Bikas Chakrabarti

Bikas K. Chakrabarti
Born	(1952-12-14) 14 December 1952 (age 72) Calcutta, India
Alma mater	Calcutta University
Known for	Quantum annealing Econophysics Kinetic exchange models of markets
Awards	Shanti Swarup Bhatnagar Award
Scientific career
Fields	Physics, Economics
Institutions	Saha Institute of Nuclear Physics, Kolkata Indian Statistical Institute, Kolkata S. N. Bose National Centre for Basic Sciences, Kolkata

Bikas Kanta Chakrabarti (born 14 December 1952 in Kolkata (erstwhile Calcutta) is an Indian physicist. ^[1] At present he is INSA Scientist (Physics) at the Saha Institute of Nuclear Physics & visiting professor (Economics) at the Indian Statistical Institute, Kolkata, India.

Biography

Chakrabarti received his Ph.D. degree from Calcutta University in 1979. Following post-doctoral work at the University of Oxford and the University of Cologne, he joined the faculty of Saha Institute of Nuclear Physics (SINP) in 1983. He is S. S. Bhatnagar Prize awardee (1997) and former J. C. Bose National Fellow (2011-2020). He is a former director of SINP. At present he is INSA Scientist at SINP (2021-) and also Honorary Visiting Professor of economics (2007-) at the Indian Statistical Institute. Emeritus Professor of SINP and of S.N. Bose National Centre for Basic Sciences. Much of Chakrabarti's research has centered around statistical condensed matter physics (including Quantum annealing; see also Timeline of quantum computing) and applications to social sciences (see e.g., Econophysics).

Honors, awards & recognitions

Awards and fellowships

• Young Scientist Award of Indian National Science Academy, New Delhi (1984) ^[2]
• Shanti Swarup Bhatnagar Award of the Council of Scientific and Industrial Research, India (1997)
• Fellow, Indian Academy of Sciences, Bangalore (1997-)
• Fellow, Indian National Science Academy, New Delhi (2003-)
• Honorary Visiting Professor of Economics, Indian Statistical Institute, Kolkata (2007- )
• Outstanding Referee Award of the American Physical Society (2010)
• J. C. Bose National Fellow, Department of Science and Technology (India) (2011-2020)

Quantum annealing

• "Idea of quantum annealing” ... due to "tunnelling through infinitely high classical barriers separating infinitely many metastable states was indeed put forward even earlier, in [Ray, Charabarti & Chakrabarti, Phys. Rev. B (1989)], ..." (4th para, Introduction), ^[3] write Erio Tosatti et al. in their Topical Review (2006)

• "The phenomenon of quantum tunneling suggests that it can be more efficient to explore the state space quantum mechanically in a quantum annealer [Ray, Chakrabarti & Chakrabarti, Phys. Re. B (1989); ...]" (2nd para, 1st sentence), ^[4] write Sergio Boixo, Daniel Lidar, John M. Martinis, Matthias Troyer, et al. (2014)

• "Quantum annealing [Ray, Chakrabarti & Chakrabarti, Phys. Rev. B (1989); ...; Das & Chakrabarti, Rev. Mod. Phys. (2008)] uses quantum tunneling instead of thermal excitations to escape from local minima ..." [see 2nd para], ^[5] write Matthias Troyer et al.(Open Access; 2015)

• "Quantum annealing ... is a technique inspired by classical simulated annealing [Ray, Chakrabarti & Chakrabarti, Phys. Rev. B (1989)] that aims to take advantage of quantum tunnelling." (1st sentence), ^[6] write Sergio Boixo, Hartmut Neven et al. (Open Access, 2016)

• "Quantum annealing aims at finding low-energy configurations ... by a controlled quantum adiabatic evolution ... to escape local minima through multiple tunneling events [Ray, Charabarti & Chakrabarti, Phys. Rev. B (1989); ...; Das & Chakrabarti, Rev. Mod. Phys. (2008)]" (1st sentence) ... It can "lead to extremely powerful alternative computational devices”(3rd sentence), ^[7] write Riccardo Zecchina (ICTP) et al. (Open Access, 2018)

