Optimal multi-spectral squeezing via deterministic 2D-phase optimization

• URL: http://arxiv.org/abs/2606.20192v1
• Date: Thu, 18 Jun 2026 13:05:53 GMT
• Title: Optimal multi-spectral squeezing via deterministic 2D-phase optimization
• Abstract summary: We develop a sequential algorithm that reaches the global maximum of the visibility in a pixel basis and scales linearly with the number of pixels.<n>In our waveguide-based setup, the optimized mask increases the visibility from 76% to 84%, corresponding to a 20% gain in mode-matching efficiency.<n>These results establish deterministic spatial phase shaping as an effective, interpretable route to enhanced multimode squeezing in waveguide platforms.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Optimization routines are ubiquitous in quantum information technologies and essential to reach the resource levels required by quantum protocols. Specifically, multi-spectral squeezing for use in such protocols requires that losses be kept minimal at every stage, including coherent detection, which is performed by interfering the signal with a classical local-oscillator beam. This in turn requires control over all optical degrees of freedom of the beam in order to optimize the detection. The most general framework for this optimization relies on agnostic, off-the-shelf machine-learning techniques. Here we take the opposite approach: by focusing on a physical description of the specific optical process, we develop a deterministic sequential algorithm that provably reaches the global maximum of the visibility in a pixel basis and scales linearly with the number of pixels, thereby offering an efficient and theoretically grounded alternative to black-box optimization. In our waveguide-based setup, the optimized mask increases the visibility from 76% to 84%, corresponding to a 20% gain in mode-matching efficiency. Multi-spectral squeezing measurements confirm that this improvement translates directly into quantum readout: for the most squeezed spectral mode, the squeezing increases from $-2.08$ dB to $-2.64$ dB, consistent with the inferred efficiency gain. These results establish deterministic spatial phase shaping as an effective, interpretable route to enhanced multimode squeezing in waveguide platforms.

