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Found 12 papers, 3 papers with code
Renormalizing Diffusion Models
We explain how to use diffusion models to learn inverse renormalization group flows of statistical and quantum field theories.
Analyzing Populations of Neural Networks via Dynamical Model Embedding
The specific model to be emulated is determined by a model embedding vector that the meta-model takes as input; these model embedding vectors constitute a manifold corresponding to the given population of models.
Hardware-efficient learning of quantum many-body states
Efficient characterization of highly entangled multi-particle systems is an outstanding challenge in quantum science.
The Complexity of NISQ
The recent proliferation of NISQ devices has made it imperative to understand their computational power.
Revisiting dequantization and quantum advantage in learning tasks
In this note, we prove that classical algorithms with SQ access can accomplish some learning tasks exponentially faster than quantum algorithms with quantum state inputs.
Quantum advantage in learning from experiments
Quantum technology has the potential to revolutionize how we acquire and process experimental data to learn about the physical world.
Exponential separations between learning with and without quantum memory
We study the power of quantum memory for learning properties of quantum systems and dynamics, which is of great importance in physics and chemistry.
A Hierarchy for Replica Quantum Advantage
We prove that given the ability to make entangled measurements on at most $k$ replicas of an $n$-qubit state $\rho$ simultaneously, there is a property of $\rho$ which requires at least order $2^n$ measurements to learn.
Quantum Algorithmic Measurement
We initiate the systematic study of experimental quantum physics from the perspective of computational complexity.
Quantum Physics Strongly Correlated Electrons
Gravitational Constrained Instantons
We find constrained instantons in Einstein gravity with and without a cosmological constant.
High Energy Physics - Theory General Relativity and Quantum Cosmology
Spectral decoupling in many-body quantum chaos
We argue that in a large class of disordered quantum many-body systems, the late time dynamics of time-dependent correlation functions is captured by random matrix theory, specifically the energy eigenvalue statistics of the corresponding ensemble of disordered Hamiltonians.
High Energy Physics - Theory Statistical Mechanics Strongly Correlated Electrons Quantum Physics
Quantum Overlapping Tomography
By leveraging (i) that single-qubit measurements can be made in parallel, and (ii) the theory of perfect hash families, we show that all $k$-qubit reduced density matrices of an $n$ qubit state can be determined with at most $e^{\mathcal{O}(k)} \log^2(n)$ rounds of parallel measurements.
Quantum Physics Quantum Gases Strongly Correlated Electrons
