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自测试是对所声称量子设备的一种高安全级别验证, 仅根据设备观测到的统计数据来确认设备中所制备的量子态和所执行的测量. 制备-测量场景下量子系统的自测试可依赖于测量统计关联来实现. 目前针对制备-测量场景量子系统自测试的研究比较单一, 只有当统计关联满足一定的不等式要求时才能实现其系统的自测试. 本文进一步提出了制备-测量场景下量子比特态制备集和测量集实现自测试的新标准, 实现了比BB84粒子更多的量子比特态集及测量集的自测试, 这有利于满足实际实验对不同量子态集制备的需求. 此外, 对所提出的标准进行了鲁棒性分析, 使新标准在实验噪声下具有实际意义. 本文的研究增加了量子比特态制备和测量系统自测试标准的多样性, 有利于实际不同非纠缠单量子系统的自测试.Self-testing is the high-level security verification of a claimed quantum device, confirming the quantum states prepared in the device and the measurements performed based solely on the observed statistics. The statistical correlations can realize the self-testing of the quantum system in the preparing-and-measuring scenario. However, most of previous studies focused on the self-testing of shared entangled states between devices, at present only a few researches are presented and the existing work can only simultaneously self-test the states and measurements when some witness inequalities reach a maximum violation. We focus on four-state preparation and the selected scenarios of two measurements. In this scenario, Armin Tavakoli et al. [Tavakoli A, Kaniewski J, Vértesi T, Rosset D, Brunner N 2018 Phys. Rev. A 98 062307] have put forward a criterion based on the dimensional witness violation inequality which can achieve BB84 particles and corresponding Pauli measurements. However, in addition to the maximum violation of the inequality, any statistics with deviation from the maximum deviation cannot be self-tested. Besides, only the BB84 particle preparation and measurements system can be self-tested with that criterion, resulting in a large number of four-state preparation and two measurement systems that cannot be self-tested. Therefore, in this work, in addition to the maximum violation of that dimension inequality, we directly focus on the full observed statistics and further propose some new criteria for self-testing qubit quantum systems in the preparing-and-measiuring scenarios. And the self-testing criteria are proven in an ideal case. We construct a local isometry by using the constructions commonly used in device-independent cases, exchange the target system with the additional system, and realize the self-testing of more qubit state sets and measurement sets than BB84 particles. This meets the requirements for practical experiments to realize various tasks by different quantum state sets. In addition, we perform a robust analysis of the proposed criteria and use fidelity to describe the closeness of the state to the ideal state of the auxiliary system. Finally, an improved dimensional-dependent NPA method is used to optimize the lower bound of the robustness, making the new criteria practical under experimental noise. We use the YALIMP software package in MATLAB and the solver SEDUMI to solve this optimization problem. The present research increases the diversity of qubit state preparations and self-testing of measurement system, which is beneficial to the actual self-testing of different non-entangled single quantum systems.
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Keywords:
- self testing /
- prepare-and-measurement /
- witness inequality /
- robustness
[1] Acín A, Brunner N, Gisin N, Massar S, Pironio S, Scarani V 2007 Phys. Rev. Lett. 98 230501Google Scholar
[2] Mayers D, Yao A 2004 Quant. Inf. Comput. 4 273Google Scholar
[3] Ekert A K 1991 Phys. Rev. Lett. 67 661Google Scholar
[4] Bell J S 1964 Physics Physique Fizika 1 195Google Scholar
