A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
Advanced Search
Volume 8 Issue 3
Mar.  2021

IEEE/CAA Journal of Automatica Sinica

  • JCR Impact Factor: 15.3, Top 1 (SCI Q1)
    CiteScore: 23.5, Top 2% (Q1)
    Google Scholar h5-index: 77， TOP 5
Turn off MathJax
Article Contents
Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2021  >  8(3): 534-553
Wen-Ran Zhang, "Ground-0 Axioms vs. First Principles and Second Law: From the Geometry of Light and Logic of Photon to Mind-Light-Matter Unity-AI&QI," IEEE/CAA J. Autom. Sinica, vol. 8, no. 3, pp. 534-553, Mar. 2021. doi: 10.1109/JAS.2021.1003868
Citation: Wen-Ran Zhang, "Ground-0 Axioms vs. First Principles and Second Law: From the Geometry of Light and Logic of Photon to Mind-Light-Matter Unity-AI&QI," IEEE/CAA J. Autom. Sinica, vol. 8, no. 3, pp. 534-553, Mar. 2021. doi: 10.1109/JAS.2021.1003868
shu

Ground-0 Axioms vs. First Principles and Second Law: From the Geometry of Light and Logic of Photon to Mind-Light-Matter Unity-AI&QI

doi: 10.1109/JAS.2021.1003868
More Information
    Abstract
  • Without the geometry of light and logic of photon, observer-observability forms a paradox in modern science, truth-equilibrium finds no unification, and mind-light-matter unity is unreachable in spacetime. Subsequently, quantum mechanics has been shrouded with mysteries preventing itself from reaching definable causality for a general purpose analytical quantum computing paradigm. Ground-0 Axioms are introduced as an equilibrium-based, dynamic, bipolar set-theoretic unification of the first principles of science and the second law of thermodynamics. Related literatures are critically reviewed to justify the self-evident nature of Ground-0 Axioms. A historical misinterpretation by the founding fathers of quantum mechanics is identified and corrected. That disproves spacetime geometries (including but not limited to Euclidean and Hilbert spaces) as the geometries of light and truth-based logics (including but not limited to bra-ket quantum logic) as the logics of photon. Backed with logically definable causality and Dirac 3-polarizer experiment, bipolar quantum geometry (BQG) and bipolar dynamic logic (BDL) are identified as the geometry of light and the logic of photon, respectively, and wave-particle complementarity is shown less fundamental than bipolar complementarity. As a result, Ground-0 Axioms lead to a geometrical and logical illumination of the quantum and classical worlds as well as the physical and mental worlds. With logical resolutions to the EPR and Schrödinger’s cat paradoxes, an analytical quantum computing paradigm named quantum intelligence (QI) is introduced. It is shown that QI makes mind-light-matter unity and quantum-digital compatibility logically reachable for quantum-neuro-fuzzy AI-machinery with groundbreaking applications. It is contended that Ground-0 Axioms open a new era of science and philosophy—the era of mind-light-matter unity in which human-level white-box AI&QI is logically prompted to join Einstein’s grand unification to foster major scientific advances.

     