Related papers

• Pulse engineering via projection of response functions at infinite nonlinear order [0.0]
  We propose an algorithm for optimal control problems in quantum computing.<n>The proposed algorithm efficiently generates high-fidelity control protocols for multi-qubit systems.<n>The results indicate faster convergence regarding iteration steps and computational time.
  arXiv  Detail & Related papers  (2026-07-27T17:55:57Z)
• LithoGRPO: Fast Inverse Lithography via GRPO Reinforced Flow Matching [51.14153938143746]
  Inverse Lithography Technology (ILT) generates optimized masks that enhance the fidelity of pattern transfer onto wafers.<n>We introduce LithoGRPO, an ILT framework that integrates the flow-matching paradigm with GRPO-based reinforcement learning (RL) fine-tuning.<n>To improve RL sampling efficiency, we propose a fast shot-counting algorithm for manufacturability evaluation, achieving over 130x speedup.
  arXiv  Detail & Related papers  (2026-05-29T18:01:59Z)
• Antenna Array Beamforming Based on a Hybrid Quantum Optimization Framework [1.599072005190786]
  This paper proposes a hybrid quantum optimization framework for large-scale antenna-array beamforming.<n>For phase optimization, a Gray-code and odd-combination encoding scheme is introduced to improve robustness.<n>For amplitude optimization, a geometric spin-combination encoding and a two-stage strategy are developed.
  arXiv  Detail & Related papers  (2026-03-20T15:54:50Z)
• BONNI: Gradient-Informed Bayesian and Interior Point Optimization for Efficient Inverse Design in Nanophotonics [28.968853022624444]
  Inverse design provides a systematic approach for developing high-performance nanophotonic devices.<n>We introduce BONNI: Bayesian optimization through neural network ensemble surrogates with interior point optimization.<n>We demonstrate BONNI's capabilities in the design of a distributed Bragg reflector and a dual-layer grating coupler.
  arXiv  Detail & Related papers  (2026-02-20T11:26:45Z)
• Robust Quantum Control for Bragg Pulse Design in Atom Interferometry [0.0]
  We formulate a robust optimal control algorithm to synthesize minimum energy pulses that can transfer a cold atom system into various momentum states.<n>The algorithm is applied to optimize the atomic beam operation in ultra-cold atom interferometry.
  arXiv  Detail & Related papers  (2025-02-07T02:29:27Z)
• Quantum landscape tomography for efficient single-gate optimization on quantum computers [0.0]
  Circuit optimization is a fundamental task for practical applications of near-term quantum computers. We propose a process called quantum landscape tomography to characterize the influence of individual gates on the entire circuit. Our findings highlight the potential of quantum landscape tomography to enhance circuit optimization in near-term quantum computing applications.
  arXiv  Detail & Related papers  (2024-07-25T18:00:06Z)
• Variational quantum algorithm for enhanced continuous variable optical phase sensing [0.0]
  Variational quantum algorithms (VQAs) are hybrid quantum-classical approaches used for tackling a wide range of problems on noisy quantum devices. We implement a variational algorithm designed for optimized parameter estimation on a continuous variable platform based on squeezed light.
  arXiv  Detail & Related papers  (2023-12-21T14:11:05Z)
• Dynamic Frame Interpolation in Wavelet Domain [57.25341639095404]
  Video frame is an important low-level computation vision task, which can increase frame rate for more fluent visual experience. Existing methods have achieved great success by employing advanced motion models and synthesis networks. WaveletVFI can reduce computation up to 40% while maintaining similar accuracy, making it perform more efficiently against other state-of-the-arts.
  arXiv  Detail & Related papers  (2023-09-07T06:41:15Z)
• Optimal Algorithms for the Inhomogeneous Spiked Wigner Model [89.1371983413931]
  We derive an approximate message-passing algorithm (AMP) for the inhomogeneous problem. We identify in particular the existence of a statistical-to-computational gap where known algorithms require a signal-to-noise ratio bigger than the information-theoretic threshold to perform better than random.
  arXiv  Detail & Related papers  (2023-02-13T19:57:17Z)
• Retrieving space-dependent polarization transformations via near-optimal quantum process tomography [55.41644538483948]
  We investigate the application of genetic and machine learning approaches to tomographic problems. We find that the neural network-based scheme provides a significant speed-up, that may be critical in applications requiring a characterization in real-time. We expect these results to lay the groundwork for the optimization of tomographic approaches in more general quantum processes.
  arXiv  Detail & Related papers  (2022-10-27T11:37:14Z)
• Multipoint-BAX: A New Approach for Efficiently Tuning Particle Accelerator Emittance via Virtual Objectives [47.52324722637079]
  We propose a new information-theoretic algorithm, Multipoint-BAX, for black-box optimization on multipoint queries. We use Multipoint-BAX to minimize emittance at the Linac Coherent Light Source (LCLS) and the Facility for Advanced Accelerator Experimental Tests II (FACET-II)
  arXiv  Detail & Related papers  (2022-09-10T04:01:23Z)
• Direct Optimal Control Approach to Laser-Driven Quantum Particle Dynamics [77.34726150561087]
  We propose direct optimal control as a robust and flexible alternative to indirect control theory. The method is illustrated for the case of laser-driven wavepacket dynamics in a bistable potential.
  arXiv  Detail & Related papers  (2020-10-08T07:59:29Z)
• Adaptive pruning-based optimization of parameterized quantum circuits [62.997667081978825]
  Variisy hybrid quantum-classical algorithms are powerful tools to maximize the use of Noisy Intermediate Scale Quantum devices. We propose a strategy for such ansatze used in variational quantum algorithms, which we call "Efficient Circuit Training" (PECT) Instead of optimizing all of the ansatz parameters at once, PECT launches a sequence of variational algorithms.
  arXiv  Detail & Related papers  (2020-10-01T18:14:11Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.