Future Topics for My Writing on Quantum Computing

Jack Krupansky
Oct 8, 2019 · 28 min read

This informal paper lists some of the topics I expect to be writing on related to quantum computing in the coming months and years.

First, here’s a full list of my existing writing related to quantum computing:

I have no idea in what order I’ll tackle my remaining ideas. In fact, I commonly come up with other topics and write about them first.

Readers should feel free to comment on what they would find most helpful in the near term. And suggest additional topics as well. And also cite existing online writing which might seem to at least partially satisfy any of the listed topics.

There is no particular order to this list, just as they came to mind and as I collected them from old notes.

Currently I am doing a fair amount more reading and research than writing, particularly on the quantum mechanics and physics side of the house, but I hope to get back to writing more purely about quantum computing within a few months. Or not — I may take a longer break, three months, six months, a year, or maybe even 18 months to give the field time to catch up with my writing.

I have already written fairly extensively on many of these topics, but my real goal is to take it to the next level, the next level of depth. There’s too much superficial hype, useless jargon, and extraneous detail floating around; my goal is to dig down to real, actual ground truth. And to limit myself to plain language to the maximal extent possible.

In a lot of cases I don’t yet know enough to write with any true sense of authority. I view research, reading, and writing as one integrated super-activity. If I find that I have gaps in knowledge when writing, that motivates me to do more reading and research to endeavor to fill those gaps. Writing is a good test of how complete and deep your knowledge really is.

Ultimately, I think I’d like to see 50 to 100 “What is…?” papers to cover the breadth of key concepts of quantum computing. That might be suited to be a full book, but I’m more interested in having easily digested chunks of free online material than a physical book.

There is another, shorter, list at the end of topics that I have no intention of writing about.

This is a living list and will grow on an almost-daily basis.

Without further ado, here is the list of topics:

