Skip to main content
Log in

Reciprocal Class of Jump Processes

  • Published:
Journal of Theoretical Probability Aims and scope Submit manuscript

Abstract

Processes having the same bridges as a given reference Markov process constitute its reciprocal class. In this paper we study the reciprocal class of compound Poisson processes whose jumps belong to a finite set \(\mathcal {A}\subset \mathbb {R}^{d}\). We propose a characterization of the reciprocal class as the unique set of probability measures on which a family of time and space transformations induces the same density, expressed in terms of the reciprocal invariants. The geometry of \(\mathcal {A}\) plays a crucial role in the design of the transformations, and we use tools from discrete geometry to obtain an optimal characterization. We deduce explicit conditions for two Markov jump processes to belong to the same class. Finally, we provide a natural interpretation of the invariants as short-time asymptotics for the probability that the reference process makes a cycle around its current state.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Bernstein, S.: Sur les liaisons entre les grandeurs aléatoires. Vehr. des intern. Mathematikerkongress Zürich I, 288–309 (1932)

    MATH  Google Scholar 

  2. Carlen, E.A., Pardoux, E.: Differential calculus and integration by parts on Poisson space. In: Albeverio, S., Blanchard, P., Testard, D. (eds.) Stochastics, Algebra and Analysis in Classical and Quantum Dynamics, volume of 59 Mathematics and Its Applications, pp. 63–73. Springer, Berlin (1990)

    Google Scholar 

  3. Carmichael, J.P., Masse, J.C., Theodorescu, R.: Processus gaussiens stationnaires réciproques sur un intervalle. C. R. Acad. Sci., Paris, Sér. I 295, 291–293 (1982)

    MathSciNet  MATH  Google Scholar 

  4. Chay, S.C.: On quasi-Markov random fields. J. Multivar. Anal. 2(1), 14–76 (1972)

    Article  MathSciNet  MATH  Google Scholar 

  5. Chen, L.H.Y.: Poisson approximation for dependent trials. Ann. Probab. 3(3), 534–545 (1975)

    Article  MathSciNet  MATH  Google Scholar 

  6. Clark, J.M.C.: A local characterization of reciprocal diffusions. Appl. Stoch. Anal. 5, 45–59 (1991)

    MathSciNet  MATH  Google Scholar 

  7. Conforti, G., Léonard, C.: Reciprocal class of random walks on graphs. Preprint, 2015. arXiv:1505.01323

  8. Conforti, G., Murr, R., Léonard, C., Rœlly, S.: Bridges of Markov counting processes. Reciprocal classes and duality formulae. Electron. Commun. Probab. 20(18), 1–12 (2015)

    MATH  Google Scholar 

  9. Conforti, G., Rœlly, S.: Bridge mixtures of random walks on an Abelian group. Bernoulli J. (2016, accepted)

  10. Cressie, N.A.C.: Statistics for Spatial Data. Wiley, New Jersey (1993)

    MATH  Google Scholar 

  11. Cruzeiro, A.B., Zambrini, J.C.: Malliavin calculus and Euclidean quantum mechanics. I. Functional calculus. J. Funct. Anal. 96(1), 62–95 (1991)

    Article  MathSciNet  MATH  Google Scholar 

  12. Dai Pra, P.: A stochastic control approach to reciprocal diffusion processes. Appl. Math. Optim. 23(1), 313–329 (1991)

    Article  MathSciNet  MATH  Google Scholar 

  13. De Loera, J.A., Hemmecke, R., Köppe, M.: Algebraic and Geometric Ideas in the Theory of Discrete Optimization. MOS-SIAM Series on Optimization. SIAM, Philadelphia (2013)

    MATH  Google Scholar 

  14. Jacod, J., Shiryaev, A.N.: Limit theorems for stochastic processes. Grundlehren der mathematischen Wissenschaften. Springer, Berlin (2003)

