Matthias Wulff v0.10.1
Reality-check quantum claims
From the developer
Not specified in the available declarations: pricing & account requirements.
What is the state of quantum computing hardware today, and how fast is it improving?
Developer declarations; not independently tested. Listing last checked Nov 14, 2026. Package observed Nov 14, 2026.
From the marketplace listing
See for yourself what today's quantum computers can actually do, and how far they are from the applications in the headlines. You do not need to be a physicist: ask in plain language, and the plugin runs the numbers on real hardware records, each one taken from a published source. Is it realistic yet? Paste a paper, a press release, a roadmap or a headline and compare its claims with today's hardware, or describe a computation or pick one of the example algorithms and see how likely today's best hardware is to get it right, with and without error correction. What would it take? See how much better the hardware would have to get, and how many physical qubits and how much run time a well-known goal such as breaking RSA-2048 needs once error correction is included. How fast is progress? Compare trapped-ion, superconducting and neutral-atom hardware side by side, follow the record error rates and qubit counts over the years, and see when the trend would reach a target if it held (an extrapolation, not a forecast). The answers to the first two questions show their assumptions and caveats, and every hardware record links to the paper or vendor publication it comes from. The plugin gives you numbers, not verdicts: what they mean for quantum computing stays your judgement. For experts, the same tools take exact inputs: qubit count, circuit depth, per-gate error rate, surface-code distance, qLDPC codes, and logical qubits with T count for full fault-tolerant footprints (surface code on the Litinski cost model, qLDPC on the published bicycle architecture). Limitations: this is a deliberately simplified model. It treats noise with the standard surface-code approximation and a routing allowance for hardware with fixed connections, and leaves out effects such as leakage, crosstalk, measurement errors, single-qubit gate errors and idling. Where a measured benchmark score and the model disagree, the measurement wins. All tools are read-only and take no personal data.
Language: English · Automatically detected from descriptions.
Exact text from the indicated source. A mention alone does not establish support for your task.
Check whether a computation is realistic on today's quantum hardware Test the claims in a paper, press release, roadmap or headline against today's hardware numbers See how much better the hardware must get before a given computation works Size well-known goals, such as breaking RSA-2048, in physical qubits and run time Compare trapped-ion, superconducting and neutral-atom hardware side by side Follow record error rates and qubit counts over time, and project when a target is reached Explore example algorithms, error-correction codes and measured hardware benchmark scores Assumptions and caveats with feasibility and requirement answers, a primary source for every hardware record
See for yourself what today's quantum computers can actually do, and how far they are from the applications in the headlines. You do not need to be a physicist: ask in plain language, and the plugin runs the numbers on real hardware records, each one taken from a published source. Is it realistic yet? Paste a paper, a press release, a roadmap or a headline and compare its claims with today's hardware, or describe a computation or pick one of the example algorithms and see how likely today's best hardware is to get it right, with and without error correction. What would it take? See how much better the hardware would have to get, and how many physical qubits and how much run time a well-known goal such as breaking RSA-2048 needs once error correction is included. How fast is progress? Compare trapped-ion, superconducting and neutral-atom hardware side by side, follow the record error rates and qubit counts over the years, and see when the trend would reach a target if it held (an extrapolation, not a forecast). The answers to the first two questions show their assumptions and caveats, and every hardware record links to the paper or vendor publication it comes from. The plugin gives you numbers, not verdicts: what they mean for quantum computing stays your judgement. For experts, the same tools take exact inputs: qubit count, circuit depth, per-gate error rate, surface-code distance, qLDPC codes, and logical qubits with T count for full fault-tolerant footprints (surface code on the Litinski cost model, qLDPC on the published bicycle architecture). Limitations: this is a deliberately simplified model. It treats noise with the standard surface-code approximation and a routing allowance for hardware with fixed connections, and leaves out effects such as leakage, crosstalk, measurement errors, single-qubit gate errors and idling. Where a measured benchmark score and the model disagree, the measurement wins. All tools are read-only and take no personal data.
quantum computing quantum error correction surface code qLDPC fault tolerance resource estimation qubit feasibility
· 3 observations
Long description changed from “(Litinski cost model).” to “(surface code on the Litinski cost model, qLDPC on the published bicycle architecture).”. Version changed from “0.8.1” to “0.10.1”.
View comparison →Package or technical metadata updated
View technical comparison →Find competitors to follow as you develop your plugin.
Write a clear check-in message for someone who has agreed to support your goal.
Shared terms: check, anyone, goal, yourself
Find and book hotels, tours and activities with Booking Wolf: rates for your dates, what the same stay is listed at on other booking site...
Shared terms: check, actually, pick, rate
Brain Rot Index, Focus Room and a 7-day plan to use your phone less.
Shared terms: check, physical, pick, rate
Research Evidence Finder: an expert research librarian and evidence analyst. Finds what the research really says: evidence-based answers ...
Shared terms: claim, expert, headline, paper
Set up and manage Replio voice-training projects from chat: name the training, add knowledge, agree training goals, review AI personas an...
Shared terms: goal, paste, pick, progress
--- name: get-started description: First-run guide for Quantum Expectations. Use right after the plugin is installed, or when the user asks what the plugin can do or how to start. Offers three starting questions and runs the first one the user picks with the plugin's tools. --- Introduce the plugin in two sentences, in plain language: it helps the user judge for themselves what today's quantum computers can actually do, and its results come with the assumptions, caveats and sources the tools return. Assume no physics background unless the user shows one. Offer the user three ways to start and ask which one fits: 1. Is it realistic yet? Paste a paper, a press release, a roadmap or a headline and compare its claims with today's hardware, or check one computation on today's hardware: its size (qubits), its length (depth), and a hardware type or a per-gate error rate. For a document, pull out its quantitative claims and test them with the tools; report what the numbers show, not a verdict on the claim, a judgement of the company or an investment view. 2. What would it take? Give a computation and the success rate you need, and get the error rate the hardware would need and whether any current hardware reaches it. For a well-known goal such as breaking RSA-2048, size the full error-corrected machine in physical qubits and run time. 3. How fast is progress? Compare the hardware types side by side, or follow the record error rates and qubit counts over time. If the user has no computation in mind, list the current reference hardware or the example algorithms with the plugin's tools first so they have real numbers to start from. Explain a technical term the first time it comes up. Run the option they choose with the plugin's tools. Report the numbers the tools return, keep the caveats and source links that come with them, and do not add a verdict the tools did not compute.
0.10.1: numerical precision fix in the effective-error calculation (model 6.0.1); compare_hardware_scenarios accepts at most 50 hardware ids and compares a repeated id once; compute_quantum_volume_rate requires gate and readout times of at least 1e-18 s. Tool names are unchanged. 0.10.0: compute_fault_tolerant_resources sizes qLDPC machines too (optional errorCorrectionCode, default surface); list_qldpc_codes serves each code's architecture data; compute_expectation counts qLDPC blocks as the published architecture does. Surface-code results are unchanged.
Declared in the saved package. Remote tools may change independently.
Publisher declarations from the archived package. These are separate from our research and the live service's terms.
Package observed Nov 14, 2026.
plugin_asdk_app_6adf9b7e45f88191bd7d8eeda8055807
Download plugin data (JSON)Plugin details: served from cache. Prepared . Refreshed when plugin data changes or after 6 hours. Your account and Follow status are live.
