2 citations · 3 across the 3 of their papers we have counts for
6 papers
Algorithmic Randomness and Kolmogorov Complexity for Qubits
Tejas Bhojraj
Nies and Scholz defined quantum Martin-Löf randomness (q-MLR) for states (infinite qubitstrings). We define a notion of quantum Solovay randomness and show it to be equivalent to q…
Notions of indifference for genericity: Union and subsequence sets
Tejas Bhojraj
A set is said to be a universal indifferent set for -genericity if for every -generic and for all , is also -generic. Miller showed that ther…
Prefix-free quantum Kolmogorov complexity
Tejas Bhojraj
We introduce quantum-K (), a measure of the descriptive complexity of density matrices using classical prefix-free Turing machines and show that the initial segments of weak So…
Global Optimum Search in Quantum Deep Learning
Lanston Hau Man Chu, Tejas Bhojraj, Rui Huang
This paper aims to solve machine learning optimization problem by using quantum circuit. Two approaches, namely the average approach and the Partial Swap Test Cut-off method (PSTC)…
Quantum algorithmic randomness
Tejas Bhojraj
Quantum Martin-Löf randomness (q-MLR) for infinite qubit sequences was introduced by Nies and Scholz. We define a notion of quantum Solovay randomness which is equivalent to q-MLR.…
Generating Randomness from a Computable, Non-random Sequence of Qubits
Tejas Bhojraj
Nies and Scholz introduced the notion of a state to describe an infinite sequence of qubits and defined quantum-Martin-Lof randomness for states, analogously to the well known conc…