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Kuantum Devrelerinde Kapı ve Giriş Tespiti için YOLO Tabanlı Bir Yöntem

Yıl 2023, Cilt: 35 Sayı: 2, 527 - 540, 01.09.2023
https://doi.org/10.35234/fumbd.1269274

Öz

Tersinir kuantum devreleri farklı türde ve sayıdaki kuantum kapıları kullanılarak oluşturulmaktadır. Kuantum devreleri oluşturulurken kullanılacak kapı sayısının optimize edilmesi maliyeti ve karmaşıklığı azaltmaktadır. Tersinir kuantum devrelerinde durum tablolarının elde edilmesi ve optimizasyonu için giriş sayısı, çıkış sayısı ve kapı sayılarının bilinmesi önemlidir. Ayrıca bu parametreler kuantum devrelerinde oluşabilecek arızaların tespit edilmesinde de kullanılmaktadır. Literatürde kuantum devreleri için giriş, çıkış ve kapı sayılarının tespitinde eksiklik vardır. Ayrıca, literatürde yapılan uygulamaların test edilebilmesi için sınırlı sayıdaki standart kuantum devreleri kullanılmaktadır. Bu kapsamda kullanılabilecek veri setlerinin çok az olduğu tespit edilmiştir. Literatürdeki bu eksikliklerin giderilmesi çalışmamızın amacını, önerilen yöntem ise çalışmamızın özgünlüğünü oluşturmaktadır. Bu çalışmada Yolo (You Only Look Once) tabanlı yöntemler kullanılarak kapı sayısı ve giriş sayısı tespit edilmiştir. “MATLAB” ve “RCViewer+” programları kullanılarak CNOT, Feynman ve Toffoli kapılarından oluşan büyük bir veri seti oluşturulmuştur. Bu çalışmada, 1-8 kapı sayısına ve 3-7 giriş sayısına sahip toplamda 5000 adet kuantum devre oluşturulmuştur. Elde edilen veri setleri üzerinde kapılar ve girişler etiketlenmiştir. Etiketlenen veri setleri üzerinde 80:20 eğitim ve test oranı ile YoloV4, YoloV7 ve YoloV7x yöntemleri uygulanmıştır. YoloV4, YoloV7 ve YoloV7x yöntemleri için sırasıyla %87.1, %89.7 ve %89.3 mAP hesaplanmıştır. Önerilen yöntem 2800 iterasyon çalıştırılmış ve en iyi sonuç YoloV7 algoritması ile elde edilmiştir.

Destekleyen Kurum

TÜBİTAK

Proje Numarası

121E439

Teşekkür

Bu çalışma TUBİTAK tarafından desteklenmiştir. Proje No: 121E439.

