Zobrazeno 1 - 10
of 111
pro vyhledávání: '"Leichenauer, Stefan"'
Autor:
Nezami, Sepehr, Lin, Henry W., Brown, Adam R., Gharibyan, Hrant, Leichenauer, Stefan, Salton, Grant, Susskind, Leonard, Swingle, Brian, Walter, Michael
Publikováno v:
PRX Quantum 4, 010321 (2023)
In [1] we discussed how quantum gravity may be simulated using quantum devices and gave a specific proposal -- teleportation by size and the phenomenon of size-winding. Here we elaborate on what it means to do 'Quantum Gravity in the Lab' and how siz
Externí odkaz:
http://arxiv.org/abs/2102.01064
Autor:
Peters, Evan, Caldeira, João, Ho, Alan, Leichenauer, Stefan, Mohseni, Masoud, Neven, Hartmut, Spentzouris, Panagiotis, Strain, Doug, Perdue, Gabriel N.
We present a quantum kernel method for high-dimensional data analysis using Google's universal quantum processor, Sycamore. This method is successfully applied to the cosmological benchmark of supernova classification using real spectral features wit
Externí odkaz:
http://arxiv.org/abs/2101.09581
Tensor networks, originally designed to address computational problems in quantum many-body physics, have recently been applied to machine learning tasks. However, compared to quantum physics, where the reasons for the success of tensor network appro
Externí odkaz:
http://arxiv.org/abs/2007.06082
Originating from condensed matter physics, tensor networks are compact representations of high-dimensional tensors. In this paper, the prowess of tensor networks is demonstrated on the particular task of one-class anomaly detection. We exploit the me
Externí odkaz:
http://arxiv.org/abs/2006.02516
Publikováno v:
Phys. Rev. Research 2, 033402 (2020)
The quantum approximate optimization algorithm (QAOA) is widely seen as a possible usage of noisy intermediate-scale quantum (NISQ) devices. We analyze the algorithm as a bang-bang protocol with fixed total time and a randomized greedy optimization s
Externí odkaz:
http://arxiv.org/abs/2005.13103
Autor:
Brown, Adam R., Gharibyan, Hrant, Leichenauer, Stefan, Lin, Henry W., Nezami, Sepehr, Salton, Grant, Susskind, Leonard, Swingle, Brian, Walter, Michael
Publikováno v:
PRX Quantum 4, 010320 (2023)
With the long-term goal of studying models of quantum gravity in the lab, we propose holographic teleportation protocols that can be readily executed in table-top experiments. These protocols exhibit similar behavior to that seen in the recent traver
Externí odkaz:
http://arxiv.org/abs/1911.06314
We introduce a new class of generative quantum-neural-network-based models called Quantum Hamiltonian-Based Models (QHBMs). In doing so, we establish a paradigmatic approach for quantum-probabilistic hybrid variational learning, where we efficiently
Externí odkaz:
http://arxiv.org/abs/1910.02071
Autor:
Verdon, Guillaume, McCourt, Trevor, Luzhnica, Enxhell, Singh, Vikash, Leichenauer, Stefan, Hidary, Jack
We introduce Quantum Graph Neural Networks (QGNN), a new class of quantum neural network ansatze which are tailored to represent quantum processes which have a graph structure, and are particularly suitable to be executed on distributed quantum syste
Externí odkaz:
http://arxiv.org/abs/1909.12264
Publikováno v:
Phys. Rev. Research 2, 023074 (2020)
The Quantum Approximate Optimization Algorithm (QAOA) is a standard method for combinatorial optimization with a gate-based quantum computer. The QAOA consists of a particular ansatz for the quantum circuit architecture, together with a prescription
Externí odkaz:
http://arxiv.org/abs/1909.07621
Publikováno v:
Phys. Rev. D 100, 126006 (2019)
We show that the bulk region reconstructable from a given boundary subregion --- which we term the reconstruction wedge --- can be much smaller than the entanglement wedge even when backreaction is small. We find arbitrarily large separations between
Externí odkaz:
http://arxiv.org/abs/1908.03975