

  • Often a sub-step: first find v(t), then compute distance, momentum or kinetic energy from it.

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

Formula cluster

Laws of motion

The v-t law is the derivative of the distance-time law.

Worked example

A train moves at v₀ = 10 m/s and accelerates with a = 1.5 m/s² for t = 8 s: v = 1.5 × 8 + 10 = 22 m/s (79 km/h).

Applications

Acceleration measurement (0-to-100 time), braking deceleration, lift control, sports analysis (sprint start)

Quanta exam set

Curated exam set for "Velocity-Time Law":

Question (front)

Which formula describes Velocity-Time Law?

Answer in your set

Question (front)

How do you rearrange v = a·t + v₀ for Time to reach a target speed?

Answer in your set

Question (front)

Which common mistake happens with Velocity-Time Law?

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

v=a*tv=at+v0v = a·t + v₀Geschwindigkeit-Zeit-GesetzEndgeschwindigkeit berechnenBeschleunigung Formel Zeitvelocity time formulaa=v/t umstellen

Related formulas

More Physics formulas

Frequently asked questions about Velocity-Time Law

How do you calculate the final speed with v = a·t + v₀?+

Multiply the acceleration by the time and add the initial velocity. Example: a train travels at v₀ = 10 m/s and accelerates for 8 s at a = 1.5 m/s²: v = 1.5 × 8 + 10 = 22 m/s, which is about 79 km/h. All quantities belong in SI units; divide a speed in km/h by 3.6 before substituting. Intuitively the formula says: the acceleration states how many m/s the body gains per second. At a = 1.5 m/s² it thus gets 1.5 m/s faster every second. When braking, insert a as negative and v decreases accordingly.

What does an acceleration of 1 m/s² mean intuitively?+

It means the velocity increases by 1 m/s every second; after three seconds the body is 3 m/s faster. The double unit m/s² is best read as "(m/s) per s". For scale: a brisk small car manages about 3 m/s² when pulling away, emergency braking is 8 to 10 m/s², free fall is 9.81 m/s², and a Formula 1 car brakes at up to 50 m/s² (about 5g). Acceleration is not limited to speeding up: physically every change of velocity is an acceleration, including braking (negative sign) and even pure changes of direction in circular motion.

How do you rearrange v = a·t + v₀ for the time?+

First subtract v₀ on both sides, then divide by a: t = (v − v₀)/a. The numerator is the change in velocity, not the final velocity, which is the most common mistake. Example: a car accelerates at a = 2.5 m/s² from 0 to 100 km/h (27.8 m/s): t = (27.8 − 0)/2.5 ≈ 11.1 s. Slowing from 26 m/s to 20 m/s at a = −2 m/s²: t = (20 − 26)/(−2) = 3 s; two negative signs cancel and the time is positive as expected. If a negative time comes out, signs or start and end values are swapped. A unit check (m/s divided by m/s² gives s) secures the result.

What is the difference between velocity and acceleration?+

Velocity says how fast the position changes (m/s); acceleration says how fast the velocity changes (m/s²). Both can independently be large, small or zero: an aircraft in cruise is very fast but unaccelerated (a = 0). A ball at the top of a vertical throw momentarily has v = 0 yet is fully accelerated at g = 9.81 m/s², otherwise it would stay up there. The directions need not agree either: when braking, a points against the motion. This distinction is the core of many conceptual questions; anyone who equates v and a fails exactly these tasks.

How do you read velocity and acceleration from diagrams?+

Remember two rules: slope and area. In the s-t diagram the slope is the velocity; a steeper curve means faster, a parabola indicates acceleration. In the v-t diagram the slope is the acceleration: a line with positive slope means constant a, a horizontal line uniform motion. Additionally, the area under the v-t curve is the distance travelled; for the trapezoid made of the v₀ rectangle and the acceleration triangle this gives exactly s = v₀t + ½at². Exam problems like to combine segments: first accelerate, then drive at constant speed, then brake. Split the diagram into these phases and compute the areas separately.

Retain Velocity-Time Law for exams

Create a curated FSRS exam set for v = a·t + v₀: 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 Velocity-Time Law?

Here is how to work through a typical Velocity-Time Law (v = a·t + v₀) task step by step:

  1. 1

    Task

    A car accelerates at a = 2.5 m/s² from 0 to 100 km/h. How long does it take?

    Solution path

    100 km/h = 27.8 m/s. t = (27.8 − 0)/2.5 ≈ 11.1 s.

  2. 2

    Task

    A cyclist speeds up from 20 m/s to 26 m/s in 3 s. Find a.

    Solution path

    a = (26 − 20)/3 = 2 m/s².

v = a·t + v₀ · 10 cards ready

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