The prevailing cosmological constant and cold dark matter (ΛCDM) cosmic concordance model accounts for the radial expansion of the universe after the Big Bang. The model appears to be authoritative because it is base...The prevailing cosmological constant and cold dark matter (ΛCDM) cosmic concordance model accounts for the radial expansion of the universe after the Big Bang. The model appears to be authoritative because it is based on the Einstein gravitational field equation. However, a thorough scrutiny of the underlying theory calls into question the suitability of the field equation, which states that the Einstein tensor <strong><em>G</em></strong><span style="white-space:nowrap;"><sub><em><span style="white-space:nowrap;">μv</span></em></sub></span> is a constant multiple of the stress-energy tensor <em> <strong>T</strong></em><span style="white-space:nowrap;"><sub><em><span style="white-space:nowrap;">μv</span></em></sub> </span>when they both are evaluated at the same 4D space-time point: <strong style="white-space:normal;"><em>G</em></strong><sub><em><span style="white-space:nowrap;">μv</span> </em></sub>= 8<span style="white-space:nowrap;">π</span>k<strong style="white-space:normal;"><em>T</em></strong><sub><em><span style="white-space:nowrap;">μv</span></em></sub>, where k is the gravitational constant. Notwithstanding its venerable provenance, this equation is incorrect unless the cosmic pressure is <em>p</em> = 0;but then all that remains of the Einstein equation is the Poisson equation which models the Newtonian gravity field. This shortcoming is not resolved by adding the cosmological constant term to the field equation, <strong style="white-space:normal;"><em>G</em></strong><sub><em><span style="white-space:nowrap;">μv</span> </em></sub>+<span style="white-space:nowrap;">Λ</span> <strong style="white-space:normal;"><em>g</em></strong><sub><em><span style="white-space:nowrap;">μv</span> =<span style="white-space:normal;">8<span style="white-space:nowrap;">π</span></span><span style="white-space:normal;">k</span><strong style="white-space:normal;"><em>T</em></strong><sub style="white-space:normal;"><em><span style="white-space:nowrap;">μv</span></em></sub><span style="white-space:normal;">,</span></em></sub> as in the ΛCDM model, because then <em>p</em> = Λ, so the pressure is a universal constant, not a variable. Numerous studies support the concept of a linearly expanding universe in which gravitational forces and accelerations are negligible because the baryonic mass density of the universe is far below its critical density. We show that such a coasting universe model agrees with SNe Ia luminosity vs. redshift distances just as well or even better than the ΛCDM model, and that it does so without having to invoke dark matter or dark energy. Occam’s razor favors a coasting universe over the ΛCDM model.展开更多
To reveal the fundamental aspects hidden behind a variety of transient events in mechanics,physics,and biology,the highly desired ability to acquire three-dimensional(3D)images with ultrafast temporal resolution has b...To reveal the fundamental aspects hidden behind a variety of transient events in mechanics,physics,and biology,the highly desired ability to acquire three-dimensional(3D)images with ultrafast temporal resolution has been long sought.As one of the most commonly employed 3D sensing techniques,fringe projection profilometry(FPP)reconstructs the depth of a scene from stereo images taken with sequentially structured illuminations.However,the imaging speed of current FPP methods is generally capped at several kHz,which is limited by the projector-camera hardware and the number of fringe patterns required for phase retrieval and unwrapping.Here we report a novel learning-based ultrafast 3D imaging technique,termed single-shot super-resolved FPP(SSSR-FPP),which enables ultrafast 3D imaging at 100,000 Hz.SSSR-FPP uses only one pair of low signal-to-noise ratio(SNR),low-resolution,and pixelated fringe patterns as input,while the high-resolution unwrapped phase and fringe orders can be deciphered with a specific trained deep neural network.Our approach exploits the significant speed gain achieved by reducing the imaging window of conventional high-speed cameras,while"regenerating"the lost spatial resolution through deep learning.To demonstrate the high spatio-temporal resolution of SSSR-FPP,we present 3D videography of several transient scenes,including rotating turbofan blades,exploding building blocks,and the reciprocating motion of a steam engine,etc.,which were previously challenging or even impossible to capture with conventional methods.Experimental results establish SSSR-FPP as a significant step forward in the field of 3D optical sensing,offering new insights into a broad spectrum of dynamic processes across various scientific disciplines.展开更多
