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).
Hardy-Weinberg Equilibrium
The Hardy-Weinberg equilibrium links the allele frequencies p and q in an ideal population with the genotype frequencies and stays constant from generation to generation as long as no evolutionary factors act.
Free · no credit card · in your study plan in 2 minutes
Formula
p^2 + 2pq + q^2 = 1Variables & units – Hardy-Weinberg Equilibrium
| Symbol | Meaning | Unit |
|---|---|---|
| p | Frequency of the dominant allele A | – (0…1) |
| q | Frequency of the recessive allele a | – (0…1) |
| p² | Frequency of the homozygous dominant genotypes (AA) | – (0…1) |
| 2pq | Frequency of the heterozygous genotypes (Aa), the carriers | – (0…1) |
| q² | Frequency of the homozygous recessive genotypes (aa) | – (0…1) |
Derivation & background – Hardy-Weinberg Equilibrium
Godfrey H. Hardy and Wilhelm Weinberg showed independently in 1908 that allele and genotype frequencies do not change without evolutionary factors. The genotype frequencies are the expansion of (p + q)² under random mating. Assumptions: very large population, no mutation, selection, migration or genetic drift, and random mating.
Exam blueprint
Validity range
Applies to an ideal population: very large, no mutation, selection, migration or genetic drift, and with random mating; for one gene with two alleles.
Derivation steps
Under random mating the alleles combine like the expansion of (p + q)².
- 1The allele frequencies add up to p + q = 1.
- 2Squaring: (p + q)² = p² + 2pq + q² = 1 gives the three genotype frequencies.
Rearrangements
Recessive allele frequency from the phenotype
Only the homozygous recessive phenotype (aa) has directly the frequency q².
Dominant allele frequency
Follows from p + q = 1.
Heterozygote proportion (carriers)
The factor 2 counts Aa and aA.
Task variant
16 % of a population show the recessive phenotype. Determine p, q and the heterozygote proportion.
q² = 0.16 → q = 0.4; p = 1 − 0.4 = 0.6; 2pq = 2·0.6·0.4 = 0.48, i.e. 48 % carriers. Check: 0.36 + 0.48 + 0.16 = 1.
1 in 10,000 has a recessive genetic disease. What is the carrier frequency?
q² = 0.0001 → q = 0.01; p = 0.99; 2pq = 2·0.99·0.01 = 0.0198 ≈ 2 %, i.e. about 1 carrier in 50 people.
Common mistakes
Confusing q with q².
The recessive phenotype gives q²; q is obtained only by taking the square root.
Forgetting the factor 2 in 2pq.
Heterozygotes arise in two ways (Aa and aA), hence 2pq.
Counting heterozygotes into the dominant phenotype p².
The dominant phenotype comprises p² + 2pq; only the genotype AA is p².
Assuming equilibrium despite selection or a small population.
With evolutionary factors the formula does not hold; deviations point exactly to that.
Exam context
- Typical in advanced genetics/evolution: carrier frequencies of genetic diseases and testing for equilibrium.
These mistakes cost points in real exams. The set drills them until they stick.
Formula cluster
Population genetics
Connects allele frequencies, probability and evolutionary factors.
Worked example
If 16 % of individuals show the recessive phenotype, then q² = 0.16, so q = 0.4 and p = 1 − 0.4 = 0.6. Then p² = 0.36 (36 % AA) and 2pq = 2·0.6·0.4 = 0.48 (48 % Aa). Check: 0.36 + 0.48 + 0.16 = 1.00 ✓.
Applications
Population genetics, calculating carrier frequencies for recessive genetic diseases, human genetics, evolutionary biology, detecting selection through deviation from equilibrium
Quanta exam set
Curated exam set for "Hardy-Weinberg Equilibrium":
Question (front)
Which formula describes Hardy-Weinberg Equilibrium?
Answer in your set
Question (front)
How do you rearrange p² + 2pq + q² = 1 for Recessive allele frequency from the phenotype?
Answer in your set
Question (front)
Which common mistake happens with Hardy-Weinberg Equilibrium?