    Book  MATH  Google Scholar 

  15. Jamison, B.: Reciprocal processes: the stationary Gaussian case. Ann. Math. Stat. 41(5), 1624–1630 (1970)

    Article  MathSciNet  MATH  Google Scholar 

  16. Jamison, B.: Reciprocal processes. Zeitschrift für Wahrscheinlichkeitstheorie und Verwandte Gebiete 30(1), 65–86 (1974)

    Article  MathSciNet  MATH  Google Scholar 

  17. Jamison, B.: The Markov processes of Schrödinger. Zeitschrift für Wahrscheinlichkeitstheorie und Verwandte Gebiete 32(4), 323–331 (1975)

    Article  MATH  Google Scholar 

  18. Krener, A.J.: Reciprocal diffusions and stochastic differential equations of second order. Stochastics 107(4), 393–422 (1988)

    Article  MathSciNet  MATH  Google Scholar 

  19. Krener, A.J.: Reciprocal diffusions in flat space. Probab. Theory Relat. Fields 107(2), 243–281 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  20. Léonard, C., Rœlly, S., Zambrini, J.C.: Reciprocal processes. A measure-theoretical point of view. Probab. Surv. 11, 237–269 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  21. Levy, B.C.: Characterization of multivariate stationary Gaussian reciprocal diffusions. J. Multivar. Anal. 62(1), 74–99 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  22. Levy, B.C., Krener, A.J.: Dynamics and kinematics of reciprocal diffusions. J. Math. Phys. 34(5), 1846–1875 (1993)

    Article  MathSciNet  MATH  Google Scholar 

  23. Mecke, J.: Stationäre zufällige Maße auf lokalkompakten Abelschen Gruppen. Zeitschrift für Wahrscheinlichkeitstheorie und Verwandte Gebiete 9(1), 36–58 (1967)

    Article  MathSciNet  MATH  Google Scholar 

  24. Murr, R.: Reciprocal Classes of Markov Processes. An Approach with Duality Formulae. Ph.D. thesis, Universität Potsdam. http://opus.kobv.de/ubp/volltexte/2012/6301/pdf/premath26.pdf (2012)

  25. Nelson, E.: Dynamical Theories of Brownian Motion, vol. 2. Princeton University Press, Princeton (1967)

    MATH  Google Scholar 

  26. Neukirch, J.: Algebraic Number Theory. Grundlehren der mathematischen Wissenschaften: a series of comprehensive studies in mathematics. Springer, Berlin (1999)

    Book  MATH  Google Scholar 

  27. Privault, N., Zambrini, J.C.: Markovian bridges and reversible diffusion processes with jumps. Annales de l’Institut Henri Poincaré (B), Probababilités et Statistiques 40(5), 599–633 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  28. Rœlly, S.: Reciprocal processes. A stochastic analysis approach. In: Korolyuk, V., Limnios, N., Mishura, Y., Sakhno, L., Shevchenko, G. (eds.) Modern Stochastics and Applications. Optimization and its applications, vol. 90, pp. 53–67. Springer, Berlin (2014)

    Chapter  Google Scholar 

  29. Rœlly, S., Thieullen, M.: A characterization of reciprocal processes via an integration by parts formula on the path space. Probab. Theory Relat. Fields 123(1), 97–120 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  30. Rœlly, S., Thieullen, M.: Duality formula for the bridges of a brownian diffusion: application to gradient drifts. Stoch. Process. Appl. 115(10), 1677–1700 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  31. Schrödinger, E.: Über die Umkehrung der naturgesetze. Sitzungsberichte Preuss. Akad. Wiss. Berlin. Phys. Math 144, 144–153 (1931)

    MATH  Google Scholar 

  32. Slivnjak, I.M.: Some properties of stationary streams of homogeneous random events. Teor. Verojatnost. i Primenen. 7, 347–352 (1962). In Russian

    MathSciNet  Google Scholar 

  33. Stein, C.: Approximate Computation of Expectations. IMS Lecture Notes. Institute of Mathematical Statistics, Hayward (1986)

    Google Scholar 

  34. Thieullen, M.: Second order stochastic differential equations and non-Gaussian reciprocal diffusions. Probab. Theory Relat. Fields 97(1–2), 231–257 (1993)

    Article  MathSciNet  MATH  Google Scholar 

  35. Thieullen, M., Zambrini, J.C.: Symmetries in the stochastic calculus of variations. Probab. Theory Relat. Fields 107(3), 401–427 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  36. Wakolbinger, A.: A simplified variational characterization of Schrödinger processes. J. Math. Phys. 30(12), 2943–2946 (1989)

    Article  MathSciNet  MATH  Google Scholar 

  37. Zambrini, J.C.: Variational processes and stochastic versions of mechanics. J. Math. Phys. 27(9), 2307–2330 (1986)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sylvie Rœlly.

