US-12625079-B2 - Adaptive information mining interferometry apparatuses and methods

US12625079B2US 12625079 B2US12625079 B2US 12625079B2US-12625079-B2

Abstract

Imaging systems and methods are disclosed for detecting objects in low photon environments. Embodiments modulate separate groups of photons from the same source, modulate the wavefronts of the separate groups of photons, recombine the modulated photons, utilize information of the recombined photons (such as by utilizing pre-trained reinforcement learning networks and/or by using the Fisher information), and iteratively adjust the manner in which the wavefronts are modulated to detect objects in the sub-Rayleigh region, and in dim regions with a small number of photons, for example, on the order of 10,000 per second or less. Further embodiments determine the iterative modulation patterns utilizing pre-trained reinforcement learning networks.

Inventors

Zubin Jacob
Hyunsoo CHOI
Fanglin Bao
Adrian Ezequiel RUBIO LOPEZ

Assignees

PURDUE RESEARCH FOUNDATION

Dates

Publication Date: 20260512
Application Date: 20231114

Claims (19)

1 . An apparatus, comprising: a light separator configured to separate photons traveling in a single pathway into a first pathway and a second pathway; a first spatial light modulator configured to modulate photons traveling along the first pathway; a light combiner configured to combine a first subset of photons traveling along the first pathway after being modulated by the first spatial light modulator with a first subset of photons traveling along the second pathway and direct these combined photons along a third pathway, and combine a second subset of photons traveling along the first pathway after being modulated by the first spatial light modulator with a second subset of photons traveling along the second pathway and direct these combined photons along a fourth pathway; a first photon detector configured to receive photons traveling along the third pathway and output a first signal representative of the distribution of photons traveling along the third pathway; a second photon detector configured to receive photons traveling along the fourth pathway and output a second signal representative of the distribution of photons traveling along the fourth pathway; and one or more processors configured to receive the first signal representative of the distribution of photons traveling along the third pathway, receive the second signal representative of the distribution of photons traveling along the fourth pathway, generate a first command for the first spatial light modulator based on the first and second signals, and provide the first command to the first spatial light modulator, and wherein the first spatial light modulator is configured to modulate photons traveling along the first pathway according to the first command of the of the one or more processors.
2 . The apparatus of claim 1 , wherein the first command is generated based at least in part on a pre-trained reinforcement learning network that has undergone prior training to address resolution of multiple sources within the sub-Rayleigh region in a low photon regime.
3 . The apparatus of claim 1 , wherein the first command is generated based at least in part on Fisher information of the photons traveling along at least one of the third and fourth pathways.
4 . The apparatus of claim 1 , further comprising: a second spatial light modulator configured to modulate photons traveling along the second pathway; wherein the first subset of photons traveling along the second pathway being combined by the light combiner are a first subset of photons that are traveling along the second pathway after being modulated by the second spatial light modulator wherein the one or more processors are configured to generate a second command for the second spatial light modulator based on the first and second signals, and provide the second command to the first spatial light modulator; and wherein the second spatial light modulator is configured to modulate photons traveling along the second pathway according to the second command of the one or more processors.
5 . The apparatus of claim 4 , wherein at least one of the first and second commands are generated based at least in part on a pre-trained reinforcement learning network that has undergone prior training to address resolution of multiple sources within the sub-Rayleigh region in a low photon regime.
6 . The apparatus of claim 4 , wherein at least one of the first and second commands are generated based at least in part on Fisher information of the photons traveling along at least one of the third and fourth pathways.
7 . A method, comprising: separating light traveling in a single pathway into a first pathway and a second pathway, the light including photons; modulating the photons traveling along the first pathway; combining a first subset of photons traveling along the first pathway with a first subset of photons traveling along the second pathway and directing these combined photons along a third pathway; combining a second subset of photons traveling along the first pathway with a second subset of photons traveling along the second pathway and directing these combined photons along a fourth pathway; detecting photons traveling along the third pathway and outputting a first signal representative of the distribution of photons traveling along the third pathway; detecting photons traveling along the fourth pathway and outputting a second signal representative of the distribution of photons traveling along the fourth pathway; receiving the first signal representative of the distribution of photons traveling along the third pathway; receiving the second signal representative of the distribution of photons traveling along the fourth pathway; generating a first command based on the first and second signals; and modifying said modulating the photons traveling along the first pathway based on the first command.
