Quantum Optics and Information Research Group Seminar
University of Connecticut
Delivered June 2013 by Elie Wolfe
based on http://arxiv.org/abs/1208.4119 by Rob Spekkens and Chris Wood
SMarketing, la Integración de Marketing y VentasJuan Merodio
El SMarketing es un alineamiento estratégico entre marketing y ventas con el objetivo de maximizar el impacto cuantitativo y cualitativo de las acciones hacia potenciales clientes que impactará en el crecimiento del negocio.
This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
How to Build a Module in Odoo 17 Using the Scaffold MethodCeline George
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Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Thinking of getting a dog? Be aware that breeds like Pit Bulls, Rottweilers, and German Shepherds can be loyal and dangerous. Proper training and socialization are crucial to preventing aggressive behaviors. Ensure safety by understanding their needs and always supervising interactions. Stay safe, and enjoy your furry friends!
SMarketing, la Integración de Marketing y VentasJuan Merodio
El SMarketing es un alineamiento estratégico entre marketing y ventas con el objetivo de maximizar el impacto cuantitativo y cualitativo de las acciones hacia potenciales clientes que impactará en el crecimiento del negocio.
This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
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Odoo provides an option for creating a module by using a single line command. By using this command the user can make a whole structure of a module. It is very easy for a beginner to make a module. There is no need to make each file manually. This slide will show how to create a module using the scaffold method.
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Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
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http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
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Causal Structure and Quantum Correlations - review seminar on the work of Spekkens and Wood
1. Work by Robert Spekkens and Chris Wood
arXiv:1208.4119
qplus.burgarth.de
presented to research group 6/13/2013 by Elie Wolfe
6/13/2013
arXiv:1208.4119
1
2. Algorithms exist to find all-possible causal structures for
a given probability distribution.
These algorithms are motivated by Machine Learning.
So, using formal methods, what are the causal structures
consistent with QM?
Spoiler: NONE!
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3. Cause (influence) points to it’s effect.
A STRUCTURE is looser than a MODEL.
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4. 6/13/2013
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and independant
|
|
,
,
; 0
B b
A a
A B
P A B P A
P B A P B
P A B P A P B
H A B H A H B
A
I A
B
B
; ,
; | | | , |
1
log
H | H , H H ;
x X
I A B H A H B H A B
I A B C H A C H B C H A B C
H X P x
P x
X Y X Y Y X I X Y
and conditionally independant given
| , |
| , |
, | | |
, | | |
|
; | 0
B b
A a
A B C
P A B C P A C
P B A C P B C
P A B C P A C P B C
H A B C H A C H B
B
C
A
I A B C
C
5. 1. No cycles. Influence cannot self-loop.
2. Reichenbach’s Common Cause Principle: If A and B
are not statistically independent then they must share
a common cause. In other words, A influences B, B
influences A, or C influences both A and B. In terms of
a graph: A must be connected to B by a causal path.
3. No fine tuning. If A and B are statistically
independent then they should not be causally
connected.
Additionally, every structure has “Instrumental
Inequalities” that restrict beyond just independence.
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6. If not independent
If correlated then must have common cause
(exception example – conservation of momentum)
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( ; ) 0I A B
C
A
B
A
B
B
A
OR OR
B
A
=
7. Called “Faithful” or “Stable” in the literature.
If have common cause then must be correlated
Because if B influences A then it should show up in the data.
Implausible that complex structure should be mistaken for
simple. Degrees of freedom argument!
(exception: binary one-time-pad)
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A C AC B
A B C AC ABC
AB A B
BC B C
A B
8. Such correlations can be found, but they require
interdependance of the conditional probabilities. The number
of C.P. labels is greater than the number of free variables
allowed by the C.I. data.
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A B
6 free parameters
A B C AC BC ABC
AB A B
5 free parameters
A B C AC ABC
AB A B
BC B C
+4
+1
+1 +4
+1
+2
9. 6/13/2013
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9
If the only way B experiences the influence of A is through some
intermediate variable(s) C then A and B are conditionally independent
given C.
implies
Markov condition: Causal structures imply that every variable X is
conditionally independent of its nondescendants given its parents,
,
|
A C B C
A B C
X1
X4 X3
X5
X2
Nondescendants | ParentsX X X
10. Clearly structure implies CI, but no-fine-tuning means CI
implies structure as well. If an effect has multiple influences,
then information about the effect presumably adds
nontrivially to the to the mutual information of the influences.
RCCP: If A and B are correlated then A and B should
have a common cause.
NFT1: If A and B are independent then A and B
should not be modeled with a common cause.
NFT2: If A and B are independent given C then,
treating all ancestors of C as correlated, A and B should not
have a common cause path which bypasses C.
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|S C T
11. Input: (S⊥C|T) ie. S & C must have common cause , but all causal paths
must not bypass T, including all of T’s ancestors, which we take to be all
correlated when T is given.
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13. Input:
Output:
Input: Actually strength of the QM correlations
Output: NULL SET
The difference is that CI alone is incomplete input. (A candidate structure
implies Instrumental Inequalities. The instrumental inequalities of the
candidate structure above are none other than the Bell inequalities!)
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(X ? Y );(A ? Y jX);(B ? XjY )
A B
X Y
¸
“The instrumental inequality can, in a sense, be viewed as a generalization of Bell's
inequality for cases where direct causal connection is permitted to operate between the
correlated observables, X and Y:” -J. Pearl. Causality: Models, Reasoning, and Inference. Sec. 8.4.
X
A
Y
B
14. 6/13/2013
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A B
X Y
¸
A B
X Y
¸
A B
X Y
¸
Superluminal
Causation
A B
X Y
¸
A B
X Y
¸
A B
X Y
¸¹
Lessthan
FreeWill
A B
X Y
¸
A B
X Y
¸
A B
X Y
¸¹
Retrocausation
(w/ocycles)
15. Taking all 3 lemmas together cannot reproduce Bell-
inequality violating statistics, and yet they are real…
So what premise should we modify? Major open
question in Quantum Foundations.
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1. Directed Acyclic Graphs labeled
with conditional probabilities
represent all causal models.
2. Reichenbach’s principle:
correlations must be explained by a
causal model
3. No fine-tuning of the causal model
• Can we reasonably question Reichenbach’s principle?
• Are there types of fine-tuning that aren’t so objectionable?
• Should we allow cycles in our causal models?
• Must we use conditional probabilities? (conditional density operator!)
16. The field of Causal Discovery Algorithms is hard
pressed to move beyond only conditional
independence analysis. True candidate testing,
however, requires computation of the Instrumental
Inequalities, which is NP hard, not unlike enumerating
Bell Inequalities. Quantum Foundations has developed
tools for assessing the possibility of local explanations
of correlations. The techniques of QM are presumably
useful then for developing Causal Discovery Algorithms!
This has applications to machine learning, medicine,
genetics, economics…
New! Journal of Causal Inference. (How new? Volume
1, Issue 1 was first published 6/4/2013, merely 9 days
ago!)
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