• "The previous examples have relied on energy barriers in the classical cost that scale with problem size to foil single-spin-update Simulated Annealing. This agrees with the intuition that a Stoquastic Adiabatic Quantum Computation advantage over Simulated Annealing is associated with tall and thin barriers [Ray, Chakrabarti, and Chakrabarti, Phys. Rev. B (1989); Das & Chakrabarti, Rev. Mod. Phys. (2008)]."(p. 015002-37), ^[8] write Daniel Lidar et al. (2018)

• “Earliest work in laying foundation of quantum annealing was done in 1989 [Ray, Chakrabarti & Chakrabarti, Phys. Rev. B], showing that quantum fluctuations can increase the ergodicity in a spin-glass model, by tunneling between 'trapping' minima, separated by narrow potential barriers. ... Das & Chakrabarti [Rev. Mod. Phys. (2008)] gives ... clear picture of fundamental physical properties and mechanism.” (Introduction), ^[9] write Helmut Ritsch et al. (Open Access, 2022)

• “Adiabatic quantum computation [Farhi et al., Science, 2001; Das & Chakrabarti, Rev. Mod. Phys., 2008]” (Abstract) ...“has attracted intense interest [Das & Chakrabarti, Rev. Mod. Phys., 2008; Farhi et al., Science, 2001] owing to its potential speedup over classical algorithms” (Introduction), ^[10] write Frank Wilczek et al. (Open Access, 2023)

• "Quantum annealing and other inspired methods have garnered increasing interest because of their quantum attributes that could offer potential solutions to the challenges inherent in combinatorial optimization problems [Ray, Chakrabarti & Chakrabarti, Phys. Rev. B (1989); ...] ... D-wave systems ... utilize superconducting quantum interferometers [...; Das & Chakrabarti, Rev. Mod. Phys. (2008)] to execute quantum annealing ..." (Introduction, 1st & 2nd para), ^[11] write Yoshihisa Yamamoto (scientist) et al. (Open Access, 2024)

• "Adiabatic algorithms [Das & Chakrabarti, Rev. Mod. Phys. (2008)]: This is a heuristic algorithm based on physical insight which often works well but for which no convergence guarantees exist", write Ignacio Cirac et al., in their perspective review on Second Quantum Revolution: Quantum Computing & Information (Physics in Horizon 2050, Chapter 7.2.1, p. 7-11) ^[12] (Open Access, 2024)

• "Indeed, it has been established that quantum annealing shows convergence to the optimal (ground) state with larger probability than simulated annealing in a variety of cases if the same annealing schedule is used [...; Das & Chakrabarti, Rev. Mod. Phys. (2008)]. The intuition for the enhanced performance is that quantum fluctuations allow for tunneling events through particularly spiky peaks of the energy landscape [Ray, Chakrabarti & Chakrabarti, Phys. Rev. B (1989); Denchev et al., Phys. Rev. X (2016)], which in contrast are not possible when using classical simulated annealing." (Introduction, 2nd para), ^[13] write Subir Sachdev et al. (2025)

• "The idea of quantum annealing traces its origins from the pioneering works in [Kadowaki & Nishimori, Phys. Rev. E (1998); Ray, Chakrabarti & Chakrabarti, Phys. Rev. B (1989)], where quantum fluctuations have been introduced into the simulated annealing process with the aim to converge to the global minimum quicker than classical simulated annealing (see [Das & Chakrabarti, Rev. Mod. Phys. (2008); Albash & Lidar, Rev. Mod. Phys. (2018)] for comprehensive reviews on quantum annealing)." (Introduction, 3rd para), ^[14] , write Sougato Bose (Univ. College London) et al. (Open Access, 2025)

