arXiv subjects

Benjamin Rogers

Publications and source records attributed to Benjamin Rogers.

5 recordsLinked to original sources

arXiv2026

Collaborative estimation and evaluation of SARS-CoV-2 variant nowcasting in the United States

The ability to estimate and predict pathogen variant dynamics can inform public health responses, including planning for increased transmission or severity, shifts in population immunity, or changes to vaccine or therapeutic effectiveness. The COVID-19 pandemic demonstrated the importance of monitoring SARS-CoV-2 variant evolution through viral genome sequencing, enabling predictive models to estimate variant frequencies in the recent past, present, and short-term future. Collaborative forecasting Hubs provided a valuable way to centralize predictive modeling of epidemiological indicators such as cases, hospitalizations, and deaths during the pandemic; however, none existed for variant dynamics. Here, we discuss the creation of the United States SARS-CoV-2 Variant Nowcast Hub, designed to solicit estimates of the relative abundance of a specified set of SARS-CoV-2 variants at the U.S. state level. We discuss the design decisions and challenges in building the Hub and its scoring procedures. Using submissions from the Hub's first respiratory virus season (nowcast dates October 9th, 2024 to June 4th, 2025), we evaluate five individual models and a baseline model. We found that the baseline model, which pools sequences across the U.S., performs well overall, with most individual models performing similarly or slightly worse. Locations with lower sequencing volumes exhibited greater variability in model performance. Models submitted for a single location outperformed those submitted for all locations, potentially due to greater timeliness and magnitude of local data. Much remains to be investigated regarding relative model performance across different phases of variant emergence, and we conclude by proposing future directions within and beyond this Hub.

stat.AP↗

arXiv2026

Echo Cross Resonance gate error budgeting on a superconducting quantum processor

High fidelity quantum operations are key to enabling fault-tolerant quantum computation. Superconducting quantum processors have demonstrated high-fidelity operations, but on larger devices there is commonly a broad distribution of qualities, with the low-performing tail affecting near-term performance and applications. Here we present an error budgeting procedure for the native two-qubit operation on a 32-qubit superconducting-qubit-based quantum computer, the OQC Toshiko gen-1 system. We estimate the prevalence of different forms of error such as coherent error and control qubit leakage, then apply error suppression strategies based on the most significant sources of error, making use of pulse-shaping and additional compensating gates. These techniques require no additional hardware overhead and little additional calibration, making them suitable for routine adoption. An average reduction of 3.7x in error rate for two qubit operations is shown across a chain of 16 qubits, with the median error rate improving from 4.6$\%$ to 1.2$\%$ as measured by interleaved randomized benchmarking. The largest improvements are seen on previously under-performing qubit pairs, demonstrating the importance of practical error suppression in reducing the low-performing tail of gate qualities and achieving consistently good performance across a device.

quant-ph↗

arXiv2023

Evaluating infectious disease forecasts with allocation scoring rules

Recent years have seen increasing efforts to forecast infectious disease burdens, with a primary goal being to help public health workers make informed policy decisions. However, there has only been limited discussion of how predominant forecast evaluation metrics might indicate the success of policies based in part on those forecasts. We explore one possible tether between forecasts and policy: the allocation of limited medical resources so as to minimize unmet need. We use probabilistic forecasts of disease burden in each of several regions to determine optimal resource allocations, and then we score forecasts according to how much unmet need their associated allocations would have allowed. We illustrate with forecasts of COVID-19 hospitalizations in the US, and we find that the forecast skill ranking given by this allocation scoring rule can vary substantially from the ranking given by the weighted interval score. We see this as evidence that the allocation scoring rule detects forecast value that is missed by traditional accuracy measures and that the general strategy of designing scoring rules that are directly linked to policy performance is a promising direction for epidemic forecast evaluation.

stat.AP↗

arXiv2014

Hybrid optomechanics for Quantum Technologies

We review the physics of hybrid optomechanical systems consisting of a mechanical oscillator interacting with both a radiation mode and an additional matter-like system. We concentrate on the cases embodied by either a single or a multi-atom system (a Bose-Einstein condensate, in particular) and discuss a wide range of physical effects, from passive mechanical cooling to the set-up of multipartite entanglement, from optomechanical non-locality to the achievement of non-classical states of a single mechanical mode. The reviewed material showcases the viability of hybridised cavity optomechanical systems as basic building blocks for quantum communication networks and quantum state-engineering devices, possibly empowered by the use of quantum and optimal control techniques. The results that we discuss are instrumental to the promotion of hybrid optomechanical devices as promising experimental platforms for the study of non-classicality at the genuine mesoscopic level.

quant-ph↗

arXiv2014

Long-range multipartite entanglement close to a first order quantum phase transition

We provide insight in the quantum correlations structure present in strongly correlated systems beyond the standard framework of bipartite entanglement. To this aim we first exploit rotationally invariant states as a test bed to detect genuine tripartite entanglement beyond the nearest-neighbor in spin-1/2 models. Then we construct in a closed analytical form a family of entanglement witnesses which provides a sufficient condition to determine if a state of a many-body system formed by an arbitrary number of spin-1/2 particles possesses genuine tripartite entanglement, independently of the details of the model. We illustrate our method by analyzing in detail the anisotropic XXZ spin chain close to its phase transitions, where we demonstrate the presence of long range multipartite entanglement near the critical point and the breaking of the symmetries associated to the quantum phase transition.

quant-ph↗