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Simanshu Kumar

Publications and source records attributed to Simanshu Kumar.

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OAM-Induced Lattice Rotation Reveals a Fractional Optimum in Fault-Tolerant GKP Quantum Sensing

Photon loss and dephasing rapidly degrade the sensitivity of quantum sensors, yet systematic methods for designing error-correcting codes whose geometry is simultaneously adapted to the sensing task and the noise channel do not exist. Here we establish that orbital-angular-momentum (OAM) encoding and Gottesman-Kitaev-Preskill (GKP) lattice geometry are structurally coupled: an OAM mode of topological charge $\ell$ induces a phase-space rotation $\theta_\ell=\ell\pi/\ell_{\max}$, corresponding to a family of twisted GKP stabilizer lattices. Using an end-to-end differentiable Strawberry Fields--TensorFlow circuit, we jointly optimise $\ell$, the lattice aspect ratio $r$, and the finite-energy envelope $\epsilon$ to maximise quantum Fisher information subject to $P_{\rm err}\leq10^{-3}$. The optimum occurs at the fractional charge $\ell=1.5$ ($\theta=67.5^\circ$), implementable with a half-integer spiral phase plate, which reduces $P_{\rm err}$ by $23.9\times$ relative to the square-lattice baseline while leaving $\mathcal{F}_Q$ unchanged to within $0.2\%$. This surpasses the best integer value ($\ell=2$, $15.7\times$) and arises from an exact $180^\circ$ periodicity of the $P_{\rm err}(\theta)$ landscape, confirmed analytically and numerically. We derive a transcendental balance equation for the optimal angle $\theta^*(\eta,\gamma,r)$ and prove that it decreases with both $\gamma$ and $\eta$. A Shannon-inspired metrological capacity $\mathcal{C}=\mathcal{F}_Q\cdot(-\ln P_{\rm err})$, maximised at $\ell=1.5$ with a $41\%$ gain over the square lattice, quantifies the joint sensitivity--fault-tolerance resource. These results establish a geometric design principle for noise-adaptive quantum sensors and a fully open-source differentiable template extensible to other bosonic code families.

quant-ph

Quantum-Enhanced Single-Parameter Phase Estimation with Adaptive NOON States

Quantum metrology promises phase sensitivity surpassing the shot-noise limit by exploiting entanglement and photon-number correlations. NOON states-maximally path-entangled $N$-photon superpositions $(|N,0\rangle + |0,N\rangle)/\sqrt{2}$ -achieve the Heisenberg limit $1/N$ for single-parameter estimation, as demonstrated experimentally by Afek et al. (2010) using hybrid coherent-plus-squeezed light up to $N=5$. We present an end-to-end differentiable quantum-optical framework-implemented in Strawberry Fields (Killoran et al., 2019) with a TensorFlow backend -that learns optimal circuit parameters by maximising the classical Fisher information (CFI) across all coincidence channels for $N=2,3,4,5$. Starting from proper numerical reproductions of the Afek et al. coincidence fringes, verified by FFT analysis and parity measurements, we apply gradient descent (Adam) to the eight trainable circuit parameters. Raw CFI improvements grow dramatically with photon number: $+153\%$ ($N=2$), $+834\%$ to $+956\%$ ($N=3$), $+829\%$ to $+1598\%$ ($N=4$), and $+1775\%$ ($N=5$), alongside post-selection rate improvements of $+153\%$ to $+3269\%$, and an $8\times$ to $133\times$ improvement in useful measurement events per pulse across $N=2$-$5$. A fundamental inter-channel trade-off is identified at $N=2$ but weakens at higher $N$ where the Afek initialisation is further from optimal. These results provide numerically rigorous benchmarks for adaptive single-parameter quantum sensing and demonstrate that the Afek working point is significantly suboptimal at $N\geq 3$. QFI calculations confirm that the optimised probe reaches $82\%$ of the Heisenberg limit at $N=2$ and improves from $36\%$ to $58\%$ at $N=5$, while useful measurement events per pulse improve by $8\times$ to $133\times$ across all $N$, making quantum-enhanced sensing at $N\geq 3$ experimentally practical.

quant-ph