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Dekker pursued a Master of Science in Applied Physics at the University of Twente and obtained another master's degree in Technology Design from the Eindhoven University of Technology in 2000. He completed his PhD in medicine in 2003, and undertook a residency in Radiotherapy Medical Physics at Maastro Clinic from 2003 to 2005.
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Andre_Dekker
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Dekker served as a Radiotherapy Medical Physics Resident at Maastro Clinic from 2003 to 2005, later assuming the role of Medical Physics Head and Member of the Management Team until 2010. He was the Head of Information & Services, Member of the Management Team at Maastro Clinic from 2010 to 2015, and Scientific Director at Maastro Innovations from 2010 to 2018. He has served on advisory boards of organizations, including the European Society for Radiotherapy & Oncology, Hanarth Fund, MD Anderson, Novo Nordisk Foundation, Luxemburg National Research Fund and Peter Munk Cardiac Centre. He serves as the Head of Clinical Data Science at UM's Medical Center, while concurrently holding the positions of Full Professor of Clinical Data Science, Chief Scientific Officer at Medical Data Works, and Medical Physicist at Maastro Clinic.
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Andre_Dekker
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Dekker co-led the ProTRAIT project, focused on creating a unified database for evaluating clinical data from patients undergoing proton treatment, which was featured in Dutch media outlets. He emphasized AI's potential to enhance decision-making in radiation oncology by facilitating shared decision-making between physicians and patients in an Imaging Technology News piece, and discussed ethical AI solutions benefiting patients through academic, healthcare, and technology partnerships in an interview with Innovation Origins. He was invited to the American Society for Radiation Oncology to share his vision on the future of AI in the radiation oncology field. In addition, he addressed researchers from NITC and doctors from MVRCCRI, highlighting the significant potential of applying machine learning methods for early cancer detection and treatment.
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Andre_Dekker
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Dekker has focused his research on constructing global FAIR data-sharing infrastructures, employing AI to develop outcome prediction models from that data, and utilizing those models to enhance patient outcomes.
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Andre_Dekker
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Dekker, alongside Pieter Kubben and Michel Dumontier, co-authored Fundamentals of Clinical Data Science which delved into topics such as personalized medicine offering insights in a healthcare-optimized style without requiring mathematical or coding expertise. His research on the increasing significance of clinical decision-support systems in radiation oncology discussed the multistage process involved in developing robust prediction models, emphasizing the critical role of predictive models in optimizing treatment outcomes. In a collaborative study, he proposed a system for characterizing and classifying oligometastatic disease.
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Andre_Dekker
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Dekker explored radiomics, particularly in non-small-cell lung cancer imaging, addressing the challenges of extracting quantitative features from medical images to develop diagnostic, prognostic, or predictive models integrating biological and medical data. Collaborating with a team of researchers, he conducted a radiomic analysis of 1,019 patients with lung or head-and-neck cancer using computed tomography (CT) imaging data, identifying prognostic radiomic features that showed significant power in independent datasets of the cancer patients. Additionally, in describing the concept and potential of radiomics in cancer research, he and his collaborators proposed guidelines to enhance the scientific integrity and clinical relevance of radiomics investigations. Furthermore, his systematic review assessed the reproducibility of radiomic features used in cancer imaging for clinical decision making, noting that feature stability is influenced by factors such as image acquisition settings, reconstruction algorithms, and preprocessing methods.
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Andre_Dekker
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Dekker introduced a method for analyzing plethysmographic signals to identify heart rate variability parameters linked to respiration rate, leading to an improved pulse oximeter functionality for noninvasive respiration rate monitoring. His development of an apparatus resulted in an approved patent for monitoring secondary physiological processes by analyzing optical signal variations. He then presented a method utilizing photoplethysmography to gather physiological parameters, involving filtering and analyzing pleth signals to identify components of interest for determining respiratory parameters.
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Andre_Dekker
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Tsevi Mazeh, born in 1946 in Jerusalem is an Israeli astrophysicist, professor of astrophysics at Tel Aviv University.
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Tsevi_Mazeh
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He serves as president of the Institute of Astronomy at Tel Aviv University. He works particularly in the field of exoplanet research. He is known, among other things, for being a co-discoverer of HD 114762 b, the first substellar mass object (the status of a planet or brown dwarf remains uncertain) known outside the Solar System.