[5] Brunner N, Cavalcanti D, Pironio S, Scarani V, Wehner S 2014 Rev. Mod. Phys. 86 419Google Scholar
[6] Pironio S, Acín A, Massar S, de La Giroday A B, Matsukevich D N, Maunz P, Olmschenk S, Hayes D, Luo L, Manning T A, Monroe C 2010 Nature 464 1021Google Scholar
[7] Liu Y, Zhao Q, Li M H, Guan J Y, Zhang Y, Bai B, Zhang W, Liu W Z, Wu C, Yuan X, Li H, Munro W J, Wang Z, You L, Zhang J, Ma X, Fan J, Zhang Q, Pan J W 2018 Nature 562 548Google Scholar
[8] Aharon N, Massar S, Pironio S, Silman J 2016 New J. Phys. 18 025014Google Scholar
[9] Maitra A, Paul G, Roy S 2017 Phys. Rev. A 95 042344Google Scholar
[10] Gheorghiu A, Kashefi E, Wallden P 2015 New J. Phys. 17 083040Google Scholar
[11] Bancal J D, Navascués M, Scarani V, Vértesi T, Yang T H, 2015 Phys. Rev. A 91 022115Google Scholar
[12] Wang Y K, Wu X Y, Scarani V 2016 New J. Phys. 18 025021Google Scholar
[13] Pál K F, Vértesi T, Navascués M 2014 Phys. Rev. A 90 042340Google Scholar
[14] Baccari F, Augusiak R, Šupić I, Tura J, Acín A 2020 Phys. Rev. Lett. 124 020402Google Scholar
[15] Šupić I, Bowles J 2020 Quantum 4 337Google Scholar
[16] Li X H, Wang Y K, Han Y G, Qin S J, Gao F and Wen Q Y 2020 IEEE J. Sel. Areas Commun. 38 589Google Scholar
[17] Coladangelo A, Goh K T, Scarani V 2017 Nat. Commun. 8 15485Google Scholar
[18] Šupić I, Hoban M J 2016 New J. Phys. 18 075006Google Scholar
[19] Tavakoli A, Kaniewski J, Vértesi T, Rosset D, Brunner N 2018 Phys. Rev. A 98 062307Google Scholar
[20] Ambainis A, Leung D, Mancinska L, Ozols M 2008 arXiv: 0810.2937
[21] Hayashi M, Iwama K, Nishimura H, Raymond R, Yamashita S 2006 New J. Phys. 8 129Google Scholar
[22] Pawłowski M, Brunner N 2011 Phys. Rev. A 84 010302(RGoogle Scholar
[23] Li H W, Pawłowski M, Yin Z Q, Guo G C, Han Z F 2012 Phys. Rev. A 85 052308Google Scholar
[24] Masanes L 2003 arXiv: quant-ph/0309137 [quant-ph]
[25] Masanes L 2005 arXiv: quant-ph/0512100 [quant-ph]
[26] McKague M, Yang T H, Scarani V 2012 J. Phys. A Math. Theor. 45 455304Google Scholar
[27] Yang T H, Vértesi T, Bancal J D, Scarani V, Navascués M 2014 Phys. Rev. Lett. 113 040401Google Scholar
[28] Scarani V 2012 Acta Phys. Slovaca. 62 347Google Scholar
[29] Wu X Y, Cai Y, Yang T H, Le H N, Bancal J D, and Scarani V 2014 Phys. Rev. A 90 042339Google Scholar
[30] Clauser J F, Horne M A, Shimony A, Holt R A 1969 Phys. Rev. Lett. 23 880Google Scholar
[31] Navascués M, Pironio S, Acín A 2007 Phys. Rev. Lett. 98 010401Google Scholar
[32] Navascués M, Pironio S, Acín A 2008 New J. Phys. 10 073013Google Scholar
[33] Navascués M, de la Torre G, Vértesi T 2014 Phys. Rev. X 4 011011Google Scholar
[34] Navascués M, Vértesi T 2015 Phys. Rev. Lett. 115 020501Google Scholar
[35] Li H W, Mironowicz P, Pawłowski M, Yin Z Q, Wu Y C, Wang S, Chen W, Hu H G, Guo G C, Han Z F 2013 Phys. Rev. A 87 020302(RGoogle Scholar
[36] Mironowicz P, Li H W, Pawłowski M 2014 Phys. Rev. A 90 022322Google Scholar
[37] Lofberg J YALMIP: A Toolbox for Modeling and Optimization in MATLAB, Proceedings of the CACSD Conference Taipei, China, September 24, 2004
[38] Sturm J F 1999 Optim. Methods Softw. 11 625Google Scholar
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图 1 制备测量量子系统示意图, 其中Alice一侧随机制备4个量子态由x来控制态的选择; Bob一侧随机从两个测量基中进行选择, 以测量发送来的量子态, 由y控制
Fig. 1. Schematic diagram of the preparation measurement quantum system, in which four quantum states are randomly prepared on Alice’s site and x controls the selection of states. The measurements in Bob’s site are randomly selected from two measurement bases with y.