Answer in your set
+ 8 more cards: units, variables, derivation, example, exam task
These 11 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 Biology formulas
Frequently asked questions about Hardy-Weinberg Equilibrium
How do you calculate allele frequencies with the Hardy-Weinberg equation?+
The easiest starting point is the recessive phenotype, because only the genotype aa is outwardly unambiguous. Its frequency equals q². Taking the square root of q² gives the frequency q of the recessive allele. The frequency of the dominant allele follows from p = 1 − q. Then all genotypes can be calculated: p² for homozygous dominant (AA), 2pq for heterozygous (Aa) and q² for homozygous recessive (aa). Example: if 16 % show the recessive phenotype, then q² = 0.16, so q = 0.4 and p = 0.6. Then 36 % are AA, 48 % Aa and 16 % aa. As a check, the three proportions always add up to 1.
Why does 2pq mean the frequency of carriers?+
A heterozygous individual carries one dominant and one recessive allele, that is Aa. Under random combination of alleles this pairing can arise in two ways: the dominant allele comes from the father and the recessive from the mother, or vice versa. Each way has probability p·q, together p·q + q·p = 2pq. That is why the factor 2 appears in the formula. These individuals are called carriers because they can pass on the recessive allele without showing it in their own phenotype. For a recessive genetic disease the carriers are genetically important, because two phenotypically healthy carriers can have an affected child with aa. A common mistake is to forget the factor 2.
Which conditions must be met for the Hardy-Weinberg equilibrium?+
The equilibrium requires an idealized population in which no evolutionary factors act. Specifically, five conditions must be met: first, a very large population so that random fluctuations of the frequencies, genetic drift, play no role. Second, no mutations that create new alleles. Third, no selection, meaning all genotypes are equally viable and fertile. Fourth, no immigration or emigration, that is no migration. Fifth, random mating, panmixia, without favouring particular genotypes. If these conditions hold, allele and genotype frequencies stay constant across generations. In nature this is never fully given, so the rule serves as a null model: if a population deviates measurably, it is a sign that an evolutionary factor such as selection is actually acting.
How do you estimate the carrier frequency of a recessive genetic disease?+
You use the known frequency of affected individuals, because this equals the frequency of the homozygous recessive genotype q². Taking the square root of q² gives q, the frequency of the disease allele. Then p = 1 − q and the sought carrier frequency is 2pq. Example: if a disease occurs in 1 of 10,000 people, then q² = 0.0001, so q = 0.01 and p = 0.99. The carrier frequency is then 2pq = 2·0.99·0.01 = 0.0198, i.e. about 2 percent or roughly 1 carrier in 50 people. Strikingly, there are many more healthy carriers than affected individuals, because the rare allele occurs mostly hidden in heterozygotes. This estimate is a standard tool of human genetics.
What does a deviation from the Hardy-Weinberg equilibrium indicate?+
If the observed genotype frequencies deviate clearly from those expected under p² + 2pq + q², at least one equilibrium condition is violated. An excess of homozygotes can indicate inbreeding or non-random mating. A shortage of a particular genotype often points to selection, when that genotype is disadvantaged. Migration that brings in foreign alleles, or a small population with strong genetic drift, also shift the frequencies. Therefore the rule is above all a null model: it provides the expected values for the case that no evolution takes place, and through the comparison makes visible whether and how a population changes. In practice one tests the deviation statistically, classically with a chi-square test, before concluding a specific evolutionary factor.
Retain Hardy-Weinberg Equilibrium for exams
Create a curated FSRS exam set for p² + 2pq + q² = 1: 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 Hardy-Weinberg Equilibrium?
Here is how to work through a typical Hardy-Weinberg Equilibrium (p² + 2pq + q² = 1) task step by step:
- 1
Task
16 % of a population show the recessive phenotype. Determine p, q and the heterozygote proportion.
Solution path
q² = 0.16 → q = 0.4; p = 1 − 0.4 = 0.6; 2pq = 2·0.6·0.4 = 0.48, i.e. 48 % carriers. Check: 0.36 + 0.48 + 0.16 = 1.
- 2
Task
1 in 10,000 has a recessive genetic disease. What is the carrier frequency?
Solution path
q² = 0.0001 → q = 0.01; p = 0.99; 2pq = 2·0.99·0.01 = 0.0198 ≈ 2 %, i.e. about 1 carrier in 50 people.
p² + 2pq + q² = 1 · 11 cards ready
Study as an exam set