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Tsevi_Mazeh
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This article about an Israeli scientist is a stub. You can help Wikipedia by expanding it.
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Tsevi_Mazeh
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IEEE Electron Device Letters is a peer-reviewed scientific journal published monthly by the IEEE. It was founded in 1980 by IEEE Electron Devices Society. The journal covers the advances in electron and ion integrated circuit devices. Its editor-in-chief is Sayeef Salahuddin (University of California, Berkeley).
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IEEE_Electron_Device_Letters
https://en.wikipedia.org/wiki/IEEE_Electron_Device_Letters
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According to the Journal Citation Reports, the journal has a 2022 impact factor of 4.9.
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IEEE_Electron_Device_Letters
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This article about an engineering journal is a stub. You can help Wikipedia by expanding it.
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IEEE_Electron_Device_Letters
https://en.wikipedia.org/wiki/IEEE_Electron_Device_Letters
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See tips for writing articles about academic journals. Further suggestions might be found on the article's talk page.
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IEEE_Electron_Device_Letters
https://en.wikipedia.org/wiki/IEEE_Electron_Device_Letters
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This article about a physics journal is a stub. You can help Wikipedia by expanding it.
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IEEE_Electron_Device_Letters
https://en.wikipedia.org/wiki/IEEE_Electron_Device_Letters
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See tips for writing articles about academic journals. Further suggestions might be found on the article's talk page.
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IEEE_Electron_Device_Letters
https://en.wikipedia.org/wiki/IEEE_Electron_Device_Letters
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IEEE Transactions on Nanotechnology is a peer-reviewed scientific journal published by IEEE. Sponsored by IEEE Nanotechnology Council, the journal covers physical basis and engineering applications in nanotechnology. Its editor-in-chief is Sorin Coțofană (Delft University of Technology).
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IEEE_Transactions_on_Nanotechnology
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According to the Journal Citation Reports, the journal has a 2022 impact factor of 2.4.
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IEEE_Transactions_on_Nanotechnology
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This article about an engineering journal is a stub. You can help Wikipedia by expanding it.
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IEEE_Transactions_on_Nanotechnology
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See tips for writing articles about academic journals. Further suggestions might be found on the article's talk page.
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IEEE_Transactions_on_Nanotechnology
https://en.wikipedia.org/wiki/IEEE_Transactions_on_Nanotechnology
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This article about a physics journal is a stub. You can help Wikipedia by expanding it.
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IEEE_Transactions_on_Nanotechnology
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See tips for writing articles about academic journals. Further suggestions might be found on the article's talk page.
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IEEE_Transactions_on_Nanotechnology
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In statistical mechanics, the random-subcube model (RSM) is an exactly solvable model that reproduces key properties of hard constraint satisfaction problems (CSPs) and optimization problems, such as geometrical organization of solutions, the effects of frozen variables, and the limitations of various algorithms like decimation schemes.
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Random_subcube_model
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The RSM consists of a set of N binary variables, where solutions are defined as points in a hypercube. The model introduces clusters, which are random subcubes of the hypercube, representing groups of solutions sharing specific characteristics. As the density of constraints increases, the solution space undergoes a series of phase transitions similar to those observed in CSPs like random k-satisfiability (k-SAT) and random k-coloring (k-COL). These transitions include clustering, condensation, and ultimately the unsatisfiable phase where no solutions exist.
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Random_subcube_model
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The RSM is equivalent to these real CSPs in the limit of large constraint size. Notably, it reproduces the cluster size distribution and freezing properties of k-SAT and k-COL in the large-k limit. This is similar to how the random energy model is the large-p limit of the p-spin glass model.
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Random_subcube_model
https://en.wikipedia.org/wiki/Random_subcube_model
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There are N particles. Each particle can be in one of two states − − 1 , + 1 .
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Random_subcube_model
https://en.wikipedia.org/wiki/Random_subcube_model
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The state space { − − 1 , + 1 } N has 2 N states. Not all are available. Only those satisfying the constraints are allowed.
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Random_subcube_model
https://en.wikipedia.org/wiki/Random_subcube_model
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Each constraint is a subset A i of the state space. Each A i is a "subcube", structured like A i = ∏ ∏ j ∈ ∈ 1 : N A i j where each A i j can be one of { − − 1 } , { + 1 } , { − − 1 , + 1 } .