Additional information

The first author acknowledges the Berlin Mathematical School and the Research Training Group 1845 Stochastic Analysis with Applications in Biology, Finance and Physics for their financial support.

Appendix

Appendix

1.1 Proof of Step 1 in Theorem 4.2

We first observe that it is sufficient to prove that

$$\begin{aligned} \mathbb {Q}(.|\mathbf {N}_1=\mathbf {n}) << \mathbb {P}_{\nu }(.|\mathbf {N}_1=\mathbf {n}) \, \text { for all } \mathbf {n}\text { such that }\mathbb {Q}(\mathbf {N}_1=\mathbf {n})>0. \end{aligned}$$

To this aim, we use an approximation argument.

Let us fix \(\mathbf {n}\) and construct a discrete (dyadic) approximation of the jump times. For \(m \ge \max _{j=1,\ldots ,A} \log _{2} (n^j)+1:=\bar{m}\) , \(\mathcal {D}^m\) is composed by A ordered sequences of dyadic numbers, the jth sequence having length \(n^j\):

$$\begin{aligned} \mathcal {D}^{m}\!:= \!\left\{ \mathbf {k}= (k^j_i)_{j \le A, i \le n^j} : \, k^j_i \in 2^{-m} \mathbb {N}, 0 < k^{j} _{i-1} < k^{j}_{i} \le 1, \quad \forall j \le A, \quad \forall i \le n^j \right\} \end{aligned}$$

For \(\mathbf {k}\in \mathcal {D}^m\), we define the subset of trajectories whose jump times are localized around \(\mathbf {k}\):

$$\begin{aligned} O^{m}_{\mathbf {k}} = \left\{ \mathbf {N}_1= \mathbf {n}\right\} \cap \bigcap _{\mathop { i \le n^j}\limits ^{j \le A }} \left\{ 0 \le k^j_i - T^j_i < 2^{-m} \right\} \end{aligned}$$
(6.4)

Moreover, as a final preparatory step, we observe for every \( m \ge \bar{m} \), \(\mathbf {k},\mathbf {k}' \in \mathcal {D}^{m}\) one can easily construct \( u \in \mathcal {U}\) such that:

$$\begin{aligned} u(j,t) = t+k'^j_i-k^j_i , \quad \forall j \le A, i \le n^j \ \mathrm{and} \ t \ \mathrm{s.t.} \ 0 \le k^j_i - t < 2^{-m} \end{aligned}$$
(6.5)

We can observe that (6.5) ensures \(\dot{u}(j,T^j_i) =1 \) over \(O^{m}_{\mathbf {k}}\), and that \(O_{\mathbf {k}'}^m = \pi _u^{-1}(O^{m}_{\mathbf {k}})\). We choose \(F= \mathbbm {1}_{ O^{\mathbf {n}}_{\mathbf {k}'} } \mathbbm {1}_{\{\mathbf {N}_1=\mathbf {n}\}}/\mathbb {Q}(\mathbf {N}_1= \mathbf {n})\) and u as in (6.5) and apply (3.1) to obtain :

