ð JP | ð¬ð§ EN | Last sync: 2026-08-13
AI寺åå±ãããâºåºç€æ°çéå ŽâºéåããŒããŠã§ã¢å ¥é
â åºç€æ°çéå Žããã
ð¯ ã·ãªãŒãºæŠèŠ
æ¬ã·ãªãŒãºã¯éåã³ã³ãã¥ãŒãã£ã³ã°å ¥éã®å¯Ÿããªãå·»ã§ãããã¡ãã®ã³ãŒã¹ã¯èªããããŒããŠã§ã¢ã®è¬åº§ã§ã¯ãªããšæèšããŠããŸããè¶ äŒå°éåããããã€ãªã³ãã©ãããäžæ§ååã¯ããã§ã¯èª€å·®ç¹æ§ãé¢ä¿ããç®æã«ã®ã¿ç»å Žãããã³ããŒã¬ã³ã¹ã¯ãã€ãºã¢ãã«ã®ãã©ã¡ãŒã¿ãšããŠå ¥ã£ãŠããŸããæ¬ã³ãŒã¹ã¯ãŸãã«ãã®ç©ºçœãåããŸããã¢ã«ãŽãªãºã ç·šããéåã³ã³ãã¥ãŒã¿ã¯äœãèšç®ããããããåãã®ã«å¯Ÿããæ¬ã³ãŒã¹ã¯ãéåã³ã³ãã¥ãŒã¿ã¯äœã§ã§ããŠããªããã°ãªããªãããããããŠããªãã©ã®åè£ãææç§åŠè ãèŠèŠãã®ããäœãã«åŸéãããã®ãããåããŸãã
貫ãèŠç¹ã¯å¯é¡ã«æ²ãããšããã§ãåç« ã§ãããæè·ããŸããããªãã¡éåããŒããŠã§ã¢ã¯ææã®åé¡ã§ãããšããããšã§ããè¶ äŒå°éåãããã®ã³ããŒã¬ã³ã¹ã¯ãæ°ããã¡ãŒãã«ã®ã¢ã¢ã«ãã¡ã¹è¡šé¢é žåèäžã®2æºäœæ¬ é¥ã決ããŸããã·ãªã³ã³äžã¹ãã³éåãããã®ã³ããŒã¬ã³ã¹ã¯ãæ®ç $^{29}\mathrm{Si}$ æ¿åºŠãšé žåèçé¢ã®ãã©ãããæ±ºããŸããã€ãªã³ãã©ãããå¶éããéåå ç±ã¯ã黿¥µè¡šé¢ã®é»å Žãã€ãºããæ¥ãŸããããããžã«ã«ãªææ¡ã¯åå°äœ-è¶ äŒå°çé¢ã®å質ã§ç«ã€ãåããããæ±ºãŸããŸãããããã®å ŽåãçŽ åã®æ§èœææš â $T_1$ã$T_2^\ast$ãQå€ â ã¯ææåéã®éã«ãã®ãŸãŸç¿»èš³ã§ããŸããæå€±è§ãçé¢ãã©ããå¯åºŠãåäœäœçŽåºŠã衚é¢åå çã§ãã
å š5ç« ã§1æ¹åŒãã€ãæ±ãããã®åã«ãæ¯èŒã®èšèªãåºå®ãã第1ç« ã眮ããŸããåè¿°ã¯å®£äŒçã§ã¯ãªãæå³ããŠç©ççã§ãããææããŸã ååã§ãªãããããŠããã¯ãã®ææã ããèª å®ãªçãã§ãããšãã¯ããè¿°ã¹ãŸããæ³å®èªè ã«ãšã£ãŠããã¯è峿·±ãçãã§ããä»äºãã©ãã«ããããæããŠãããããã§ãã
åŠç¿ãã¹
éåååŠ"] P2["æšå¥š
éåã³ã³ãã¥ãŒãã£ã³ã°"] A["第1ç«
äœãè¯ãéå
ããããäœãã®ã"] B["第2ç«
è¶ äŒå°
éåããã"] C["第3ç«
ã€ãªã³
ãã©ãã"] D["第4ç«
äžæ§
åå"] E["第5ç«
å ã»ã¹ãã³ã»