图 2 允许对制备状态和相应测量操作进行自测试的局域同构映射,
$ H $ 为哈达玛门,$ Z $ 和$ X $ 为与泡利$ {\sigma }_{x} $ ,$ {\sigma }_{z} $ 门局域等价的门,${\left|0\right.\rangle}_{{\rm{a}}{\rm{n}}{\rm{c}}{\rm{i}}{\rm{l}}{\rm{l}}{\rm{a}}}$ 是辅助系统, 具有所需自测试系统的正确维度, 并将输入态系统记为主(Main)系统Fig. 2. The local isometry for the prepared states and corresponding measurements.
$ H $ is the Hadamar gate,$ Z $ and$ X $ is the locally equivalent gate to the Pauli gate$ {\sigma }_{x}, {\sigma }_{z} $ .${\left|0\right.\rangle}_{{\rm{a}}{\rm{n}}{\rm{c}}{\rm{i}}{\rm{l}}{\rm{l}}{\rm{a}}}$ is ancilla system, which has the correct dimensions for the system to be self-tested, and the input-state system is labeled as the Main system.图 4 单态保真度
$ F $ 的下限. 在相关性误差为$ \varepsilon $ 时, 4种自测试标准的鲁棒性$(\theta ={\text{π}}/2, {\alpha }_{00}={\text{π}}/4, {\alpha }_{01}={\text{π}}/4, 2{\text{π}}/3,$ $7{\text{π}}/12, {\text{π}}/2)$ Fig. 4. Lower bound for the certifiable singlet fidelity F as a function of the imperfection of the observed correlations ε. We plot the bounds for four-setting criteria
$(\theta ={\text{π}}/2, {\alpha }_{00}= $ $ {\text{π}}/4, {\alpha }_{01}={\text{π}}/4, 2{\text{π}}/3, 7{\text{π}}/12, {\text{π}}/2)$ .表 1 QRAC实验中统计值
$ {\rm{t}}{\rm{r}}\left({\rho }_{00}{M}_{y}\right) $ 在Bloch球上的表示Table 1. The Bloch sphere expression of the value of
$ {\rm{t}}{\rm{r}}\left({\rho }_{00}{M}_{y}\right) $ in QRAC experiment制备态 测量基 $ {M}_{0} $ $ {M}_{1} $ $ {\rho }_{00} $ $ {\rm{t}}{\rm{r}}\left({\rho }_{00}{M}_{0}\right)={\boldsymbol{r}}_{00}\cdot {\boldsymbol{b}}_{0} $ $ {\rm{t}}{\rm{r}}\left({\rho }_{00}{M}_{1}\right)={\boldsymbol{r}}_{00}\cdot {\boldsymbol{b}}_{1} $ $ {\rho }_{01} $ $ {\rm{t}}{\rm{r}}\left({\rho }_{01}{M}_{0}\right)={\boldsymbol{r}}_{01}\cdot {\boldsymbol{b}}_{0} $ $ {\rm{t}}{\rm{r}}\left({\rho }_{01}{M}_{1}\right)={\boldsymbol{r}}_{01}\cdot {\boldsymbol{b}}_{1} $ $ {\rho }_{10} $ $ {\rm{t}}{\rm{r}}\left({\rho }_{10}{M}_{0}\right)={\boldsymbol{r}}_{10}\cdot {\boldsymbol{b}}_{0} $ $ {\rm{t}}{\rm{r}}\left({\rho }_{10}{M}_{1}\right)={\boldsymbol{r}}_{10}\cdot {\boldsymbol{b}}_{1} $ $ {\rho }_{11} $ $ {\rm{t}}{\rm{r}}\left({\rho }_{11}{M}_{0}\right)={\boldsymbol{r}}_{11}\cdot {\boldsymbol{b}}_{0} $ $ {\rm{t}}{\rm{r}}\left({\rho }_{11}{M}_{1}\right)={\boldsymbol{r}}_{11}\cdot {\boldsymbol{b}}_{1} $ -
[1] Acín A, Brunner N, Gisin N, Massar S, Pironio S, Scarani V 2007 Phys. Rev. Lett. 98 230501Google Scholar
[2] Mayers D, Yao A 2004 Quant. Inf. Comput. 4 273Google Scholar
[3] Ekert A K 1991 Phys. Rev. Lett. 67 661Google Scholar
[4] Bell J S 1964 Physics Physique Fizika 1 195Google Scholar
[5] Brunner N, Cavalcanti D, Pironio S, Scarani V, Wehner S 2014 Rev. Mod. Phys. 86 419Google Scholar
[6] Pironio S, Acín A, Massar S, de La Giroday A B, Matsukevich D N, Maunz P, Olmschenk S, Hayes D, Luo L, Manning T A, Monroe C 2010 Nature 464 1021Google Scholar
