Skip to content

GCRI · 양자기술

양자와 소재

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.

01캔버스

일이 진행되는 방식.

시스템 · 이 주제 주변예시

Quantum testbed

Quantum and materials · Testbed lab · Device QD-77

Calibration cycleGCRI · 양자기술

큐비트

Q01421160.02In spec
Q183480.01In spec
Q269990.01Drifting
Q3142210.05Drifting
Q4162830.03Drifting

Device

Topology
heavy-hex, illustrative
2Q fidelity
0.989
이용
by committee
라벨
관측
Quantum testbed: the screen’s structure, terms and states for Quantum and materials.예시 이름과 예시 값으로, 실제 기록이나 운영 중인 시스템이 아닌 설계안입니다.

그림Quantum testbed: example names and illustrative values, not a record or a live system.

02질문

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.

메커니즘

Defects cause decoherence

Impurities, surface defects and two-level 시스템 in materials interact with qubits and shorten coherence. Better materials and fabrication extend it.

메커니즘

Fabrication sets yield

Producing many identical qubits needs precise fabrication. Variability between devices, even from one wafer, limits how far systems can scale.

메커니즘

Some inputs are scarce

Helium-3 for dilution refrigerators, isotopically enriched silicon and specialised lasers have limited suppliers, creating supply risks.

메커니즘

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.

03방법과 근거

How quantum and materials is modelled, measured and tested.

모형, 그 가정, 데이터, 불확실성을 과학자나 엔지니어가 확인할 형태로 제시합니다. 구조는 발행된 방법을 따릅니다. 제시된 값은 예시이며 결과가 아닙니다.

시스템 모형

The couplings between the systems in quantum and materials: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.

++−+양자사이버지역사회경제R 강화B 균형
Causal loop diagram from the page’s systems; signs show the direction of influence. Illustrative structure for a system dynamics or network model, not estimated couplings.
FAIR 지침 원칙 · GO FAIR와 FORCE11W3C PROV · 월드 와이드 웹 컨소시엄불확실성의 일관된 처리에 관한 지침 · IPCCCEOS 분석 준비 데이터(Analysis Ready Data) · 지구관측위성위원회
04영역 전반

Quantum devices depend on materials with their own supply risks.

05지표

측정되는 것과 그 정확도.

각 지표에는 단위, 주기, 그 뒤의 출처 종류, 값에 붙을 근거 표시가 있습니다. 값은 표시하지 않습니다. 값은 프로그램이 자체 권한으로 제공합니다.

지표단위주기출처 유형라벨
Qubit coherence time by material platformmicrosecondsper publicationPeer-reviewed results관측
Device yield in fabricationpercent of functional qubitsper fabrication runFoundry and lab reports보고됨
Helium-3 supplylitres per year연간Government and industry reports추정
Quantum chemistry demonstrations with classical comparison건수검토별Literature review추정
Specialised component supplierscount by component평가별Supply chain studies추정
Materials databases used for qubit research건수평가별Research surveys보고됨
06출처

근거의 출처.

이름이 명시된 공개 데이터셋과 기관 기록으로, 각각 라이선스 등급이 있습니다. 협약에 따른 출처는 그 조건에 따라서만 사용하며 결코 재게시하지 않습니다.

출처제공하는 것라이선스 등급
Peer-reviewed materials and device literatureCoherence and fabrication resultsLicence per article
Materials Project and other open materials databasesComputed materials properties공개, CC BY 4.0
Government reports on helium-3 and critical inputsSupply and demand of scarce inputsPublic, terms per government
Quantum supply chain studiesComponent suppliers and dependenciesLicence per publication (to check)
Benchmark studies of quantum chemistry algorithmsComparisons with classical methodsLicence per publication
07결정

누가 결정하며 근거는 무엇에 쓰이는지.

Quantum Technologies prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.

결정 주체질문이 페이지가 제공하는 근거
연구 재원 제공 기관Which materials and fabrication research to supportBottleneck reviews
Industry and national 랩How to secure specialised inputsSupply risk assessments
Chemistry and materials researchersWhere quantum simulation could help their workUse case assessments

이 주제가 생산하는 산출물

  • 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
08핵심 질문

전문가가 묻는 것.

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?
09메커니즘

메커니즘과 동인.

The behaviour of molecules and materials depends on how electrons interact. For many 시스템, 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.

10방법과 데이터

연구되는 방식과 방법의 한계.

방법 또는 데이터표시 내용한계
Classical computational chemistryAccurate results for many 시스템Cost grows quickly for strongly correlated electrons
Quantum algorithm resource estimationQubits and operations needed for target problemsHighly sensitive to algorithm and hardware assumptions
Small-scale quantum simulation experimentsProof of principle on simple moleculesNot yet beyond classical reach for useful problems
Experimental materials characterisationGround truth for validationExperiments are costly and not always available
11방법

연구되는 방식과 방법이 말할 수 없는 것.

  1. 재료과학과 화학결맞음 시간 연장을 위한 소재 · 제조 편차 · 양자 화학 활용 사례이곳에서의 적용
  2. 물리학과 양자과학큐비트 잡음 특성 분석 · 양자 시계 계측 · 양자 효과 검증이곳에서의 적용
  3. 양자 컴퓨팅, 센싱 및 통신비교 가능한 벤치마킹 · 기술 성숙도 평가 · 보안 영향 추적이곳에서의 적용
12Where this page’s references

Where this page’s references lead.

이 페이지를 읽을 때 기준이 되는 기구와 문서. 상태와 판은 바뀌며, 각 링크는 발행 기구로 연결됩니다.

13질문

질문과 답변.

Why do materials matter for qubits?
Because defects and impurities in materials disturb qubits and shorten coherence, so better materials and fabrication directly improve device performance.
What is quantum simulation?
Using a controllable quantum system or quantum computer to model another quantum system, such as a molecule or material.
Are there supply risks for quantum technology?
Some inputs, such as helium-3 and certain lasers and isotopes, have few suppliers, which supply chain studies identify as risks.
Has a quantum computer already designed a new material or drug?
Not in a way that classical methods could not match. Current demonstrations are proofs of principle on small systems.
Why is chemistry a natural application?
Because molecules are quantum systems. Simulating quantum systems with quantum hardware avoids some of the exponential costs classical computers face.
Should organisations wait for quantum simulation?
That is their decision. Evidence suggests classical methods will remain the workhorse for most problems for some time, while research into quantum methods continues.
보고서기여하기

이 페이지에서 증거를 기여하십시오.

보고서 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.

GCRI양자기술기하급수 기술전망 보고
양자기술

방법, 데이터세트 또는 질문을 가져오십시오.

정보와 문의는 오늘부터 열려 있습니다. 문의에는 참조 번호가 부여되고 다음 단계가 안내됩니다. 신청, 결제, 컴퓨팅 할당, 등록은 해당 팀, 약관, 심사 역량이 갖추어졌을 때만 열립니다.