Quantum Computing – Exploring the Next Potential Paradigm Shift in High Performance Computing
Quantum computing is a new computational technology at the intersection of quantum physics and computer science [1]. A Quantum Computer (QC) is a device that makes direct use of quantummechanical phenomena of superposition and entanglement to perform operations on data, which is encoded in qubits. A qubit [2] is any welldefined, twolevel quantumsystem which constitutes the basic computation unit of a QC.
Quantumcomputing is interesting because of its potential to provide at least a polynomial speedup over classical computing for many classes of practical problems, and an exponential speedup for particular problems such as integer factorization [3]. Massive parallelism is fundamentally embedded in QC through the underlying quantum mechanical principles.
Why Now?
Developments in Quantum mechanics, a field of modern physics that predates 1900, enabled the development of the first transistor in 1947 at Bell Labs by Bardeen, Brattain and Shockley [4]. This led to the development of the first integrated circuit in 1958 [5], followed by tremendous progress in computer technology followed with the number of transistors doubling roughly every 1.5 years.
This phenomenon, captured popularly as Moore’s law has lasted well into this decade with the attendant increase in computational power of classical computing technology. Technical and attendant economic challenges limit further advancements, as physical dimensions of transistors approach 5 nanometers around the year 2021, leading to the disbandment of the International Technology Roadmap for Semiconductors [6,7] in 2016 [8].
In this historical backdrop, Quantum computers have been advancing in their computational capability expressed in the number of qubits. In a remarkable parallel to Moore’s law, the number of qubits in a QC has been doubling roughly every 1.5 years.
The Technology
The technology is still in an early stage of development. The current focus is on basic research, quantumcomputing hardware, and quantumcomputing algorithms. The first quantum computers (quantum annealing computers and gatebased quantum machines) are currently being tested in laboratories and large corporations. Unsurprisingly, the interest of investors and the big corporate players in this topic has grown significantly in recent years due to the rapid progress in this field.
Challenges
Several major technical and conceptual challenges need to be overcome to realize a practical, generalpurpose QC. Increasing the number of basic quantumcomputational units (called qubits), while keeping or extending their coherencetime (useful time) and their interconnectivity, poses a substantial challenge at this time, with no clear lines of attack.
Experts currently guesstimate that it will take more than 10 years for a generalpurpose Quantum Computer to become available (beyond 2025).
Quantum Computing at SAP
SAP’s enterprise software solutions require highperformance database operations and efficient solution of complex, exponential timecomplexity [9] combinatorial optimization problems [10], both of which can potentially be accelerated by Quantum Computing. While we expect classical (inmemory) architectures to remain the major computational paradigm in the next decade, Quantum Computing may have a direct impact on SAP’s future due to its potential as noted above.
In the meantime, specialpurpose Quantum Computers may be able to solve specific computational problems faster than the best classical computers. SAP, therefore, continues to explore this potential to determine if we can leverage the technology to create significant value for our customers before the first generalpurpose QuantumComputer is realized.
SAP’s approach to Quantum Computing
Our approach is to work with the leading experts and quantum technology players in academia and industry on developments in this field. We are assessing the timescale and the applicationdomains of these developments and how they might impact the future of SAP and our customers. We are evaluating Qubit scaling, QC SW and HW Architecture, QC algorithms, QC SDKs, and timetoexpected quantumequivalence for problems of interest to SAP to establish their technical feasibility and timescale for SAP.
To create a holistic point of view, we are already collaborating with different entities and teams across SAP on various topics (combinatorialoptimization, quantumkey distribution for quantumsecure communication, etc.) and will continue to educate our internal teams to prepare SAP for this possible computational paradigm shift.
References

Quantum Computing, https://en.wikipedia.org/wiki/Quantum_computing

Qubit, https://en.wikipedia.org/wiki/Qubit

Shor’s Algorithm, https://en.wikipedia.org/wiki/Shor%27s_algorithm

Transistor, https://en.wikipedia.org/wiki/Transistor

Integrated Circuit, https://en.wikipedia.org/wiki/Integrated_circuit

“Transistors Won’t Shrink Beyond 2021, Says Final ITRS Report,” July 28, 2016, https://www.hpcwire.com/2016/07/28/transistorswontshrinkbeyond2021saysfinalitrsreport/

International Technology Roadmap for Semiconductors, https://www.semiconductors.org/main/international_technology_roadmap_for_semiconductors_itrs_archives/

International Technology Roadmap for Semiconductors, https://en.wikipedia.org/wiki/International_Technology_Roadmap_for_Semiconductors

Time Complexity, https://en.wikipedia.org/wiki/Time_complexity

Combinatorial Optimization, https://en.wikipedia.org/wiki/Combinatorial_optimization
Good day, Former Member
Interesting, I proposed it in Oct.2016:
Dynamic Antidote
https://www.itcentralstation.com/users/ricardodolinskigarrido/projects/12508
What is it?
Dynamic antidote online for each threat against cybercrime attacks
How it Works
Applying cognitive compute located in clouds computing in quantum computers would be possible to track online patterns of threat, apply dynamic obfuscation cognitive in real time of the recurrent threats in its pattern identified, isolate source of threat and isolate its corresponding action; then it would be possible develop dynamic antidote online for each threat pattern.
A proposed flow in the process of Dynamic Antidote would be to:
1.a. Identify threat patterns happening with IBM Watson.
1.b. Hand it off to IBM Business Process Manager (BPM).
1.c. Notify System Administrators and the System itself in real time with IBM Business Process Manager (BPM) & Business Operations Connect when threat patterns are discovered / identified.
2.a. Identify initiate actions using IBM Business Process Manager (BPM) & IBM Watson.
2.b. Apply Dynamic Obfuscation Cognitive in real time of the recurrent threats in its pattern identified to isolate source of threat and isolate its corresponding action.
2.c. Initiate more actions (i.e. auto shut down servers, close down internet access, etc.) with IBM Security Access Manager (ISAM) & IBM Watson.
A contribution against cybercrime attacks indicated in The 2016 Internet Organised Crime Threat Assessment (IOCTA)
https://www.europol.europa.eu/content/internetorganisedcrimethreatassessmentiocta2016
ok
Former Member
username: Former Member
S_User: S0018218833
P_User: P1942534595
dni.05338843Z
email: ricardo.dolinski@celeritech.biz