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The Revolutionary Beginner's Guide to Quantum Computing: Why We Don't Have Quantum Computers Yet — and What the Geometric Alternative Offers

Rowan Brad Quni-Gudzinas

Published May 26, 2026• 0 citations
Publisher

Abstract

A 20-chapter beginner's guide to quantum computing that starts with an honest question — why don't we have quantum computers yet? The guide teaches the standard curriculum accurately, explains why the standard approach faces a thermodynamic wall (a 20,000-fold cooling gap that is Carnot-limited), and introduces the ultrametric alternative: passive geometric fault tolerance on Bruhat-Tits trees, with DOI-registered evidence, computationally validated error thresholds 75 times higher than surface codes, and three falsifiable predictions. This is the v1.2 edition (August 2026). Five quantitative statements from the May 2026 edition are corrected, each verified by an independent computation deposited with this record (artifacts/verification/verify_guide_claims.py, 35 checks, all passing; see Appendix B). Appendix A records the research program's progress since May 2026, including a trapped-ion falsifiability register, an audit of a 2026 no-go theorem on quantum error correction and quantum Darwinism, and the program's own correction on prime-valuation readings of quantum codes. This deposit includes the complete source set: manuscript, HTML, PDF, references (BibTeX), citation audit, project plan, license, and verification artifacts. v1.2.1 (August 2026): post-publication audit corrections. Chapter 20's summary now lists seven open problems (including the QEC–Darwinism tradeoff); the LHC temperature comparison is marked approximate (95×, rounded); Appendix A correction #5 completed; the citation audit's internal-reference count corrected; open problem 7 carries its numeric bound (F_L > 0.874). No quantitative claims changed. v1.2.2 (August 2026): deposit-file corrections. LICENSE now contains the full CC BY 4.0 International legal code, and README.md is the deposit manifest (a project-blueprint README was attached in v1.2.1 by an automation error). No content changes.

DOI
10.5281/zenodo.20391554

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A dichotomous Leggett–Garg witness for braid-representation density in SU(2)_k: exact at d=2, dimension-limited at d ≥ 3

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Files of this version are restricted (18 October 2026) because it was released under earlier licence terms: all files, including the source code, were under CC BY 4.0. All current versions use one clear licensing: paper, figures and data under CC BY 4.0, source code under the Apache License, Version 2.0. Please use the latest version: https://doi.org/10.5281/zenodo.20531124 Whether a temporal (Leggett–Garg) measurement can certify the computational power of an anyonic braid representation — its density in the unitary group, the property underlying universal topological quantum computation — has, to our knowledge, not been studied. We give a complete operational characterization of when the dichotomous Lüders–Leggett–Garg witness K₃ = 2 C(B) − C(B²) resolves braid-representation density across the SU(2)_k family. At d = 2 (the spin-½ fusion space) the witness resolves density exactly: it saturates the dimension-independent Lüders bound 3/2 on every dense representation and stays strictly below it on the finite ones, which on this minimal-rank, one-qubit space occur precisely at k ∈ {2,4,8} — a sharp threshold distinct from the all-rank finite set k ∈ {1,2,4} of Freedman–Larsen–Wang and Kuperberg. The k = 4 representation is structurally inert (K₃ = 1 for every measurement axis) despite a larger quantum dimension than k = 3, its braid image being finite; and k = 8 is pinned at 3/√5 (at Q = ẑ; 1.427 axis-optimized). Both follow from the underlying SO(3) geometry. At d ≥ 3 the same witness ceases to resolve density — it saturates 3/2 even on finite representations — and we trace this to the extra dimension itself, not to any particular braid angle. We frame the resulting no-go question — whether every such witness is density-blind at d ≥ 3 — as an open problem. Version notes (v1.0 → v1.1, following a comprehensive internal review of the full series): • A one-sentence correction note is added at the end of Sec. III.B: the closed-form passage stating that ẑ is a 5-fold axis at k = 8 (σ₁ = 144°) is corrected — σ₁ (144° about the measurement axis ẑ) gives K₃ = 1, not 3/√5; the value 3/√5 is realized by a distinct 72° rotation about a different tilted 5-fold axis. Fixed in both Sec. III.B and Appendix C, in the same in-text "Correction to v1.0:" format as the companion papers. 