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What are the most promising applications of quantum computing today, and how can we expect them to impact fields like medicine, finance, and logistics in the near future?
Quantum computing promises to revolutionize many sectors, but understanding where its impact will first become tangible remains an open question. For those working in or studying quantum computing:
What practical applications do you see quantum computing enabling within the next 5-10 years?
How do current quantum algorithms like quantum annealing or variational algorithms help solve real-world problems in areas like drug discovery, portfolio optimization, or supply chain management?
Are there specific fields or problems where quantum computing might make an impact sooner than others, and what are the hurdles in achieving these outcomes?
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Posted by danita •
One example of practical application:
**By considering multiple routes simultaneously, quantum computers can identify more efficient paths, minimizing delivery times and fuel consumption. Imagine the competitive advantage that a delivery company could enjoy if quantum optimization reduced its fuel costs by 10% to 20%
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Posted by danita •
I think I found a good paper published by Cornell U. on the subject. If this is of interest to you, this is the reference: https://arxiv.org/abs/2312.02279
Challenges and Opportunities in Quantum Optimization
Recent advances in quantum computers are demonstrating the ability to solve problems at a scale beyond brute force classical simulation. As such, a widespread interest in quantum algorithms has developed in many areas, with optimization being one of the most pronounced domains. Across computer science and physics, there are a number of different approaches for major classes of optimization problems, such as combinatorial optimization, convex optimization, non-convex optimization, and stochastic extensions. This work draws on multiple approaches to study quantum optimization. Provably exact versus heuristic settings are first explained using computational complexity theory - highlighting where quantum advantage is possible in each context. Then, the core building blocks for quantum optimization algorithms are outlined to subsequently define prominent problem classes and identify key open questions that, if answered, will advance the field. The effects of scaling relevant problems on noisy quantum devices are also outlined in detail, alongside meaningful benchmarking problems. We underscore the importance of benchmarking by proposing clear metrics to conduct appropriate comparisons with classical optimization techniques. Lastly, we highlight two domains - finance and sustainability - as rich sources of optimization problems that could be used to benchmark, and eventually validate, the potential real-world impact of quantum optimization.
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Posted by RMTboy •
would you have any reference to a scientific paper showing these numbers ?
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Posted by danita •
The reference is: "How quantum computing will transform logistics" by Yuval Boger in www.forbes.com
Hope this will help you. Have a great day.
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Posted by danita •
In algo trading, quantum computers can support more efficient and precise algorithms for trading on financial markets.
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Posted by RMTboy •
do you know in the world who is working particularly on that ? do you have any paper I could read ?
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Posted by danita •
These are the references I found that may help you. They appear in a literature review by Mohammed Fourmou and the article's name is "Practical algorithmic high-frequency trading" (however, they don't seem to acknowledge the use of quantum computers): to me algo trading is already so highly sophisticated that I wonder how quantum computers can improve it!)
References
Carasik, Bob, "IT Infrastructure for High-Frequency Trading" (2013). WHICEB 2013 Proceedings. 13.
Shigeki Kohda. Kenichi Yoshida. Characteristics and Forecast of High-frequency Trading
Christian Leber, Benjamin Geib, Heiner Litz. (2011) High Frequency Trading Acceleration using FPGAs
Andrew Boutros, Brett Grady, Mustafa Abbas and Paul Chow. High Frequency Trading Acceleration using FPGAs
Michael Aitken, Douglas Cumming, Feng Zhan. Trade Size, High Frequency Trading, and Co-Location Around the
World* European Journal of Finance, forthcoming
Wendy L. Currie, Jonathan J. M. Seddon. The regulatory, technology and market ‘dark arts trilogy’ of high frequency
trading: a research agenda. Journal of Information Technology (2016)
Michael A. Goldstein, Pavitra Kumar, Frank C. Graves. Computerized and High-Frequency Trading. The Financial
Review 49 (2014) 177–202
Ajay Acharya. Dr. Nandini. S. Sidnal. High Frequency Trading with Complex Event Processing. 2016 IEEE 23rd
International Conference on High Performance Computing Workshops
Boming Huang, Yuxiang Huan, Li Da Xu, Lirong Zheng & Zhuo Zou. Automated trading systems statistical and
machine learning methods and hardware implementation: a survey. (2019) Automated trading systems statistical and
machine learning methods and hardware implementation: a survey, Enterprise Information Systems, 13:1, 132-144,
DOI: 10.1080/17517575.2018.1493145
Mohammad Sadoghi, Martin Labrecque, Harsh Singh, Warren Shum, Hans-Arno Jacobsen University of Toronto.
Efficient Event Processing through Reconfigurable Hardware for Algorithmic Trading.
Joel Hasbrouck and Gideon Saar. (2005). Technology and Liquidity Provision: The Blurring of Traditional Definitions.
Gregory Laughlin Anthony Aguirre and Joseph Grundfest. Information Transmission Between Financial Markets in
Chicago and New York.
