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Lara Janiurek

Publications and source records attributed to Lara Janiurek.

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Continuum Limits of Lazy Open Quantum Walks

We derive the continuous spacetime limit of the one dimensional lazy discrete time quantum walk, obtaining explicit macroscopic evolution equations for a three state model in the presence of decoherence. While continuum limits of two state quantum walks are well established, an explicit continuous spacetime formulation for the lazy three state walk, particularly including noise, has not previously been constructed. Using an SU(3) representation of a Grover type coin together with a Lindblad formulation of decoherence acting either on the coin or the spatial subspace, we systematically expand the discrete dynamics in both space and time to obtain continuum master equations governing the coarse grained evolution. The resulting generators yield a genuine partial differential equation description of the walk, going beyond purely probabilistic or spectral correspondences. We show that the unitary limit is governed by a Dirac-type SU(3) Hamiltonian describing ballistic advection of left and right moving modes coupled by local symmetric mixing, with the rest state acting as an additional internal degree of freedom. Coin dephasing selectively damps internal coherences while preserving coherent spatial transport, whereas spatial dephasing suppresses long range spatial interference and rapidly drives the dynamics toward classical behaviour. This continuum framework clarifies how internal symmetry, rest state coupling, and distinct decoherence channels shape large scale transport in lazy open quantum walks, and provides a foundation for future extensions toward multichannel quantum transport models and quantum-inspired algorithms.

quant-ph

Quantum Walks on Arbitrary Spatial Networks with Rydberg Atoms

Rydberg atoms provide a highly promising platform for quantum computation, leveraging their strong tunable interactions to encode and manipulate information in the electronic states of individual atoms. Key advantages of Rydberg atoms include scalability, reconfigurable connectivity, and native multi-qubit gates, making them particularly well-suited for addressing complex network problems. These problems can often be framed as graph-based tasks, which can be efficiently addressed using quantum walks. In this work, we propose a general implementation of staggered quantum walks with Rydberg atoms, with a particular focus on spatial networks. We also present an efficient algorithm for constructing the tessellations required for the staggered quantum walk. Finally, we demonstrate that our proposal achieves quadratic speedup in spatial search algorithms.

quant-ph

Transferability of Photometric Redshifts Determined using Machine Learning

In this work the random forest algorithm GALPRO is implemented to generate photometric redshift posteriors, and its performance when trained and then applied to data from another survey is investigated. The algorithm is initially calibrated using a truth dataset compiled from the DESI Legacy survey. We find that the testing and training datasets must have very similar redshift distributions, with the range of their photometric data overlapping by at least 90% in the appropriate photometric bands in order for the training data to be applicable to the testing data. Then GALPRO is again trained using the DESI dataset and then applied to a sample drawn from the PanSTARRS survey, to explore whether GALPRO can be first trained using a trusted dataset and then applied to an entirely new survey, albeit one that uses a different magnitude system for its photometric bands, thus requiring careful conversion of the measured magnitudes for the new survey before GALPRO can be applied. The results of this further test indicate that GALPRO does not produce accurate photometric redshift posteriors for the new survey, even where the distribution of redshifts for the two datasets overlaps by over 90%. Hence, we conclude that the photometric redshifts generated by GALPRO are not suitable for generating estimates of photometric redshifts and their posterior distribution functions when applied to an entirely new survey, particularly one that uses a different magnitude system. However, our results demonstrate that GALPRO is a useful tool for inferring photometric redshift estimates in the case where a spectroscopic galaxy survey is nearly complete, but is missing some spectroscopic redshift values.

astro-ph.GA