  1. FAQ. I’ve catalogued quite a few questions, but answers are needed. I already have many answers at least at a superficial level, but I want to get to the bottom of things, to ground truth before trying to sound authoritative. The FAQ will contain only relatively brief answers, and link to individual papers which have much more expansive detail on the topic, if necessary.
  2. Glossary for quantum computing. I already have one, but it is too-comprehensive — only 3,000 entries, and is more of a comprehensive dictionary than a brief glossary. May need different glossaries for different audiences (personas.) Something on the order of 50 to 100 terms would be ideal. In addition, my current glossary has many TBD entries which still need to be fleshed out.
  3. Personas, use cases, and access patterns for quantum computing. Who, what, and how for the use of quantum computers. Including managers, executives, non-quantum technical staff, IT service staff, scientists, engineers, operations staff (e.g., those seeking optimization), marketing, sales, technical support, etc. I’ve written such a categorization for databases and cybersecurity; every field could use one.
  4. Tutorial. Plural, for different audiences, personas, use cases, and access patterns. Actually, I have no intention of doing such writing for the foreseeable future since I’m more focused on ideas, principles, and theory than hands-on usage. Still, at some stage I may be tempted to do at least some kind of tutorial. Meanwhile, I expect that much of my writing will be usable for an introduction to many facets of quantum computing.
  5. What is quantum ready? Seems a bit vague and ambiguous. Needs a crisper presentation. Existing focus seems to be on users being ready for the future and some not-yet-existent future technology rather than existing technology being ready for clear and existing use cases. So, it’s more of a marketing pitch for the most part. Still, some are likely to be confused about it, so it is worth pointing out in detail what it is not.
  6. Are current quantum computers really quantum ready?
  7. Current quantum computers are not really quantum ready
  8. Are current quantum computers really ready for quantum ready?
  9. What are the criteria for a quantum computer to be quantum ready?
  10. For what personas and use cases are current quantum computers quantum ready?
  11. Which personas are most ripe for quantum ready?
  12. What are the stages for quantum readiness for the various personas and use cases?
  13. Will understanding of current quantum computers really help that much if and when the technology evolves substantially over the next five to ten years?
  14. Might most organizations be much better off by waiting for the ENIAC moment if not the FORTRAN moment before even dipping a toe into the waters of quantum computing? Might the ENIAC moment and the FORTRAN moment be better standards to judge the onset of the Quantum Ready era? Unless of course an organization has one or more teams of Lunatic Fringe personas who can handle any and all technologies no matter how difficult and undeveloped.
  15. What are appropriate demonstration projects for quantum computing?
  16. What are the advantages of quantum computing? Only two: the exponential speedup of quantum parallelism and probabilistic computation rather than strict determinism (true random numbers as an intrinsic feature rather than requiring an external source of entropy).
  17. Where is quantum computing as of <today>? Status update every few months. Not all the gory details but just an overall report card for progress towards mainstream adoption.
  18. Is quantum computing still at the stage of basic research, experimentation, and waiting? IOW, not close to being ready for mainstream adoption? Is it even ready for the Lunatic Fringe yet? We’ll be at this stage for the foreseeable future — research and experimentation will advance, but “Waiting for Quantum” will be the M.O. for most organizations.
  19. What’s next for quantum computing as of <today>? Companion to “Where is quantum computing…” Focus on 6–12 month outlook. Update several times a year, as advances occur.
  20. How close to the ENIAC moment are we as of <today>?
  21. How close to the FORTRAN moment are we as of <today>?
  22. Are quantum computers still only usable by the Lunatic Fringe as of <today>?
  23. What big breakthrough would open up the floodgates for quantum computing?
  24. What is the maximal number of qubits which can be simulated using classical processors? Somewhere in the 48 to 53 range?
  25. What is a quantum computer? Short and sweet, but very, very precise. Still too many areas which are more than a bit foggy. Of one thing I am certain: Nobody needs another puff piece on quantum computing. The difficulty is that it’s problematic to reach many different audiences with one paper.
  26. What is quantum computing? Both hardware and software. Lots of superficial and misleading puff pieces out there.
  27. What is quantum computing? Ditto, but the software more than the hardware. Lots of superficial and misleading puff pieces out there.
  28. Introduction to quantum computing. Alternate title.
  29. What are the basics of quantum computing? Not a puff piece, but solid information. How does quantum parallelism actually work — how do you use it?
  30. Hello World program for quantum computing. No clue what it should really look like. A single X or H gate might suffice, but my inclination is that it should be the simplest program which shows a practical example of quantum parallelism with results that most people can understand. Something that inspires people to say “Wow, that’s cool!
  31. Need 4–6 introductory algorithms that have obvious practical application to replace the current introductory algorithms which do not have obvious practical application. Hello World quantum program could be one of them, or incorporate one of them. And probably at least one quantum program which incorporates at least two if not three of the algorithms. Focus on algorithmic building blocks.
  32. What are the 5–100 concepts which must be understood to understand the power of quantum computing? Unclear how many or even what the minimal list is.
  33. What are the 500 to 1,000 concepts which must be mastered to master quantum computing?
  34. What is quantum computation? The terminology can get confusing.
  35. What does a quantum algorithm look like?
  36. What does a quantum program look like?
  37. What does a quantum application look like?
  38. What is a quantum circuit? No, it’s not hardware.
  39. What is hybrid quantum computing?
  40. What is quantum parallelism? This is probably the single most important topic.
  41. What is quantum mechanics?
  42. What is quantum communication? The world of Bob and Alice.
  43. No, quantum computing and quantum communication are not the same thing.
  44. What is quantum networking? Doesn’t exist yet, but hypothetically.
  45. What is quantum information science? Quantum computing and quantum communication, and eventually quantum networking. And who knows what else in the more distant future.
