5 papers
The trainability of photonic quantum circuits
Alexander Makarovskiy, Adam Taylor, Zhenghao Li +5
Variational quantum algorithms are a leading approach to near-term quantum computing, but their scalability can be limited by barren plateaus and the sampling cost of resolving sma…
Quantum latent distributions in deep generative models
Omar Bacarreza, Thorin Farnsworth, Alexander Makarovskiy +6
Many successful families of generative models leverage a low-dimensional latent distribution that is mapped to a data distribution. Though simple latent distributions are often use…
Boundaries for quantum advantage with single photons and loop-based time-bin interferometers
Samo Novák, David D. Roberts, Alexander Makarovskiy +2
Loop-based boson samplers interfere photons in the time degree of freedom using a sequence of delay lines. Since they require few hardware components while also allowing for long-r…
A Binary Optimisation Algorithm for Near-Term Photonic Quantum Processors
Alexander Makarovskiy, Mateusz Slysz, Åukasz Grodzki +5
Binary optimisation tasks are ubiquitous in areas ranging from logistics to cryptography. The exponential complexity of such problems means that the performance of traditional comp…
Exact gradients for linear optics with single photons
Giorgio Facelli, David D. Roberts, Hugo Wallner +3
Though parameter shift rules have drastically improved gradient estimation methods for several types of quantum circuits, leading to improved performance in downstream tasks, so fa…