101 quantum chemistry, how to start

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Among the potential uses of optic hardware and quantum computing, there is chemical simulation. Being exponentially faster than their classical counterparts, quantum computing gives hope about drug development and other chemical processes. This article is not for experienced quantum researchers. It is an introduction to motivate boys and girls to this field. To avoid information overload, circuit design is not covered here. If you are interested in this click the reference link at the bottom.

Let’s start: the starting point to quantum chemistry and drug development is the variational quantum eigensolver (VQE). In practice, VQE is a hybrid algorithm (partially…


Useful things beyond the two hypes

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A recent controversial paper tried to define a new formalism for deep learning in terms of quantum fields. Indeed, qubits are described naively as a state between zero and one, and each node of a neural network, similarly is a value between zero and one meaning probability or something alike. It is intuitive to imagine an overlap. Both topics have been overly boosted by (unmotivated?) hype, though they are both useful technologies. Beyond the hype(s), there might be some opportunities combining the two approaches.

Indeed, the idea is not new, and several authors have already tried to reframe existing machine…


More Machine learning and less chunky hardware

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We all have seen this year the video on YouTube with Elon Musk the alive pig the brain implant connected to a computer. One of the speculations was that “it will create super-cognition” (whatever that means). Despite being more on the side of science-fiction and borderline with ethical approvals, everybody was talking about it.

In all this hype (more due to the figure of Elon Musk than real science), most of the people neglected two things: The annual Brain Computer Interface Award where scientists compete with their latest advancements in this topic, and the many startups which are actually creating…


Current state-of-art tools putting together quantum physics and artificial intelligence

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Data science and machine learning are definitely among the buzz words nowadays. At startup competitions and conferences I have seen too much. AI-trained beer draft to give you the perfect taste, plastic bag with sensor training IoT systems based on machine learning on how much people swing them, toilets with machine learning based system to optimize lights usage. Seriously? Is this innovation?

Either people just put this technology anywhere to sound cool, or machine learning is the “new electricity” and therefore there is nothing cool anymore about it.

About 10–15…


why some countries are still behind

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If you work or are interested in science, probably have seen the meme below. The article was written in 1992 and I can imagine that this issue has only worsened over time. A screenshot of one of the major publishers of scientific articles talking about inaccessibility which is inaccessible itself! For the people not in the field, science works like this:

  1. You do some research, you find results and submit for revision to journals.
  2. When the paper is accepted and it is going to be published, you have to pay a fee (ranging from…


Moving from buzzwords innovation to need centered innovation

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It is clear that our society has become innovation seeker. However, generally we see incremental innovation. Namely, <<buzzword>> (e.g. machine learning, quantum computing, blockchain…) used in a specific domain… bam! It is true that we are living a renaissance in many fields, and often is given by hard work but sometimes it feels just like milking the winning cow.

Biodesign innovation is driven by specific needs. Medical technology innovators in both business and academia often follow a “technology push” strategy: a technology or approach is discovered, and it is the new “hammer” used to all nails. They (but also we)…


Harnessing the power of machine learning with Open Source tools for drug discovery

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Proteins, made up of chains of amino acids, are the building blocks of life, drug discovery tasks generally include predicting protein folding, docking, and interactions. This has several applications from vaccines to other kinds of drugs especially for neurodegenerative diseases, and material science. As in other fields, biotech, biology, and medicine have been positively affected by the advancements in machine learning and quantum computing. The main advantages of in-silico drug design are related to the infinite variations which can be simulated and tried compared to tenfold costs and time in trial-and-error tests in the real world. …


Thoughts and Theory

How quantum computing is holding the promise to develop drugs for neurodegenerative diseases and more

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Computational methods for drug design have been investigated for many years. One critical aspect of drug design is to infer or predict the folding of proteins, which will lead to identifying how proteins interact with each other. For instance, most neurodegenerative diseases are based on misfolded proteins which spread through the brain, designing the complementary proteins which will block them holds the promise to treatments.


even if you are not physicist

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“Nature isn’t classical, dammit, and if you want to make a simulation of nature, you’d better make it quantum mechanical. “

Richard Feynman

Quantum computing will be the future in computing at least in some fields as chemistry simulation and options prediction. Everybody should be able to access it, independently from the geographical location, gender, educational level, etc.

Geography inclusion: Quantum computers are not cheap at the moment (we talk about 15 millions USD investments) without mentioning the knowledge to set it up, but you can start using a quantum computer through cloud platforms…

Dr. Alessandro Crimi

Researcher, Lecturer, and founder of www.yawlab.io Interested in biotech, medicine, cooperation, education and entrepreneurship, also in low-income countries.

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