  46. What is quantum information? Tricky. Lots of hype. Qubits vs. quantum state vs. subset of quantum state. No definitive definition.
  47. Quantum information theory. New concept, or at least a new term. No clear definition.
  48. Does it make sense to contemplate quantum storage? Hypothetically. Qubits are quantum “storage” technically, but they can’t be read, copied, or moved around freely as with bits in classical storage. Still, an interesting topic to contemplate for the more distant future.
  49. What is a qubit? Seems obvious, but there is plenty of nuance. A treatment is needed that is functionally complete and easy to understand. In plain language.
  50. What is quantum state?
  51. What can I do (and not do) with a qubit?
  52. How does a qubit work? Partially independent of physical technology, but partially dependent on the particular physical technology.
  53. Is a qubit comparable to the transistor of classical computing?
  54. A qubit is comparable to a flip flop in classical computing. It can hold one unit of information (quantum state) and operate on it.
  55. A qubit and a bit are not comparable — one is a hardware device and the other is information
  56. A qubit is a storage and processing device for quantum state rather than being information per se
  57. What is a quantum gate (or quantum logic gate)? Not hardware, comparable to classical software operation or instruction.
  58. What is a quantum circuit? Sequence of quantum logic gates, a quantum program.
  59. What is a quantum program? Basically the same as a quantum circuit, although a quantum circuit could be embedded in a larger quantum circuit — a fraction or portion of the larger quantum circuit, while a quantum program is the totality of what a quantum computer is given to execute, with measurements of qubits to be returned as “results.”
  60. What is measurement? Capture the final state of a qubit upon completion of a quantum program, to be passed back to the classical application which invoked the quantum program. Captures either a binary 0 or a binary 1 even if the qubit has some more complex quantum state.
  61. What is a quantum application? A classical application which utilizes one or more quantum programs (circuits.)
  62. What constitutes a “working” quantum computer? Such as a minimum number of qubits, minimum coherence time, and degree of connectivity. This is an evolving standard — at one time even a single “working” qubit was a super-big deal. Or even 5 or 8 qubits. Now, is 53 really enough to “work” on real-size real-world problems? 128? 256? Or is coherence time the main limiting factor? Or connectivity? Still, the term gets used and thrown around far too casually, begging for clarification.
  63. What is linear algebra?
  64. How much physics do you need to know to understand the basics of quantum computing?
  65. How much physics do you need to know to master quantum computing?
  66. How much quantum mechanics do you need to know to understand the basics of quantum computing?
  67. How much quantum mechanics do you need to know to master quantum computing?
  68. What is bra-ket notation?
  69. Three interpretations of Schrödinger’s cat. Ignorance (one and then the other but we don’t know when the transition occurs), absolutely simultaneous (both at all times until observed), and oscillating (random or periodic between the two until observed.) Which interpretation applies to quantum mechanics and quantum computing? And likely none are absolutely correct. The original model does not take into account asymmetric probability amplitudes. Applying real-world examples to the world of quantum mechanics may never be exactly correct.
  70. What are the key concepts of quantum mechanics?
  71. How much linear algebra do you need to know to understand the basics of quantum computing?
  72. How much linear algebra do you need to know to master quantum computing?
  73. How much number theory do you need to understand to understand advanced quantum algorithms? Such as using order-finding (period-finding), including Shor’s algorithm.
  74. What are eigenstates, eigenvectors, and eigenvalues?
  75. What are the eigenvalues for a qubit? The basis states or the probability amplitudes?
  76. What are the eigenvalues for entangled qubits? The computational basis states or the probability amplitudes?
  77. What is probability amplitude?
  78. What are pure states and mixed states?
  79. How do you debug a quantum application?
  80. How effective are quantum simulators for debugging quantum circuits? Are quantum simulators the answer for most common debugging issues?
  81. Trick for debugging on a real quantum computer. Already described in The Greatest Challenges for Quantum Computing Are Hardware and Algorithms. Can effectively single step by executing only the first k gates and then measuring, then reset and execute the first k+1 steps and measure again, rinse and repeat. Rerun each k steps some number of times to get a statistically valid sample of how stable qubit values are at each step. Can apply the same technique to both physical and simulated quantum computers, although with a simulator the quantum state could be examined without collapse, so rerun would not be needed, although still need repetitions for statistically valid results.
  82. What criteria should be used to judge the quality of quantum code?
  83. How should quantum code be commented?
  84. What is quantum computational chemistry? Sometimes just quantum chemistry or computational chemistry and in contrast to classical computational chemistry. Read Quantum computational chemistry by McArdle, et al for more in-depth treatment.
  85. Glossary for quantum computational chemistry
  86. What is VQE?
  87. What is a variational quantum eigensolver?
  88. What is quantum simulation?
  89. What is the difference between quantum simulation and a quantum simulator? The former is a simulation of quantum physics on a quantum computer, while the latter is simulating a quantum computer and quantum circuit on a classical computer. Still, people get confused and conflate them.
  90. What are the key features of a quantum simulation?
  91. What criteria must an application meet to be appropriate for a quantum computer?
  92. When is and when isn’t quantum computing appropriate for an application?
  93. What is computational diversity? Applications which utilize a variety of computing methods — some combination of classical digital software, analog signal processing, quantum computation, GPUs, FPGAs, and possibly even custom hardware.
  94. How many qubits will be needed before we see a significant quantum application? To reach the ENIAC moment.
  95. What is a quantum resource? Superposition, entanglement, interference, quantum parallelism.
  96. What benefits does quantum superposition provide?
  97. What’s really going on with superposition? How does it really work, under the hood.
  98. What benefits does quantum entanglement provide?
  99. What is the precise phenomenological mechanism for entanglement? How does it really work, under the hood.
  100. What benefits does quantum interference provide?
  101. How does quantum interference really work, under the hood?