Econophysics

• "Influential" & "Elegant" papers from "Kolkata School" (pp. 1705, 1711) on “Statistical mechanics of money, wealth & income”, ^[15] write Physicist Victor Yakovenko (Univ. Maryland) & Economist J. Barkley Rosser Jr. (2009)

• See Wikipedia entry on Kinetic exchange models of markets for contributions in modelling the income and wealth distributions (hosted 2010)

• “Fathers of Econophysics" (p. 15), ^[16] Thesis by C. Schinckus, Dept. History and Philosophy of Science, Univ. Cambridge (Open Access, 2018)

• "A number of disciplines have wholeheartedly embraced mathematical tools and models from physics ... For example, the physicist Bikas Chakrabarti has applied the kinetic theory of gas to models of markets ... His is not a one-off example; the list ... includes luminaries such as Jan Tinbergen, the first ever recipient of the Nobel Prize in economics.", write (in p. 211) ^[17] Mariza Uzunova Dang et al., in their Oxford IB book on Theory of Knowledge (Access by Google & Wikipedia, 2020)

• "Historic conference in Kolkata (India, 1995)": One of the six major events in the last hundred and twenty years of physics applications "in economics and finance ... [since] appearance of the doctoral dissertation by Louis Bachelier in 1900" (Fig. 2 & caption), ^[18] Econophysics spl. issue editorial by H. Eugene Stanley et al. (Open Access, 2022)

• "Foundational papers” (Abstract & throughout), ^[19] Topical Review on ‘Twenty-five years of Kinetic exchange models of markets’ by M. Greenberg (Economics, UMass Amherst) & H. Oliver Gao (Systems Engineering, Cornell Univ.) (Open Access, 2024)

• Kolkata Game: See Wikipedia entry on Kolkata Paise Restaurant Problem for game theoretic modelling of decentralized social optimizations (hosted 2025).

• “Econophysics: An Introduction [Sinha, Chatterjee, Chakraborti & Chakrabarti, Wiley, 2010]” has been the only suggested Textbook for the Econophysics course, ^{[20] [21]} offered (Teacher: Diego Garlaschelli) for last one & half a decade by the Leiden University physics dept. (where the inaugural-year [1969] economics Nobel Laureate Jan Tinbergen did undergrad and Ph.D. in statistical physics of economy under Paul Ehrenfest). Course offer started in 2012-2013 & is continuing up to the present academic year 2025-2026. (All Prospectuses are available online)

Books

• Quantum Ising Phases and Transitions in Transverse Ising Models, Bikas K. Chakrabarti, Amit Dutta and Parongama Sen, Springer-Verlag, Heidelberg (1996) [2nd Ed., with Sei Suzuki & Jun-ichi Inoue (2013)]
• Statistical Physics of Fracture and Breakdown in Disordered Solids, Bikas K. Chakrabarti and L. Gilles Benguigui, Oxford University Press, Oxford (1997)
• Econophysics: An Introduction, Sitabhra Sinha, Arnab Chatterjee, Anirban Chakraborti and Bikas K. Chakrabarti, Wiley-VCH, Berlin (2011)
• Econophysics of Income & Wealth Distributions, Bikas K. Chakrabarti, Anirban Chakraborti, Satya R. Chakravarty and Arnab Chatterjee, Cambridge University Press, Cambridge (2013)
• Sociophysics: An Introduction, Parongama Sen and Bikas K. Chakrabarti, Oxford University Press, Oxford (2014)
• Quantum Phase Transitions in Transverse Field Spin Models: From Statistical Physics to Quantum Information, Amit Dutta, Gabriel Aeppli, Bikas K. Chakrabarti, Uma Divakaran, Thomas Felix Rosenbaum & Diptiman Sen, Cambridge University Press, Cambridge (2015)
• Quantum Spin Glasses, Annealing and Computation, Shu Tanaka, Ryo Tamura & Bikas K. Chakrabarti, Cambridge University Press, Cambridge (2017)