$$\begin{aligned} \begin{aligned} \mathbb {Q}\left( O^{m}_{\mathbf {k}'} \Big | \mathbf {N}_1= \mathbf {n}\right)&= \mathbb {Q}\left( \left\{ \omega : \pi _{u}(\omega ) \in O^{m}_{\mathbf {k}}\right\} | \mathbf {N}_1=\mathbf {n}\right) \\ \!&= \!\mathbb {Q}\left( \mathbbm {1}_{O^{m}_{\mathbf {k}}} \exp \left( \sum _{j=1}^{A}\int _{0}^{1} \log \varXi ^{\nu }(j,t,u(j,t)) \ \dot{u}(j,t) \mathrm{d}N_t^j \right) \Big | \mathbf {N}_1\!=\! \mathbf {n}\right) \\&\ge C \ \mathbb {Q}\left( O^{m}_{\mathbf {k}}\Big | \mathbf {N}_1= \mathbf {n}\right) , \end{aligned} \end{aligned}$$

where

$$\begin{aligned} C:= \Big ( \inf _{s,t \in [0,1], j \le A } \varXi ^{\nu } (j,s,t) \Big )^{\sum _{j} \mathbf {n}_j} >0 \end{aligned}$$
(6.6)

since \(\nu \in \mathcal {J}\). With a simple covering argument, we obtain, for all \( m \ge \bar{m}\) and \( \mathbf {k}\in \mathcal {D}^m \),

$$\begin{aligned}&\sharp \mathcal {D}^m \min \left\{ 1,\frac{1}{C} \right\} \mathbb {Q}\left( O^{m}_{\mathbf {k}} | \mathbf {N}_1=\mathbf {n}\right) \\&\quad \le \mathbb {Q}\left( O^{m}_{\mathbf {k}} | \mathbf {N}_1=\mathbf {n}\right) + \sum _{\mathop {\mathbf {k}' \ne \mathbf {k}}\limits ^{\mathbf {k}' \in \mathcal {D}^m}} \mathbb {Q}\left( O^{m}_{\mathbf {k}'} |\mathbf {\mathbf {N}_1} = \mathbf {n}\right) \le 1 . \end{aligned}$$

It can be shown with a direct computation that \(\frac{1}{|\mathcal {D}^m|} \le C' \mathbb {P}_{\nu }( O^m_{\mathbf {k}} | \mathbf {\mathbf {N}_1}=\mathbf {n})\) for some \(C'>0\) uniformly in \(m, \mathbf {k}\in \mathcal {D}^m\) (the proof is given in Lemma 6.6). Therefore there exists a constant \(C^{''}>0\) such that:

$$\begin{aligned} \mathbb {Q}\left( O^{m}_{\mathbf {k}}|\mathbf {N}_1=\mathbf {n}\right) \le C^{''} \ \mathbb {P}_{\nu }\left( O^{m}_{\mathbf {k}}|\mathbf {N}_1=\mathbf {n}\right) ,\quad \forall m \ge \bar{m} , \mathbf {k}\in \mathcal {D}^{m} . \end{aligned}$$

With a standard approximation argument, using the fact that \(\mathbb {Q}(\varOmega ) =1\), we can extend the last bound to any measurable set. This completes the proof of the absolute continuity.

We are left with the proof of the following Lemma.

Lemma 6.6

Let \(\mathcal {D}^m\) and \(\mathbb {P}_{\nu }\) as before. Then there exists a constant \(C^{'}\) such that for m large enough,

$$\begin{aligned} C^{'} \ \mathbb {P}_{\nu }\left( O^{m}_{\mathbf {k}}|\mathbf {N}_1= \mathbf {n}\right) \ge \frac{1}{\sharp \mathcal {D}^{m}} \end{aligned}$$

Proof

We want to prove that for \(\mathbf {n}\in \mathbb {N}^A \):

$$\begin{aligned} \frac{1}{\sharp \mathcal {D}^m} \le C' \mathbb {P}_{\nu }\left( O^{m}_{\mathbf {k}}| \mathbf {N}_1=\mathbf {n}\right) , \quad \forall \ m \ge \max _{j\le A} \log (n^j)+1 , \, \mathbf {k}\in \mathcal {D}^m \end{aligned}$$
(6.7)

