You don't need a PhD to try Quantum Computing

Quantum computing is no longer just for physicists. With tools like Qiskit and Cirq, as well as domain-specific languages like Q#, developers now have a growing number of ways to experiment with quantum circuits.

This talk offers a beginner-friendly, practical overview of where quantum computing stands today for developers. We’ll look at the current tools, languages, and simulators, including Qiskit, Cirq, and Strange, and how they fit into familiar programming environments. No physics background required, just curiosity.

Transcript

1. You donʼt need a PhD to try Quantum Computing Matteo Di Pirro Kynetics, Inc
2. About me • Principal Software Engineer @ Kynetics Inc • DevOps + application software ◦ Embedded ◦ Cloud • Been writing Scala code for ~ 5 years • No previous quantum physics/mechanics background
3. Agenda • Quantum computing: What and Why? • What about classical software developers? • QC simulation • Conclusion
4. Quantum Computing: Why? • Feynman, 1982 => Some experiments are difficult to simulate with computers • Quantum exp can do computations a classical computer can’t ◦ Constructive and destructive patterns • Some problems are difficult to solve with classical computers ◦ But “easy” for quantum computers Not about increasing the computational power, but changing how the computation is done
5. Quantum/Classical Computing /1 QC won’t be faster than Classical Computing for every problem Still unclear what QC will be useful for (Besides cryptography and physics/chemistry simulations!!)
6. Quantum/Classical Computing /2 QC won’t be faster than Classical Computing for every problem Still unclear what QC will be useful for (Besides cryptography and physics/chemistry simulations!!) Quantum and Classical computers will co-exist in the future!
7. The Qubit /1 • Can be ‘0’, ‘1’, or a “combination” of them ◦ Superposition • Represented as a vector ◦ α and β are amplitudes ◦ |α|2 and |β|2 are probabilities • Created by a quantum phenomenon • Subject to noise ◦ Interference ◦ Miscalibration => |0> => |1>
8. The Qubit /2 The cat can be dead or alive, but we won’t know until we open the box • Dead = 0 • Alive = 1 • Box closed => superposition • Box open => measurement
9. SWEs Just Wanna Have Fun /1 Large-scale QC are still many years away Quantum algorithms are very difficult to write
10. SWEs Just Wanna Have Fun /2 Large-scale QC are still many years away Quantum algorithms are very difficult to write But we want to play and learn new tools and languages
11. Quantum simulation Dedicated languages Libraries for existing languages
12. Quantum Random Number Generation Problem: Generate a (truly) random number in [0, max) 1. Determine how many bits are needed to represent max a. nbits = floor(ln(max) / ln(2) + 1) 2. Generate a binary string with length = nbits (quantum part) a. result 2 3. If result 10 > max, retry step #2 4. Return result 10
13. Strange Java • Quantum computing for the JVM • Low-level and high-level libraries • Straightforward (but simplified) API ◦ Not an SDK • Used for educational purposes and for JVM-based prototyping • Integration in JVM application • Less suited for research
14. IBM Qiskit • Based on Python • Comprehensive software stack ◦ SDK + Runtime ◦ Algorithm development ◦ HPC orchestration ◦ Noise simulation (also from real quantum devices) • Access to IBM’s real quantum hardware • Hardware agnostic ◦ Transpiler maps program qubits into physical ones
15. Google Cirq • Based on Python • Noisy Intermediate-Scale Quantum computing • Fine grained noise modelling • Hardware-aware ◦ Granular control over timing and placement of gates • Allows for deep optimisation of quantum devices • Integration with existing quantum hardware
16. Microsoft Q# • Quantum programming language ◦ Syntax similar to C# and F# • Built for hybrid quantum-classical applications ◦ Quantum code called by classical host program • Hardware agnostic ◦ Program qubits mapped to physical qubits • Configurable noise models • Part of Microsoft QDK
17. Conclusions • Quantum principles are already being leveraged ◦ Quantum Key Distribution ◦ Quantum Random Number Generation • Developers can start experimenting now ◦ Locally ◦ Cloud ◦ Real Quantum Hardware • Many other applications are still possible
18. If you think you understand quantum mechanics, you donʼt understand quantum mechanics. Richard Feynman Fortunately, you donʼt need to understand quantum mechanics if you want to leverage it. Johan Vos Creator of Strange) Matteo Di Pirro matteo.dipirro@kynetics.com VCard Code
19. Other relevant simulators/libraries • TensorFlow Quantum (Google) ◦ Prototyping of hybrid quantum-classical ML models ◦ Quantum data • CoqQ ◦ Framework to reason about quantum programs in Coq ◦ Used for soundness proofs • AWS Braket ◦ Up to 34 qubit simulator