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Query complexity is a common tool for comparing quantum and classical computation, and it has produced many examples of how quantum algorithms differ from classical ones. Here we investigate in detail the role that oracles play for the advantage of quantum algorithms. We do so by using a simulation framework, Quantum Simulation Logic (QSL), to construct oracles and algorithms that solve some problems with the same success probability and number of queries as the quantum algorithms. The framework can be simulated using only classical resources at a constant overhead as compared to the quantum resources used in quantum computation. Our results clarify the assumptions made and the conditions needed when using quantum oracles. Using the same assumptions on oracles within the simulation framework we show that for some specific algorithms, such as the Deutsch-Jozsa and Simon’s algorithms, there simply is no advantage in terms of query complexity. This does not detract from the fact that quantum query complexity provides examples of how a quantum computer can be expected to behave, which in turn has proved useful for finding new quantum algorithms outside of the oracle paradigm, where the most prominent example is Shor’s algorithm for integer factorization.

Julia is a modern programming language that is (so they say) as easy to use as Python and as fast as Fortran, combined with the expressive power of Lisp. I will introduce the language via examples taken from linear algebra, differential equations, and scientific visualization.

In QFT, the renormalization group is usually formulated in Euclidean signature. I will discuss time-dependent probes of the RG, in Lorentzian signature, and derive new dynamical constraints that govern the spread of local operators. Through a chain of Wick rotations and dualities, the same methods lead to new sum rules for inflationary correlators, which relate observable quantities like the inflationary speed of sound to properties of the UV.