ããããžãŒãšç·æ¬"] P1 --> A P2 --> A A --> B A --> C A --> D B --> E C --> E D --> E style P1 fill:#e2e8f0,stroke:#94a3b8,stroke-width:1px,color:#334155 style P2 fill:#e2e8f0,stroke:#94a3b8,stroke-width:1px,color:#334155 style A fill:#667eea,stroke:#764ba2,stroke-width:2px,color:#fff style B fill:#7b2cbf,stroke:#764ba2,stroke-width:2px,color:#fff style C fill:#7b2cbf,stroke:#764ba2,stroke-width:2px,color:#fff style D fill:#7b2cbf,stroke:#764ba2,stroke-width:2px,color:#fff style E fill:#9d4edd,stroke:#764ba2,stroke-width:2px,color:#fff
第1ç« ã¯çç¥ã§ããŸããã$T_1$ã$T_2$ã$T_2^\ast$ã6æ¬ã®æ¯èŒè»žããããŠä»ã®4ç« ãå説ããã«çšããåäœã®çŽæãå®çŸ©ããŸãã第2ç« ã»ç¬¬3ç« ã»ç¬¬4ç« ã¯äºãã«ç¬ç«ã§ãã©ã®é ã«èªãã§ãã1ç« ã ãèªãã§ãæ§ããŸããã第5ç« ã¯æ®ãæ¹åŒããŸãšããããã§ç¬¬1ç« ã®è»žã«æ²¿ã£ãŠãã¹ãŠãæ¯èŒããŸããããæåŸã«èªãã§ãã ããã
ð åŠç¿ç®æš
æ¬ã·ãªãŒãºãä¿®äºãããšã以äžã®ããšãã§ããããã«ãªããŸãã
- DiVincenzoåºæºãæããããããã«ã€ããŠã©ã®çŽ åã»ææã®ç©ççæ§è³ªãå¶çŽãšãªãããè¿°ã¹ããã
- $T_1$ã$T_2$ã$T_2^\ast$ ãå³å¯ã«å®çŸ©ãã$T_2 \le 2T_1$ ã®éçãå°ãããããããç°å¢ãã€ãºã¹ãã¯ãã«ã®ã©ã®éšåãæž¬ã£ãŠãããã説æã§ãã
- åäž»èŠæ¹åŒã®æ©æ§ãããã«ããã¢ã³ãã説æã§ããããã©ã³ãºã¢ã³ã®ãžã§ã»ããœã³éç·åœ¢æ§ãã€ãªã³éã®å ±æéåã¢ãŒããäžæ§ååé åã®Rydbergå°éãäºééåãããã®äº€æçžäºäœçš
- ãã©ã³ãºã¢ã³ã®éèª¿åæ§ãæ°å€å¯Ÿè§åã§å°ããPaulãã©ããã® Mathieu å®å®å³ãèšç®ããRydbergå°éã®ãã€ããã¯ã¹ãã·ãã¥ã¬ãŒããã亀æçµåããäºéãããã察è§åãããããªãã¡åæ©æ§ãåãå ¥ããã®ã§ã¯ãªãæ°å€çã«æ€èšŒã§ãã
- ä»»æã®æ¹åŒã«ã€ããŠãçŸåšã³ããŒã¬ã³ã¹ãå¶éããŠããææãã£ãã«ãç¹å®ãããã®èšºæã確å®ãããæž¬å®ãæãããã
- ããŒããŠã§ã¢ã«é¢ãã䞻匵ããåŒçšãããè£ çœ®ã¹ããã¯ã§ã¯ãªãç©ççãªæ ¹æ â ãšãã«ã®ãŒã¹ã±ãŒã«ãã¹ã±ãŒãªã³ã°åãæ¥ç¶æ§ããã€ãºã¹ãã¯ãã« â ã«åºã¥ããŠèªãã
ð åæç¥è
å¿ é ã 2æºäœç³»ãèª¿åæ¯ååãæéäŸåæåè«ãå転波è¿äŒŒã®æ°Žæºã®éåååŠïŒéåååŠå ¥éãåç §ããŠãã ããã第2ç« ã¯éååããLCåè·¯ã第3ç« ã¯ Mathieu æ¹çšåŒãšãµã€ããã³ãé·ç§»ã第4ç« ã¯ACã·ã¥ã¿ã«ã¯ã·ãããçšããŸãã
