Showing posts with label Quantum Chemistry. Show all posts
Showing posts with label Quantum Chemistry. Show all posts

Quantum Computing - Areas Of Application.

 




Quantum simulation, quantum linear algebra for AI and machine learning, quantum optimization and search, and quantum factorization are the four most well-known application cases. 


I go through them in detail in this paper, as well as issues leaders should think about when evaluating prospective use cases. 

I concentrate on prospective applications in a few areas that, according to studies, might profit the most in the near term from the technology: medicines, chemicals, automotive, and finance. 

The total value at risk for these sectors might be between $300 billion and $700 billion (to be cautious). 




Chemicals


Chemicals may benefit from quantum computing for R&D, manufacturing, and supply-chain optimization. 


  • Consider how quantum computing may be utilized to enhance catalyst designs in the manufacturing process. 
  • New and improved catalysts, for example, could allow existing production processes to save energy—a single catalyst can increase efficiency by up to 15%—and innovative catalysts could allow for the replacement of petrochemicals with more sustainable feedstocks or the breakdown of carbon for CO2 usage. 

A realistic 5 to 10% efficiency boost in the chemicals sector, which spends $800 billion on production each year (half of which depends on catalysis), would result in a $20 billion to $40 billion gain in value. 





Pharmaceuticals


Quantum computing has the potential to improve the biopharmaceutical industry's research and development of molecular structures, as well as providing value in manufacturing and farther down the value chain. 


  • New medications, for example, cost an average of $2 billion and take more than 10 years to reach the market once they are discovered in R&D. 
  • Quantum computing has the potential to make R&D more quicker, more focused, and accurate by reducing the reliance on trial and error in target identification, drug design, and toxicity assessment. 
  • A shorter R&D timetable might help deliver medications to the correct patients sooner and more efficiently—in other words, it would enhance the quality of life of more people. 
  • Quantum computing might also improve production, logistics, and the supply chain. 


While it's difficult to predict how much revenue or patient impact such advancements will have, in a $1.5 trillion industry with average EBIT margins of 16 percent (by our calculations), even a 1 to 5% revenue increase would result in $15 billion to $75 billion in additional revenue and $2 billion to $12 billion in EBIT. 




Finance


Quantum-computing applications in banking remain a ways off, and the benefits of any short-term applications are speculative. 


  • However, I feel that portfolio and risk management are the most potential applications of quantum computing in finance. 
  • Quantum-optimized loan portfolios that concentrate on collateral, for example, might let lenders to enhance their services by decreasing interest rates and freeing up money. 


Although it is too early—and complicated—to evaluate the value potential of quantum computing–enhanced collateral management, the worldwide loan industry is estimated to be $6.9 trillion in 2021, implying that quantum optimization might have a substantial influence.



Automobiles


Quantum computing can help the automotive sector with R&D, product design, supply-chain management, manufacturing, mobility, and traffic management. 


  • By improving features such as route planning in complicated multirobot processes (the path a robot travels to perform a job), such as welding, gluing, and painting, the technology might, for example, reduce manufacturing process–related costs and cut cycle times. 


Even a 2% to 5% increase in efficiency might provide $10 billion to $25 billion in annual value in an industry that spends $500 billion on manufacturing expenditures. 



~ Jai Krishna Ponnappan


You may also want to read more about Quantum Computing here.





Quantum Chemistry and Quantum Biology

 


Quantum Chemistry - With quantum theory scientists also recognized a whole new connection between physics and chemistry. 


How atoms combine to form molecules and other compounds is determined by the quantum properties of the electron shells in those atoms. 

That implies that chemistry is nothing more than applied quantum physics. 

Only with knowledge of quantum physics can the structures of chemical bonds be understood. Some readers may recall the cloud-like structures that form around the atomic nucleus. 

These clouds, which are called orbitals, are nothing but approximate solutions of the fundamental equation of quantum mechanics, the Schrödinger equation. 

They determine the probabilities of finding the electrons at different positions (but note that these solutions only consider the interactions between the electrons and the atomic nucleus, not those between the electrons). 


“Quantum chemistry” consists in calculating the electronic structures of molecules using the theoretical and mathematical methods of quantum physics and thereby analyzing properties such as their reactive behavior, the nature and strength of their chemical bonds, and resonances or hybridizations. 


The ever increasing power of computers makes it possible to determine chemical processes and compounds more and more precisely, and this has gained great significance not only in the chemical industry and in materials research, but also in disciplines such as drug development and agro-chemistry. 


Quantum Biology - Last but not least, quantum physics helps us to better understand the biochemistry of life. 


A few years ago bio-scientists started talking about “quantum biology”. For example, the details of photosynthesis in plants can only be understood by explicitly considering quantum effects. 

And among other things, the genetic code is not completely stable, as protons in DNA are vulnerable to the tunnel effect, and it is this effect that is partly responsible for the emergence of spontaneous mutations. 

Yet as always, when something is labelled with the word “quantum”, there is some fuzziness in the package. 

Theoretically, the structures of atoms and molecules and the dynamics of chemical reactions can be determined by solving the Schrödinger equation (or other quantum equations) for all atomic nuclei and electrons involved in a reaction. 

However, these calculations are so complicated that, using the means available today, an exact solution is possible only for the special case of hydrogen, i.e., for a system with a single proton and a single electron. In more complex systems, i.e., in practically all real applications in chemistry, the Schrödinger equation can only be solved using approximations. 

And this requires the most powerful computers available today. 

Theoretically, the equations of quantum theory can be used to calculate any process in the world. 

However, even for simple molecules the calculations are so complex that they require the fastest computers available today, and physicists must nevertheless satisfy themselves with only approximate results. 


You may also want to read more about Quantum Computing here.




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