    • FullText(HTML)
  • loading
    • References(88)
  • [1]
    G. Boole, An Investigation of the Laws of Thought. London: MacMillan, 1854.
    [2]
    S. Carnot, Réflexions sur la Puissance Motrice du feu et sur les Machines Propres à Développer Cette Puissance. Paris: Bachelier, 1824.
    [3]
    W. R. Zhang, YinYang Bipolar Relativity: A Unifying Theory of Nature, Agents and Causality with Applications in Quantum Computing, Cognitive Informatics and Life Sciences, New York: IGI Global, 2011.
    [4]
    W. R. Zhang, “The road from fuzzy sets to definable causality and bipolar quantum intelligence–To the memory of Lotfi A. Zadeh,” J. Intell. Fuzzy Syst., vol. 36, no. 4, pp. 3019–3032, Apr. 2019. doi: 10.3233/JIFS-172159
    [5]
    J. McCarthy, “From here to human-level AI,” Artif. Intell., vol. 171, no. 18, pp. 1174–1182, Dec. 2007. doi: 10.1016/j.artint.2007.10.009
    [6]
    N. Bohr, “On the notions of causality and complementarity,” Dialectica, vol. 2, no. 3–4, pp. 312–319, Nov. 1948. doi: 10.1111/j.1746-8361.1948.tb00703.x
    [7]
    A. Einstein, Famous Letter to J. E. Switzer (1953). [cf. de Solla Price, D. (1963), Science since Babylon. Yale U. Press, New Haven, 15, Note 10. ]
    [8]
    A. Einstein, “Maxwell’s influence on the evolution of the idea of physical reality (On the one hundredth anniversary of Maxwell’s birth),” Published, 1931, in James Clerk Maxwell: A Commemoration Volume, Cambridge University Press. “On the methods of theoretical physics,” (1933) in Ideas and Opinions. (New York: Bonanza, 1954), pp. 270–276.
    [9]
    A. Einstein, “Physics and reality,” J. of the Franklin Institute, vol. 221, no. 3, pp. 349–382, 1936.
    [10]
    A. Einstein, “The foundation of the general theory of relativity,” Ann. Phys., vol. 49, pp. 769–822, 1916.
    [11]
    L. Smolin, The Trouble With Physics: The Rise of String Theory, the Fall of a Science, and what Comes Next? New York: Houghton Mifflin Company, 2006.
    [12]
    L. A. Zadeh, “Fuzzy sets,” Inform. Control, vol. 8, no. 3, pp. 338–353, Jun. 1965. doi: 10.1016/S0019-9958(65)90241-X
    [13]
    L. A. Zadeh, “Fuzzy logic,” Scholarpedia, vol. 3, no. 3, pp. 1766, 2008. doi: 10.4249/scholarpedia.1766
    [14]
    R. Rorty, Contingency, Irony, and Solidarity. Cambridge: Cambridge University Press, 1989.
    [15]
    Y. Hao, Fuzzy Control and Modeling: Analytical Foundations and Applications. New York: Wiley-IEEE Press, 2000.
    [16]
    J. M. Garibaldi, “The need for fuzzy AI,” IEEE/CAA J. Autom. Sinica, vol. 6, no. 3, pp. 610–622, May 2019. doi: 10.1109/JAS.2019.1911465
    [17]
    C. T. Lin and C. S. G. Lee, Neural Fuzzy Systems: A Neuro-Fuzzy Synergism to Intelligent Systems. Upper Saddle River, NJ, USA: Prentice Hall, 1996.
    [18]
    W. R. Zhang and L. Zhang, “A multiagent data warehousing (MADWH) and multiagent data mining (MADM) approach to brain modeling and neurofuzzy control,” Inform. Sci., vol. 167, no. 1-4, pp. 109–127, Dec. 2004. doi: 10.1016/j.ins.2003.05.011
    [19]
    S. C. Gao, M. C. Zhou, Y. R. Wang, J. J. Cheng, H. Yachi, and J. H. Wang, “Dendritic neuron model with effective learning algorithms for classification, approximation, and prediction,” IEEE Trans. Neural Netw. Learn. Syst., vol. 30, no. 2, pp. 601–614, Feb. 2019. doi: 10.1109/TNNLS.2018.2846646
    [20]
    Y. H. Luo, S. N. Zhao, D. S. Yang, and H. G. Zhang, “A new robust adaptive neural network backstepping control for single machine infinite power system with TCSC,” IEEE/CAA J. Autom. Sinica, vol. 7, no. 1, pp. 48–56, Jan. 2020.
    [21]
    P. M. Kebria, A. Khosravi, S. M. Salaken, and S. Nahavandi, “Deep imitation learning for autonomous vehicles based on convolutional neural networks,” IEEE/CAA J. Autom. Sinica, vol. 7, no. 1, pp. 82–95, Jan. 2020. doi: 10.1109/JAS.2019.1911825
