A Quantum Approximate Optimization Algorithm — TEI-tagged view

Edward Farhi, Jeffrey Goldstone, Sam Gutmann · 2014 · quantum-computing · arXiv:1411.4028 · full text at the source · TEI xml · tagged edition · index · concepts · authors
Where this record's text came from. faceted 2026-08 by reading the locally held text (pdftext); every evidence string verified as an exact substring of that text before merging. METADATA MISMATCH: the queue entry is titled 'A Quantum Approximate Optimization Algorithm' (Farhi, Goldstone, Gutmann 2014, arXiv 1411.4028), but the article text below the quote line is a different paper — 'Analog Quantum Approximate Optimization Algorithm' by Barraza, Alvarado Barrios, Peng, Lamata, Solano and Albarrán-Arriagada (arXiv 2112.07461v2), which cites Farhi et al. as reference [14]. All facets here describe the text that is actually in the file, per the rule to quote only from below the line; the id is kept as given. Only one claim_relation is recorded: the paper also explicitly distinguishes itself from shortcuts-to-adiabaticity techniques ("our AQAOA algorithm is not a shortcut to adiabaticity (STA) technique"), but 'distinguishes-f | 2026-08-09: the staged full text was a different paper (arXiv 2112.07461, Barraza et al., "Analog QAOA"). Re-staged from arXiv 1411.4028v1; 11 of 16 stored excerpts re-verified against it, 5 traced to the wrong paper and deleted. Update, 12 August 2026: claim type, phenomenon and method (with their evidence) were BLANKED. They had been read from arXiv 2112.07461 (Barraza et al.), whose text stood in this record's place until the 2026-08-09 restaging; that pass replaced the text and deleted five quotes but left these facets. The record is queued to be re-read from the correct text. Other layers were left alone - they are not shown to be wrong. Update, 18 September 2026: this record was later re-read from the correct text, Farhi, Goldstone and Gutmann (2014); its quotes all verify against that paper; one concept term, 'variational algorithm', dates from the earlier reading and does not occur in it. The sentences above about the analog paper record what happened before the re-staging.
Some words in these quotes contain the wrong character. The PDF this text was extracted from substituted 5 characters inside a word — a currency sign or a stray accent where a letter pair belongs, as in signi¢cantly for significantly, or a single ligature glyph, as in confidence. They are valid characters in the wrong place, so they survive every encoding check. The quotes keep them for the same reason as above, and a search of this page will not find the affected words.
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Other fields define these differently the same word, defined another way in another discipline
algorithm 5 fields · standard-deviation 3 fields
Tags on this paper every tag the record carries, whether or not the words occur in the text below — a number is how many papers in the corpus carry that tag; a tag with no number is unique to this paper
quantum algorithm3 combinatorial optimization2 qubit2 MaxCut QAOA2 approximation ratio2 classical algorithms circuit depth2 mathematical-proof27
Method, as described: algorithm-design-and-proof

Our tag layer for this paper

Cross-disciplinary analysis
content-tags & facets: phenomenon · claim-type · cross-domain-transfer · mechanism · claim-relation · replication-status · limitation — grounded in the full text
phenomenonapproximate solutions to combinatorial optimization problems— “Approximate optimization asks for a string z for which C(z) is close to the maximum of C.”
claim-typemethod— “The QAOA can be run on a quantum computer with p growing with n as long as there is a strategy for choosing sets of angles.”
method — evidence— “It is possible to analyze the performance of the QAOA for p = 2 on 3-regular graphs.”
mechanismTHE WHOLE ALGORITHM IS ONE INTEGER KNOB: the state is built by alternating two operators p times over a uniform starting superposition, and the paper's claim is that the quality of the approximation improves as p is raised— “We introduce a quantum algorithm that produces approximate solutions for combinatorial op- timization problems. The algorithm depends on an integer p ≥ 1 and the quality of the approx- imation improves as p is increased.”mechanisms[0]
mechanismthe first operator is made diagonal in the computational basis, which buys two things at once - every term in the product COMMUTES, and each term's locality is no worse than the locality of the clause it came from— “All of the terms in this product commute because they are diagonal in the computational basis and each term’s locality is the locality of the clause α .”mechanisms[1]
mechanismTHE PARAMETER RANGE IS DERIVED FROM A PROPERTY OF THE OBJECTIVE, NOT CHOSEN: because the objective has integer eigenvalues, one angle can be restricted to lie between 0 and 2 pi— “Because C has integer eigen- values we can restrict γ to lie between 0 and 2 π.”mechanisms[2]
mechanismMONOTONICITY IS STRUCTURAL RATHER THAN EMPIRICAL: the maximisation at p minus one IS a constrained maximisation at p, so the best value at each depth can never fall below the best value at the depth beneath it— “Note that the maximization at p − 1 can be viewed as a constrained maximization at p so Mp ≥ Mp−1. (9)”mechanisms[3]
mechanismthe algorithm is used by repetition rather than by a single shot: measure in the computational basis, evaluate the objective on the string obtained, and repeat with the SAME angles - enough repetitions produce a string whose value is very near or above the expectation— “Use the quantum computer to get the state |γ , β ⟩. Measure in the computational basis to get a string z and evaluate C(z). Repeat with the same angles. Enough repetitions will produce a strin g z with C(z) very near or greater than Fp”mechanisms[4]