Kaynakça

  • Zeilinger A. Experiment and the foundations of quantum physics. Rev Mod Phys 1999;71.
  • Yetis H, Karakose M. Optimization of Mass Customization Process using. IEEE International Symposium on Systems Engineering (ISSE), 2020.
  • Kubodera M, Awai H. Automatic Quantum Circuit Generator by Genetic Programming and Three-qubit Superdense Coding to Transmit Three Classical Bit Codes n.d.
  • Khalfaoui K, Boudjedaa T, Kerkouche EH. Automatic design of quantum circuits: Generation of quantum teleportation protocols. Quantum Inf Process 2021;20:283. https://doi.org/10.1007/s11128-021-03208-8.
  • Yetiş H, Karaköse M. A New Framework Containing Convolution and Pooling Circuits for Image Processing and Deep Learning Applications with Quantum Computing Implementation. TS 2022;39:501–12. https://doi.org/10.18280/ts.390212.
  • Yuan S, Venegas-Andraca SE, Wang Y, Luo Y, Mao X. Quantum Image Edge Detection Algorithm. Int J Theor Phys 2019;58:2823–33. https://doi.org/10.1007/s10773-019-04166-9.
  • Nagamani AN, Prasad HV, Hathwar RS, Agrawal VK. Design of optimized reversible multiplier for high speed DSP application. 2015 10th International Conference on Information, Communications and Signal Processing (ICICS), Singapore: IEEE; 2015, p. 1–5. https://doi.org/10.1109/ICICS.2015.7459869.
  • Steane A. Quantum Computing. Rep Prog Phys 1998;61:117–73. https://doi.org/10.1088/0034-4885/61/2/002.
  • Shor PW. Fault-Tolerant Quantum Computation n.d.
  • Short PW. Polynomial-Time Algorithms for Prime Factorization and Discrete Logarithms on a Quantum Computer 2023.
  • Shor PW. Algorithms for quantum computation: discrete logarithms and factoring 2002:124–34. https://doi.org/10.1109/sfcs.1994.365700.
  • Kheirandish D, Haghparast M, Reshadi M, Hosseinzadeh M. Efficient techniques for fault detection and location of multiple controlled Toffoli-based reversible circuit. Quantum Information Processing 2021;20:1–31. https://doi.org/10.1007/s11128-021-03292-w.
  • Kuantum bilgisayar nedir, nasıl çalışır ve nasıl yapılır? 2019.
  • Mohammed FMA. Yüksek Performanslı Kuantum Hesaplama Simülasyonları. Karadeniz Teknik Üniversitesi, 2019.
  • Kheirandish D, Haghparast M, Reshadi M, Hosseinzadeh M. Efficient designs of reversible sequential circuits. J Supercomput 2021;77:13828–62. https://doi.org/10.1007/s11227-021-03735-2.
  • Handique M, Biswas S, Deka JK. Test Generation for Bridging Faults in Reversible Circuits Using Path-Level Expressions. J Electron Test 2019;35:441–57. https://doi.org/10.1007/s10836-019-05811-1.
  • Pathak N, Misra NK, Bhoi BK, Kumar S. Concept and Algorithm of Quantum Computing During Pandemic Situation of COVID-19. In: Somani AK, Mundra A, Doss R, Bhattacharya S, editors. Smart Systems: Innovations in Computing, vol. 235, Singapore: Springer Singapore; 2022, p. 523–35. https://doi.org/10.1007/978-981-16-2877-1_48.
  • Thakral S, Bansal D. A Quick Guide to Implement Reversible Logic. 2018 4th International Conference on Computing Communication and Automation (ICCCA), Greater Noida, India: IEEE; 2018, p. 1–5. https://doi.org/10.1109/CCAA.2018.8777469.
  • Gaur HM, Singh AK, Ghanekar U. Offline Testing of Reversible Logic Circuits: An Analysis. Integration 2018;62:50–67. https://doi.org/10.1016/j.vlsi.2018.01.004.
  • Hüseyi̇n Ulucan. Süperi̇letken kubi̇tli̇ kuantum bi̇lgi̇sayarlar ve kuantum hesaplama. İstanbul Gelişim Üniveritesi, 2017.
  • Yetiş H, Karaköse M. The Usage of Quantum Computer and Computing for High Performance in Machine Learning Methods. Türkiye Bilişim Vakfı Bilgisayar Bilimleri Ve Mühendisliği Dergisi 2021:47–56.
  • Soeken M, Frehse S, Wille R, Drechsler R. Revkit: A toolkit for reversible circuit design. Journal of Multiple-Valued Logic and Soft Computing 2012;18:55–65.
  • Yetis H, Karakose M. Binary Pooling Circuits for Quantum Computing. 2021 International Conference on Decision Aid Sciences and Application, DASA 2021 2021:161–4. https://doi.org/10.1109/DASA53625.2021.9682243.
  • Susam Ö, Altun M. An efficient algorithm to synthesize quantum circuits and optimization. 2014 21st IEEE International Conference on Electronics, Circuits and Systems, ICECS 2014 2014:570–3. https://doi.org/10.1109/ICECS.2014.7050049.
  • Lukac M, Kameyama M, Perkowski M, Kerntopf P, Moraga C. Fault Models in Reversible and Quantum Circuits 2017:475–93. https://doi.org/10.1007/978-3-319-33924-5_19.
  • Perkowski M, Biamonte J, Lukac M. Test generation and fault localization for quantum circuits. Proceedings of The International Symposium on Multiple-Valued Logic 2005:62–8. https://doi.org/10.1109/ismvl.2005.46.
  • Haydar Kızılırmak. Kuantum Hata Düzeltme. Ankara Üniversitesi Fen Bilimleri Enstitüsü, 2020.
  • Thakral S, Manhas P, Verma J. Quantum Implementation of Reversible Logic Gates Using RCViewer+ Tool. In: Dutta P, Chakrabarti S, Bhattacharya A, Dutta S, Piuri V, editors. Emerging Technologies in Data Mining and Information Security, vol. 491, Singapore: Springer Nature Singapore; 2023, p. 409–18. https://doi.org/10.1007/978-981-19-4193-1_39.
  • Thakral S, Bansal D. Optimized Quantum Implementation Approach. 2019 5th International Conference On Computing, Communication, Control And Automation (ICCUBEA), Pune, India: IEEE; 2019, p. 1–5. https://doi.org/10.1109/ICCUBEA47591.2019.9128728.
  • Thakral S, Bansal D. A Novel Reversible DSG Gate and Its Quantum Implementation. In: Singh Tomar G, Chaudhari NS, Barbosa JLV, Aghwariya MK, editors. International Conference on Intelligent Computing and Smart Communication 2019, Singapore: Springer Singapore; 2020, p. 1443–50. https://doi.org/10.1007/978-981-15-0633-8_142.
  • Thabah SD, Saha P. Low Quantum Cost Realization of Reversible Binary-Coded-Decimal Adder. Procedia Computer Science 2020;167:1437–43. https://doi.org/10.1016/j.procs.2020.03.354.
  • Kamaraj A, Marichamy P, Kaviyashri KP. Realization and Optimization of Quantum Equivalent Circuits of Reversible Combinational Circuits. J Comput Theor Nanosci 2020;17:2080–4. https://doi.org/10.1166/jctn.2020.8852.
  • Sultana M, Prasad M, Roy P, Sarkar S, Das S, Chaudhuri A. Comprehensive quantum analysis of existing four variable reversible gates. 2017 Devices for Integrated Circuit (DevIC), Kalyani, India: IEEE; 2017, p. 116–20. https://doi.org/10.1109/DEVIC.2017.8073918.
  • Kalantari Z, Eshghi M, Mohammadi M, Jassbi S. Low-cost and compact design method for reversible sequential circuits. J Supercomput 2019;75:7497–519. https://doi.org/10.1007/s11227-019-02912-8.
  • Du Y, Pan N, Xu Z, Deng F, Shen Y, Kang H. Pavement distress detection and classification based on YOLO network. International Journal of Pavement Engineering 2020;0:1–14. https://doi.org/10.1080/10298436.2020.1714047.
  • Chen J, Liu H, Zhang Y, Zhang D, Ouyang H, Chen X. A Multiscale Lightweight and Efficient Model Based on YOLOv7: Applied to Citrus Orchard. Plants 2022;11:3260. https://doi.org/10.3390/plants11233260.
  • Demir K, Yaman O. Su Altı Çöp Tespiti İçin YOLOv4 Tabanlı Bir Yöntem. International Informatics Congress (IIC2022), Batman, Türkiye: 2022.