æšå¥šã éåã³ã³ãã¥ãŒãã£ã³ã°å ¥éãæ¬ã·ãªãŒãºã¯ãã¡ãã§ç¢ºç«ããéåãããã®é åºãã²ãŒãèšå·ãç¶æ ãã¯ãã«ã®èŠçŽãçšãã第5ç« ã¯ãã¡ãã®èª€ãèšæ£ã®èšè¿°ãåç §ããŸãã2ã€ã䜵ããŠèªãããšãæ³å®ãããäœéšã§ãããç©çé¢ã§ã¯æ¬ã³ãŒã¹ã¯èªå·±å®çµããŠããŸãã
å¿ é ã Python 3.8以éãšNumPyãSciPyãMatplotlibããã¹ãŠã®ã³ãŒãäŸã¯çŽ ã®NumPyãŸãã¯SciPyã§ãããéåSDKãããŒããŠã§ã¢ããã¯ãšã³ããã·ãªãŒãºäžã«äžåç»å ŽããŸããã
ãããšæçšïŒå¿ é ã§ã¯ãªãïŒã 第2ç« ã®ããã®åºäœç©ç â è¶ äŒå°å ¥éãã第2ç« ã§1ç¯ã«èŠçŽããCooper察圢æãšãžã§ã»ããœã³ç©çãæ±ã£ãŠããŸã â ãšã第5ç« ã®ã¹ãã³éåãããã®ç¯ã®ããã®ã¹ãã³ãããã¯ã¹å ¥éã
ð ç« æ§æ
第1ç« ïŒäœãè¯ãéåããããäœãã®ã
è¯ãéåããããåæã«çžåãã2ã€ã®ãã®ã§ãªããã°ãªããªãçç±ãšãèªç¶ã®æ¹åŒãšäººå·¥ã®æ¹åŒããã®ççŸãã©ãå¥ã ã«è§£æ¶ããŠããããDiVincenzoåºæºãšãã®åé ç®ã®ç©ççå 容ã6æ¬ã®æ¯èŒè»ž â ã³ããŒã¬ã³ã¹ãã²ãŒãå¿ å®åºŠãšéåºŠãæ¥ç¶æ§ãåçŸæ§ãšæ©çãŸããåäœæž©åºŠãã¹ã±ãŒã©ããªã㣠â ãæãããããã1æ¬ã§é äœã¥ããããšåè ãå€ããããšãå®éçã«ç€ºããŸãããã³ããŒã¬ã³ã¹ã®å ±éèšèªïŒ$T_1$ã$T_2$ã$T_2^\ast$ããã€ãºãã¯ãŒã¹ãã¯ãã«å¯åºŠã2æºäœæºååã«ãã $1/f$ ãã€ãºããããŠãã£ã«ã¿ãŒé¢æ°ãæåŸã«ãRabiæ¯åãèªç±èªå°æžè¡°ãRamseyçžãHahnãšã³ãŒãCPMGåçãã«ãããªã³ã°ã第äžåçããåçŸããBlochæ¹çšåŒã®å®éšå®€ãæ§ç¯ããŸãã
äž»èŠããã㯠ïŒDiVincenzoåºæº · æ¯èŒã®è»ž · $T_1$ / $T_2$ / $T_2^\ast$ · ãã€ãºãã¯ãŒã¹ãã¯ãã«å¯åºŠ · $1/f$ ãã€ãºãšTLS · Blochæ¹çšåŒ · Ramsey枬å®ãšãšã³ãŒ · CPMGã¹ã±ãŒãªã³ã°
ð» ã³ãŒãäŸ7å â±ïž 40-45å ð äžçŽ
第2ç« ïŒè¶ äŒå°éåããã
è¶ äŒå°ãšãžã§ã»ããœã³å¹æããCooper察圢æãã2ã€ã®ãžã§ã»ããœã³é¢ä¿åŒãŸã§ãLCåè·¯ã®éååãšã人工ååãããããéç·åœ¢çŽ åãå¿ èŠãšããçç±ããã©ã³ãºã¢ã³ïŒã³ãµã€ã³ããã³ã·ã£ã«ãéèª¿åæ§ããã㊠$E_J/E_C$ ã倧ããããã«ã€ããŠéèª¿åæ§ãé»è·ãã€ãºäžææ§ãšåŒãæããæ§é ããã€ã¯ãæ³¢ãã«ã¹ã«ããå¶åŸ¡ãšåæ£èªã¿åºãããããŠããã«å¿ èŠãªæå°éã®åè·¯QEDã2éåãããã²ãŒãã®æ©æ§ â 容éçµåããã¥ãŒããã«ã«ãã©ãcross-resonanceãæåŸã«ãã³ããŒã¬ã³ã¹ã®ææç§åŠïŒè¡šé¢ããã³çé¢é žåèäžã®2æºäœç³»ãèªé»æå€±ã®åå çè§£æãé平衡æºç²åãåºæ¿ã®éžæã