James J. Angel. When Finance Meets Physics: The Impact of the Speed of Light on Financial Markets and their
Regulation. The Financial Review, Forthcoming, May 2014
ALEX FRINO, VITO MOLLICA* and ROBERT I. WEBB. THE IMPACT OF CO‐LOCATION OF SECURITIES
EXCHANGES’ AND TRADERS’ COMPUTER SERVERS ON MARKET LIQUIDITY
C.T. Brownlees , G.M. Gallo. Financial econometric analysis at ultra-high frequency: Data handling concerns.∗
Computational Statistics & Data Analysis 51 (2006) 2232 – 2245.
Andrei Kirilenko; Richard B. Sowers; Xiangqian Meng. A multiscale model of high-frequency trading. Algorithmic
Finance (2013), 2:1, 59-98 DOI: 10.3233/AF-13017
Jiahao Chen , Xiaofei Li. Analysis of frequent trading effects of various machine learning models. School of
Information and Mathematics, Yangtze University, Jingzhou 434023, Hubei, China.
Kiyoshi Kanazawa, Takumi Sueshige, Hideki Takayasu, and Misako Takayasu. (2018). Derivation of the Boltzmann
Equation for Financial Brownian Motion: Direct Observation of the Collective Motion of High-Frequency Traders.
DOI: 10.1103/PhysRevLett.120.138301
Babak Mahdavi-Damghani. Introducing the HFTE Model: A Multi-Species Predator–Prey Ecosystem for High-
Frequency Quantitative Financial Strategies. EQRC & Oxford-Man Institute of Quantitative Finance.
Pietro FODRA. Huyên PHAM. (2013). High frequency trading in a Markov renewal model
Álvaro Cartea† and Sebastian Jaimungal‡. (2013). Modeling Asset Prices for Algorithmic and High Frequency
Trading Forthcoming in Applied Mathematical Finance.∗
Statistical Modeling of High-Frequency Financial Data: Facts, Models, and Challenges. IEEE SIGNAL PROCESSING
MAGAZINE (2011).
Luc Bauwens and Nikolaus Hautsch. Modelling Financial High Frequency Data Using Point Processes.
YOSIHIKO OGATA. (1978). THE ASYMPTOTIC BEHAVIOUR OF MAXIMUM LIKELIHOOD ESTIMATORS
FOR STATIONARY POINT PROCESSES. Ann. Inst. Statist. Math.
ROBERT F. ENGLE AND JEFFREY R. RUSSELL. (2014). Autoregressive Conditional Duration: A New Model for
Irregularly Spaced Transaction Data. http://www.jstor.org/stable/2999632
Clive G. Bowsher. (2012). Modelling Security Market Events in Continuous Time: Intensity Based, Multivariate Point
Process Models.
V. Chavez-Demoulin, J.A. McGill. (2012). High-frequency financial data modeling using Hawkes processes. Faculty of
Business and Economics, University of Lausanne, Switzerland.
Emmanuel Bacry. Jean-François Muzy. (2013). Hawkes model for price and trades high-frequency.
Mandes, Alexandru. Algorithmic and high-frequency trading strategies: A literature review. MAGKS Joint Discussion
Paper Series in Economics, No. 25-2016
PETTER N. KOLM & LEE MACLIN. Algorithmic Trading. Encyclopedia of Quantitative Finance (EQF).
Joel Hasbrouck, Gideon Saar. (2013) Low-latency trading. Journal of Financial Markets 16 (2013) 646–679.
Yacine Aı̈ l t-Sahalia. Mehmet Sağlam. (2021). High Frequency Market Making: The Role of Speed.
S. V. S. P. P. Jaya Sankar Krishna a, Akankhya Panda b, Pappu Sindhuja. (2023). Algorithmic Strategies in High
Frequency Trading: A Comprehensive Review. DOI: https://doi.org/10.55248/gengpi.4.1123.113132
Brandon Beckhardt, David Frankl , Charles Lu, and Michael Wang. (2016). A Survey of High-Frequency Trading
Strategies
Steve Yang, Mark Paddrik, Roy Hayes, Andrew Todd, Andrei Kirilenko, Peter Beling, and William Scherer. Behavior
Based Learning in Identifying High Frequency Trading Strategies.
Marcos M. López de Prado, Ph.D.. (2011). Advances in High Frequency Strategies. Library of Congress Control
Number: 2011904210
David Easley. Marcos M. López de Prado. Maureen O’Hara. (2012). THE VOLUME CLOCK: INSIGHTS INTO THE
HIGH FREQUENCY PARADIGM
High frequency trading strategies. (2021). https://ssrn.com/abstract=2973019
ÁLVARO CARTEA. SEBASTIAN J AIMUNGAL. RISK METRICS AND FINE TUNING OF HIGH-FREQUENCY
TRADING STRATEGIES. Mathematical Finance, Vol. 00, No. 0 (xxx 2013), 1–36
Marco Avellaneda & Sasha Stoikov. (2006). High-frequency trading in a limit order book
Joel Hasbrouck. (2016). High Frequency Quoting: Short-Term Volatility in Bids and Offe
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Posted by danita •
quantum algorithms can improve and streamline medical imaging, allowing for early-stage diagnosis of conditions. Quantum techniques can process genomic datasets much faster, facilitating personalized medicine.
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Posted by danita •
Sorry, I have not been very inventive, these answers are on the internet.