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III.D and Appendix C, matching the section's own title. Several smaller consistency and wording items from the same pass are corrected; no result, figure, or table value changes. • The d ≥ 5 scope statement is sharpened from "implied, not verified" to structural: no finite d = 5 anyon representation exists to test for k ≤ 16 (verified via an internal level sweep, k ≤ 16, not included in this deposit; the in-deposit sweep artifacts cover k ≤ 10). • The reported witness value is defined explicitly as the supremum over the braid-group image; the d ≥ 3 no-resolution result is scoped to odd d (neutral reading) with the even-d ≥ 4 neutral case noted as open. • A companion-work citation to the Fibonacci-only (k = 3) Leggett–Garg Letter (Concept-DOI 10.5281/zenodo.20372744) is added in the Introduction; a one-sentence limitation on weak/nonprojective measurement protocols is added to the Discussion; series-convention items (section numbering depth, PDF-metadata subject field) are applied. • An AI-use disclosure ("Use of AI tools") is added at the end of the paper. Four scripts that previously wrote their results only to stdout now also write JSON result files (no computation changed); the full exhaustive search additionally confirms that exactly three finite d ≥ 3 representations exist in the whole k ≤ 12 search space. • The Code and data section is qualified: the internal k ≤ 16 level sweep behind the d ≥ 5 scope statement (Appendix C) is not part of this deposit, matching the existing README disclosure. • Release date set (2026-07-22). About this series: This record is part of a series of related works from my independent research on Fibonacci anyons, with Ising anyons as their natural counterpart. I started in April 2026, and it has been a long and insightful journey in which I learned a lot; the work uses different methods and stays within verifiable, nonspeculative physics. The common thread of the series is a split: Ising anyons are limited to Clifford operations, while Fibonacci anyons are computationally universal, and across the series I map what standard witnesses of nonclassicality can and cannot certify on such systems. I consider Fibonacci anyons a serious candidate for topological quantum computing, given their universality and their topological protection against local noise. A hybrid approach with Ising is conceivable, but problems such as instability and certification would have to be solved first, and each needs research of its own. This paper resolves the split across the whole SU(2)_k family and characterizes when the temporal Leggett-Garg witness certifies the density of a braid representation, the property behind universal topological quantum computation: on the one-qubit fusion space it resolves density exactly, saturating the quantum bound on every dense representation and staying below it on the finite ones, whose inert behaviour follows from the underlying SO(3) geometry, while in higher dimensions the same witness ceases to resolve density, which is framed as an open problem; within the series it is the map that generalizes the split and supplies the mechanism behind it. Use of AI tools: In the research, processing, and writing of this paper and its results I worked together with generative AI tools, in practice a system of multiple coordinated AI instances that I set up and orchestrate (large language models, mainly Claude, by Anthropic, inside Claude Code). At their current context sizes I found it far more effective to work with several specialized instances, each with its own role and its own harness of rules and parameters that I designed and refined through feedback, than to load a single instance with all of the material; for my workflow that would have been inefficient, though this depends on the individual implementation. I lead this collaboration: I choose the research directions, set the goals, and make the final decisions in open exchange with the AI, learning actively as the work proceeds. The AI carries out the drafting, including the mathematical and technical parts, the numerical computation, and the literature search, under my direction. The AI works autonomously only task by task, within the structure I develop through feedback: it completes a task, and at open questions that need me it stops until the point is settled before the next step. Along the way I witness and take many of the decisions that shape the path, and it is common for me to spot things that need improvement. The work spans many separate runs, and a single simulation or build task alone can take up to an hour, so it could not happen all together in one autonomous run; and had I let the AI do all of it together alone, even if it is possible, it would no longer be my work but the AI's. I run multiple verifications at the different stages of the work and one before release, including cross-checks with an unrelated AI model from a different company, and all references are checked against the original sources. In the end what matters are human eyes, a principle that is itself written into the parameters of my system: I reach out to experts after publishing for review and feedback, so I learn what is solid and what must be corrected or falsified. My scripts for reproduction and review are released with this record. These tools are not authors; I am the author, and I take full responsibility for all scientific content and decisions leading to these results and their publication.

