{"id":608696,"date":"2026-03-27T07:10:00","date_gmt":"2026-03-27T12:10:00","guid":{"rendered":"https:\/\/towardsdatascience.com\/?p=608696"},"modified":"2026-03-24T17:46:20","modified_gmt":"2026-03-24T22:46:20","slug":"a-beginners-guide-to-quantum-computing-with-python","status":"publish","type":"post","link":"https:\/\/towardsdatascience.com\/a-beginners-guide-to-quantum-computing-with-python\/","title":{"rendered":"A Beginner\u2019s Guide to Quantum Computing with Python"},"content":{"rendered":"\n

Intro<\/mdspan><\/h2>\n\n\n\n

Quantum Mechanics<\/strong><\/a> <\/strong>is a fundamental theory in physics that explains phenomena at a microscopic scale (like atoms and subatomic particles). This \u201cnew\u201d (1900) field differs from Classical Physics, which describes nature at a macroscopic scale (like bodies and machines) and doesn\u2019t apply at the quantum level.<\/p>\n\n\n\n

Quantum Computing<\/strong><\/a> <\/strong>is the exploitation of properties of Quantum Mechanics to perform computations and solve problems that a classical computer can\u2019t and never will. <\/p>\n\n\n\n

Normal computers speak the binary code<\/a> language: they assign a pattern of binary digits (1s and 0s) to each character and instruction, and store and process that information in bits<\/strong><\/a>. Even your Python code is translated into binary digits when it runs on your laptop. For example:<\/p>\n\n\n\n

The word “Hi” \u2192 “h”: 01001000<\/code> and “i”: 01101001<\/code> \u2192 01001000 01101001<\/code><\/p>\n\n\n\n

On the other end, quantum computers process information with qubits<\/a><\/strong> (quantum bits), which can be both 0 and 1 at the same time. That makes quantum machines dramatically faster than normal ones for specific problems (i.e. probabilistic computation).<\/p>\n\n\n\n

Quantum Computers<\/h2>\n\n\n\n

Quantum computers use atoms and electrons, instead of classical silicon-based chips. As a result, they can leverage Quantum Mechanics to perform calculations much faster than normal machines. For instance, 8-bits is enough for a classical computer to represent any number between 0 and 255, but 8-qubits is enough for a quantum computer to represent every number between 0 and 255 at the same time<\/strong>. A few hundred qubits would be enough to represent more numbers than there are atoms in the universe.<\/p>\n\n\n\n

The brain of a quantum computer is a tiny qubit chip<\/strong> made of metals or sapphire.<\/p>\n\n\n\n

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Photo by Niek Doup<\/a> on Unsplash<\/a><\/figcaption><\/figure>\n\n\n\n

However, the most iconic part is the big cooling hardware made of gold that looks like a chandelier hanging inside a steel cylinder: the dilution refrigerator<\/strong>. It cools the chip to a temperature colder than outer space as heat destroys quantum states (basically the colder it is, the more accurate it gets).<\/p>\n\n\n\n

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Photo by Planet Volumes<\/a> on Unsplash<\/a><\/figcaption><\/figure>\n\n\n\n

That is the leading type of architecture, and it’s called superconducting-qubits: artificial atoms created from circuits using superconductors (like aluminum) that exhibit zero electrical resistance at ultra-low temperatures. An alternative architecture is ion-traps (charged atoms trapped in electromagnetic fields in ultra\u2011high vacuum), which is more accurate but slower than the former.<\/p>\n\n\n\n

There is no exact public count of how many quantum computers are out there, but estimates are around 200 worldwide. As of today, the most advanced ones are:<\/p>\n\n\n\n

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  1. IBM’s Condor<\/em><\/a>, the largest qubit count built so far (1000 qubits), even if that alone doesn\u2019t equal useful computation as error rates still matter.<\/li>\n\n\n\n
  2. Google’s Willo<\/em>w<\/a> (105 qubits), with good error rate but still far from fault\u2011tolerant large\u2011scale computing.<\/li>\n\n\n\n
  3. IonQ’s Tempo<\/em><\/a> (100 qubits), ion-traps quantum computer with good capabilities but still slower than superconducting machines.<\/li>\n\n\n\n
  4. Quantinuum\u2019s Helios<\/em><\/a> (98 qubits), uses ion-traps architecture with some of the highest accuracy reported today.<\/li>\n\n\n\n
  5. Rigetti Computing’s Ankaa<\/em><\/a> (80 qubits).<\/li>\n\n\n\n
  6. Intel’s Tunnel Falls<\/em><\/a> (12 qubits).<\/li>\n\n\n\n
  7. Canada Xanadu’s Aurora<\/em><\/a> <\/em>(12 qubits), the first photonic quantum computer, using light instead of electrons to process information.<\/li>\n\n\n\n
  8. Microsoft’s Majorana<\/em><\/a>, the first computer designed to scale to a million qubits on a single chip (but it has 8 qubits at the moment).<\/li>\n\n\n\n
  9. Chinese SpinQ’s Mini<\/em><\/a>, the first portable small-scale quantum computer (2 qubits).<\/li>\n\n\n\n
  10. NVIDIA’s QPU<\/em><\/a> (Quantum Processing Unit<\/em>), the first GPU-accelerated quantum system.<\/li>\n<\/ol>\n\n\n\n

    At the moment, it’s impossible for a normal person to own a large-scale quantum computer, but you can access them through the cloud.<\/p>\n\n\n\n

    Setup<\/h2>\n\n\n\n

    In Python, there are several libraries to work with quantum computers around the world:<\/p>\n\n\n\n