A YOLO-Based Method for Detection of Gate and Input in Quantum Circuits

Yıl 2023, Cilt: 35 Sayı: 2, 527 - 540, 01.09.2023
https://doi.org/10.35234/fumbd.1269274

Öz

Reversible quantum circuits are constructed using different types and numbers of quantum gates. Optimizing the number of gates to be used while creating quantum circuits reduces the cost and complexity. It is important to know the number of inputs, outputs, and gates for obtaining and optimizing state tables in reversible quantum circuits. In addition, these parameters are also used to detect faults that may occur in quantum circuits. There is a lack of determination of the input, output, and gate numbers for quantum circuits in the literature. In addition, a limited number of standard quantum circuits are used to test the applications made in the literature. It has been determined that there are very few datasets that can be used in this context. Elimination of these deficiencies in the literature constitutes the aim of our study, and the proposed method constitutes the originality of our study. In this study, the number of gates and inputs were determined by using Yolo (You Only Look Once) based methods. A large dataset consisting of CNOT, Feynman, and Toffoli gates was created using the “MATLAB” and “RCViewer+” programs. In this study, a total of 5000 quantum circuits with 1-8 gate numbers and 3-7 input numbers were created. Gates and inputs are labeled on the obtained datasets. YoloV4, YoloV7, and YoloV7x methods were applied to the tagged datasets with a training and testing ratio of 80:20. 87.1%, 89.7% and 89.3% mAP were calculated for the YoloV4, YoloV7 and YoloV7x methods, respectively. The proposed method was run for 2800 iterations and the best result was obtained with the YoloV7 algorithm.

