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Algorithmic shadow spectroscopy
We present shadow spectroscopy as a simulator-agnostic quantum algorithm for estimating
energy gaps using very few circuit repetitions (shots) and no extra resources (ancilla qubits) …
energy gaps using very few circuit repetitions (shots) and no extra resources (ancilla qubits) …
Combining matrix product states and noisy quantum computers for quantum simulation
Matrix product states (MPSs) and matrix product operators (MPOs) have been proven to be a
powerful tool to study quantum many-body systems but are restricted to moderately …
powerful tool to study quantum many-body systems but are restricted to moderately …
Deep Circuit Compression for Quantum Dynamics via Tensor Networks
Dynamic quantum simulation is a leading application for achieving quantum advantage.
However, high circuit depths remain a limiting factor on near-term quantum hardware. We …
However, high circuit depths remain a limiting factor on near-term quantum hardware. We …
A Review and Collection of Metrics and Benchmarks for Quantum Computers: definitions, methodologies and software
Quantum computers have the potential to provide an advantage over classical computers in
a number of areas. Numerous metrics to benchmark the performance of quantum computers …
a number of areas. Numerous metrics to benchmark the performance of quantum computers …
Direct Estimation of the Density of States for Fermionic Systems
Simulating time evolution is one of the most natural applications of quantum computers and
is thus one of the most promising prospects for achieving practical quantum advantage …
is thus one of the most promising prospects for achieving practical quantum advantage …
Dynamic, symmetry-preserving, and hardware-adaptable circuits for quantum computing many-body states and correlators of the anderson impurity model
We present a hardware-reconfigurable ansatz on $ N_q $-qubits for the variational
preparation of many-body states of the Anderson impurity model (AIM) with $ N_ {\text …
preparation of many-body states of the Anderson impurity model (AIM) with $ N_ {\text …
Classical and quantum algorithms for many-body problems
T Ayral - Comptes Rendus. Physique, 2025 - comptes-rendus.academie-sciences …
The many-body problem is central to many fields, such as condensed-matter physics and
chemistry, but also to combinatorial optimization, which is nothing but a classical many-body …
chemistry, but also to combinatorial optimization, which is nothing but a classical many-body …
[PDF][PDF] Tensor-Variate Machine Learning on Graphs
YL Xu - core.ac.uk
Traditional machine learning algorithms are facing significant challenges as the world enters
the era of big data, with a dramatic expansion in volume and range of applications and an …
the era of big data, with a dramatic expansion in volume and range of applications and an …