In their recent work published in PRX Quantum, Timo Eckstein, Refik Mansuroglu, Stefan Wolf, Ludwig Nützel, Stephan Tasler, Martin Kliesch, and Michael J. Hartmann present a strategy to reduce the required number of measurements for estimating the energy of quantum lattice models.
In quantum computing, in contrast to its classical counterpart, the result of a computation is typically not a single deterministic bitstring but a probability distribution encoded in the prepared quantum state. Hence, a central task after the state preparation is to efficiently extract the desired information from this distribution, via measurements on the generated quantum state. A particularly relevant near-term measurement task is energy estimation for low-energy states, as they are considered an enabler for material science research via quantum computing.
The method introduced in this paper is based on partitioning a lattice into local patches of multiple adjacent lattice sites and then measuring those in the eigenbases of their local Hamiltonians. This requires a measurement gate sequence that transforms the local eigenstates into the computational basis, in which measurements can be realised. In their work, Timo Eckstein and his coworkers find that this strategy typically reduces the required number of measurements by several orders of magnitude.
Moreover, they prove that it always requires fewer measurements for the same precision as “naive” sampling in the computational basis.
It is expected that these results have a noticeable impact on near-term eigenstate preparation algorithms, as those typically need to estimate the state’s energy numerous times. Importantly, the patch size can be freely chosen to fit the available gate budget, starting from as little as one layer of mutually commuting 2-qubit gates, which are simply appended to the end of the existing quantum circuit.
For more information, see the publication in PRX Quantum:
Shot-Noise Reduction for Lattice Hamiltonians
Timo Eckstein, Refik Mansuroglu, Stefan Wolf, Ludwig Nützel, Stephan Tasler, Martin Kliesch, and Michael J. Hartmann
PRX Quantum 7, 020303 (2026)
In their recent work published in PRX Quantum, Timo Eckstein, Refik Mansuroglu, Stefan Wolf, Ludwig Nützel, Stephan Tasler, Martin Kliesch, and Michael J. Hartmann present a strategy to reduce the required number of measurements for estimating the energy of quantum lattice models.
In quantum computing, in contrast to its classical counterpart, the result of a computation is typically not a single deterministic bitstring but a probability distribution encoded in the prepared quantum state. Hence, a central task after the state preparation is to efficiently extract the desired information from this distribution, via measurements on the generated quantum state. A particularly relevant near-term measurement task is energy estimation for low-energy states, as they are considered an enabler for material science research via quantum computing.
The method introduced in this paper is based on partitioning a lattice into local patches of multiple adjacent lattice sites and then measuring those in the eigenbases of their local Hamiltonians. This requires a measurement gate sequence that transforms the local eigenstates into the computational basis, in which measurements can be realised. In their work, Timo Eckstein and his coworkers find that this strategy typically reduces the required number of measurements by several orders of magnitude.
Moreover, they prove that it always requires fewer measurements for the same precision as “naive” sampling in the computational basis.
It is expected that these results have a noticeable impact on near-term eigenstate preparation algorithms, as those typically need to estimate the state’s energy numerous times. Importantly, the patch size can be freely chosen to fit the available gate budget, starting from as little as one layer of mutually commuting 2-qubit gates, which are simply appended to the end of the existing quantum circuit.
For more information, see the publication in PRX Quantum:
Shot-Noise Reduction for Lattice Hamiltonians
Timo Eckstein, Refik Mansuroglu, Stefan Wolf, Ludwig Nützel, Stephan Tasler, Martin Kliesch, and Michael J. Hartmann
PRX Quantum 7, 020303 (2026)