äž»èŠããã㯠ïŒãžã§ã»ããœã³é¢ä¿åŒ · åè·¯ã®éåå · ãã©ã³ãºã¢ã³ · éèª¿åæ§ · $E_J/E_C$ ãšé»è·åæ£ Â· 忣èªã¿åºã · ãã¥ãŒããã«ã«ã㩠· cross-resonance ãšåšæ³¢æ°è¡çª · TLSãšåå ç · æºç²å
ð» ã³ãŒãäŸ7å â±ïž 45-50å ð äžçŽ
第3ç« ïŒã€ãªã³ãã©ãã
Paulãã©ããã®ç©çïŒMathieuæ¹çšåŒãæ¬ããã³ã·ã£ã«ããããŠå®å®é åãéåãããã®æ ãæ â è¶ åŸ®çŽ°æºäœãšå åŠé·ç§»ã®å¯Ÿæ¯ããããŠã¯ããã¯é·ç§»ãç¹å¥ã§ããçç±ãã¬ãŒã¶ãŒå·åŽãšãµã€ããã³ãåå ããDopplerå·åŽããåäžéåã¢ãŒãã®åè§£ãµã€ããã³ãå·åŽãŸã§ãå ±æãã©ãã³ã¢ãŒãã«åºã¥ãã²ãŒãæ©æ§ããCirac-Zolleræ¹åŒããããã«åã£ãŠä»£ãã£ãMÞlmer-SÞrensenã²ãŒããŸã§ãå šçµåæ§ãšãã®ä»£åïŒã²ãŒãé床ãã¢ãŒãã®æ··éãã€ãªã³æ°ã«å¯Ÿããã¹ã±ãŒãªã³ã°ãæåŸã«å·¥åŠã»ææäžã®èª²é¡ â ãã©ãã衚é¢ã«ç±æ¥ããç°åžžå ç±ãç空ããããŠå åŠç³»ã®è€éãã
äž»èŠããã㯠ïŒMathieuæ¹çšåŒ · æ¬ããã³ã·ã£ã« · å®å®é å · è¶ åŸ®çŽ°éåããããšå åŠéåããã · ãµã€ããã³ãå·åŽ Â· MÞlmer-SÞrensenã²ãŒã · å šçµåæ§ Â· ç°åžžå ç±
ð» ã³ãŒãäŸ7å â±ïž 45-50å ð äžçŽ
第4ç« ïŒäžæ§åå
ã¬ãŒã¶ãŒå·åŽãæ£ä¹±åããå ã¢ã©ã»ã¹ãç£æ°å åŠãã©ãããŸã§ãå ãã€ãŒã¶ãŒãšååé åïŒå極ååãåé 眮ããããŠããããåŸãä»»æã®ãžãªã¡ããªãRydbergç¶æ ãšå°é广ããçžäºäœçšã® $n^{11}$ ã¹ã±ãŒãªã³ã°ãå°éååŸã$C_6$ ä¿æ°ãšãšãã«ãã²ãŒããšããã®æ¹åŒãç¹åŸŽã¥ãã2ã€ã®åäœæ§åŒ â ããžã¿ã«ã²ãŒããšãIsingããã«ããã¢ã³ãçŽæ¥å®è£ ããã¢ããã°éåã·ãã¥ã¬ãŒã·ã§ã³ãæåŸã«èª å®ãªè©äŸ¡ïŒäžèŠæš¡ã¬ãžã¹ã¿ãžã®èªç¶ãªã¹ã±ãŒãªã³ã°ãšãããã«å¯Ÿããååæå€±ãã²ãŒãå¿ å®åºŠã®ç©ççéçããããŠç Žå£çãªèªã¿åºãã
äž»èŠããã㯠ïŒå ã¢ã©ã»ã¹ãšMOT · 忥µåå · å ãã€ãŒã¶ãŒ · Rydbergå°é · $C_6$ ãšå°éååŸ Â· ããžã¿ã«åäœãšã¢ããã°åäœ Â· ååæå€± · ç Žå£çèªã¿åºã
ð» ã³ãŒãäŸ6å â±ïž 40-45å ð äžçŽ
第5ç« ïŒå ã»åå°äœã¹ãã³ã»ããããžã«ã«ããããŠç·æ¬