    [22]
    J. F. Qiao, F. Li, C. L. Yang, W. J. Li, and K. Gu, “A self-organizing RBF neural network based on distance concentration immune algorithm,” IEEE/CAA J. Autom. Sinica, vol. 7, no. 1, pp. 276–291, Jan. 2020. doi: 10.1109/JAS.2019.1911852
    [23]
    J. J. Wang and T. Kumbasar, “Parameter optimization of interval Type-2 fuzzy neural networks based on PSO and BBBC methods,” IEEE/CAA J. Autom. Sinica, vol. 6, no. 1, pp. 247–257, Jan. 2019. doi: 10.1109/JAS.2019.1911348
    [24]
    J. F. Qiao and H. B. Zhou, “Modeling of energy consumption and effluent quality using density peaks-based adaptive fuzzy neural network,” IEEE/CAA J. Autom. Sinica, vol. 5, no. 5, pp. 968–976, Sept. 2018. doi: 10.1109/JAS.2018.7511168
    [25]
    W. R. Zhang, “Bipolar fuzzy sets and relations: A computational framework for cognitive modeling and multiagent decision analysis,” in Proc. 1st Int. Joint Conf. North American Fuzzy Information Processing Society Biannual Conf., San Antonio, TX, USA, 1994, pp. 305–309.
    [26]
    W. R. Zhang, “YinYang bipolar fuzzy sets,” in Proc. IEEE World Congr. Computational Intelligence, Anchorage, Alaska, 1998, pp. 835–840.
    [27]
    W. R. Zhang, “Equilibrium relations and bipolar cognitive mapping for online analytical processing with applications in international relations and strategic decision support,” IEEE Trans. Syst. Man Cybern. Part B:Cybern., vol. 33, no. 2, pp. 295–307, Apr. 2003. doi: 10.1109/TSMCB.2003.810444
    [28]
    W. R. Zhang and L. L. Zhang, “YinYang bipolar logic and bipolar fuzzy logic,” Inform. Sciences, vol. 165, no. 3–4, pp. 265–287, Oct. 2004. doi: 10.1016/j.ins.2003.05.010
    [29]
    W. R. Zhang, H. J. Zhang, Y. Shi, and S. S. Chen, “Bipolar linear algebra and YinYang-N-Element cellular networks for equilibrium-based biosystem simulation and regulation,” J. Biol. Syst., vol. 17, no. 4, pp. 547–576, Mar. 2009. doi: 10.1142/S0218339009002958
    [30]
    W. R. Zhang, “Equilibrium energy and stability measures for bipolar decision and global regulation,” Int. J. Fuzzy Syst., vol. 5, no. 2, pp. 114–122, 2003.
    [31]
    W. R. Zhang, “YinYang bipolar universal modus ponens (BUMP)–A fundamental law of non-linear brain dynamics for emotional intelligence and mental health,” in Proc. 10th Joint Conf. Information Sciences, Salt Lake City, Utah, US, 2007, 89–95.
    [32]
    W. R. Zhang, A. K. Pandurangi, and K. E. Peace, “YinYang dynamic neurobiological modeling and diagnostic analysis of major depressive and bipolar disorders,” IEEE. Trans. Biomed. Eng., vol. 54, no. 10, pp. 1729–39, Oct. 2007. doi: 10.1109/TBME.2007.894832
    [33]
    W. R. Zhang, A. K. Pandurangi, K. E. Peace, Y. Q. Zhang, and Z. M. Zhao, “MentalSquares: A generic bipolar support vector machine for psychiatric disorder classification, diagnostic analysis and neurobiological data mining,” Int. J. Data Min. Bioinform., vol. 5, no. 5, pp. 532–557, Oct. 2011. doi: 10.1504/IJDMB.2011.043034
    [34]
    W. R. Zhang, “From equilibrium-based business intelligence to information conservational quantum-fuzzy cryptography–A cellular transformation of bipolar fuzzy sets to quantum intelligence machinery,” IEEE Trans. Fuzzy Syst., vol. 26, no. 2, pp. 656–669, Apr. 2018. doi: 10.1109/TFUZZ.2017.2687408
    [35]
    W. R. Zhang, “Programming the mind and decrypting the universe–A bipolar quantum-neuro-fuzzy associative memory model for quantum cognition and quantum intelligence,” in Proc. Int. Joint Conf. Neural Networks, Anchorage, Alaska, USA, 2017, 1180–1187.
    [36]
