Quantum programming via algebraic effects- cross-fertilization between quantum and probabilistic programming
Abstract
This proposal is concerned with foundations for programming languages that support quantum effects. It is important for programmers to be able to test their programs on traditional hardware as well as on quantum hardware. This means it is important to be able to simulate some aspects of quantum hardware on a traditional computer. There are different levels of simulation in practice. Sometimes, a very detailed simulation is necessary, involving aspects of the quantum hardware such as noise and error need to be simulated. Other times, a very quick high level simulation is sufficient, where the main interest is the amount of resources used rather than the actual results. Somewhere in between, it may sometimes be appropriate to simulate some parts of the quantum program by replacing them with efficient traditional programs, ignoring the intricacies of the quantum hardware. The programmer needs fine-grained control for this full spectrum ranging from running on actual quantum hardware to a high level overview of resources. I propose to make progress on good languages for quantum programming by leveraging the recent framework of algebraic effects. It allows the programmer to separate the main structure of the program from specific and detailed choices about how it will be run. This is very useful in practice because once the separation is made, a theoretician can develop mathematical models of computational phenomena separate from the generalities of programming practice. The key work package of this project is to build on a connection with another new form of programming- probabilistic programming for statistical modelling. Recently, algebraic effects have been applied to probabilistic programming to allow a fine-grained refined method of modelling. The method here is to bring this method to bear on quantum programming, thus cross-fertilizing the two fields.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 07, 2023
- Source ID
- FA95502110038
Entities
People
- Samuel Staton
Organizations
- Air Force Office of Scientific Research
- United States Air Force
- University of Oxford