  102. What are the theoretical limits of quantum computing?
  103. What are the practical limits of quantum computing?
  104. How quantum computing has given me a much deeper appreciation of the power of classical computing. Quantum computing may do a few things much better (quantum parallelism, probabilistic computing, generation of random numbers), but classical computing has so many features to offer than are not available in quantum computing, yet. At best, a quantum circuit is no more than a simple code block in a classical program.
  105. Will quantum Fourier transforms work for a large number of qubits? See Shor. Banding or approximate FFTs work, sort of, but will they have enough precision for applications needing a fairly deterministic result, such as factoring of large numbers for Shor.
  106. What qualities are needed for a true quantum programming language?
  107. What are the criteria for a quantum high-level language? Some interesting high-level abstractions which can automatically be translated or compiled into raw quantum circuits. Ability of the compiler to optimize across those high-level abstractions, and even to optimize globally. The abstractions should be semantically rich so that many common mistakes or misuses can be detected and reported by the compiler. Some sort of quantum data types are needed, which can be compiled into qubits.
  108. What is the programming model for quantum computing?
  109. What criteria must a programming model have to be suitable for quantum computing?
  110. Is quantum computing a model which only a physicist could love?
  111. Is D-Wave a true general-purpose quantum computer?
  112. When is D-Wave a better choice than a gate-based quantum computer?
  113. What is a gate-based quantum computer?
  114. What is NISQ? How noisy?
  115. What are NISQ and FTQC devices? How fault-tolerant?
  116. Do we really need quantum error correction (QEC)? Or can we just ride the wave of steadily improving qubit quality?
  117. Is there a happy medium between NISQ and FTQC devices?
  118. What is quantum error mitigation?
  119. Is nearest-neighbor connectivity a major limitation, just an annoyance, or a non-problem?
  120. Hype about quantum computing. Most of what I write is intended to dispel hype about quantum computing as it is. Is all hype harmful? Is any hype beneficial
  121. Is hype about quantum computing deterring meaningful progress?
  122. To what extent can we project quantum computing based on the historical trajectory of classical computing?
  123. Parallels to the evolution of computers in the 1940’s, 1950’s, 1960’s, 1970’s, and 1980’s. Dramatic changes, sometimes leaps, sometimes gradual incremental advances. Significant changes in underlying technologies.
  124. What does the future hold for quantum computing?
  125. Need for much-higher performance and much-higher accuracy in quantum computer simulators. Possibly even using massively parallel classical supercomputers, with thousands of processors, to get as far as we can, especially until we have more powerful quantum computers with enough qubits and long enough coherence. Possibly using GPUs and FPGAs, or even full-custom hardware.
  126. Are we on the verge of entering a dark age for quantum computing where competitive companies and secretive government agencies which have a proprietary or security interest in secrecy will be reluctant to publicly and transparently publish their quantum accomplishments? Both hardware and algorithms. Or, they may publish some of their work, but sanitized to hide the most significant work.
  127. Quantum computer as a coprocessor. Much of the processing for a typical application — or even something such as Shor’s algorithm — must be performed on a classical computer, with a quantum circuit (or quantum program) simply a “subroutine” called in the middle of overall processing.
  128. Is a quantum computer merely a quantum calculator? The coprocessor model. Merely a single block of code rather than a full program or application with no control structures, data structures, nested function calls, rich data types, I/O, database access, or network access.
  129. What does it mean to have a quantum computer in the cloud?
  130. What potentially new applications might quantum computing enable or outright create rather than existing applications it can be applied to? Of course, who could possibly know in advance. Consider as basic research. Apply this principle to algorithms as well as machines and applications. Who knew what applications the telephone, TV, or the Internet would eventually enable?
  131. Characteristics of algorithms to document. Qubit requirements. Connectivity requirements — is nearest-neighbor enough, big-O for swaps needed based on input size. Coherence needed — big-O for gates based on input size.
  132. Algorithmic building blocks, design patterns, quantum circuit libraries, and quantum application frameworks. Building blocks for quantum programs. More semantically meaningful than raw, low-level quantum logic gates.
  133. What are the most important algorithmic building blocks for quantum applications?
  134. What are the physical concepts of quantum computing? But abstracted away from particular implementations. And maybe separately link from each physical abstraction to each concrete physical conception.
  135. What is a computational basis state?
  136. What is a computational basis?
  137. How is each distinct computational basis state of an n-qubit ensemble represented physically? Using energy? Or some other physical phenomenon? If n qubits subjected to n Hadamard gates have 2^n computational basis states, how are all of those computational basis states represented, physically? If by energy, that’s a huge amount of energy. Or, are computational basis states merely a bookkeeping fiction, and if so, what do they really stand in for, physically?
  138. What is a Hilbert space? Does the average user need to know? If so, what exactly do they need to know?
  139. What can and can’t the Bloch sphere tell you about quantum computing?
  140. What are the merits and limits of the various technologies for implementing quantum computers?
  141. How much can a layperson understand about quantum computing?
  142. Need for algorithm design guidelines. What factors to keep in mind when designing quantum algorithms.
  143. Need for guidelines for problem decomposition to develop a quantum algorithm. What opportunities to look for to exploit the capabilities of quantum computing, primarily quantum parallelism.
  144. Design and development process and tasks for quantum algorithms
  145. How can we understand quantum computing when there are no classical analogs? Actually, we have plenty of analogs from the real world that don’t fit cleanly into classical computing. And we do implement many of them using classical computing, just not very efficiently.
  146. Quantum supremacy for one application does not imply quantum supremacy for any other applications
  147. Will any of the current crop of quantum computing hardware technologies be the one which achieves broad quantum supremacy, across a wide range of practical applications, or has that ultimate hardware technology not yet been invented?
