Part IX. Company and Investing · Chapter 81
Reading Roadmaps Like an Operator
A quantum roadmap is a document written by an interested party about a future that depends on physics, capital, and supply chains. Operators read it anyway — by translating every milestone into metrics, dependencies, and evidence they can request.
In this chapter 9 sections
Rewrite every roadmap milestone as an observable with units, provenance, prerequisites, integration owner, and failure branch; then schedule on the longest unresolved dependency chain rather than the vendor’s headline date.
Roadmaps become useful when nouns turn into measured verbs. 'Logical qubit', 'scale', 'advantage', and 'fault tolerant' each hide multiple exit criteria. An operator rewrites every milestone with units, a measurement protocol, a primary record, prerequisite nodes, owner, failure branch, and review event.
Turn milestone nouns into measured verbs
The roadmap is a directed acyclic graph. Earliest completion for a child is the maximum completion of its parents plus its own validated duration. Physical error, cycle time, decoder throughput, logical operations, fabrication yield, control and application resources can occupy different paths. The longest unresolved path sets the conditional date.
Roadmap ledger with dependencies and owners
The resource estimate by Gidney and Ekerå supplies explicit assumptions that can become nodes; it does not supply a universal roadmap. GAO, the National Academies, and the benchmarking review anchor dated evidence. OpenQASM and official SDKs can be integration milestones. ACM’s artifact policy supports reproducible exit records.
A logical-qubit target hides throughput prerequisites
A headline logical-operation milestone depends on below-threshold physical behavior, repeated syndrome extraction, decoder throughput, and a validated logical gate. The decoder node slips from quarter 2 to quarter 4. The child cannot remain in quarter 3. Recomputing the graph moves the conditional result to quarter 5 and identifies the responsible dependency without claiming that every other task stops.
Artifact contract. A dated milestone DAG with executable dependency, cycle, and earliest-date checks. Every milestone has a measurable exit criterion and source; no child precedes an unmet parent; the output reports a conditional interval and failing dependency instead of one unsupported date.
Executable reference fixture
def schedule(roadmap):
errors = []
nodes = roadmap.get("milestones", {})
for name, node in nodes.items():
duration, exit_gate = node.get("duration", {}), node.get("exit", {})
if type(node.get("parents")) is not list or not node.get("source_id"):
errors.append(name + "_parents_or_source")
if type(duration.get("value")) is not int or duration.get("unit") != "review intervals":
errors.append(name + "_duration")
if type(exit_gate.get("threshold")) not in (int, float) or not exit_gate.get("unit"):
errors.append(name + "_exit")
if any(parent not in nodes for parent in node.get("parents", [])):
errors.append(name + "_unknown_parent")
finish = {}
pending = set(nodes)
while pending and not errors:
ready = sorted(name for name in pending if all(parent in finish for parent in nodes[name]["parents"]))
if not ready:
errors.append("cycle")
break
for name in ready:
finish[name] = max([finish[parent] for parent in nodes[name]["parents"]] or [0]) + nodes[name]["duration"]["value"]
pending = pending - set(ready)
target = roadmap.get("target")
return {"decision": "invalid" if errors else f"conditional-interval-{finish[target]}",
"errors": sorted(set(errors)), "finish": finish, "target_finish": finish.get(target)}
roadmap = {"scenario": "logical-qubit dependency roadmap", "target": "logical", "milestones": {
"physical": {"parents": [], "duration": {"value": 1, "unit": "review intervals"},
"exit": {"threshold": 0.005, "unit": "error/cycle"}, "source_id": "scenario:device-plan"},
"syndrome": {"parents": ["physical"], "duration": {"value": 1, "unit": "review intervals"},
"exit": {"threshold": 1.0, "unit": "MHz"}, "source_id": "scenario:control-plan"},
"decoder": {"parents": ["syndrome"], "duration": {"value": 2, "unit": "review intervals"},
"exit": {"threshold": 1.0, "unit": "Msyndromes/s"}, "source_id": "scenario:decoder-plan"},
"logical": {"parents": ["syndrome", "decoder"], "duration": {"value": 1, "unit": "review intervals"},