文摘The prevailing cosmological constant and cold dark matter (ΛCDM) cosmic concordance model accounts for the radial expansion of the universe after the Big Bang. The model appears to be authoritative because it is based on the Einstein gravitational field equation. However, a thorough scrutiny of the underlying theory calls into question the suitability of the field equation, which states that the Einstein tensor <strong><em>G</em></strong><span style="white-space:nowrap;"><sub><em><span style="white-space:nowrap;">μv</span></em></sub></span> is a constant multiple of the stress-energy tensor <em> <strong>T</strong></em><span style="white-space:nowrap;"><sub><em><span style="white-space:nowrap;">μv</span></em></sub> </span>when they both are evaluated at the same 4D space-time point: <strong style="white-space:normal;"><em>G</em></strong><sub><em><span style="white-space:nowrap;">μv</span> </em></sub>= 8<span style="white-space:nowrap;">π</span>k<strong style="white-space:normal;"><em>T</em></strong><sub><em><span style="white-space:nowrap;">μv</span></em></sub>, where k is the gravitational constant. Notwithstanding its venerable provenance, this equation is incorrect unless the cosmic pressure is <em>p</em> = 0;but then all that remains of the Einstein equation is the Poisson equation which models the Newtonian gravity field. This shortcoming is not resolved by adding the cosmological constant term to the field equation, <strong style="white-space:normal;"><em>G</em></strong><sub><em><span style="white-space:nowrap;">μv</span> </em></sub>+<span style="white-space:nowrap;">Λ</span> <strong style="white-space:normal;"><em>g</em></strong><sub><em><span style="white-space:nowrap;">μv</span> =<span style="white-space:normal;">8<span style="white-space:nowrap;">π</span></span><span style="white-space:normal;">k</span><strong style="white-space:normal;"><em>T</em></strong><sub style="white-space:normal;"><em><span style="white-space:nowrap;">μv</span></em></sub><span style="white-space:normal;">,</span></em></sub> as in the ΛCDM model, because then <em>p</em> = Λ, so the pressure is a universal constant, not a variable. Numerous studies support the concept of a linearly expanding universe in which gravitational forces and accelerations are negligible because the baryonic mass density of the universe is far below its critical density. We show that such a coasting universe model agrees with SNe Ia luminosity vs. redshift distances just as well or even better than the ΛCDM model, and that it does so without having to invoke dark matter or dark energy. Occam’s razor favors a coasting universe over the ΛCDM model.
基金supported by National Key Research and Development Program of China(2022YFB2804603,2022YFA1205002,2024YFE0101300)National Natural Science Foundation of China(U21B2033,62075096,62105151,62175109,62227818,62361136588)+4 种基金Leading Technology of Jiangsu Basic Research Plan(BK20192003)"333 Engineering"Research Project of Jiangsu Province(BRA2016407)Jiangsu Provincial"One belt and one road"innovation cooperation project(BZ2020007)Fundamental Research Funds for the Central Universities(30921011208,30919011222,30920032101)Open Research Fund of Jiangsu Key Laboratory of Spectral Imaging&Intelligent Sense(USGP202105,JSGP202201).
文摘To reveal the fundamental aspects hidden behind a variety of transient events in mechanics,physics,and biology,the highly desired ability to acquire three-dimensional(3D)images with ultrafast temporal resolution has been long sought.As one of the most commonly employed 3D sensing techniques,fringe projection profilometry(FPP)reconstructs the depth of a scene from stereo images taken with sequentially structured illuminations.However,the imaging speed of current FPP methods is generally capped at several kHz,which is limited by the projector-camera hardware and the number of fringe patterns required for phase retrieval and unwrapping.Here we report a novel learning-based ultrafast 3D imaging technique,termed single-shot super-resolved FPP(SSSR-FPP),which enables ultrafast 3D imaging at 100,000 Hz.SSSR-FPP uses only one pair of low signal-to-noise ratio(SNR),low-resolution,and pixelated fringe patterns as input,while the high-resolution unwrapped phase and fringe orders can be deciphered with a specific trained deep neural network.Our approach exploits the significant speed gain achieved by reducing the imaging window of conventional high-speed cameras,while"regenerating"the lost spatial resolution through deep learning.To demonstrate the high spatio-temporal resolution of SSSR-FPP,we present 3D videography of several transient scenes,including rotating turbofan blades,exploding building blocks,and the reciprocating motion of a steam engine,etc.,which were previously challenging or even impossible to capture with conventional methods.Experimental results establish SSSR-FPP as a significant step forward in the field of 3D optical sensing,offering new insights into a broad spectrum of dynamic processes across various scientific disciplines.