Proje Numarası

121E439

Kaynakça

  • Zeilinger A. Experiment and the foundations of quantum physics. Rev Mod Phys 1999;71.
  • Yetis H, Karakose M. Optimization of Mass Customization Process using. IEEE International Symposium on Systems Engineering (ISSE), 2020.
  • Kubodera M, Awai H. Automatic Quantum Circuit Generator by Genetic Programming and Three-qubit Superdense Coding to Transmit Three Classical Bit Codes n.d.
  • Khalfaoui K, Boudjedaa T, Kerkouche EH. Automatic design of quantum circuits: Generation of quantum teleportation protocols. Quantum Inf Process 2021;20:283. https://doi.org/10.1007/s11128-021-03208-8.
  • Yetiş H, Karaköse M. A New Framework Containing Convolution and Pooling Circuits for Image Processing and Deep Learning Applications with Quantum Computing Implementation. TS 2022;39:501–12. https://doi.org/10.18280/ts.390212.
  • Yuan S, Venegas-Andraca SE, Wang Y, Luo Y, Mao X. Quantum Image Edge Detection Algorithm. Int J Theor Phys 2019;58:2823–33. https://doi.org/10.1007/s10773-019-04166-9.
  • Nagamani AN, Prasad HV, Hathwar RS, Agrawal VK. Design of optimized reversible multiplier for high speed DSP application. 2015 10th International Conference on Information, Communications and Signal Processing (ICICS), Singapore: IEEE; 2015, p. 1–5. https://doi.org/10.1109/ICICS.2015.7459869.
  • Steane A. Quantum Computing. Rep Prog Phys 1998;61:117–73. https://doi.org/10.1088/0034-4885/61/2/002.
  • Shor PW. Fault-Tolerant Quantum Computation n.d.
  • Short PW. Polynomial-Time Algorithms for Prime Factorization and Discrete Logarithms on a Quantum Computer 2023.
  • Shor PW. Algorithms for quantum computation: discrete logarithms and factoring 2002:124–34. https://doi.org/10.1109/sfcs.1994.365700.
  • Kheirandish D, Haghparast M, Reshadi M, Hosseinzadeh M. Efficient techniques for fault detection and location of multiple controlled Toffoli-based reversible circuit. Quantum Information Processing 2021;20:1–31. https://doi.org/10.1007/s11128-021-03292-w.
  • Kuantum bilgisayar nedir, nasıl çalışır ve nasıl yapılır? 2019.
  • Mohammed FMA. Yüksek Performanslı Kuantum Hesaplama Simülasyonları. Karadeniz Teknik Üniversitesi, 2019.
  • Kheirandish D, Haghparast M, Reshadi M, Hosseinzadeh M. Efficient designs of reversible sequential circuits. J Supercomput 2021;77:13828–62. https://doi.org/10.1007/s11227-021-03735-2.
  • Handique M, Biswas S, Deka JK. Test Generation for Bridging Faults in Reversible Circuits Using Path-Level Expressions. J Electron Test 2019;35:441–57. https://doi.org/10.1007/s10836-019-05811-1.
  • Pathak N, Misra NK, Bhoi BK, Kumar S. Concept and Algorithm of Quantum Computing During Pandemic Situation of COVID-19. In: Somani AK, Mundra A, Doss R, Bhattacharya S, editors. Smart Systems: Innovations in Computing, vol. 235, Singapore: Springer Singapore; 2022, p. 523–35. https://doi.org/10.1007/978-981-16-2877-1_48.
  • Thakral S, Bansal D. A Quick Guide to Implement Reversible Logic. 2018 4th International Conference on Computing Communication and Automation (ICCCA), Greater Noida, India: IEEE; 2018, p. 1–5. https://doi.org/10.1109/CCAA.2018.8777469.
  • Gaur HM, Singh AK, Ghanekar U. Offline Testing of Reversible Logic Circuits: An Analysis. Integration 2018;62:50–67. https://doi.org/10.1016/j.vlsi.2018.01.004.
  • Hüseyi̇n Ulucan. Süperi̇letken kubi̇tli̇ kuantum bi̇lgi̇sayarlar ve kuantum hesaplama. İstanbul Gelişim Üniveritesi, 2017.
  • Yetiş H, Karaköse M. The Usage of Quantum Computer and Computing for High Performance in Machine Learning Methods. Türkiye Bilişim Vakfı Bilgisayar Bilimleri Ve Mühendisliği Dergisi 2021:47–56.