8 . The method of claim 7 , wherein said generating a first command for the first spatial light modulator is based at least in part on a pre-trained reinforcement learning network that has undergone prior training to address resolution of multiple sources within the sub-Rayleigh region in a low photon regime.
9 . The method of claim 7 , wherein said generating a first command for the first spatial light modulator is based at least in part on Fisher information of the photons traveling along at least one of the third and fourth pathways.
10 . The method of claim 7 , further comprising: modulating the photons traveling along the second pathway; generating a second command based on the first and second signals; and modifying said modulating the photons traveling along the second pathway based on the second command.
11 . The method of claim 10 , wherein said generating a second command is based at least in part on a pre-trained reinforcement learning network that has undergone prior training to address resolution of multiple sources within the sub-Rayleigh region in a low photon regime.
12 . The method of claim 10 , wherein said generating a second command is based at least in part on Fisher information of the photons traveling along at least one of the third and fourth pathways.
13 . An apparatus, comprising: means for separating photons traveling in a single pathway into first and second pathways, modulating light traveling in at least one of the first and second pathways, and combining the first and second pathways into third and fourth pathways; a first photon detector configured to receive photons traveling along the third pathway and output a first signal representative of the distribution of photons traveling along the third pathway; a second photon detector configured to receive photons traveling along the fourth pathway and output a second signal representative of the distribution of photons traveling along the fourth pathway; and one or more processors configured to receive the first signal representative of the distribution of photons traveling along the third pathway, receive the second signal representative of the distribution of photons traveling along the fourth pathway, and generate a first command for the first spatial light modulator based on the first and second signals; and wherein said means for separating photons traveling in a single pathway into first and second pathways, modulating light traveling in at least one of the first and second pathways, and combining the first and second pathways into third and fourth pathways is modified based on the first command.
14 . The apparatus of claim 13 , wherein said means includes a light separator configured to separate photons traveling in the single pathway into the first pathway and the second pathway; a first spatial light modulator configured to modulate photons traveling along the first pathway; and a light combiner configured to combine the first subset of photons traveling along the first pathway after being modulated by the first spatial light modulator with the first subset of photons traveling along the second pathway and direct these combined photons along the third pathway, and combine the second subset of photons traveling along the first pathway after being modulated by the first spatial light modulator with the second subset of photons traveling along the second pathway and direct these combined photons along the fourth pathway.
15 . The apparatus of claim 14 , wherein the first command is generated based at least in part on a pre-trained reinforcement learning network that has undergone prior training to address resolution of multiple sources within the sub-Rayleigh region in a low photon regime.
16 . The apparatus of claim 14 , wherein the first command is generated based at least in part on Fisher information of the photons traveling along at least one of the third and fourth pathways.
17 . The apparatus of claim 14 , wherein said means includes a second spatial light modulator configured to modulate photons traveling along the second pathway; wherein the light combiner is configured to combine the first subset of photons traveling along the first pathway with a first subset of photons traveling along the second pathway after being modulated by the second spatial light modulator and direct these combined photons along the third pathway; wherein the light combiner is configured to combine the second subset of photons traveling along the first pathway with a second subset of photons traveling along the second pathway after being modulated by the second spatial light modulator and direct these combined photons along the fourth pathway; and wherein the one or more processors are configured to generate a second command for the second spatial light modulator based on the first and second signals.
18 . The apparatus of claim 17 , wherein at least one of the first and second commands are generated based at least in part on a pre-trained reinforcement learning network that has undergone prior training to address resolution of multiple sources within the sub-Rayleigh region in a low photon regime.
19 . The apparatus of claim 17 , wherein at least one of the first and second commands are generated based at least in part on Fisher information of the photons traveling along at least one of the third and fourth pathways.