•Jun 3, 2026•0 citations
A 20-chapter beginner's guide to quantum computing that starts with an honest question — why don't we have quantum computers yet? The guide teaches the standard curriculum accurately, explains why the standard approach faces a thermodynamic wall (a 20,000-fold cooling gap that is Carnot-limited), and introduces the ultrametric alternative: passive geometric fault tolerance on Bruhat-Tits trees, with DOI-registered evidence, computationally validated error thresholds 75 times higher than surface codes, and three falsifiable predictions. This is the v1.2 edition (August 2026). Five quantitative statements from the May 2026 edition are corrected, each verified by an independent computation deposited with this record (artifacts/verification/verify_guide_claims.py, 35 checks, all passing; see Appendix B). Appendix A records the research program's progress since May 2026, including a trapped-ion falsifiability register, an audit of a 2026 no-go theorem on quantum error correction and quantum Darwinism, and the program's own correction on prime-valuation readings of quantum codes. This deposit includes the complete source set: manuscript, HTML, PDF, references (BibTeX), citation audit, project plan, license, and verification artifacts. v1.2.1 (August 2026): post-publication audit corrections. Chapter 20's summary now lists seven open problems (including the QEC–Darwinism tradeoff); the LHC temperature comparison is marked approximate (95×, rounded); Appendix A correction #5 completed; the citation audit's internal-reference count corrected; open problem 7 carries its numeric bound (F_L > 0.874). No quantitative claims changed. v1.2.2 (August 2026): deposit-file corrections. LICENSE now contains the full CC BY 4.0 International legal code, and README.md is the deposit manifest (a project-blueprint README was attached in v1.2.1 by an automation error). No content changes.
Quantum computing is stalled. Despite decades of investment, no quantum computer has solved a problem that a classical computer cannot. The standard explanation — that we need better error correction — assumes the mathematical framework itself is correct. This document argues that the framework is not correct. The assumption that quantum state space is a continuous manifold — inherited from classical physics without scrutiny — may be the root cause of the field's stagnation. Replacing the continuous manifold with an ultrametric (tree-based) geometry provides passive fault tolerance: errors are geometrically confined rather than actively corrected. This document presents the mathematical foundations, computational validation results, and a set of pre-registered falsifiable predictions. If ultrametric encoding produces the predicted error suppression, it offers a path to fault-tolerant quantum computing at 4 K with dramatically reduced qubit overhead. If it does not, the hypothesis is falsified. Either outcome advances the field.
This record bundles two engagement artifacts derived from the v1.4 register of the Trapped-Ion Ultrametric Testbed (10.5281/zenodo.22025544): (1) industry-brief-2026-08-20.md — "Why Measure Error Correlations Before Choosing a Code": a one-page brief answering whether the ultrametric quantum error-correction path is worth pursuing given its published independent-error threshold disadvantage (~55x below surface codes). The brief leads with the honest disclosure, frames the single falsifiable bet (error structure at scale is not independent), and offers four theory-neutral instruments (an 8-week trapped-ion probe, a laptop benchmark, an energy-audit template, and a QEC-Darwinism constraint checker). (2) correlated-error-benchmark-spec-2026-08-20.md — a pre-registered measurement protocol with six observables, five metrics, and three binding decision rules (including KILL-ULTRAMETRIC, which is binding on the program itself). The protocol is theory-neutral: the correlation metrics improve any code choice, ultrametric or not. Both artifacts are published as open engagement documents; the register's decision rules and kill-conditions are pre-registered. No hardware-advantage claim is made in either document.
Quantum Computing represents a transformative shift in the way we process information. Rooted in the principles of quantum mechanics—superposition, entanglement, and interference—it promises computational capabilities far beyond the reach of classical machines. Problems once considered intractable, such as large-scale optimization, cryptographic analysis, and complex system simulations, now appear within conceivable reach. This book is designed to provide a clear and structured introduction to the foundations and frontiers of quantum computing. It bridges the gap between theory and practice, guiding readers from the fundamental concepts of qubits and quantum gates to advanced topics such as quantum algorithms, error correction, and emerging quantum architectures. Mathematical rigor is balanced with intuitive explanations, ensuring accessibility for students, researchers, and professionals from diverse backgrounds in science, engineering, and computing.