  • Soeken M, Frehse S, Wille R, Drechsler R. Revkit: A toolkit for reversible circuit design. Journal of Multiple-Valued Logic and Soft Computing 2012;18:55–65.
  • Yetis H, Karakose M. Binary Pooling Circuits for Quantum Computing. 2021 International Conference on Decision Aid Sciences and Application, DASA 2021 2021:161–4. https://doi.org/10.1109/DASA53625.2021.9682243.
  • Susam Ö, Altun M. An efficient algorithm to synthesize quantum circuits and optimization. 2014 21st IEEE International Conference on Electronics, Circuits and Systems, ICECS 2014 2014:570–3. https://doi.org/10.1109/ICECS.2014.7050049.
  • Lukac M, Kameyama M, Perkowski M, Kerntopf P, Moraga C. Fault Models in Reversible and Quantum Circuits 2017:475–93. https://doi.org/10.1007/978-3-319-33924-5_19.
  • Perkowski M, Biamonte J, Lukac M. Test generation and fault localization for quantum circuits. Proceedings of The International Symposium on Multiple-Valued Logic 2005:62–8. https://doi.org/10.1109/ismvl.2005.46.
  • Haydar Kızılırmak. Kuantum Hata Düzeltme. Ankara Üniversitesi Fen Bilimleri Enstitüsü, 2020.
  • Thakral S, Manhas P, Verma J. Quantum Implementation of Reversible Logic Gates Using RCViewer+ Tool. In: Dutta P, Chakrabarti S, Bhattacharya A, Dutta S, Piuri V, editors. Emerging Technologies in Data Mining and Information Security, vol. 491, Singapore: Springer Nature Singapore; 2023, p. 409–18. https://doi.org/10.1007/978-981-19-4193-1_39.
  • Thakral S, Bansal D. Optimized Quantum Implementation Approach. 2019 5th International Conference On Computing, Communication, Control And Automation (ICCUBEA), Pune, India: IEEE; 2019, p. 1–5. https://doi.org/10.1109/ICCUBEA47591.2019.9128728.
  • Thakral S, Bansal D. A Novel Reversible DSG Gate and Its Quantum Implementation. In: Singh Tomar G, Chaudhari NS, Barbosa JLV, Aghwariya MK, editors. International Conference on Intelligent Computing and Smart Communication 2019, Singapore: Springer Singapore; 2020, p. 1443–50. https://doi.org/10.1007/978-981-15-0633-8_142.
  • Thabah SD, Saha P. Low Quantum Cost Realization of Reversible Binary-Coded-Decimal Adder. Procedia Computer Science 2020;167:1437–43. https://doi.org/10.1016/j.procs.2020.03.354.
  • Kamaraj A, Marichamy P, Kaviyashri KP. Realization and Optimization of Quantum Equivalent Circuits of Reversible Combinational Circuits. J Comput Theor Nanosci 2020;17:2080–4. https://doi.org/10.1166/jctn.2020.8852.
  • Sultana M, Prasad M, Roy P, Sarkar S, Das S, Chaudhuri A. Comprehensive quantum analysis of existing four variable reversible gates. 2017 Devices for Integrated Circuit (DevIC), Kalyani, India: IEEE; 2017, p. 116–20. https://doi.org/10.1109/DEVIC.2017.8073918.
  • Kalantari Z, Eshghi M, Mohammadi M, Jassbi S. Low-cost and compact design method for reversible sequential circuits. J Supercomput 2019;75:7497–519. https://doi.org/10.1007/s11227-019-02912-8.
  • Du Y, Pan N, Xu Z, Deng F, Shen Y, Kang H. Pavement distress detection and classification based on YOLO network. International Journal of Pavement Engineering 2020;0:1–14. https://doi.org/10.1080/10298436.2020.1714047.
  • Chen J, Liu H, Zhang Y, Zhang D, Ouyang H, Chen X. A Multiscale Lightweight and Efficient Model Based on YOLOv7: Applied to Citrus Orchard. Plants 2022;11:3260. https://doi.org/10.3390/plants11233260.
  • Demir K, Yaman O. Su Altı Çöp Tespiti İçin YOLOv4 Tabanlı Bir Yöntem. International Informatics Congress (IIC2022), Batman, Türkiye: 2022.
Toplam 37 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Mühendislik
Bölüm MBD
Yazarlar