  148. When can we expect to see quantum supremacy for a practical problem? Business, science, engineering, finance.
  149. What is the smallest quantum computer which will solve a practical problem? Number of qubits, length of coherence. May imply quantum supremacy. Or maybe simply easier to implement than a classical solution. Maybe a classical solution is available, but requires hundreds or thousands of processors.
  150. What is a quantum Fourier transform (QFT)? For that matter, what is a Fourier transform (or discrete Fourier transform)? Why does it matter, and when can and should a QFT be used? How does an algorithm have to be designed or adapted to utilize a QFT? What are the limits?
  151. What is a resonator?
  152. How is a qubit read? Measured.
  153. How are two qubits entangled?
  154. What is quantum coherence?
  155. What is quantum decoherence?
  156. How reliable do qubits need to be to solve a wide range of practical problems?
  157. What is the minimum quantum coherence of qubits needed to solve a wide range of practical problems?
  158. Need for a free, online, interactive quantum computer simulator. And nice to integrate that with the option to run on a real, physical quantum computer as well, with the same user interface. There actually are some.
  159. How good are quantum simulators?
  160. How fast are quantum simulators?
  161. What does it mean that quantum computing is probabilistic rather than deterministic?
  162. How many repetitions of a quantum circuit are needed to assure that an accurate result is captured? What formula or rule of thumb to use to calculate.
  163. What is computational complexity and Big-O? Or algorithmic complexity.
  164. What are BQP and QMA and which is better and why? Bounded-probability quantum polynomial complexity class, quantum Merlin-Arthur complexity class. BQP vs. QMA == P vs. NP. P and BQP are “efficient” while QMA and NP are not — polynomial vs. exponential (or worse.)
  165. Complexity classes
  166. Quantum computing for technical managers. Not the details about quantum algorithms, but enough to facilitate the management of technical teams who are deep in the details.
  167. Quantum computing for non-technical managers.
  168. Quantum computing for technical executives.
  169. Quantum computing for non-technical executives.
  170. Quantum computing for IT staff. They’re not deep into details of quantum circuits, but they need to plan, deploy, support, and maintain infrastructure to support quantum computing.
  171. Quantum computing for senior classical algorithm designers. What conceptual framework do they need to change their mindset?
  172. Quantum computing for entry level quantum software engineers. They are free of the baggage of classical computing (for the most part, and lacking an emotional commitment to it.) Quantum computing from scratch. Very clean. Devoid of casting quantum computing in terms of classical computing — no “It’s like a classical 0 and 1, but…”
  173. Quantum computing for technical journalists. Definitely a need for this!
  174. Quantum computing for non-technical journalists. Definitely a need for this!
  175. Quantum computing for policymakers. Government types. Definitely a need for this!
  176. Budgeting for quantum computing. Especially for moving from experimental stage to production-scale operations.
  177. What is a unitary transformation? Or unitary transform, or unitary matrix.
  178. Why must a quantum computation be reversible?
  179. Relationship between quantum logic gates and unitary transformations
  180. Which unitary transformations are permitted and which are prohibited?
  181. Why must a quantum computation be reversible?
  182. What is phase?
  183. Why must phase be estimated rather than directly measured?
  184. What is phase estimation? And how to use it.
  185. What are the limits to phase estimation? Number of distinct phases and the minimum difference between any two phases.
  186. When will quantum phase estimation be practical? How many qubits, what circuit depth, and what coherence time will be needed to get various levels of precision? How much, if any, can we do with today’s hardware (18–20 qubits and limited coherence time)? Will 53 qubits enable a useful degree of quantum phase estimation? If not, how many qubits and coherence time will be needed to get interesting levels of precision?
  187. What is order-finding? And how to use it.
  188. What is period-finding? And how to use it.
  189. What is the difference between order-finding and period-finding? None that I can discern, but there may be some nuance that has escaped my comprehension.
  190. What is amplitude amplification? And how to use it.
  191. What is a wave function?
  192. What does it mean for a wave function to collapse?
  193. What can quantum tomography tell us about what is happening to the quantum states of the qubits in a quantum computer while and after a quantum circuit has been executed?
  194. How does a SWAP gate work, especially in light of the no-cloning theorem?
  195. How can SWAP and “routing” be used to overcome limited connectivity between qubits?
  196. What is the no-cloning theorem? Why does it matter? Does it really impact much at all?
  197. Why can’t I set a qubit to a specific quantum state? Unless you know it’s current state already. Can only rotate relatively, not set to a specific angle of rotation. Technically could set an ancillary qubit and then swap with the desired qubit.
  198. How to achieve explainable quantum computing. As with AI. Unfortunately, that could be a real challenge when using quantum parallelism and probabilistic computing.
  199. How do you create a quantum program?
  200. Using classical code to generate quantum circuits. Commonly with python libraries.
  201. Using templates to generate quantum circuits.
  202. Using application frameworks to generate quantum circuits.
  203. Need to highlight the quantum parallelism portion of every algorithm. What gives it an advantage over a functionally equivalent classical program.
  204. When might we expect to see the first universal quantum computer — merging quantum gates and classical instructions?
  205. How complex can a quantum program be? Maybe that’s the same as total gate count, or maybe some gates are more expensive. And, many gates could be executed in parallel, presuming that the firmware supports execution of multiple gates in parallel.
  206. Is quantum computing required to achieve artificial general intelligence? The answer may be yes, but for now it is not known or at least unproven.
  207. What is the potential and prospects for photonic quantum computing? What is Xanadu really up to and who else might be pursuing similar approaches?
  208. What’s the simplest quantum computer possible? Just for curiosity.
  209. What is post-quantum cryptography. AKA quantum-safe cryptography or quantum-resistant cryptography. Is it needed — will Shor’s algorithm work any time in the next 25 years? And when is it needed? What will it cost? NIST has ongoing efforts on this front.
