arXiv subjects

A. Jadbabaie

Publications and source records attributed to A. Jadbabaie.

4 recordsLinked to original sources

arXiv2026

Radioactive Molecules as Laboratories of Fundamental Physics

Radioactive molecules provide a powerful new platform in the search for new physics at energy scales complementary to high-energy particle colliders. By combining enhancements from nuclear properties with the sensitivity and control offered by molecular structure, experiments with radioactive molecules offer great reach in the search for new physics beyond the Standard Model. Rapid progress in this field is being driven by advances in the production and control of radioactive molecules, alongside the development of new experimental tools and theoretical techniques. In this Perspective, we discuss the current status and future prospects of this rapidly developing, interdisciplinary field at the intersection of nuclear physics, atomic and molecular physics, and particle physics.

physics.atom-ph↗

arXiv2016

Minimal Actuator Placement with Bounds on Control Effort

We address the problem of minimal actuator placement in linear systems so that the volume of the set of states reachable with one unit or less of input energy is lower bounded by a desired value. First, following the recent work of Olshevsky, we prove that this is NP-hard. Then, we provide an efficient algorithm which, for a given range of problem parameters, approximates up to a multiplicative factor of O(logn), n being the network size, any optimal actuator set that meets the same energy criteria; this is the best approximation factor one can achieve in polynomial time, in the worst case. Moreover, the algorithm uses a perturbed version of the involved control energy metric, which we prove to be supermodular. Next, we focus on the related problem of cardinality-constrained actuator placement for minimum control effort, where the optimal actuator set is selected to maximize the volume of the set of states reachable with one unit or less of input energy. While this is also an NP-hard problem, we use our proposed algorithm to efficiently approximate its solutions as well.

math.OC↗

arXiv2016

Mapping quantum state dynamics in spontaneous emission

The evolution of a quantum state undergoing radiative decay depends on how the emission is detected. We employ phase-sensitive amplification to perform homodyne detection of the spontaneous emission from a superconducting artificial atom. Using quantum state tomography, we characterize the correlation between the detected homodyne signal and the emitter's state, and map out the conditional back-action of homodyne measurement. By tracking the diffusive quantum trajectories of the state as it decays, we characterize selective stochastic excitation induced by the choice of measurement basis. Our results demonstrate dramatic differences from the quantum jump evolution that is associated with photodetection and highlight how continuous field detection can be harnessed to control quantum evolution.

quant-ph↗

arXiv2011

Accelerated Dual Descent for Network Optimization

Dual descent methods are commonly used to solve network optimization problems because their implementation can be distributed through the network. However, their convergence rates are typically very slow. This paper introduces a family of dual descent algorithms that use approximate Newton directions to accelerate the convergence rate of conventional dual descent. These approximate directions can be computed using local information exchanges thereby retaining the benefits of distributed implementations. The approximate Newton directions are obtained through matrix splitting techniques and sparse Taylor approximations of the inverse Hessian.We show that, similarly to conventional Newton methods, the proposed algorithm exhibits superlinear convergence within a neighborhood of the optimal value. Numerical analysis corroborates that convergence times are between one to two orders of magnitude faster than existing distributed optimization methods. A connection with recent developments that use consensus iterations to compute approximate Newton directions is also presented.

math.OC↗