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University of Cambridge > Talks.cam > Theory - Chemistry Research Interest Group > Developing Hybrid Quantum Monte Carlo Algorithms for Low Quantum Overheads and Improved Noise Resilience

## Developing Hybrid Quantum Monte Carlo Algorithms for Low Quantum Overheads and Improved Noise ResilienceAdd to your list(s) Download to your calendar using vCal - Dr Maria-Andreea Filip, University of Cambridge
- Wednesday 24 May 2023, 14:30-15:30
- Unilever Lecture Theatre, Yusuf Hamied Department of Chemistry.
If you have a question about this talk, please contact Lisa Masters. Quantum chemistry problems have recently become particularly interesting targets for quantum
computing algorithms due to their exponentially scaling Hilbert space which can be efficiently
mapped onto a linear number of qubits, promising significant memory improvements in quantum
over classical algorithms.
However, in the era of noisy intermediate-scale quantum (NISQ) devices and hybrid algorithms,
the size of chemical systems that can be treated is still severely limited, with hardware noise
and qubit decoherence precluding useful computation even for modest numbers of qubits.
Aditionally, most current quantum algorithms aim to use quantum devices to measure physical
quantities of interest effectively exactly. Lowering noise to acceptable levels therefore requires
non-trivial repetitions of the preparation and measurement procedure, which is both time- and
resource-consuming.
Quantum Monte Carlo (QMC) algorithms[1,2] have proven effective at lowering the computa-
tional overhead of challenging problems, both in classical This talk is part of the Theory - Chemistry Research Interest Group series. ## This talk is included in these lists:- All Talks (aka the CURE list)
- Department of Chemistry
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- Unilever Lecture Theatre, Yusuf Hamied Department of Chemistry
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