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In 2025, quantum computing is rapidly scaling up, bringing clearer architectures and a fierce push toward building logical qubits. Even though the NISQ era is still here, researchers are focused on boosting fidelity and managing the heavy error-correction demands that stand between today’s systems and real quantum advantage. #QuantumComputing #NISQ #TechLeadership #QuantumTech #QuantumChemistry #QAOA #FutureOfTech
Meet the new Enabla #OpenAccess lecture by Prof. Sergey Denisov from the Oslo Metropolitan University, where he discusses the theoretical and experimental aspects of parameterized circuits and their ability to simulate random unitaries, offering a deep dive into NISQ implementations and their potential for sampling random channels.
Have a question? Ask online through our website, and Sergey will help you understand the material better! A must-watch for anyone involved in quantum computing and random matrix theory!
🔗 Watch the full lecture here: https://enabla.com/pub/1122/about
Abstract: We consider the spectral properties of random quantum channels, both theoretically and experimentally, discuss parameterized circuits in their ability to simulate random unitaries, and present results confirming the ability of NISQ implementations of these circuits to sample certain ensembles of random channels
#ComputerScience #QuantumComputing #RandomMatrixTheory #QuantumCircuits #NISQ #OpenScience
Adaptive Trotterization for Time-Dependent Hamiltonian Quantum Dynamics Using Piecewise Conservation Laws
Our new paper introduces an adaptive Trotterization algorithm to tackle time-dependent Hamiltonians in digital quantum simulation. We propose piecewise conserved quantities to control and estimate errors & error accumulation. Read more here in this PRL:
Digital quantum simulation relies on Trotterization to discretize time evolution into elementary quantum gates. On current quantum processors with notable gate imperfections, there is a critical trade-off between improved accuracy for finer time steps, and increased error rate on account of the larger circuit depth. We present an adaptive Trotterization algorithm to cope with time dependent Hamiltonians, where we propose a concept of piecewise ``conserved'' quantities to estimate errors in the time evolution between two (nearby) points in time; these allow us to bound the errors accumulated over the full simulation period. They reduce to standard conservation laws in the case of time independent Hamiltonians, for which we first developed an adaptive Trotterization scheme [H. Zhao et al., Making Trotterization adaptive and energy-self-correcting for NISQ devices and beyond, PRX Quantum 4, 030319 (2023).]. We validate the algorithm for a time dependent quantum spin chain, demonstrating that it can outperform the conventional Trotter algorithm with a fixed step size at a controlled error.
Making Trotterization Adaptive and Energy-Self-Correcting for NISQ Devices and Beyond
Digital quantum simulation requires time discretization by means of Trotterization. A finer time step improves simulation precision but inevitably leads to increased experimental errors for today’s noisy intermediate-scale quantum computers. Check out in our recent publication how to make Trotterization adaptive:
https://journals.aps.org/prxquantum/abstract/10.1103/PRXQuantum.4.030319