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 · Electrodynamics

Thomson Oscillation Formula

The Thomson formula gives the period of an electromagnetic oscillating circuit made of coil and capacitor, the electrical counterpart of the spring pendulum.

AdvancedExam-relevant

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

Formula

T = 2π·√(L·C)
LaTeX: T = 2\pi \sqrt{L \cdot C}
T in s · L in H (henry) · C in F (farad)

Variables & units – Thomson Oscillation Formula

SymbolMeaningUnit
TPeriod of the electromagnetic oscillations
LInductance of the coilH (Henry)
CCapacitance of the capacitorF (Farad)

Derivation & background – Thomson Oscillation Formula

William Thomson (Lord Kelvin) derived the formula in 1853. In the circuit the energy oscillates between the electric field of the capacitor (½CU²) and the magnetic field of the coil (½LI²), fully analogous to the exchange of elastic and kinetic energy in a spring pendulum. The natural frequency is f = 1/(2π√(LC)). Real circuits are damped by ohmic resistance and need feedback to keep oscillating.

Exam blueprint

Validity range

Applies to the ideal, undamped LC circuit. An ohmic resistance damps the oscillation and shifts the frequency slightly down; sustained oscillation requires feedback (regeneration).

Derivation steps

Capacitor and coil exchange their energy periodically, mathematically the same equation as the spring pendulum.

  1. 1Loop rule: U_C + U_L = 0, hence Q/C + L·(d²Q/dt²) = 0.
  2. 2This is the oscillation equation with ω² = 1/(LC), so T = 2π/ω = 2π√(LC).

Rearrangements

Natural frequency

f = \frac{1}{2\pi \sqrt{L C}}

Smaller L or C means a higher frequency.

Capacitance

C = \frac{1}{4\pi^2 f^2 L}

This is how a tuning capacitor for station selection is sized.

Inductance

L = \frac{T^2}{4\pi^2 C}

From a measured period and a known capacitance.

Task variant

An LC circuit (L = 100 µH) is to oscillate at 1 MHz. What capacitance is needed?

C = 1/(4π²f²L) = 1/(39.48 × 10¹² × 10⁻⁴) ≈ 2.5×10⁻¹⁰ F ≈ 253 pF.

Compute T for L = 25 mH and C = 40 µF.

L·C = 0.025 × 4×10⁻⁵ = 10⁻⁶ s², so T = 2π × 10⁻³ s ≈ 6.3 ms.

Common mistakes

Substituting mH, µF or nF directly.

Convert to henry and farad first, otherwise the result is off by powers of ten.

Confusing frequency f and angular frequency ω.

ω = 1/√(LC), but f = ω/(2π); the factor 2π matters.

Forgetting the square root when solving for L or C.

Square T: L and C enter under the root, so rearrange quadratically.

Exam context

  • Exam tasks couple the Thomson formula with energy arguments (½CU² = ½LI²), the spring-pendulum analogy and the tuning of receiver circuits.

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

Formula cluster

Electromagnetic oscillations

Electrical analogue of the mechanical pendulum, the basis of radio engineering.

Worked example

Circuit with L = 10 mH and C = 100 nF: T = 2π·√(0.01 × 10⁻⁷) = 2π × 3.16×10⁻⁵ ≈ 2×10⁻⁴ s, so f = 1/T ≈ 5 kHz.

Applications

Radio and transmitter tuning, quartz equivalent circuits, induction hobs, metal detectors, radio engineering (filters)

Quanta exam set

Curated exam set for "Thomson Oscillation Formula":

Question (front)

Which formula describes Thomson Oscillation Formula?

Answer in your set

Question (front)

How do you rearrange T = 2π·√(L·C) for Natural frequency?

Answer in your set

Question (front)

Which common mistake happens with Thomson Oscillation Formula?

