59 citations · 91 across the 6 of their papers we have counts for
6 papers
Unbiased sampling from Boltzmann distributions with noisy energies
Iwo Sanderski, Gian Gentinetta, Giuseppe Carleo
Sampling from the Boltzmann distribution is central to computational physics, yet hard when the energy is known only through a stochastic estimate, such as with machine-learned mol…
Quantum Finite Temperature Lanczos Method
Gian Gentinetta, Friederike Metz, William Kirby +1
The computation of thermal properties of quantum many-body systems is a central challenge in our understanding of quantum mechanics. We introduce the Quantum Finite Temperature Lan…
Correcting and extending Trotterized quantum many-body dynamics
Gian Gentinetta, Friederike Metz, Giuseppe Carleo
A complex but important challenge in understanding quantum mechanical phenomena is the simulation of quantum many-body dynamics. Although quantum computers offer significant potent…
Overhead-constrained circuit knitting for variational quantum dynamics
Gian Gentinetta, Friederike Metz, Giuseppe Carleo
Simulating the dynamics of large quantum systems is a formidable yet vital pursuit for obtaining a deeper understanding of quantum mechanical phenomena. While quantum computers hol…
Quantum Kernel Alignment with Stochastic Gradient Descent
Gian Gentinetta, David Sutter, Christa Zoufal +2
Quantum support vector machines have the potential to achieve a quantum speedup for solving certain machine learning problems. The key challenge for doing so is finding good quantu…
The complexity of quantum support vector machines
Gian Gentinetta, Arne Thomsen, David Sutter +1
Quantum support vector machines employ quantum circuits to define the kernel function. It has been shown that this approach offers a provable exponential speedup compared to any kn…