æ®ãæ¹åŒçŸ€ãšãããã«ç¶ãæ¯èŒãå éåèšç®ïŒåäžå åãå ãçžäºäœçšãããããšã®å°é£ãããããŠæž¬å®åã®æ¹åŒãšã¬ãŠã·ã¢ã³ããœã³ãµã³ããªã³ã°ãå®éã«ã©ãã«äœçœ®ããã®ããåå°äœã¹ãã³éåãããïŒéåãããã亀æçžäºäœçšããããŠã·ãªã³ã³ã®åäœäœç²Ÿè£œ â ææã®è°è«ãæ¹åŒã®èŠéããæ±ºãããæ¬ã·ãªãŒãºã§æãæå¿«ãªäºäŸã§ããããããžã«ã«éåèšç®ïŒé坿ãšããªã³ãšMajoranaã¢ãŒããä¿è·ãæ¬è³ªçã§ããçç±ãšãããèŠããªããã®ïŒæºç²åãã€ãºãã³ã°ïŒããããŠåçå®èšŒãšå®çšã®è·é¢ã«ã€ããŠã®ççŽãªèšè¿°ãç¶ãã¹ã³ã¢ã«ãŒãã¯ç¬¬1ç« ã®è»žã«æ²¿ã£ãŠå šæ¹åŒãæ¯èŒããŸããæ°å€ã®èšé²ã§ã¯ãªãç©ççå¶çŽã«ãã£ãŠæ¯èŒãããŸã åè ã¯ããªãããšãæèšããŸããæåŸã«ãããããã¹ãŠãææç ç©¶è ã«ãšã£ãŠäœãæå³ããããè¿°ã¹ãŸãã
äž»èŠããã㯠ïŒç·åœ¢å åŠãšKLM · 枬å®åéåèšç® · éåãããã¹ãã³éåããã · 亀æçžäºäœçš · $^{28}\mathrm{Si}$ 粟補 · Majoranaã¢ãŒã · éå¯æçµ±èš Â· æºç²åãã€ãºãã³ã° · æ¹åŒéã¹ã³ã¢ã«ãŒã
ð» ã³ãŒãäŸ6å â±ïž 45-50å ð äžçŽ
ð€ èšæ³ãšåäœ
èŠçŽã¯ç¬¬1ç« ã§åºå®ãã以åŸå€æŽããŸãããã©ã®ç« ã®æ°åŒãã³ãŒããä»ã®ç« ãšçµã¿åãããŠäœ¿ããŸãã
| èšå· | æå³ |
|---|---|
| $\hbar = 1$ | ããã«ããã¢ã³ã¯æç®åäœã§æžããç©ççãªãšãã«ã®ãŒã§ã¯ $\hbar$ ãæç€ºçã«åŸ©å ãã |
| $\omega_q$ã$\omega_d$ | éåããããšé§åã®è§åšæ³¢æ°ïŒrad/sïŒãåŒçšæã¯ $\omega/2\pi$ ã Hz ã§ |
| $\Omega$ | Rabiåšæ³¢æ°ïŒè§ïŒã$\pi$ ãã«ã¹ã¯ $\pi/\Omega$ ãèŠãã |
| $\Delta = \omega_q - \omega_d$ | é¢èª¿ïŒè§ïŒ |
| $T_1$ | ãšãã«ã®ãŒç·©åæéïŒçžŠïŒ |
| $T_2$ | ãšã³ãŒåŸã®ã³ããŒã¬ã³ã¹æéã$1/T_2 = 1/(2T_1) + 1/T_\varphi$ |
| $T_2^\ast$ | ãšã³ãŒãªãã®ã³ããŒã¬ã³ã¹æéãéçãªäžåäžæ§ãå«ã |
| $S(f)$ | çåŽãã€ãºãã¯ãŒã¹ãã¯ãã«å¯åºŠã$\langle\delta\omega^2\rangle = \int_0^\infty S\,df$ |
| $E_J$ã$E_C$ | è¶ äŒå°åè·¯ã®ãžã§ã»ããœã³ãšãã«ã®ãŒãšå é»ãšãã«ã®ãŒïŒç¬¬2ç« ïŒ |
| $\eta$ | æç²ã€ãªã³ã®Lamb-Dickeãã©ã¡ãŒã¿ïŒç¬¬3ç« ïŒ |
| $C_6$ã$R_b$ | Rydbergçžäºäœçšä¿æ°ãšå°éååŸïŒç¬¬4ç« ïŒ |