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Random_subcube_model
https://en.wikipedia.org/wiki/Random_subcube_model
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The available states is the union of these subsets: S = ∪ ∪ i A i
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Random_subcube_model
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Each random subcube model is defined by two parameters α α , p ∈ ∈ ( 0 , 1 ) .
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Random_subcube_model
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To generate a random subcube A i , sample its components A i j IID according to P r ( A i j = { − − 1 } ) = p / 2 P r ( A i j = { + 1 } ) = p / 2 P r ( A i j = { − − 1 , + 1 } ) = 1 − − p
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Random_subcube_model
https://en.wikipedia.org/wiki/Random_subcube_model
102,130
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Now sample 2 ( 1 − − α α ) N random subcubes, and union them together.
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Random_subcube_model
https://en.wikipedia.org/wiki/Random_subcube_model
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The entropy density of the r -th cluster in bits is s r := 1 N log 2 ⁡ ⁡ | A r |
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Random_subcube_model
https://en.wikipedia.org/wiki/Random_subcube_model
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The entropy density of the system in bits is s := 1 N log 2 ⁡ ⁡ | ∪ ∪ r A r |
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Random_subcube_model
https://en.wikipedia.org/wiki/Random_subcube_model
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Let n ( s ) be the number of clusters with entropy density s , then it is binomially distributed, thus E [ n ( s ) ] = 2 ( 1 − − α α ) N P → → 2 N Σ Σ ( s ) + o ( N ) V a r [ n ( s ) ] = 2 ( 1 − − α α ) N P ( 1 − − P ) V a r [ n ( s ) ] E [ n ( s ) ] 2 → → 2 − − N Σ Σ ( s ) where P := ( N s N ) p ( 1 − − s ) N ( 1 − − p ) s N , Σ Σ ( s ) := 1 − − α α − − D K L ( s ‖ ‖ 1 − − p ) D K L ( s ‖ ‖ 1 − − p ) := s log 2 ⁡ ⁡ s 1 − − p + ( 1 − − s ) log 2 ⁡ ⁡ 1 − − s p
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Random_subcube_model
https://en.wikipedia.org/wiki/Random_subcube_model
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By the Chebyshev inequality, if Σ Σ > 0 , then n ( s ) concentrates to its mean value. Otherwise, since E [ n ( s ) ] → → 0 , n ( s ) also concentrates to 0 by the Markov inequality.
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Random_subcube_model
https://en.wikipedia.org/wiki/Random_subcube_model
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Thus, n ( s ) → → { 2 N Σ Σ ( s ) + o ( N ) if Σ Σ ( s ) > 0 0 if Σ Σ ( s ) < 0 almost surely as N → → ∞ ∞ .
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Random_subcube_model
https://en.wikipedia.org/wiki/Random_subcube_model
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When Σ Σ = 0 exactly, the two forces exactly balance each other out, and n ( s ) does not collapse, but instead converges in distribution to the Poisson distribution P o i s s o n ( 1 ) by the law of small numbers.
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Random_subcube_model
https://en.wikipedia.org/wiki/Random_subcube_model
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For each state, the number of clusters it is in is also binomially distributed, with expectation 2 ( 1 − − α α ) N ( 1 − − p / 2 ) N = 2 N ( log 2 ⁡ ⁡ ( 2 − − p ) − − α α )
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Random_subcube_model
https://en.wikipedia.org/wiki/Random_subcube_model
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So if α α < log 2 ⁡ ⁡ ( 2 − − p ) , then it concentrates to 2 N ( log 2 ⁡ ⁡ ( 2 − − p ) − − α α ) , and so each state is in an exponential number of clusters.
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Random_subcube_model
https://en.wikipedia.org/wiki/Random_subcube_model
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Indeed, in that case, the probability that all states are allowed is [ 1 − − [ 1 − − ( 1 − − p / 2 ) N ] 2 ( 1 − − α α ) N ] 2 N ∼ ∼ e − − e − − 2 N ( log 2 ⁡ ⁡ ( 2 − − p ) − − α α ) + N ln ⁡ ⁡ 2 → → 1
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Random_subcube_model
https://en.wikipedia.org/wiki/Random_subcube_model
102,140
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Thus almost surely, all states are allowed, and the entropy density is 1 bit per particle.
