A survey on the complexity of learning quantum states
A Anshu, S Arunachalam - Nature Reviews Physics, 2024 - nature.com
Quantum learning theory is a new and very active area of research at the intersection of
quantum computing and machine learning. Important breakthroughs in the past two years …
quantum computing and machine learning. Important breakthroughs in the past two years …
Speed limits and locality in many-body quantum dynamics
We review the mathematical speed limits on quantum information processing in many-body
systems. After the proof of the Lieb–Robinson Theorem in 1972, the past two decades have …
systems. After the proof of the Lieb–Robinson Theorem in 1972, the past two decades have …
Efficient tensor network simulation of ibm's eagle kicked ising experiment
We report an accurate and efficient classical simulation of a kicked Ising quantum system on
the heavy hexagon lattice. A simulation of this system was recently performed on a 127-qubit …
the heavy hexagon lattice. A simulation of this system was recently performed on a 127-qubit …
Optimal learning of quantum Hamiltonians from high-temperature Gibbs states
We study the problem of learning a Hamiltonian H to precision ε, supposing we are given
copies of its Gibbs state ρ=\exp(-βH)/Tr(\exp(-βH)) at a known inverse temperature β. Anshu …
copies of its Gibbs state ρ=\exp(-βH)/Tr(\exp(-βH)) at a known inverse temperature β. Anshu …
Group-theoretic error mitigation enabled by classical shadows and symmetries
Estimating expectation values is a key subroutine in quantum algorithms. Near-term
implementations face two major challenges: a limited number of samples required to learn a …
implementations face two major challenges: a limited number of samples required to learn a …
Quantum advantage and stability to errors in analogue quantum simulators
Several quantum hardware platforms, while being unable to perform fully fault-tolerant
quantum computation, can still be operated as analogue quantum simulators for addressing …
quantum computation, can still be operated as analogue quantum simulators for addressing …
Quantum many-body systems in thermal equilibrium
ÁM Alhambra - PRX Quantum, 2023 - APS
The thermal or equilibrium ensemble is one of the most ubiquitous states of matter. For
models comprised of many locally interacting quantum particles, it describes a wide range of …
models comprised of many locally interacting quantum particles, it describes a wide range of …
[PDF][PDF] Learning shallow quantum circuits
Despite fundamental interests in learning quantum circuits, the existence of a
computationally efficient algorithm for learning shallow quantum circuits remains an open …
computationally efficient algorithm for learning shallow quantum circuits remains an open …
Measuring the Loschmidt amplitude for finite-energy properties of the Fermi-Hubbard model on an ion-trap quantum computer
Calculating the equilibrium properties of condensed-matter systems is one of the promising
applications of near-term quantum computing. Recently, hybrid quantum-classical time …
applications of near-term quantum computing. Recently, hybrid quantum-classical time …
Phase-sensitive quantum measurement without controlled operations
Many quantum algorithms rely on the measurement of complex quantum amplitudes.
Standard approaches to obtain the phase information, such as the Hadamard test, give rise …
Standard approaches to obtain the phase information, such as the Hadamard test, give rise …