| $J$ | äºééåãããã®äº€æçµåïŒç¬¬5ç« ïŒ |
| $X, Y, Z, H$ãCNOT | ã²ãŒãèšå·ãå§åйã³ãŒã¹ãšåäž |
ãšãã«ã®ãŒåäœã è¶ äŒå°å路㯠GHzãã€ãªã³ãã©ãããšäžæ§åå㯠MHzãã¹ãã³ã¯ MHz ãŸãã¯ãã¹ã©ã§è¡šããŸãã第1ç« ã§æç®ãäžåºŠç€ºã â 1 GHz 㯠4.14 $\mu$eV ã«ããã㊠48 mK ã«å¯Ÿå¿ããŸã â 以éã®åç« ã¯ãã®åéã®æç®ãçšããåäœã«åŸããŸãã
éåãããã®é åºã éåããã0ã巊端ãã€æäžäœãããã§ãããéåã³ã³ãã¥ãŒãã£ã³ã°å ¥éãšå®å šã«åäžã§ããããã¯Qiskitã®èŠçŽãšã¯éã§ãã
ð æ¬ã·ãªãŒãºã®ç¯å²
æ¬ã·ãªãŒãºã¯ç©çãšææã®è¬åº§ã§ããåæ¹åŒãããã«ããã¢ã³ããæç€ºããåæ©æ§ãå°èŠæš¡ã§æ°å€çã«æ€èšŒããåã³ããŒã¬ã³ã¹éçãç©ççãªèµ·æºãŸã§èŸ¿ããŸãã
æ§èœã¬ã³ãŒã衚ã§ã¯ãããŸããã éåãããæ°ãå¿ å®åºŠã®èšé²ãåŒçšãããè£ çœ®ã¹ããã¯ã¯å š5ç« ã®ã©ãã«ãç»å ŽããŸãããããããæ°å€ã¯èªãŸããåã«å€ããªããããã説æã®åããã¡ãŸãããã¹ã±ãŒãªã³ã°åãéžæåãåå çã®è°è«ã¯çã§ããç¶ããŸãã
ãã³ããŒæ¯èŒã§ã¯ãããŸããã äŒæ¥ã®ããŒããããã補ååãã©ããå è¡ããŠãããã®è©äŸ¡ã¯æ±ããŸãããæ¹åŒãæ¯èŒããç®æã§ã¯ç©ççå¶çŽã§æ¯èŒãã第5ç« ã¯ãŸã åè ãããªãããšãæèšããŸãã
ã¢ã«ãŽãªãºã ã®è¬åº§ã§ã¯ãããŸããã ãããã®è£ 眮ãäœãèšç®ããã®ãããããŠãªãææç ç©¶è ãããããé¢å¿ããã€ã¹ããªã®ãã¯éåã³ã³ãã¥ãŒãã£ã³ã°å ¥éããèªã¿ãã ãããæ¬ã³ãŒã¹ã¯ãã®å¯Ÿã®çæ¹ã§ãã
宣äŒã§ã¯ãããŸããã ããŸã ã§ããªãããããŠæ¹åãããã¹ãææã¯ããã ããèª å®ãªçãã§ãããšãã¯ããããè¿ã£ãŠããçãã§ãã
ð æšå¥šåŠç¿ãã¹
ãã¿ãŒã³1ïŒå®å šç¿åŸã³ãŒã¹ïŒ6-7æ¥ïŒ
- 1æ¥ç®ïŒç¬¬1ç« 1.1-1.5ç¯ â åºæºã軞ããã³ããŒã¬ã³ã¹ã®èšèª
- 2æ¥ç®ïŒç¬¬1ç« 1.6ç¯ â ãã®5ã€ã®ã³ãŒãäŸãå®è¡ãïŒã³ãŒãäŸ1ã2ã¯1.1ç¯ãš1.3ç¯ã«ãããŸãïŒãRamsey/ãšã³ãŒã®åé¢ãèªåã§åçŸãã
- 3æ¥ç®ïŒç¬¬2ç« â è¶ äŒå°éåããããTLSãšåå çã®ç¯ã§ç· ãã
- 4æ¥ç®ïŒç¬¬3ç« â ã€ãªã³ãã©ãã
- 5æ¥ç®ïŒç¬¬4ç« â äžæ§åå
- 6æ¥ç®ïŒç¬¬5ç« 5.1-5.3ç¯ â å ãã¹ãã³ãããããžãŒ
- 7æ¥ç®ïŒç¬¬5ç« 5.4-5.5ç¯ãšæŒç¿ â ã¹ã³ã¢ã«ãŒããšããããèªåã®ç ç©¶ã«äœãæå³ããã
ãã¿ãŒã³2ïŒ1æ¹åŒãæ·±ãïŒ1æ¥ïŒ