We can first compute explicitly \(\sharp \mathcal {D}^m\) with a simple combinatorial argument: Each \(\mathbf {k}\in \mathcal {D}^m\) is constructed by choosing \(n^j\) dyadic intervals, \( j \le A\), and ordering them. Therefore

$$\begin{aligned} \sharp \mathcal {D}^m = \prod _{j=1}^{A} \left( {\begin{array}{c}2^{m}\\ n^j\end{array}}\right) . \end{aligned}$$
(6.8)

On the other hand, we observe that defining \(\tilde{\nu }(\mathrm{d}x\mathrm{d}t) =\sum _{j=1}^{A}\delta _{a^j}(\mathrm{d}x) \otimes \mathrm{d}t\), \(\mathbb {P}_{\tilde{\nu }}\) is equivalent to \(\mathbb {P}_{\nu }\), and therefore, we can prove (6.7) replacing \(\mathbb {P}_{\nu }\) with \(\mathbb {P}_{\tilde{\nu }}\). To do this, for each \(\mathbf {k}\in \mathcal {D}^m\), we define the function:

$$\begin{aligned} \delta : \{ 1,\ldots , 2^{m} \} \times \{1,\ldots ,A \} \longrightarrow \{ 0,1 \} \\ \delta ( i,j) := {\left\{ \begin{array}{ll} 1, &{} \quad \text{ if } i \in \left\{ 2^{m}\mathbf {k}^j_1,\ldots ,2^{m} \mathbf {k}^j_{n^j} \right\} \\ 0 , &{} \quad \text{ otherwise } \text{. }\end{array}\right. } \end{aligned}$$

Then, using the explicit distribution of \(\mathbb {P}_{\tilde{\nu }}\),

$$\begin{aligned}&\mathbb {P}_{\tilde{\nu }}\left( O^m_{\mathbf {k}} | \mathbf {N}_1= \mathbf {n}\right) \\&\quad = \mathbb {P}_{\tilde{\nu }} \left( \bigcap _{(i,j) \in \{1,..,2^m \} \times \{1,..,A\}} \left\{ N^j_{\frac{i}{2^m}} - N^j_{\frac{i}{2^m}} = \delta (i,j) \right\} \Big | \mathbf {N}_1=\mathbf {n}\right) \\&\quad = \exp (A)\exp (-2^{-m})^{2^{m}A} (2^{-m})^{\left( \sum _j n^j \right) }\prod _{j=1}^A n^j! = \prod _{j=1}^A 2^{-mn^j} n^j! \end{aligned}$$

It is now easy to see that there exists a constant \(C_0>0\) such that:

$$\begin{aligned} \left( {\begin{array}{c}2^m\\ n^j\end{array}}\right) \ge C_0 \frac{2^{m n^j}}{ n^j!} , \quad \forall \ j \le A , \ m \ge \max _{j=1,\ldots ,A} \log (n^j)+1, \ \mathbf {k}\in \mathcal {D}^m \end{aligned}$$

from which the conclusion follows. \(\square \)

1.2 Proof of Proposition 5.4

  1. (i)

    Let \(\mathbf {n}\in \mathbb {N}^A, \mathbf {m} \in \mathfrak {F}_{\mathbf {A},\mathbf {n}} \). Since \(\ker ^{*}_{\mathbb {Z}}(\mathbf {A})\) is a lattice basis, there exists \(\mathbf {c}_1,\ldots ,\mathbf {c}_K \subseteq (\ker ^{*}_{\mathbb {Z}}(\mathbf {A})\cup -\ker ^{*}_{\mathbb {Z}}(\mathbf {A}))^K \) such that, if we define recursively

    $$\begin{aligned} w_0 = \mathbf {n}, \quad w_k = \theta _{\mathbf {c}_k} w_{k-1} \end{aligned}$$

    then we have that \(w_K = \mathbf {m}\). Let us consider l large enough such that

    $$\begin{aligned} l \ \min _{j=1,\ldots ,A} \bar{c}^j \ge \left| \min _{\mathop {k=1,\ldots ,K}\limits ^{j=1\ldots ,A}}w^j_k\right| . \end{aligned}$$
    (6.9)

