79 citations · 303 across the 11 of their papers we have counts for
11 papers
Deep learning lattice gauge theories
Anuj Apte, Anthony Ashmore, Clay Cordova +1
Monte Carlo methods have led to profound insights into the strong-coupling behaviour of lattice gauge theories and produced remarkable results such as first-principles computations…
Quantum Alternating Operator Ansatz (QAOA) beyond low depth with gradually changing unitaries
Vladimir Kremenetski, Anuj Apte, Tad Hogg +2
The Quantum Approximate Optimization Algorithm and its generalization to Quantum Alternating Operator Ansatz (QAOA) is a promising approach for applying quantum computers to challe…
A Quadratic Speedup in the Optimization of Noisy Quantum Optical Circuits
Robbe De Prins, Yuan Yao, Anuj Apte +1
Linear optical quantum circuits with photon number resolving (PNR) detectors are used for both Gaussian Boson Sampling (GBS) and for the preparation of non-Gaussian states such as…
Obstructions to Gapped Phases from Non-Invertible Symmetries
Anuj Apte, Clay Cordova, Ho Tat Lam
Quantum systems in 3+1-dimensions that are invariant under gauging a one-form symmetry enjoy novel non-invertible duality symmetries encoded by topological defects. These symmetrie…
Non-Convex Optimization by Hamiltonian Alternation
Anuj Apte, Kunal Marwaha, Arvind Murugan
A major obstacle to non-convex optimization is the problem of getting stuck in local minima. We introduce a novel metaheuristic to handle this issue, creating an alternate Hamilton…
Embedding Learning in Hybrid Quantum-Classical Neural Networks
Minzhao Liu, Junyu Liu, Rui Liu +4
Quantum embedding learning is an important step in the application of quantum machine learning to classical data. In this paper we propose a quantum few-shot embedding learning par…