GCRI · فناوری‌های کوانتومی
کوانتوم و مواد
Quantum technologies depend on materials, from superconducting circuits and semiconductor spin qubits to photonic chips and isotopically pure crystals. In turn, quantum simulation may one day help design new materials and molecules. This page sets out how materials limit quantum devices, how quantum methods could aid materials science, and what evidence serves the researchers and funders working at this intersection.
چگونه کار اجرا می‌شود.
Quantum testbed
Quantum and materials · Testbed lab · Device QD-77
کیوبیت‌ها
| Q0 | 142 | 116 | 0.02 | In spec |
| Q1 | 83 | 48 | 0.01 | In spec |
| Q2 | 69 | 99 | 0.01 | Drifting |
| Q3 | 142 | 21 | 0.05 | Drifting |
| Q4 | 162 | 83 | 0.03 | Drifting |
Device
- Topology
- heavy-hex, illustrative
- 2Q fidelity
- 0.989
- دسترسی
- by committee
- برچسب
- مشاهده‌شده
شکل.Quantum testbed: example names and illustrative values, not a record or a live system.
Quantum and materials: how the risk develops.
Chemistry and materials simulation. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Defects cause decoherence
Impurities, surface defects and two-level سامانه‌ها in materials interact with qubits and shorten coherence. Better materials and fabrication extend it.
Fabrication sets yield
Producing many identical qubits needs precise fabrication. Variability between devices, even from one wafer, limits how far systems can scale.
Some inputs are scarce
Helium-3 for dilution refrigerators, isotopically enriched silicon and specialised lasers have limited suppliers, creating supply risks.
Quantum simulation of matter
Simulating molecules and materials is a leading candidate use of quantum computers, though classical methods remain strong for most problems today.
How quantum and materials is modelled, measured and tested.
مدل، مفروضات، داده‌ها و عدم قطعیت آن، به شکلی که دانشمند یا مهندس بررسی می‌کند. ساختارها از روش‌های منتشرشده پیروی می‌کنند. مقادیر ترسیم‌شده تبیینی‌اند، نه یافته.
مدل سامانه
The couplings between the systems in quantum and materials: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.
Quantum devices depend on materials with their own supply risks.
Materials studies are designed for the مجموعهٔ نظام‌های راهبردی. Export controls coordinated through the Wassenaar Arrangement and national lists apply to some quantum items.
- Supply data for specialised materials.
- Export control analyses.
What is measured, and how well.
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | دورهٔ تکرار | Source type | برچسب |
|---|---|---|---|---|
| Qubit coherence time by material platform | microseconds | per publication | Peer-reviewed results | مشاهده‌شده |
| Device yield in fabrication | percent of functional qubits | per fabrication run | Foundry and lab reports | گزارش‌شده |
| Helium-3 supply | litres per year | annual | Government and industry reports | برآوردشده |
| Quantum chemistry demonstrations with classical comparison | count | per review | Literature review | برآوردشده |
| Specialised component suppliers | count by component | per assessment | Supply chain studies | برآوردشده |
| Materials databases used for qubit research | count | per assessment | Research surveys | گزارش‌شده |
Where the evidence comes from.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| منبع | What it gives | Licence class |
|---|---|---|
| Peer-reviewed materials and device literature | Coherence and fabrication results | Licence per article |
| Materials Project and other open materials databases | Computed materials properties | Open, CC BY 4.0 |
| Government reports on helium-3 and critical inputs | Supply and demand of scarce inputs | Public, terms per government |
| Quantum supply chain studies | Component suppliers and dependencies | Licence per publication (to check) |
| Benchmark studies of quantum chemistry algorithms | Comparisons with classical methods | Licence per publication |
Who decides, and what the evidence serves.
Quantum Technologies prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| چه کسی تصمیم می‌گیرد | The question | Evidence this page serves |
|---|---|---|
| Research funders | Which materials and fabrication research to support | Bottleneck reviews |
| Industry and national آزمایشگاه‌های | How to secure specialised inputs | Supply risk assessments |
| Chemistry and materials researchers | Where quantum simulation could help their work | Use case assessments |
Outputs this topic produces
- Materials bottleneck reviews for qubit platforms
- Supply risk assessments for specialised inputs
- Assessments of quantum simulation use cases with classical baselines
- Evidence notes for research funders
What experts ask.
The question is whether quantum simulation will beat improving classical methods on problems that matter.
- Which chemical and materials problems are genuinely hard for classical methods?
- How large and how error-free must a quantum computer be to simulate them usefully?