    W. R. Zhang, “A logical path from neural ensemble formation to cognition with mind-light-matter unification: The eternal Dow can be told,” Int. J. Cogn. Inform. Nat. Intell., vol. 12, no. 4, pp. 20–54, 2018. doi: 10.4018/IJCINI.2018100102
    [37]
    W. R. Zhang, “Information conservational security with ‘Black Hole’ keypad compression and scalable one-time pad–An analytical quantum intelligence approach to pre- and post-quantum cryptography,” Cryptology ePrint archive (ia.cr/2019/913).
    [38]
    W. R. Zhang, “Beyond spacetime geometry – The death of philosophy and its quantum reincarnation,” J. Mod. Phys., vol. 9, no. 9A, pp. 1272–1284, Sept. 2012.
    [39]
    W. R. Zhang, “YinYang bipolar atom–An eastern road toward quantum gravity,” J. Mod. Phys., vol. 3, no. 9A, pp. 1261–1271, Sept. 2012.
    [40]
    W. R. Zhang and F. Marchetti, “A logical exposition of Dirac 3-polarizer experiment and its potential impact on computational biology,” in Proc. 6th ACM Conf. Bioinformatics, Computational Biology, and Health Informatics, Atlanta, GA, 2015, 517–518.
    [41]
    W. R. Zhang and F. Marchetti, “YinYang bipolar quantum geometry and bipolar quantum superposition Part I–A background independent geometrical and logical exposition of Dirac 3-polarizer experiment,” Fract. Geomet. Nonl. Anal. Med. Biol., vol. 1, no. 2, pp. 61–68, Aug. 2015.
    [42]
    W. R. Zhang and F. Marchetti, “YinYang bipolar quantum geometry and bipolar quantum superposition Part II–Toward an equilibrium-based analytical paradigm of quantum mechanics and quantum biology,” Fract. Geomet. Nonl. Anal. Med. Biol., vol. 2, no. 1, pp. 69–77, Aug. 2015.
    [43]
    W. R. Zhang, “G-CPT symmetry of quantum emergence and submergence–An information conservational multiagent cellular automata unification of CPT symmetry and CP violation for equilibrium-based many-world causal analysis of quantum coherence and decoherence,” J. Quant. Inform. Sci., vol. 6, no. 2, pp. 62–97, May 2016. doi: 10.4236/jqis.2016.62008
    [44]
    W. R. Zhang, “Bipolar quantum logic gates and quantum cellular combinatorics–A logical extension to quantum entanglement,” J. Quant. Inform. Sci., vol. 3, no. 2, pp. 93–105, Jun. 2013. doi: 10.4236/jqis.2013.32014
    [45]
    W. R. Zhang and K. Peace, “Causality is logically definable–Toward an equilibrium-based computing paradigm of quantum agent and quantum intelligence (QAQI),” J. Quant. Inform. Sci., vol. 4, pp. 227–268, Dec. 2014. doi: 10.4236/jqis.2014.44021
    [46]
    W. R. Zhang, “A geometrical and logical unification of mind, light and matter,” in Proc. 15th IEEE Int. Conf. Cognitive Informatics & Cognitive Computing, Palo Alto, CA, USA, 2016, 188–197.
    [47]
    R. Arul, G. Raja, A. O. Almagrabi, M. S. Alkatheiri, S. H. Chauhdary, and A. K. Bashir, “A quantum-safe key hierarchy and dynamic security association for LTE/SAE in 5G scenario,” IEEE Trans. Ind. Inform., vol. 16, no. 1, pp. 681–690, Jan. 2020. doi: 10.1109/TII.2019.2949354
    [48]
    H. Gao, J. Wu, C. Wei, and G. W. Wei, “MADM method with interval-valued bipolar uncertain linguistic information for evaluating the computer network security,” IEEE Access, vol. 7, pp. 151506–151524, Oct. 2019. doi: 10.1109/ACCESS.2019.2946381
    [49]
    W. R. Zhang, K. E. Peace, and H. J. Han, “YinYang bipolar dynamic organizational modeling for equilibrium-based decision analysis: Logical transformation of an indigenous philosophy to a global science,” Asia Pac. J. Manag., vol. 33, no. 3, pp. 723–766, Sept. 2016. doi: 10.1007/s10490-016-9480-1
    [50]
    C. Jana, M. Pal, and J. Q. Wang, “Bipolar fuzzy Dombi aggregation operators and its application in multiple-attribute decision-making process,” J. Ambient Intell. Human. Comput., vol. 10, no. 9, pp. 3533–3549, Sept. 2019. doi: 10.1007/s12652-018-1076-9