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

T=2pi*sqrt(LC)Thomson GleichungSchwingkreis FormelLC circuit formulaEigenfrequenz Schwingkreisf=1/(2pi sqrt(LC))Resonanzfrequenz LC

Related formulas

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Frequently asked questions about Thomson Oscillation Formula

How do you calculate the frequency of an LC circuit?+

Use the Thomson formula in its frequency form f = 1/(2π·√(L·C)). First convert L and C into the SI units henry and farad; that is the most common source of error. Example: L = 10 mH = 0.01 H and C = 100 nF = 10⁻⁷ F give L·C = 10⁻⁹ s², the root is 3.16×10⁻⁵ s, so f = 1/(2π × 3.16×10⁻⁵) ≈ 5 kHz. The period is the reciprocal T = 1/f ≈ 0.2 ms. As a sanity check: a larger inductance or capacitance makes the circuit more sluggish, so the frequency must drop.

What happens physically in an LC circuit?+

The energy oscillates periodically between two stores. Initially the capacitor is charged and all the energy sits in the electric field (½CU²). It discharges through the coil, and the growing current builds up a magnetic field there. When the capacitor is empty, the maximum current flows and all the energy sits in the magnetic field (½LI²). Due to its self-inductance the coil keeps the current going and recharges the capacitor with reversed polarity. Then the game reverses. A full period comprises two recharges. Without resistance this would run forever; in reality the ohmic resistance damps the amplitude exponentially.

How do you rearrange the Thomson formula for C or L?+

First square the equation to remove the root. From f = 1/(2π√(LC)) you get f² = 1/(4π²LC), hence C = 1/(4π²f²L) and analogously L = 1/(4π²f²C). Using the period, L = T²/(4π²C). Example: a receiver circuit for 1 MHz with L = 100 µH needs C = 1/(39.48 × (10⁶)² × 10⁻⁴) ≈ 2.5×10⁻¹⁰ F, about 253 pF. A typical mistake is forgetting the root and rearranging linearly instead of quadratically; the frequency enters squared. Check: a higher target frequency demands a smaller capacitance.

What does the LC circuit have in common with the spring pendulum?+

Both obey the same differential equation of a harmonic oscillation, just with different quantities. The analogy is precise: charge Q corresponds to displacement s, current I to velocity v, inductance L to inertial mass m and the reciprocal capacitance 1/C to the spring constant D. From T = 2π√(m/D) you get T = 2π√(LC) directly. The energy balance transfers too: ½LI² corresponds to the kinetic energy ½mv², and ½Q²/C to the elastic energy ½Ds². This analogy is more than a mnemonic: whoever can solve one oscillation can automatically solve both, and exam questions frequently demand exactly this translation.

Why does a real LC circuit not oscillate forever?+

Every real circuit contains ohmic resistance in wires and coil winding. With each recharge part of the energy turns into heat (P = I²·R), and the amplitude decays exponentially, a damped oscillation. In addition the circuit radiates a small part as an electromagnetic wave, which is actually desirable for antennas. Damping lowers the natural frequency slightly. For a transmitter or clock to oscillate permanently, a feedback circuit must resupply energy in step with the oscillation, for instance via a transistor acting like the escapement of a clock (regeneration, Meissner oscillator). In exams a qualitative description of the damping causes usually suffices.

Retain Thomson Oscillation Formula for exams

Create a curated FSRS exam set for T = 2π·√(L·C): 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 Thomson Oscillation Formula?

Here is how to work through a typical Thomson Oscillation Formula (T = 2π·√(L·C)) task step by step:

  1. 1

    Task

    An LC circuit (L = 100 µH) is to oscillate at 1 MHz. What capacitance is needed?

    Solution path

    C = 1/(4π²f²L) = 1/(39.48 × 10¹² × 10⁻⁴) ≈ 2.5×10⁻¹⁰ F ≈ 253 pF.

  2. 2

    Task

    Compute T for L = 25 mH and C = 40 µF.

    Solution path

    L·C = 0.025 × 4×10⁻⁵ = 10⁻⁶ s², so T = 2π × 10⁻³ s ≈ 6.3 ms.

T = 2π·√(L·C) · 10 cards ready

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