Reyhan Yılmaz 0000-0001-5899-0957

Orhan Yaman 0000-0001-9623-2284

Mehmet Karaköse 0000-0002-3276-3788

Proje Numarası 121E439
Yayımlanma Tarihi 1 Eylül 2023
Gönderilme Tarihi 22 Mart 2023
Yayımlandığı Sayı Yıl 2023 Cilt: 35 Sayı: 2

Kaynak Göster

APA Yılmaz, R., Yaman, O., & Karaköse, M. (2023). Kuantum Devrelerinde Kapı ve Giriş Tespiti için YOLO Tabanlı Bir Yöntem. Fırat Üniversitesi Mühendislik Bilimleri Dergisi, 35(2), 527-540. https://doi.org/10.35234/fumbd.1269274
AMA Yılmaz R, Yaman O, Karaköse M. Kuantum Devrelerinde Kapı ve Giriş Tespiti için YOLO Tabanlı Bir Yöntem. Fırat Üniversitesi Mühendislik Bilimleri Dergisi. Eylül 2023;35(2):527-540. doi:10.35234/fumbd.1269274
Chicago Yılmaz, Reyhan, Orhan Yaman, ve Mehmet Karaköse. “Kuantum Devrelerinde Kapı Ve Giriş Tespiti için YOLO Tabanlı Bir Yöntem”. Fırat Üniversitesi Mühendislik Bilimleri Dergisi 35, sy. 2 (Eylül 2023): 527-40. https://doi.org/10.35234/fumbd.1269274.
EndNote Yılmaz R, Yaman O, Karaköse M (01 Eylül 2023) Kuantum Devrelerinde Kapı ve Giriş Tespiti için YOLO Tabanlı Bir Yöntem. Fırat Üniversitesi Mühendislik Bilimleri Dergisi 35 2 527–540.
IEEE R. Yılmaz, O. Yaman, ve M. Karaköse, “Kuantum Devrelerinde Kapı ve Giriş Tespiti için YOLO Tabanlı Bir Yöntem”, Fırat Üniversitesi Mühendislik Bilimleri Dergisi, c. 35, sy. 2, ss. 527–540, 2023, doi: 10.35234/fumbd.1269274.
ISNAD Yılmaz, Reyhan vd. “Kuantum Devrelerinde Kapı Ve Giriş Tespiti için YOLO Tabanlı Bir Yöntem”. Fırat Üniversitesi Mühendislik Bilimleri Dergisi 35/2 (Eylül 2023), 527-540. https://doi.org/10.35234/fumbd.1269274.
JAMA Yılmaz R, Yaman O, Karaköse M. Kuantum Devrelerinde Kapı ve Giriş Tespiti için YOLO Tabanlı Bir Yöntem. Fırat Üniversitesi Mühendislik Bilimleri Dergisi. 2023;35:527–540.
MLA Yılmaz, Reyhan vd. “Kuantum Devrelerinde Kapı Ve Giriş Tespiti için YOLO Tabanlı Bir Yöntem”. Fırat Üniversitesi Mühendislik Bilimleri Dergisi, c. 35, sy. 2, 2023, ss. 527-40, doi:10.35234/fumbd.1269274.
Vancouver Yılmaz R, Yaman O, Karaköse M. Kuantum Devrelerinde Kapı ve Giriş Tespiti için YOLO Tabanlı Bir Yöntem. Fırat Üniversitesi Mühendislik Bilimleri Dergisi. 2023;35(2):527-40.