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Random_subcube_model
https://en.wikipedia.org/wiki/Random_subcube_model
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If α α > α α d := log 2 ⁡ ⁡ ( 2 − − p ) , then it concentrates to zero exponentially, and so most states are not in any cluster. Those that do are exponentially unlikely to be in more than one. Thus, we find that almost all states are in zero clusters, and of those in at least one cluster, almost all are in just one cluster. The state space is thus roughly speaking the disjoint union of the clusters.
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Random_subcube_model
https://en.wikipedia.org/wiki/Random_subcube_model
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Almost surely, there are n ( s ) = 2 N Σ Σ ( s ) clusters of size 2 N s , therefore, the state space is dominated by clusters with optimal entropy density s ∗ ∗ = arg ⁡ ⁡ max s ( Σ Σ ( s ) + s ) .
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Random_subcube_model
https://en.wikipedia.org/wiki/Random_subcube_model
102,143
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Thus, in the clustered phase, the state space is almost entirely partitioned among 2 N Σ Σ ( s ∗ ∗ ) clusters of size 2 N s ∗ ∗ each. Roughly, the state space looks like exponentially many equally-sized clusters.
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Random_subcube_model
https://en.wikipedia.org/wiki/Random_subcube_model
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Another phase transition occurs when Σ Σ ( s ∗ ∗ ) = 0 , that is, α α = α α c := p ( 2 − − p ) + log 2 ⁡ ⁡ ( 2 − − p ) When α α > α α c , the optimal entropy density becomes unreachable, as there almost surely exists zero clusters with entropy density s ∗ ∗ . Instead, the state space is dominated by clusters with entropy close to s c , the larger solution to Σ Σ ( s c ) = 0 .
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Random_subcube_model
https://en.wikipedia.org/wiki/Random_subcube_model
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Near s c , the contribution of clusters with entropy density s = s c − − δ δ to the total state space is 2 N s ⏟ ⏟ size of clusters × × 2 N Σ Σ ( s ) ⏟ ⏟ number of clusters = 2 N ( s + Σ Σ ( s ) ) = 2 N ( s c − − δ δ − − Σ Σ ′ ( s c ) δ δ ) At large N , the possible entropy densities are s c , s c − − 1 / N , s c − − 2 / N , … … . The contribution of each is 2 N s c , 2 N s c 2 − − ( 1 + Σ Σ ′ ( s c ) ) , 2 N s c 2 − − 2 ( 1 + Σ Σ ′ ( s c ) ) , … …
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Random_subcube_model
https://en.wikipedia.org/wiki/Random_subcube_model
102,146
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We can tabulate them as follows:
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Random_subcube_model
https://en.wikipedia.org/wiki/Random_subcube_model
102,147
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Thus, we see that for any ϵ ϵ > 0 , at N → → ∞ ∞ limit, over 1 − − ϵ ϵ of the total state space is covered by only a finite number of clusters. The state space looks partitioned into clusters with exponentially decaying sizes. This is the condensation phase.
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Random_subcube_model
https://en.wikipedia.org/wiki/Random_subcube_model
102,148
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When α α > 1 , the number of clusters is zero, so there are no states.
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Random_subcube_model
https://en.wikipedia.org/wiki/Random_subcube_model
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The RSM can be extended to include energy landscapes, allowing for the study of glassy behavior, temperature chaos, and the dynamic transition.
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Random_subcube_model
https://en.wikipedia.org/wiki/Random_subcube_model
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Emilio Méndez Pérez (born 22 May 1949) is a Spanish physicist. His research has focused on the study of the optical and electronic properties of semiconductor nanomaterials. Particularly notable are his discoveries on the effects of an electric field on the electronic properties of quantum wells and superlattices, especially the experimental demonstration of the so-called " Stark effect " and the so-called " Wannier–Stark ladder ".
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Emilio_Méndez_Pérez
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In 1998, he was awarded the Prince of Asturias Awards for Technical and Scientific Research along Pedro Miguel Echenique Landiríbar.
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Emilio_Méndez_Pérez
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This article about a physicist is a stub. You can help Wikipedia by expanding it.
