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hellow,I'm Hope, I obsess over quantum computing and I draw. quantum stuff : https://t.me/HilbertSpacee
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the book was also amazing
it's crazy how the author was a software engineer and wrote this magnificent book(his other books are in my list)
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as a girl, education gives you choices. I believe choice is the most important thing to have. your whole life depends on it.
the system isn't made for you, and being incompetent on top of that is a slap to your future self.
(it's really disappointing to have the access generations of women didn't have and not use it to your advantage.)
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current investment in quantum science and technology
(South Africa is the only African country that has investment in this space around 12 million. For comparison USA and China are investing 9.2 and 17.05 billion respectively)
source
https://www.qureca.com/quantum-initiatives-worldwide/
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Ewin Tang (born 2000) is a computer scientist at the University of California, Berkeley. She was named as one of 2019 Science Forbes 30 Under 30 for her work developing classical algorithms which matched the performance of the fastest known quantum algorithms, done as an undergraduate under the supervision of Scott Aaronson.
(she's so inspiring. I wish to read and understand her work someday)
Link
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I was checking to see this years winning projects. unfortunately it has been postponed to august because of the war.
(I actually miss it so much. It was the first time I felt like I belonged in the qc space...maybe next year🤞)
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"if quantum computers start breaking cryptography a few years from now, don’t you dare come to this blog and tell me that I failed to warn you. This post is your warning. Please start switching to quantum-resistant encryption, and urge your company or organization or blockchain or standards body to do the same."Scott Aaronson (also one of the 3 scientists who said no to Epstein) https://scottaaronson.blog/?p=9718
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a little progress on this topic: https://zxscope.vercel.app
built a site to clearly see how circuits in qasm format can be optimized and have their T-count reduced.
what this does:
- take a qasm circuit as input
- show the zx diagram of the circuit, then after applying rewrite rules, produce an equivalent circuit with less T-count
- convert the reduced diagram back into qasm format
it mainly uses the PyZX library for the logic.
(this is important because applying T gates, which are non-clifford gates, is expensive. zx calculus helps find an equivalent circuit without doing matrix operations, which makes it fast.)
#zx
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Barbara Liskov is credited with formalizing and inventing the concept of abstract data types (ADTs) and data abstraction in the early 1970s.
https://youtu.be/T9CGjbPZeaM?si=NOfB2Vhdr8wi1FY3
(tbh I thought data abstraction was one of those concepts that was always there. she's really amazing.)
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The biggest change I made regarding learning is starting with questions preferably (3–10 questions) when learning about a topic.
For example: what is it, why is it important, and how does it work are the most common questions I ask for almost every concept I learn, with more depending on the context.
This has absolutely been a game changer for me because before this, I would just dive into a subject like jumping into a skydive unprepared and sometimes with no parachute (analogy is still work in progress). Anyway, now I have structure, and it feels far less overwhelming.
Also, knowing the questions are limited for the session makes me realize it is going to end, which is nice.
Anyways, I found this especially helpful in a space where learning is not optimized for an exam or structured by an institution.
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There was an event today organized by the company Riverlane. I was a bit late, and I was only able to listen to the second panel discussion, where representatives from Nvidia and HPE Quantum were the guests.
Few things I learned were:
Nvidia
Nvidia's approach is to advance accelerated quantum supercomputing, and they are working on bringing AI models to advance quantum computing while also using AI as part of the process. One example I saw was their recent work in decoders using a convolutional neural network coupled with a global decoder, which performed better (I think). Another example mentioned was using AI to find lower-depth circuits, better syndrome extraction, and for reasoning over different architectures... more.
HPE Quantum:
HPE is advancing quantum computing by integrating it with high-performance computing (HPC) and AI, aiming for a hybrid quantum-classical approach that makes the technology practical for enterprise use cases like simulation and optimization. They are working on full-stack integration with a top-down approach, starting from the application side and then working with different quantum vendors that are suitable for the specific application.
QLDPC code?
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