As classical transistors reach their physical limits due to quantum tunneling, new metrics and computing paradigms like quantum are required for continued progress.
Quantum computing operates on probabilistic principles within its own complexity class (BQP) to solve specific problems more efficiently than classical computers.
Key milestones in quantum computing hardware are traced from early algorithms in the 1980s to the recent multi-qubit chips from IBM, Google, and others.
The quantum ecosystem consists of hardware manufacturers, cloud providers offering quantum access, software companies, and end-users in sectors like finance and aerospace.
Quantum programming involves arranging gates in a circuit, similar to a music sheet, which requires knowledge of quantum physics and linear algebra to build effective algorithms.
Quantum DevOps extends the classical CI/CD pipeline with a critical evaluation step to assess algorithm compatibility and performance on specific, error-prone quantum backends.
The DIN SPEC 91480 provides a standardized set of KPIs and benchmarks to evaluate and compare the performance of different quantum hardware and algorithms.
The quantum software development lifecycle requires collaboration between mathematicians and physicists, involving unique steps like circuit translation and simulation before running on real hardware.
While practical utility is targeted for 2030, accessible tools like Crisp make it easier than ever for developers to start exploring and implementing quantum algorithms.
31:17Julian Burr
34:14Isabell Heider & David Alber
28:04Alexander Pirker
28:26Alex Waldherr
30:57Tomislav Tipurić, Alexander Glätzle & Jan Goetz
25:46Alex Waldherr
43:21Alexandra Waldherr
30:37Tomislav Tipurić
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Jobs that call for the skills explored in this talk.
SYSKRON GmbH
Regensburg, Germany
eleQtron GmbH
Delft Circuits B.V.