    [51]
    Y. X. Zhang, X. Yin, and Z. F. Mao, “Study on risk assessment of pharmaceutical distribution supply chain with bipolar fuzzy information,” J. Intell. Fuzzy Syst., vol. 37, no. 2, pp. 2009–2017, Sept. 2019. doi: 10.3233/JIFS-179263
    [52]
    K. T. Atanassov, “Intuitionistic fuzzy sets,” Fuzzy Sets Syst., vol. 20, no. 1, pp. 87–96, Aug. 1986. doi: 10.1016/S0165-0114(86)80034-3
    [53]
    J. F. Nash Jr., “Equilibrium points in n-person games,” Proc. Natl. Acad. Sci. USA, vol. 36, no. 1, pp. 48–49, Jan. 1950. doi: 10.1073/pnas.36.1.48
    [54]
    J. Nash, “Non-cooperative games,” Ann. Math., vol. 54, no. 2, pp. 286–295, 1951. doi: 10.2307/1969529
    [55]
    S. Hawking and L. Mlodinow, The Grand Design. New York: Random House Digital, Inc., 2010.
    [56]
    S. W. Hawking, “Black hole explosions?” Nature, vol. 248, no. 5443, pp. 30–31, Mar. 1974. doi: 10.1038/248030a0
    [57]
    A. Einstein, B. Podolsky, and N. Rosen, “Can quantum-mechanical description of physical reality be considered complete?” Phys. Rev., vol. 47, no. 10, pp. 777–780, May 1935. doi: 10.1103/PhysRev.47.777
    [58]
    E. Schrödinger, “Die gegenwärtige Situation in der Quantenmechanik,” Naturwissenschaften, vol. 23, no. 48, pp. 807–812, Nov. 1935. doi: 10.1007/BF01491891
    [59]
    P. A. M. Dirac, The Principles of Quantum Mechanics. Oxford: Oxford University Press, 1930.
    [60]
    W. Heisenberg, “Über den anschaulichen Inhalt der quantentheoretischen Kinematik und Mechanik,” Z. Physik, vol. 43, no. 3, pp. 172–198, Mar. 1927.
    [61]
    W. R. Zhang and K. E. Peace, “Revealing the ubiquitous effects of quantum entanglement--Toward a notion of god logic,” J. Quant. Inform. Sci., vol. 3, no. 4, pp. 143–153, Dec. 2013. doi: 10.4236/jqis.2013.34019
    [62]
    R. P. Feynman, Quantum Electrodynamics. Boston: Addison Wesley, 1962.
    [63]
    R. P. Feynman, QED: The Strange Theory of Light and Matter. Princeton: Princeton University Press, 1985.
    [64]
    M. Gell-Mann, “A schematic model of baryons and mesons,” Phys. Lett., vol. 8, no. 3, pp. 214–215, Feb. 1964. doi: 10.1016/S0031-9163(64)92001-3
    [65]
    P. A. M. Dirac, “A theory of electrons and protons,” Proc. Roy. Soc. Lond. A, vol. 126, no. 801, pp. 360–365, Jan. 1930. doi: 10.1098/rspa.1930.0013
    [66]
    R. P. Feynman, “Nobel Lecture: The Development of the Space-Time View of Quantum Electrodynamics,” 1965. [Online]. Available: https://www.nobelprize.org/prizes/physics/1965/feynman/lecture/
    [67]
    W. R. Zhang, “Six conjectures in quantum physics and computational neuroscience,” in Proc. 3rd Int. Conf. Quantum, Nano and Micro Technologies, Cancun, Mexico, 2009, pp. 67–72.
    [68]
    American Psychiatric Association, Diagnostic and Statistical Manual of Mental Disorders. 5th ed. Arlington, VA: American Psychiatric Publishing, 2013.
    [69]
    World Health Organization, The ICD-10 Classification of Mental and Behavioural Disorders. Geneva, Switzerland: World Health Organization, 1992.
    [70]
    W. R. Zhang, “YinYang bipolar lattices and L-sets for bipolar knowledge fusion, visualization, and decision,” Int. J. Inform. Technol. Decis. Mak., vol. 4, no. 4, pp. 621–645, Dec. 2005. doi: 10.1142/S0219622005001763
    [71]
    W. R. Zhang, “YinYang bipolar fuzzy sets and fuzzy equilibrium relations: For clustering, optimization, and global regulation,” Int. J. Inform. Technol. Decis. Mak., vol. 5, no. 1, pp. 19–46, Mar. 2006. doi: 10.1142/S0219622006001885
    [72]
    B. Kosko, “Fuzzy cognitive maps,” Int. J. Man-Mach. Stud., vol. 24, no. 1, pp. 65–75, Jan. 1986. doi: 10.1016/S0020-7373(86)80040-2
    [73]