Reviews

• B. K. Chakrabarti and M. Acharyya, Dynamic Transitions and Hysteresis, Rev. Mod. Phys. 71, 847 (1999)
• A. Das and B. K. Chakrabarti, Quantum Annealing and Analog Quantum Computations, Rev. Mod. Phys. 80, 1061 (2008)
• S. Pradhan, A. Hansen, and B. K. Chakrabarti, Failure Processes in Elastic Fiber Bundles, Rev. Mod. Phys. 82, 499 (2010).
• H. Kawamura, T. Hatano, N. Kato, S. Biswas, and B. K. Chakrabarti, Statistical Physics of Fracture, Friction, and Earthquakes, Rev. Mod. Phys. 84, 839 (2012).
• A. Rajak, S. Suzuki, A. Dutta and B. K. Chakrabarti, Quantum Annealing: An Overview, Phil. Trans. Royal Soc. A, 381, 20210417 (2023).

References

1. "INSA". Insaindia.org. Archived from the original on 4 March 2016. Retrieved 28 September 2013.
2. "Young Scientist Awardees". INSA. Archived from the original on 11 October 2013. Retrieved 28 September 2013.
3. Santoro, Giuseppe E.; Tosatti, Erio (2006). "Optimization using quantum mechanics: quantum annealing through adiabatic evolution". J. Phys. A: Math. Gen. 39 (36): R393. doi:10.1088/0305-4470/39/36/R01.
4. Boixo, Sergio; Rønnow, Troels F.; Isakov, Sergei V.; Wang, Zhihui; Wecker, David; Lidar, Daniel A.; Martinis, John M.; Troyer, Matthias (2014). "Evidence for quantum annealing with more than one hundred qubits". Nat. Phys. 10 (3): 218–224. arXiv: 1304.4595 . Bibcode:2014NatPh..10..218B. doi:10.1038/nphys2900.
5. Heim, Bettina; Rønnow, Troels F.; Isakov, Sergei V.; Troyer, Matthias (2015). "Quantum versus classical annealing of Ising spin glasses". Science. 348 (6231): 215–217. arXiv: 1411.5693 . Bibcode:2015Sci...348..215H. doi:10.1126/science.aaa4170. PMID   25765071.
6. Boixo, Sergio; Smelyanskiy, Vadim N.; Shabani, Alireza; Isakov, Sergei V.; Dykman, Mark; Denchev, Vasil S.; Amin, Mohammad H.; Smirnov, Anatoly Yu; Mohseni, Masoud; Neven, Hartmut (2016). "Computational multiqubit tunnelling in programmable quantum annealers". Nat. Commun. 7 10327. Bibcode:2016NatCo...710327B. doi:10.1038/ncomms10327. PMC   4729842 . PMID   26739797.
7. Baldassi, Carlo; Zecchina, Riccardo (2018). "Efficiency of quantum vs. classical annealing in nonconvex learning problems". Proc. Natl. Acad. Sci. 115 (7): 1457–1462. arXiv: 1706.08470 . Bibcode:2018PNAS..115.1457B. doi: 10.1073/pnas.1711456115 . PMC   5816144 . PMID   29382764.
8. Albash, Tameem; Lidar, Daniel A. (2018). "Adiabatic quantum computation". Rev. Mod. Phys. 90 (1) 015002. arXiv: 1611.04471 . Bibcode:2018RvMP...90a5002A. doi:10.1103/RevModPhys.90.015002.
9. Starchl, Elias; Ritsch, Helmut (2022). "Unraveling the origin of higher success probabilities in quantum annealing versus semi-classical annealing". J. Phys. B: At. Mol. Opt. Phys. 55 (2): 025501. arXiv: 2010.14256 . Bibcode:2022JPhB...55b5501S. doi:10.1088/1361-6455/ac489a.