- Can near-term noisy devices provide any useful result, or is error correction required?
- How will results be verified when classical methods cannot reproduce them?
- Which industrial and scientific questions would change if simulation improved?
Mechanisms and drivers.
The behaviour of molecules and materials depends on how electrons interact. For many سامانه‌ها, classical approximations such as density functional theory work well. For strongly correlated systems, such as some catalysts, transition-metal complexes and high-temperature superconductors, the computational cost of exact classical simulation grows very rapidly with system size. A quantum computer represents quantum states natively and could, in principle, simulate such systems efficiently.
Resource estimates for industrially relevant problems suggest that large, error-corrected machines would be required. Meanwhile classical methods, including tensor networks and machine-learning approaches, keep improving and raising the bar. Quantum materials research also runs the other way: new materials are needed to build better qubits.
How it is studied, and where the methods stop.
| Method or data | What it shows | محدودیت‌ها |
|---|---|---|
| Classical computational chemistry | Accurate results for many سامانه‌ها | Cost grows quickly for strongly correlated electrons |
| Quantum algorithm resource estimation | Qubits and operations needed for target problems | Highly sensitive to algorithm and hardware assumptions |
| Small-scale quantum simulation experiments | Proof of principle on simple molecules | Not yet beyond classical reach for useful problems |
| Experimental materials characterisation | Ground truth for validation | Experiments are costly and not always available |
How it is studied, and what the methods cannot say.
- 01علم مواد و شیمیMaterials for longer coherence · Fabrication variability · Quantum chemistry use casesApplied here
- 02فیزیک و علم کوانتومCharacterising qubit noise · Metrology of quantum clocks · Verifying quantum effectsApplied here
- 03محاسبات، سنجش و ارتباطات کوانتومیComparable benchmarking · Technology readiness assessment · Security implications trackingApplied here
Where this page’s references lead.
نهادها و اسنادی که این صفحه بر پایهٔ آن‌ها خوانده می‌شود. وضعیت و ویراست‌ها تغییر می‌کنند؛ هر پیوند به نهاد صادرکننده می‌رود.
پرسش و پاسخ.
Why do materials matter for qubits?
What is quantum simulation?
Are there supply risks for quantum technology?
Has a quantum computer already designed a new material or drug?
Why is chemistry a natural application?
Should organisations wait for quantum simulation?
شواهد را از همین صفحه ارسال کنید.
گزارش‌ها is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.
- ایمیلدرگاه GW-GCRIاز همین صفحه ارسال کنیدشواهد، یک اصلاحیه، یک مورد، یک روش، یک داوری، یک ترجمه یا ورودی نمایه. با برچسب این صفحه میرسد تا ویراستار مسئول آن را دریافت کند.
- Zenodoسپردهٔ بازآن را واگذار کنید و به جامعه ارائه دهیدسابقهٔ خود را با شناسهٔ ORCID خود در Zenodo منتشر کنید و سپس آن را در همانجا به جامعهٔ Reports ارسال کنید. گزینشگران آن را داوری می‌کنند؛ DOI از آنِ شما میماند.
- گزارش‌هاGCRIهمهٔ راههای مشارکت را ببینیدانواع مشارکت، نحوهٔ بررسی هر یک، اعتباری که دریافت میکنید، مجوز و آنچه هرگز پذیرفته نمیشود.
هرگز داده شخصی، جزئیات حساس زیرساخت یا چیزی را که حق اشتراکش را ندارید نفرستید. هر مشارکت پیش از استفاده داوری می‌شود؛ ارسال آن حق مؤلفی یا ویرایشی نمی‌دهد و حمایت مالی هرگز یافته‌ای را نمی‌خرد.
یک روش، یک مجموعه‌داده یا یک پرسش بیاورید.
اطلاعات و درخواست‌ها امروز باز است. هر درخواست یک شمارهٔ پیگیری می‌گیرد و گام بعدی را مشخص می‌کند؛ درخواست‌های عضویت، پرداخت‌ها، تخصیص رایانش و ثبت‌نام‌ها تنها زمانی باز می‌شوند که تیم، شرایط و ظرفیت داوری آن‌ها فراهم باشد.
اسناد حقوقی.
نقشه‌ها، داده‌ها و ارقام این سایت برای زمینه و اطلاعات عمومی نشان داده می‌شوند. توصیه، پیش‌بینی یا هشدار نیستند؛ حدود این اطلاعات در سلب مسئولیت‌ها و اعلامیه‌های داده بیان شده است.