[7] Liu Y, Zhao Q, Li M H, Guan J Y, Zhang Y, Bai B, Zhang W, Liu W Z, Wu C, Yuan X, Li H, Munro W J, Wang Z, You L, Zhang J, Ma X, Fan J, Zhang Q, Pan J W 2018 Nature 562 548Google Scholar
[8] Aharon N, Massar S, Pironio S, Silman J 2016 New J. Phys. 18 025014Google Scholar
[9] Maitra A, Paul G, Roy S 2017 Phys. Rev. A 95 042344Google Scholar
[10] Gheorghiu A, Kashefi E, Wallden P 2015 New J. Phys. 17 083040Google Scholar
[11] Bancal J D, Navascués M, Scarani V, Vértesi T, Yang T H, 2015 Phys. Rev. A 91 022115Google Scholar
[12] Wang Y K, Wu X Y, Scarani V 2016 New J. Phys. 18 025021Google Scholar
[13] Pál K F, Vértesi T, Navascués M 2014 Phys. Rev. A 90 042340Google Scholar
[14] Baccari F, Augusiak R, Šupić I, Tura J, Acín A 2020 Phys. Rev. Lett. 124 020402Google Scholar
[15] Šupić I, Bowles J 2020 Quantum 4 337Google Scholar
[16] Li X H, Wang Y K, Han Y G, Qin S J, Gao F and Wen Q Y 2020 IEEE J. Sel. Areas Commun. 38 589Google Scholar
[17] Coladangelo A, Goh K T, Scarani V 2017 Nat. Commun. 8 15485Google Scholar
[18] Šupić I, Hoban M J 2016 New J. Phys. 18 075006Google Scholar
[19] Tavakoli A, Kaniewski J, Vértesi T, Rosset D, Brunner N 2018 Phys. Rev. A 98 062307Google Scholar
[20] Ambainis A, Leung D, Mancinska L, Ozols M 2008 arXiv: 0810.2937
[21] Hayashi M, Iwama K, Nishimura H, Raymond R, Yamashita S 2006 New J. Phys. 8 129Google Scholar
[22] Pawłowski M, Brunner N 2011 Phys. Rev. A 84 010302(RGoogle Scholar
[23] Li H W, Pawłowski M, Yin Z Q, Guo G C, Han Z F 2012 Phys. Rev. A 85 052308Google Scholar
[24] Masanes L 2003 arXiv: quant-ph/0309137 [quant-ph]
[25] Masanes L 2005 arXiv: quant-ph/0512100 [quant-ph]
[26] McKague M, Yang T H, Scarani V 2012 J. Phys. A Math. Theor. 45 455304Google Scholar
[27] Yang T H, Vértesi T, Bancal J D, Scarani V, Navascués M 2014 Phys. Rev. Lett. 113 040401Google Scholar
[28] Scarani V 2012 Acta Phys. Slovaca. 62 347Google Scholar
[29] Wu X Y, Cai Y, Yang T H, Le H N, Bancal J D, and Scarani V 2014 Phys. Rev. A 90 042339Google Scholar
[30] Clauser J F, Horne M A, Shimony A, Holt R A 1969 Phys. Rev. Lett. 23 880Google Scholar
[31] Navascués M, Pironio S, Acín A 2007 Phys. Rev. Lett. 98 010401Google Scholar
[32] Navascués M, Pironio S, Acín A 2008 New J. Phys. 10 073013Google Scholar
[33] Navascués M, de la Torre G, Vértesi T 2014 Phys. Rev. X 4 011011Google Scholar
[34] Navascués M, Vértesi T 2015 Phys. Rev. Lett. 115 020501Google Scholar
[35] Li H W, Mironowicz P, Pawłowski M, Yin Z Q, Wu Y C, Wang S, Chen W, Hu H G, Guo G C, Han Z F 2013 Phys. Rev. A 87 020302(RGoogle Scholar
[36] Mironowicz P, Li H W, Pawłowski M 2014 Phys. Rev. A 90 022322Google Scholar
[37] Lofberg J YALMIP: A Toolbox for Modeling and Optimization in MATLAB, Proceedings of the CACSD Conference Taipei, China, September 24, 2004
[38] Sturm J F 1999 Optim. Methods Softw. 11 625Google Scholar
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