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Emilio_Méndez_Pérez
https://en.wikipedia.org/wiki/Emilio_Méndez_Pérez
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Nonmetallic material, or in nontechnical terms a nonmetal, refers to materials which are not metals. Depending upon context it is used in slightly different ways. In everyday life it would be a generic term for those materials such as plastics, wood or ceramics which are not typical metals such as the iron alloys used in bridges. In some areas of chemistry, particularly the periodic table, it is used for just those chemical elements which are not metallic at standard temperature and pressure conditions. It is also sometimes used to describe broad classes of dopant atoms in materials. In general usage in science, it refers to materials which do not have electrons that can readily move around, more technically there are no available states at the Fermi energy, the equilibrium energy of electrons. For historical reasons there is a very different definition of metals in astronomy, with just hydrogen and helium as nonmetals. The term may also be used as a negative of the materials of interest such as in metallurgy or metalworking.
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Nonmetallic_material
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Variations in the environment, particularly temperature and pressure can change a nonmetal into a metal, and vica versa; this is always associated with some major change in the structure, a phase transition. Other external stimuli such as electric fields can also lead to a local nonmetal, for instance in certain semiconductor devices. There are also many physical phenomena which are only found in nonmetals such as piezoelectricity or flexoelectricity.
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Nonmetallic_material
https://en.wikipedia.org/wiki/Nonmetallic_material
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The original approach to conduction and nonmetals was a band-structure with delocalized electrons (i.e. spread out in space). In this approach a nonmetal has a gap in the energy levels of the electrons at the Fermi level. In contrast, a metal would have at least one partially occupied band at the Fermi level; in a semiconductor or insulator there are no delocalized states at the Fermi level, see for instance Ashcroft and Mermin. These definitions are equivalent to stating that metals conduct electricity at absolute zero, as suggested by Nevill Francis Mott, and the equivalent definition at other temperatures is also commonly used as in textbooks such as Chemistry of the Non-Metals by Ralf Steudel and work on metal–insulator transitions.
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Nonmetallic_material
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In early work this band structure interpretation was based upon a single-electron approach with the Fermi level in the band gap as illustrated in the Figure, not including a complete picture of the many-body problem where both exchange and correlation terms can matter, as well as relativistic effects such as spin-orbit coupling. A key addition by Mott and Rudolf Peierls was that these could not be ignored. For instance, nickel oxide would be a metal if a single-electron approach was used, but in fact has quite a large band gap. As of 2024 it is more common to use an approach based upon density functional theory where the many-body terms are included. Rather than single electrons, the filling involves quasiparticles called orbitals, which are the single-particle like solutions for a system with hundreds to thousands of electrons. Although accurate calculations remain a challenge, reasonable results are now available in many cases.
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Nonmetallic_material
https://en.wikipedia.org/wiki/Nonmetallic_material
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It is also common to nuance somewhat the early definitions of Alan Herries Wilson and Mott. As discussed by both the chemist Peter Edwards and colleagues, as well as Fumiko Yonezawa, it is also important in practice to consider the temperatures at which both metals and nonmetals are used. Yonezawa provides a general definition:
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Nonmetallic_material
https://en.wikipedia.org/wiki/Nonmetallic_material
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Band structure definitions of metallicity are the most widely used, and apply both to single elements such as insulating boron as well as compounds such as strontium titanate. (There are many compounds which have states at the Fermi level and are metallic, for instance titanium nitride.) There are many experimental methods of checking for nonmetals by measuring the band gap, or by ab-initio quantum mechanical calculations.
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Nonmetallic_material
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An alternative in metallurgy is to consider various malleable alloys such as steel, aluminium alloys and similar as metals, and other materials as nonmetals; fabricating metals is termed metalworking, but there is no corresponding term for nonmetals. A loose definition such as this is often the common useage, but can also be inaccurate. For instance, in this useage plastics are nonmetals, but in fact there are (electrically) conducting polymers which should formally be described as metals. Similar, but slightly more complex, many materials which are (nonmetal) semiconductors behave like metals when they contain a high concentration of dopants, being called degenerate semiconductors. A general introduction to much of this can be found in the 2017 book by Fumiko Yonezawa
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The term nonmetal (chemistry) is also used for those elements which are not metallic in their normal ground state; compounds are sometimes excluded from consideration. Some textbooks use the term nonmetallic elements such as the Chemistry of the Non-Metals by Ralf Steudel, which also uses the general definition in terms of conduction and the Fermi level. The approach based upon the elements is often used in teaching to help students understand the periodic table of elements, although it is a teaching oversimplification. Those elements towards the top right of the periodic table are nonmetals, those towards the center (transition metal and lanthanide) and the left are metallic. An intermediate designation metalloid is used for some elements.