mechanismthe authors name the difficulty rather than presenting the method as complete - it is not obvious in advance how to pick good angles - and for p that does not grow with n they offer a search over a fine grid on the compact parameter set— “The rub is that it is not obvious in advance how to pick good angles. If p doesn’t grow with n, one possibility is to run the quantum computer with angles (γ , β ) chosen from a fine grid on the compact set [0 , 2π]p × [0, π ]p, moving through the grid to find the maximum of Fp.”mechanisms[5]
mechanismthe grid search is made tractable by a BOUND ON THE PARTIAL DERIVATIVES of the objective's expectation, which is what turns a search over a continuous compact set into an efficient one— “Since the partial derivatives of Fp(γ , β ) in (7) are bounded by O(m2 + mn) this search will efficiently produce a string z for which C(z) is close to Mp or larger.”mechanisms[6]
mechanismfor fixed p and bounded clause participation the angles are found by an EFFICIENT CLASSICAL CALCULATION rather than by quantum search, and those angles are then used to run the quantum computer and produce the measured string— “However we show in the next section that if p does not grow with n and each bit is involved in no more than a fixed number of clauses, then there is an e fficient classical calculation that determines the angles that maximize Fp. These angles are then used to run the quantum computer to produce the state |γ , β ⟩ which is measured in the…mechanisms[7]
mechanismTHE CONSTRAINT IS ENFORCED BY THE BASIS: for the independent-set variant the orthonormal basis consists only of strings that correspond to independent sets, so the space is exponentially large but smaller than the full 2^n, and is NOT a simple tensor product of qubits— “The Hilbert space for our quantum algorithm has an orthonormal ba sis |z⟩ where z is any string corresponding to an independent set. In cases of interest , the Hilbert space dimension is exponentially large in n, though not as big as 2 n. The Hilbert space is not a simple tensor product of qubits.”mechanisms[8]
mechanismthe mixing operator is likewise restricted rather than penalised: it is the adjacency matrix of the hypercube confined to the legal strings, so the walk it generates can only ever move between independent sets— “Note that B is the adjacency matrix of the hypercube restricted to the legal s trings, that is, those that correspond to independent sets in the given graph.”mechanisms[9]
builds-on the quantum adiabatic algorithm— “There is an adiabatic path (which stays at th e top of the spectrum throughout) with run time T that achieves this as T goes to infinity.”claim_relations[0]
sensethe approximation ratio - AS OUTPUT OVER OPTIMUM: the quantity reported is the objective value at the algorithm's own output divided by the true maximum, so it is a ratio against a quantity that must already be known to state it— “ratio is C(z), where z is the output of the quantum algorithm, divided by the maximum of C”senses[0]
sensethe algorithm's names - ITS OWN ACRONYM SURVIVED AND A SECOND NAME WAS ADDED LATER: the paper calls it the QAOA throughout - its expanded name survives only inside a damaged sentence - while the word the field now uses for its class, variational, appears nowhere in itsenses[1]
sensep - THE ONE KNOB, AND IT SETS BOTH SIDES OF THE TRADE: the paper introduces the algorithm as depending on an integer p, with quality improving as p rises and circuit depth rising with it, so a result quoted without its p is not a result about this algorithmsenses[2]
auditQAOA —contrasted-with→ classical algorithms — Audit 2026-09-28: DOUBTFUL - read against its full span and kept, but endpoint by anaphora: 'This p = 1 result' = the QAOA's result (previous sentence).concept_edges[1]
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Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
limitations[0]
for which uselimitation — the p = 1 performance reported here for 3-regular graphs: the authors state it
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limitations[1]
for which uselimitation — any extrapolation from p = 1 to larger p: the authors state the p = 2 case on 3-regular graphs is more complicated and that they show only partial results for it
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limitations[2]
for which uselimitation — the claim that approximation quality improves with p: the depth of the circuit grows linearly with p times, at worst, the number of constraints, so the two move together
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limitations[3]
for which uselimitation — results reported at p = 2 on 3-regular graphs: the authors state the algorithm at that depth cannot detect whether the graph is bipartite, that is, completely satisfiable
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limitations[4]
evidence status notemechanism — 2026-08-16: A WORD IS SPLIT BY A SPURIOUS SPACE INSIDE THIS QUOTE - "approx- imation" for "approximation". The extraction inserts a space at what was a line break in the PDF, and it does this throughout this file. The quote is an exact substring of the staged text and the meaning is unaffected, but A READER SEARCHING FOR THE UNBROKEN WORD WILL NOT FIND IT, which is the whole reason this is recorded. No pattern in our tools detects it: both halves of a broken word are plausible tokens, so it is invisible to every guard and was found by eye.