- 第1ç« 1.2-1.4ç¯ â ä»ãèªãã®ã«è¶³ãèšèª
- é¢å¿ã®ããæ¹åŒã®ç« ããã³ãŒããŸã§å«ããŠéèª
- 第5ç« 5.4ç¯ â ãã®æ¹åŒãä»ãšæ¯ã¹ãŠã©ãã«äœçœ®ããã
ãã¿ãŒã³3ïŒææç ç©¶è ã³ãŒã¹ïŒåæ¥ïŒ
- 1.5ç¯ â æ¬ã³ãŒã¹ã®ç«å Žãšãåæ¹åŒãå¶éããŠãããã®ã®è¡š
- 2.6ç¯ â èªé»æå€±ãTLSãåå çè§£æãæ¬ã·ãªãŒãºã§æãèžã¿èŸŒãã ææã®è°è«
- 3.6ç¯ â ãã©ãã衚é¢ã«ç±æ¥ããç°åžžå ç±
- 5.2ç¯ãš5.5ç¯ â åäœäœç²Ÿè£œãšãææç§åŠãè²¢ç®ãããäœå°
ð¯ ç·ååŠç¿ææ
ç¥èã¬ãã«
- â DiVincenzoåºæºãš6æ¬ã®æ¯èŒè»žãæãã軞ãç©ççã«çµåããŠããçç±ã説æã§ãã
- â åäž»èŠæ¹åŒã®åäœåçãããã«ããã¢ã³ãã説æã§ãã
- â $T_1$ã$T_2$ã$T_2^\ast$ ãå®çŸ©ãããããããç°å¢ã®ã©ã®åšæ³¢æ°åãæ¢ã£ãŠããããèšãã
- â åæ¹åŒã§æ¯é çãªãææã«åŸéããããã³ããŒã¬ã³ã¹ãã£ãã«ãæãããã
å®è·µã¹ãã«
- â Blochæ¹çšåŒãç©åããRabiã»Ramseyã»ãšã³ãŒã»CPMGã®æž¬å®ãæ°å€çã«åçŸã§ãã
- â ãã©ã³ãºã¢ã³ã®ããã«ããã¢ã³ãé»è·åºåºã§å¯Ÿè§åããéèª¿åæ§ãšé»è·åæ£ãåãåºãã
- â Mathieuå®å®å³ãRydbergå°éã®æéçºå±ã亀æçµåãã2ã¹ãã³ã®ã¹ãã¯ãã«ãèšç®ã§ãã
- â ãšãã«ã®ãŒã¹ã±ãŒã«ãåäœæž©åºŠãã²ãŒãäºç®ã第äžåçããèŠç©ããã
å¿çšå
- â ããŒããŠã§ã¢ã®è«æãèªã¿ãè£ çœ®ã¹ããã¯ãšã¯åãé¢ããŠãã®ç©çç䞻匵ãç¹å®ã§ãã
- â äžçµã®ã³ããŒã¬ã³ã¹æž¬å®ãããã©ã®ãã€ãºåž¯åãããã£ãŠã©ã®æ¬ é¥éå£ãå€åãããã蚺æã§ãã
- â èªåã®ææåéã®å°éæ§ãæ¬åéã®çŸåšã®åŸéèŠå ãšäº€ããå ŽæãèŠã€ãããã
ð ïž äœ¿çšæè¡ã»ããŒã«
äž»èŠã©ã€ãã©ãª
- numpy â æ¬ã·ãªãŒãºã®ãã¹ãŠã®ã·ãã¥ã¬ãŒã·ã§ã³
- scipy â Blochæ¹çšåŒã®ODEç©åãåºæå€åé¡ãMathieuæ¹çšåŒã®ããã®ç¹æ®é¢æ°
- matplotlib â ã³ããŒã¬ã³ã¹æ²ç·ãå®å®å³ãããã³ã·ã£ã«åœ¢ç¶
éçºç°å¢
- Python : 3.8以äž
- Jupyter Notebook : æšå¥šãã»ãšãã©ã®äŸãçãæ¢çŽ¢çãªãã
- Google Colabã§ãã¹ãŠã®äŸãåäœããŸããGPUãéåããã¯ãšã³ããå®éšè£ 眮ã¯ããããäžèŠã§ã
ð æ¬¡ã®ã¹ããã
çºå±åŠç¿
- åè·¯éåé»ç£ååŠã忣èªã¿åºããšãã©ã¡ããªãã¯å¢å¹ ãæ¬æ Œçã«æ±ãæ°Žæºã§