Aimed at advanced undergraduate and graduate-level students, this textbook covers the core topics of quantum computing in a format designed for a single-semester course. It will be accessible to learners from a range of disciplines, with an understanding of linear algebra being the primary prerequisite. The textbook introduces central concepts such as quantum mechanics, the quantum circuit model, and quantum algorithms, and covers advanced subjects such as the surface code and topological quantum computation. These topics are essential for understanding the role of symmetries in error correction and the stability of quantum architectures, which situate quantum computation within the wider realm of theoretical physics. Graphical representations and exercises are included throughout the book and optional expanded materials are summarized within boxed 'Remarks'. Lecture notes have been made freely available for download from the textbook's webpage, with instructors having additional online access to selected exercise solutions.
Maity et al. (arXiv:2608.03944, 2026) proved a tight no-go theorem: QEC and Quantum Darwinism cannot coexist above F_L > 0.874. We audit this through Ostrowski's lens on Bruhat-Tits tree code spaces. v1.9 corrects a red-team finding: the v1.8 text conflated the full-environment theorem boundary (0.874, place-invariant) with the per-fragment model boundary (~0.80, shifted by the single-qubit fragment criterion). The no-go theorem is satisfied (chi(E)=H2(F_bare), R=0 above 0.874); the per-fragment first-redundancy boundary is at ~0.80, shifted below the threshold; the (0.80, 0.874) window is the forbidden-window artifact (alpha-sweep null, reported honestly). Three results: quantization confirmed, N_eff reduction confirmed, disciplined null result on the fidelity-resolved staircase.
Files of this version are restricted (18 October 2026) because it was released under earlier licence terms: all files, including the source code, were under CC BY 4.0. All current versions use one clear licensing: paper, figures and data under CC BY 4.0, source code under the Apache License, Version 2.0. Please use the latest version: https://doi.org/10.5281/zenodo.20531124 Whether a temporal (Leggett–Garg) measurement can certify the computational power of an anyonic braid representation — its density in the unitary group, the property underlying universal topological quantum computation — has, to our knowledge, not been studied. We give a complete operational characterization of when the dichotomous Lüders–Leggett–Garg witness K₃ = 2 C(B) − C(B²) resolves braid-representation density across the SU(2)_k family. At d = 2 (the spin-½ fusion space) the witness resolves density exactly: it saturates the dimension-independent Lüders bound 3/2 on every dense representation and stays strictly below it on the finite ones, which on this minimal-rank, one-qubit space occur precisely at k ∈ {2,4,8} — a sharp threshold distinct from the all-rank finite set k ∈ {1,2,4} of Freedman–Larsen–Wang and Kuperberg. The k = 4 representation is structurally inert (K₃ = 1 for every measurement axis) despite a larger quantum dimension than k = 3, its braid image being finite; and k = 8 is pinned at 3/√5 (at Q = ẑ; 1.427 axis-optimized). Both follow from the underlying SO(3) geometry. At d ≥ 3 the same witness ceases to resolve density — it saturates 3/2 even on finite representations — and we trace this to the extra dimension itself, not to any particular braid angle. We frame the resulting no-go question — whether every such witness is density-blind at d ≥ 3 — as an open problem. Version notes (v1.0 → v1.1, following a comprehensive internal review of the full series): • A one-sentence correction note is added at the end of Sec. III.B: the closed-form passage stating that ẑ is a 5-fold axis at k = 8 (σ₁ = 144°) is corrected — σ₁ (144° about the measurement axis ẑ) gives K₃ = 1, not 3/√5; the value 3/√5 is realized by a distinct 72° rotation about a different tilted 5-fold axis. Fixed in both Sec. III.B and Appendix C, in the same in-text "Correction to v1.0:" format as the companion papers. No numerical value changes (3/√5 was and remains correct); only the angle/element attribution is corrected. • Attribution and scope: the {2,4,8} finite-image classification is now attributed to Freedman–Larsen–Wang (the k = 8 icosahedral borderline case via Kuperberg), with Tuba–Wenzl and Rowell–Tuba added as the underlying B₃-finiteness references; the {2,4,8} finite set is qualified throughout (abstract + 8 sites) as specific to the minimal-rank, one-qubit (d = 2) fusion space, distinct from the all-rank finite set k ∈ {1,2,4}; the FLW citation is completed. • The geometric discriminator distinguishing binary (SU(2), |G| = 48/24/120) from projective (SO(3), order 24/12/60) group orders is added, together with the general sector-phase family δ*(k) = πk/(k+2) unifying the σ₁ angles at k = 2, 4, 8. • Correction (internal review pass): a statement that the state-optimized value reaches 3/2 "for any nontrivial dynamics at every d ≥ 2" contradicted the paper's own Table I (at d = 2 the k = 4 and k = 8 values are 1.0 and 1.427, not 3/2); it is corrected to d ≥ 3 in Sec. III.D and Appendix C, matching the section's own title. Several smaller consistency and wording items from the same pass are