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The term is sometimes also used when describing dopants of specific elements types in compounds, alloys or combinations of materials, using the periodic table classification. For instance metalloids are often used in high-temperature alloys, and nonmetals in precipitation hardening in steels and other alloys. Here the description implicitly includes information on whether the dopants tend to be electron acceptors that lead to covalently bonded compounds rather than metallic bonding or electron acceptors.
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A quite different approach is used in astronomy where the term metallicity is used for all elements heavier than helium, so the only nonmetals are hydrogen and helium. This is a historical anomaly. In 1802, William Hyde Wollaston noted the appearance of a number of dark features in the solar spectrum. In 1814, Joseph von Fraunhofer independently rediscovered the lines and began to systematically study and measure their wavelengths, and they are now called Fraunhofer lines. He mapped over 570 lines, designating the most prominent with the letters A through K and weaker lines with other letters.
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About 45 years later, Gustav Kirchhoff and Robert Bunsen noticed that several Fraunhofer lines coincide with characteristic emission lines identifies in the spectra of heated chemical elements. They inferred that dark lines in the solar spectrum are caused by absorption by chemical elements in the solar atmosphere. Their observations were in the visible range where the strongest lines come from metals such as Na, K, Fe. In the early work on the chemical composition of the sun the only elements that were detected in spectra were hydrogen and various metals, with the term metallic frequently used when describing them. In contemporary usage all the extra elements beyond just hydrogen and helium are termed metallic.
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The astrophysicst Carlos Jaschek, and the stellar astronomer and spectroscopist Mercedes Jaschek, in their book The Classification of Stars, observed that:
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Nonmetallic_material
https://en.wikipedia.org/wiki/Nonmetallic_material
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There are many cases where an element or compound is metallic under certain circumstances, but a nonmetal in others. One example is metallic hydrogen which forms under very high pressures. There are many other cases as discussed by Mott, Inada et al and more recently by Yonezawa.
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There can also be local transitions to a nonmetal, particularly in semiconductor devices. One example is a field-effect transistor where an electric field can lead to a region where there are no electrons at the Fermi energy (depletion zone).
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Nonmetals have a wide range of properties, for instance the nonmetal diamond is the hardest known material, while the nonmetal molybdenum disulfide is a solid lubricants used in space. There are some properties specific to them not having electrons at the Fermi energy. The main ones, for which more details are available in the links are:
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Axial loading is defined as applying a force on a structure directly along a given axis of said structure. In the medical field, the term refers to the application of weight or force along the course of the long axis of the body. The application of an axial load on the human spine can result in vertebral compression fractures, but can also allow effective load-bearing during head-carrying.
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This biophysics -related article is a stub. You can help Wikipedia by expanding it.
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Kompaneyets equation refers to a non-relativistic, Fokker–Planck type, kinetic equation for photon number density with which photons interact with an electron gas via Compton scattering, first derived by Alexander Kompaneyets in 1949 and published in 1957 after declassification. The Kompaneyets equation describes how an initial photon distribution relaxes to the equilibrium Bose–Einstein distribution. Komapaneyets pointed out the radiation field on its own cannot reach the equilibrium distribution since the Maxwells equation are linear but it needs to exchange energy with the electron gas. The Kompaneyets equation has been used as a basis for analysis of the Sunyaev–Zeldovich effect.
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Kompaneyets_equation
https://en.wikipedia.org/wiki/Kompaneyets_equation
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FOKKER
Consider a non-relativistic electron bath that is at an equilibirum temperature T e , i.e., k B T e ≪ ≪ m e c 2 , where m e is the electron mass. Let there be a low-frequency radiation field that satisfies the soft-photon approximation, i.e., ℏ ℏ ω ω ≪ ≪ m e c 2 where ω ω is the photon frequency. Then, the enery exchange in any collision between photon and electron will be small. Assuming homogeneity and isotropy and expanding the collision integral of the Boltzmann equation in terms of small energy exchange, one obtains the Kompaneyets equation.
