Experimental Demonstration of Conditional Weak Measurement and Its Use on Incompatible Observables

2021 ◽  
Author(s):  
Thomas J. Bailey ◽  
Raphael A. Abrahao ◽  
Jeff S. Lundeen
2006 ◽  
Vol 73 (2) ◽  
Author(s):  
Qin Wang ◽  
Fang-Wen Sun ◽  
Yong-Sheng Zhang ◽  
Jian-Li ◽  
Yun-Feng Huang ◽  
...  

Quantum ◽  
2021 ◽  
Vol 5 ◽  
pp. 599
Author(s):  
Aldo C. Martinez-Becerril ◽  
Gabriel Bussières ◽  
Davor Curic ◽  
Lambert Giner ◽  
Raphael A. Abrahao ◽  
...  

Incompatible observables underlie pillars of quantum physics such as contextuality and entanglement. The Heisenberg uncertainty principle is a fundamental limitation on the measurement of the product of incompatible observables, a 'joint' measurement. However, recently a method using weak measurement has experimentally demonstrated joint measurement. This method [Lundeen, J. S., and Bamber, C. Phys. Rev. Lett. 108, 070402, 2012] delivers the standard expectation value of the product of observables, even if they are incompatible. A drawback of this method is that it requires coupling each observable to a distinct degree of freedom (DOF), i.e., a disjoint Hilbert space. Typically, this 'read-out' system is an unused internal DOF of the measured particle. Unfortunately, one quickly runs out of internal DOFs, which limits the number of observables and types of measurements one can make. To address this limitation, we propose and experimentally demonstrate a technique to perform a joint weak-measurement of two incompatible observables using only one DOF as a read-out system. We apply our scheme to directly measure the density matrix of photon polarization states.


2008 ◽  
Vol 128 (4) ◽  
pp. 677-682 ◽  
Author(s):  
Taku Takaku ◽  
Noriyuki Iwamuro ◽  
Yoshiyuki Uchida ◽  
Ryuichi Shimada

Author(s):  
Suresha .M ◽  
. Sandeep

Local features are of great importance in computer vision. It performs feature detection and feature matching are two important tasks. In this paper concentrates on the problem of recognition of birds using local features. Investigation summarizes the local features SURF, FAST and HARRIS against blurred and illumination images. FAST and Harris corner algorithm have given less accuracy for blurred images. The SURF algorithm gives best result for blurred image because its identify strongest local features and time complexity is less and experimental demonstration shows that SURF algorithm is robust for blurred images and the FAST algorithms is suitable for images with illumination.


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