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mechanisms[0]
evidence status notemechanism — 2026-08-16: A WORD IS SPLIT BY A SPURIOUS SPACE INSIDE THIS QUOTE - "eigen- values" for "eigenvalues". The extraction inserts a space at what was a line break in the PDF, and it does this throughout this file. The quote is an exact substring of the staged text and the meaning is unaffected, but A READER SEARCHING FOR THE UNBROKEN WORD WILL NOT FIND IT, which is the whole reason this is recorded. No pattern in our tools detects it: both halves of a broken word are plausible tokens, so it is invisible to every guard and was found by eye.
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mechanisms[2]
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Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
mechanisms[4]
evidence status notemechanism — 2026-08-16: A WORD IS SPLIT BY A SPURIOUS SPACE INSIDE THIS QUOTE - "an e fficient" for "an efficient". The extraction inserts a space at what was a line break in the PDF, and it does this throughout this file. The quote is an exact substring of the staged text and the meaning is unaffected, but A READER SEARCHING FOR THE UNBROKEN WORD WILL NOT FIND IT, which is the whole reason this is recorded. No pattern in our tools detects it: both halves of a broken word are plausible tokens, so it is invisible to every guard and was found by eye.
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mechanisms[7]
evidence status notemechanism — 2026-08-16: A WORD IS SPLIT BY A SPURIOUS SPACE INSIDE THIS QUOTE - "an orthonormal ba sis" for "an orthonormal basis". The extraction inserts a space at what was a line break, throughout this file. Separately, this span was NARROWED: it originally ran through equation (39), whose large brace is stored as Private Use Area codepoints U+F8F1-U+F8F3. An internal tool refused it; the merge gate's dry run had reported it clean.
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mechanisms[8]
replicationuntested
limitationthe classical preprocessing to choose the angles can require space doubly exponential in p
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limitations[0]
limitationThe authors state their headline result is beaten by classical methods already known.
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limitations[1]
limitationThe next case up is analysed only partially, and the paper says so.
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limitations[2]
limitationThe cost of the improvement is circuit depth, which grows with the same knob that buys the quality.
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limitations[3]
limitationThere is a property of the input the algorithm at p = 2 is stated to be unable to see at all.
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limitations[4]
Content tags
content-observations: finding · quantity · variable · definition · key-term — grounded in the full text
findingThe approximation ratio can be made arbitrarily close to 1 by making p large enough, independent of n.
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content_tags.findings[0]
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findingFor MaxCut on 3-regular graphs at p=1, QAOA guarantees a cut at least 0.6924x the optimum.
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content_tags.findings[1]
quantity0.6924 — guaranteed approximation ratio for MaxCut on 3-regular graphs at p=1
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content_tags.quantities[0]
quantity2p angles — variational parameters (γ, β) defining the depth-p QAOA state
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content_tags.quantities[1]
variableapproximation ratio (dependent)
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content_tags.variables[1]
evidence status notevariable — QUOTE RECOVERED FROM THE PAPER'S OWN CHARACTERS. The recorded quote was LETTERS-ONLY IDENTICAL to this stretch of the staged text but not an exact substring of it - spaces, hyphens, ligature glyphs or mathematical operators differed, so it could never anchor. This is the file's own text between the same two letters: not produced by a rule about the damage, copied out of the file. Round-trip checked (the recovered span is letters-only equal to the original) and length-checked. The text as originally recorded is kept in evidence as extracted.content_tags.variables[1]
definitioncombinatorial optimization problem
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content_tags.definitions[0]
definitionMaxCut
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content_tags.definitions[1]
evidence status notedefinition — QUOTE RECOVERED FROM THE PAPER'S OWN CHARACTERS. The recorded quote was LETTERS-ONLY IDENTICAL to this stretch of the staged text but not an exact substring of it - spaces, hyphens, ligature glyphs or mathematical operators differed, so it could never anchor. This is the file's own text between the same two letters: not produced by a rule about the damage, copied out of the file. Round-trip checked (the recovered span is letters-only equal to the original) and length-checked. The text as originally recorded is kept in evidence as extracted.content_tags.definitions[1]
key-termsquantum, algorithm, optimization, circuit, MaxCut, graphs, unitary, objective, combinatorial
Concepts
terms this paper carries, each with the sentence it was cut from — the layer that joins one paper to another. Terms with no quote yet are on CONCEPTS.html.
conceptMaxCut
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concepts[4]
conceptQAOA
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concepts[5]
conceptapproximation ratio
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concepts[6]
conceptclassical algorithms
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concepts[7]
conceptcircuit depth
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concepts[8]
Statistics — cross-field join keys
field-invariant statistical terms, used in their statistical sense (gated on a number / symbol / test). A p-value or a standard deviation means the SAME thing in physics, biology, psychology and sociology — so these are the strongest cross-field join keys. Grounded verbatim.
mean μ as written: mean of
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content_tags.statistics[0]
standard-deviation SD/σ
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content_tags.statistics[1]

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