"exit": {"threshold": 0.001, "unit": "logical error/operation"}, "source_id": "scenario:system-plan"}}}
base_result = schedule(roadmap)
bad_decoder = {key: value for key, value in roadmap["milestones"]["decoder"].items() if key != "source_id"}
bad_result = schedule({**roadmap, "milestones": {**roadmap["milestones"], "decoder": bad_decoder}})
delayed_decoder = {**roadmap["milestones"]["decoder"], "duration": {"value": 3, "unit": "review intervals"}}
delayed_result = schedule({**roadmap, "milestones": {**roadmap["milestones"], "decoder": delayed_decoder}})
assert base_result["target_finish"] == 5 and base_result["finish"]["decoder"] == 4
assert bad_result["decision"] == "invalid" and "decoder_parents_or_source" in bad_result["errors"]
assert delayed_result["target_finish"] == 6 and delayed_result["decision"] == "conditional-interval-6"
print(f"PASS: 81 roadmap workbook base={base_result['target_finish']} intervals invalid={bad_result['errors']} decoder_delay={delayed_result['target_finish']}")| Milestone | Parent completion | Own duration | Earliest quarter |
|---|---|---|---|
| Physical cycle | 0 | 1 | 1 |
| Syndrome stream | 1 | 1 | 2 |
| Decoder throughput | 2 | 2 after slip | 4 |
| Logical operation | max(2,4) | 1 | 5 |
Exact validation command: python3 tools/validate_briefs.py --briefs data/editorial_briefs_64_87.json --from 64 --through 87 --check-rewritten-sources --execute-artifacts
Critical paths move when evidence arrives
Manage evidence, not dates. Each review asks whether the exit measurement exists under its declared scale and conditions. A failed node activates its alternative branch and recomputes the path. A vendor date can be recorded as a claim, but the operating plan uses the dependency-derived interval and exposes disagreement.
Red-team a five-year roadmap
Prompt. Translate five roadmap claims into a dependency graph with measured exits.
Deliverable. Milestone table, units, primary source, parent dependencies, owner, earliest/latest conditional dates, failure branch, and refresh event.
Pass condition. The DAG is acyclic, every date follows all parents, no milestone uses 'scale' without a quantity, and changing one dependency recomputes the critical path.
Model answer: date becomes a conditional interval
Format. Five-node logical-operation roadmap whose headline year becomes a conditional range.
The five-node model produces an earliest conditional quarter of 5 after decoder delay. It does not assign probability or pretend the durations are known precisely. The answer lists physical performance and decoder throughput as separate prerequisites, names the owner of each test, and schedules the next review when primary evidence is expected.
Verification. The fixture validates the DAG and reproduces the shifted date when decoder throughput is delayed by one review interval.
Companion work
Artifacts for this chapter
These entries resolve to checked-in local source. Commands are reproduced exactly from the chapter manifest, and source-embedded fixtures are exported as direct downloads.
diligence dossier
Quantum roadmap dependency and critical-path record
Reproduce or test
python3 tools/validate_briefs.py --briefs data/editorial_briefs_64_87.json --from 64 --through 87 --check-rewritten-sources --execute-artifacts
Provenance
Sources and review
- U.S. Government Accountability Office. Quantum Computing and Communications: Status and Prospects. GAO. 2021government technology assessment
- Association for Computing Machinery. Artifact Review and Badging. ACM Publications. 2026official reproducibility policy
- IBM Quantum. Qiskit documentation. IBM. 2026official documentation
- Google Quantum AI. Cirq documentation. Google. 2026official documentation
- OpenQASM Technical Steering Committee. OpenQASM 3 specification. Linux Foundation Joint Development Foundation. 2026official technical specification
- Craig Gidney and Martin Ekerå. How to factor 2048 bit RSA integers in 8 hours using 20 million noisy qubits. Quantum. 2021primary peer-reviewed resource estimate
- Timothy Proctor et al.. Benchmarking quantum computers. Nature Reviews Physics. 2025peer-reviewed perspective
- National Academies of Sciences, Engineering, and Medicine. Quantum Computing: Progress and Prospects. National Academies Press. 2019consensus study report
The load-bearing claims in the chapter are mapped inline to this registered source set. A citation supports only the bounded claim beside it.