  210. When will Shor’s algorithm be able to break strong encryption?
  211. Suggested milestones for judging progress on implementing Shor’s algorithm for cracking public key encryption
  212. Will Shor’s algorithm really work for very large public keys? What are the factors working against an effective solution? How many hardware advances will be required?
  213. Need for a rewrite of Shor’s algorithm that is more complete and provides full justification of all details. See my list of issues with Shor’s algorithm.
  214. Need a baseline implementation of Shor’s algorithm. There can be many derivative algorithms and implementations and improvements, but there should be a single agreed-upon starting point even if suboptimal.
  215. Need a baseline classical implementation of Shor’s algorithm. Something to compare against, at least for smaller numbers. Maybe up to 16 or even 32 bits? Simply coding the quantum order-finding subroutine in classical code. Three levels of implementation: 1) simple, naive, single-processor, trying each order candidate sequentially, 2) multi-processor for each candidate order in parallel, 3) parallel multi-processor computations for a batch of trial random numbers in parallel.
  216. In what areas is research still required for quantum computing? Plenty. Like all areas. We need better hardware, more hardware choices, and better approaches and tools for algorithm design.
  217. How much additional money should be pumped into quantum computing? And in what areas would additional money really make a difference?
  218. How much additional basic research on quantum computing should the federal government itself fund? As opposed to the commercial sector. And in what areas? Which areas benefit more from federal government funding than commercial sector funding?
  219. GitHub as the repository of record for quantum algorithms, circuits, and applications. Include configuration data as well as at least a few sets of sample input data and sample results — to facilitate tests for reproducibility. Include minimal documentation as well, and link to any relevant published papers (preferably on arXiv.org.)
  220. arXiv.org as the repository of record for preprints of any and all formal papers related to quantum computing. Hiding the full text of papers behind paywalls is simply not acceptable.
  221. Which aspects of artificial intelligence (AI) can benefit significantly from quantum computing, and which are not likely to get any significant benefit?
  222. Could video games benefit significantly from quantum computing? Just curious.
  223. Could high-resolution image and video processing benefit significantly from quantum computing? May depend on the availability of much higher qubit counts.
  224. Could audio processing benefit significantly from quantum computing?
  225. Could quantum computing enable 3-D interactive video?
  226. What are the GHZ and W quantum states, and how can they be exploited?
  227. Need for open source and full transparency for all libraries used to build quantum applications.
  228. What quantum computing advances are covered by intellectual property restrictions?
  229. Might intellectual property (IP — patents) deter rapid progress in quantum computing, or might IP incentivize progress in alternative technologies to get around restrictive IP policies?
  230. Do we need open source designs for quantum computers?
  231. Need for open source and transparency for the software, firmware, and control logic for quantum computers. The digital logic, firmware, and software which directly controls qubits — maps quantum logic gates and unitary transforms to qubit control signals (laser, microwave, flux bias, etc.)
  232. Big data and quantum computing. Need to “chunk” data and “stitch” results, even for D-Wave.
  233. No, quantum computing doesn’t magically solve all big data problems. Or any of them for that matter. A quantum computer can only work with a very limited amount of input data, which must be encoded in the gate structure of the quantum circuit, and can only produce a very limited amount of output data, limited to one classical bit for every qubit.
  234. I/O, database access, and network access for quantum computing. There is no I/O, database access, or network access from a quantum circuit. Need preprocessing and post-processing to feed relatively small chunks of data into a quantum circuit and then post-process a relatively small number of classical bits of output. The quantum computer is used as a coprocessor.
  235. Might quantum-only computing be meaningful? Purely speculative. May be irrelevant if we achieve a universal quantum computer which merges both quantum and classical computing.
  236. Quantum-inspired algorithms for classical computers. Especially for massively parallel systems (dozens, hundreds, thousands of processors) and distributed systems. Essentially a stop-gap until we to large-scale quantum computers (hundreds or thousands of qubits, or even 50–75 qubits), but may still have significant value for algorithms which cannot be cleanly mapped to pure quantum algorithms.
  237. Can quantum computers ever completely replace classical computers? Maybe when we achieve universal quantum computers which are a deeply-integrated hybrid of quantum and classical operations and data.
  238. How might quantum computing fit in with Kurzweil’s Singularity? Pure speculation, but interesting nonetheless. Which might occur first? Are they definitely interrelated, or categorically distinct?
  239. What are the advantages of a trapped-ion quantum computer?
  240. How many different technologies are there for implementing quantum computers?
  241. Can qubits have more than two states? Asymmetric probability amplitudes and phase. Qutrits and qudits as well. Also the continuous-variable model (CV) qumodes of Xanadu’s photonic quantum computing.
  242. What datatypes are supported by quantum computers? Just raw, individual qubits — anything else is purely interpreted by the application.
  243. What programming languages are supported by quantum computers? None really. It’s all raw machine language. A wide range of classical programming languages can be used to construct a quantum circuit, one quantum logic gate at a time, which is then downloaded to an actual quantum computer (or a quantum computer simulator) for execution and to retrieve the results. But no high-level language code is executed on a quantum computer.
  244. List of early, seminal papers for quantum computing. Beyond Feynman’s.
  245. The ethics of quantum computing. Not clear, but it is worth pondering.
  246. Software engineering for quantum computing.
  247. The first qubit. And the first gate execution. And the first entanglement of two qubits. Wikipedia is a bit fuzzy on this.
  248. The first quantum computer. That depends on criteria for what constitutes a working quantum computer.
  249. What was the first notable quantum computer?
  250. What are the Chinese up to? Or the Russians?
  251. What is the killer application for quantum computing?
  252. What did Feynman have to say about quantum computing?
