arXiv subjects

Omri Porat

Publications and source records attributed to Omri Porat.

4 recordsLinked to original sources

arXiv2026

Ancilla mediated steady-state engineering in open quantum systems

Engineering the properties of a reservoir and its coupling to a quantum system is a powerful tool for simulating quantum thermodynamic processes and for generating otherwise inaccessible steady states. Yet tailoring both the reservoir and its coupling within a single platform remains challenging. Here we introduce a platform, in which an ancilla qubit mediates the coupling of a target system to a reservoir, providing independent control over the interaction form, coupling strength, and effective reservoir temperature. Our implementation uses the electron spin of a single nitrogen-vacancy center in diamond as the ancilla and a proximal $^{13}$C nuclear spin as the target. By alternating engineered unitary interactions with dissipative ancilla resets, we realize dynamics naturally described by a collision model, enabling straight-forward tracking of the work, heat, coherence, and entropy generated at every collision. We experimentally demonstrate conventional thermalization and also realize anti-thermalization: the stabilization of the target system in a temperature opposite to that of its reservoir. Finally, harnessing this steady-state engineering, we utilize the nuclear spin as a quantum battery, achieving a steady-state ergotropy exceeding $70\%$ of the theoretical maximum.

quant-ph↗

arXiv2026

Tuneable magnetic behaviour, electronic structure and nitrogen vacancy formation in Gd$_{x}$Sm$_{1-x}$N

The rare earth nitrides are the only series of intrinsic ferromagnetic semiconductors where the interplay of spin and unquenched orbital angular momentum provides access to a range of magnetic behaviour. Furthermore, the magnetic properties can be finely tuned through the combination of multiple lanthanide ions in the nitride. Here we present a combined computational and experimental study on the electronic and magnetic properties of Gd$_x$Sm$_{1-x}$N and discuss the effect of cation substitution on the internal exchange field and band structure. We find that as the coercive field of Gd$_x$Sm$_{1-x}$N changes over orders of magnitude via cation substitution the internal exchange field changes by $\sim$20%. Control of these material properties is vital in the field of superconducting spintronics. Finally, motivated by an enhanced concentration of nitrogen vacancies in films with higher Sm content, we investigate computationally the formation of nitrogen vacancy defects in Gd$_x$Sm$_{1-x}$N finding that the formation energy is significantly reduced for vacancy sites adjacent to Sm ions rather than Gd ions.

cond-mat.mtrl-sci↗

arXiv2025

Approximating Pandora's Knapsack via Simple Policies

We introduce Pandora's Knapsack: a hybrid between the classic stochastic knapsack problem [Dean et al., 2008] and Pandora's box [Weitzman, 1979]. As in stochastic knapsack, items have sizes drawn from known distributions, and items that fit within a knapsack contribute to the total value. As in Pandora, every item $i$ comes in a box that costs $c_i$ to open. What distinguishes our problem is that the size is revealed only after opening the box and paying the cost. We study the power of simple decision-making policies to approximate Pandora's Knapsack, along two complexity axes: (i)~knowledge of size distributions, and (ii)~adaptivity. We show that adding costs to stochastic knapsack completely changes the algorithmic landscape, and policies must now be complex along both axes to be approximately-optimal. We complement these impossibilities by showing that with full distributional information and slightly more adaptivity---allowing adaptive skipping of items---a constant approximation can be recovered. Our analysis reveals an economic quantity, namely ROI (return-on-investment, defined as the jobs' minimum utility over cost), which smoothly characterizes the performance of simple policies. Across a hierarchy of increasingly adaptive policies, we establish near-tight adaptivity gaps all governed by ROI. To demonstrate the importance of the ROI parameter in characterizing simple policies, we revisit Pandora's Box, and show that return-on-investment exactly captures the adaptivity gap in this classic problem as well. As a corollary, we get that simple policies are approximately-optimal provided the ROI is sufficiently large.

cs.GT↗

arXiv2025

A Comprehensive Machine Learning Framework for Micromobility Demand Prediction

Dockless e-scooters, a key micromobility service, have emerged as eco-friendly and flexible urban transport alternatives. These services improve first and last-mile connectivity, reduce congestion and emissions, and complement public transport for short-distance travel. However, effective management of these services depends on accurate demand prediction, which is crucial for optimal fleet distribution and infrastructure planning. While previous studies have focused on analyzing spatial or temporal factors in isolation, this study introduces a framework that integrates spatial, temporal, and network dependencies for improved micromobility demand forecasting. This integration enhances accuracy while providing deeper insights into urban micromobility usage patterns. Our framework improves demand prediction accuracy by 27 to 49% over baseline models, demonstrating its effectiveness in capturing micromobility demand patterns. These findings support data-driven micromobility management, enabling optimized fleet distribution, cost reduction, and sustainable urban planning.

cs.LG↗