Description

This application claims the benefit of U.S. Provisional Application No. 63/383,691, filed 14 Nov. 2022, the entirety of which is hereby incorporated herein by reference. GOVERNMENT RIGHTS This invention was made with government support under HR00112090124 awarded by the Defense Advanced Research Projects Agency (DARPA). The government has certain rights in the invention. FIELD Embodiments of this disclosure relate generally to object detection in low photon environments, for example, detection of space objects. BACKGROUND The ability for imaging systems to differentiate between two or more objects has received increased attention for, for example, tracking orbital debris and detecting asteroids that could pose a collision risk with Earth. The field of tracking these types of objects is commonly referred to as Space Situational Awareness (SSA) or Space Domain Awareness (SDA). However, it was realized by the inventors of the current disclosure that problems exist with current imaging system and that improvements are needed. For example, Current imaging systems (for example, AO systems) used for SSA/SDA can include Shack Hartman Wavefront Sensors (SHWFS) and deformable mirrors (DM) to correct for atmospheric turbulence. However, these systems do not work in the shot noise limited regime. It was also realized by the inventors of the present disclosure that the algorithms and hardware of existing systems are optimized for classical light intensity as opposed to information contained in the photons themselves. It was realized by the inventors of the current disclosure that improvements in object detection are needed. For example, it was realized that improvements in object detection in low photon environments are needed. Certain preferred features of the present disclosure address these and other needs and provide other important advantages. SUMMARY Embodiments of the present disclosure provide an improved adaptive information mining interferometry apparatuses and methods. Embodiments of the present disclosure include a quantum-inspired imaging system which provides dramatically improved resolution (10×) for objects within a sub-Rayleigh region. Embodiments operate in the shot-noise limited regime of low photon number (i.e., low signal to noise ratio (SNR)) where the quantum advantage can exist over existing classical imaging systems. The measurement approach of example embodiments extracts optimal information from every single photon entering, for example, a telescope aperture as opposed to conventional direct imaging which only measures intensity in a fixed Fourier basis. Specific uses for various embodiments include space debris detection and characterization as well as interstellar/solar system object characterization. Embodiments of the present disclosure do not require assumptions of equal brightness, known number of sources or known centroid. Embodiments adaptively update the modes for measurement for every approximate 100 photons based on the measurement results of previous approximate 100 photons. In some embodiments, the modes are determined using reinforcement learning, while in other embodiments the modes are determined using information metrics, such as Fisher information metrics. The initialization for the first approximate 100 photons can be performed in a fixed Zernike mode basis, which can help exploit the circular aperture symmetry. Optimal measurement modes can reduce the uncertainty in estimating the scene parameters and can be determined by iteratively solving for modes that optimize the chosen metrics. Example metrics include but are not limited to reinforcement learning rewards, the Fisher information, and the image sharpness. In some embodiments the optimal measurement modes are decided by iteratively using a pre-trained reinforcement learning network, and in some embodiments the optimal measurement modes are decided by iteratively solving for the eigenmodes of the quantum Fisher information matrix. Embodiments of the present disclosure utilize an adaptive architecture which performs high efficiency, high speed real-time modal modulation at the single turbulent photon level. Embodiments of the present disclosure provide an improved adaptive information mining interferometry apparatuses and methods. Embodiments provide improved adaptive information mining interferometry utilizing pre-trained reinforcement learning networks. Further example embodiments provide improved adaptive information mining Fisher interferometry apparatuses and methods. Embodiments of the present disclosure provide apparatuses and systems for imaging that overcomes the Rayleigh limit. Further embodiments provide apparatuses and systems for imaging at low photon numbers. Still further embodiments provide apparatuses and systems for imaging faint sources, for example, dim objects. Additional embodiments provide apparatuses and systems for adaptive imaging. Yet additional embodiments provide apparatuses and systems for it