- ããªã±ã«ãã³ã«ãããã¢ã¢ã«ãã¡ã¹èªé»äœã®ãã€ã¯ãæ³¢æå€±ãçµæãšåããããæž¬å®æè¡ã
- éå誀ãèšæ£ãšèæ éã¢ãŒããã¯ãã£ããããŠç¬Šå·ã®éžæãæ¹åŒã®æäŸããæ¥ç¶æ§ã«ã©ãäŸåããã
- ãã©ãã黿¥µãšæµ ãæ¬ é¥äžå¿ã®è¡šé¢ç§åŠ
é¢é£ã·ãªãŒãº
- éåã³ã³ãã¥ãŒãã£ã³ã°å ¥é â ãã®å¯Ÿã®ã¢ã«ãŽãªãºã åŽ
- éåæ©æ¢°åŠç¿å ¥é â MIåŽã§ã®å¿çšãšãå€å žããŒã¹ã©ã€ã³ã«åãŠããã®èª å®ãªæ€èšŒ
- éåã»ã³ã·ã³ã°å ¥é â åãéåç³»ãææã®èšæž¬åšãšããŠäœ¿ã
- éåãœãããŠã§ã¢ã¹ã¿ãã¯å ¥é â ã³ã³ãã€ã©ã»èŒæ£ã»èª€ãç·©åãå®éã«äœãããŠãããããããã¹ã¿ãã¯ã®èªäœã§åŠã¶
- éåååŠå ¥é â 2æºäœç³»ãèª¿åæ¯ååãæåè«
- è¶ äŒå°å ¥é â Cooper察圢æãšãžã§ã»ããœã³å¹æãæ¬æ Œçã«
- ã¹ãã³ãããã¯ã¹å ¥é â ã¹ãã³èŒžéã亀æçžäºäœçšãç£æ§ææ
å®è·µãããžã§ã¯ã
- 第1ç« ã®éå ·ç®±ã2éåãããã«æ¡åŒµããçžé¢ãã€ãºäžã§ã®2éåãããã²ãŒããã·ãã¥ã¬ãŒããã
- å ¬è¡šããã $T_1$ ãŸã㯠$Q_i$ ã®ããŒã¿ãåããåå çã¢ãã«ã§è¡šé¢æå€±è§ãæœåºãã
- æš¡æ¬ããŒã¿ã«å¯ŸããŠCPMGãã€ãºåå ãå®è£ ãã3æ¡ã«ããã£ãŠ $S(f)$ ã埩å ãã
- éžãã æ¹åŒã«ã€ããŠãä»®æ³çãª1000éåãããæ©ã®å·åŽããã³å¶åŸ¡ãã£ãã«ã®äºç®ãèŠç©ãã
â ïž å 責äºé
- æ¬ã³ã³ãã³ãã¯æè²ã»ç ç©¶ã»æ å ±æäŸã®ã¿ãç®çãšããŠãããå°éçãªå©èš(æ³åŸã»äŒèšã»æè¡çä¿èšŒãªã©)ãæäŸãããã®ã§ã¯ãããŸããã
- æ¬ã³ã³ãã³ãããã³ä»éããCode examplesã¯ãçŸç¶æå§¿(AS IS)ãã§æäŸãããæç€ºãŸãã¯é»ç€ºãåãããååæ§ãç¹å®ç®çé©åæ§ãæš©å©éäŸµå®³ãæ£ç¢ºæ§ã»å®å šæ§ãåäœã»å®å šæ§çãããªãä¿èšŒãããŸããã
- å€éšãªã³ã¯ã第äžè ãæäŸããããŒã¿ã»ããŒã«ã»ã©ã€ãã©ãªçã®å 容ã»å¯çšæ§ã»å®å šæ§ã«ã€ããŠãäœæè ããã³æ±å倧åŠã¯äžåã®è²¬ä»»ãè² ããŸããã
- æ¬ã³ã³ãã³ãã®å©çšã»å®è¡ã»è§£éã«ããçŽæ¥çã»éæ¥çã»ä»éçã»ç¹å¥ã»çµæçã»æ²çœ°çæå®³ãçããå Žåã§ããé©çšæ³ã§èš±å®¹ãããæå€§éã®ç¯å²ã§ãäœæè ããã³æ±å倧åŠã¯è²¬ä»»ãè² ããŸããã
- æ¬ã³ã³ãã³ãã®å 容ã¯ãäºåãªã倿Žã»æŽæ°ã»æäŸåæ¢ãããããšããããŸãã
- æ¬ã³ã³ãã³ãã®èäœæš©ã»ã©ã€ã»ã³ã¹ã¯æèšãããæ¡ä»¶(äŸ: CC BY 4.0)ã«åŸããŸããåœè©²ã©ã€ã»ã³ã¹ã¯éåžžãç¡ä¿èšŒæ¡é ãå«ã¿ãŸãã