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Kompaneyets_equation
https://en.wikipedia.org/wiki/Kompaneyets_equation
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The Kompaneyets equation for the photon number density n ( ω ω , t ) reads
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Kompaneyets_equation
https://en.wikipedia.org/wiki/Kompaneyets_equation
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where σ σ T is the total Thomson cross-section and n e is the electron number density; λ λ e = 1 / ( n e σ σ T ) is the Compton range or the scattering mean free path. As evident, the equation can be written in the form of the continuity equation
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https://en.wikipedia.org/wiki/Kompaneyets_equation
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If we introudce the rescalings
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Kompaneyets_equation
https://en.wikipedia.org/wiki/Kompaneyets_equation
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the equation can be brought to the form
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Kompaneyets_equation
https://en.wikipedia.org/wiki/Kompaneyets_equation
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The Kompaneyets equation conserves the photon number
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Kompaneyets_equation
https://en.wikipedia.org/wiki/Kompaneyets_equation
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where V is a sufficiently large volume, since the energy exchange between photon and electron is small. Furthermore, the equilibrium distribution of the Kompaneyets equation is the Bose–Einstein distribution for the photon gas,
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https://en.wikipedia.org/wiki/Kompaneyets_equation
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Zeldovich regularization refers to a regularization method to calculate divergent integrals and divergent series, that was first introduced by Yakov Zeldovich in 1961. Zeldovich was originally interested in calculating the norm of the Gamow wave function which is divergent since there is an outgoing spherical wave. Zeldovich regularization uses a Gaussian type-regularization and is defined, for divergent integrals, by
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Zeldovich_regularization
https://en.wikipedia.org/wiki/Zeldovich_regularization
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and, for divergent series, by
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Zeldovich_regularization
https://en.wikipedia.org/wiki/Zeldovich_regularization
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2007, 2008 Fulbright Scholar
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https://en.wikipedia.org/wiki/Francesca_E._DeMeo
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Francesca DeMeo, or Francesca E. DeMeo (born 1984), is an American doctoral astrophysicist, researcher and speaker specializing in the study of celestial bodies in the Solar System, including more particularly asteroids, comets and moons. She is the creator of the modern system of taxonomic classification of asteroids with Schelte J. Bus. With Benoît Carry, she brought a new vision of the main asteroid belt. She pursued entrepreneurial activities alongside astronomy.
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Francesca DeMeo was born in 1984. At the age of 18, she pursued in-depth studies of physics and planetary sciences at the Massachusetts Institute of Technology in Cambridge until 2006. She obtained two undergraduate degrees : B.S. in Physics and B.S. in Earth, Atmospheric, and Planetary Sciences.
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https://en.wikipedia.org/wiki/Francesca_E._DeMeo
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In 2007, she received a M.S. in Planetary Science including small celestial bodies, asteroids, comets, moons, etc.
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https://en.wikipedia.org/wiki/Francesca_E._DeMeo
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She was awarded a Fulbright Scholarship in 2007 and 2008 to study of planetary sciences within astronomy and astrophysics as a Fulbright Advanced Student, to pursue a PhD at the Paris Observatory in Meudon on the study of small bodies in the Solar System. In 2009, she received an Eiffel excellence scholarship to support her final year of doctoral studies.
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In 2009 she published the Bus-DeMeo asteroid taxonomic classification system. This system has become the reference in the spectral classification of asteroids. She obtained her Ph.D. in Astronomy and Astrophysics in 2010. The dissertation on small solar bodies was titled: The Compositional Variation of Small Bodies across the Solar System. Her thesis co-supervisors are Maria Antonella Barucci and Richard P. Binzel.
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Francesca_E._DeMeo
https://en.wikipedia.org/wiki/Francesca_E._DeMeo
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The taxonomy paper from 2009 is one of the most cited papers in all of asteroid science, 672 times as of June 23, 2024.
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https://en.wikipedia.org/wiki/Francesca_E._DeMeo
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She obtained her Ph.D. in Astronomy and Astrophysics in 2010. The dissertation on small solar bodies was titled: "The Compositional Variation of Small Bodies across the Solar System". Her thesis co-supervisors are Maria Antonella Barucci and Richard P. Binzel, with whom she continued collaborating.
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https://en.wikipedia.org/wiki/Francesca_E._DeMeo
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DeMeo's papers on planetology in Nature and Icarus about Pluto, Triton, Charon, (52872) Okyhroe, (90482) Orcus, (379) Huenna and Small Solar System body.
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https://en.wikipedia.org/wiki/Francesca_E._DeMeo
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In 2011, Francesca DeMeo served as co-founder, CIO of Cambridge Select Inc. The same year, she served as a volunteer member of the board of directors of the Governor's Academy and remained there until 2021.