  253. Need for much higher standards for documentation. Current doc is very uneven and even incomplete. Make it easier to compare across machines.
  254. Need for standards for quantum computing. Hardware and software. All interfaces and APIs. Common libraries of circuits, algorithmic building blocks, design patterns, and frameworks available across all or at least multiple families of disparate quantum computers. Common programming models and programming languages, both high-level and low-level, available across all or at least multiple families of disparate quantum computers. Common terminology, vocabulary, and glossaries available across all or at least multiple families of disparate quantum computers. Common metrics for performance, timing, reliability, and coherence available across all or at least multiple families of disparate quantum computers.
  255. Refine and resolve my Lingering Obstacles to My Full and Deep Understanding of Quantum Computing
  256. Need simple plain text notation for even complex quantum states. No greek letters, math symbols, or other obscure notation. No complex or obscure graphics. 0 and 1 are obvious. 0/1 for superposition of 0 and 1. Etc.
  257. How to generate a random decimal numbers using only qubit operations. How to map power of 2 random numbers to any decimal range.
  258. How much of the Quantum Algorithm Zoo has relevance to current quantum computers and simulators?
  259. Quantum computing 2.0 — quantum computing needs a reboot. The underlying basics (physics) may not have changed, but a more modern formulation is needed, that is simultaneously algorithmically more powerful and easier to comprehend.
  260. What is spin physically and how does it fit in with quantum computing?
  261. How does spin make a qubit work?
  262. How does magnetism fit in with quantum computing?
  263. How are qubits reset to zero at the start of a quantum computation? By what physical mechanism? How long does that take compared to executing a single quantum logic gate?
  264. What is quantum co-design? Quantum co-design principles.
  265. What does it mean to measure in the computational basis?
  266. What does it mean to measure in other than the computational basis? Simply rotate qubits around the X or Y axis before measurement? Measurement is always in the Z-axis basis? But why do it — motivation?
  267. How many pieces of information can a qubit represent? Phase — imaginary portion of complex probability amplitude, in addition to the difference between the probability of |0> and |1>. Is that three? Or still just two? Or… what?
  268. What is a universal gate set? What constitutes it? What can and can’t you do with it? Clifford group and a single two-qubit gate (CNOT)?
  269. What is a Clifford group? What constitutes it? What can and can’t you do with it?
  270. Can we estimate the probability amplitude(s) for a qubit? Not directly observable (measurable), but maybe some combination of rotation and phase estimation? How many repeated runs of a circuit would be needed to produce an accurate estimation?
  271. Full list of the common quantum logic gates. Maybe graphical symbols as well — or links. Link to details of the specific unitary transforms. Plain language descriptions of the gates. Not-so-common gates as well.
  272. What do we know about Google’s 72-qubit quantum computer?
  273. The twin challenges of how to do basic computations and how to exploit parallelism on a quantum computer. Even relatively simply math and algebraic expressions are not directly available on a quantum computer. And how to restructure iterative algorithms for parallel execution is a real challenge.
  274. What does it mean to be Quantum Native? As in #QuantumNative. Actually, it’s ambiguous, at least three if not four distinct meanings.
  275. What is a Hamiltonian? Total energy of a system, but what does that really involve and why does it matter?
  276. What are the key performance indicators (KPI) or metrics for an algorithm? And how do different algorithm compare?
  277. What is the difference between code, algorithm, and circuit?
  278. Quantum algorithms as a process that produces a circuit
  279. What is adiabatic quantum computing?
  280. What is time evolution?
  281. The importance of heuristic methods. Even on a quantum computer, many quantum simulation problems are still exponentially hard, so clever shortcuts are needed.
  282. What are T1 and T2? And T2*. What are common, desirable, and acceptable values?
  283. What is the Hartree-Fock method? Quantum simulation of both physics and chemistry, quantum computational chemistry. When is it relevant, when can it be avoided and how? What are its implications?
  284. Career opportunities in quantum computing
  285. What tasks and applications might still be beyond even quantum computing in 20 to 25 years?
  286. When will a quantum computer be able to calculate the ground-state energy of aspirin? C9H8O4. How many qubits? How many gates? What connectivity? How many repetitions (“shots”)? If drug design is a key future for quantum computing, it seems as if aspirin is a good test as a “starting gate.”
  287. What might post-quantum computing look like? Speculation. Just for fun. Or maybe a great science fiction story. Make use of worm holes? Make use of time travel (e.g., send data into the past, compute, and then it is complete in the present, or retrieve data or results from the future)? Spiritual computing? Extrasensory perception? Or, might the purported Singularity technically be post-quantum computing? Maybe qubits which can do everything a neuron can? True, human-level AI?
  288. How to get quantum computing beyond the mere curiosity stage?
  289. Is the inability to directly observe or measure probability amplitudes of qubits a fatal flaw of quantum computing? Its Achilles Heel?
  290. What would Turing say about quantum computing?
  291. How does quantum computing relate to a Turing machine?
  292. Would it make sense to have a multiprocessor quantum computer? Could run multiple quantum programs simultaneously, or multiple variations (ansatze) simultaneously for variational methods. How many parallel processors? 4, 8, 16, 64, 128, 256, 1024, 4096?
  293. My personal cut on Google’s quantum supremacy announcement. Technical “cheat”, profound significance, or somewhere in the middle? What might be the first “real” (practical) application to achieve quantum supremacy? What might be the first “real” (practical) application to use more than 20 qubits, or say, 40 of those 53 qubits? What does Google’s feat actually allow us to do, today?
  294. When did quantum computing initially earn the status of being an emerging technology? Maybe IBM Q Experience availability? Or, has it yet?
  295. When will quantum computing exit from being an emerging technology and enter the mainstream? Break out as standalone topic, but currently embedded in What Is Quantum Algorithmic Breakout and When Will It Be Achieved?.
  296. Checklists for documentation of algorithms, implementations, and test cases. And a secondary checklist for implementations for documenting deviations from a published algorithm. Including what documentation should appear in a GitHub repository.

