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February
,
2022
Hannah Sage

Quantum Computing Used to Feel Like Rocket Science, but Not Anymore

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I’m fairly new to quantum computing. When I started working with Classiq not too long ago, I predicted quantum computing was going to feel like rocket science - or maybe more like neurosurgery. But now, I know it shouldn’t feel like either one. Let me tell you why.

Before Classiq, any time I read a word preceded by “quantum,” my cortisol levels slightly rose. There’s something so out-of-this-world about these tiny scales that it’s often hard to wrap my brain around. And quantum technology is evolving every day. It seems like you could place the word in front of any field and it would stick: quantum chemistry, quantum finance, quantum biology, etc. I knew that quantum computing could be an extremely useful tool in these fields, a vehicle for breakthrough discoveries, but it can sometimes feel overwhelming.

To even begin understanding the underlying science of quantum computing, like rocket science, you need a very solid foundation in math and physics. There are complex numbers, differential equations, theorems on theorems, and, of course, the whole Greek alphabet - lowercase and uppercase. On top of the hefty fundamental knowledge, there’s also the systems approach, with each sub-system requiring a certain level of know-how in various domains. To be able to create quantum computing circuits, it felt as if I needed to master every level of the technology stack: from what qubits and quantum gates are, to how they are made, cooled, controlled, and programmed. 

But I soon realized that quantum computing isn’t the only innovative field with great complexity. I doubt many of us truly understand how cell phones are made - how the CPU is built, how the wireless network is accessed, how the touchscreen works, how Android or iOS is built - but that doesn’t prevent us from using its GPS, creating and using apps, or taking advantage of its other functions. We could say that an iPhone, too, feels like rocket science, without the right tools. Do we really need a deep understanding of every layer to derive value?

The same could be said about the web. Do I need to understand internet routing, assembly language, or how TCP/IP work in order to use or create web pages? Probably not. Like the phone, through years of innovative work from all sorts of brilliant minds, abstraction layers were constructed, allowing me to assume that the CPU, or internet routing, “just works.” I’m not saying this to say we shouldn’t question how things work - I think we all should - just that I don’t need to worry too much about how they work to put them to good use.

So what tools are available to make quantum computing user-friendly? To start, IBM offers a free online platform for creating quantum circuits or running a circuit on their 5 qubit quantum computer. This kind of accessibility to the public is vital for more innovation, and the Qiskit resources are very helpful. If you’re designing a hardware chip, there’s IBM’s new tool Qiskit Metal.

While the IBM Quantum Experience is an excellent learning site, I soon realized that designing software by manually connecting gates and qubits would not work for larger machines. Without the equivalent abstraction layers for quantum, we might require thousands of years to finish a system as complex as a rocket. To fully take advantage of quantum computing, users need platforms like Classiq, which offers a more abstracted design space, allowing us to take part in quantum algorithm design, regardless of how deep our knowledge of the underlying layers is.

From the transition of quantum computing to a higher, functional model, I can spend less time worrying about the underlying mechanics and more time creating new solutions - the creativity in design begins. Groundbreaking discoveries happen when people create independently, compare each other’s work, and constructively criticize one another. Algorithms, like most things, are not one-size-fits-all; with different needs, come different methods. Allowing people to design in an abstract space is necessary for new and exciting quantum algorithms.

With the advancements in quantum hardware and software, the possibilities seem endless, from modeling climate change to advanced flight orbits. Quantum computing can feel like rocket science, but with the right tools, our grandchildren could be designing million qubit circuits by the same age we were learning how to use a calculator.

After some time here with Classiq, it no longer feels like rocket science. It feels like I’m on the rocket, traveling into an exciting future with my colleagues and our customers.

I’m fairly new to quantum computing. When I started working with Classiq not too long ago, I predicted quantum computing was going to feel like rocket science - or maybe more like neurosurgery. But now, I know it shouldn’t feel like either one. Let me tell you why.

Before Classiq, any time I read a word preceded by “quantum,” my cortisol levels slightly rose. There’s something so out-of-this-world about these tiny scales that it’s often hard to wrap my brain around. And quantum technology is evolving every day. It seems like you could place the word in front of any field and it would stick: quantum chemistry, quantum finance, quantum biology, etc. I knew that quantum computing could be an extremely useful tool in these fields, a vehicle for breakthrough discoveries, but it can sometimes feel overwhelming.

To even begin understanding the underlying science of quantum computing, like rocket science, you need a very solid foundation in math and physics. There are complex numbers, differential equations, theorems on theorems, and, of course, the whole Greek alphabet - lowercase and uppercase. On top of the hefty fundamental knowledge, there’s also the systems approach, with each sub-system requiring a certain level of know-how in various domains. To be able to create quantum computing circuits, it felt as if I needed to master every level of the technology stack: from what qubits and quantum gates are, to how they are made, cooled, controlled, and programmed. 

But I soon realized that quantum computing isn’t the only innovative field with great complexity. I doubt many of us truly understand how cell phones are made - how the CPU is built, how the wireless network is accessed, how the touchscreen works, how Android or iOS is built - but that doesn’t prevent us from using its GPS, creating and using apps, or taking advantage of its other functions. We could say that an iPhone, too, feels like rocket science, without the right tools. Do we really need a deep understanding of every layer to derive value?

The same could be said about the web. Do I need to understand internet routing, assembly language, or how TCP/IP work in order to use or create web pages? Probably not. Like the phone, through years of innovative work from all sorts of brilliant minds, abstraction layers were constructed, allowing me to assume that the CPU, or internet routing, “just works.” I’m not saying this to say we shouldn’t question how things work - I think we all should - just that I don’t need to worry too much about how they work to put them to good use.

So what tools are available to make quantum computing user-friendly? To start, IBM offers a free online platform for creating quantum circuits or running a circuit on their 5 qubit quantum computer. This kind of accessibility to the public is vital for more innovation, and the Qiskit resources are very helpful. If you’re designing a hardware chip, there’s IBM’s new tool Qiskit Metal.

While the IBM Quantum Experience is an excellent learning site, I soon realized that designing software by manually connecting gates and qubits would not work for larger machines. Without the equivalent abstraction layers for quantum, we might require thousands of years to finish a system as complex as a rocket. To fully take advantage of quantum computing, users need platforms like Classiq, which offers a more abstracted design space, allowing us to take part in quantum algorithm design, regardless of how deep our knowledge of the underlying layers is.

From the transition of quantum computing to a higher, functional model, I can spend less time worrying about the underlying mechanics and more time creating new solutions - the creativity in design begins. Groundbreaking discoveries happen when people create independently, compare each other’s work, and constructively criticize one another. Algorithms, like most things, are not one-size-fits-all; with different needs, come different methods. Allowing people to design in an abstract space is necessary for new and exciting quantum algorithms.

With the advancements in quantum hardware and software, the possibilities seem endless, from modeling climate change to advanced flight orbits. Quantum computing can feel like rocket science, but with the right tools, our grandchildren could be designing million qubit circuits by the same age we were learning how to use a calculator.

After some time here with Classiq, it no longer feels like rocket science. It feels like I’m on the rocket, traveling into an exciting future with my colleagues and our customers.

About "The Qubit Guy's Podcast"

Hosted by The Qubit Guy (Yuval Boger, our Chief Marketing Officer), the podcast hosts thought leaders in quantum computing to discuss business and technical questions that impact the quantum computing ecosystem. Our guests provide interesting insights about quantum computer software and algorithm, quantum computer hardware, key applications for quantum computing, market studies of the quantum industry and more.

If you would like to suggest a guest for the podcast, please contact us.

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