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https://en.wikipedia.org/wiki/Francesca_E._DeMeo
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Color transparency is a phenomenon observed in high-energy particle physics, where hadrons (particles made of quarks such as a proton or mesons) created in a nucleus propagate through that nucleus with less interaction than expected. It suggests that hadrons are first created with a small size in the nucleus, and then grow to their nominal size. Here, color refers to the color charge, the property of quarks and gluons that determines how strongly they interact through the nuclear strong force.
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Color_transparency
https://en.wikipedia.org/wiki/Color_transparency
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Color transparency is also known as "color screening", "color coherence" or "color neutrality".
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Color_transparency
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Color transparency arises from the behavior of quarks inside hadrons. These quarks are held together by the strong interaction, mediated by gluons. At high energies, when a high-energy hadron -or more generally a color singlet object interacts with a nucleus, it can propagate in the nucleus with less scattering than expected. This reduced scattering, or transparency, is attributed to the fact soon after the hadron is created, the gluon cloud surrounding the quarks is more compact, viz the effective size of the singlet object is small, leading to reduced interaction. This effect is observed in experiments involving high-energy electron scattering off nuclei, where the transparency increases with increasing energy of the incoming particles, or more precisely with the 4-momentum transfer Q between the accelerated particle beam and target nucleus.
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Color transparency is interpreted as the creation of point-like configurations (PLC), also called small-size configurations (SSC) or ejectile, that are color singlet and of radius r ∼ ∼ ℏ ℏ / Q , where ℏ ℏ is the reduced Planck constant. The radius is small because the quarks are close to each other, making their external color fields to cancel, much like the electric field of an electric dipole vanishes at distances much larger than the dipole size. If the energy-momentum of the PLC/SSC/ejectile is high enough, it does not have time to expand to its nominal size (e.g., about 0.8 fm if the PLC/SSC becomes a proton) while propagating in the target nucleus, resulting in it going through the nucleus unimpeded.
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Color_transparency
https://en.wikipedia.org/wiki/Color_transparency
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CONSTANT
The above interpretation is in the partonic language, which uses quarks and gluons as the degrees of freedom. Due to the quark-hadron duality, or parton-hadron duality, meaning that all QCD predictions can be expressed using a hadronic basis, color transparency can also be described using hadronic degrees of freedom. In that case, the ejectile, although not a hadron (i.e., not an eigenstate of the QCD Hamiltonian despite being color singlet), can be represented as a superposition of hadrons. Such a superposition state has a smaller size than each individual hadron. As the ejectile propagates in the nucleus, all but one of the hadron states constituting the ejectile state are filtered out by the interaction of the ejectile with the nucleons in the nucleus. The remaining hadronic state corresponds to the hadron eventually produced in the reaction. The filtering out of the other states occurs after a typical formation time τ τ f . If the distance c τ τ f is larger than the nucleus size, then no filtering happens in the nucleus, the ejectile keeps its small size, and propagates largely unhindered. This is color transparency described with hadronic degrees of freedom.
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The phenomenon has been observed in several experiments, including experiment E791 at Fermilab. The experiment ran from June 1988 to January 1992 and collided high-energy (500 GeV) pions onto carbon and platinum nuclei. The experiment observed evidence of color transparency in the production of vector mesons, such as ρ ρ and ϕ ϕ mesons. Other experiments that observed evidence for color transparency include the E665 experiment, also at Fermilab, the HERMES experiment at DESY, and the E02-110 experiment at Jefferson Lab.
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The experimental signal for color transparency is the "nuclear transparency", defined as the ratio between the nuclear cross section per nucleon over that on a free nucleon. Color transparency then predicts an increase of nuclear transparency with Q .
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Color transparency is important because it provides valuable insights into the strong interaction. In fact, color transparency is a prediction of the quantum field theory of the strong force, quantum chromodynamics (QCD). Additionally, color transparency has implications for nuclear physics and the structure of atomic nuclei. By studying how particles interact with nuclei at high energies, one learns more about the distributions of quarks and gluons within nucleons and how they are affected by the surrounding nuclear environment. The noticeable modification of these distributions by the nuclear environment is known as the EMC effect and is, as of 2024, a vibrant field of research in particle and nuclear physics.
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Phys. 69, 1 (2013) [arXiv:1211.2826 [nucl-th]].]
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