April 3, 2020: Chicago Quantum:
Quick progress update. We are analyzing 240 highly liquid, US equities. We can run them classically through a 100% comprehensive 'brute force' analysis to find the best combination of assets to hold in a portfolio, in sections. We can then run them in different combinations to find even better (or worse) portfolio combinations. This is delivering insights on asset performance, both good and bad.
We are running these on a dedicated server, and our personal computing devices, while we push the envelope on classical methods. Our test is how many assets we can run at one time. N assets creates 2^N-1 portfolios. In other words, 28 assets has 268M unique portfolio options (what we are working on classically now), and 30 assets would be ~ 1 billion unique portfolios.
Just last night we completed a classical run of 28 liquid US equity assets on our HP Z420 workstation, with 48GB RAM, a 1TB disk drive, and a 100GB SSD. That run looked at 268 million unique portfolio combinations in a brute force manner. That means we calculate the Sharpe Ratio for every portfolio combination with standard, equal weights, of those 28 equities, to find the best portfolios for an investor like you or me. This is non-trivial on our server.
In comparison, we can execute N=27 successfully with 100% accuracy and coverage of unique portfolio options, in about an hour or less. N=27 equities is half the work of N=28. We continue to believe that this exponentially growing complexity problem is a good candidate for quantum approaches. BTW, we would like to look at hundreds of stocks at once...which would be a brute force approach of 2^100s of unique portfolios.
We are finding valuable insights in the US equity market data in terms of building higher expected returns with lower standard deviation of returns. In other words, to build a portfolio that we think delivers more profit with less risk.
We have underway a separate effort to write the QUBO to run these as an optimization on a quantum annealing system.
Future steps for our team (meaning maybe next week):
1) Integrate bonds and commodities into our analysis. Does it help generate better portfolios?
2) Look at 'classical, probabilistic' methods to reduce the number of unique portfolios to analyze while still arriving at the best (or almost best) answer. This could include using sampling for seeding a genetic algorithm. This is important if we want to look at all 240 assets in one run because we cannot afford a server that can execute bootstrap analysis on 2^240-1 unique portfolios.
Contact us for more info...and watch for publications / videos where we start to explain our results.
After a 90 minute call last Friday, the team has its work cut out for it. We are building out our classical models for portfolio optimization.
We are starting to work through how to optimize it further, and to port the problem to quantum computers.
Our team of associates is growing. We stand ready to serve clients and help them solve complex computational or IT-centric problems. We also have a strong interest in security and sourcing.
Terrill joins us while maintaining his position and roles at Harrisburg University.
One of those roles is leading their QIS degree program.
In this newsletter, we discuss three topics: 1/ progress on NSF Grant for Portfolio Optimization using quantum computers, 2/ decision to abandon DoE Grant for topic 36.D (quantum transducation hardware), and 3/ marketing and networking activities undertaken, and scheduled for April 2020.
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The team at the DoE has released topics for Phase 1, Release 2, Version 3 SBIR/STTR funding. We are looking into topic 36 (Quantum Information Sciences).
The key topics are around Superconducting Radio Frequency (SRF), the cold components around the quantum computer, and quantum networking.
Altaf.firstname.lastname@example.org is the point of contact for Topic 36.
We have created an overlapping set of social media assets to share knowledge.
Facebook, Twitter, LinkedIn, Reddit, Medium, ResearchGate, and more.
We help clients understand quantum computing and quantum technologies, visualize what is possible in their business, and help them create their quantum advantage through their quantum use case.
We published two articles via Medium:
We published about a dozen YouTube videos:
We also published 2 eBooks (on this site in Use Cases and Platforms).
We earned our first revenue, and the team is working on running certain programs and algorithms. Our team's expertise continues to grow.
Written by Jeffrey Cohen, President, US Advanced Computing Infrastructure, Inc.
While writing a pitch for quantum computing and our firm to a potential partner, looked for related startups to learn from. Quantum computing is not production-ready. Governments, universities and industry are still developing the technology.
A related technology is quantum dots. These are very useful in that they convert light to electricity, and electricity to light in very specific frequencies (read colors). This firm has made some seemingly unrelated, but clever announcements lately about their shift to new markets including blockchain, product tags (e.g., RF tags but cheaper and tamper proof). They have also filed sever SEC documents, so I thought I would take a look.
1) Company overview from early 2019 shows the stress of being a startup (See SEC Filing here). How something like a lawsuit from a previous lender can distract and disturb the ongoing operations. How the promise of a new technology takes time, patience, tenacity and a willingness to play the long-term game.
2) A January 2018 interview with CEO Stephen Squires, found here, gives a solid overview of the company, the technology, and the vision to a non-scientist.
3) The company looks like it is losing about $7M to $8M this year, down from over $9M last year, and is starting to see some revenues (~ $1M) from a manufacturing partnership in India.
Why post this? It is a reminder that a new quantum technology that could have far-reaching impacts in both lighting, consumer displays, and possibly quantum computing takes time to develop and commercialize. It starts with a vision, humble beginnings, tenacity and hard work. It starts with humble beginnings. One firm, focusing on lowering the cost of production and application of quantum dots in LED displays by 50% to 80%, is on a long journey. They figured out that they could spray the dots right on the LED bulbs instead of on a firm that is then integrated into the display. The film is expensive.
Is this a fairly priced stock? Not sure...after a few hours of homework there is much to consider. For example, SEC filings show a delay in releasing their most recent 10Q and 10K. There is that lawsuit the CEO mentioned. Seeking Alpha entry shows about $3M in debt, and near-zero revenue. 52 week range is $.02 to $.06. This is a near zero revenue bet on a future investment.
Nanoco Group PLC is a competitor that we blogged about earlier...how are they doing?
Here is a picture of the 5 year stock price chart for QTMM (thank you Yahoo Finance):
US Advanced Computing Infrastructure Inc., nor Jeffrey Cohen, nor any related persons have a position in QTMM, nor are we receiving compensation for writing this BLOG entry. This is not investment advice.
This is a discussion of a quantum technology startup running a marathon to commercialization success.
Words we tweeted most frequently from July 1 - Sept 4 2019:
Thank you www.wordclouds.com.
Just published. I was Tweeting about something I want to be true, but my colleagues disagreed. So, here is the math and model to scale a quantum computing system.
It shows that today’s quantum computers are 10x more energy efficient than classical supercomputers, ceteris paribus.
당신의 의견에 감사드립니다. 한국 온라인 게임 '플래시 사이트'는 아직 TLS 1.3 보안 프로토콜을 사용합니까? BTW, 나는 Niantic 게임을한다.
Thank you for your comment. Do Korean online gaming 'flash sites' use TLS 1.3 security protocol yet? BTW, I play Niantic games.
Strategic IT Management Consultant with a strong interest in Quantum Computing. Consulting for 29 years and this looks as interesting as cloud computing was in 2010.