    We then consider the sequence \(w'_k\), \(k = 0,\ldots ,K+2l\) defined as follows:

    $$\begin{aligned} w'_k= {\left\{ \begin{array}{ll} \theta _{\bar{\mathbf {c}}}w'_{k-1}, \quad &{} \text{ if } \,\,1 \le k \le l\\ \theta _{\mathbf {c}_{k-l}} w'_{k-1}, \quad &{} \text{ if } \,\, l+1 \le k \le K+l \\ \theta _{-\bar{\mathbf {c}}} w'_{k-1} \quad &{} \text{ if } \,\, K+l+1 \le k \le K+2l .\end{array}\right. } \end{aligned}$$

    It is now easy to check, thanks to condition (6.9) that

    $$\begin{aligned} \ w'_k \in \mathfrak {F}_{\mathbf {A},\mathbf {n}} \quad \forall \ k \le K+2l . \end{aligned}$$

    Since all the shifts involved in the definition of \(w'_k\) are associated with vectors in \(\ker ^{*}_{\mathbb {Z}}(\mathbf {A})\cup - \ker ^{*}_{\mathbb {Z}}(\mathbf {A})\), we also have that \( w'_k \in \mathfrak {F}_{\mathbf {A},\mathbf {n}} \) and \((w'_{k-1},w'_k)\) are an edge of \(\mathcal {G}(\mathfrak {F}_{\mathbf {A},\mathbf {n}} ,\ker ^{*}_{\mathbb {Z}}(\mathbf {A})), k \le K+2l\).

    Moreover we can check that

    $$\begin{aligned} w'_{K+2l} = \mathbf {n}+ l \bar{c} + \sum _{k \le K} c_k - l \bar{c} = \mathbf {m} \end{aligned}$$

    Therefore \(\mathbf {n}\) and \(\mathbf {m}\) are connected in \(\mathcal {G}(\mathfrak {F}_{\mathbf {A},\mathbf {n}} ,\ker ^{*}_{\mathbb {Z}}(\mathbf {A}))\), and the conclusion follows since the choice of \(\mathbf {m}\) is arbitrarily in \(\mathfrak {F}_{\mathbf {A},\mathbf {n}} \) and \(\mathbf {n}\) any point in \(\mathbb {N}^A\).

  2. (ii)

    Let \(\mathbf {n}\in \mathbb {N}^A, \mathbf {m} \in \mathfrak {F}_{\mathbf {A},\mathbf {n}} \). Since \(\ker ^{*}_{\mathbb {Z}}(\mathbf {A})\) is a lattice basis, there exists \(K < \infty \) and \(\mathbf {c}_1,\ldots ,\mathbf {c}_K \subseteq (\ker ^{*}_{\mathbb {Z}}(\mathbf {A})\cup - \ker ^{*}_{\mathbb {Z}}(\mathbf {A}))^K \) such that if we define recursively :

    $$\begin{aligned} w_0 = \mathbf {n}, \quad w_k = \theta _{\mathbf {c}_k} w_{k-1} \end{aligned}$$
    (6.10)

    then we have that \(w_K = \mathbf {m}\)

Observe that w.l.o.g there exists \(K^+\) s.t. \(\mathbf {c}_k \in \ker ^{*}_{\mathbb {Z}}(\mathbf {A})\) for all \( k \le K^+ \ \) and \(\mathbf {c}_k \in \ -\ker ^{*}_{\mathbb {Z}}(\mathbf {A})\ ,k \in \{ K^+ +1,\ldots ,A\} \). Applying the hypothesis, one can check directly that \(\{ w_{k} \}_{0 \le k \le K}\) is a path which connects \(\mathbf {n}\) to \(\mathbf {m}\) in \(\mathcal {G}(\mathfrak {F}_{\mathbf {A},\mathbf {n}} ,\ker ^{*}_{\mathbb {Z}}(\mathbf {A})) \).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Conforti, G., Dai Pra, P. & Rœlly, S. Reciprocal Class of Jump Processes. J Theor Probab 30, 551–580 (2017). https://doi.org/10.1007/s10959-015-0655-3

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10959-015-0655-3

Keywords

Mathematics Subject Classification (2010)

Navigation