Again, this list will be updated on a fairly frequent basis.

And for topics previously on this list, see my list of current writing on quantum computing:

Comments welcome.

My intention is to remain focused on ideas, issues, principles, and theory, so here are the topics that I have no intention of writing about:

  1. Hands-on tutorials
  2. Hands-on details of particular quantum computers
  3. Hands-on details of particular algorithms. With some rare exceptions.
  4. Hands-on details of particular quantum circuits. With some rare exceptions.
  5. Hands-on details of particular class libraries
  6. Hands-on details of use of particular programming languages
  7. Common, popular, and favorite circuit patterns and quantum programming pearls. I’ll discuss the need, but stay away from the details.
  8. Physical details of particular quantum computers. Including specifications, timing, and performance.
  9. Details of particular unitary transforms or particular quantum logic gates. With some rare exceptions.
  10. Details of support software
  11. “How to…” in general. Some rare exceptions.
  12. Funding and grant announcements. Unless something especially noteworthy.
  13. Announcements of partnerships and deals
  14. Press releases. Unless something especially noteworthy.
  15. Marketing
  16. Market studies and projections

And finally, I am a text-only guy, so I won’t be publishing pictures or photos, diagrams, charts, artwork, or complex mathematical formulas or anything involving lots of greek letters or mathematical symbols. Just plain-language text and bullet points.


Freelance Consultant

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