10. Yin, Xu-Fei; Yao, Xing-Can; Wu, Biao; Fei, Yue-Yang; Mao, Yingqiu; Zhang, Rui; Liu, Li-Zheng; Wang, Zhenduo; Li, Li; Liu, Nai-Le; Wilczek, Frank; Chen, Yu-Ao; Pan, Jian-Wei (2023). "Solving independent set problems with photonic quantum circuits". Proc. Natl. Acad. Sci. 120 (22) e2212323120. Bibcode:2023PNAS..12012323Y. doi: 10.1073/pnas.2212323120 . PMC   10235971 . PMID   37216545.
11. Aonishi, Toru; Nagasawa, Tatsuya; Koizumi, Toshiyuki; Gunathilaka, Mastiyage Don Sudeera Hasaranga; Mimura, Kazushi; Okada, Masato; Kako, Satoshi; Yamamoto, Yoshihisa (2024). "Highly Versatile FPGA-Implemented Cyber Coherent Ising Machine". IEEE Access. 12: 175843. arXiv: 2406.05377 . Bibcode:2024IEEEA..12q5843A. doi:10.1109/ACCESS.2024.3504008.
12. EPS Grand Challenges, IOP Publishing. 2024.
13. Schlömer, Henning; Sachdev, Subir (2025). "Quantum annealing with chaotic driver Hamiltonians". Ann. Phys. 479 170042. arXiv: 2409.20538 . Bibcode:2025AnPhy.47970042S. doi:10.1016/j.aop.2025.170042.
14. "Enhancing energy gap via quantum annealing". Quantum Sci. Tech. 10: 045010. 2025. doi:10.1088/2058-9565/adf2d5.
15. Yakovenko, Victor M.; Rosser, J. Barkley (2009). "Colloquium: Statistical mechanics of money, wealth, and income". Rev. Mod. Phys. 81 (4): 1703. arXiv: 0905.1518 . Bibcode:2009RvMP...81.1703Y. doi:10.1103/RevModPhys.81.1703.
16. Schinckus, Christophe (2018), When Physics Became Undisciplined An Essay on Econophysics, doi:10.17863/CAM.27052
17. Theory of Knowledge, OUP (2020), Oxford University Press, 21 May 2020, ISBN   978-0-19-849773-8
18. Kutner, R.; Schinckus, C.; Stanley, H. E. (2022). "Three Risky Decades: A Time for Econophysics". Entropy. 24 (5): 627. Bibcode:2022Entrp..24..627K. doi: 10.3390/e24050627 . PMC   9141609 . PMID   35626511.
19. Greenberg, Max; Gao, H. Oliver (2024). "Twenty-five years of random asset exchange modeling". Eur. Phys. J. B. 97 (6) 69. arXiv: 2309.12418 . Bibcode:2024EPJB...97...69G. doi:10.1140/epjb/s10051-024-00695-3.
20. Leiden Univ. Econophysics Prospectus (2012-2013)
21. -Leiden Univ. Econophysics Prospectus (2025-2026)

External links

• CUP book Macro-Econophysics by Aoyama et al., Foreword: pp. xxv-xxvi (2017)(Google Access)
• Kolkata stories on: a) Economics (2006) b) Fracture-Earthquake Statphysics (2017) b) Econophysics (2021)(all Open Access)
• Quantum Mind, Consciousness & Quantum Annealing, Kauffman et al. (2023) (Open Access)
• Kolkata Index for inequality in a) CC model, Cui et al., EPL (2023), b) Wright Capitalism model, Borba et al., Physica A (2025), c) Extended CC model, Lin et al., JOS (2025)
• Development of Econophysics from India (2025)
• "Quantum annealing ..., first proposed by Chakrabarti (1981)" ... et al. (1989, 2008) ... solves computation “via quantum evolution towards the ground states”, Li et al., Proc. ACM (2025) (Open Access)