corrected; no result, figure, or table value changes. • The d ≥ 5 scope statement is sharpened from "implied, not verified" to structural: no finite d = 5 anyon representation exists to test for k ≤ 16 (verified via an internal level sweep, k ≤ 16, not included in this deposit; the in-deposit sweep artifacts cover k ≤ 10). • The reported witness value is defined explicitly as the supremum over the braid-group image; the d ≥ 3 no-resolution result is scoped to odd d (neutral reading) with the even-d ≥ 4 neutral case noted as open. • A companion-work citation to the Fibonacci-only (k = 3) Leggett–Garg Letter (Concept-DOI 10.5281/zenodo.20372744) is added in the Introduction; a one-sentence limitation on weak/nonprojective measurement protocols is added to the Discussion; series-convention items (section numbering depth, PDF-metadata subject field) are applied. • An AI-use disclosure ("Use of AI tools") is added at the end of the paper. Four scripts that previously wrote their results only to stdout now also write JSON result files (no computation changed); the full exhaustive search additionally confirms that exactly three finite d ≥ 3 representations exist in the whole k ≤ 12 search space. • The Code and data section is qualified: the internal k ≤ 16 level sweep behind the d ≥ 5 scope statement (Appendix C) is not part of this deposit, matching the existing README disclosure. • Release date set (2026-07-22). About this series: This record is part of a series of related works from my independent research on Fibonacci anyons, with Ising anyons as their natural counterpart. I started in April 2026, and it has been a long and insightful journey in which I learned a lot; the work uses different methods and stays within verifiable, nonspeculative physics. The common thread of the series is a split: Ising anyons are limited to Clifford operations, while Fibonacci anyons are computationally universal, and across the series I map what standard witnesses of nonclassicality can and cannot certify on such systems. I consider Fibonacci anyons a serious candidate for topological quantum computing, given their universality and their topological protection against local noise. A hybrid approach with Ising is conceivable, but problems such as instability and certification would have to be solved first, and each needs research of its own. This paper resolves the split across the whole SU(2)_k family and characterizes when the temporal Leggett-Garg witness certifies the density of a braid representation, the property behind universal topological quantum computation: on the one-qubit fusion space it resolves density exactly, saturating the quantum bound on every dense representation and staying below it on the finite ones, whose inert behaviour follows from the underlying SO(3) geometry, while in higher dimensions the same witness ceases to resolve density, which is framed as an open problem; within the series it is the map that generalizes the split and supplies the mechanism behind it. Use of AI tools: In the research, processing, and writing of this paper and its results I worked together with generative AI tools, in practice a system of multiple coordinated AI instances that I set up and orchestrate (large language models, mainly Claude, by Anthropic, inside Claude Code). At their current context sizes I found it far more effective to work with several specialized instances, each with its own role and its own harness of rules and parameters that I designed and refined through feedback, than to load a single instance with all of the material; for my workflow that would have been inefficient, though this depends on the individual implementation. I lead this collaboration: I choose the research directions, set the goals, and make the final decisions in open exchange with the AI, learning actively as the work proceeds. The AI carries out the drafting, including the mathematical and technical parts, the numerical computation, and the literature search, under my direction. The AI works autonomously only task by task, within the structure I develop through feedback: it completes a task, and at open questions that need me it stops until the point is settled before the next step. Along the way I witness and take many of the decisions that shape the path, and it is common for me to spot things that need improvement. The work spans many separate runs, and a single simulation or build task alone can take up to an hour, so it could not happen all together in one autonomous run; and had I let the AI do all of it together alone, even if it is possible, it would no longer be my work but the AI's. I run multiple verifications at the different stages of the work and one before release, including cross-checks with an unrelated AI model from a different company, and all references are checked against the original sources. In the end what matters are human eyes, a principle that is itself written into the parameters of my system: I reach out to experts after publishing for review and feedback, so I learn what is solid and what must be corrected or falsified. My scripts for reproduction and review are released with this record. These tools are not authors; I am the author, and I take full responsibility for all scientific content and decisions leading to these results and their publication.