    W. R. Zhang, S. S. Chen, and J. C. Bezdek, “Pool2: A generic system for cognitive map development and decision analysis,” IEEE Trans. Syst. Man Cybern., vol. 19, no. 1, pp. 31–39, Jan.–Feb. 1989. doi: 10.1109/21.24529
    [74]
    W. R. Zhang, S. S. Chen, W. Wang, and R. S. King, “A cognitive-map-based approach to the coordination of distributed cooperative agents,” IEEE Trans. Syst. Man Cybern., vol. 22, no. 1, pp. 103–114, Jan.–Feb. 1992. doi: 10.1109/21.141315
    [75]
    W. R. Zhang, “NPN fuzzy sets and NPN qualitative algebra: A computational framework for bipolar cognitive modeling and multiagent decision analysis,” IEEE Trans. Syst. Man Cybern. Part B:Cybern., vol. 26, no. 4, pp. 561–575, Aug. 1996. doi: 10.1109/3477.517031
    [76]
    W. R. Zhang, “Information conservational YinYang Bipolar quantum-fuzzy cognitive maps - mapping business data to business intelligence,” in Proc. IEEE Int. Conf. Fuzzy Systems, Vancouver, BC, Canada, 2016, pp. 2279–2286.
    [77]
    E. R. Kandel, J. H. Schwartz, T. M. Jessell, S. A. Siegelbaum, and A. J. Hudspeth, Principles of Neural Science, 5th ed. New York: McGraw-Hill Medical, 2013.
    [78]
    S. Lloyd, Programming the Universe: A Quantum Computer Scientist Takes on the Cosmos. New York: A Division of Random House, Inc., 2007.
    [79]
    W. R. Zhang, “On the nature of natural intelligence–A revision of Laozi,” in Proc. IEEE 17th Int. Conf. Cognitive Informatics & Cognitive Computing, Berkeley, CA, USA, 2018, pp. 316–323.
    [80]
    M. N. Huhns and M. P. Singh, Readings in Agents. San Francisco, California: Morgan Kaufmann, 1998.
    [81]
    W. R. Zhang, “Nesting, safety, layering, and autonomy: A reorganizable multiagent cerebellar architecture for intelligent control with application in Legged locomotion and gymnastics,” IEEE Trans. Syst. Man Cybern. Part B:Cybern., vol. 28, no. 3, pp. 357–375, Jan. 1998.
    [82]
    X. Luo, M. C. Zhou, Y. N. Xia, Q. S. Zhu, A. C. Ammari, and A. Alabdulwahab, “Generating highly accurate predictions for missing QoS data via aggregating nonnegative latent factor models,” IEEE Trans. Neural Netw. Learn. Syst., vol. 27, no. 3, pp. 524–537, Mar. 2016.
    [83]
    D. Wu, Q. He, X. Luo, M. S. Shang, Y. He, and G. Y. Wang, “A posterior-neighborhood-regularized latent factor model for highly accurate web service QoS prediction,” IEEE Trans. Serv. Comput., 2019. DOI: 10.1109/TSC.2019.2961895
    [84]
    L. A. Zadeh, “Is there a need for fuzzy logic?” Inform. Sci., vol. 178, no. 13, pp. 2751–2779, Jul. 2008. doi: 10.1016/j.ins.2008.02.012
    [85]
    L. A. Zadeh, “Causality is undefinable–Toward a theory of hierarchical definability,” in Proc. 10th IEEE Int. Conf. Fuzzy Systems, Melbourne, Victoria, Australia, 2001, 67–68
    [86]
    D. Hilbert, “Mathematical problems,” Bull. Amer. Math. Soc., vol. 8, pp. 437–479, 1902. doi: 10.1090/S0002-9904-1902-00923-3
    [87]
    G. W. Leibniz, “Explication de 1’arithmétique binaire,” Memoires de l’Academie Royale, 1703: 85–89, 1703.
    [88]
    A. Einstein, Letter to Max Born (1926), published in 1971, Irene Born (translator), The Born-Einstein Letters, Walker and Company, New York.
    • Related Articles
    • Supplements(0)

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(16)

    Get Citation
    PDF
    XML

    Article Metrics

    Article views (3188) PDF downloads(118) Cited by()

    Highlights

    • First principles of science and second law of thermodynamics are set-theoretically unified.
    • A misinterpretation by the founding fathers of quantum mechanics is identified and corrected.
    • The geometry of light and the logic of photon are identified for mind-light-matter unity AI&QI.

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return