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Variational quantum time evolution (VarQTE) allows us to simulate dynamical quantum systems with parameterized quantum circuits. We derive a posteriori, global phase-agnostic error bounds for real and imaginary time evolution based on McLachlans variational principle that can be evaluated efficiently. Rigorous error bounds are crucial in practice to adaptively choose variational circuits and to analyze the quality of optimization algorithms. The power of the new error bounds, as well as, the performance of VarQTE are demonstrated on numerical examples.
Quantum error correction is vital for implementing universal quantum computing. A key component is the encoding circuit that maps a product state of physical qubits into the encoded multipartite entangled logical state. Known methods are typically no
Variational Quantum Algorithms (VQAs) are a promising application for near-term quantum processors, however the quality of their results is greatly limited by noise. For this reason, various error mitigation techniques have emerged to deal with noise
The road to computing on quantum devices has been accelerated by the promises that come from using Shors algorithm to reduce the complexity of prime factorization. However, this promise hast not yet been realized due to noisy qubits and lack of robus
Imaginary time evolution is a powerful tool for studying quantum systems. While it is possible to simulate with a classical computer, the time and memory requirements generally scale exponentially with the system size. Conversely, quantum computers c
Quantum error mitigation techniques are at the heart of quantum hardware implementation, and are the key to performance improvement of the variational quantum learning scheme (VQLS). Although VQLS is partially robust to noise, both empirical and theo